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The Effects of Extirpation of Frogs on the Trophic Structure in
Tropical Montane Streams in Panama
A Dissertation
Submitted to the Faculty
of
Drexel University
by
Meshagae Endrene Hunte-Brown
in partial fulfillment of the
requirements for the degree
of
Doctor of Philosophy
May 2006
©Copyright 2006 Meshagae E. Hunte-Brown
All Rights Reserved
i
Dedication
This is dedicated to my husband, Andrew and to my daughter Michal. My precious
Michal, who in an instant took me to a new dimension in love, that I did not know
existed. You have given me a new purpose, new drive and new determination, all without
an ounce of effort. Andrew, you are a blessing beyond compare. For what you have done
and what you have refrained from doing, for trudging through Panamá with me, for
grinding leaves with me, for doing all that you could with me, rather than doing away
with me, I love you and I thank you.
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Acknowledgments
I owe a great deal of thanks to many people, without whose help, this project would not
have made it to completion.
Firstly, I would like to thank my advisor, mentor and friend, Dr. Susan Kilham. Your
reputation within the scientific community speaks volumes, you are an extraordinary
scientist and facilitator, a dedicated motivator and friend. Thank you for always giving
me and ear when I needed it, for all you words of advice and encouragement and
especially for seeing the things in me that I did not see in myself. You have left a mark on
my mind and in my heart that can never be erased.
I would also like to say a Dr. Cathy Pringle, another stellar scientist, whose work I spent
much time reading while working on my Master’s research in Jamaica. Your
encouragement, guidance and advice especially when we were in the field in Panamá for
the first time and re my dissertation have proved to be invaluable. To the other members
of my committee, Dr. Hal Avery, Dr. Walter Bien, Dr. Danielle Kreeger and Dr. Jim
Spotila, I thank you all your time and assistance that was a necessary part of taking me to
the point of a completed dissertation.
This project was part a collaborative research being carried out by the TADS (Tropical
Amphibain Declines in Streams) team. Sue Kilham and Cathy Pringle are members of the
TADS team, but I also owe a great deal to the other PI’s on the TADS project, Dr. Karen
Lips and Dr. Matt Whiles for their guidance over the past few years. Special thanks
iii
Roberto Brenés and J. Checo Colon Gaud who lived in the field for the duration of
the field season of the project and who always provided expert and willing help in all
areas from sample and data collection to interpreter. Scott Connelly and Chad
Montgomery also provided much needed assistance in sample and data collection for my
research. And to all the other members of the TADS team such as Becky Bixby and Scot
Peterson, who also provided information that aided in the interpretation of my own data.
To the ever-expanding TADS team, thank you for all your work in getting the message
out to the scientific community and the world at large.
Anyone who has done research involving living creatures, let alone living creatures in
another country can relate to how difficult permitting processes can be. Thanks to the
Smithsonian Tropical Research Institute (STRI) especially Maria Leone, Orelis
Aresomena, Marcela Paz, Meylin Hernandez, David Roiz, Raineldo Urriola, Yvette
McKenzie, Anabelle Arroyo, Patrizia Pinzon for taking care of everything from
permitting to transportation and shipping of equipment and samples to accommodations.
The unit at STRI performed like a well-oiled machine and I thankfully have not been
exposed to usual red-tape of carrying out research over seas because of the efforts and
commitment to service of the afore mentioned persons. I would also be remiss if I did not
say a special thank you to Sr Jorge Herrerra whose warm smile and friendly manner
became something to look forward to with each new trip to Panamá.
Thank you to Tom Maddox and the team at the Stable Isotope and Soil Microbiology Lab
at University of Georgia, for working with me to get my samples analyzed on my
iv
schedule, which is not easy to do, since every researcher’s work is ‘priority 1’. I also
need to say thanks to Luane Steffy for teaching me the stable isotope technique, which
was obviously a very necessary part of this whole process. Anika McKessey did a very
good job of keeping me on top of administrative deadlines, and keeping me in the know
about important things, such as thesis formatting requirements, also a very necessary part
of the dissertation process. Brenda Jones-Bowden (Ms Brenda) and Christine (Kamazuki)
Kuszmaul in the Bioscience and Biotechnology office at Drexel took care of the many
administrative hiccups that can bring progress to a screeching halt, I am grateful for all
you’ve done on my behalf. My other friends in the US and Jamaica took up the slack in
everything from listening to complaining, to encouragement and proofing.
Lastly, I owe a huge debt of gratitude to my husband and the rest of my family. Truly,
this work is the result of group effort, and if it were allowed, I would have you on the
stage with me to collect the diploma. Many people say ‘they are there for you’, but my
family has been here and there, from my house to Panamá and back, from my husband
collecting samples with me in Panamá, to my grandmother, Momsie and the many other
hands in my immediate and extended family that have held my newborn so that I could
work. I absolutely, positively would not be at this point without you.
v
Table of Contents
LIST OF TABLES .......................................................................................................VIII
LIST OF FIGURES .....................................................................................................VIII
CHAPTER 1: INTRODUCTION.................................................................................... 1 LITERATURE REVIEW ..................................................................................................................................1
Introduction to Food Webs ....................................................................................................................1 The Study of Food Webs ........................................................................................................................2 Mixing Models .....................................................................................................................................10 Stoichiometry .......................................................................................................................................13 Scale.....................................................................................................................................................18 Current velocity ...................................................................................................................................23 Population dynamics............................................................................................................................24 Interaction Strength/Trophic Cascades ...............................................................................................25 Detritus ................................................................................................................................................27 Omnivory .............................................................................................................................................29 Taxonomic Resolution..........................................................................................................................31
SITE DESCRIPTION.....................................................................................................................................32 CHAPTER 2: THE EFFECTS OF FROG EXTIRPATION ON PERIPHYTON ∆15N AND ∆13C SIGNATURES IN A TROPICAL MONTANE STREAM IN PANAMÁ......................................................................................................................... 43
ABSTRACT:................................................................................................................................................43 INTRODUCTION:.........................................................................................................................................44 METHODS:.................................................................................................................................................47 RESULTS:...................................................................................................................................................49 DISCUSSION:..............................................................................................................................................51
Stable Isotope Signals between and Within Sites.................................................................................51 Tadpole density and periphyton...........................................................................................................54 Change in Isotope Signal with Time ....................................................................................................55
REFERENCES .............................................................................................................................................58 FIGURES ....................................................................................................................................................61
CHAPTER 3: THE EFFECTS OF FROG EXTIRPATION ON THE TROPHIC STRUCTURE OF TROPICAL MONTANE STREAMS IN PANAMÁ AS REVEALED BY STABLE ISOTOPES........................................................................ 64
ABSTRACT:................................................................................................................................................64 INTRODUCTION:.........................................................................................................................................65 METHODS:.................................................................................................................................................67 RESULTS:...................................................................................................................................................71 DISCUSSION:..............................................................................................................................................74
The stream food webs: A broad view...................................................................................................74 The stream food webs: A closer look ...................................................................................................80 The riparian food web: ........................................................................................................................82
REFERENCES .............................................................................................................................................86 TABLES AND FIGURES ...............................................................................................................................90
vi
CHAPTER 4: THE EFFECTIVENESS OF ISOSOURCE AS A TOOL FOR ELUCIDATING TROPHIC STRUCTURE IN TROPICAL STREAM FOOD WEBS............................................................................................................................... 96
ABSTRACT:................................................................................................................................................96 INTRODUCTION:.........................................................................................................................................97 METHODS:.................................................................................................................................................99 RESULTS AND DISCUSSION:.....................................................................................................................100 REFERENCES: ..........................................................................................................................................108 TABLES AND FIGURES .............................................................................................................................110
LIST OF REFERENCES:............................................................................................ 117
APPENDICES............................................................................................................... 127
VITA............................................................................................................................... 174
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List of Tables
Table 1.1 Substrate Composition by Site and Season in El Copé and La Fortuna ........... 40
Table 3.1 Average Physico-chemical data in streams: El Copé and Fortuna, Panamá from June 2003 to May 2005............................................................................................. 90
Table 3.2 Nutrient Concentrations in streams in El Copé and Fortuna ............................ 90
Table 4.1 Table of tadpole species with measured and adjusted stable isotope values and presence/absence of feasible solutions.................................................................... 110
Table A.1 Stable Isotope Raw Data................................................................................ 127
Table.A.2 Number of individuals collected in each taxon.............................................. 173
viii
List of Figures
Figure 1.1 Map of Panamá showing the study sites of El Copé and La Fortuna............. 32
Figure 1.2 Photographs showing rain forest in El Copé ................................................... 33
Figure 1.3 View from within rain forest in El Copé ......................................................... 33
Figure 1.4 Monthly rainfall and tadpole density in El Cope from June 2003 to May 2005................................................................................................................................... 34
Figure 1.5 Schematic of Study reach in Rio Guabal, El Copé with sampling stations indicated and photographs from each station............................................................ 35
Figure 1.6 Photographs of frogs found in El Copé: a) Atelopus zeteki b) Eleutherodactylus gaigei c) Hyla rufitela................................................................. 36
Figure 1.7 Photograph of forest in La Fortuna ................................................................. 37
Figure 1.9 Schematic of Study reach in Quebrada Chorro, La Fortuna with sampling stations indicated and photographs from each station .............................................. 39
Figure 1.10 Substrate composition by site and season in El Copé and La Fortuna in Panamá from June 2003 to May 2005 ...................................................................... 41
Figure 1.11 Photographs of filamentous algae in Rio Guabal, El Copé after the September 2004 die-off............................................................................................................... 42
Figure 2.1 δ15N and δ13C signals of the periphyton in the riffle and pool environments in El Copé and Fortuna from June 2003 to May 2005. Relative amounts of rainfall received are noted on the figure. <200mm = Low Rain, 200-400mm = Med Rain and >400mm = Hi Rain ................................................................................................... 61
Figure 2.2 Tadpole density and periphyton δ15N signal in riffle and pool environments in El Copé from June 2003 to May 2005. The threshold density of tadpoles is labeled as 10 individuals per m2 and threshold periphyton δ15N signal labeled as 4‰. ‘*’ denotes samples taken after die-offs had begun ....................................................... 62
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Figure 2.3 Scatter plots of all periphyton δ13C and δ15N signals in Fortuna and pre and post decline El Copé................................................................................................... 63
Figure 3.1 Scatter plots of all stable isotope data in Fortuna and pre and post decline El Copé from June 2003 to May 2005........................................................................... 91
Figure 3.2 – Scatter plots of δ13C and δ15N values for leaf pack biofilm in Fortuna and post decline El Copé. ................................................................................................ 92
Figure 3.3 δ15N and δ13C of major groups in Fortuna and pre and post decline El Copé. Chart a: Leaf pack N = 45, Periphyton N = 37, FBOM N = 15, Seston N = 6, Invertebrates, N = 391, Crabs N = 13, Tadpole N = 98, Fish N = 182, Snake N = 174, Frog N = 204. Chart b: Leaf pack N = 12, Periphyton N = 12, FBOM N = 3, Seston N = 2, Invertebrates, N = 38, Crabs N = 3, Fish N = 11, Shrimp N = 3 Spiders N = 7, Leaf Pack Biofilm N = 12. Chart c: Leaf pack N = 13, Periphyton N = 12, FBOM N = 5, Seston N = 3, Invertebrates, N = 51, Crabs N = 7, Fish N = 22, Leaf Pack Biofilm, N = 12. Chart d: Leaf pack N = 60, Periphyton N = 33, FBOM N = 20, Seston N = 8, Invertebrates N = 388, Crabs N = 65, Tadpole N = 2, Fish N = 10............................................................................................................................... 93
Figure 3.4 δ15N signal of selected resources in El Copé and Fortuna. The resources chosen were present at both sites on all sampling occasions. El Copé: Periphyton N = 58, Leaf Pack Biofilm N = 24, Hydropsychidae N = 53, Perlidae N = 20, Fish N = 204, Crab N = 23. Fortuna: Periphyton N = 33, Leaf Pack Biofilm N = 16, Hydropsychidae N = 78, Perlidae N = 57, Fish N = 10, Crab N = 65.................... 94
Figure 3.5 Scatter and summary stable isotope plots for riparian food webs (Adult frogs, snakes and lizards) Bufo haematiticus N = 17, Eleutherodactylus talamancae N = 17, Eleutherodactylus puntariolus N = 3, Centrolenella prosoblepon N = 3, Hyla colymbiphyllum N = 33, Colostethus flotator N = 3, Colostethus inguinalis N = 14, Norops lionotus N = 3, Rhadicula vermiformis N = 3, Leptodeira septentrionalis N = 12, Imantodes cenchoa N = 15, Sibon annulatus N = 30, Oxybelis brevrirostris N = 99, Dispas N = 15. ................................................................................................ 95
Figure 4.1a- Feasible resource utilization of Colostethus inguinalis and the resources leaf pack, leaf pack biofilm, periphyton and FBOM: Fractionation = 1.8‰................. 111
Figure 4.1b- Feasible resource utilization of Colostethus inguinalis and the resources leaf pack, leaf pack biofilm, periphyton and FBOM: Fractionation = 2.0‰................ 112
x
Figure 4.2a- Feasible resource utilization of Rana warszewitschii and the resources leaf pack, leaf pack biofilm, periphyton and FBOM: Fractionation = 1.8‰.................. 113
Figure 4.2b- Feasible resource utilization of Rana warszewitschii and the resources leaf pack, leaf pack biofilm, periphyton and FBOM: Fractionation = 2.0‰................. 114
Figure 4.2c- Feasible resource utilization of Rana warszewitschii and the resources leaf pack, leaf pack biofilm, periphyton and FBOM: Fractionation = 2.8‰................. 115
Figure 4.3 - Mixing polygons for the tadpoles (Colostethus inguinalis and Rana warszewitschii) and resources (leaf packs, leaf pack biofilm, periphyton and FBOM). The δ13C signatures of the tadpoles have been corrected by a factor of 1‰ and the δ15N signals have been corrected by 1.8‰, 2.0‰, 2.8‰ and 3.4‰.......... 116
xi
Abstract
The Effects of Extirpation of Frogs on the Trophic Structure in Tropical Montane Streams in Panama
Meshagae Endrene Hunte-Brown Susan S. Kilham, Ph.D.
Amphibian populations are in global decline. Species that have stream dwelling tadpoles
and inhabit upper montane environments are disproportionately affected. Tadpoles are
keystone herbivores in the streams so their removal is expected to have a wide range of
ecosystem effects. This inspired the collaborative TADS (Tropical Amphibian Declines
in Streams) project which investigated the spectrum of ecosystem effects of the frog
extirpation. The study was conducted in the uplands of Panamá at two sites that were
differentially affected by the die offs. This arm of the TADS project used stable isotopes
to investigate the changes in trophic structure in the streams. During the field season, a
massive die off event occurred at the healthy site. This provided a unique opportunity to
study the changes in trophic structure as they were transpiring. Several interesting trends
were elucidated. The ultimate source of nitrogen and carbon are different at both sites.
The food web was truncated in the absence of the tadpoles, resources that were thought to
be important in the system proved not to be and fractionation of 15N and 13C varied
between the sites. In keeping with the trends in the current literature, the IsoSource
mixing model software was used to evaluate the trophic linkages. IsoSource which is
used to determine relative contributions of multiple sources to a consumer, proved to be
ineffective for pioneer studies such as this one. It is clear from the data however, that the
trophic structure in both locations is significantly different and that the tadpoles provided
an important subsidy to the food web. Some compartments of the food web in El Copé
xii
have already begun to approach prevailing conditions in Fortuna, but further studies
are required to determine the length of time required for the entire system to equilibrate
and approximate to the current conditions in Fortuna.
1
CHAPTER 1: Introduction
Literature Review
Introduction to Food Webs There are a variety of advantages associated with studying food webs (Tavares-Cromar
and Williams 1996). These advantages range from an increased understanding of
community structure, dynamics and ecology, to better understanding of solutions to
problems such as predicting biological concentrations of contaminants. Advantages also
include tools to develop better strategies for integrated pest management, disease-causing
vector control, wastewater treatment and wildlife conservation.
The concept of a food web has been a central theme in ecology ever since its classical
development (Lindeman 1942) and it has provided an important conceptual link between
population and community ecology (Woodward and Hildrew 2002). A food web may be
defined as a network of consumer-resource interactions among a group of organisms,
populations or aggregate trophic units (Winemiller and Polis 1996). They are the
ecologically flexible scaffolding around which communities are assembled and structured
(Paine 1996) because they represent the pathways along which energy and materials flow
within and between ecosystems. They differ in structure and function between stream
types, even though they will have some common elements (Hershey and Peterson 1996).
These differences in the structure and function of the food webs are determined by many
factors which include riparian characteristics (Cummins et al. 1989), biogeography,
geomorphology, gradient and the characteristics of the substratum (Gregory et al. 1991),
2
and interspecific interactions (Power 1992). The food webs observed in streams reflect
these factors, which themselves constrain the species that comprise the food web. The
energy base of food webs, light, nutrients and organic matter inputs, on the other hand are
determined by canopy, riparian zone and watershed characteristics (Hershey and Peterson
1996).
The Study of Food Webs Classical food web studies rely on species lists and the presence/absence of feeding links,
while searching for across-system patterns in trophic structure (Vander Zanden and
Rasmussen 1999). When studying food webs, the initial objectives are to identify the
principal sources of organic matter in the system (Hershey and Peterson 1996), assign
consumers to trophic levels within the web and attempt to identify the major food sources
for each of these consumers. In most streams there are 3 or 4 trophic levels in the food
web (Mantel et al. 2004) and the species comprising these trophic levels are restricted by
the factors that determine the structure and function of the food web. Food webs in small
streams are very different from those in large rivers, they have high connectivity and a
high proportion of generalists (Mantel et al. 2004). Two of the factors that greatly
influence organic matter sources for the food web are canopy cover of the riparian
vegetation and the physical gradient. These factors are often interrelated, and are
confounded by the effects of substrate.
Approaches to studying food webs may be qualitative or quantitative. Qualitative
approaches elucidate linkages and connections without ascribing strengths to the
3
interactions. Quantitative studies require years of work (even for one stream) and involve
many different types of approaches.
Food webs are often quite complex. This complexity is very likely the reason that
scientists attempting to unravel the intricacy of trophic relationships have used so many
approaches. General approaches used to study food web dynamics are gut analyses,
carbon or energy budgets and stable isotope tracer studies. The question of interest, as
well as the resources available, will dictate which approach or combination of approaches
should be used (Hershey and Peterson 1996).
Energetic approaches such as that described in the River Continuum Concept (RCC)
(Vannote et al. 1980) predict the occurrence of certain functional groups in different
sections of rivers, according to the available energy resources. The RCC suggests that the
relative importance of allochthonous as opposed to autochthonous inputs changes from
headwater to mouth as the physical structure of the river changes, so in the forested
headwaters allochthonous inputs are thought to be most important while the reverse is
purported to be true in the more open low altitude regions of the river. However,
attempting to tease apart information where there are high degrees of omnivory, which is
very likely to occur in stream systems, becomes very difficult. Further, the RCC does not
acknowledge the environmental patchiness that is characteristic of streams. It is also
noteworthy that if the study stream does not approach the physical nature of the stream
used to develop the RCC, the predictions of the RCC may not be met (Hunte 1999).
4
Gut analyses are often conducted to determine major food sources for consumers. There
are some inherent shortcomings with this method however. For most stream consumers,
gut content analysis will underestimate both the biomass and the variety of food ingested,
because some items may be unrecognizable, or it may be that only soft tissues may have
been ingested (Hershey and Peterson 1996). As such, bias can be introduced from
variations in gut clearance time of different prey items or greater apparent incidence of
prey with sclerotized parts (Mantel et al. 2004). This is further compounded because soft-
bodied animals, such as flatworms and molluscs are particularly hard to detect in gut
content analyses (Closs and Lake 1994), and this method will also not provide any
information on the diet of fluid feeders. The diets may also change dramatically with the
seasonal availability of food, ontogeny, or even diel period, so long-term comprehensive
studies would be required. The techniques used in gut content analysis may themselves
cause loss of information. Bacteria may be extremely important both numerically and
nutritionally, but will not be evident in the gut unless properly stained and preserved.
Life history stage can potentially affect the amount of food in the gut (Tavares-Cromar
and Williams 1996). Newly hatched individuals, as well as older individuals preparing
for pupation, for example, are often encountered with empty guts. Therefore gut analyses
provide a ‘snapshot’ of the consumer’s diet at the time of sampling (Mantel et al. 2004,
Pinnegar and Polunin 1999), but will not provide estimates of food web structures unless
the diets of the prey and the prey’s prey etc. are also investigated (Vander Zanden and
Rasmussen 1999, Yoshii 1999). While the method can be helpful in determining resource
use by organisms, it is a reflection only of the food ingested at the time of sampling
5
(Kang et al. 1999) rather than assimilation (Yoshii 1999, Evans-White et al. 2001) and
can therefore be misleading (Kling et al. 1992). With all of this said, gut analyses have a
place in the construction of food web diagrams, and they can be used to generate
hypotheses which can subsequently be tested (Hershey and Peterson 1996).
Stable isotope analyses (SIA) are an additional independent way of tracking the transfer
of organic carbon and nitrogen from plant and detrital sources to primary and secondary
consumers (Hershey and Peterson 1996, Herman et al. 2000). This method can provide
both ‘source-to-sink’ and process information (Peterson and Fry 1987, Riera et al. 1999).
Stable isotope analysis provides a powerful tool for unraveling the complex structure of
food webs (Gannes et al. 1997, Stapp et al. 1999, Yoshii 1999, Yoshii et al. 1999, Post et
al. 2000, O’Reilly et al. 2002) and is based on the fact that organisms retain the stable
isotope signals of the resources they assimilate (Machás and Santos 1999). With the
advancement of technology and our understanding of trophic relationships, the trends in
the literature have moved towards this method of following transfers of organic carbon
and nitrogen through the community (Vander Zanden and Rasmussen 1999). Of all the
methods currently available, it seems to be able to give the most definitive answers, with
the least amount of speculation.
In many ecosystems the animals have different 13C : 12C and 15N :14N ratios and therefore
the diets of the consumers can be inferred from the isotope ratios in the consumers’
tissues (Hershey and Peterson 1996). Animal tissues become only slightly enriched in 13C
in relation to their food (∆~1‰ δ13C) per trophic step (Finlay et al. 1999, Yoshii 1999,
6
Kilham and Pringle 2000) and certain aspects of an animal’s diet can be reconstructed
from the isotopic ratios of animal carbon if the potential food sources of the organism had
differing 13C:12C ratios (DeNiro and Epstein 1981). Therefore, stable isotope data for
carbon is typically used to provide information regarding the base of the food web (Boon
and Bunn 1994, Hecky and Hesslein 1995, Vander Zanden and Rasmussen 1999, Yoshii
1999, O’Reilly et al. 2002).
Minawaga and Wada (1984) report that the nitrogen content in field animals was strongly
affected by the isotopic content of their food source. Organisms became more
significantly enriched in 15N in relation to their food (∆ ~3.4‰ δ 15N, compared to ∆
~1‰ δ13C per trophic step) (DeNiro and Epstein 1981, Cabana and Rasmusssen 1996,
Vander Zanden et al. 1999, Vander Zanden and Rasmussen 1999, Yoshii 1999, Post et al.
2000, Vander Zanden and Rasmussen 2001). This observation is widespread among most
animals collected from many kinds of ecosystems (Minawaga and Wada 1984). The
trophic enrichment in 15N of the consumer with respect to its food is predictable enough
to permit its use as an indicator of realized trophic level (Minawaga and Wada 1984,
Kling et al.1992, Cabana and Rasmussen 1996, Hershey and Peterson 1996, Peterson
1999, Stapp et al. 1999). Cabana and Rasmussen (1994) report that the variable trophic
positions of species in food-chains can be better predicted from δ15N values than
taxonomy. Given that there is little trophic shift in 13C and a measurable and predictable
shift in 15N, the combination of C and N isotopes are often used to aid in the study of
organic matter transfer and trophic structure of ecosystems (DeNiro and Epstein 1981,
7
Kling et al. 1992, Hershey and Peterson et al. 1996, Kang et al. 1999) as this reduces the
possible ambiguities in source and trophic level assignments (Peterson 1999).
Ecosystems often contain natural isotopic distributions that allow for easy differentiation
of organic matter sources for the various consumers (Hershey and Peterson 1996,
Sanzone et al. 2003). For example, with respect to the base of the food web, plants with
different modes of photosynthesis, phytoplankton and benthic algae have distinct δ 13C
signatures, so it is possible to tell what the food source of the primary consumer was
(Gannes et al. 1997, Vander Zanden et al. 1999, Vander Zanden and Rasmussen 1999,
Kilham and Pringle 2000).
The fact that the base of the food web is made up of different types of organisms begs the
question of whether stable isotope analyses are even necessary since the morphology of
the consumer should indicate what its food resource is i.e. functional or feeding group
concept. The problem with using feeding apparatus morphology as an indication of
resource of choice is that the morphology does not always agree with the diet. Organisms
have been known to occupy different functional groups in different latitudes, or stream
reaches. The Ephemeropteran family Caenidae, for example, is described as a filterer
(Hyslop pers comm.) and as a scraper (Palmer et al. 1993a). Marchant et al. (1985) found
that shredders and predators did not vary between sites as predicted by the RCC. This
could very likely have been because there was diet switching in different regions of the
stream, which would invalidate some of the functional group categorizations.
Furthermore, diatom detritus and riparian vegetation detritus are very likely mixed
8
together on the substratum (Hershey and Peterson 1996), but these types have different
signals and organisms may very likely be selecting the nature of the detritus they utilize,
for reasons varying from the stoichiometry of the food resource to the organism’s ability
to digest the material. One of the chief strengths of stable isotope analysis is that it
measures assimilation that has been integrated over the time scale of tissue turnover
(Kling et al. 1992, Hecky and Hesslein 1995, Vander Zanden and Rasmussen 1999,
Yoshii 1999, Yoshii et al. 1999, March and Pringle 2003).
There is also data which demonstrates that there is habitat-specific variation in baseline δ
13C and δ 15N, consequently, isotopic studies should include the widest possible range of
baseline organisms (Vander Zanden and Rasmussen 1999). Pringle and Hamazaki (1998)
showed that it was important to distinguish between algal resources when investigating
trophic effects, so as not to overlook the differential effects of macro-consumers on
different algal groups. Therefore, a requirement for sound stable isotope tracer work is
that the δ-values of the end members must be well known (Peterson 1999, Vander
Zanden and Rasmussen 2001). If the δ-values of the food resources are well known, and
animals utilize more than one resource, it is possible to determine the relative importance
of each resource.
As previously alluded to, interpreting δ 15N signatures of higher consumers, relative to an
appropriate base line, can provide time-integrated depictions of trophic structure (Cabana
and Rasmussen 1996, Yam and Dudgeon 2005). An isotopic ratio of an organism is
usually understood to represent its diet, but the ratio is also time specific, representing an
9
average ratio related to tissue turnover rate and the life of the organism (O’Reilly et al.
2002). Stable isotopes also provide a continuous measure of trophic position, not just
discrete trophic levels, which integrate the assimilation of mass from all the trophic
pathways (Post et al. 2000). This method of analysis can efficiently determine the
strength of the trophic interactions (Kling et al. 1992) and thus trace the flow of energy
through the system.
The stable isotope approach is also useful to determine food chain length (Post et al.
2000). Chain length is described by Schoener (1989) as the number of links between the
basal (i.e. having no prey) and top (i.e. having no predators) trophic species. Post et al.
(2000) used stable isotope techniques to investigate maximum trophic level which is
conceptually similar to food chain length, and reported that this was an important
characteristic of ecological communities because it influenced community structure,
ecosystem function and contaminant concentration of top predators in the system.
Trophic position is an attribute of a single species within a web, while maximum trophic
position is a characteristic of the foodweb. Changes in trophic position of a single top
predator must be caused by lengthening of the food web between the base and the top,
while adding a new top predator increases the maximum trophic level (Post et al. 2000).
One of the important advantages of stable isotopes is that the technique can provide a
continuous measure of trophic position which integrates the energy flow through
different trophic pathways leading to an organism (Post 2002).
10
The stable isotope approach is useful at all scales (Peterson 1999), but the approach has a
weakness when end members are not separated enough for good resolution in mixing
calculations, and when 3 or more end members are present, so multiple tracers may be
needed, and spatial and temporal sampling may also be needed to elucidate the trends.
Additional insights from gut content analysis may be important to support findings
(Peterson 1999) as diet analysis can provide a taxonomic resolution which is unattainable
by stable isotope analysis, especially in complex food webs (Hecky and Hesslein 1995).
These techniques are more effectively used in combinations. They are not sufficiently
powerful by themselves, they provide quick reliable information on trophic relationships
in benthic communities (Peterson 1999), and they are best used in a hypothesis testing
mode.
Mixing Models The trophic base of many aquatic systems is very diverse, with the end result being
multiple sources of organic matter entering the food web (Benstead et al. 2006, Hamilton
et al. 2004). As mentioned earlier, gut content analyses are not as useful in providing
definitive information about the trophic base of food webs. While stable isotope analysis
can be more useful toward this end, SIA has an inherent shortcoming when there are
multiple potential sources. This sparked the development of mixing models, computer
software which calculate the relative contributions of multiple sources to a consumer.
However, mixing models are not without limitations; they are often limited in providing
unique solutions by the number of isotopes analyzed, since data from n isotopes are
needed to find a solution for n + 1 resources.
11
Typically, two stable isotopes are used in food web studies. Therefore, researchers have
often limited studies to three potential resources by including only those sources that are
assumed to be important or have been shown to be important through other types of
analyses (Benstead et al, 2006, Phillips and Gregg 2003). These deliberate inclusions
and omissions can potentially lead to misinterpretations of the food web.
In an effort to overcome some of these problems with mixing models, Phillips and Gregg
(2003) developed IsoSource, a mixing model software, which is designed for situations in
which n isotopes are being analyzed but there are > n + 1 potential sources. The software
is available for public use at http://www.epa.gov/wed/pages/models.htm (Phillips and
Gregg 2003). IsoSource uses the stable isotope data to calculate the possible range of
source contributions, first by calculating all possible combinations of source utilization
that sum to 100% by user specified increments. In the next step, isotope values of each
mixture of resources are described, using linear mixing model equations that preserve
mass balance within a user specified tolerance.
The IsoSource method is a very timely addition to the growing range of statistical
techniques used for analyzing isotope data (Benstead et al. 2006), since it can provide
narrow ranges of source contributions. The IsoSource approach is also very useful for
showing that a source is not important in a particular food web. The major disadvantage
with the software is that it requires the user to already have detailed knowledge about the
food web. Therefore, IsoSource is not as useful when doing initial food web
12
investigations, where the researcher is attempting to uncover the path of energy and
material transfer in the food web. IsoSource also requires the user to be certain of what
the fractionation factor of the isotope in question is in the food web. A resource polygon
is drawn using the isotope values of the resources. The isotope signatures are corrected
by the fractionation factor; the fractionation factor is subtracted from the value of the
consumer, or alternatively added to the resources while the consumer value remains
unchanged. After the correction, the isotope value of the consumer must fall within the
boundaries of the resource polygon in order for IsoSource to compute a solution (Phillips
and Gregg 2003).
The requirement of knowing the fractionation factor can be problematic since in the
tropics, a body of data is emerging that shows that the fractionation factor for 15N is very
likely between 1.8 and 2‰ rather than 3 - 4‰ as had been previously reported in the
literature. It is also becoming apparent that different organisms can have different
fractionation factors (Jardine et al. 2005), different functional groups can have different
fractionation factors, for example predators fractionate more 15N than non-predators
(Vanderklift and Ponsard 2003). Different body tissues can also have varying
fractionating factors as well; small animals are usually ground whole, while a portion of
muscle for example may be taken from larger animals, which further compounds the
problem. Consumer diet can have a large effect on fractionation factor (Adams and
Sterner 2000, Vanderklift and Ponsard 2003) and there can be large differences in 15N
enrichment according to the main biochemical pathwayway of nitrogen excretion
(McCutchan et al. 2003, Vanderklift and Ponsard 2003). Jardine et al. (2005) showed that
13
even taxa with similar diets do not necessarily have similar δ15N signals. Variation in
fractionation values in resource signatures and among individuals complicates
interpretation of trophic interactions (Mantel et al. 2004) and obviously using the wrong
fractionation factor would completely change the computed result and therefore the
interpretation of the food web. ‘The weakest link in the application of mixing models to a
dietary reconstruction relates to the estimation of appropriate fractionation values’
(Phillips and Koch 2002). So once again, while IsoSource is a timely and very useful
development, when there is much prior knowledge about the system being studied, it is
not as useful for pioneer trophic studies.
Stoichiometry The term ecological stoichiometry can be used to describe the balance of energy and
materials or the balance of multiple chemical substances in ecological interactions and
processes (Sterner and Elser 2002). It deals with how differences or similarities between
the elemental composition of resources and requirements of the consumer influence
ecosystem processes. The theory was initially developed for pelagic communities;
relationships between nutrient stoichiometry of primary producers and consumers, as
well as nutrient fluxes and organism growth were studied (Liess and Hillebrand 2005).
The concept of ecological stoichiometry provides a mechanistic framework for how
animal species vary in mediating nutrient recycling, which is a vital ecosystem process
(Vanni et al. 2002) and a stoichiometric framework has long been used to study
interactions among trophic levels in different ecosystems (Bowman et al. 2005). Within
this framework the food items that are consumed are in essence, parcels of elements that
14
may or may not be in balance with a consumer’s elemental requirements (Cross et al.
2003). Therefore, the two primary questions of ecological stoichiometry are: a) what
causes the observed variation in carbon to nutrient ratios among organisms and b) what
are the consequences of mismatches between the requirements of organisms and nutrient
content of their food source (Frost et al. 2005). Severe consumer-resource imbalances
may strongly affect the structure of food webs (Cross et al. 2005) and constrain or alter
key ecosystem processes.
Common to all organisms is the challenge of acquiring sufficient quantities of energy and
elements for growth, reproduction and maintenance (Frost et al. 2005b). Fundamental to
the concept of ecological stoichiometry is coming to terms with the effects of insufficient
supplies of certain elements on physiological processes of consumers. Redfield’s (1958)
classic work on the relatively constant molar ratio of carbon, nitrogen and phosphorus
(106C:16N:1P) is really the base of ecological stoichiometry and has since been widely
used as the point of reference for assessing nutrient limitation of primary producers. The
C:N:P ratio of organic matter at the base of food webs likely plays a major role in food
web dynamics in the benthos (Bowman et al. 2005) and animals can also play important
roles in nutrient dynamics in aquatic ecosystems (Sterner and Elser 2002).
At the base of the food web, periphyton N:P content has been shown to be positively
correlated with water N:P in streams (Stelzer and Lamberti 2001) and since the nutrient
state can be very variable in open systems such as streams, benthic invertebrates that
consume periphyton must cope with a wide range of food quality that may influence
15
stoichiometric relationships (Liess and Hillebrand 2005). It is important to make the
statement at this point that the resource referred to as ‘periphyton’ may not consist solely
of algae. Moulton et al. (2004) described periphyton as a ‘complex association of
microalgae and heterotrophic organisms’ which is intimately associated with the
extracellular organic matter derived from the organisms of the periphyton themselves, as
well as sedimentation and the surrounding water. Hamilton et al. (2001) showed that
algal cells can in fact be a minor component of the organic matter associated with
surfaces in shaded streams and Frost et al. (2005) found algal cells to be a minor
component of organic matter collected from a variety of substrata in aquatic
environments. At any rate, many benthic consumers not only rely on periphyton as a food
source, but on allochthonous input as well (Cross et al. 2005). In forested streams the
main form of allochthonous inputs are in the form of leaf litter (Wetzel 2001) and the C:
nutrient ratio of leaf litter is usually high compared to that of periphyton (Cross et al.
2003). Fine particulate organic matter (FPOM) usually has higher nutrient content and
therefore lower C:N than coarse particulate organic matter (CPOM) (Cross et al. 2005)
(such as leaf litter) and appears to decline with decreasing particle size.
Considering higher trophic levels in the food web, invertebrates generally, are richer in N
than periphyton i.e. the C:N ratio of periphyton is higher than the C:N ratio of
invertebrates (Vanni et al. 2002, Elser et al. 2005). Invertebrates are also richer in P than
periphyton i.e. the C:P ratio of periphyton is higher than the C:P ratio of invertebrates
(Vanni et al. 2002). Further, when comparing the invertebrates by functional groups,
predators have been found to contain higher levels of N and P than the shredders,
16
collectors and scrapers which themselves do not differ much from each other (Cross et al.
2003, Evans-White and Lamberti 2005). Body stoichiometry can also differ among
vertebrate taxa, but vertebrates generally contain much more P in the form of bone tissue
than invertebrates. Stoichiometric theory however, implies that different food types do
not have inherent qualities. The premise is that food quality is in fact relative based on
the nutritional requirements of the consumer (Cross et al. 2003). Therefore, focus should
be placed on the relative imbalances between the C:N:P of the consumers and their food,
instead of focusing only on the nutrient content of the food.
Central to the theory of ecological stoichiometry is the concept that individual organisms
maintain elemental homeostasis within a small range (Sterner and Elser 2002), because
their nutritional demands do not vary much (Cross et al. 2005). Benthic invertebrates in
general seem to be reasonably homeostatic (Cross et al. 2003, Bowman et al. 2005,
Evans-White and Lamberti 2005). Their nutrient stoichiometry is usually less variable
than that of the basal resource they consume (Sterner and Elser 2002, Liess and
Hillebrand 2005) whether periphyton or leaf litter (Cross et al. 2005). In general, both
producers and consumers show some degree of discrimination when acquiring nutrients
in order to obtain the mixture of elements needed for growth and maintenance (Frost et
al. 2005b) and to achieve homeostasis. However, the reason consumers are better at
maintaining homeostasis is likley because elemental uptake by aquatic producers is
controlled in part by supply and demand, i.e. growth rate and nutrient availability (Frost
et al. 2005b). Homeostasis like any other biological rule however, has exceptions. There
are examples where the C:P and C:N of stream insects have been somewhat plastic
17
(Cross et al. 2003) and where up to four-fold differences in C:P and N:P ratios were
found in certain taxa when other known causes of variation were controlled.
Homeostasis refers primarily to the maintenance of nutrient stoichiometry of individual
organisms, however, families or species within classes or orders of invertebrates can
differ significantly in their C:N:P stoichiometry. Liess and Hillebrand (2005) and Vanni
et al. (2002) found that family identity more so than species identity was critical in
explaining variations in nutrient content. Several important factors are known to
contribute to this variation in consumer nutrient ratios (Cross et al. 2003). These factors
include differences in ontogeny or life history strategy as well as relative allocation of
structural molecules.
The nutrient content of organisms can vary among size classes (Vanni et al. 2002). Since
smaller species tend to have higher growth rates, C:P and N:P tend to be lower in these
species because there tends to be larger amounts of P in ribosomal RNA in fast growing
species (Cottingham 2002, Liess and Hillebrand 2005) and therefore the lower C:P and
N:P of small bodied species is a consequence of the negative allometric scaling of growth
rate with body size (Sterner and Elser 2002). As previously mentioned, differences in
body structure can also affect stoichiometry. Species with heavy or extensive
exoskeletons contain relatively more C and N than soft-bodied species, because structural
molecules like chitin contain primarily C, small amounts of N and no P (Elser et al.
1996). Liess and Hillebrand (2005) found that Coleopterans had higher C:P and N:P than
all other arthropods in their study. This is the case especially if the beetles/ beetle larvae
18
are small bodied, because there is a much larger exoskeleton to body tissue ratio. Other
studies have also shown similar trends with the C:P ratio of certain taxa of aquatic insects
such as Coleopterans and Trichopterans being high relative to the other taxa in the studies
(Cross et al. 2003, Evans-White and Lamberti 2005).
The differential stoichiometry of consumers has important consequences for ecosystem
processes (Cottingham 2002), for example, differences in consumer N:P relative to
resource N:P, combined with homeostasis and the laws of mass balance, dictate that
excess nutrients be recycled into the environment. Generally, elemental constraints on
organisms can alter dynamics of inter-specific interactions in food webs (Demott and
Gulati 1999) and ecological stoichiometry provides a useful perspective to examine food
web processes and ecosystem function, because it links energy, elements, organisms and
ecological processes in ecosystems.
Scale The resources for stream organisms originate from a variety of sources of varying
importance depending on space and time (Peterson 1999), and this variety of resources
makes energy relationships in food webs difficult to understand. Stream food webs are
produced by forces acting on them at a range of spatiotemporal scales (Woodward and
Hildrew 2002). The present understanding of food web relationships is limited by a
rudimentary appreciation of spatial and temporal scales of food webs (Power and Dietrich
2002). Ecologists have increasingly stressed the importance of scale (Woodward and
Hildrew 2002) because there have been justified concerns that communities and
19
populations are studied at scales that are most often smaller than required for adequate
understanding of the system (Boon and Bunn 1994, Tavares-Cromar and Williams 1996,
Malmqvist 2002, Woodward and Hildrew 2002). Scale involves at least three dimensions,
space, time and level of biological organization (Cottingham 2002). The task of defining
appropriate spatial and temporal scales for food web studies is especially important since
the scales used will influence the structure of the resultant web, but there are also
considerable difficulties (Closs and Lake 1994, Cottingham 2002).
Spatial Scale
It is generally quite difficult to define the limits of natural ecological communities, and
therefore, in practice this is often a very subjective exercise and food web descriptions
are usually defined by the habitat being studied (Closs and Lake 1994). Plants and
animals are often grouped into communities based on their patterns of occurrence over
broad scales of spatial heterogeneity, and even then, there is always influence and
interactions with adjacent and even distant communities. Stream and river systems are
generally highly subsidized because their downhill position relative to their watershed
aids the movement of materials towards them (Vanni et al. 2005). Pringle (1997) has
reiterated that there is a need for expansion of stream connectivity beyond the traditional
paradigms that focus on downstream effects of upstream processes. Downstream changes
can also have profound effects at the population, community, ecosystem and landscape
levels in upstream reaches of streams. Stream reaches that are upstream of degraded areas
are particularly vulnerable to the exotic species that are often common in degraded areas.
The downstream reach therefore can act as a source of exotic species.
20
Allochthonous inputs of resources, organisms, nutrients or detritus across landscapes can
have strong effects on recipient food webs (Hamilton et al. 2004, Carpenter et al. 2005,
Paetzold and Tockner 2005, Vanni et al. 2005). Processes operating at the landscape
scale, like dispersal of adult insects across catchments, can influence food web structure
at smaller scales and inputs of detritus or organisms may have complex effects depending
on the trophic position at which the subsidies enter the food web (Vanni et al. 2005).
Terrestrial arthropods that fall from the riparian zone into the water provide a potentially
important energy subsidy into aquatic food webs (Woodward and Hildrew 2002).
Therefore, forest and stream communities are interdependent through the exchange of
organic materials across their common boundary (Kato and Wada 2004). Even the most
circumscribed habitats, such as water-filled tree hollows, possess trophic links with the
surrounding environment (Closs and Lake 1994). Vagile consumers like tadpoles and fish
often ingest algae in one location and deposit feces in another location (Peterson and
Boulton 1999). This kind of activity also serves to make the ‘would-be’ boundary of a
community indistinguishable. Therefore, no community food web can be considered to
be a discrete unit. The smaller the scale at which the measurements are made, the fewer
the number of species that will be found in a functional group, and the more apparent
their functional characteristics become. That being said, the contribution of species to
fluxes is progressively masked as measurements are made over increasingly large areas,
containing more species (Anderson 2000).
Temporal Scales
Temporal variation is an important aspect of food web studies that has largely been
ignored (Tavares-Cromar and Williams 1996). Temporal resolution of different trophic
21
levels is also very important (O’Reilly et al. 2002) and small organisms tend to show
greater temporal variability in δ15N (Cabana and Rasmussen 1996). Often species and
reactions recorded over periods of time of up to a year may be lumped together and this
may obscure significant temporal variations in structure (Closs and Lake 1994). This can
be a serious flaw in studies of food webs from very variable habitats. Ecological
communities rarely occur in stable environments, and they rarely ever experience
equilibrium population dynamics (Winemiller and Polis 1996). Few predators seem to
consume prey in constant ratios for their entire life cycles. Aquatic organisms especially
show much size dependent predation, and diet shifts often occur in response to seasonal
availability of prey species. One way to look at food webs is to only represent the
interactions that are occurring at the point of sampling. However, because of the
dynamism of trophic relationships in streams, a food web complied in this way may not
be an accurate portrayal of the community one week later (Closs and Lake 1994).
Mobile predators can also introduce error in the interpretation of food webs. When the
system involves a key mobile predator, the abundance of the predator at one location can
change quickly, resulting in its omission from the species list. This causes food webs to
appear to be shorter than they truly are. If sampling continues over longer periods of
time, the resulting food webs usually contain more species and have more interactions
(Closs and Lake 1994). As is expected, some ecological systems may be more affected by
temporal processes than others, and therefore, food webs from such ecosystems will be
quite variable. Systems that have shorter generation times, absent members for parts of
the year and diet switching, will have more variation than those systems with longer
22
generation times, less diet switching and the same members present at all times (Tavares-
Cromar and Williams 1996).
The large spatial and temporal variations in isotopic signatures of primary producers can
confound attempts to establish the chief dietary sources of consumers (Boon and Bunn
1994). It is therefore important to quantify these variations before conclusions can be
drawn regarding the relative importance of allochthonous versus autochthonous sources
of energy. Streams with intermittent flow are ideal environments in which to study spatial
and temporal variation in food web structure (Closs and Lake 1994). The amplitude of
physico-chemical parameters, like dissolved oxygen, depth and current velocity in an
intermittent stream is very often larger than that of a permanent stream of comparable
size. The variability of the streams permits examination of seasonal variation on aspects
of food web structure, like predator-prey ratios and food chain length (Closs and Lake
1994). Finlay et al. (1999) found that invertebrate predators in pool and riffle habitats
largely depend on locally available prey.
The physical heterogeneity of streams has important implications for the distribution of
invertebrates. Although the difference in currents and substratum support different
assemblages, the interaction between species with similar habitat requirements is scale
dependent. A negative correlation between potential competitors can therefore only be
revealed at fine scales (Malmqvist 2002). The heterogeneity of the habitat affects
predation rates in the stream because in heterogeneous areas, there are more prey refuges
(Pringle 1996, Malmqvist 2002). Scale will also vary with the taxonomy of the organisms
23
being examined (Woodward and Hildrew 2002). Rotifer populations will grow and shrink
over much shorter time and smaller areas than fish populations for example. The spatial
sources of energy and nutrients determine the type and strength of interactions that
community members have with each other. These interactions are also affected by how
resident or transient the community members are (Power and Dietrich 2002).
Current velocity Finlay et al. (1999) did some interesting work on the effects of current velocity on carbon
isotope ratios. Because of the difficulty involved in obtaining ‘clean’ samples of epilithic
algae, they used herbivores in the investigation. In productive rivers, the researchers
found that there was no significant difference between δ13C values of the herbivores.
Secondly, in unproductive rivers, there was a continuous depletion in δ13C with
increasing current velocity, that is, maximum carbon isotope fractionation by algae
occurred where the CO2 supply rate (i.e. current velocity) was highest. It is apparent
therefore, that CO2 availability in relation to primary production determines the effect of
current velocity on algal carbon isotope ratios. The effects of current velocity on δ13C
may be explained by the fact that in situations of high current velocity, when CO2 supply
rates are higher, the algae discriminate against the heavier 13CO2.
The effect that flow has on the δ13C is very important since variability in consumer δ13C
that is erroneously ascribed to a reliance on terrestrial carbon rather than flow effects on
δ13C, will result in an underestimation of algal carbon contributions to food webs (Finlay
et al. 1999). One of the fundamental principles of stream ecology is that upstream,
24
middle and lower reaches are trophically connected by the transport of organic matter and
nutrients (Vannote et al. 1980). Since δ13C is shown to vary naturally with current
velocity (Finlay et al. 1999), this can be used as a tool to delineate the spatial scales of
the transport processes and also to examine the role of predator/prey mobility in the
trophic interactions of neighboring river habitats.
Population dynamics
Population dynamics is regarded as one of the most important processes responsible for
structure of communities and food webs (Bengtsson and Martinez 1996). Trophic
structure, evolutionary changes, energetics and nutrients as well as other biotic and
abiotic factors may also affect food web structure and function. There is increasing
awareness of the importance of dispersal, patchiness and spatial heterogeneity
(Malmqvist 2002) as they relate to food web analyses (Holt 1996). Most field based food
web studies are done at small scales due to logistic constraints. At this scale, behavioral
interactions, mobility and patchiness in resource availability become the important
factors that affect predator impacts and local food web structure (Woodward and Hildrew
2002). The significance of temporal variation and the role of life history on communities
are also coming to the forefront of research. The temporal and spatial scales are being
highlighted because they are often correlated; the shifting of perspective in one
dimension therefore requires adjustment in the other (Woodward and Hildrew 2002).
25
Interaction Strength/Trophic Cascades
Food webs are often quite complex, and the relative strength and importance of the
interactions between the species in these webs is highly variable and has been the source
of much debate (Power and Dietrich 2002). Energy generally flows from the more basal
resources up to consumers. Top-down interactions, on the other hand, link consumers to
the resource populations they regulate or limit and has been considered to be one of the
most important mechanisms that balances natural populations (Konishi et al. 2001).
Berlow (1999) reports that the loss or removal of individual species can cause dramatic
changes in communities regardless of the strength of the interaction. A weak interaction
is defined by Berlow (1999) as one which, when removed, fails to cause statistically
significant changes in abundance of certain species. These so-called weak interactions,
though not directly affecting species abundances, often have important stabilizing or
noise-dampening roles. It is also important to distinguish between those interactions that
are strong but variable and when averaged appear to be weak, and those interactions that
are consistently weak (Berlow 1999). Research management should focus not only on
species that have strong impacts i.e. keystone and functionally dominant species, but also
investigate the conditions under which weak interactions magnify, as opposed to dampen
variations in the natural communities (Berlow 1999) and in so doing, broaden the
understanding of the effects of species loss on community organization.
The total effect of deleting a species includes density and per capita effects. The effect of
a rare species on the dynamics of the food web can be qualitatively different from the
same species when it is abundant. Predators may reduce the numbers of their prey in such
26
ways as, constraining the prey’s feeding space or time, preventing the colonization of
habitats, or causing the prey to emigrate (Power et al. 1985). The effect that predators
have on their prey depends on the biological attributes of both predator and prey, as well
as the setting of their interaction (Power 1992), because predators that are functionally
important in one habitat may not be in another. As prey refuges increase, the efficiency
with which predators decrease the prey population decreases. The net significance of
predators is weakest in continuous habitats that have many refuges, and strongest in
isolated habitats that have fewer refugia (Power 1992).
Changes in the densities of certain species have strong effects on their ecological
communities (Power et al. 1992). Strong effects are caused by species which directly
alter ecosystem phenomena (example of N-fixing by cyanobacteria). At top trophic
levels, keystone predators alter communities by exerting disproportionately strong effects
on competitively dominant consumers, so species that would otherwise be out-competed
are benefited (Power et al. 1992). Trophic cascades occur when the removal of an
important consumer at trophic level n releases the populations from predation pressure at
the n-1 level and the species at n-2 trophic level are exposed to increased predation
pressure, i.e., when top-predators regulate prey populations, leading to extraordinary
changes in abundance and biomass of the lower trophic levels (Konishi et al.2001, Ruetz
et al. 2002). The top-down effects of predators however varies among prey species
because of differential consumer vulnerability to predation (Power et al. 1992, Konishi et
al.2001).
27
In theory, food webs that have weak interactions, should show very little if any
relationship between environmental predictability and the structure of the food web
(Closs and Lake 1994). Pringle and Hamazaki (1998) postulate that trophic cascades are
rare in tropical streams that are characterized by large omnivores. Woodward and
Hildrew (2002) report that high linkage density and/or species richness enhances
stability, and more stable systems should be less prone to trophic cascades and switching
between alternative stable states. Therefore, linear webs with more discrete trophic levels
are more prone to cascades and species extinctions, than broader, shorter, more
interconnected generalist webs (Woodward and Hildrew 2002). By the same token,
generalist predators cause less disruption than specialist predators, as long as they exhibit
prey switching at low prey densities. For the most part, trophic generalism and omnivory
have the potential to weaken the strength of cascades.
Detritus It is well known that dead organic matter may be ingested by aquatic invertebrates
(Minshall 1967) and allochthonous detritus is of particular importance as it generally
forms the major source of energy inputs (Webster et al. 1999, Graca et al. 2000, Murphy
and Giller 2000) in upland streams. Detritus is one of the links between the terrestrial and
aquatic environment and is defined by Minshall (1967) as any material of organic origin
which is permanently incapable of reproduction. This includes partially decomposed or
finely divided plant material as well as dead animal matter. Wetzel (2001) reports that
much of the detritus in lakes and streams originates from terrestrial, wetland and littoral-
zone plants and defines detritus as ‘organic carbon lost by non-predatory means from any
28
trophic level (including egestion, excretion, secretion and so forth), or inputs from
sources external to the ecosystem that enter and cycle in the system.’ Detritus-based food
webs may be described as donor-controlled since the consumers do not regulate the
supply of energy to the system (Ruetz et al. 2002) even though the consumers are able to
regulate the assimilation rate of the detritus into the system.
Detritus typically forms a key basal resource in freshwater food webs (Closs and Lake
1994), especially those in small shaded streams, where various forms of detritus are the
principal food source for most of the primary consumers. Theoretically, a large supply of
detritus in a food web should increase community resistance as well as resilience to
disturbance (Tavares-Cromar and Williams 1996). Utilization of an ever-present resource
such as detritus is exceptionally advantageous in variable and unstable stream habitats
(Closs and Lake 1994). Minshall (1967) reported that on a quantitative basis,
allochthonous leaf detritus was by far the most important food resource in a stream. This
may be because the C:P ratio in the detritus is such that the organisms have to consume
large amounts in order to meet their phosphorus and/or nitrogen requirements.
The need for chemical tracers of organic matter and trophic relationships is greatest in
ecosystems that are dominated by detritus because the origins of detritus usually cannot
be visually determined (Peterson and Fry 1987). It was mentioned earlier that the widest
possible range of baseline organisms should be included in stable isotope studies. This
wide baseline must also be extended to include detritus, since it is such an important part
of the trophic system in aquatic communities (Minshall 1967). Detritus has been known
29
to exceed the amount of organic carbon present as living material in bacteria, plankton,
flora and fauna (Wetzel 2001).
Omnivory Omnivory plays a potentially important role in the structuring of stream communities
(Pringle and Hamazaki 1998, Parkyn et al. 2001) especially in the tropics (Graca et al.
2000). It is an important attribute of food webs which can have important consequences
for energetics, top-down feed-back and community stability (Cabana and Rasmussen
1994). If omnivory is defined as feeding on more than one trophic level (Tavares-Cromar
and Williams 1996), then omnivores are able to affect communities in different ways than
a keystone predator for example that feeds on one level (Pringle and Hamazaki 1998).
Ontogenetic shifts will further complicate the role of the omnivore because resource use
of the population is going to be dependent on age (Parkyn et al. 2001). In some cases
omnivores utilize resources from different trophic levels, but only assimilate from one.
Omnivores such as the crayfish for example, consume detritus, but it is not incorporated
into body muscle; so the animal functions as an omnivore, but energetically acts as a
predator (Parkyn et al. 2001). Thorp and Delong (1998) also showed through stable
isotope data that hydropsychid caddis flies feed from a specific portion of the seston but
do not assimilate everything.
In the tropics, trophic relationships are obscured by high degrees of omnivory (Kilham
and Pringle 2000) and stable isotopes can be very helpful in determining the degree of
omnivory. Critical to the development of a predictive framework of tropical streams is
30
establishing the significance of omnivory, because tropical streams typically have an
abundance of omnivorous macroconsumers (Pringle and Hamazaki 1998) and omnivory
is argued to increase with food web size (Woodward and Hildrew 2002). Pringle and
Hamazaki (1998) found that omnivores have strong direct effects on smaller primary
consumers as well as on basal resources. Small fish and crayfish, considered large
omnivores, tend to shorten the food web in streams where larger aquatic predators like
catfish are absent (Evans White et al. 2001) because they are less vulnerable to the
smaller predators than herbivores or detritivores. Life history omnivory, which is the
feeding of different life stages at different trophic levels, necessitates the treatment of the
various life stages as separate entities (Tavares-Cromar and Williams 1996). This
occurrence affects the links in the food web as the relative strength of links between
certain species changes over the ontogeny of the individuals in the species.
The methods used to identify trophic links highly influence the outcome of the study. The
use of several approaches, e.g. gut analyses, feeding trials and stable isotopes increases
the probability of recording interactions. It is usually not feasible to use multiple methods
of analysis. The most useful method today seems to be stable isotope analysis, which has
been reported as being a good tool to determine the degree of omnivory and Cabana and
Rasmussen (1994) found that the patterns of δ15N provided an efficient method for
estimating omnivory. In order to arrive at an estimate, a comparison is made between the
δ15N increment between two adjacent trophic levels in the field and the increment of
3.4‰ expected from laboratory studies involving pure diets. However, while stable
isotopes can give information on the amount of omnivory that takes place in an
31
ecosystem, the method is unable to give precise information about the components of the
omnivorous diet. This is the point at which gut analysis, while having some
disadvantages of its own, funding and time permitting, could be used to supplement the
data. For reasons already discussed, it would be necessary to include a wide range of base
line organisms as well as detritus for this stage of the analysis.
Taxonomic Resolution Taxonomic resolution is also important. Differing degrees of taxonomic resolution at
different trophic levels within a web will affect the observed food-chain length (Closs
and Lake 1994). Chain lengths are often observed to be shorter if lower trophic levels are
pooled into large taxonomic groups such as detritivore, insect or herbivore. Organisms
should be identified, as much as possible, to the level of species, to prevent loss of
information as diets can vary greatly between species of the same genus. The spatial
heterogeneity of the habitat could be an important consideration and it might also be
prudent to look at the sub-webs in different regions of the stream (headwaters, middle
and lower reaches) as the base of the food web changes from primarily allochthonous to
autochthonous along the length of the river.
32
Site Description
Figure 1.1 Map of Panamá showing the study sites of El Copé and La Fortuna
The study was carried out in Panamá at two sites, La Fortuna, which experienced frog
extirpations in 1997 and El Copé, which had a healthy frog population at the start of the
current study. There was one study stream at each site: Quebrada Chorro in La Fortuna
and Rio Guabal in El Copé.
EL COPE
Parque Nacional G. D. Omar Torríjos H, El Copé, Coclé, Panamá
The park is on the eastern region of Cordillera Central (8o 40´ 04.0˝ N, 80o 35´ 35.6˝ W)
and is approximately 700m above sea level (Figure 1.1). There are 2 major drainages, Río
Guabal on the Atlantic slope, and the Río Colorado on the Pacific slope. There is a
surrounding rain forest that represents a transitional climate between the Atlantic and
Pacific slopes.
33
Figure 1.2 Photographs showing rain forest in El Copé
The Forest
The forest canopy has tree fall gaps where light is able to penetrate, but for the most part
is uniformly dense with about 70% cover. Though there may be significant primary
production in the streams, and the main energy source most likely is allochthonous inputs
from the riparian zone.
Figure 1.3 View from within rain forest in El Copé
Rainfall
As in many areas in the tropics, there is a wet and dry season. The wet season lasts from
early May to October or November, with the dry season lasting from January to April.
a b
a b
34
The area typically receives ~2,500 mm of rainfall per year (Dietrich et al. 1996), but
received 3,500 – 4,000mm per annum over the duration of the study (Figure 1.4). The
daily temperature during the early to mid wet season (May to August) averages of ~21°C
(range from 17-27° C).
0100
200300
400500
600700
800
Jun-
03
Jul-0
3Au
g-03
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ct-0
3
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-03
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04M
ar-0
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ay-0
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-04
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b-05
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-05
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-05
Date
Rai
nfal
l (m
m)
0
5
10
15
20
25
30
35
Tadp
ole
Dens
ity
(#/s
q m
)
RainfallTad Density
Figure 1.4 Monthly rainfall and tadpole density in El Cope from June 2003 to May 2005
The Stream – Rio Guabal
Río Guabal is a high gradient stream with approximately 74% canopy cover (Figure
1.5). There are distinct pool, run, riffle sequences, and occasional waterfalls and
plunge pools.
35
Figure 1.5 Schematic of Study reach in Rio Guabal, El Copé with sampling stations indicated and photographs from each station
The amphibian fauna of El Copé is diverse. There are 74 species known from the site,
with at least 22 having stream dwelling larvae, and at least 40 occupying riparian
habitats. The tadpoles were normally abundant throughout the year (Figure 1.4).
100m
100m
40m
60m
0m
0m
20m
80m
1m 5m
Stream flow
36
Tadpoles were the only vertebrate grazers in the headwaters of the Río Guabal and
may have been in competition with baetids and chironomids for resources.
Figure 1.6 Photographs of frogs found in El Copé: a) Atelopus zeteki b) Eleutherodactylus gaigei c) Hyla rufitela
The fish Brachyrhaphis roswithae, one large Macrobrachium shrimp, and one crab
(Pseudothelphusa tistani) were the macro consumers present in these streams.
Approximately 26 families of aquatic insects representing all functional feeding
groups have been identified from streams in the park.
FORTUNA
Reserva Forestal Fortuna, Chiriquí, Panamá
The Fortuna site is located in the highlands of Chiriquí province in western Panamá
(8˚ 42´ N, 82˚ 14´W) (Figure 1.1). Fortuna is ~200 km west of El Copé and is at an
elevation of 1,000 - 1,400 m. The over 19,000 hectares of forest is located primarily
above the Edwin Fabrega Dam on the upper Chiriquí River.
a b c
37
The Forest
Like El Copé, the canopy is uniformly dense (> 70%) over lower order streams and
primary production appears to be relatively low, with litter fall from riparian
vegetation again seeming to be the primary energy source
Figure 1.7 Photograph of forest in La Fortuna Rainfall
The mean annual air temperature is ~18°C and the mean annual rainfall is ~4,000 mm
(Lips 1999) (Figure 1.4). The habitats include montane rainforest at high elevations,
lower montane rainforest and eventually lowland rainforest at <750 m.
0
100
200
300
400
500
600
700
800
Jun-
03
Jul-0
3Au
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m)
0
5
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35Ta
dpol
e De
nsity
(#
/sq
m)
RainfallTad Density
Figure 1.8 Monthly Rainfall and tadpole density in La Fortuna from June 2003 to May 2005
38
The Stream - Quebrada Chorro
Some of the streams in the area are high-gradient and have distinct pool, run, riffle
sequences, with waterfalls and plunge pools, granitic outcrops and frequent large
boulders, while others have a moderate gradient and substrate consisting primarily of
pebbles, gravel, sand, and silt in depositional areas (Figure 1.9). Quebrada Chorro is
intermediate in physical characteristics between these two stream types.
39
Figure 1.9 Schematic of Study reach in Quebrada Chorro, La Fortuna with sampling stations indicated and photographs from each station
60m
island
100m
100m
80m
40m
0m
20m
0m5m
1m
Stream flow
60m
40
The amphibian population in Fortuna was extirpated in 1997 and the fauna in the
Quebrada Chorro is quite different from that in Rio Guabal. Brachyrhaphis roswithae
is seldom in Quebrada Chorro site and similarly, no shrimp have been sighted in this
stream. In contrast to El Cope however, crabs are often observed and in most cases
are larger than they are in El Cope.
Substrate Composition
The substrate in Rio Guabal and Quebrada Chorro consists primarily of pebbles and
gravel with frequent large cobbles and boulders, and with sand in depositional areas
(Courtesy of J. Checo Colon Gaud) (Table 1.1 and Figure 1.10,).
Table 1.1 Substrate Composition by Site and Season in El Copé and La Fortuna
Site Avg. Depth (m) %Cobble %Pebble %Gravel %Sand %Silt
Total El Cope 0.12 24.44 25.34 19.77 9.74 20.49 Fortuna 0.15 22.77 22.23 16.34 29.55 8.75 Dry Season El Cope 0.13 22.32 24.82 23.39 5.18 24.11 Fortuna 0.15 19.8 21.63 21.22 27.76 9.39 Wet Season El Cope 0.12 25.97 25.71 17.14 13.05 17.86 Fortuna 0.15 25.08 22.7 12.54 30.95 8.25
41
Substrate Composition by Site and Season
0%
20%
40%
60%
80%
100%
El Cope- all
El Cope- dry
El Cope- wet
Fortuna- all
Fortuna- dry
Fortuna- wet
Silt
Sand
Gravel
Pebble
Cobble
Figure 1.10 Substrate composition by site and season in El Copé and La Fortuna in Panamá from June 2003 to May 2005
Over the course of the field study, there was a massive die-off of stream dwelling
anurans in El Cope and in Rio Guabal. The die-offs began in September to October
2004 at the beginning of the rainy season, when the tadpole density would normally
be undergoing its cyclical decline in streams because of adult emergence, but the
numbers did not recover as there was no new recruitment. Subsequent to the die-offs,
there were blooms of filamentous algae in the streams.
42
Figure 1.11 Photographs of filamentous algae in Rio Guabal, El Copé after the September 2004 die-off
(Courtesy of Roberto Brenes)
Even after the algal mats (Figure 1.11) were no longer obvious, the surface of the
stones were noticeably more slippery in Rio Guabal than they had been on prior
sampling trips and more slippery than in Fortuna. There also appeared to be
noticeably less organic matter in the pools and backwaters of Rio Guabal than there
had been on previous sampling occasions.
a
c
b
d
43
CHAPTER 2: The Effects of Frog Extirpation on Periphyton δ15N and δ13C Signatures in a Tropical Montane Stream in Panamá.
Abstract: Amphibian populations in upland regions have been on the decline globally and stream
dwelling anurans in particular have been severely affected. Tadpoles are functionally
dominant herbivores in the streams, therefore, their extirpation is expected to cause
significant changes in ecosystem structure and function. This study is part of the larger
collaborative TADS (Tropical Amphibian Declines in Streams) Project, and is concerned
mainly with assessing the impact of extirpation on the stable isotope signatures of
autochthonous basal resources, specifically periphyton. The study sites are located in the
uplands of Panama in two locations, which are 200 km apart: La Fortuna (severe
declines) and El Copé (unaffected by declines at beginning of study). El Copé in fact had
massive declines over the course of the study, which presented a unique opportunity to
study a system during an extirpation event. The data reveal interesting trends supporting
the hypothesis that the source of nitrogen is atmospheric in Fortuna, but is recycled in El
Copé. No significant differences were found between stable isotope signatures in riffles
and pools at either location, however the stable isotope signals of carbon were
significantly lower at El Copé than at Fortuna while the stable isotope signatures of
nitrogen were significantly higher in El Copé than Fortuna. There is a positive correlation
between tadpole density and the δ15N signal of the periphyton, supporting the hypothesis
that recycled N from tadpoles is an important component of N budget. The range in δ13C
signals is wider in Fortuna than in El Copé, while the range in δ15N signals is wider in El
Copé than in Fortuna. The δ15N signal of the periphyton in El Copé has become depleted
44
in 15N since the local decline but at the completion of the study there was no apparent
change in the δ13C signal in El Copé.
Introduction: Amphibian populations have been on the decline over the past several years, and over the
last 20 years, 13 Latin American countries have reported massive declines or even
extirpations primarily in upland regions (Lips et al. 2003). The widespread declines in
amphibian populations are of particular concern because amphibians are indicator species
and are sensitive to a variety of environmental contaminations (Kiesecker and Blaustein
1997, Lips 1999). Species associated with aquatic habitats appear to be more affected and
most of the declines have occurred at elevations greater than 500m in Central America
(Young et al. 2001). Tadpoles are functionally dominant herbivores in these systems
(Dickman 1968), and therefore, their extirpation is expected to cause significant increases
in periphyton biomass, reduced biomass-specific primary production, reduced quantity
and quality of fine particulate organic matter along with other effects on ecosystem
structure and function. This study is part of the much larger collaborative TADS
(Tropical Amphibian Declines in Streams) study that looks at a range of effects caused by
the loss of the frogs, including changes in food web structure, community structure and
production budgets among other ecosystem characteristics.
Historically, the energy source for lotic systems has generally been thought to be
allochthonous for high gradient headwater streams (Vannote et al. 1980) such as the ones
in which most of the amphibian declines have occurred. However, in streams worldwide,
45
it would be difficult to find an object that is not at least partly covered by periphyton
(Dickman 1968). Significant autotrophic production can occur in streams and rivers
(Minshall 1978, March and Pringle 2003, Hamilton et al. 2004), since in fast-moving
water the periphyton community can attain large biomass (Hansson 1992). Periphyton is
a major food resource for benthic invertebrates (Lamberti et al. 1989), most likely
because of its higher nutritional quality compared to detritus (Yam and Dudgeon 2005).
Periphyton is important for some vertebrates and anuran herbivory is known to change
algal biomass and community structure in permanent lotic systems (Dickman 1968,
Peterson and Boulton 1999, Ranvestel et al. 2004). Given the emerging awareness of the
importance of periphyton as an energy source, understanding the various ways that this
base resource is affected by the extirpations is very important.
Stable isotopes of carbon and nitrogen have been widely used in quantitatively assessing
food web structure (Peterson and Fry 1987, OReilly et al.2002, Woodward and Hildrew
2002) as ecosystems often contain natural isotopic distributions that allow for easy
differentiation of organic matter sources for the various consumers (Hershey and
Peterson 1996, Sanzone et al. 2003). Measuring the ratios of stable isotopes is an
independent way of tracking the transfer of organic carbon and nitrogen from plant and
detrital sources to primary and secondary consumers (Hershey and Peterson 1996,
Herman et al. 2000). With the advancement of technology, the trends in the literature
have moved towards this method of following transfers of these resources through the
community (Vander Zanden and Rasmussen 1999). Stable isotope analyses can provide
both ‘source-to-sink’ and process information (Peterson and Fry 1987, Riera et al. 1999).
46
The method is based on the fact that organisms retain the stable isotope signals of the
resources they assimilate (Mahcás and Santos 1999).
Using stable isotopes as a tool can reveal information about the ultimate source of
nitrogen and carbon in the systems. The δ15N signatures of primary producers are known
to vary widely among and within systems, as well as over time (Cabana and Rasmussen
1996). Comparatively higher δ15N signals would suggest that the ultimate source of
nitrogen in the system was recycled, while δ15N signals closer to zero suggests an
atmospheric source of nitrogen, since the ratio of 15N : 14N in each sample is compared to
the 15N : 14N ratio naturally occurring in air.
Algal δ13C can be very strongly affected by several factors (Finlay 2004) and the effect of
abiotic factors like water velocity are important, because the periphytic algae is at the
base of the food web (Trudeau and Rasmussen 2003) and abiotic factors can therefore
affect the stable isotope signatures of consumers in the food web. Primary producers will
tend to discriminate against the uptake of heavier isotopes, therefore, supply rate (i.e.
flow rate) can affect the δ13C signature of periphyton (Finlay 2004). Similarly, organisms
will discriminate against heavier isotopes during metabolic activity (McCutchan et al.
2003). There is selective excretion and respiration of the lighter 12C compounds during
food assimilation and heavier isotopes are hoarded in the body tissues. In the case of
heterotrophic respiration for example, the lighter 12C isotope being released as CO2, can
affect the form of CO2 that is available to primary producers. Finlay (2004) found this to
be the case in a study of 19 rivers in Mendocino County, California. Rounick and James
47
(1984) found that the source of carbon can have significant influences on the δ13C
signature of the biota in stream habitats. The emphasis of this paper is to investigate the
differences in the stable isotope signal of periphyton in two streams that were
differentially affected by the frog extirpations, but were otherwise similar.
Methods: Site Description: The study was conducted at two sites in Panamá, Central America; one
site, La Fortuna reported frog extirpations in 1997, while the second site, El Copé had a
healthy anuran population at the beginning of the study. La Fortuna is located in western
Panamá in the highlands of Chiriquí province (8˚ 42´ N, 82˚ 14´W) (Figure 1.1). The
forest has a uniformly dense canopy and is located primarily above the Edwin Fabrega
Dam on the upper Chiriquí River. The study stream in Fortuna, Quebrada Chorro has a
moderate gradient with distinct pool, run, riffle sequences, with waterfalls and plunge
pools, frequent large boulders and granitic outcrops, as well as substrates consisting
primarily of pebbles, gravel, sand, and silt in depositional areas. A 100m reach was
selected in each location as the study area. Since the current project is part of the larger
TADS study, the study reaches chosen overlapped with the study reaches of the other
projects, to ensure continuity of the dataset.
El Copé is located 200km east of La Fortuna in Parque Nacional G. D. Omar Torríjos H,
El Copé, Coclé (Figure 1.1). The study stream in El Copé was Río Guabal, which had
similar physical characteristics to Que. Chorro in La Fortuna. The amphibian fauna of El
Copé was diverse with 74 species known from the site, at least 22 of which had stream
48
dwelling larvae, and 40 occupied riparian habitats. The amphibians were abundant
throughout the year, and tadpoles were the only vertebrate grazers in the headwaters of
the Río Guabal. The wet season lasts from mid May to November and both locations
received 3,500 - 4,500 mm of rain per annum over the duration of the study (Figure 1.8).
During the wet season in September 2004, when the instream tadpoles would normally
have begun a cyclical decline because of adult emergence, there were massive die-offs of
the stream-dwelling frogs. Consequently, the stream tadpole population was unable to
recover because there was no new recruitment.
Sample and Data Collection: Samples and physico-chemical data were collected from
June 2003 to May 2005. Water temperature, pH, dissolved oxygen and conductivity were
measured using Quanta hydrolab and water velocity was measured using a Global Water
Flow Probe. Rainfall and air temperature were recorded daily at each site, using a rain
gauge and maximum-minimum thermometer and tadpole densities were determined by
daily instream counts. The instream substrate composition and discharge were also
determined.
Periphyton samples were collected using a modified loeb sampler (Loeb 1981). Five
collections were taken every 20m along the 100m study reach from riffle areas and then
combined to make an individual sample. This process was also repeated in pool areas The
composite samples were then filtered onto glass fiber filters and frozen. The frozen filters
were transported to Drexel University, Philadelphia, Pennsylvania to be prepared for
stable isotope analysis. Punches of 0.9cm diameter were take from the filters and dried in
49
a drying oven at 65-70°C for 24hrs. After drying, 2 punches were loaded into 5 x 9 tin
capsules (Costech Analytical Technologies Inc) and placed in 96-well plates. Replicate
samples were included for every fifth sample. The samples were sent to the Stable
Isotope and Soil Biology Lab at the Institute of Ecology, University of Georgia, Athens,
Georgia where the samples were analyzed for stable isotope content using Carlo Erba NA
1500 CHN analyzer coupled to a Finnigan Delta C mass spectrometer. Poplar and bovine
standards were inserted after 12 samples. Isotope ratios are expressed as δ13C ‰ or δ15N
‰ according to the equation:
δ13C ‰ or δ15N ‰ = [(Rsample/Rstandard) – 1] x 1000 δ‰
where Rsample is the 13C:12C or 15N:14N ratio of the sample and Rstandard is the 13C:12C or
15N:14N ratio of the standard (PeeDee belemnite carbonate for δ13C and atmospheric N for
δ15N).
Results: Before the die-off event in El Copé, the tadpole density varied from 2 individuals per m2
to 29 individuals per m2, with the greatest density occurring in the driest months, while
the tadpole density in Fortuna was zero (Figures 1.4 and 1.8). One of the physical
characteristics of the sites that was measured was the substrate composition. This was
different at both sites, specifically with respect to the smaller size fractions. Rio Guabal,
El Copé had more silt in comparison with Quebrada Chorro, Fortuna, while Fortuna had
more sand (Figure 1.10).
A threshold δ15N value of 4‰ was chosen as the ‘high’ mark for δ15N. The threshold was
set at 4‰ because the standard for δ15N is atmospheric nitrogen which has a δ15N value
50
of 0‰, and the fractionation factor of organisms in the tropics is thought to be 1.8 – 2 ‰
(Kilham and Pringle 2000), therefore a value of 4‰ would represent one food web step
higher than expected. A tadpole density of 10 individuals/m2 was chosen as the threshold
density.
One-way ANOVA was used to compare periphyton δ15N and δ13C in riffles and pools
between El Copé and La Fortuna, as well as within both sites. The δ15N values were
significantly higher (p <0.01) in El Copé than La Fortuna for both riffles and pools. The
δ13C values in El Copé were significantly lower than in Fortuna (p < 0.0001 in riffles and
p < 0.001 in pools). No significant differences in periphyton δ13C and δ15N signals were
found between the riffles and pools within the sites at either Fortuna or El Copé (Figure
2.1, N = 6).
Regression analyses were carried out comparing tadpole density to periphyton δ15N and
rainfall to periphyton δ15N in El Copé. No statistically significant relationship was found
between rainfall and periphyton δ15N or between tadpole density and periphyton δ15N in
either riffles or pools at the p < 0.05 significance level. While there was no direct linear
relationship, from Figure 2.2 it can be seen that almost every sample occasion, when the
tadpole density was high (above 10 individuals / m2), the periphyton δ15N is also high
(above 4‰) in both riffles and pools.
Scatter plots were drawn for all periphyton data from El Copé according to sample date,
resulting in one pre-decline and two post-decline plots to be compared with one
51
composite plot for Fortuna (Figure 2.3). Since no significant difference was found
between the riffle and pool δ15N or δ13C within El Copé and Fortuna, no distinction was
made between riffle and pool data on the scatter plots. Comparing the δ13C values
between the plots, it is evident that the δ13C values in El Copé are more negative than in
Fortuna and that there was a much wider spread in the δ13C in Fortuna than in El Copé.
The plots also show a gradual decrease in δ15N signal of the periphyton at El Copé, with
the δ15N signals in the final scatter plot for El Copé May 2005 approaching the δ15N
signals in Fortuna.
Discussion:
Stable Isotope Signals between and Within Sites
A number of studies have shown differences in δ13C signals of periphyton related to CO2
supply rate or water velocity (Finlay et al. 1999, Trudeau and Rasmussen 2003, Finlay
2004). Studies such as these have demonstrated that when the water velocity is higher
and the boundary layer next to the periphyton is thinner, there is a higher supply rate of
CO2 and greater discrimination by the algae against the heavier 13C isotope.
Consequently, the δ13C signal of periphyton in faster moving water is comparatively
lower (more negative). Flow rate has also been shown to affect the δ15N signal of
periphyton. The mechanism is thought to be the same as in the case for δ13C, where the
stable isotope signal is related to supply rate and the δ15N signal of the periphyton
decreases with increased flow rate.
52
In this study, no significant difference was found between the δ13C and δ15N signals of
the periphyton in riffles and pools in El Copé and La Fortuna. This finding is in keeping
with studies such as France and Cattaneo (1998) and MacLeod and Barton (1998), where
the δ13C signal did not change with current velocity in the expected pattern. There are a
number of potential reasons for this apparent departure from the expected outcome. It is
important of course to clearly define the flow regimen of the microhabitats being referred
to as riffles and pools in the studies before results can be compared. In the Finlay et al.
(1999) study, riffles were defined as regions in the stream which had flow rates > 0.3m/s
and pool habitats as having flow rates < 0.25m/s, while Trudeau and Rasmussen (2003)
set up flow rates from 0.05m/s to 0.62m/s in their laboratory experiment. In the current
study, pools were defined as having near zero flow, and riffles as areas that had obvious
turbulent surface flow, and in fact the flow rates in such areas ranged from 0.15 – 0.3m/s
Another point to note is that the differences observed by Finlay et al. (1999) occurred in
un-productive streams and the study reported no change in isotope signal in productive
streams. The streams in this study would more accurately be described as intermediate in
production rather than unproductive. Yet another reason for the seeming inconsistency
with the Finlay et al. (1999) outcome could be related to the amount of respiration taking
place in the microenvironment. Finlay (2004) demonstrated that respiration sources of
CO2 were important to the periphyton in headwater streams. Organisms will favor lighter
isotopes for respiration and metabolic activity, so the lighter isotopes are released as CO2
and excretory products. Therefore, in environments where there is a lot of respiration, for
example, where there are high levels of decomposition, the CO2 supply rate is increased
53
(just as it is when the current velocity is higher), and more 12CO2 is available. Therefore,
the decomposition that can take place in pool microhabitats acts in antagonism to the
effect of current velocity, which can result in no appreciable difference between the
stable isotope signals in the riffles and pools. It may also be that since the stream is not
unproductive, CO2 is being heavily utilized, and there can be no discrimination against
heavy isotopes because demand outstrips supply and trends of depletion in heavier
isotopes do not occur.
The δ13C signal in El Copé is significantly lower than it is in Fortuna. The substrate
composition may help to explain this difference. In El Copé there is more silt than there
is in Fortuna. Tadpole feces may very likely be a large component of the silt, and this
would lead to high rates of CO2 production from the activity of bacteria and fungi. As
previously mentioned, the CO2 released from biological activity and available to primary
producers will be depleted in heavier isotopes, leading to an overall decrease in the
isotope signal of the periphyton as differences in carbon sources have been shown to
influence δ13C values of biota in streams (Rounick and James 1984).
Contrastingly, significant differences were found in the nitrogen stable isotope signals
between sites. The δ15N signal of the periphyton was higher in El Copé than in La
Fortuna. In El Copé, the presence of the tadpoles adds a new resource to the system. The
tadpole feces enter the environment, the nitrogen becomes recycled through the food web
and the δ15N signal of the periphyton reflects this recycled nitrogen. In Fortuna there is an
unknown contribution from recycled nitrogen of invertebrates and fish but the δ15N signal
54
is closer to atmospheric because there are no tadpoles and the primary source of nitrogen
would therefore atmospheric.
Tadpole density and periphyton
No significant linear relationship was found between δ15N and rainfall. Increased rainfall
is expected to cause a reduction in the δ15N signal via at least two mechanisms; through
the direct effect of dilution, or indirectly, through the water velocity/boundary layer
effect. Once again, riffle and pool data were combined since there was no significant
difference between the δ15N signal in the riffle and pool habitats in El Copé. There was
also no significant linear relationship between tadpole density and periphyton δ15N.
Though there is an absence of a linear relationship, it is still apparent that there is some
correlation between the tadpole density and the δ15N of the periphyton. On pre-decline
sampling occasions, the δ15N signal was high whenever the tadpole density was high and
low when the tadpole density was low. This observation coupled with the findings of
Whiles et al. (2006), where organic seston exported from El Copé streams where tadpoles
were present were found to be significantly higher in nitrogen content than streams in La
Fortuna without tadpoles, once again suggests a strong effect of tadpoles on the nutrient
cycling through the system via their feces.
There are fecal contributions by other organisms in the stream and during periods of low
flow, there is an increased effect of the feces of all the remaining biota in the stream.
However, estimated egestion rates of tadpoles in the dry season in El Copé streams
however, are of the order of 10mg m-2hr-1 AFDM (Whiles et al. 2006), so the
contribution of tadpole feces is quite significant. Therefore, on occasions where the
55
tadpole density is high (usually in the dry season), more feces are created and this has a
greater effect on the δ15N signal of the periphyton. The excretion of ammonia by the
tadpoles and other organisms can also affect the nutrient dynamics of the system as a
whole and the δ15N signal of the periphyton in particular. However, because of
discrimination against heavier isotopes during metabolism (McCutchan et al. 2003),
nitrogen inputs into the water from excretion of tadpoles and other organisms would
necessarily have a depleted δ15N signal and would not explain the increased δ15N signal
of the periphyton in El Copé. This therefore suggests, that the tadpole feces do in fact
have a very strong influence on the system, since the δ15N signals are higher in the
presence of the tadpoles, when the other processes taking place in situ would necessarily
result in a decrease in the δ15N signal.
Change in Isotope Signal with Time
The scatter plots give a very interesting view of the differences between El Copé and
Fortuna, as well as giving insight into what occurred in El Copé over time. An
outstanding difference between the 2 composite plots for El Copé and Fortuna is the
difference in the range of δ13C signal between the sites. In El Copé ∆ δ13C is
approximately 6 ‰ while in Fortuna ∆ δ13C was approximately 10‰. This is once again
reflective of the source CO2 in both locations. The presence of the tadpole feces in El
Copé, leads to higher rates of decomposition and more bacterial and fungal activity. This
effectively supplies the primary producers with a somewhat steady and reliable supply of
lighter CO2. In Fortuna on the other hand, the absence of such activity means that
generally the CO2 available will be heavier. The absence of a steady reliable supply of
56
lighter CO2 also means that the ratio of 13C : 12C of the CO2 available is much more
variable and more dependent on abiotic factors such as the water velocity. The result was
that the δ13C signal of the periphyton reflects this variability in the CO2 available for
primary production.
The opposite trend is evident in relation to the δ15N of periphyton between the sites.
There is more variability in the δ15N signal in El Copé than in Fortuna. This is once again
related to the source of nitrogen in both places. The source of nitrogen in Fortuna is
atmospheric, which has a constant ratio of 15N : 14N. The δ15N signal of the periphyton in
Fortuna is closer to atmospheric and the observed variability in the δ15N signal in Fortuna
is likely related to variability in local supply rate i.e. water velocity. In El Copé on the
other hand, the nitrogen supply has a large recycled component and therefore the δ15N of
the periphyton at this site is more affected by the presence of the tadpoles. Tadpole
abundance varies over a wide range over the course of the study. It is this variability in
tadpole density and therefore tadpole feces that is reflected in the δ15N of the periphyton.
The pre and post-decline scatter plots reveal a very interesting trend (Figures 2.3c, d).
The δ15N signal has gradually decreased in the months following the die-off. Once again,
this occurred when the tadpole density was very low in February 2005 and is nearly zero
in May 2005. The influence of tadpole feces has been gradually removed from the system
and the δ15N signal approaches the atmospheric signal. The sample sizes were smaller in
the post-decline plots, but it is also apparent that there has been no real change in the δ13C
signal since the die-off. This may be related to the fact that there was likely a fair amount
57
of decomposition still being carried out in the stream possibly from dead and decaying
tadpoles and adult frogs.
The site at La Fortuna is not currently being monitored, but monthly periphyton samples
are being taken in El Copé by the TADS team. This is important since El Copé has
already begun to approach Fortuna, if only in the δ15N signal. The δ13C signal in El Copé
is expected to also become more similar to that in La Fortuna when the pulse of
decomposition caused by the die-offs subsides. The continuing studies will help to
determine whether El Copé does in fact become more similar to Fortuna in both δ15N and
δ13C signals, as well as determine the length of time required for the process to take
place.
58
References Cabana, G., Rasmussen, J. 1996. Comparison of aquatic chains using nitrogen isotopes. Ecology. 93 : 10844-10847 Dickman, M. 1968. The effect of grazing by tadpoles on the structure of a periphyton community. Ecology. 49 : 1188-1190 Finlay, J., Power, M., Cabana, G. 1999. Effects of water velocity on algal carbon isotope ratios: Implications for river food web studies. Limnology and Oceanography. 44 : 1198-1203 Finlay, J.C. 2004. Patterns and controls of lotic algal stable carbon isotope ratios. Limnology and Oceanography. 49 : 850-861 France, R.L. 1996. Absence or masking of metabolic fractionations of 13c in a freshwater benthic foodweb. 1996. Freshwater Biology. 36 : 1-6 France, R., Cattaneo, A. 1998. δ13C variability of benthic algae: effects of water colour via modulation by stream current. Freshwater Biology. 39 : 617-622 Hansson, L. 1992. Factors regulating periphytic algal biomass. Limnology and Oceanography. 37 : 322-328 Herman, P., Middelburg,. J, Widdows, J., Lucas, C., Heip, C. 2000. Stable isotopes as trophic tracers: combining field sampling and manipulative labeling of food resources for macrobenthos. Marine Ecology Progress Series. 204 : 79-92 Hershey, A.E., Peterson, B.J. 1996. Stream food webs. p 511 - 530. In Methods in Stream Ecology. (Ed by F.R. Hauer and G.A. Lamberti). Academic Press. UK Kiesecker, J., Blaustein, A. 1998. Effects of introduced bullfrogs and smallmouth bass on microhabitat use, growth and survival of native red-legged frogs (Rana aurora). Conservation Biology. 12 : 776-787 Kilham, S.S., Pringle, C.M. 2000. Food webs in two neotropical stream systems as revealed by stable isotopes. Verhandlungen Internationale Vereinigung für Limnolgie 27 : 1768-1775 Lamberti, G.A., Gregory, S.V., Askenas, L.R., Steinman, A.D., McIntire, C.D. 1898. Productive capacity of periphyton as a determinant of plant-herbivore interactions in streams. Ecology. 70 : 1840-1856 Lips, K. 1999. Mass mortality and population declines of anurans at an upland site in western Panama. Conservation Biology. 13 : 117-125
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Lips, K., Reeve, J., Witters, L. 2003. Ecological traits predicting amphibian population declines in Central America. Conservation Biology. 17: 1078-1088 Loeb, S. L. 1981. An in situ method for measuring the primary productivity and standing crop of the epilithic periphyton community in lentic systems. Limnology and Oceanography 26: 394-399 McCutchan, J.H. Jr., Lewis, W.M. Jr., Kendall, C., McGrath, C. 2003. Variation in trophic shift for stable isotope ratios of carbon, nitrogen and sulfur. Oikos. 102: 378 – 390 MacLeod, N.A., Barton, D.R. 1998. Effects of light intensity, water velocity, and species composition on carbon and nitrogen stable isotope ratios in periphyton. Canadian Journal of Fisheries and Aquatic Sciences. 55 : 1919-1925 Machás, R., Santos, R. 1999. Sources of organic matter in Ria Formosa revealed by stable isotope analysis. Acta Oecologia. 20 : 463-469 March, JG., Pringle, C.M. 2003. Food web structure and basal resource utilization along a tropical island stream continuum, Puerto Rico. Biotropica. 35 : 84 - 93 Mninshall, G.W. 1967. Role of allochthonous detritus in the trophic structure of a woodland spring brook community. Ecology. 8 : 139-149
O’Reilly, C.M., Hecky, H.E., Cohen, A.S., Plisnier, P.D. 2002. Interpreting stable isotope food webs: Recognizing the role of time averaging at different trophic levels. Limnology and Oceanography. 47 : 306-309 Peterson, C., Boulton, A. 1999. Stream permanence influences microalgal food availability to grazing tadpoles in arid-zone springs. Oecologia. 18 : 340-352 Peterson, B.J., Fry, B. 1987. Stable isotopes in ecosystem studies. Annual Review Ecology and Systematics. 18 : 193-320
Riera, P., Stal, L., Nieuwenhuize, J., Richard, P., Blanchard, G., Gentil, F. 1999. Determination of food sources for benthic invertebrates in a salt marsh (Aiguillon Bay, France) by carbon and nitrogen stable isotopes: importance of locally produced sources. Marine Ecology Progress Series. 187 : 301-307
Rounick, J.S., James, M.R. 1984. Geothermal and cold springs faunas: Inorganic carbon sources affect isotope values. Limnology and Oceanography. 29 : 386-389 Sanzone, D., Meyer, J., Marti, E., Gardiner, E., Tank, J., Grimm. N. 2003. Carbon and nitrogen transfer from a desert stream to riparian predators. Oecologia 134: 238-250
60
Trudeau V., Rasmussen, J.B. 2003. The effect of water velocity on stable carbon and nitrogen isotope signatures of periphyton. Limnology and Oceanography. 48 : 2194-2199 Vander Zanden, M.J.V., Rasmussen, J.B. 1999. Primary consumer δ13C and δ 15N and the trophic position of aquatic consumers. Ecology. 80 : 1395-1404 Vannote, R., Minshall, G., Cummins, K., Sedell, J., Cushing, C. 1980. The river continuum concept. Canadian Journal of Fisheries and Aquatic Sciences. 37 : 130-137 Whiles, M., Lips, K., Pringle, C., Kilham, S.S., Bixby, R.J., Brenes, R., Connelly, S., Colon Gaud, J.C., Hunte-Brown, M., Huryn, A. D., Montgomery, C., Peterson, S. 2006. The Consequences of Amphibian Population Declines to the Structure and Function of Neotropical Stream Ecosystems. Frontiers in Ecology and the Environment. 4 : 27-34. Woodward, G. Hildrew A. 2002. Food web structure in riverine landscapes. Freshwater Biology 47 : 777-798 Yam, R.S., Dudgeon, D. 2005. Stable isotope investigation of food use by Caridina spp. (Decapoda: Atyidae) in Hong Kong Streams. Journal of the North American Benthological Society. 24 : 68-81 Young, B., Lips, K., REaser, J., Ibánez, R., Salas, A., Cedeño, J., Coloma, L., Ron, S., Marca, E., Meyer, J., Muñoz, A., Bolaños, F., Chaves, G., Romo, D. 2001. Population declines and priorities for amphibian conservation in Latin America. Conservation Biology. 15 : 1213-1223
61
Figures Periphyton δ15N in Riffles and Pools (El Cope)
-2
0
2
4
6
Jun 03 Hi Rain
Aug 03 Low Rain
Jan 04 Med Rain
May 04 Low Rain
Sep 04 Med Rain
Feb 05 Med Rain
May 05Med Rain
Date
δ15N
RifflePool
Periphyton δ15N in Pools and Riffles (Fortuna)
-2
0
2
4
6
Jun 03 Hi Rain
Aug 03 Med Rain
Jan 04 Med Rain
May 04 Hi Rain
Sep 04 Hi Rain
May 05 Hi Rain
Date
δ15N
RifflePool
Periphyton δ13C in Riffles and Pools (El Cope)
-32
-31
-30
-29
-28
-27
-26
-25
-24
Jun 03 Hi Rain
Aug 03 Lo Rain
Jan 04 Med Rain
May 04 Low Rain
Sep 04 Med Rain
Feb 05 Med Rain
May 05Med Rain
Date
δ13C
RifflePool
Periphyton δ13C in Riffles and Pools (Fortuna)
-32
-31
-30
-29
-28
-27
-26
-25
-24
Jun 03 Hi Rain
Aug 03 Med Rain
Jan 04 Med Rain
May 04 Hi Rain
Sep 04 Hi Rain
May 05 Hi Rain
Date
δ13C
RifflePool
Figure 2.1 δ15N and δ13C signals of the periphyton in the riffle and pool environments in El Copé and Fortuna from June 2003 to May 2005. Relative amounts of rainfall received are noted on the
figure. <200mm = Low Rain, 200-400mm = Med Rain and >400mm = Hi Rain
a
b
c
d
62
Figure 2.2 Tadpole density and periphyton δ15N signal in riffle and pool environments in El Copé from June 2003 to May 2005. The threshold density of tadpoles is labeled as 10
individuals per m2 and threshold periphyton δ15N signal labeled as 4‰. ‘*’ denotes samples taken after die-offs had begun
Tad Density and Periphyton δ15N compared with Rainfall
0
1
2
3
4
5
6
Lo Med Lo Hi* Med* Med*
Amount of Rainfall
δ15N
024681012141618
Tad
Den
sity
( #'
s /s
q m
)
δ15N Tad Density
63
Periphyton Scatter Plot - El Cope - June '03 - Sep '04
-2
0
2
4
6
8
10
-34 -33 -32 -31 -30 -29 -28 -27 -26 -25 -24 -23 -22 -21 -20
δ13C
δ15N
Periphyton Scatter - Fortuna
-2
0
2
4
6
8
10
-34 -33 -32 -31 -30 -29 -28 -27 -26 -25 -24 -23 -22 -21 -20
δ13C
δ15N
Periphyton Scatter - El Cope Feb '05
-2
0
2
4
6
8
10
-34 -32 -30 -28 -26 -24 -22 -20
δ13C
δ15N
Periphyton Scatter - El Cope May 05
-2
0
2
4
6
8
10
-34 -32 -30 -28 -26 -24 -22 -20
δ13C
δ15N
Figure 2.3 Scatter plots of all periphyton δ13C and δ15N signals in Fortuna and pre and post decline El Copé.
a b
c
d
64
CHAPTER 3: The Effects of Frog Extirpation on the Trophic Structure of Tropical Montane Streams in Panamá as Revealed by Stable Isotopes
Abstract: Amphibian populations, though relatively inconspicuous, can comprise a significant
proportion of vertebrate biomass in tropical forests. Unfortunately, these large
populations of amphibians have been experiencing massive extirpations over the past few
decades and stream dwelling species are disproportionately affected. This is of particular
concern because the tadpoles are functionally dominant herbivores in the streams, so their
extirpation is expected to have significant consequences for ecosystem structure and
function. This study is part of the larger collaborative TADS (Tropical Amphibian
Declines in Streams) Project. Stable isotopes of carbon and nitrogen are employed to
investigate the trophic relationships in two streams that were differentially affected by the
frog extirpations, as well as a subset of the riparian food web in El Copé, specifically
lizards, snakes, spiders and adult frogs. The study was carried out at two sites in the
uplands of Panamá - Fortuna where the amphibian population has been extirpated since
1997 and El Copé where there was a healthy amphibian population at the beginning of
the study. Over the course of the study, a massive die off occurred in El Copé, affording a
unique opportunity to study the food web during an extirpation event. A number of
interesting trends were recognizable from the data. The nitrogen source in El Copé has a
strong recycled component compared with Fortuna. The food web is truncated in the
absence of the tadpoles. The δ15N signal of most stream resources is higher in El Copé
than it is in Fortuna. There appears to be more fractionation of δ13C in Fortuna than in El
65
Copé. The spiders have an aquatic signal in El Copé and there is more fractionation in
tadpoles than aquatic insects.
Introduction: The concept of a food web has been a central theme in ecology ever since its classical
development (Elser et al. 2000). Food webs provide an important conceptual link
between population and community ecology (Woodward and Hildrew 2002) and
represent pathways along which energy and materials flow within and between
ecosystems. They differ in structure and function between stream types, even though they
have some common elements (Hershey and Peterson 1996) and they are often quite
complex. In most streams there are 3 or 4 trophic levels in the food web (Mantel et al.
2004) and the species comprising these trophic levels are restricted by the factors that
determine the structure and function of the food web.
Stable isotope analysis can be used to track the transfer of organic carbon and nitrogen
from plant and detrital sources to primary and secondary consumers (Hershey and
Peterson 1996, Herman et al. 2000). This method provides a powerful tool for
unraveling the complex structure of food webs (Gannes et al. 1997, Stapp et al. 1999,
Post et al. 2000, O’Reilly et al. 2002) and is based on the fact that organisms retain the
stable isotope signals of the resources they assimilate (Mahcás and Santos 1999).
In many ecosystems the organisms have different 13C : 12C and 15N :14N ratios and
therefore the diets of the consumers can be inferred from the isotopic ratios in the
consumers’ tissues (Hershey and Peterson 1996). Animal tissues become only slightly
66
enriched in 13C in relation to their food (∆~1‰ δ13C) per trophic step (Finlay et al. 1999,
Yoshii 1999, Kilham and Pringle 2000), but become more significantly enriched in 15N in
relation to their food (∆ ~3.4‰ δ 15N) (Cabana and Rasmusssen 1996, Yoshii 1999, Post
et al. 2000, Vander Zanden and Rasmussen 2001). Therefore, certain aspects of an
animal’s diet can be reconstructed from the isotopic ratios (DeNiro and Epstein 1981).
Stable isotope data for carbon are typically used to provide information regarding the
basal resources of the food web (Boon and Bunn 1994, Hecky and Hesslein 1995, Vander
Zanden and Rasmussen 1999, Yoshii 1999, O’Reilly et al. 2002) while trophic
enrichment in 15N of the consumer with respect to its food is predictable enough to permit
its use as an indicator of realized trophic level (Minawaga and Wada 1984, Kling et
al.1992, Cabana and Rasmussen 1996, Hershey and Peterson 1996, Peterson 1999, Stapp
et al. 1999). Stable isotope analyses provide continuous measures of trophic position,
rather than discrete trophic levels (Post et al. 2000). This method of analysis can
efficiently determine the strength of the trophic interactions (Kling et al. 1992) and thus
trace the flow of energy through the system.
This study was carried out in the uplands of Panama, in an effort to investigate the
changes in stream trophic structure as a result of the extirpation of stream dwelling frogs.
It is widely known that amphibian populations have been on the decline over the past
several years, and as many as 13 Latin American countries have reported massive
declines or even extirpations primarily in upland regions over the last 20 years (Lips et al.
2003). Amphibians are known to be indicator species and are sensitive to a variety of
67
environmental contaminations (Kiesecker and Blaustein 1997, Lips 1999), so the
widespread declines are especially concerning.
Many of the amphibian extirpations appear to be caused by chytrid fungal infections and
species found in or near aquatic habitats at elevations >500m are more vulnerable than
terrestrial and lowland species (Young et al. 2001). The tadpoles are functionally
dominant herbivores in these systems (Dickman 1968), and therefore, their extirpation is
expected to cause significant increases in periphyton biomass, reduced biomass-specific
primary production, reduced quantity and quality of fine particulate organic matter along
with other effects on ecosystem structure function. This study is part of the much larger
collaborative TADS (Tropical Amphibian Declines in Streams) study that look at a range
of effects caused by the loss of the frogs, including changes in food web structure,
community structure and production budgets among other ecosystem characteristics.
Methods: Site Description: The study was conducted at two sites in Panamá, Central America; one
site, La Fortuna reported had frog extirpations in 1997, while the second site, El Copé
had a healthy anuran population at the beginning of the study. La Fortuna is located in
western Panamá in the highlands of Chiriquí province (8˚ 42´ N, 82˚ 14´W) (Figure 1.1).
The forest has a uniformly dense canopy and is located primarily above the Edwin
Fabrega Dam on the upper Chiriquí River. The study stream in Fortuna, Quebrada
Chorro, has a moderate gradient, distinct pool, run, riffle sequences, with waterfalls and
plunge pools, frequent large boulders and granitic outcrops, as well as substrates
consisting primarily of pebbles, gravel, sand, and silt in depositional areas. A 100m reach
68
was selected in each location as the study area. Since the current study is part of the
TADS project, the study reaches chosen overlapped with the study reaches of the other
projects, to ensure continuity of the dataset.
El Copé is located 200km east of La Fortuna in Parque Nacional G. D. Omar Torríjos H,
El Copé, Coclé (Figure 1.1). The study stream in El Copé was Río Guabal, which had
similar physical characteristics to Que. Chorro in La Fortuna. The amphibian fauna of El
Copé was diverse with 74 species known from the site, at least 22 of which had stream
dwelling larvae, and at least 40 occupied riparian habitats. The amphibians were
abundant throughout the year, and tadpoles were the only vertebrate grazers in the
headwaters of the Río Guabal. The wet season lasts from mid May to November and both
locations received 3,500 - 4,500mm of rain per annum over the duration of the study
(Figures 1.2 and 1.4). There is a normal cyclical decrease in tadpole abundance around
the onset of the wet season each year, which corresponds with adult emergence. In
September 2004 when the decrease in tadpole abundance would normally have occurred,
there were massive die-offs of the stream dwelling frogs. Consequently, the stream
tadpole population was unable to recover because of a lack of new recruitment.
Sample and Data Collection: Physico-chemical data were collected monthly from June
2003 to May 2005. Water temperature, pH, dissolved oxygen and conductivity were
measured using a Quanta hydrolab and water velocity was measured using a Global
Water Flow Probe. Rainfall and air temperature were recorded daily at each site, using a
rain gauge and maximum-minimum thermometer and tadpole densities were determined
69
by daily instream counts. The instream substrate composition and discharge were also
determined.
Biological samples were collected seasonally to coincide with the dry, early-wet and wet
seasons. Samples were collected from riffles and pools every 20m along the 100m study
reach. Fine benthic organic matter (FBOM) was opportunistically sampled using a turkey
baster to siphon water from pool areas where FBOM was obvious. The water containing
the FBOM was then filtered onto a glass fiber filter. Seston was collected by filtering 2L
of fast flowing water onto a glass fiber filter and periphyton samples were collected using
modified loeb samplers (Loeb 1981). Five collections of periphyton were taken every
20m along the 100m study reach, from riffle and pool areas and then combined to make
individual riffle and pool samples. The composite samples were then filtered onto glass
fiber filters. The biofilm growing on leaves in the stream was collected by rinsing leaves
by hand in a filter funnel and then filtering the water onto a glass fiber filter.
Coarse particulate organic matter (CPOM) was collected by hand from the stream and
associated invertebrates removed. Filamentous green algae was removed by hand from
submerged surfaces. Standard kick net procedures were used to collect invertebrates from
riffle areas, while in pool areas, rocks were disturbed and aquarium nets used to collect
the invertebrates and tadpoles. Fish were collected using kick nets and aquarium nets,
while spiders were collected by using a twig to tap them into a collection bag. Snakes,
lizards and adult frogs were collected, euthanized and sample tissues taken by R. Brenes
and C. Montgomery under a collecting permit to Dr. K. Lips. All filters and samples were
70
frozen and transported to Drexel University, Philadelphia, Pennsylvania to be prepared
for stable isotope analysis. The number of individuals of each taxon collected varied
depending on availability and permit allowances. The N for each group is recorded in
Appendix 2.
Sample Preparation and Analysis: Punches of 0.9cm diameter were taken from the filters
and dried in a drying oven at 65-70°C for 24hrs. After drying 2 punches were loaded into
5 x 9mm tin capsules (Costech Analytical Technologies Inc). All other samples were
ground to a fine powder and loaded into 4 x 6mm tin capsules. The loaded capsules were
then placed in 96-well plates, with replicates included for every fifth sample. The
samples were sent to the Stable Isotope and Soil Biology Lab at the Institute of Ecology,
University of Georgia, Athens, Georgia where they were analyzed for stable isotope
content using Carlo Erba NA 1500 CHN analyzer coupled to a Finnigan Delta C mass
spectrometer. Poplar and bovine standards were inserted after 12 samples. Isotope ratios
are expressed as δ13C ‰ or δ15N ‰ according to the equation:
δ13C ‰ or δ15N ‰ = [(Rsample/Rstandard) – 1] x 1000 δ‰
where Rsample is the 13C:12C or 15N:14N ratio of the sample and Rstandard is the 13C:12C or
15N:14N ratio of the standard (PeeDee belemnite carbonate for δ13C and atmospheric N for
δ15N).
71
Results: Fortuna and El Copé had similar amphibian populations prior to the 1997 extirpation in
Fortuna (Lips 1999). At the beginning of the study the major difference between the sites
was the absence of frogs in Fortuna as there were over 50 species of amphibians in El
Copé and densities ranged between 2 and 29 individuals per m2 (Figure 1.2). After the
extirpation occurred in October 2004, the amphibian population density in El Copé was
found to be close to zero, as it was in Fortuna.
The substrate composition was found to be different at both sites especially with respect
to the smaller size fractions. There was more sand and less silt in Fortuna than there was
in El Copé (Figure 1.10). Average water temperature was 21.4°C in El Copé and 18.4°C
in Fortuna. The DO was similar at both sites; 6.5mg/l in El Cope and 7.0mg/l in Fortuna.
The pH was also similar at both sites with values averaging 8.2 in El Copé and 8.3 in
Fortuna, while the conductivity was higher in El Copé (0.03mS) than in Fortuna
(0.01mS) (Table 3.1). The nutrient concentrations were low at both sites (Table 3.2) (S.
Connelly pers. comm.).
The scatter plots of the stable isotope data (Figure 3.1) demonstrate an interesting feature
of the food web at both sites. There are no obvious trophic levels, but rather a continuum
from primary producer to top consumer. The scatter plots of pre-decline data from El
Copé compared with Fortuna reveal interesting trends (Figures 3.1a and b). The food web
appears to be truncated in Fortuna compared with El Copé. The slope of the isotope
signatures in the food web in El Copé is much steeper than it is in Fortuna because there
72
seems to be more fractionation of δ13C in Fortuna than there is in El Copé. The isotope
signal of the periphyton is very different at both sites. The periphyton δ15N signal is
lower in Fortuna than it is in El Copé and the δ13C signal is more negative in El Copé
than it is in Fortuna. The δ15N signals of the consumers are also higher in El Copé than
they are in Fortuna. The range of δ13C of the insects is wider in El Copé than in Fortuna.
In El Copé the fish are the top consumers while the crabs seem to have taken on that role
in Fortuna.
When comparing the pre and post decline scatter plots for El Copé there do not seem to
be any obvious differences (Figures 3.1a, c and d). On closer analysis, however, it
appears that the trend among the points in the post-decline plots has changed from linear
to curvilinear. From the post decline plots it seems that the food web in El Copé has not
yet approximated to that in Fortuna. Scatter plots of the leaf pack biofilm (Figure 3.2),
indicate that the composition of the leaf pack biofilm is very different in Fortuna and El
Copé. The δ15N of the biofilm in El Copé is generally higher than it is in Fortuna while
the reverse is true for the δ13C signal. In addition, Figures 3.2 a and c indicate that there
have been some changes within El Copé in the leaf pack biofilm since the amphibian
decline.
Summary charts were also drawn for all the resources in El Copé and Fortuna. The crabs,
frogs and snakes do not appear to be a part of the stream food web (Figure 3.3) and the
δ13C signal among this group is closer to terrestrial than aquatic. Although the range is
very wide, it does not appear that the seston is an important part of the food web in pre-
73
decline El Copé while the seston does seem more important in post-decline El Copé. The
δ15N signal of the herbivorous tadpoles is higher than that of the insects, while the fish
remain the top consumers in the system. The summary charts for post-decline El Copé
(Figures 3.3 b and c) are very similar to the pre-decline chart (Figure 3.3a). The
filamentous algae point is not shown in the May 2005 summary because the δ13C signal
for the filamentous algae was very negative (-41.7‰, N = 4) compared with the other
values. This δ13C value indicates that the filamentous algae were not part of the food web
in El Copé.
The summary plot for Fortuna (Figure 3.3b) is quite dissimilar to El Copé. The
filamentous algae have a δ13C signal which does fall within the range of the other
resources in the food web. The periphyton has a very different stable isotope signal in
Fortuna than it does in El Copé; the δ15N signal in Fortuna is depleted while the δ13C
signal is enriched. The food web is also not as clearly defined as it is in El Copé. The
most outstanding difference once again is the comparatively low δ15N signals of
consumers because of lower δ15N fractionation in Fortuna. This difference is further
demonstrated in that the δ15N signal of the selected resources is significantly higher (p <
0.1) in almost very case in El Copé (Figure 3.4).
Figure 3.5 shows the summary and scatter plots for the adult frogs, lizards and snakes.
While only a small subset of the riparian and terrestrial food web was sampled, a few
interesting observations are apparent. Bufo had the highest δ15N of all the anurans, and
seems to have a trophic position more similar to the snakes than to the frogs (Figure
74
3.5a). The data suggest that Eleutherodactylus talamancae and E. punctariolus are
feeding at slightly different trophic levels. It is possible that the ‘circled’ snakes feed on
the ‘circled’ frogs and that the lizard Norops lionotus is also eaten by the snakes.
Centrolenella prosoblepon does not appear to be used as food by any of the snake
samples and apparently no prey species used by the snake Sibon annulatus have ben
sampled.
Discussion:
The stream food webs: A broad view
Comparing the scatter plots of the stream food webs reveals a few outstanding trends.
One major feature of the scatter plots of the stream food webs in Figure 3.1 is that each
plot is a continuum of values. There is no clustering of resources into clearly identifiable
trophic levels. Trophic relationships in tropical stream systems are often indistinct
because of omnivory (Pringle and Hamazaki 1998, Kilham and Pringle 2000, Parkyn et
al. 2001) and omnivory has been implicated as having an important role in structuring
stream communities (Graca et al. 2000) Omnivory can be defined as feeding at multiple
trophic levels (Tavares-Cromar and Williams 1996) either within one life stage, or as
lifestyle omnivory which occurs when organisms switch diets with ontogentic
development. Tropical stream systems characteristically have an abundance of
omnivorous macroconsumers (Pringle and Hamazaki 1998) and the stable isotope data in
this study suggest that this may also be the case in the study streams.
75
Over the course of the field season of the study, it became evident that the periphyton and
leaf packs were not as heavily utilized as initially thought and that the biofilm on the
leaves was more important. The δ15N signal of the leaf biofilm indicated that it was in
fact an important resource being utilized by the stream organisms in El Copé but it did
not seem to be as important in Fortuna. The composition of the biofilm is unknown, but it
is very probable that it is different in El Copé and Fortuna. The absence of the tadpoles
and consequently their feces means that the microbial community composition could be
very different in both locations. These differences in microbial community composition
can translate into differences in palatability and nutritional quality of the biofilm and
ultimately differences in utilization between sites.
Figure 3.2 shows the stable isotope signals of the leaf pack biofilm in Fortuna and post-
decline El Copé. There is a wider range in the δ15N signal of the biofilm in El Copé than
there is in Fortuna, likely as a result of microbial activity in the remaining FBOM, which
apparently decreases from February 2005 to May 2005 (8 months post decline). This
variability in the biofilm δ15N could explain the variability in the rest of the food web,
especially the insects. The δ15N signal of the biofilm in El Copé also seems to become
more depleted with time. In February there were 8 points above 4‰ compared to 3 in
May. The absence of the tadpoles and their feces in post decline El Copé means that the
recycled component of the δ15N is gradually lost, and the δ15N signal of the biofilm is
expected to eventually be very similar to that in Fortuna.
76
It is also interesting that the range δ13C signal of the leaf pack biofilm is greater in
Fortuna than it is in El Copé. In El Copé the δ13C signal of the biofilm seems to be
becoming more depleted after the die-offs as there are 8 points above -28‰ in February
compared to 5 in May. This could be due to a pulse in CO2 production due to higher
decomposition rates after the die-offs resulting in increased 12CO2 availability, which
would ultimately decrease the δ13C signal of the biofilm.
Figures 3.1a and b demonstrate the fact that the food web is condensed in Fortuna, and
the slope of the two isotopes in Fortuna is less than it is in El Copé. One reason for this
observation may be that there is less trophic fractionation of 13C in El Copé. Trophic
fractionation of 13C may be affected by the substrate composition at both sites and the
potential effects of substrate composition on carbon dioxide production. There is more of
the silt size fraction in El Copé than there is in Fortuna (Figure 1.6), and the silt very
likely has a significant FBOM component, consisting largely of feces tadpoles and other
organisms. Tadpole egestion rates have been estimated at 10 mg m-2 hr-1 in the dry season
in El Copé streams (Whiles et al. 2006), therefore the most significant fecal contribution
is thought to come from the tadpoles. The presence of the tadpole feces ultimately leads
to increased microbial activity, specifically decomposition and respiration. Generally,
molecules with heavier isotopes are discriminated against during uptake and metabolic
activity, therefore carbon dioxide produced from respiration is typically depleted in 13C
(McCutchan et al. 2003). Consequently, the increased microbial decomposition in El
Copé ultimately leads to increased availability of 12CO2 molecules. Since the lighter
molecules are favored by the primary producers, the end result is that the δ13C signal was
77
relatively depleted (more negative) in El Copé. In Fortuna, the tadpoles have been
extirpated, and there is less FBOM and silt than there is in El Copé. This could lead to
less decomposition, and thus less in situ production of 12CO2. In the absence of in situ
CO2 production, the only significant source of CO2 would be the atmosphere through the
water and this would increase susceptibility to the effects of flow rate on the δ13C signal.
Typically, the δ13C signal of the primary producers is enriched (less negative) in slow
flow conditions and depleted in δ13C when there is faster flow (Finlay et al. 1999). The
variability that would necessarily exist in the producer δ13C due to differences in flow is
transferred up the food web. The result is the wide variation observed in δ13C signal of
the producers and consumers in Fortuna.
In contrast, there is more trophic fractionation of 15N in El Copé than there is in Fortuna
(Figure 3.1). While the nutrient concentration was found to be low at both sites (Table
3.2), in El Copé the nitrogen supplied to the basal autotrophs in the system has a large
recycled component. The source of this recycled nitrogen is the organisms themselves,
specifically the tadpoles via their feces, which probably leads to the higher δ15N signal
observed in El Copé. In addition to nitrogen inputs from tadpole feces, nitrogen inputs
can also come from excretion of ammonia by the tadpoles and other organisms. However,
δ15N signals of excreted ammonia are depleted in 15N because of discrimination against
heavier isotopes during metabolism (McCutchan et al. 2003). Therefore the enriched
δ15N signal in El Copé suggests a strong influence of tadpole feces on the nitrogen
available to the autotrophs and the enriched δ15N signal is then transferred up the food
web. The absence of the tadpole feces in Fortuna means that the recycled component is
78
not as significant, the atmosphere becomes more important as a source of nitrogen, and
the result is the observed δ15N signal being more depleted in Fortuna.
In a previous study carried out at the same site in 2000 (Kilham et al. unpubl data) only
the very largest tadpole in the study had insect remains in the stomach. Ranvestel et al.
(2004) also working at the same location, found that 31% of the gut contents of the
tadpoles was periphyton, 50% was amorphous detrital material, one individual had
ingested filamentous algae, but 9 of the 10 individuals examined had ingested terrestrial
plant leaves. The data in the current study show that the tadpoles are not a full step higher
than the insects and it is unlikely that they are generally able to ingest insects (R. Brenes
pers. comm.). Vanderklift and Ponsard (2003) demonstrated that many factors can affect
fractionation. They found that the fractionation factor was higher among vertebrates than
invertebrates. The insects represented in Figures 3.1 and 3.3 range in functional group
from herbivorous to predatory. Although the tadpoles in the study do not eat insects, they
exhibit δ15N signals even higher than those of the predatory insects in the study. This is
because there is more fractionation among vertebrates than invertebrates, because of the
demands of vertebrate metabolism. Therefore, tadpoles utilizing an identical diet to
insects would be expected to have a more enriched δ15N signal.
With the passage of time, one might expect the post-decline scatter plots from El Copé
(Figure 3.1c and d) to resemble the scatter plot from Fortuna (Figure 3.1b) where
amphibian declines were first reported seven years earlier. However, stable isotopes
reflect trophic position at the scale of tissue turn over (Kling et al. 1992, Hecky and
79
Hesslein 1995, March and Pringle 2003), and the post decline samples were collected
five and eight months after the tadpole decline began in El Copé. Therefore, the reason
the food web in El Copé does not closely resemble that of Fortuna may simply be that
there was not enough time between the die-off and sample collection, and the system in
El Copé is still in transition.
Although the post-decline sample sizes in El Copé are smaller than the pre-decline
sample size, a subtle change in the post-decline scatter plots is discernable: a change from
a linear to curvilinear shape. This may be a part of the transition process to the post
decline state represented by Fortuna. If we consider that the stable isotope signal averages
trophic position over the scale of tissue turn over, the primary producers would be the
first group in which a change in the isotopic signature would be detected. This has
already been observed as the δ15N signal of the periphyton has become more depleted in
the months following the decline (Chapter 2). The next group to be affected would be the
primary consumers or invertebrates and the δ15N signal of the group would become more
depleted in δ15N while the secondary consumers may remain unchanged. Over time this
gradual depletion in δ15N of each successive consumer group, when displayed as a scatter
plot, will result in the general shape of the scatter being curvilinear, because the slope of
the lower section of the plot decreases at a faster rate than the upper section. This gradual
change is expected to continue until the system reaches a new equilibrium and the scatter
once again is approximately linear as it already is in Fortuna.
80
The stream food webs: A closer look
Food chain length is the number of links between basal (those which have no prey) and
top (those which have no predators) trophic species (Schoener 1989). Maximum trophic
level (Post et al. 2000) is conceptually similar to food chain length and is an important
community characteristic because it affects community structure, and ecosystem
function. The change in δ15N signal from the base to the top of the food web is different
at both sites. In El Copé ∆ δ15N is 6.5‰ while at Fortuna the ∆ δ15N is 4.3‰, a difference
of 2.2‰ between the chain lengths at both sites. With the emerging data showing that the
∆ δ15N per trophic step is 1.8 – 2‰, it is apparent that in the absence of the frogs, the
food chain length has become truncated by the equivalent of one trophic step.
Figure 3.3a shows the pre-decline trophic structure in El Copé. The general structure of
the food web is relatively simple. The fish are the top consumers in El Copé and the adult
frogs and snakes are riparian and terrestrial. Therefore it is expected that the δ13C signal
of these groups would be closer to the terrestrial signal. Most of the frogs consume
terrestrial insects (Savage 2002). In the case of the crabs, although they live in the stream,
the crabs tend to feed on detritus, which is generally terrestrial in origin. March and
Pringle (2003) reported some reliance on leaf detritus by the crab and in their study,
while Rudnick and Resh (2005) reported that the gut contents of the crabs were
dominated by terrestrial detritus. This results in the observed δ13C signal of the crabs
being closer to the terrestrial signal. The crabs collected in the streams were for the most
part reasonably small (carapace width <30mm), therefore the whole body was used in the
samples. This can affect the δ13C signal of the crabs, because the exoskeleton of the crab
81
contains more carbon than the muscle tissue. Therefore, samples containing exoskeleton
can be more enriched in 13C and this effect on the δ13C signal is enhanced as surface area
to volume ratio increases. In Fortuna, the crabs tended to be larger than they were in El
Copé (carapace width >30mm) and the stable isotope signal of the crabs seemed to
indicate that they had taken over the position as top consumer compared with the fish in
El Copé. However, because of the large amount of fractionation of stream δ13C in
Fortuna compared with El Copé, it may just be that the δ13C signal of the other stream
consumers has so closely approached the terrestrial signal that it appears as though the
crabs are now a part of the stream food web.
The average isotopic signal of the seston suggests that it is not an integral part of the food
web Figure 3.3a. However, there was a lot of variability in the seston, so it can not be
totally ruled out of the aquatic food web in El Copé. The isotopic signals of the FBOM,
on the other hand, suggest that this resource may be important in the food web. This
observation supports the hypothesis that tadpole feces are an important resource in El
Copé since much of the FBOM is thought to be tadpole feces.
In contrast to the simple linear structure of the food web in El Copé, the food web in
Fortuna is not as well defined (Figure 3.3b). The δ15N signals of the resources are lower
in Fortuna than they are in El Copé. Figure 3.4 further demonstrates the difference in
nitrogen source between the two sites. The basal resources and consumers shown in
Figure 3.4 were present on all sampling occasions at both sites. The δ15N signal is
significantly higher in these resources in El Copé compared with Fortuna, in every case
82
except the crabs. As previously discussed, the δ13C signal of the crabs suggests that they
are not a part of the stream food web, therefore the crabs would be less affected by the
δ15N signals lower in the stream food web. Seston, (which is not shown in Figure 3.4), is
very variable and may be of terrestrial origin as well and is therefore not as influenced by
the instream δ15N signal as the other resources. In the case of the basal resources and
consumers that are 100% aquatic in origin however, the recycled nitrogen signal that is
present in El Copé because of the presence of the tadpole feces, is transferred up the food
web, and in every case, the δ15N signal is higher in El Copé than it is in Fortuna.
The riparian food web:
The adult frogs, snakes, spiders and lizards make up the riparian food web, and even
though it was not possible to sample the entire riparian food web, these important players
were collected and some inferences made from the stable isotope signals. The spiders
were collected from riparian vegetation and their δ15N signals suggest that they are a part
of the aquatic food web, possibly feeding on emergent adult insects. The aquatic insects
would still have a strong aquatic signal immediately after emergence and maintain this
signal until feeding in the terrestrial environment and subsequent tissue turn over occurs.
Further, some adult insects do not feed, so it is possible for the aquatic stable isotope
signal to persist in some insects over their life span, which in turn affects the isotope
signal of any organisms that feed on them.
Body size and longevity can influence stable isotope signals because of the effect of
tissue turnover rate; longer-lived and larger animals tend to have more enriched signals
83
because the tissue turnover rate is usually slower than it is for smaller short-lived
organisms and metabolic activity simply continues to cause enrichment of the heavier
isotopes at the cellular level. The linear pattern of the scatter plot in Figure 3.5b
demonstrates that samples collected are a part of the same food web. The continuous
array of the plots rather then clumping into groups is probably because omnivory is
important in this riparian food web.
The wide range in stable isotope signatures of adult anurans at El Copé indicate that they
feed at different trophic levels. Among the species sampled there are at least 3 different
diets. The frog Centrolenella prosoblepon has the lowest δ15N signal of the frog species
sampled. This species is very small bodied (Savage 2002), with body size reaching a
maximum of 31mm which would necessarily affect the kinds of prey it is able to take,
and can partially explain its low δ15N signal. A single Centrolenella prosoblepon
individual was found in Fortuna over the course of the study and while there was a small
difference in δ15N signal between sites for the species, the δ13C signal of the sample from
Fortuna was more enriched in 13C than any of the samples collected in El Copé by at least
1.5‰ and up to 2.5‰. This supports the argument that δ13C signals can be a good
indicator of habitat. It is also interesting that the difference in δ13C signal of this frog
species in the riparian web is in the same direction as the differences between the
organisms in the stream food webs in El Copé and Fortuna. This suggests that the effects
of the factors which govern instream δ13C have been transferred into the riparian and
possibly terrestrial web.
84
The second diet (Figure 3.5) is represented by the five frogs with similar signals:
Colostethus flotator, C. inguinalis, Eleutherodactylus talamnacae, E. punctariolus and
Hyla columba. These species are small to moderate in size (Savage 2002) and appear to
be feeding similarly. The toad Bufo haematiticus by comparison is moderate to large in
size and its δ15N signal is similar to that of the snakes. Savage (2002) reported that this
toad has a diet which consists primarily of ants. Considering that the diet of ants is highly
variable, ranging from plant tissue to carcasses of vertebrates, if the diet of Bufo were to
include ants which consume carrion, it would be expected that the δ15N signal of the
toads would be enriched.
Among the snakes Sibon annulatus has the lowest trophic position. S. annulatus is a
small species reaching a maximum length of 557mm (Savage 2002) and feeds on snails
and slugs, which for the most part are herbivorous, making S. annulatus a secondary
consumer. Feeding at this comparatively low trophic level, compared with a snake that
feeds on insectivorous frogs, coupled with the small body size of S. annulatus would
result in the rather low δ15N signal of the species. The snakes Leptodeira septentrionalis,
Imantodes cenchoa and Oxybelis brevirostris are all larger snakes with lengths that can
exceed 1,000 mm and they all eat frogs, toads and lizards. The larger body size coupled
with the prey items of choice for these groups can explain the elevated δ15N signal.
In conclusion, some important differences in trophic structure have been observed
between the two sites. Apart from the known effects of tadpoles by bioturbation during
feeding (Flecker et al. 1999), as well as the effects of their feeding on the algal
85
community composition (Dickman 1968, Loman 2001, Ranvestel et al. 2004), the
tadpoles subsidize the stream food web through production of feces. The differences in
stable isotope signals of the basal resources and consumers are quite clear between El
Copé and Fortuna. The δ15N signal of the resources in El Copé show a strong recycled
signal compared with Fortuna in almost every case. The crabs, though living in the
stream, consume detritus of terrestrial origin, and with no stream predators, essentially
become a trophic dead end in the stream food web. The spiders contrastingly, live in the
riparian zone but appear to feed from the stream. Generally, the stream food web is
simple and linear when the tadpoles are present, but has become truncated and non-linear
in Fortuna where the tadpoles are absent.
The data strongly support the hypothesis that tadpole feces are a major subsidy in the
stream food web. An important part of confirming the influence of the tadpole feces in
the stream systems would be to carry out continued studies in El Copé. Periphyton
samples are already being taken monthly. Seasonal sampling (dry, early wet and wet
season) of the other components of the food web has not yet begun, but sampling of the
other basal resources as well as the invertebrates and fish can only help to better explain
the processes that are taking place in the food web as a result of the extirpation. If it were
only possible to take samples annually however, it would be recommended that they be
taken at same time each year to remove any confounding effects of differences in rainfall.
Follow up studies in El Copé will reveal interesting information about the mechanisms
involved and the length of time required for a site that has suffered recent extirpations to
equilibrate.
86
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Tables and Figures
Table 3.1 Average Physico-chemical data in streams: El Copé and Fortuna, Panamá from June 2003 to May 2005
Site Temperature
°C
DO
mg/L
pH Conductivity
mS
El Copé 21.4 6.53 8.21 0.03
Fortuna 18.4 7.00 8.27 0.01
Table 3.2 Nutrient Concentrations in streams in El Copé and Fortuna
NH4-N
mg/L
NO3-N
mg/L
PO4-P
mg/L
Total PO4-P
mg/L
El Cope Filtered 0.002 0.170 0.007 0.015
El Cope Unfiltered 0.001 0.143 0.006 0.016
Fortuna Filtered 0.005 0.130 0.006 0.009
Fortuna Unfiltered 0.003 0.120 0.007 0.020
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El Cope Scatter Plot - June '03 - Sep '04
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Fortuna Scatter Plot
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El Cope Scatter Plot - Post Decline (Feb '05)
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El Cope Scatter Plot - Post Decline (May'05)
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Figure 3.1 Scatter plots of all stable isotope data in Fortuna and pre and post decline El Copé from June 2003 to May 2005.
a b
c
d
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Scatter Plot of Leaf Pack Biofilm - El Cope Feb '05
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Scatter Plot of Leaf Pack Biofilm - Fortuna
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Scatter Plot of Leaf Pack Biofilm - El Cope May '05
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Figure 3.2 – Scatter plots of δ13C and δ15N values for leaf pack biofilm in Fortuna and post decline El Copé.
a b
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Summary El Cope - Pre-decline
δ13C
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δ15 Ν
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Leaf PackInvertsFishPeriphytonCrabFBOMFish fecesSestonTadpolesSnakesFrogs
Summary El Cope - Post-decline (Feb 05)
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10 FishInvertsCrabsShrimpLeaf PackFBOMLP BiofilmPeriphytonSestonSpiders
Summary El Cope - Post-decline (May 05)
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10LP BiofilmFishCrabInvertsLeaf PackFBOMSestonPeriphyton
Summary - Fortuna
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10InvertsFishFish fecesCrabFBOMLeaf PackPeriphytonSestonTadpoleFil AlgLP Biofilm
Figure 3.3 δ15N and δ13C of major groups in Fortuna and pre and post decline El Copé. Chart a: Leaf pack N = 45, Periphyton N = 37, FBOM N = 15, Seston N = 6,
Invertebrates, N = 391, Crabs N = 13, Tadpole N = 98, Fish N = 182, Snake N = 174, Frog N = 204. Chart b: Leaf pack N = 12, Periphyton N = 12, FBOM N = 3, Seston N = 2, Invertebrates, N = 38, Crabs N = 3, Fish N = 11, Shrimp N = 3 Spiders N = 7, Leaf
Pack Biofilm N = 12. Chart c: Leaf pack N = 13, Periphyton N = 12, FBOM N = 5, Seston N = 3, Invertebrates, N = 51, Crabs N = 7, Fish N = 22, Leaf Pack Biofilm, N =
12. Chart d: Leaf pack N = 60, Periphyton N = 33, FBOM N = 20, Seston N = 8, Invertebrates N = 388, Crabs N = 65, Tadpole N = 2, Fish N = 10.
a b
c d
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δ15N of selected resources in El Cope and Fortuna
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Peri LP Biofilm Hydro Perlidae Fish Crab
Resource
δ15N
Cope
Fortuna
Figure 3.4 δ15N signal of selected resources in El Copé and Fortuna. The resources chosen were present at both sites on all sampling occasions. El Copé: Periphyton N = 58, Leaf Pack Biofilm N = 24, Hydropsychidae N = 53, Perlidae N = 20, Fish N = 204, Crab N = 23. Fortuna: Periphyton N = 33, Leaf Pack Biofilm N = 16, Hydropsychidae N = 78,
Perlidae N = 57, Fish N = 10, Crab N = 65.
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Adult Frogs Snakes and Lizards
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-28 -27 -26 -25 -24 -23 -22 -21δ13C
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Bufo haem Centro prosop Colost f lot Colost ing Eleuth punctEleuth talam Hyla Colymb Norops lion Iman cench Oxy brevRhad verm Glass Frog (Fortuna) L sept S ann Dispas
Figure 3.5 Scatter and summary stable isotope plots for riparian food webs (Adult frogs, snakes and lizards) Bufo haematiticus N = 17, Eleutherodactylus talamancae N = 17,
Eleutherodactylus puntariolus N = 3, Centrolenella prosoblepon N = 3, Hyla colymbiphyllum N = 33, Colostethus flotator N = 3, Colostethus inguinalis N = 14,
Norops lionotus N = 3, Rhadicula vermiformis N = 3, Leptodeira septentrionalis N = 12, Imantodes cenchoa N = 15, Sibon annulatus N = 30, Oxybelis brevrirostris N = 99,
Dispas N = 15.
Scatter Plot Frogs Lizards and Snakes
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CHAPTER 4: The Effectiveness of IsoSource as a Tool for Elucidating Trophic Structure in Tropical Stream Food Webs
Abstract:
Stream food webs generally have multiple sources of organic matter as well as complex
trophic relationships. Stable isotope analysis has become an invaluable tool for
investigating trophic relationships in food webs and is especially powerful because it
integrates consumer diets over time. However, the mixing of resources in consumers’
diets often causes difficulty in interpreting trophic linkages, and the relative importance
of different dietary components. The IsoSource mixing model software developed by
Phillips and colleagues was designed to address the problem of multiple sources in food
webs and other stable isotope studies and was selected for use in this study as a good
candidate for a quantitative food web analysis. The current study is part of a larger
collaborative Tropical Amphibian Declines in Stream (TADS) project which is concerned
with the ecosystem effects of amphibian extirpation. The study site was in the uplands of
Panamá and was focused on quantitatively assessing the trophic dynamics in stream food
webs that have been differentially affected by the global amphibian extirpations. The
intent was to use IsoSource to quantitatively assess the food webs in the presence and
absence of the amphibians. However, key to successful application of the IsoSource
mixing model is a detailed knowledge of the food web, especially the fractionation factor
of the components of the food web. Unfortunately, many factors can affect fractionation
factor, even within the same food web. These factors include functional group, form of
nitrogen excretion and dietary balance among others. In this study, the tadpole species are
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used to demonstrate that even small changes in the ‘assigned’ fractionation factor can
significantly change the mixing model output and therefore interpretation of trophic
relationships. In light of this, the IsoSource mixing model is not useful for pioneer trophic
studies where there is little prior knowledge of the food web.
Introduction: In most aquatic systems, there are multiple sources of organic matter entering the food
web, because the base of the food web is very diverse (Benstead et al. 2006, Hamilton et
al. 2004). Stable isotopes analysis (SIA) can be more useful for providing information
about resource utilization at different trophic levels, because one of the principal
strengths of SIA is that it measures assimilation of resources that has been integrated over
the time scale of tissue turnover (Kling et al. 1992, Hecky and Hesslein 1995, Vander
Zanden and Rasmussen 1999, March and Pringle 2003). Despite this important
advantage, SIA has as an intrinsic shortcoming when there are multiple potential sources.
The need to overcome this difficulty inspired the development of mixing models, which
are computer software programs that are designed to calculate the relative contributions
of multiple sources to a consumer.
Mixing models are not without their own inadequacies. They are often limited in
presenting a unique solution based on the number of isotopes that are analyzed. Data for
n isotopes are needed to give a solution for n+1 resources (Phillips and Gregg 2003) and
in most food web studies the stable isotope ratios of two elements are used. This often
limited the researcher to include only three potential resources, and thus forced the
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investigator to choose those resources that had been assumed or shown to be important by
other studies (Benstead et al. 2006, Phillips and Gregg 2003). Such deliberate inclusions
and omissions have the potential to lead to false impressions about trophic links.
Dilemmas such as these prompted Phillips and Gregg (2003) to develop IsoSource, a
mixing model software which is available for public use at http://www.epa.gov/wed/
pages/models.htm. IsoSource is designed for those situations where n isotopes are
analyzed but there are > n+1 possible sources. The software uses the stable isotope data
to calculate the possible combinations of resource use that sum to 100% by user specified
increments. Next, the program describes the mixtures of resources that preserve mass
balance, within a user specified tolerance using linear mixing model equations.
The characteristics of the questions asked in this study seemed to indicate IsoSource as
the ideal tool to unravel the complicated issue of ‘who is eating how much of whom’ in
tropical montane streams. There have been widespread declines of anuran populations
associated with streams in highland regions of the neotropics for the past few decades.
The tadpoles are known functionally dominant herbivores in streams (Dickman 1968)
and so their extirpation is expected to have large effects on ecosystem characteristics.
This study is part of the larger collaborative Tropical Amphibian Declines in Streams
(TADS) project which is looking at the ecosystem effects of the extirpation, such as
differences in secondary production, as well as algal composition and standing crop, and
is focused particularly in the changes in trophic structure as a result of the extirpations.
The study was carried out in the highlands of Panamá and is focused on determining what
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the food resources of the stream dwelling tadpole species are as well as the relative
proportions of each resource in the tadpole diets.
The IsoSource mixing model has been described as a very timely addition to the growing
range of statistical techniques used for analyzing isotope data (Benstead et al. 2006),
since it can provide narrow ranges of source contributions. The mixing model is also
effective at showing that a resource is not important in a food web. IsoSource was
therefore chosen for use in the current study to elucidate the trophic linkages in the
stream food web being studied, in particular the food resources of the tadpoles.
Methods:
Basal resources (leaf packs, leaf pack biofilm, periphyton and FBOM) were collected,
prepared for SIA and analyzed as detailed in Chapter 3. IsoSource was then used to
evaluate the relative contributions of the basal resources to the mixed signal observed in
the tadpoles per Phillips and Gregg (2003). The source increment was set at 1% and
tolerance was set at ± 0.1%. Stable isotope data were run through the models for the
individual tadpole species as well as averaged for the tadpole group as a whole.
Fractionation factors of 1.8‰, 2.0‰, 2.8‰ and 3.4‰ were used when running the data
through the model.
Data are emerging in the literature that suggest that fractionation in the tropics ranges
between 1.8 and 2.0‰ (Kilham and Pringle 2000), so these values were used to run the
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data through the model. The 2.8‰ fractionation value was selected because Vanderklift
and Ponsard (2003) reported that fractionation among vertebrates in controlled laboratory
studies is about 2.8‰ compared with 2.0‰ in invertebrates and a fractionation factor of
3.4‰ was also used because classically 15N fractionation has been reported to be 3.4‰
(DeNiro and Epstein 1981, Post et al. 2000, Vander Zanden and Rasmussen 2001).
Results and Discussion:
Feasible resource utilization combinations were only found for two of the five tadpole
species analyzed, namely Colostethus inguinalis and Rana warszewitschii (Table 4.1). In
the case of C. inguinalis, feasible solutions were found when fractionation factors of
1.8‰ and 2.0‰ were used. However there were noticeable differences between the
utilization ranges of the resources for these fractionation values. At a fractionation of
1.8‰ the range in leaf pack biofilm usage was from 25 to 72% (Figure 4.1a). Possible
utilization of periphyton ranged from 0 to 18%, while the range for leaf packs was from 0
to 32%, and the range in possible contribution of FBOM was very broad, from 0 to 72%.
A change in fractionation factor of only 0.2‰ in the case of C. inguinalis resulted in a
very different output from the software with the feasible diet proportions being better
constrained (Figure 4.1b). In the case of leaf pack biofilm, the utilization range by C.
inguinalis ranged from 43 to 67% and leaf pack utilization from 17 to 35% (Figure 4.1b).
The possible range in FBOM usage is from 0 to 38% and periphyton seems to not be an
important part of the diet because its utilization range is 0 to 6 %.
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In the case of R. warszewitschii, possible solutions were found for 3 different
fractionation values (Table 4.1). When the fractionation factor was 1.8‰, possible ranges
for leaf pack utilization were between 0 and 21% while the periphyton seemed to be very
important ranging in utilization from 52 to 87% (Figure 4.2a). Leaf pack biofilm did not
seem to be an important player at this fractionation level, as the range in utilization varied
from 0 to 18% and although the range for FBOM is from 0 to 41%, this resource did not
appear to be very important since the proportions which occurred more frequently were at
the lower end of the range.
When the fractionation factor was changed to 2.0‰, there were small changes in the
possible resource use proportions, but the relative importance of the resources were the
same (Figure 4.2b). Periphyton ranged from 39 to 73% and leaf packs from 7 to 30%.
The FBOM still had a wide range, from 0 to 47%, once again with the smaller
proportions having higher frequencies. The leaf pack biofilm contribution was once again
close to zero with the range being from 0 to 22%
A fractionation factor of 2.8‰ gives a very different result (Figure 4.2c). The possible
contribution of FBOM now ranges from 0 to 63% and contributions from leaf pack
biofilm ranging from 0 to 33%. The significant difference from the previous two cases is
in the relative importance of periphyton and leaf packs. The leaf pack involvement ranges
from 33 to 66% while the periphyton contribution ranges from 0 to 35% (Figure 4.2).
Therefore, when the fractionation factor is changed to 2.8‰, the relative importance of
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periphyton compared with leaf packs is reversed. The fractionation factors chosen are
supported by recent and classic literature, 1.8‰ – 2.0‰ (Kilham and Pringle 2000),
2.8‰ (Vanderklift and Ponnsard 2003) and 3.4‰ (Minagawa and Wada 1984), and yet in
both species that had feasible solutions, small changes in the fractionation factor resulted
in significant differences in interpretation of food web linkages.
It is also noteworthy that IsoSource was unable to find feasible solutions for three of the
tadpole species. The tadpoles have already been shown to be functionally dominant
herbivores (Dickman 1968), therefore it is reasonable to expect that with the range of
fractionation factors used, there should have been feasible solutions. When using
IsoSource, a resource polygon is drawn using the isotope values of the resources. The
isotope signatures are corrected by the fractionation factor; the fractionation factor is
subtracted from the value of the consumer, or alternately added to the resources while the
consumer value remains unchanged. In the current study, the fractionation factors were
subtracted from the consumer signature. After the correction, the isotope value of the
consumer must fall within the boundaries of the resource polygon in order for IsoSource
to compute a solution (Phillips and Gregg 2003).
However, if the mixing polygon of possible sources is narrow, IsoSource may have
difficulty computing the solutions (Phillips and Gregg 2003), since the mixture may not
fall inside the polygon once it is set up. Figure 4.3 demonstrates that the mixing polygon
for the resources in this study is in fact narrow. In order for there to be well constrained
feasible solutions, the mixing polygon has to be broad, with the mixture signal falling
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close to a corner. So for food webs, this means that there needs to be a wide range in the
isotope signals of the potential sources. In stream food webs, there can be a range in the
δ13C signal since terrestrial and aquatic signals are generally different. At the base of the
food web, however, there is not expected to be large range in the δ15N signal, therefore, it
is very probable that the polygon will not be very broad. This may ultimately lead to
IsoSource being unable to compute feasible resource combinations.
Ideally the consumer needs to fall close to one corner of the mixing polygon and this
requirement can also be problematic. In the current study, the consumers of interest were
tadpoles, which are known keystone herbivores of periphyton (Dickman 1968).
Therefore, providing that the correct fractionation factor is used, the tadpoles would be
expected to occupy a position close to the periphyton corner of the polygon. This did
occur for R. warszewitschii for two of the four fractionation factors used (Figure 4.3).
However, generally the other stream organisms are not keystone or functionally dominant
species, and especially in the case of the predatory insects, they can be largely
opportunistic and may consume equal proportions of various prey species. Since the
software ideally requires the consumer to be eating largely disproportionate amounts of
the resources to give well constrained solutions, this is another reason that IsoSource may
not be appropriate for tropical food web studies.
The results also beg the question of whether 3.4‰ is an appropriate fractionation factor
to use in the tropics. It is now coming to the forefront in the literature that 3.4‰ may not
be the actual trophic fractionation factor in the tropics (Kilham and Pringle 2000), and the
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results of the current study join in supporting this trend. No feasible solutions were found
in any case when a fractionation factor of 3.4‰ was used even in those cases where other
fractionation factors yielded feasible combinations of resource utilization.
The requirement for knowing the fractionation factor to a high degree of certainty is a
fatal flaw as it pertains to use of IsoSource in tropical stream food web studies. 15N
fractionation has historically been considered to be 3.4‰ but Minawaga and Wada
(1984) actually showed a range in trophic enrichment of 15N fractionation from 1.3‰ to
5.3‰ and many factors can influence 15N fractionation. Taxon is an important criterion
that can affect trophic fractionation as Vanderklift and Ponsard (2003) showed that
fractionation for invertebrates was 2.08‰ but 2.88‰ for vertebrates. Functional group is
another factor that can affect fractionation, as laboratory studies showed that within the
same group (example, invertebrates vs. vertebrates) predatory organisms tend to
fractionate more 15N than their non-predator counterparts (Vanderklift and Ponsard
2003). Different organisms within the same functional group can also have different
fractionation factors. Jardine et al. (2005) showed from field studies that 15N fractionation
of Perlidae (Stonefly) was greater than for Rhyacophilidae (Caddisfly) even though both
families are predatory invertebrates (∆δ15N was calculated between the animal tissue and
gut contents).
There can also be different fractionation factors in different body tissues and Vanderklift
and Ponsard (2003) showed that muscle tissue had the lowest fractionation among birds
while kidney tissue had the lowest fractionation among mammal tissues investigated.
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While this can be controlled for by the researcher, it will necessarily require a change in
how samples are collected and prepared since small animals, like insects are usually
ground whole (and may even be combined), but for larger animals, a portion of muscle
tissue is generally used.
The diet of the consumer can affect nitrogen fractionation. Vanderklift and Ponsard
(2003) showed that carnivores, herbivores and omnivores had trophic fractionation
factors of 2.69‰, 2.98‰ and 2.56‰ respectively, but the fractionation factor of
detritivores was significantly lower at 0.53‰. The quality of the diet is also very
important. Adams and Sterner (2000) showed a marked increase in 15N fractionation of
Daphnia magna with C:N ratio of its diet, i.e. trophic fractionation of 15N was higher
when the food quality was poorer. Contrastingly, McCutchan et al. (2003) showed in
laboratory studies that trophic fractionation had a mean of 1.4‰ for consumers that were
raised on invertebrate diets, compared with a fractionation of 3.3‰ for consumers raised
on other high-protein diets, but the consumers considered in the McCutchan (2003) study
were butterflies and fish.
These variations in fractionation factors are compounded by the fact that the biochemical
form of nitrogen excretion can also have significant effects on δ15N enrichment.
Vanderklift and Ponsard (2003) showed that trophic fractionation in laboratory studies
among organisms that excrete urea was 2.73‰, while it was 2.00‰, for animals that
excreted ammonia. The study also demonstrated that among the ammonotelic organisms,
vertebrates fractionate more 15N than invertebrates. As a consequence of the mode of
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excretion, organisms will have differing trophic fractionation depending on their habitat
(Vanderklift and Ponsard 2003). Aquatic animals will exhibit lower fractionation than
terrestrial animals, because the primary mode of excretion in the aquatic habitat is
ammonia.
Variation in fractionation values in resource signatures and among individuals
complicates interpretation of trophic interactions (Mantel et al. 2004). For the researcher,
attempting to keep track of the various fractionation factors of all the players based on
taxon, functional group, nitrogen excretion and diet would be a formidable task, though
quite necessary, since when using mixing models, the outcomes can be very sensitive to
small changes in fractionation factors. This study demonstrates that using an incorrect
fractionation value can completely change the computed solution set and consequently
the interpretation of the trophic relationships. ‘The weakest link in the application of
mixing models to a dietary reconstruction relates to the estimation of appropriate
fractionation values’ (Phillips and Koch 2002).
In conclusion, IsoSource is a timely development, and is probably very useful in other
types of stable isotopes studies. However, as it pertains to food web analyses, unless there
is significant prior knowledge about the system being studied, supported preferably by
laboratory studies to confirm actual fractionation factors of focal species, IsoSource can
not provide definitive information. The major disadvantage with the software is that it
requires the user to already have detailed knowledge about the food web, so it is not
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useful in pioneer trophic studies when initial food web investigations are being carried
out in an attempt to uncover the path of energy and material transfer in a food web.
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References: Adams T. S., Sterner R.W. 2000. The Effect of Dietary Nitrogen Content on Trophic Level 15N Enrichment. Limnology and Oceanography. 45(3) : 601 – 607 Benstead, J. P., March, J.G., Fry, B., Ewel, K., Pringle, C.M. 2006. Testing Isosource: Stable Isotope Analysis of a Tropical Fishery with Diverse Organic Matter Sources. Ecology. 87 : 326-333 Dickman, M. 1968. The Effect of Grazing by Tadpoles on the Structure of a Periphyton Community. Ecology. 49 : 1188-1190. Hamilton, S.K., Tank, J.L., Raikow, D.F., Siler, E.R. Dorn, N.J., Leonard, N.E. 2004. The Role of Instream Vs Allochthonous N in Stream Food Webs: Modeling the Results of an Isotope Addition Experiment. Journal of the North American Bentholological Society. 23(3) : 429 – 448. Hecky, R., Hesslein, R. 1995. Contributions of benthic algae to lake food webs as revealed by stable isotope analysis. Journal of the North American Benthological Society. 14 : 631-653. Kilham, S.S., Pringle, C.M. 2000. Food webs in two neotropical stream systems as revealed by stable isotopes. Verhandlungen Internationale Verein Limnolgie 27 : 1768-1775. Kling, G., Fry, B., O’Brien, W. 1992. Stable isotopes and planktonic trophic structure in arctic lakes. Ecology 73 : 561-566. Jardine, T.D., Curry, R. A., Heard, K.S., Cunjak, R.A. 2005. High Fidelity: Isotopic Relationship between Stream Invertebrates and their Gut Contents. Journal of the North American Bentholological Society. 24(2) 290 - 299 McCutchan, J.H. Jr., Lewis, W.M. Jr., Kendall, C., McGrath, C. 2003. Variation in Trophic Shift for Stable Isotope Ratios of Carbon, Nitrogen and Sulfur. Oikos. 102: 378 – 390. Mantel, S.K., Salas, M., Dudgeon, D. 2004. Foodweb Structure in a Tropical Asian Forest Stream. Journal of the North American Bentholological Society.23(4) : 728 – 755.
March, JG., Pringle, C.M. 2003. Food Web Structure and Basal Resource Utilization Along a Tropical Island Stream Continuum, Puerto Rico. Biotropica. 35(1) : 84 - 93
Marchant, R., Metzeling, L. Graesser, A., Suter, P. 1985. The organization of macroinvertebrate communities in the major tributaries of the LaTrobe River, Victoria, Australia. Freshwater Biology. 15 : 315-332.
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Minagawa, M., Wada, E. 1984. Stepwise enrichment of 15N along food chains: Further evidence and the relation between δ15N and animal age. Geochimica et Cosmochimica Acta. 48 : 1135-1140. Phillips, D.L., Koch, P.L. 2002. Incorporating Concentration Dependence in Stable Isotope Mixing Models. Oecologia. 130 : 114 – 125.
Phillips, D.L. Gregg, J.W. 2003. Source Partitioning Using Stable Isotopes: Coping With Too Many Sources. Oecologia. 136 : 261 – 269.
Vander Zanden, M.J.V., Rasmussen, J.B. 1999. Primary consumer δ13C and δ 15N and the trophic position of aquatic consumers. Ecology, 80 : 1395-1404. Vanderklift, M.A., Ponsard, S. 2003. Sources of Variation in Consumer-diet δ15N enrichment: a Meta-analysis. Oecologia. 136 : 169 - 182
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Tables and Figures
Table 4.1 Table of tadpole species with measured and adjusted stable isotope values and presence/absence of feasible solutions
Tadpole Species δ13C adjusted δ13C δ15N
15N fractionation factor
adjusted δ15N solutions
Centrolenella sp -25.17 -26.17 4.63 1.80 2.83 No 2.00 2.63 No 2.80 1.83 No 3.40 1.23 No Colostethus flotator -26.96 -27.96 5.45 1.80 3.65 No 2.00 3.45 No 2.80 2.65 No 3.40 2.05 No Colostethus inguinalis -27.59 -28.59 5.09 1.80 3.29 Yes 2.00 3.09 Yes 2.80 2.29 No 3.40 1.69 No Hyla colymba -27.02 -28.02 5.49 1.80 3.69 No 2.00 3.49 No 2.80 2.69 No 3.40 2.09 No Rana warszewitschii -28.41 -29.41 5.14 1.80 3.34 Yes 2.00 3.14 Yes 2.80 2.34 Yes 3.40 1.74 No Combined tadpoles -27.17 -28.17 5.17 1.80 3.37 No 2.00 3.17 No 2.80 2.37 No 3.40 1.77 No
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Figure 4.1a- Feasible resource utilization of Colostethus inguinalis and the resources leaf pack, leaf pack biofilm, periphyton and FBOM: Fractionation = 1.8‰
SOURCE: FBOM SOURCE: LEAF PACK
SOURCE: PERIPHYTON SOURCE: LEAF PACK BIOFILM
112
Figure 4.1b- Feasible resource utilization of Colostethus inguinalis and the resources leaf pack, leaf pack biofilm, periphyton and FBOM: Fractionation = 2.0‰
SOURCE: LEAF PACK BIOFILM
SOURCE: FBOM SOURCE: LEAF PACK
SOURCE: PERIPHYTON
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Figure 4.2a- Feasible resource utilization of Rana warszewitschii and the resources leaf pack, leaf pack biofilm, periphyton and FBOM: Fractionation = 1.8‰
SOURCE: FBOM SOURCE: LEAF PACK
SOURCE: PERIPHYTON SOURCE: LEAF PACK BIOFILM
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Figure 4.2b- Feasible resource utilization of Rana warszewitschii and the resources leaf pack, leaf pack biofilm, periphyton and FBOM: Fractionation = 2.0‰
SOURCE: LEAF PACK BIOFILM
SOURCE: FBOM SOURCE: LEAF PACK
SOURCE: PERIPHYTON
115
Figure 4.2c- Feasible resource utilization of Rana warszewitschii and the resources leaf pack, leaf pack biofilm, periphyton and FBOM: Fractionation = 2.8‰
SOURCE: FBOM SOURCE: LEAF PACK
SOURCE: LEAF PACK BIOFILMSOURCE: PERIPHYTON
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Figure 4.3 - Mixing polygons for the tadpoles (Colostethus inguinalis and Rana warszewitschii) and resources (leaf packs, leaf pack biofilm, periphyton and FBOM). The
δ13C signatures of the tadpoles have been corrected by a factor of 1‰ and the δ15N signals have been corrected by 1.8‰, 2.0‰, 2.8‰ and 3.4‰.
Mixing Polygon - C. ing
0
2
4
6
-31 -30 -29 -28 -27
δ13C
δ15N
FBOMLP BiofilmPeriLPTad (corrected)
Mixing Polygon - R war
0
2
4
6
-31 -30 -29 -28 -27
δ13C
δ15N
FBOMLP BiofilmPeriLPTad (corrected)
117
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Appendices
Table A.1 Stable Isotope Raw Data Stable Isotope Data El Copé - June ‘03
LOCATION SAMPLE NUMBER Sample
Wt. Total Total δ13 C δ15 N (mg) %C %N vs. PDB vs. Air
Riffle LIBELULLIDAE 2 1.510 44.42 11.05 -26.81 4.70
Riffle LIBELULLIDAE 1 1.363 46.66 10.69 -27.62 5.68
Pool BR II 1 1.778 39.13 10.38 -25.64 6.70
Pool BR II 1 1.677 40.92 10.68 -25.68 7.17
Pool BR II-D 1 1.252 42.54 10.79 -26.00 7.37
Riffle BR II 1 1.609 41.66 10.33 -26.28 7.27
Riffle BR II-D 1 2.248 39.52 9.76 -26.36 7.17
Pool BR III 1 1.197 36.49 8.83 -25.46 8.31
Pool BR III-D 1 1.403 36.59 8.87 -25.62 8.27
Pool BR III 7 1.924 45.03 11.79 -25.91 7.24
Riffle BR III 1 1.417 38.23 9.64 -25.89 8.09
Riffle BR III 3 2.280 41.75 10.66 -26.13 6.93
Riffle BR III-D 1 1.700 41.93 10.98 -26.01 7.01
Riffle BR III 1 1.995 39.36 10.09 -25.79 8.02
Pool BR IV 3 2.184 43.81 10.75 -26.48 7.18
Pool BR IV-D 1 3.042 45.36 11.21 -26.83 ALD
Pool BR V 2 3.376 44.63 11.34 -26.04 ALD
Riffle BR V 1 1.969 39.22 10.50 -25.65 7.20
Riffle BR V 1 3.132 41.09 9.91 -26.31 7.80
Pool BR YOLK 1 1.576 42.98 10.97 -26.17 6.88
Riffle BR YOLK 1 1.447 43.32 10.71 -25.50 7.80
Riffle CALOPTERYGIDAE 1 1.631 44.65 9.88 -26.50 1.74
Riffle CALOPTERYGIDAE 1 1.434 41.27 9.85 -27.22 4.22
Riffle CALOPTERYGIDAE 2 1.358 44.87 11.97 -27.38 3.17
Riffle CALOPTERYGIDAE 1 1.145 45.30 12.01 -27.47 3.39
Riffle CALOPTERYGIDAE 1 2.044 45.43 11.09 -29.20 2.64
Riffle CALOPTERYGIDAE 1 1.257 46.18 11.36 -26.17 2.09
Pool CRAB 1.280 23.01 4.01 -23.69 4.54
Riffle CRAB I 1 1.259 28.40 4.37 -25.97 4.76
Riffle CRAB I 2 2.406 29.97 5.24 -26.08 5.05
Riffle CRAB IV 1 3.514 21.87 3.69 -24.16 3.71
Riffle CRAB IV-D 1 2.171 25.59 4.77 -24.72 3.94
Riffle ELMIDAE 6 1.796 45.87 10.91 -26.18 2.54
Riffle ELMIDAE 1 1.173 44.16 9.31 -26.96 3.32
Pool FBOM n/a filter 0.00 0.00 -25.92 8.00
Pool FISH FECES n/a filter 0.00 0.00 -26.07 6.01
Pool FISH FECES n/a filter 0.00 0.00 -26.97 5.94
Pool FISH FECES n/a filter 0.00 0.00 -26.46 6.46
Pool FISH FECES n/a filter 0.00 0.00 -27.09 3.44
Riffle FISH FECES n/a filter 0.00 0.00 -26.02 6.98
Riffle FISH FECES n/a filter 0.00 0.00 -26.98 5.14
128
LOCATION SAMPLE NUMBER Sample
Wt. Total Total δ13 C δ15 N (mg) %C %N vs. PDB vs. Air
Riffle FISH FECES n/a filter 0.00 0.00 -28.17 6.02
Pool GYRINIDAE 1 1.280 52.31 9.73 -29.58 5.20
Pool GYRINIDAE 2 1.411 50.82 9.69 -27.41 5.64
Pool GYRINIDAE-D 1 1.326 50.82 9.81 -27.48 5.48
Riffle GYRINIDAE 1 1.735 44.56 10.72 -25.86 1.45
Riffle HYDROPSYCHIDAE 1 1.426 46.37 10.49 -27.09 3.60
Riffle HYDROPSYCHIDAE 3 1.489 43.90 8.78 -28.01 3.61
Riffle HYDROPSYCHIDAE 2 1.223 46.14 9.02 -28.52 3.46
Riffle HYDROPSYCHIDAE 1 1.335 44.61 8.64 -28.14 3.52
Riffle HYDROPSYCHIDAE-D 1 1.347 48.22 7.79 -28.85 3.73
Riffle HYDROPSYCHIDAE 1 1.223 44.10 8.98 -28.07 3.53
Pool L.P. n/a 3.447 44.61 1.61 -30.13 1.05
Pool L.P.-D n/a 2.859 43.97 1.53 -29.28 0.78
Pool L.P. n/a 4.136 46.68 1.52 -30.07 1.58
Pool L.P-D n/a 2.494 46.59 1.51 -29.84 1.42
Riffle L.P. n/a 2.351 28.40 1.09 -29.00 2.03
Riffle L.P.-D n/a 3.129 32.62 1.29 -29.58 1.91
Riffle L.P. n/a 2.943 47.37 1.54 -30.64 0.18
Riffle L.P.-D n/a 2.923 47.06 1.39 -30.28 0.28
Riffle L.P. n/a 4.717 46.52 1.88 ALD 0.78
Riffle L.P. n/a 3.516 46.22 1.81 -28.85 1.86
Riffle L.P. n/a 2.951 44.94 1.86 -30.24 1.06
Riffle L.P. n/a 3.845 44.78 1.59 -29.48 1.05
Pool GERRIDAE 17 1.358 47.74 10.51 -26.78 5.03
Riffle NAUCORIDAE 1 1.231 48.79 10.41 -30.77 2.58
Riffle NAUCORIDAE 1 1.264 46.40 10.10 -28.77 2.96
Riffle NAUCORIDAE-D 1 1.110 48.03 10.32 -29.16 3.41
Riffle OLIGOCHAETA 1 1.659 30.53 6.44 -26.11 4.06
Pool PERIPHYTON n/a filter 0.00 0.00 -28.60 5.32
Pool PERIPHYTON n/a filter 0.00 0.00 -30.50 5.26
Pool PERIPHYTON n/a filter 0.00 0.00 -28.61 4.20
Riffle PERIPHYTON n/a filter 0.00 0.00 -30.91 2.91
Riffle PERIPHYTON-D n/a filter 0.00 0.00 -30.88 2.61
Riffle PERIPHYTON n/a filter 0.00 0.00 -28.43 3.89
Riffle PERIPHYTON n/a filter 0.00 0.00 -29.92 2.69
Riffle PERIPHYTON n/a filter 0.00 0.00 -30.27 2.19
Riffle PERIPHYTON n/a filter 0.00 0.00 -29.50 2.71
Riffle PERIPHYTON n/a filter 0.00 0.00 -26.83 2.84
Riffle PERLIDAE 1 1.332 46.62 11.16 -26.94 4.86
Riffle PERLIDAE 1 1.348 48.62 11.07 -27.88 4.44
Riffle PTYLODACTYLIDAE 1 1.486 42.18 9.48 -25.81 4.44
Riffle SESTON <98 n/a filter 0.00 0.00 -22.34 -1.86
Riffle SESTON >250 n/a filter 0.00 0.00 -13.31 -0.60
Riffle SESTON >754 n/a filter 0.00 BLD -52.95
Riffle SESTON >98 n/a filter 0.00 0.00 -26.32 4.60
Pool BR II 2 2.247 44.25 11.64 -26.28 6.30
129
LOCATION SAMPLE NUMBER Sample
Wt. Total Total δ13 C δ15 N (mg) %C %N vs. PDB vs. Air
Pool BR II-D 1.552 40.44 9.98 -26.36 6.61
Pool BR III 1 1.494 41.69 11.28 -26.05 7.51
Pool BR IV 2 1.131 38.88 9.24 -26.49 7.71
Pool BR V 1 1.563 44.74 11.49 -25.94 7.93
Pool VELIIDAE 8 1.342 50.97 10.88 -27.52 3.83
Pool VFBOM P1 n/a 32.480 4.11 0.32 -29.13 0.54
Pool VFBOM R1 n/a filter 0.00 0.00 -27.57 9.61
Pool VFBOM R1-D n/a filter 0.00 0.00 -33.39 3.33
Riparian WHIP SCORPION 1 1.795 48.06 11.98 -25.65 6.68
Riparian WHIP SCORPION-D 1 2.044 48.93 11.48 -26.10 6.55
riparian WHIP SCORPION 1 1.351 50.67 10.94 -27.59 5.34
130
Stable Isotope Data – El Copé September ‘03
LOCATION SAMPLE NUMBER Sample
Wt. Total Total δ13 C δ15N (mg) %C %N vs. PDB vs. Air
Riffle LIBELLULIDAE* 1 1.162 47.44 10.90 -31.17 1.76 Riffle LIBELLULIDAE* 1 1.111 44.43 11.51 -29.64 3.83 Riffle LIBELLULIDAE* 1 1.585 45.94 13.16 -27.31 2.46 Riffle Elmidae 3 1.087 45.41 9.71 -26.39 4.49 Riffle Elmidae 3 1.872 34.93 8.92 -25.46 6.35 Riffle Elmidae* 1 1.481 35.17 7.18 -26.44 5.37 Riffle Gyrinidae 2 1.788 52.80 9.92 -27.54 4.06 Riffle NAUCORIDAE 2* 1 2.269 50.56 12.41 -29.70 2.70 Riffle NAUCORIDAE 2* 1 1.310 48.55 11.54 -29.59 3.02 Riffle Hydropshychidae* 2 1.072 43.96 9.37 -28.66 2.98 Riffle Hydropshychidae* 13 1.564 47.02 7.23 -29.33 3.21 Riffle LP n/a 2.668 36.85 1.40 -30.78 0.88 Riffle LP-dupe n/a 2.562 38.07 1.35 -30.64 0.71 Riffle LP n/a 2.802 45.10 1.90 -28.99 0.35 Riffle LP n/a 2.432 45.12 1.62 -30.72 1.43 Riffle LP n/a 2.605 40.44 1.68 -30.27 0.09 Riffle LP n/a 2.219 48.92 1.52 -29.81 -0.54 Riffle LP-dupe n/a 2.150 49.18 1.65 -29.77 -0.67 Riffle LP n/a 2.706 47.95 1.65 -29.81 -0.61 Riffle Naucoridae 1 2.307 50.93 12.25 -26.84 3.11 Riffle Naucoridae-dupe 1 2.040 50.26 12.16 -27.12 2.77 Riffle Perlidae* 2 1.335 47.31 12.50 -27.68 3.84 Riffle BR I 3 1.496 45.40 11.83 -26.44 7.74 Riffle BR II 5 1.631 43.18 9.80 -26.56 6.25 Riffle BR II 8 1.056 42.62 10.41 -26.45 7.27 Riffle BR II 2 1.487 46.10 11.09 -26.67 6.16 Riffle BR II-dupe 2 1.219 49.31 10.05 -28.04 6.89 Riffle BR II 2 1.501 33.36 8.17 -26.24 6.82 Riffle BR II 2 1.276 40.21 9.55 -26.31 6.80 Riffle BR II 1 1.405 42.16 10.98 -26.45 7.32 Riffle BR II-dupe 1 1.469 42.17 11.26 -26.09 7.27 Riffle BR III 2 2.379 41.23 10.76 -26.35 5.73 Riffle BR III 1 2.252 43.37 11.99 -26.16 7.27 Riffle BR III 1 1.468 34.77 8.46 -25.35 7.41 Riffle BR III 1 1.255 42.77 11.62 -25.99 7.49 Riffle BR V 1 3.315 40.13 12.36 -25.43 7.96 Riffle Veliidae* 2 1.191 54.04 10.25 -27.54 4.94 Riffle Veliidae* 1 1.019 51.49 12.12 -24.83 5.41
131
Stable Isotope Data El Copé January ‘04
NUMBER Sample Wt. Total %C Total %N δ13C δ15N (mg) vs. PDB vs. Air Riffle LIBELLULIDAE 2 1.562 46.83 11.72 -27.08 3.80 Riffle LIBELLULIDAE 1 1.508 46.23 11.52 -28.99 3.73 Riffle LIBELLULIDAE-dupe 1 1.091 46.50 11.07 -29.05 4.15 Riffle PHILOPOTAMIDAE 1 1.296 36.78 8.14 -26.37 5.32 Riffle PHILOPOTAMIDAE 1 0.777 41.20 9.45 -26.35 5.16 Riffle ADULT COL 1 1.704 46.41 11.66 -26.30 1.59 Riffle Crab II 2 1.859 24.63 4.24 -24.67 4.74 Riffle Ephemeroptera 1 0.326 45.35 6.57 -28.20 0.16 Riffle Ephemeroptera 1 0.731 51.10 11.46 -30.68 3.80 Pool FBOM n/a n/a n/a n/a -29.75 2.58 Pool FBOM n/a n/a n/a n/a -28.84 3.05 Pool FBOM n/a n/a n/a n/a -29.28 0.84 Pool FBOM n/a n/a n/a n/a -29.69 2.21 Pool FBOM n/a n/a n/a n/a -29.33 2.48 Pool FBOM-dupe n/a n/a n/a n/a -29.25 2.69 Pool BR II 5 1.650 45.09 10.97 -26.46 6.76 Pool Gyrinidae 1 1.220 50.15 11.18 -26.77 4.99
Riffle Hydropsychidae 1 0.367 45.04 9.77 -27.74 4.12 Pool LP n/a 2.635 45.21 2.37 -31.67 1.29 Pool LP-dupe n/a 3.134 45.59 1.97 -30.27 1.26 Pool LP n/a 2.486 35.37 1.26 -30.19 2.01 Pool LP n/a 1.856 48.87 1.56 -29.16 0.87 Pool LP n/a 2.850 44.26 1.77 -31.40 1.43 Riffle LP n/a 2.874 46.09 2.37 -31.59 1.22 Riffle LP-dupe n/a 2.689 45.12 2.17 -31.23 1.08 Riffle LP n/a 2.401 48.93 1.41 -29.07 1.80 Riffle LP n/a 2.557 44.85 1.96 -30.57 0.69 Riffle LP n/a 2.983 47.86 2.17 -30.04 0.83 Riffle LP n/a 2.687 47.39 2.19 -29.25 1.80 Riffle LP-dupe n/a 3.031 48.30 2.33 -29.75 1.71 Riffle LP n/a 2.642 44.13 1.87 -30.78 1.99
Pool GERRIDAE 1 0.557 50.39 12.48 -26.61 5.60
Riffle GERRIDAE 1 1.218 51.80 10.84 -27.23 6.28
Riparian Moss n/a 3.220 25.85 1.46 -27.81 -0.09
Riparian Moss n/a 3.315 20.52 0.94 -28.86 1.33
Riparian Moss-dupe n/a 3.851 16.05 0.81 -28.82 2.14
Riparian Moss n/a 2.659 32.61 1.83 -29.76 1.54
Riparian Moss n/a 1.456 57.55 3.12 -30.51 0.82
Riparian Moss n/a 2.959 36.17 2.37 -30.13 1.36
Riparian Moss-dupe n/a 3.291 36.49 2.28 -30.30 1.41
Riparian Moss n/a 1.913 40.16 2.37 -30.50 1.76 Pool Periphyton n/a filter n/a n/a -29.48 3.00 Pool Periphyton n/a filter filter filter -30.40 4.43 Pool Periphyton-dupe n/a filter filter filter -30.95 4.16
132
LOCATION SAMPLE NUMBER Sample Wt. Total %C Total %N δ13C δ15N (mg) vs. PDB vs. Air Pool Periphyton n/a filter n/a n/a -29.29 3.69 Pool Periphyton n/a filter filter filter -28.14 6.95 Pool Periphyton n/a filter filter filter -32.16 4.57 Riffle Periphyton n/a filter n/a n/a -28.17 1.04 Riffle Periphyton n/a filter filter filter -28.66 4.72 Riffle Periphyton-dupe n/a filter filter filter -30.57 4.73 Riffle Periphyton n/a filter n/a n/a -28.95 1.93 Riffle Periphyton-dupe n/a filter n/a n/a -28.49 2.17 Riffle Periphyton n/a filter filter filter -29.40 4.82 Riffle Periphyton n/a filter filter filter -28.26 5.35 Riffle Periphyton n/a filter filter filter -27.66 6.34 Riffle Perlidae 1 1.343 50.26 11.42 -27.92 5.94 Pool Psephenidae 1 0.873 44.93 11.18 -30.34 3.55 Pool Psephenidae-dupe 1 1.153 46.94 11.20 -30.73 2.18
Riparian Riparian Leaves n/a 3.121 45.54 2.50 -33.09 1.81
Riparian Riparian Leaves n/a 2.512 36.30 1.99 -33.78 0.64
Riparian Riparian Leaves n/a 2.853 42.95 3.17 -35.32 2.10 Riffle Veliidae 6 1.252 51.00 11.42 -26.65 3.55 Riffle Veliidae 4 1.516 54.00 10.72 -27.86 3.84 Riffle Veliidae 1 0.693 51.51 10.58 -27.45 5.40
133
Stable Isotope Data El Copé May ‘04
LOCATION SAMPLE NUMBER Sample
Wt. Total Total δ13 C δ15 N (mg) %C %N vs. PDB vs. Air Riffle ADULT COL 1 1.422 49.10 10.30 -25.27 1.43 Riffle LIBELLULIDAE 1 1.217 46.05 10.29 -28.39 4.00 Riffle LIBELLULIDAE 2 1.442 45.27 11.70 -30.11 2.76 Riffle LIBELLULIDAE 2 1.421 44.35 11.68 -28.94 3.10 Riffle LIBELLULIDAE –D 2 2.394 43.48 11.42 -29.10 2.58 Riffle LIBELLULIDAE 1 1.473 44.73 12.05 -30.12 2.87 Riffle BAETIDAE 1 0.514 45.21 11.05 -27.74 4.55 Riffle BAETIDAE 1 1.497 47.51 11.13 -26.85 4.79 Riffle CRAB I 1 1.733 25.36 4.81 -28.32 4.56 Riffle CRAB I 1 2.039 30.11 5.70 -26.66 4.53 Riffle CRAB I 1 1.687 25.17 4.79 -25.23 4.92 Riffle CRAB II 1 1.405 29.21 5.91 -26.71 5.68 Riffle ELMIDAE 3 1.467 45.75 10.72 -25.98 2.90 Riffle ELMIDAE 5 1.566 44.80 10.17 -26.55 3.32 Riffle ELMIDAE-D 5 1.115 44.51 9.91 -26.68 3.43 Pool FBOM n/a 1.000 n/a 3.73 -29.18 2.14 Pool FBOM n/a Filter 76.50 4.93 -29.43 1.66 Pool FBOM n/a 1.000 n/a 3.21 -29.33 2.14 Pool FBOM n/a 1.000 n/a 4.03 -29.36 2.71 Pool FBOM n/a 1.000 n/a 7.20 -29.16 1.54 Pool FBOM-D n/a 1.000 n/a 3.15 -29.18 2.06 Pool FBOM n/a 1.000 n/a 4.48 -29.32 2.30 Pool GERIIDAE 1 1.377 49.23 10.72 -27.19 4.64 Riffle GERIIDAE 1 1.864 49.87 10.95 -27.31 6.50 Pool GERIIDAE 1 1.940 53.16 9.47 -28.52 4.54 Pool GYRINIDAE 2 2.648 53.94 9.28 -27.66 4.10 Pool GYRINIDAE-D 2 2.817 54.66 8.69 -27.60 4.58 Pool GYRINIDAE 2 2.172 49.70 10.53 -26.93 5.15 Pool GYRINIDAE 1 1.198 51.24 9.52 -27.62 4.62 Pool GYRINIDAE 1 1.715 50.42 10.15 -26.96 6.11 Riffle HYDROPSYCHIDAE 14 1.040 43.71 9.65 -27.89 3.41 Riffle HYDROPSYCHIDAE –D 14 1.651 45.23 9.64 -29.50 2.88 Riffle HYDROPSYCHIDAE 29 1.187 46.35 9.97 -28.64 4.10 Riffle HYDROPSYCHIDAE –D 29 2.259 46.94 10.61 -28.39 3.71 Riffle HYDROPSYCHIDAE 13 1.543 44.87 9.82 -28.23 3.06 Riffle HYDROPSYCHIDAE 5 1.151 45.11 9.45 -28.08 3.98 Riffle HYDROPSYCHIDAE 11 2.111 47.18 10.23 -27.56 3.67 Riffle HYDROPSYCHIDAE 6 1.493 47.12 9.94 -28.24 3.44 Pool L P n/a 2.266 43.59 1.29 -28.41 -0.54 Pool L P n/a 2.342 42.71 1.96 -30.36 0.08 Pool L P-D n/a 2.204 43.11 2.01 -30.36 0.75 Pool L P n/a 2.360 41.23 1.26 -29.13 0.42 Pool LP n/a 3.096 44.05 2.07 -31.75 0.92 Pool L P n/a 2.830 46.47 1.95 -28.72 1.08 Riffle L P n/a 2.289 44.63 1.00 -29.07 -0.59
134
LOCATION SAMPLE N Sample
Wt. Total Total δ13 C δ15 N (mg) %C %N vs. PDB vs. Air Riffle L P n/a 2.860 44.20 1.84 -29.74 1.59 Riffle L P n/a 2.548 44.01 1.44 -29.83 -0.35 Riffle L P-D n/a 3.050 44.15 1.52 -29.86 -0.30 Riffle L P n/a 1.951 44.56 1.88 -29.87 1.14 Riffle L P n/a 2.677 46.31 1.60 -29.16 1.23 Riffle L P-D n/a 2.687 45.99 1.61 -29.33 1.11 Riffle L P n/a 2.461 44.65 1.84 -29.55 1.08 Riparian MOSS n/a 2.494 29.16 1.78 -29.03 1.59 Riparian MOSS n/a 1.893 33.07 1.71 -27.72 0.63 Riparian MOSS-D n/a 2.084 18.89 1.03 -28.44 0.37 Riparian MOSS n/a 0.951 45.67 11.27 -26.78 5.18 Riparian MOSS n/a 2.516 26.91 1.50 -30.49 0.66 Riparian MOSS n/a 2.000 20.13 1.35 -28.64 -0.35 Riparian MOSS n/a 2.827 32.93 1.42 -29.98 1.23 Pool NAUCORIDAE 1 1.240 48.27 10.87 -32.02 2.95 Pool NAUCORIDAE 2 1.199 46.60 11.40 -31.45 2.65 Pool PERIPHYTON n/a 1.000 n/a 2.35 -29.28 2.50 Pool PERIPHYTON n/a 1.000 n/a 2.95 -28.87 4.34 Pool PERIPHYTON n/a 1.000 n/a 3.08 -29.83 4.24 Pool PERIPHYTON n/a Filter 48.90 4.79 -27.97 4.27 Pool PERIPHYTON n/a 1.000 n/a 1.17 -28.38 3.14 Pool PERIPHYTON-D n/a 1.000 n/a 1.29 -27.63 3.31 Riffle PERIPHYTON n/a 1.000 n/a 3.46 -30.37 1.76 Riffle PERIPHYTON n/a Filter 22.20 3.10 -27.98 3.38 Riffle PERIPHYTON n/a 1.000 n/a 3.29 -28.85 2.68 Riffle PERIPHYTON n/a 1.000 n/a 3.18 -33.07 2.35 Riffle PERIPHYTON-D n/a 1.000 n/a 4.29 -32.99 2.49 Riffle PERIPHYTON n/a 1.000 n/a 2.69 -29.11 3.61 Riffle PERIPHYTON n/a 1.000 n/a 3.58 -28.55 2.72 Riffle PERLIDAE 3 1.678 46.77 11.23 -27.20 4.81 Riffle PERLIDAE 2 1.443 45.64 11.25 -28.41 4.23 Riparian RIPARIAN n/a 1.989 41.55 1.85 -32.37 -1.06 Riparian RIPARIAN n/a 2.286 42.75 3.24 -33.82 1.45 Riparian RIPARIAN n/a 2.297 38.28 2.18 -33.59 -0.58 Riparian RIPARIAN n/a 2.132 38.65 2.29 -33.22 0.90 Riparian RIPARIAN-D n/a 2.368 38.01 2.21 -33.73 0.62 Riparian RIPARIAN n/a 3.148 40.84 3.31 -33.33 1.23 Riparian RIPARIAN n/a 2.061 38.99 2.62 -33.29 0.01 Riparian RIPARIAN-D n/a 2.874 39.00 2.62 -33.33 0.29 Riffle SESTON n/a 1.000 n/a 1.03 -51.48 2.92 Riffle SESTON n/a Filter 11.78 0.96 -29.12 3.76 Pool BR II 3 1.443 41.03 10.04 -27.01 7.35 Pool BR II 1 1.073 42.94 10.56 -27.07 7.43 Pool BR II –D 1 1.051 39.30 10.32 -26.01 7.85 Riffle BR II 1 2.335 38.97 9.43 -26.58 7.12 Riffle BR II 3 1.282 40.87 9.54 -26.89 7.18
135
LOCATION SAMPLE NUMBER Sample
Wt. Total Total δ13 C δ15 N (mg) %C %N vs. PDB vs. Air Riffle BR II –D 3 1.384 41.94 10.89 -26.33 7.50 Riffle BR II 4 1.361 38.83 10.17 -26.88 6.91 Riffle BR II 1 1.112 41.88 10.45 -27.83 7.40 Pool BR III 2 1.485 39.29 9.70 -26.07 7.33 Pool BR III-D 2 1.204 42.84 10.27 -26.45 7.41 Riffle BR III 4 1.675 37.38 9.28 -25.99 7.59 Riffle BR III 2 1.621 39.78 10.37 -26.07 7.70 Riffle BR III 3 1.889 42.21 10.11 -26.72 7.29 Riffle BR III 4 2.406 40.67 9.87 -26.06 7.38 Riffle BR III 2 2.536 40.64 10.07 -26.46 6.97 Riffle BR III-D 2 1.149 39.72 9.90 -26.47 7.74 Riffle BR IV 3 2.672 40.89 10.40 -26.40 7.57 Riffle BR IV 2 1.952 38.39 9.80 -26.31 7.17 Riffle BR V 1 1.507 43.09 10.89 -26.00 7.37 Pool VELIIDAE 1 0.264 47.19 10.53 -27.16 3.52 Pool VELIIDAE 3 0.678 49.69 10.67 -27.45 4.76 Riffle VELIIDAE 1 1.064 48.32 9.65 -25.90 4.41 Riffle VELIIDAE 2 1.460 49.73 10.53 -27.36 4.26 Riffle VELIIDAE 3 1.727 48.33 10.74 -27.20 3.99 Riffle CALOPTERYGIDAE 7 2.577 6.88 0.42 -29.45 1.20 Riffle CALOPTERYGIDAE-D 7 1.889 13.83 0.73 -29.63 1.51 Riffle CALOPTERYGIDAE 1 1.215 46.38 10.64 -27.03 5.41 Riffle CALOPTERYGIDAE 1 1.089 45.31 11.37 -26.85 4.96 Riffle CALOPTERYGIDAE 3 1.561 45.91 10.19 -27.35 5.14
136
Stable Isotope Data El Copé September ‘04 LOCATION SAMPLE NUMBER Sample Wt. Total %C Total %N δ13C δ15N
(mg) vs. PDB vs. Air
Riffle BAETIDAE 1 1.230 52.15 9.75 -30.39 3.34
Pool BR II 1 1.549 45.66 11.58 -26.05 7.54
Pool BR II 1 1.144 45.73 11.12 -26.38 8.78
Pool BR II 1 2.020 45.32 11.83 -25.99 7.67
Pool BR II 1 1.134 40.05 8.70 -27.75 7.51
Pool BR II dupe 1 1.570 44.95 9.46 -28.35 7.01
Pool BR II 1 1.797 39.78 9.67 -28.14 6.40
Pool BR II 1 1.663 42.56 9.76 -28.47 6.23
Pool BR II 1 1.090 44.76 9.45 -28.05 7.02
Riffle BR II 2 1.483 42.54 11.07 -27.73 7.00
Riffle BR II 2 1.608 39.72 10.28 -27.06 7.22
Riffle BR II dupe 2 1.564 40.34 10.57 -26.92 7.36
Riffle BR II 2 1.612 39.31 9.83 -26.77 7.43
Riffle BR II 2 1.493 41.49 10.36 -26.69 7.30
Riffle BR II 1 1.582 42.62 10.51 -27.07 7.39
Pool BR II 2 2.081 47.80 13.07 -25.37 7.93
Pool BR II 2 1.781 44.96 10.84 -26.72 6.90
Pool BR II dupe 2 1.493 44.92 11.21 -26.35 7.56
Pool BR II 3 1.397 46.69 11.57 -26.82 6.52
Pool BR II 1 1.289 43.18 11.55 -26.07 7.66
Pool BR II 1 1.109 41.59 9.27 -27.06 7.50
Pool BR II 1 1.535 44.63 9.96 -26.54 7.93
Pool BR II 1 1.915 41.81 10.41 -27.39 6.71
Pool BR II dupe 1 1.533 42.62 11.60 -27.09 7.21
Pool BR II 11 1.542 39.14 9.57 -26.14 7.69
Pool BR II 1 1.449 42.81 11.13 -26.71 6.98
Pool BR II 1 1.672 43.55 11.29 -26.08 6.88
Riffle BR II 1 1.648 42.49 10.51 -26.89 7.13
Pool BR III 1 1.380 43.78 9.84 -26.81 8.28
Pool BR III dupe 1 1.265 42.18 9.59 -26.75 8.14
Pool BR III 1 1.977 47.51 10.85 -26.74 7.10
Pool BR III 1 1.535 47.66 9.81 -27.39 7.60
Pool BR III 1 1.682 43.20 9.94 -27.01 7.30
Riffle BR III 2 1.876 43.72 10.53 -26.91 7.40
Riffle BR III 2 1.742 39.54 10.02 -26.88 7.21
Riffle BR III dupe 2 1.611 43.59 10.77 -26.90 7.25
Riffle BR III 2 1.488 34.18 9.46 -25.44 7.96
Riffle BR III 1 1.689 39.51 10.30 -26.91 7.21
137
LOCATION SAMPLE NUMBER Sample Wt. Total %C Total %N δ13C δ15N
(mg) vs. PDB vs. Air
Pool BR III 1 2.203 41.99 9.56 -27.03 6.67
Pool BR III 1 1.849 37.01 9.47 -26.07 7.61
Pool BR III 1 1.955 41.79 9.76 -26.32 7.45
Pool BR III dupe 1 1.825 41.79 9.71 -26.52 7.39
Pool BR III 1 1.340 41.92 10.98 -26.10 7.65
Pool BR III 1 1.175 37.44 9.84 -25.77 8.19
Pool BR III 1 2.018 45.82 9.83 -26.92 7.39
Riffle BR IV 1 1.815 40.54 9.69 -25.92 8.25
Riffle BR IV 1 2.146 39.11 10.69 -26.29 6.91
Riffle BR IV dupe 1 1.196 39.43 10.63 -26.48 7.74
Pool BR IV 1 1.248 44.06 10.50 -26.56 7.77
Pool BR IV 1 1.894 43.62 9.79 -26.52 7.69
Riffle BR V 1 1.092 41.01 11.02 -25.65 8.39
Riffle BR V 1 2.375 42.87 10.73 -25.78 7.92
Pool BR V 1 1.253 39.85 9.71 -26.31 8.08
Pool BR V dupe 1 1.389 38.12 9.26 -26.23 7.83
Riffle BR V 1 1.245 43.22 11.28 -25.57 8.64
Pool BR YOLK 1 1.167 46.99 11.17 -26.28 8.52
Pool BR YOLK 1 1.548 47.17 11.59 -25.96 8.26
Pool BR YOLK 1 1.604 47.55 11.45 -26.15 7.94
Pool BR YOLK 1 1.457 42.42 10.76 -26.66 7.16
Pool BR YOLK dupe 1 1.555 38.47 9.56 -26.51 7.26
Pool BR YOLK 1 2.344 41.52 10.90 -26.16 7.41
Riffle CORDULIIDAE 1 1.384 47.55 11.90 -28.06 4.92
Riffle CRAB 1 1 2.611 28.22 5.62 -25.57 5.01
Riffle CRAB 1 1 1.376 25.02 3.80 -25.89 5.21
Pool CRAB II 1 2.086 23.70 4.59 -25.77 5.43
Pool CRAB II dupe 1 1.806 30.09 5.79 -26.70 5.51
Riffle ELMIDAE 1 1.499 48.42 10.26 -26.66 1.77
Riffle EPHEMEROPTERA 1 0.957 50.75 12.39 -27.79 5.91
Pool EPHEMEROPTERA 1 1.088 50.58 8.66 -31.08 3.35
Pool GERIIDAE 1 1.378 53.17 10.73 -27.55 6.00
Pool GERIIDAE 1 1.017 53.30 10.25 -28.20 5.61
Pool GERIIDAE dupe 1 1.518 51.52 11.41 -27.64 6.06
Pool GYRINIDAE 1 1.411 49.39 11.90 -26.76 5.16
Pool GYRINIDAE 1 1.472 49.23 11.22 -27.51 5.88
Pool GYRINIDAE 1 1.677 45.46 10.43 -26.92 6.15
Pool GYRINIDAE 1 1.602 50.13 11.30 -26.64 6.27
Pool GYRINIDAE 1 1.427 51.71 10.88 -27.11 6.56
138
LOCATION SAMPLE NUMBER Sample Wt. Total %C Total %N δ13C δ15N
(mg) vs. PDB vs. Air
Pool GYRINIDAE dupe 1 1.534 44.55 9.38 -27.04 6.27
Pool GYRINIDAE 1 1.636 44.25 11.06 -25.85 4.20
Riffle GYRINIDAE 1 1.481 46.69 10.16 -22.40 3.67
Riffle HYDROPSYCHIDAE 2 1.040 47.26 9.68 -28.87 3.19
Riffle HYDROPSYCHIDAE 2 1.731 46.04 9.88 -28.76 3.85
Riffle HYDROPSYCHIDAE 2 1.062 43.87 9.15 -28.77 4.28
Riffle HYDROPSYCHIDAE dupe 2 2.155 44.49 9.40 -31.43 2.43
Riffle HYDROPSYCHIDAE 2 1.201 47.14 10.69 -27.92 4.79
Riffle HYDROPSYCHIDAE 2 1.319 48.43 10.52 -27.99 4.78
Riffle HYDROPSYCHIDAE 2 1.288 44.74 10.21 -28.55 4.30
Riffle LIBELLULIDAE 1 1.408 47.24 11.97 -32.64 3.43
Riffle LIBELLULIDAE 1 1.058 47.63 11.77 -32.44 3.33
Riffle LIBELLULIDAE dupe 1 1.478 44.89 11.06 -32.42 2.94
Riffle LIBELLULIDAE 1 1.297 44.50 11.16 -33.09 3.28
Riffle LIBELLULIDAE 1 1.525 46.28 11.61 -29.20 3.21
Riffle LIBELLULIDAE 1 0.703 47.98 11.38 -33.05 3.51
Pool NAUCORIDAE 1 1.542 47.31 10.72 -31.28 3.15
Pool NAUCORIDAE 1 2.014 50.33 11.47 -28.49 3.29
Pool NAUCORIDAE dupe 1 1.690 46.47 10.57 -30.29 2.51
Pool NAUCORIDAE 1 1.730 45.62 11.11 -26.93 3.17
Pool NAUCORIDAE 1 1.817 49.15 11.32 -27.06 3.91
Riffle NAUCORIDAE 1 1.334 47.11 11.79 -33.78 3.55
Riffle NAUCORIDAE 1 1.738 50.48 10.66 -34.07 2.88
Riffle PERLIDAE 1 0.539 47.91 11.74 -28.48 5.16
Riffle PERLIDAE dupe 1 1.971 23.94 6.00 -28.21 4.91
Riffle PERLIDAE 1 1.173 49.45 12.45 -27.16 5.40
Riffle PERLIDAE 1 1.108 46.43 11.47 -28.47 4.89
Riffle PERLIDAE 1 1.186 48.37 11.57 -27.13 4.89
Riffle PTILIDACTYLIDAE 1 1.226 30.48 6.91 -26.37 4.11
Riffle PTILIDACTYLIDAE 1 1.018 45.21 9.56 -27.08 2.16
Riffle PTILIDACTYLIDAE dupe 1 1.377 46.11 10.35 -27.10 2.16
Riffle PTILIDACTYLIDAE 1 0.590 37.88 8.11 -26.94 4.31
Riffle PTILIDACTYLIDAE 1 1.188 37.14 7.92 -26.76 4.33
Riffle SHRIMP 1 1.543 34.46 7.32 -26.50 4.63
Pool VELIIDAE 3 1.516 49.77 10.94 -27.13 4.82
Pool VELIIDAE 4 1.160 51.06 10.68 -27.93 4.54
Pool VELIIDAE dupe 4 1.378 51.87 10.41 -27.60 4.82
Pool VELIIDAE 4 1.153 50.83 10.59 -26.23 4.54
Riffle VELIIDAE 1 0.597 48.67 11.01 -27.58 4.39
139
LOCATION SAMPLE NUMBER Sample Wt. Total %C Total %N δ13C δ15N
(mg) vs. PDB vs. Air
Riffle VELIIDAE 2 1.030 51.92 10.36 -27.91 4.61
Riffle VELIIDAE 2 0.774 51.25 10.59 -27.55 4.64
Pool ZYGOPTERA 2 1.125 44.77 9.19 -29.32 3.94
Pool ZYGOPTERA dupe 2 1.454 46.91 10.24 -29.50 3.99
GUABAL Bufo conif 3 2.308 38.97 5.78 -23.82 5.88
GUABAL Bufo conif 3 1.662 38.39 6.10 -23.34 5.51
GUABAL Bufo conif 3 1.708 34.49 5.30 -28.70 5.69
GUABAL Bufo conif 3 1.662 32.01 4.53 -28.74 5.51
GUABAL Bufo conif 3 1.301 34.76 5.15 -28.62 5.65
GUABAL Bufo conif dupe 3 1.180 33.35 4.83 -28.19 5.68
GUABAL Bufo conif 3 2.215 32.96 5.01 -28.57 5.98
GUABAL Centro I 1 0.966 47.15 10.37 -25.56 5.46
GUABAL Centro I 1 1.234 47.35 11.52 -17.79 4.91
GUABAL Centro I 1 1.176 47.62 12.04 -28.21 1.66
GUABAL Centro I 1 0.533 42.67 9.93 -25.76 5.06
GUABAL Centro I dupe 1 1.094 45.89 10.93 -25.59 5.61
GUABAL Centro I 1 1.229 47.58 12.02 -25.80 7.44
GUABAL Centro I 1 1.147 48.71 11.12 -25.88 5.25
GUABAL Centro I 1 1.710 48.48 10.95 -27.38 5.12
GUABAL Centro II 1 2.297 52.03 11.92 -24.60 1.17
GUABAL Col flot 1 1.767 39.02 8.27 -27.14 5.08
GUABAL Col flot dupe 1 1.488 44.27 10.55 -26.58 5.16
GUABAL Col flot 1 1.309 46.93 10.50 -26.90 5.43
GUABAL Col flot 1 1.305 47.24 11.96 -26.63 5.02
GUABAL Col flot 1 1.916 45.42 10.51 -26.99 5.73
GUABAL Hyla II 1 1.940 45.43 8.25 -26.74 5.25
GUABAL Hyla II 1 1.614 33.66 9.65 -26.56 5.12
GUABAL Rana war 2 1.794 31.58 7.41 -26.64 5.18
GUABAL Rana war 2 1.516 38.71 6.50 -28.37 5.62
GUABAL Rana war 2 1.091 30.42 7.43 -27.26 5.80
GUABAL Rana war 2 2.235 29.93 7.84 -26.89 5.66
GUABAL Rana war dupe 2 1.558 30.37 7.56 -27.05 5.33
GUABAL Rana war 2 1.284 31.84 7.62 -28.13 5.57
GUABAL Rana war 2 1.665 32.34 8.19 -28.26 5.20
GUABAL Rana war 2 1.653 32.05 6.72 -27.73 5.27
GUABAL Col ing I 1 1.276 33.93 6.21 -26.66 5.24
GUABAL Col ing I 1 2.581 29.31 7.48 -27.49 4.78
GUABAL Col ing I dupe 1 1.824 32.32 6.96 -27.45 4.89
GUABAL Col ing I 1 2.221 35.30 8.86 -28.16 5.21
140
LOCATION SAMPLE NUMBER Sample Wt. Total %C Total %N δ13C δ15N
(mg) vs. PDB vs. Air
GUABAL Col ing I 1 1.741 33.85 8.50 -28.11 5.24
141
Stable Isotope Data Tadpoles – October ’04 – January ‘05 LOCATION SAMPLE NUMBER Sample Wt. Total % C Total %N δ13C δ15N (mg) vs. PDB vs. Air
Guabal BUFO I 1 1.221 50.48 10.48 -28.51 4.60
Guabal BUFO I 1 0.872 60.77 7.07 -28.05 7.88
Guabal BUFO I 1 0.269 60.21 8.42 -28.31 8.30
Guabal BUFO I 1 1.015 59.65 7.41 -27.91 7.85
Guabal BUFO I 1 0.749 59.94 7.76 -27.76 8.08
Guabal C nubicola II 1 2.172 42.19 10.68 -25.93 5.52
Guabal C nubicola II - dupe 1 2.070 41.73 10.72 -25.88 5.61
Guabal Col flot II 1 1.857 41.39 10.60 -26.63 5.44
Guabal Col flot II 1 2.726 33.67 6.91 -26.66 5.68
Guabal Col flot II 1 2.596 38.39 9.27 -26.51 5.25
Guabal Col flot II 1 3.454 32.51 6.49 -27.32 4.97
Guabal Col flot II 1 1.091 34.67 7.03 -27.05 6.30
Guabal Col flot II 1 2.037 37.68 8.24 -26.73 4.82
Guabal Col flot II 1 2.051 27.92 4.88 -27.54 5.48
Guabal Col flot II - dupe 1 1.724 35.78 5.82 -27.27 5.56
Guabal Col flot II 1 1.019 49.96 12.07 -26.67 6.71
Guabal C flot II 1 n/a 0.50 0.09 -28.26 5.94
Guabal H. colymb 1 1.265 33.19 6.85 -27.35 4.78
Guabal H. colymb 1 2.961 40.42 10.11 -27.26 4.14
Guabal H. colymb III 1 1.248 34.49 8.66 -27.40 5.49
Guabal H. colymb III 1 1.858 39.52 9.61 -27.00 6.68
Guabal H. colymb III - dupe 1 2.401 43.86 11.17 -27.05 5.92
Guabal H. colymb III 1 0.989 33.60 7.91 -26.52 7.11
Guabal H. colymb III 1 1.593 27.73 5.63 -27.63 5.63
Guabal H. colymb III 1 2.260 34.15 8.46 -27.05 5.02
Guabal H. colymb III 1 1.393 35.59 8.35 -26.31 5.73
Guabal H. colymb III 1 1.882 38.50 8.33 -27.99 5.19
Guabal H. colymb III - dupe 1 1.624 37.34 6.53 -28.83 5.32
Guabal H. colymb III 1 1.429 45.61 11.37 -26.03 5.66
Guabal H. colymb III 1 1.468 22.88 5.47 -26.23 5.92
Guabal R. war II 1 1.011 29.16 6.52 -28.20 5.92
Guabal R. war II 1 1.053 42.31 7.89 -26.90 4.88
Guabal R. war II 1 1.003 42.91 11.35 -28.95 5.32
Guabal R. war II - dupe 1 3.043 30.93 6.58 -32.05 4.10
Guabal R. war II 1 1.469 40.23 7.65 -26.71 4.61
Guabal R. war II 1 1.260 39.32 8.58 -27.17 4.46
Guabal R. war II 1 3.274 34.14 8.64 -29.04 4.43
Guabal R. war II 1 2.743 27.19 6.09 -27.88 5.49
Guabal R. war II 1 1.246 37.96 9.85 -31.87 4.49
Guabal R. war II - dupe 1 3.812 28.08 6.09 -31.90 3.54
Guabal R. war II 1 1.037 22.77 4.97 -29.93 5.42
Guabal R. war II 1 2.462 37.13 7.56 -26.78 4.14
Guabal R. war II 1 1.104 17.64 3.32 -30.25 4.98
Guabal R. war II 1 2.021 19.74 4.26 -29.41 4.93
Guabal R. war II 1 0.664 41.60 10.08 -30.86 6.05
142
LOCATION SAMPLE NUMBER Sample Wt. Total % C Total %N δ13C δ15N (mg) vs. PDB vs. Air
Guabal R. war II 1 2.794 23.85 4.84 -27.44 4.70
Guabal R. war II 1 1.410 21.13 4.32 -29.52 4.94
Guabal R. war II 1 1.259 33.56 8.14 -30.27 5.25
143
Stable Isotope Data Adult Frogs – October ’04 – January ‘05 LOCATION SAMPLE NUMBER Sample Wt. Total % C Total %N delta C13 delta N15 (mg) vs. PDB vs. Air
Loop Adult frog 1719 1 1.383 46.38 13.87 -24.73 5.68
Guabal Adult frog 1720 1 1.568 47.18 14.29 -25.94 4.89
Guabal Adult frog 1721 1 0.983 47.55 14.09 -24.60 5.20
Guabal Adult frog 1722 1 1.151 47.14 14.84 -25.52 4.21
Guabal Adult frog 1420 1 1.787 47.54 14.61 -26.58 4.87
Guabal B evuntus 1 1.102 46.45 14.34 -25.86 5.87
Guabal B evuntus - dupe 1 1.137 46.75 14.39 -25.79 5.82
Guabal B haem 1 1.899 45.92 13.75 -24.73 7.86
Guabal B haem 1 1.109 48.82 14.34 -24.85 7.78
Guabal B haem 1 1.166 49.11 14.46 -24.77 7.80
Guabal B. haem 1 2.171 47.49 14.59 -24.65 7.47
Guabal B. haem 1 1.450 48.25 14.19 -24.64 7.69
Cascada B. haem 1 2.589 47.81 14.29 -24.86 6.68
Guabal B. haem 1 2.202 48.22 14.34 -24.62 7.26
Silenciosa B. haem 1 2.234 46.32 14.24 -24.62 7.33
Silenciosa B. haem - dupe 1 1.294 46.41 14.32 -24.50 8.05
B. buto 1 1.823 46.16 14.47 -25.70 4.61
Guabal B. conif 1 2.199 46.84 13.79 -25.44 3.77
Guabal B. conif - dupe 1 1.915 46.70 13.80 -25.50 3.87
C alb 1 1.537 47.42 14.44 -25.11 5.66
Guabal C alb 1 1.093 47.14 14.28 -25.12 5.15
Guabal C alb 1 1.112 47.48 14.54 -24.85 4.41
Loop C. albumac 1 1.170 47.76 14.47 -24.94 4.85
Guabal C. albumac 1 1.108 47.38 14.20 -24.31 6.45
Loop C ing 1 1.381 46.96 14.34 -25.57 5.31
Loop C ing - dupe 1 1.650 47.51 14.28 -25.72 5.20
Silenciosa C ing 1 2.148 47.42 14.17 -25.42 5.33
Cascada C ing 1 1.156 47.66 14.37 -24.97 6.74
Silenciosa C ing 1 1.176 47.57 14.44 -25.52 5.70
Loop C ing 1 1.094 47.25 14.43 -25.36 5.32
Silenciosa C ing 1 1.165 48.54 14.39 -25.10 6.18
Silenciosa C ing - dupe 1 1.716 47.72 14.15 -25.02 5.58
Cascada C ing 1 1.309 48.03 14.14 -25.52 7.29
Silenciosa C ing 1 1.458 46.94 14.25 -25.30 6.43
Silenciosa C ing 1 1.207 46.79 14.12 -26.49 5.40
C. ing 1 1.470 47.32 13.99 -25.43 6.85
Silenciosa C ing 1 1.472 46.89 14.16 -25.80 5.30
Guabal C. ing 1 1.063 46.38 13.80 -25.18 6.45
Guabal C. ing - dupe 1 0.888 45.85 13.85 -25.10 6.67
Tony C. ing 1 1.281 47.37 14.43 -26.05 5.51
Loop C. ing 1 1.868 49.02 14.74 -25.60 6.03
C. euknemos 1 2.576 43.44 10.97 -26.35 4.21
C. euknemos - dupe 1 2.248 43.83 11.52 -26.11 4.09
Cascada C. ilex 1 1.930 46.92 13.97 -24.87 4.54
Cascada C. ilex 1 1.214 47.46 14.75 -25.04 5.84
144
LOCATION SAMPLE NUMBER Sample Wt. Total % C Total %N delta C13 delta N15 (mg) vs. PDB vs. Air
Cascada C. nubi 1 1.083 47.46 14.04 -25.47 6.50
Loop C. nubi 1 1.105 46.49 13.97 -25.45 5.79
Cascada C. nubi 1 0.990 45.72 13.85 -25.14 7.06
Cascada C. nubi - dupe 1 1.061 45.92 13.96 -25.30 7.05
Loop C. nubi 1 1.101 48.29 14.07 -25.37 6.43
Silenciosa C. nubi 1 1.167 47.90 14.18 -25.14 5.57
Cascada C. nubi 1 1.093 46.66 14.09 -25.23 6.49
Guabal C. nubi 1 2.166 46.68 14.00 -26.76 4.55
Cascada C. nubi 1 1.718 30.30 8.92 -24.97 7.04
Cascada C. nubi - dupe 1 1.098 74.84 22.19 -25.06 6.65
Loop C. nubi 1 1.002 46.33 14.04 -25.38 5.62
Loop C. nubi 1 1.155 46.96 14.41 -25.20 6.31
Cascada C. nubi 1 1.228 46.24 13.96 -24.81 7.66
Loop C. nubi 1 1.099 47.14 13.83 -25.46 6.15
Loop C. nubi 1 1.102 46.85 13.69 -25.08 5.01
Loop C. nubi - dupe 1 1.249 46.47 13.89 -24.92 4.93
Cascada C. nubi 1 1.224 44.82 13.40 -25.05 5.64
Loop C. nubi 1 1.023 46.69 13.97 -25.09 6.05
Silenciosa C. nubi 1 1.121 47.67 13.87 -25.15 7.30
Cascada C. nubi 1 0.937 46.08 13.60 -25.55 6.47
Loop C. nubi 1 1.078 45.97 13.66 -25.48 5.53
Loop C. nubi - dupe 1 1.179 46.15 13.76 -25.30 5.47
Loop C. nubi 1 1.196 45.84 13.44 -24.97 5.65
Loop E caryo 1 1.365 45.76 13.84 -25.40 4.06
Road E nub 1 1.694 47.06 14.61 -23.06 4.84
Road E nub - dupe 1 1.501 46.55 14.45 -22.80 4.80
Guabal E padi nublei 1 1.194 46.69 14.39 -26.06 5.86
Cascada E padi nublei 1 1.819 48.02 14.72 -25.63 5.12
Guabal E padi nublei 1 2.460 46.49 14.44 -26.04 4.53
Cascada E padi nublei 1 1.032 47.81 14.43 -25.83 5.98
Guabal E padi nublei 1 1.934 47.21 14.58 -25.61 6.30
Guabal E padi nublei - dupe 1 1.246 45.62 14.35 -25.59 6.68
Cascada E padi nublei 1 2.241 47.27 14.72 -25.84 6.14
Loop E padi nublei 1 1.645 45.26 13.88 -25.90 4.40
Guabal E. padi noblei 1 1.464 45.26 13.88 -25.97 7.11
Cascada E. padi nublei 1 1.598 45.43 13.48 -26.52 4.79
Cascada E. padi nublei 1 1.613 47.40 14.37 -25.60 5.86
Loop E. padi nublei 1 1.903 45.29 14.13 -26.08 6.21
Guabal E. padi nublei 1 1.054 46.61 12.99 -25.48 5.52
Guabal E. padi nublei - dupe 1 1.733 44.11 13.70 -25.12 5.09
Guabal E. padi 1 2.272 46.00 14.29 -24.97 5.43
Cascada E tal 1 2.613 46.60 14.16 -25.38 3.29
Silenciosa C. talam 1 1.374 46.50 14.28 -26.23 4.73
Loop E talam 1 1.169 47.15 14.32 -26.35 5.08
Guabal E talam 1 1.611 46.69 14.44 -26.09 4.60
E talc? 1 1.471 46.66 14.27 -25.41 6.99
145
LOCATION SAMPLE NUMBER Sample Wt. Total % C Total %N delta C13 delta N15 (mg) vs. PDB vs. Air
E talc? - dupe 1 1.409 45.37 13.85 -25.30 7.17
Guabal E. talam 1 2.283 45.12 13.86 -25.95 3.54
Guabal E. talam 1 1.242 46.12 14.20 -25.80 4.77
Silenciosa E. talam 1 1.068 47.32 13.91 -25.45 5.83
Guabal E. talam 1 2.380 46.05 14.07 -26.32 4.75
Cascada E. talam 1 1.957 45.59 13.85 -25.48 4.80
Cascada E. talam - dupe 1 1.172 47.35 14.14 -26.00 5.23
Loop E. talam 1 1.299 46.75 13.88 -26.06 4.76
Guabal E. talam 1 2.449 43.67 13.51 -26.24 3.45
E. talam 1 3.664 46.06 13.92 -25.28 3.96
E. talam 1 3.824 38.62 10.62 -26.23 3.43
E. talam 1 2.107 39.87 10.95 -26.88 4.18
E. talam - dupe 1 1.223 42.30 11.15 -27.35 4.78
Silenciosa E. bufo 1 1.807 43.77 11.42 -25.81 5.40
Guabal E. bufo 1 1.022 46.23 14.21 -25.55 6.03
Silenciosa E. butoni 1 2.050 45.86 13.98 -25.60 4.89
Guabal E. crassi 1 1.531 44.43 13.68 -26.52 3.36
Guabal E. crassi 1 1.790 47.57 14.19 -25.67 5.43
Guabal E. crassi - dupe 1 1.872 45.65 14.11 -25.67 5.47
Guabal E. crassi 1 1.001 46.72 14.45 -27.01 3.73
Guabal E. cruentus 1 1.690 47.51 13.85 -26.28 5.86
Silenciosa E. cruentus 1 1.177 46.98 14.39 -26.70 5.33
Guabal E. cruentus 1 1.290 46.75 14.47 -26.00 4.87
Guabal E. cruentus 1 1.259 45.47 13.48 -26.31 4.31
Guabal E. cruentus - dupe 1 1.985 45.85 13.80 -25.96 3.83
Loop E. cruentus 1 1.159 45.90 13.87 -26.21 4.81
Cascada E. cruentus 1 2.344 47.56 14.27 -25.27 6.33
Guabal E. cruentus 1 1.470 46.38 14.17 -26.57 5.17
Guabal E. cruentus 1 1.023 46.01 14.30 -26.68 4.48
E. cruentus 1 1.308 45.20 14.04 -26.47 5.08
E. cruentus - dupe 1 1.467 45.71 13.94 -26.13 5.10
Guabal E. cruentus 1 1.146 46.17 14.15 -25.87 5.64
Main E. cruentus 1 1.592 45.94 14.29 -25.42 4.41
Silenciosa E. musc 1 1.162 46.91 14.33 -26.00 5.57
Guabal E. sp 1 1.600 44.89 13.76 -25.44 4.68
E. sp 1 1.312 46.23 14.13 -25.25 5.12
E. sp - dupe 1 2.084 44.22 13.47 -25.34 4.73
Mattoral H col 1 1.145 45.78 14.23 -25.15 5.14
Guabal H col 1 1.158 45.69 14.22 -24.72 6.15
Cascada H col 1 0.906 45.13 13.47 -25.20 5.41
Loop H col 1 1.043 46.69 14.02 -25.26 4.95
Guabal H col 1 1.199 44.54 13.39 -25.68 4.80
Guabal H col - dupe 1 1.268 45.62 13.08 -25.76 4.74
Guabal H col 1 0.986 46.42 13.88 -25.24 5.52
Loop H col 1 1.017 45.76 13.07 -25.38 5.37
Guabal h col 1 1.407 46.62 13.95 -25.22 3.96
146
LOCATION SAMPLE NUMBER Sample Wt. Total % C Total %N delta C13 delta N15 (mg) vs. PDB vs. Air
Silenciosa H col 1 1.162 45.37 13.16 -25.20 5.35
Cascada H col 1 1.280 44.97 14.00 -25.47 6.27
Cascada H col - dupe 1 1.058 44.21 13.27 -25.46 6.48
Silenciosa H col 1 1.893 45.89 13.72 -25.66 5.21
Silenciosa H col 1 1.632 48.19 13.37 -25.42 5.36
Cascada H col 1 1.875 46.56 13.74 -25.18 5.04
Cascada H col 1 1.313 47.06 13.69 -24.97 4.84
Silenciosa H col 1 1.079 45.66 13.53 -25.28 6.15
Silenciosa H col - dupe 1 1.548 43.48 13.09 -25.34 5.84
Guabal H col 1 2.157 41.89 12.15 -25.07 5.02
Loop H col 1 0.922 45.89 13.35 -25.32 5.85
Cascada H col 1 1.767 43.65 12.68 -25.07 6.30
Loop H col 1 2.119 45.93 13.44 -24.93 4.49
Cascada h col 1 0.996 46.23 14.06 -25.32 4.70
Cascada h col - dupe 1 2.054 48.31 12.94 -24.59 3.82
H col 1 2.601 46.57 13.41 -25.52 4.43
Loop H. col 1 1.838 12.56 2.95 -25.28 4.87
Cascada H. col 1 8.336 28.36 8.78 -25.48 6.00
Cascada H. col - dupe 1 1.149 7.15 2.14 -25.14 5.90
Loop H. col 1 1.617 61.21 18.16 -25.25 4.74
Cascada H. colymbiphyllum 1 1.272 49.88 14.88 -25.69 6.21
Cascada H. colymbiphyllum 1 1.725 37.48 10.96 -25.39 6.67
H col w/ eggs 1 1.009 29.05 8.62 -27.06 3.12
H col w/ eggs 1 1.104 386.56 76.41 -26.50 4.34
Loop H miliaria 1 2.113 112.56 23.78 -25.71 4.65
Guabal H miliaria 1 1.885 46.80 14.45 -25.53 3.94
Guabal H miliaria - dupe 1 1.914 46.58 14.17 -25.65 3.88
Guabal H palm 1 1.555 46.56 14.29 -25.91 5.26
Guabal H palm 1 1.179 47.72 13.89 -24.92 4.11
Guabal H palm 1 1.103 45.93 13.56 -25.43 4.62
Guabal H palm 1 2.427 45.72 13.95 -25.80 3.70
Guabal H palm 1 2.015 45.38 13.94 -25.64 4.09
Guabal H palm - dupe 1 1.151 45.29 14.15 -25.76 4.58
Guabal H. pal 1 1.325 44.35 13.98 -25.27 4.30
Guabal H.pal 1 0.778 46.38 14.04 -25.62 4.47
Guabal N. aterina 1 1.117 46.17 14.35 -24.98 8.26
Cascada Nelson 1 1.269 47.29 13.77 -24.64 9.20
Guabal Nelson 1 1.071 47.20 13.68 -24.84 8.47
Guabal P Velson att 1 1.065 50.36 13.96 -24.89 6.70
Loop R. warsz 1 1.705 49.08 14.57 -25.75 4.36
Silenciosa R. warsz 1 1.669 47.52 14.62 -26.09 5.44
Silenciosa R. warsz 1 2.159 48.53 14.74 -25.28 4.70
Silenciosa R. warsz - dupe 1 1.591 47.82 14.95 -25.52 5.08
S. ilex 1 1.156 46.29 14.31 -25.80 4.96
Tad tail 1466 1 1.456 46.06 14.26 -25.84 4.70
tad tail 1464 1 1.105 47.66 14.17 -25.92 6.01
147
LOCATION SAMPLE NUMBER Sample Wt. Total % C Total %N delta C13 delta N15 (mg) vs. PDB vs. Air
tad tail 1467 1 1.397 48.18 14.21 -25.86 4.43
tad tail 1645 1 1.578 47.03 13.83 -25.94 5.30
tad tail 1645 - dupe 1 1.199 47.45 13.93 -25.92 5.50
tad tail 1460 1 1.743 47.55 14.08 -25.98 4.23
tad tail 1468 1 1.524 47.61 13.99 -26.12 5.68
148
Stable Isotope Data El Copé February ‘05 LOCATION SAMPLE NUMBER Sample Wt. Total % C Total %N δ13C δ15N (mg) vs. PDB vs. Air
Riffle ANISOPTERA 1 0.986 48.86 9.79 -28.98 3.86
Riffle BAETIDAE 1 1.874 52.33 10.14 -30.84 3.76
Riffle BAETIDAE 1 1.432 50.21 12.40 -26.89 5.34
Riffle BAETIDAE 1 0.794 49.01 10.97 -27.13 5.43
Riffle BAETIDAE - dupe 1 1.275 50.02 12.24 -26.91 5.35
Pool BR I 2 1.132 48.26 11.08 -26.15 8.23
Pool BR I 2 1.188 51.22 12.09 -26.53 7.72
Pool BR I 1 1.649 50.97 11.94 -26.45 8.01
Pool BR I 2 2.029 43.33 9.78 -26.54 7.58
Pool BR I 1 1.071 45.02 11.33 -25.73 8.63
Pool BR IV 1 1.464 46.93 9.29 -26.83 8.28
Pool BR IV 1 3.115 35.69 6.92 -26.92 7.90
Pool CATFISH 1 2.356 38.92 8.05 -26.80 8.46
Pool CATFISH - dupe 1 1.200 47.14 9.59 -26.82 9.28
Riffle CRAB II 1 2.026 24.31 3.97 -23.89 4.70
Riffle CRAB II 1 2.321 24.47 4.02 -23.55 5.88
Riffle CRAB III 1 5.000 33.90 6.13 -27.70 4.07
Riffle ELMIDAE 1 0.901 47.61 10.65 -26.79 2.87
Riffle ELMIDAE - dupe 1 1.093 47.43 10.79 -26.65 2.54
Riffle ELMIDAE 1 1.277 47.15 9.74 -27.04 2.88
Riffle ELMIDAE 1 0.813 45.81 11.36 -26.86 3.54
Riffle ELMIDAE 1 0.886 46.58 11.15 -25.84 5.29
Riffle ELMIDAE 1 0.460 48.41 11.98 -26.16 3.87
Riffle ELMIDAE 1 1.363 43.95 9.37 -27.24 3.02
Riffle ELMIDAE - dupe 1 1.454 43.75 9.28 -27.30 3.25
Riffle ELMIDAE 1 1.480 49.44 10.72 -26.92 2.53
Riffle HYDROPSYCH 1 1.031 47.28 9.81 -27.69 3.75
Riffle HYDROPSYCH 1 1.627 45.95 8.16 -28.65 3.70
Riffle HYDROPSYCH 1 0.993 44.70 8.84 -28.06 4.08
Riffle HYDROPSYCH 1 1.433 50.58 9.72 -28.28 3.31
Riffle HYDROPSYCH - dupe 1 1.106 49.06 10.29 -27.70 4.13
Riffle HYDROPSYCH 1 1.494 46.57 7.85 -28.52 3.85
Riffle HYDROPSYCH 1 1.507 47.12 9.78 -28.03 3.54
Riffle HYDROPSYCH 1 1.136 46.02 7.14 -29.04 3.62
Riffle HYDROPSYCH 1 1.991 48.43 8.51 -29.12 3.24
Riffle HYDROPSYCH 1 1.380 45.67 9.14 -28.05 3.78
Riffle HYDROPSYCH - dupe 1 1.499 47.38 8.84 -28.31 3.65
Riffle HYDROPSYCH 1 1.268 48.80 11.07 -27.37 4.00
Riffle HYDROPSYCH 1 0.971 48.41 7.98 -28.47 3.83
Riffle SHRIMP VII 1 2.339 45.90 9.61 -27.93 6.85
Riffle SHRIMP VII 1 2.804 14.41 2.91 -27.67 7.47
Riffle SM TRICH 1 0.611 44.93 6.94 -28.48 3.38
Riffle SM TRICH - dupe 1 0.535 48.59 9.51 -27.70 3.48
Riffle SM TRICH 1 0.943 46.27 9.03 -28.39 3.48
Riffle SM TRICH 1 0.507 42.91 6.89 -28.40 3.83
149
LOCATION SAMPLE NUMBER Sample Wt. Total % C Total %N δ13C δ15N (mg) vs. PDB vs. Air
Riffle SM TRICH 1 1.424 43.79 7.48 -28.37 3.54
Riffle ZYG 1 1.036 48.94 11.29 -27.75 4.96
Riffle ZYG 2 1.142 47.72 11.38 -27.93 5.03
Riffle ZYG - dupe 2 0.986 48.24 11.09 -27.19 5.60
Riffle ZYG 1 1.131 48.67 10.53 -28.16 4.79
Riffle LP n/a 2.292 48.68 2.67 -30.12 2.69
Pool LP n/a 2.976 47.28 1.70 -30.92 2.27
Riffle LP n/a 2.869 48.21 2.21 -29.04 2.40
Pool LP n/a 2.876 43.05 2.06 -29.70 3.33
Pool LP n/a 2.097 48.55 2.41 -30.74 2.56
Pool LP - dupe n/a 2.620 48.47 2.27 -31.05 2.63
Riffle LP n/a 2.322 48.01 1.90 -30.33 3.34
Pool LP n/a 30.210 4.53 0.18 -29.14 1.37
Riffle LP n/a 2.197 46.42 1.76 -29.33 1.74
Pool LP n/a 3.278 42.58 2.55 -29.68 2.40
Riffle LP n/a 2.055 41.08 1.95 -31.91 1.88
Riffle LP - dupe n/a 2.734 42.43 1.90 -31.64 1.90
Riffle LP n/a 3.908 47.92 1.69 -31.05 2.95
Pool LP n/a 4.759 45.90 2.28 -31.30 2.04
Riparian MOSS n/a 4.301 27.01 1.65 -30.11 2.68
Riparian MOSS n/a 2.716 35.24 1.72 -30.84 2.30
Riparian MOSS n/a 2.213 36.01 1.78 -29.83 2.77
Riparian MOSS - dupe n/a 2.822 36.72 1.64 -29.82 2.55
Riparian MOSS n/a 2.351 29.91 1.79 -28.65 2.83
Riparian MOSS n/a 2.983 21.37 0.99 -29.71 2.38
Riparian MOSS n/a 2.503 32.31 1.78 -30.43 2.70
Riparian RIP n/a 3.228 42.57 2.12 -35.12 0.24
Riparian RIP n/a 2.441 44.68 1.87 -35.02 1.05
Riparian RIP - dupe n/a 2.587 44.67 2.02 -34.95 1.16
Riparian RIP n/a 2.062 47.07 2.03 -35.04 1.09
Riparian RIP n/a 3.095 41.97 2.42 -34.24 1.11
Riparian RIP n/a 3.602 44.42 1.86 -34.08 1.37
Riparian RIP n/a 2.287 41.76 2.27 -33.15 1.89
Pool FBOM n/a n/a n/a n/a -28.51 6.24
Pool FBOM n/a n/a n/a n/a -28.04 3.77
Pool FBOM n/a n/a n/a n/a -27.82 4.95
Pool FBOM n/a n/a n/a n/a -28.10 3.17
Pool FBOM n/a n/a n/a n/a -27.86 3.23
Pool FBOM - dupe n/a n/a n/a n/a -27.94 3.77
Pool FBOM n/a n/a n/a n/a -28.22 2.91
Riffle LPSCRAP n/a n/a n/a n/a -27.96 3.09
Riffle LPSCRAP n/a n/a n/a n/a -27.57 4.27
Riffle LPSCRAP n/a n/a n/a n/a -26.05 6.65
Riffle LPSCRAP - dupe n/a n/a n/a n/a -26.61 6.77
Riffle LPSCRAP n/a n/a n/a n/a -28.03 4.58
Pool LPSCRAP n/a n/a n/a n/a -27.11 3.11
150
LOCATION SAMPLE NUMBER Sample Wt. Total % C Total %N δ13C δ15N (mg) vs. PDB vs. Air
Pool LPSCRAP n/a n/a n/a n/a -27.47 3.73
Pool LPSCRAP - dupe n/a n/a n/a n/a -27.45 3.53
Pool LPSCRAP n/a n/a n/a n/a -26.64 5.42
Pool LPSCRAP n/a n/a n/a n/a -27.88 4.78
Pool LPSCRAP n/a n/a n/a n/a -28.09 4.38
Pool LPSCRAP n/a n/a n/a n/a -26.23 6.72
Pool LPSCRAP n/a n/a n/a n/a -28.62 2.13
Pool LPSCRAP n/a n/a n/a n/a -28.36 3.45
Riffle PERI n/a n/a n/a n/a -28.20 3.45
Riffle PERI n/a n/a n/a n/a -30.96 3.42
Riffle PERI - dupe n/a n/a n/a n/a -30.68 4.21
Riffle PERI n/a n/a n/a n/a -29.67 4.87
Riffle PERI n/a n/a n/a n/a -27.85 4.22
Riffle PERI n/a n/a n/a n/a -26.69 2.57
Pool PERI n/a n/a n/a n/a -27.30 3.32
Pool PERI n/a n/a n/a n/a -29.62 3.29
Pool PERI n/a n/a n/a n/a -29.91 3.79
Pool PERI n/a n/a n/a n/a -27.09 5.65
Pool PERI - dupe n/a n/a n/a n/a -27.19 5.81
Pool PERI n/a n/a n/a n/a -29.97 3.05
Pool PERI n/a n/a n/a n/a -28.99 3.29
Pool PERI n/a n/a n/a n/a -29.80 4.58
Pool PERI - dupe n/a n/a n/a n/a -29.73 4.40
Riffle SESTON n/a n/a n/a n/a -28.65 4.90
Riffle SESTON n/a n/a n/a n/a -28.76 2.24
Riffle SESTON n/a n/a n/a n/a -28.98 3.02
Riparian BIG BROWN SPIDER 1 1.387 45.08 12.20 -26.74 6.73
Riparian BLACK SPIDER 1 1.041 46.74 11.51 -27.64 6.26
Riparian LB SPIDER BANDED LEGS 1 0.921 45.70 11.77 -26.36 7.27
Riparian BROWN SPIDER 1 1.123 45.34 11.58 -27.00 7.25
Riparian BROWN SPIDER 1 2.376 47.87 11.59 -27.45 5.10
Riparian WHIP SCORPION 1 1.872 46.08 12.11 -26.35 5.71
Riparian WHIP SCORPION - dupe 1 1.240 46.05 11.99 -26.25 6.09
151
Stable Isotope Data El Copé May ‘05 LOCATION SAMPLE NUMBER Sample Wt. Total % C Total% N δ13 C δ15N (mg) vs. PDB vs. Air
Pool BR I 1 1.425 39.24 9.05 -26.16 7.44
Pool BR I - dupe 1 1.310 41.53 10.88 -25.54 8.32
Pool BR II 1 1.070 38.05 9.97 -26.51 7.75
Pool BR II 1 1.230 42.40 11.03 -26.12 7.72
Riffle BR III 1 2.148 44.35 11.13 -26.60 7.07
Pool BR III 1 1.266 40.82 10.90 -26.11 7.96
Pool BR III 1 1.596 37.79 9.52 -25.62 8.30
Pool BR III 1 1.333 38.31 10.01 -26.30 8.13
Pool BR III - dupe 1 1.256 36.84 9.77 -26.12 8.27
Pool BR III 1 1.633 42.51 10.34 -26.13 7.83
Pool BR III 1 1.597 37.45 9.85 -25.61 8.24
Pool BR III 1 1.313 43.00 9.13 -26.84 8.27
Pool BR III 1 1.644 36.99 8.75 -25.99 7.76
Pool BR III 1 1.090 42.92 9.43 -26.27 8.83
Pool BR III - dupe 1 1.460 39.91 8.79 -26.06 8.58
Pool BR III 1 3.797 37.02 8.74 -26.33 7.61
Pool BR III 1 1.632 37.81 9.05 -26.31 7.90
Pool BR III 1 1.846 38.13 9.26 -26.17 7.36
Riffle BR IV 1 3.750 41.34 10.65 -25.97 7.07
Riffle BR IV 1 2.197 41.76 10.02 -26.07 8.06
Pool BR IV - dupe 1 2.384 40.24 9.75 -26.03 8.05
Riffle BS TRICH 1 1.472 47.56 10.28 -28.20 3.31
Riffle CATFISH 1 5.000 43.78 11.91 -26.00 7.67
Riffle CRAB I 1 1.122 35.78 3.88 -28.01 4.07
Riffle CRAB I 1 1.103 24.00 4.12 -23.80 5.88
Riffle CRAB II 1 1.301 40.70 8.64 -25.43 5.41
Riffle CRAB II - dupe 1 2.543 27.09 4.41 -25.01 4.78
Riffle ELMIDAE 1 1.038 48.10 10.48 -27.18 3.30
Riffle ELMIDAE 1 1.227 49.68 9.64 -28.13 2.61
Riffle ELMIDAE 1 1.124 47.83 10.59 -26.33 3.42
Riffle ELMIDAE 1 1.118 49.04 10.03 -26.65 4.41
Riffle ELMIDAE 1 1.022 52.90 10.04 -27.28 4.80
Riffle EPHEM 1 1.336 49.93 11.83 -27.56 4.92
Riffle EPHEM - dupe 1 1.251 50.56 11.34 -27.67 4.80
Riffle EPHEM 3 0.831 49.92 10.65 -28.17 4.04
Riffle EPHEM 3 1.434 49.55 11.29 -27.91 4.68
Riffle EPHEM 1 0.323 49.54 12.38 -27.10 6.36
Riffle EPHEM 1 0.786 48.05 12.09 -27.25 5.42
Riffle EPHEM - dupe 1 0.904 47.14 11.98 -27.28 5.34
Riffle EPHEM 1 1.041 48.84 11.13 -27.96 4.03
Riffle FIL ALG n/a 3.684 17.75 2.45 -36.54 2.57
Riffle FIL ALG n/a 4.048 40.95 4.70 -44.14 4.04
Riffle FIL ALG n/a 3.153 32.33 3.58 -42.70 4.21
Riffle FIL ALG - dupe n/a 4.104 40.89 4.72 -43.37 3.66
Pool GERIIDAE 1 1.487 51.37 11.05 -27.54 6.32
152
LOCATION SAMPLE NUMBER Sample Wt. Total % C Total% N δ13 C δ15N (mg) vs. PDB vs. Air
Pool GERIIDAE 1 0.994 57.29 9.29 -28.47 6.02
Pool GERIIDAE 1 1.167 37.10 7.98 -27.14 6.00
Pool GERIIDAE 1 1.555 49.70 12.06 -26.63 5.48
Pool GYRINIDAE 1 1.848 41.10 8.11 -27.09 5.76
Riffle HYDROPSY 1 0.771 48.95 10.50 -28.36 2.81
Riffle HYDROPSY - dupe 1 1.025 48.52 10.34 -28.47 3.06
Riffle HYDROPSY 1 1.859 46.12 9.67 -27.44 3.67
Riffle HYDROPSY 2 1.769 47.28 9.13 -27.93 3.80
Pool LP n/a 2.321 45.13 1.91 -29.15 2.16
Pool LP n/a 2.504 45.34 1.81 -29.85 1.80
Riffle LP n/a 3.319 40.07 1.74 -31.14 1.96
Riffle LP - dupe n/a 3.027 41.53 1.86 -30.67 1.91
Riffle LP n/a 3.302 46.43 2.00 -28.81 2.13
Riffle LP n/a 3.132 45.96 2.20 -31.93 2.86
pool LP n/a 3.091 46.97 1.71 -28.26 1.43
pool LP n/a 2.939 45.91 2.55 -29.63 1.74
pool LP n/a 3.562 43.59 1.51 -30.23 1.19
pool LP - dupe n/a 2.994 44.25 1.58 -30.42 1.42
Riffle LP n/a 3.390 45.62 1.12 -29.97 0.54
Riffle LP n/a 2.315 45.43 1.93 -29.65 2.16
Riffle LP n/a 2.252 52.04 2.26 -30.30 1.79
Riparian MOSS n/a 2.416 27.72 1.42 -29.09 2.96
Riparian MOSS n/a 2.751 29.36 1.55 -29.75 2.59
Riparian MOSS - dupe n/a 3.543 31.65 1.63 -29.71 2.37
Riparian MOSS n/a 2.715 30.27 0.76 -28.36 0.74
Riparian MOSS n/a 2.445 29.33 1.45 -29.50 2.83
Riparian MOSS n/a 3.996 43.21 1.84 -29.66 3.47
Riparian MOSS n/a 2.755 45.57 2.16 -29.70 2.76
Riffle PTILO n/a 1.454 54.68 11.38 -26.88 5.25
Riffle PTILO - dupe 1 1.081 55.39 11.98 -26.07 5.64
Riffle PTILO 1 0.948 40.16 9.16 -27.46 5.03
Riffle PTILO 1 1.314 51.53 9.60 -27.89 5.55
Riffle PTILO 1 1.207 48.51 9.66 -27.03 5.24
Riparian RIP n/a 3.079 38.72 2.61 -31.38 3.03
Riparian RIP n/a 2.317 39.19 2.49 -32.39 2.47
Riparian RIP n/a 2.127 39.51 2.22 -33.30 0.02
Riparian RIP n/a 2.775 42.05 2.87 -31.31 0.82
Riparian RIP n/a 2.816 41.22 2.09 -32.81 0.38
Riparian RIP - dupe n/a 3.035 41.57 2.17 -32.78 0.42
Riparian RIP n/a 2.192 35.67 1.36 -33.72 -0.22
Riffle SM TRICH 2 0.971 42.88 8.84 -28.24 3.60
Riffle SM TRICH 2 0.855 44.56 8.97 -28.74 4.12
Riffle SM TRICH 1 0.868 45.25 9.45 -28.30 3.20
Riffle SM TRICH - dupe 3 0.680 44.24 8.57 -28.34 3.26
Riffle VELIIDAE 0.274 49.17 10.24 -26.85 5.31
Riffle VELIIDAE 1 0.546 53.74 11.20 -27.89 4.68
153
LOCATION SAMPLE NUMBER Sample Wt. Total % C Total% N δ13 C δ15N (mg) vs. PDB vs. Air
Pool VELIIDAE 1 0.949 50.48 11.34 -27.44 4.60
Pool VELIIDAE 2 1.029 49.35 11.39 -27.15 5.35
Riffle ZYG 1 1.951 45.49 11.62 -27.59 4.32
Riffle ZYG 1 1.159 47.50 11.35 -28.08 3.67
Riffle ZYG - dupe 1 1.116 46.32 11.07 -28.05 4.00
Riffle ZYG 1 1.466 47.42 10.66 -28.43 3.22
Riffle ZYG-BIG 1 1.054 48.32 11.63 -27.18 5.44
Riffle ZYG-big gill 1 1.136 47.87 12.49 -27.99 5.57
Riffle ZYG-big gill 1 1.527 47.62 12.20 -27.79 4.69
Riffle ZYG-big gill 1 1.239 49.25 11.65 -26.81 5.32
Pool FBOM n/a n/a 0.550 0.039 -29.14 3.46
Pool FBOM n/a n/a 0.313 0.025 -29.08 3.62
Pool FBOM n/a n/a 0.912 0.071 -29.39 2.91
Pool FBOM n/a n/a 0.368 0.029 -29.27 4.20
Pool FBOM - dupe n/a n/a 0.335 0.027 -29.37 3.88
Pool FBOM n/a n/a 0.439 0.034 -29.15 4.14
Riffle LP SCRAP n/a n/a 0.298 0.032 -27.88 4.23
Riffle LP SCRAP n/a n/a 1.000 0.057 -29.17 2.40
Riffle LP SCRAP n/a n/a 1.082 0.049 -27.51 3.32
Riffle LP SCRAP n/a n/a 0.473 0.036 -29.83 3.23
Riffle LP SCRAP n/a n/a 0.295 0.031 -28.69 3.77
Riffle LP SCRAP n/a n/a 0.621 0.059 -28.82 2.68
Pool LP SCRAP n/a n/a 0.271 0.021 -28.69 3.52
Pool LP SCRAP - dupe n/a n/a 0.813 0.045 -28.09 3.29
Pool LP SCRAP n/a n/a 0.205 0.023 -27.73 4.01
Pool LP SCRAP n/a n/a 0.677 0.049 -29.19 2.85
Pool LP SCRAP n/a n/a 0.472 0.043 -27.38 5.76
Pool LP SCRAP - dupe n/a n/a 0.559 0.049 -27.42 5.10
Pool LP SCRAP n/a n/a 0.560 0.050 -28.65 3.75
Riffle PERIPHYTON n/a n/a 0.422 0.049 -32.46 3.74
Riffle PERIPHYTON n/a n/a 0.209 0.030 -30.06 2.99
Riffle PERIPHYTON n/a n/a 0.716 0.063 -29.88 3.54
Riffle PERIPHYTON - dupe n/a n/a 0.703 0.062 -30.05 3.28
Riffle PERIPHYTON n/a n/a 0.322 0.045 -29.97 3.63
Riffle PERIPHYTON - dupe n/a n/a 0.390 0.043 -30.94 3.13
Riffle PERIPHYTON n/a n/a 0.376 0.042 -30.78 2.93
Riffle PERIPHYTON n/a n/a 0.615 0.068 -30.80 3.15
Pool PERIPHYTON n/a n/a 0.812 0.069 -30.09 3.81
Pool PERIPHYTON n/a n/a 0.465 0.052 -30.02 3.72
Pool PERIPHYTON n/a n/a 0.241 0.032 -32.46 3.52
Pool PERIPHYTON n/a n/a 0.449 0.046 -28.72 3.79
Riffle SESTON n/a n/a 0.274 0.022 -29.19 3.33
Riffle SESTON n/a n/a 0.276 0.022 -29.16 4.26
Riffle SESTON n/a n/a 0.039 0.004 -27.31 3.57
Riffle SESTON - dupe n/a n/a 0.041 0.004 -27.91 3.70
Riffle CRAB IV 1 n/a 0.795 0.152 -22.97 4.59
154
LOCATION SAMPLE NUMBER Sample Wt. Total % C Total% N δ13 C δ15N (mg) vs. PDB vs. Air
Riffle CRAB IV 1 n/a 0.589 0.132 -23.77 4.81
Riffle CRAB XV 1 n/a 1.371 0.338 -25.16 8.08
155
Stable Isotope Data Snakes El Copé LOCATION SAMPLE Number Sample Wt. Total %C Total %N δ13C δ15N (mg) vs. PDB vs. Air
El Cope Oxy brev 1 1.584 31.05 9.28 -23.93 8.75
El Cope Oxy brev 1 1.045 31.54 9.59 -24.02 8.14
El Cope Oxy brev 1 0.798 31.90 9.68 -24.27 8.41
El Cope Oxy brev 1 0.645 31.33 10.06 -23.87 8.35
El Cope Oxy brev 1 1.117 30.23 8.89 -24.28 8.64
El Cope Oxy brev 1 1.088 29.98 9.51 -23.85 8.70
El Cope Oxy brev 1 0.780 31.43 8.81 -24.29 9.61
El Cope Oxy brev 1 0.967 30.61 9.41 -23.78 8.53
El Cope Oxy brev 1 1.446 28.18 8.56 -23.82 8.07
El Cope Oxy brev 1 1.117 28.87 8.63 -23.75 8.10
El Cope Oxy brev 1 0.834 32.65 9.69 -24.33 7.99
El Cope Oxy brev 1 1.140 33.02 9.86 -24.20 7.75
El Cope Oxy brev 1 1.017 30.52 9.13 -24.05 8.10
El Cope Oxy brev 1 1.715 33.14 9.59 -23.91 8.54
El Cope Oxy brev 1 1.220 30.70 9.17 -23.68 7.84
El Cope Oxy brev 1 0.886 33.94 9.39 -24.32 7.87
El Cope Oxy brev 1 0.665 31.67 9.72 -24.13 8.03
El Cope Oxy brev 1 0.416 110.35 33.30 -24.23 7.38
El Cope Oxy brev 1 0.653 31.97 9.24 -24.53 8.88
El Cope Oxy brev 1 0.796 30.52 9.17 -24.00 8.72
El Cope Oxy brev 1 0.539 82.66 25.55 -23.61 7.66
El Cope Oxy brev 1 0.853 79.96 23.54 -24.14 6.82
El Cope Oxy brev 1 0.626 31.53 9.68 -24.48 8.00
El Cope Oxy brev 1 0.963 30.06 9.44 -24.22 7.99
El Cope Oxy brev 1 0.592 33.32 9.83 -24.10 9.18
El Cope Oxy brev 1 0.692 32.59 9.22 -24.25 8.88
El Cope Oxy brev 1 1.193 27.96 8.92 -23.67 7.64
El Cope Oxy brev 1 1.365 29.09 9.05 -23.80 7.36
El Cope Oxy brev 1 0.740 33.32 9.29 -24.77 8.37
El Cope Oxy brev 1 1.102 31.31 9.65 -24.14 8.07
El Cope Oxy brev 1 1.230 30.80 9.12 -24.00 8.43
El Cope Oxy brev 1 0.973 29.03 8.93 -23.58 8.51
El Cope Oxy brev 1 1.021 29.66 8.18 -24.44 8.68
El Cope Oxy brev 1 0.971 31.07 8.95 -24.15 8.08
El Cope Oxy brev 1 0.485 29.30 9.05 -24.36 9.13
El Cope Oxy brev 1 0.769 31.36 9.63 -24.30 8.61
El Cope Oxy brev 1 1.240 29.94 9.05 -23.62 7.66
El Cope Oxy brev 1 0.941 29.87 8.93 -24.03 8.26
El Cope Oxy brev 1 0.909 32.45 9.39 -23.57 8.67
El Cope Oxy brev 1 1.193 29.49 9.09 -23.93 8.00
El Cope Oxy brev 1 0.632 32.27 9.80 -23.97 8.81
El Cope Oxy brev 1 1.427 30.06 9.22 -23.92 8.26
El Cope Oxy brev 1 1.150 33.30 9.71 -23.80 8.27
El Cope Oxy brev 1 0.153 217.05 0.68 -24.01 8.21
El Cope Oxy brev 1 0.926 31.40 8.96 -23.89 8.59
156
LOCATION SAMPLE Number Sample Wt. Total %C Total %N δ13C δ15N (mg) vs. PDB vs. Air
El Cope Oxy brev 1 0.923 29.85 8.93 -24.20 8.20
El Cope Oxy brev 1 0.640 32.99 9.57 -24.17 10.14
El Cope Oxy brev 1 0.903 32.62 9.66 -24.19 9.90
El Cope Oxy brev 1 1.089 31.57 9.27 -23.82 9.96
El Cope Oxy brev 1 0.806 34.44 9.66 -24.33 8.64
El Cope Oxy brev 1 0.800 35.73 9.41 -24.68 8.71
El Cope Oxy brev 1 0.808 33.13 9.97 -24.04 8.45
El Cope Oxy brev 1 1.069 29.74 8.73 -23.94 8.88
El Cope Oxy brev 1 0.879 28.14 8.72 -23.60 8.96
El Cope Oxy brev 1 0.907 32.71 9.22 -24.48 8.11
El Cope Oxy brev 1 0.716 28.27 8.97 -23.53 8.35
El Cope Oxy brev 1 0.896 33.64 9.65 -23.97 9.09
El Cope Oxy brev 1 0.998 30.07 8.92 -23.70 8.89
El Cope Oxy brev 1 1.280 29.19 8.73 -24.10 8.22
El Cope Oxy brev 1 0.758 28.06 8.94 -23.65 8.35
El Cope Oxy brev 1 0.994 28.83 8.99 -23.48 8.43
El Cope Oxy brev 1 0.927 27.12 8.57 -23.46 8.29
El Cope Oxy brev 1 0.804 31.30 9.58 -23.97 8.70
El Cope Oxy brev 1 0.729 31.01 9.03 -23.95 8.76
El Cope Oxy brev 1 1.212 34.74 10.52 -24.21 7.45
El Cope Oxy brev 1 1.177 30.46 9.17 -24.00 7.80
El Cope Oxy brev 1 1.161 29.54 8.95 -22.66 7.99
El Cope Oxy brev 1 0.799 31.59 9.36 -23.99 8.43
El Cope Oxy brev 1 0.803 30.45 8.71 -23.97 8.80
El Cope Oxy brev 1 0.811 30.79 8.92 -24.00 8.32
El Cope Oxy brev 1 1.043 35.45 9.91 -24.22 7.93
El Cope Oxy brev 1 0.993 27.53 8.77 -23.42 8.05
El Cope Oxy brev 1 1.090 34.15 9.59 -24.43 7.86
El Cope Oxy brev 1 1.311 29.47 9.31 -23.74 8.75
El Cope Oxy brev 1 1.501 30.68 9.15 -24.06 7.86
El Cope Oxy brev 1 0.902 27.94 8.86 -23.01 9.19
El Cope Oxy brev 1 0.785 27.56 8.61 -22.76 8.37
El Cope Oxy brev 1 0.788 27.64 8.47 -23.05 8.34
El Cope Oxy brev 1 0.729 31.07 9.02 -23.96 8.74
El Cope Oxy brev 1 0.822 31.97 9.00 -24.16 8.02
El Cope Oxy brev 1 0.991 35.87 10.16 -24.42 7.95
El Cope Oxy brev 1 1.300 30.59 8.63 -24.09 9.02
El Cope Oxy brev 1 1.276 27.73 8.84 -23.46 8.16
El Cope Oxy brev 1 0.540 36.52 11.95 -23.70 8.36
El Cope Oxy brev 1 0.913 31.45 8.96 -24.16 8.23
El Cope Oxy brev 1 1.201 29.48 9.08 -24.22 8.23
El Cope Oxy brev 1 1.013 32.67 9.29 -24.06 8.42
El Cope Oxy brev 1 0.763 28.51 8.81 -23.17 8.80
El Cope Oxy brev 1 0.699 31.11 9.51 -24.10 8.37
El Cope Oxy brev 1 0.862 35.12 9.76 -24.61 8.12
El Cope Oxy brev 1 1.775 25.94 8.17 -23.47 7.76
157
LOCATION SAMPLE Number Sample Wt. Total %C Total %N δ13C δ15N (mg) vs. PDB vs. Air
El Cope Oxy brev 1 0.752 34.06 9.22 -23.80 8.10
El Cope Oxy brev 1 0.975 34.58 9.64 -24.41 8.27
El Cope Oxy brev 1 0.843 29.48 8.66 -24.05 8.49
El Cope Oxy brev 1 1.124 29.78 8.66 -24.22 8.28
El Cope Oxy brev 1 0.875 29.08 8.88 -24.05 8.46
El Cope L sept 1 0.718 26.32 7.94 -23.43 9.47
El Cope L sept 1 1.241 28.38 8.62 -23.37 8.35
El Cope L sept 1 0.989 22.43 6.51 -23.83 9.71
El Cope L sept 1 0.657 29.34 8.73 -23.60 8.68
El Cope L sept 1 1.139 30.10 9.17 -23.30 9.01
El Cope L sept 1 1.042 31.08 9.35 -23.47 8.83
El Cope L sept 1 1.043 29.36 8.70 -23.86 9.31
El Cope L sept 1 0.723 28.62 8.61 -23.63 8.85
El Cope L sept 1 0.908 31.48 8.63 -24.29 9.72
El Cope L sept 1 1.313 36.92 10.27 -24.59 8.84
El Cope L sept 1 0.647 31.73 9.19 -23.97 8.87
El Cope L sept 1 0.810 32.37 9.53 -23.79 8.59
El Cope S ann 1 1.035 30.03 8.52 -26.35 3.72
El Cope S ann 1 0.882 36.37 9.93 -27.59 2.97
El Cope S ann 1 1.230 32.54 9.30 -26.09 3.54
El Cope S ann 1 1.337 28.73 8.36 -26.03 3.38
El Cope S ann 1 1.299 34.45 9.86 -26.42 2.64
El Cope S ann 1 0.749 31.62 9.78 -25.97 2.97
El Cope S ann 1 0.756 33.05 9.41 -26.40 3.67
El Cope S ann 1 1.218 31.42 9.22 -25.76 3.15
El Cope S ann 1 0.784 32.61 9.31 -27.11 2.91
El Cope S ann 1 0.772 34.27 9.74 -26.58 3.91
El Cope S ann 1 0.866 30.62 8.78 -26.44 4.00
El Cope S ann 1 0.876 31.74 9.46 -26.45 3.84
El Cope S ann 1 0.738 35.41 9.76 -27.21 3.30
El Cope S ann 1 0.856 26.13 7.93 -26.02 3.32
El Cope S ann 1 1.409 28.42 8.09 -25.84 4.08
El Cope S ann 1 0.948 36.35 10.36 -26.98 2.89
El Cope S ann 1 0.668 33.17 9.24 -26.06 4.64
El Cope S ann 1 0.816 30.92 8.79 -25.65 4.59
El Cope S ann 1 0.895 31.56 9.25 -26.22 3.48
El Cope S ann 1 0.546 33.17 9.70 -26.67 2.64
El Cope S ann 1 1.058 33.22 9.39 -26.65 2.97
El Cope S ann 1 0.865 29.59 8.94 -26.04 3.85
El Cope S ann 1 1.180 30.85 8.94 -26.36 3.06
El Cope S ann 1 0.984 28.49 8.44 -26.06 3.28
El Cope S ann 1 0.865 34.98 9.95 -26.65 2.24
El Cope S ann 1 0.964 30.39 8.62 -25.54 3.36
El Cope S ann 1 0.796 34.75 9.91 -26.74 3.17
El Cope S ann 1 0.678 34.39 9.75 -27.42 2.74
El Cope S ann 1 0.618 37.53 10.97 -24.62 7.11
158
LOCATION SAMPLE Number Sample Wt. Total %C Total %N δ13C δ15N (mg) vs. PDB vs. Air
El Cope S ann 1 0.767 36.44 10.92 -24.61 7.37
El Cope S ann 1 0.857 32.54 9.53 -23.96 7.18
El Cope Iman cench 1 1.317 32.95 9.32 -23.92 8.74
El Cope Iman cench 1 0.856 32.62 9.19 -24.27 9.23
El Cope Iman cench 1 0.972 33.71 9.56 -23.88 9.76
El Cope Iman cench 1 0.553 31.81 9.44 -23.94 9.67
El Cope Iman cench 1 0.721 30.56 9.21 -23.74 9.55
El Cope Iman cench 1 0.752 32.21 9.28 -24.00 9.14
El Cope Iman cench 1 1.006 24.50 7.65 -22.20 9.97
El Cope Iman cench 1 1.298 29.77 9.04 -23.55 9.78
El Cope Iman cench 1 1.425 29.06 8.86 -23.38 9.00
El Cope Iman cench 1 1.156 28.02 8.36 -22.07 8.91
El Cope Iman cench 1 0.655 27.85 8.55 -21.91 8.92
El Cope Iman cench 1 1.207 30.17 9.00 -23.55 8.89
El Cope Iman cench 1 0.755 33.94 9.43 -24.39 8.62
El Cope Iman cench 1 1.058 33.89 9.82 -24.13 8.57
El Cope Iman cench 1 0.786 30.87 9.00 -23.66 9.57
El Cope Iman cench 1 0.650 30.70 8.60 -23.33 8.32
El Cope Iman cench 1 0.898 28.01 8.41 -22.90 8.08
El Cope Iman cench 1 0.953 28.87 8.58 -22.95 9.17
El Cope Iman cench 1 0.905 9.95 3.02 -23.71 9.44
El Cope Iman cench 1 1.016 30.77 8.79 -24.18 8.39
El Cope Iman cench 1 0.584 28.23 8.74 -23.07 8.94
El Cope Iman cench 1 0.532 29.09 8.49 -23.58 8.76
El Cope Iman cench 1 0.620 30.58 9.18 -23.54 8.63
El Cope Iman cench 1 0.874 30.05 8.84 -24.01 8.87
El Cope Iman cench 1 0.818 26.26 8.02 -22.91 9.58
El Cope Dispas 1 0.568 37.57 10.12 -23.99 7.83
El Cope Dispas 1 1.042 36.93 10.33 -24.45 6.40
El Cope Dispas 1 0.849 36.37 10.12 -23.71 6.91
El Cope Dispas 1 0.936 35.20 10.26 -23.59 6.79
El Cope Dispas 1 1.109 31.95 9.25 -23.45 6.78
El Cope Dispas 1 0.676 33.83 9.77 -23.71 7.49
El Cope Dispas 1 0.448 41.23 11.65 -24.10 7.12
El Cope Dispas 1 0.782 34.00 9.87 -23.77 7.07
El Cope Dispas 1 0.759 35.68 10.11 -24.29 6.90
El Cope Dispas 1 0.689 33.87 10.20 -23.73 7.00
El Cope Dispas 1 0.833 36.33 10.36 -24.11 5.57
El Cope Dispas 1 0.622 34.04 9.33 -23.47 8.23
El Cope Dispas 1 0.771 34.85 10.10 -23.91 7.10
El Cope Dispas 1 0.586 31.16 8.95 -23.59 7.92
El Cope Dispas 1 0.603 31.75 9.16 -23.16 8.01
El Cope Dispas 1 0.594 28.27 8.44 -22.65 7.87
159
Stable Isotope Data Fortuna - June ‘03
LOCATION SAMPLE NUMBER Sample Wt. Total %C
Total %N δ13 C δ15 N
(mg) vs. PDB vs. Air
Riffle ADULT COL 1 1.921 47.01 10.62 -27.80 0.24
Riffle BAETIDAE 1 0.996 47.78 10.60 -25.63 0.47
Riffle BAETIDAE dupe 1 1.161 46.77 10.10 -25.79 0.31
Riffle BR II 1 1.524 42.88 10.66 -27.71 4.68
Riffle BR III 2 1.894 43.77 10.87 -28.12 4.95
Riffle BR IV 7 2.663 40.80 10.84 -25.89 ALD
Riffle BR-FECES n/a filter 0.00 0.00 -26.99 2.92
Riffle BR-FECES n/a filter 0.00 0.00 -26.07 3.61
Riffle BR-FECES dupe n/a filter 0.00 0.00 -26.15 3.29
Riffle BR-FECES 1 filter 0.00 0.00 -25.62 2.28
Riffle LIBELLULIDAE 1 1.476 47.28 10.22 -28.84 0.63
Riffle LIBELLULIDAE 1 2.012 46.38 11.20 -26.48 0.35
Riffle CRAB 90mm 1 1.494 26.48 5.78 -23.23 5.81
Riffle CRAB FECES n/a filter 0.00 0.00 -25.58 4.13
Riffle CRAB FECES n/a filter 0.00 0.00 -26.39 4.39
Riffle CRAB FECES n/a filter 0.00 0.00 -25.96 3.17
Riffle CRAB FECES dupe n/a filter 0.00 0.00 -26.52 4.03
Riffle CRAB I 1 1.662 24.39 4.75 -24.37 3.29
Pool CRAB I 2 2.048 26.74 5.52 -23.98 3.13
Pool CRAB II 1 2.602 30.11 6.77 -23.85 4.06
Riffle CRAB II 1 1.671 30.55 6.97 -25.23 3.22
Riffle CRAB II 2 1.748 30.45 6.20 -23.96 3.21
Riffle CRAB II dupe 2 1.819 32.55 7.34 -24.09 3.61
Riffle CRAB II 2 2.249 35.31 9.72 -25.21 2.15
Riffle CRAB IV 1 2.824 31.69 8.32 -24.72 3.22
Riffle ELMIDAE 3 1.790 46.95 9.25 -26.80 0.79
Riffle ELMIDAE dupe 1 2.105 46.97 9.34 -26.75 0.63
Pool HYDROPSYCHIDAE 1 1.847 52.97 10.20 -27.65 1.47
Pool HYDROPSYCHIDAE dupe 1 2.451 50.83 10.32 -27.32 0.85
Pool HYDROPSYCHIDAE 1 1.531 46.32 11.37 -26.71 1.46
Riffle HYDROPSYCHIDAE 5 1.519 46.73 9.61 -27.41 1.72
Riffle L.P. n/a 4.803 45.46 1.25 ALD -0.19
Riffle L.P. n/a 2.822 42.63 1.74 -30.09 0.86
Riffle L.P. n/a 3.269 47.01 2.19 -30.94 0.58
Riffle OLIGOCHAETA 1 2.553 21.10 4.93 -26.68 1.39
Pool PERIPHYTON n/a filter 0.00 0.00 -27.11 2.54
Riffle PERIPHYTON n/a filter 0.00 0.00 -26.02 4.86
Riffle PERIPHYTON n/a filter 0.00 0.00 -24.26 -0.95
Riffle PERIPHYTON n/a filter 0.00 0.00 -27.92 2.10
Riffle PERIPHYTON n/a filter 0.00 0.00 -27.24 3.17
Riffle PERIPHYTON n/a filter 0.00 0.00 -24.44 -0.43
Pool PERLIDAE 1 1.709 48.46 11.41 -26.13 2.22
Riffle PERLIDAE 3 1.522 50.63 10.19 -27.09 2.59
Riffle SESTON n/a filter 0.00 0.00 -25.33 -1.77
Riffle SESTON dupe n/a filter 0.00 0.00 -27.11 0.56
160
Stable Isotope Data Fortuna - September ‘03
LOCATION SAMPLE Number Sample Wt. Total %C Total %N δ13 C δ15 N (mg) vs. PDB vs. Air
Riffle LIBELLULIDAE 1 1.825 48.26 10.74 -26.14 0.31
Riffle LIBELLULIDAE 1 2.393 49.89 9.63 -27.09 -0.22
Riffle LIBELLULIDAE 1 1.487 47.27 9.84 -26.89 1.89
Riffle LIBELLULIDAE 1 1.409 50.31 9.88 -25.18 2.03
Riffle LIBELLULIDAE 1 2.319 49.58 10.80 -27.12 0.11
Riffle LIBELLULIDAE 1 1.412 49.99 10.44 -27.16 1.34
Riffle Crab I 1 1.664 31.02 4.83 -25.53 3.93
Riffle Crab I 1 2.045 29.83 6.02 -24.24 2.75
Riffle Crab I 1 1.069 32.53 6.60 -24.97 3.15
Riffle Crab I 1 1.331 32.87 7.12 -24.95 2.97
Riffle Crab I 1 1.498 33.51 6.36 -24.77 3.28
Riffle Crab I 1 1.036 43.62 2.97 -27.47 2.77
Riffle Crab I 1 2.188 26.63 5.29 -24.01 2.31
Riffle Crab I 1 1.421 35.86 5.10 -25.83 2.94
Riffle Crab I 1 1.918 34.96 4.42 -25.96 2.72
Riffle Crab II 1 1.965 29.94 5.76 -24.45 3.42
Riffle Crab II 1 1.625 32.96 5.89 -25.04 3.74
Riffle Crab II 1 1.816 29.24 6.04 -24.09 3.06
Riffle Crab II 1 2.911 39.45 5.99 -27.41 2.83
Riffle Crab II 1 1.522 34.38 5.60 -25.58 3.65
Riffle Crab II 1 1.114 28.03 6.13 -23.86 3.79
Riffle Crab II 1 1.714 29.93 5.80 -24.48 3.58
Riffle Crab III 1 2.222 26.26 5.13 -23.76 2.86
Riffle Crab III 1 2.056 31.10 5.34 -25.25 2.96
Riffle Crab III 1 1.426 34.99 6.68 -25.61 3.43
Riffle Crab III 1 3.393 34.64 5.51 -25.96 2.37
Riffle Gyrinidae larvae 1 1.791 50.17 10.81 -26.93 1.32
Riffle Hydropshychidae 2 1.499 47.06 8.11 -27.60 1.66
Riffle Hydropsychidae* 10 1.483 48.22 7.62 -28.28 2.33
Riffle LP n/a 2.557 41.63 1.57 -27.71 2.67
Riffle LP n/a 2.138 43.79 1.67 -29.95 1.76
Riffle LP n/a 2.385 25.71 1.03 -30.02 1.85
Riffle LP n/a 2.754 25.95 1.06 -30.33 0.80
Riffle LP n/a 2.124 37.93 1.51 -31.30 0.82
Riffle LP n/a 2.167 45.99 1.62 -30.90 1.88
Riffle LP n/a 2.113 39.30 1.54 -28.21 2.84
Riffle LP n/a 2.591 47.51 2.20 -30.72 2.96
Riffle Naucoridae 1 1.224 48.33 11.23 -26.57 1.00
Riffle PERLIDAE 1 1.050 51.28 9.96 -27.05 3.78
Riffle PERLIDAE 1 1.517 49.37 10.68 -26.97 3.53
Riffle CALOPTERYGIDAE 1 1.060 46.12 11.02 -26.19 3.08
Riffle CALOPTERYGIDAE 1 1.067 49.97 10.88 -26.75 2.92
161
Stable Isotope Data Fortuna - January ‘04
LOCATION SAMPLE NUMBER Sample
Wt. Total %C Total %N δ13 C δ15 N (mg) vs. PDB vs. Air Pool LIBELLULIDAE 1 1.604 48.25 11.12 -24.84 1.13 Riffle LIBELLULIDAE 1 2.339 46.27 11.43 -26.09 0.83
Riffle LIBELLULIDAE 1 1.445 Sample
Lost Sample
Lost Riffle BAETIDAE 1 1.100 42.67 10.22 -28.01 -0.14 Riffle BAETIDAE 1 1.118 47.70 9.88 -27.43 2.04 Riffle BAETIDAE 1 1.047 47.69 10.47 -26.86 2.04
Riffle BAETIDAE 1 1.189 Sample
Lost Sample
Lost Riffle CRAB I 1 1.949 31.96 5.90 -25.03 2.99 Riffle CRAB I 1 1.551 40.47 3.22 -25.28 2.88 Riffle CRAB I 2 1.874 29.44 5.84 -24.05 3.22
Pool CRAB II 2 2.310 Sample
Lost Sample
Lost Riffle CRAB IX 1 3.137 29.89 9.28 -22.21 1.58 Riffle ELMIDAE 1 1.356 47.20 8.79 -27.72 0.77 Riffle ELMIDAE 1 1.359 46.60 9.52 -26.76 0.81 Riffle ELMIDAE 1 1.507 46.47 9.10 -26.51 0.94 Pool FBOM n/a Filter 35.30 2.86 -28.74 0.37 Pool FBOM n/a Filter 33.38 2.75 -28.70 1.02 Pool FBOM n/a Filter 21.63 1.77 -28.37 1.55 Pool FBOM n/a Filter 56.75 3.61 -28.82 1.48 Pool FBOM n/a Filter 45.332 3.16 -28.81 0.59
Pool FBOM n/a Filter Sample
Lost Sample
Lost
Pool FBOM n/a Filter Sample
Lost Sample
Lost Pool GERIIDAE 1 1.469 51.640 10.97 -26.18 3.66 Riffle HYDROPSYCHIDAE 5 0.978 47.75 8.75 -27.69 1.42 Riffle HYDROPSYCHIDAE 5 1.511 47.01 9.79 -27.41 1.92 Riffle HYDROPSYCHIDAE 1 1.331 45.32 9.75 -26.64 2.06 Riffle HYDROPSYCHIDAE 12 2.068 45.67 10.05 -26.18 1.83 Riffle HYDROPSYCHIDAE 3 1.548 53.50 10.21 -27.62 2.08 Riffle HYDROPSYCHIDAE 5 1.277 45.84 8.66 -27.42 2.11
Riffle HYDROPSYCHIDAE dupe 5 2.515 10.27 2.03 -27.49 2.08
Pool L P n/a 2.584 45.099 1.43 -30.08 0.06 Pool L P n/a 2.906 36.77 1.39 -30.49 1.33 Pool L P n/a 2.050 38.90 1.44 -30.97 1.28 Pool L P n/a 2.798 44.08 1.57 -29.78 0.48
Pool L P n/a 2.170 Sample
Lost Sample
Lost Riffle L P n/a 2.413 43.37 0.89 -28.52 -2.65 Riffle L P n/a 2.807 49.53 1.18 -29.54 -1.57 Riffle L P n/a 2.582 42.48 1.13 -29.89 -0.67 Riffle L P n/a 2.233 41.84 1.16 -30.04 0.73 Riffle L P n/a 2.240 49.13 1.33 -28.81 -0.93
Riffle L P n/a 2.894 Sample
Lost Sample
Lost
Riffle L P n/a 2.634 Sample
Lost Sample
Lost Riffle L P n/a 2.188 38.68 2.15 -29.87 1.89 Riffle L P n/a 2.707 39.28 2.19 -29.98 1.83
162
LOCATION SAMPLE NUMBER Sample
Wt. Total %C Total %N δ13 C δ15 N (mg) vs. PDB vs. Air Riparian MOSS n/a 2.983 7.43 0.54 -28.44 1.05 Riparian MOSS n/a 2.609 4.110 0.29 -29.53 -0.45 Riparian MOSS n/a 4.426 7.31 0.55 -28.04 -0.04 Riparian MOSS n/a 2.819 16.50 0.63 -30.43 -0.93 Riparian MOSS n/a 2.699 7.32 0.50 -30.39 -0.17 Riparian MOSS n/a 1.661 3.53 0.32 -30.21 1.74
Riparian MOSS n/a 1.926 Sample
Lost Sample
Lost Pool NAUCORIDAE 1 1.539 48.48 10.60 -25.95 1.15 Riffle NAUCORIDAE 1 1.134 48.722 10.37 -27.28 1.21 Pool PERIPHYTON n/a Filter 6.821 0.97 -26.51 5.11 Pool PERIPHYTON n/a Filter 5.700 0.78 -26.61 4.24 Pool PERIPHYTON n/a Filter 19.11 2.73 -25.10 1.75 Pool PERIPHYTON n/a Filter 9.62 1.56 -26.19 1.71
Pool PERIPHYTON n/a Filter Sample
Lost Sample
Lost Riffle PERIPHYTON n/a Filter 15.36 2.28 -25.96 0.84 Riffle PERIPHYTON n/a Filter 12.15 1.97 -24.39 2.02 Riffle PERIPHYTON n/a Filter 11.42 1.78 -26.61 2.06 Riffle PERIPHYTON n/a Filter 23.20 3.76 -25.44 4.85 Riffle PERIPHYTON n/a filter 8.38 1.20 -26.53 2.88 Riffle PERIPHYTON n/a Filter 7.767 1.19 -27.92 2.31
Pool PERLIDAE 1
1.158
Sample
Lost
Sample Lost
Pool PERLIDAE 1 1.072 49.10 10.34 -26.64 2.81 Riffle PERLIDAE 1 1.451 49.58 10.90 -25.93 2.97 Riffle PERLIDAE 1 2.765 59.55 11.92 -26.65 3.13 Riparian RIPARIAN n/a 2.224 41.42 1.34 -32.68 -2.23 Riparian RIPARIAN n/a 2.368 43.872 2.10 -30.70 1.00 Riparian RIPARIAN n/a 2.093 44.764 2.10 -30.75 1.09 Riparian RIPARIAN n/a 2.976 35.93 1.79 -33.79 0.07 Riparian RIPARIAN n/a 3.131 42.07 2.32 -32.67 1.62
Riparian RIPARIAN n/a
2.319
Sample
Lost
Sample Lost
Riparian RIPARIAN n/a 2.334 43.10 3.03 -30.88 0.64 Riparian RIPARIAN n/a 2.724 42.96 3.12 -31.30 0.62 Riffle SESTON n/a Filter 8.09 0.77 -29.18 5.88 Riffle SESTON n/a Filter 4.836 0.39 -28.13 4.87 Pool SHRIMP IX 1 1.959 38.72 8.37 -28.74 5.94 Pool VELIIDAE 1 0.921 49.67 10.75 -26.22 3.12 Pool CALOPTERYGIDAE 1 1.415 43.238 10.48 -26.12 2.25
163
Stable Isotope Data Fortuna - May ‘04 Sample Wt. Total %C Total %N δ13C δ15N LOCATION SAMPLE NUMBER (mg) vs. PDB vs. Air Pool LIBELLULIDAE 1 1.604 48.25 11.12 -24.84 1.13 Riffle LIBELLULIDAE 1 2.339 46.27 11.43 -26.09 0.83 Riffle LIBELLULIDAE 1 1.445 Sample Lost Sample Lost
Riffle BAETIDAE 3 1.100 42.67 10.22 -28.01 -0.14 Riffle BAETIDAE 2 1.118 47.70 9.88 -27.43 2.04 Riffle BAETIDAE dupe 2 1.047 47.69 10.47 -26.86 2.04 Riffle BAETIDAE 1 1.189 Sample Lost Sample Lost
Riffle CRAB I 2 1.949 31.96 5.90 -25.03 2.99 Riffle CRAB I 1 1.551 40.47 3.22 -25.28 2.88 Riffle CRAB I 1 1.874 29.44 5.84 -24.05 3.22 Pool CRAB II 1 2.310 Sample Lost Sample Lost
Riffle CRAB IX 1 3.137 29.89 9.28 -22.21 1.58 Riffle ELMIDAE 4 1.356 47.20 8.79 -27.72 0.77 Riffle ELMIDAE 2 1.359 46.60 9.52 -26.76 0.81 Riffle ELMIDAE dupe 2 1.507 46.47 9.10 -26.51 0.94 Pool FBOM n/a n/a 35.30 2.86 -28.74 0.37 Pool FBOM dupe n/a n/a 33.38 2.75 -28.70 1.02 Pool FBOM n/a n/a 21.63 1.77 -28.37 1.55 Pool FBOM n/a n/a 56.75 3.61 -28.82 1.48 Pool FBOM n/a n/a 45.332 3.16 -28.81 0.59 Pool FBOM n/a n/a Sample Lost Sample Lost
Pool FBOM dupe n/a n/a Sample Lost Sample Lost
Pool GERIIDAE 4 1.469 51.640 10.97 -26.18 3.66 Riffle HYDROPSYCHIDAE 6 0.978 47.75 8.75 -27.69 1.42 Riffle HYDROPSYCHIDAE 9 1.511 47.01 9.79 -27.41 1.92 Riffle HYDROPSYCHIDAE 1 1.331 45.32 9.75 -26.64 2.06 Riffle HYDROPSYCHIDAE dupe 8 2.068 45.67 10.05 -26.18 1.83 Riffle HYDROPSYCHIDAE 1 1.548 53.50 10.21 -27.62 2.08 Riffle HYDROPSYCHIDAE 1 1.277 45.84 8.66 -27.42 2.11 Riffle HYDRPSYCHIDAE dupe 1 2.515 10.27 2.03 -27.49 2.08 Pool L P n/a 2.584 45.099 1.43 -30.08 0.06 Pool L P n/a 2.906 36.77 1.39 -30.49 1.33 Pool L P dupe n/a 2.050 38.90 1.44 -30.97 1.28 Pool L P n/a 2.798 44.08 1.57 -29.78 0.48 Pool L P n/a 2.170 Sample Lost Sample Lost
Riffle L P n/a 2.413 43.37 0.89 -28.52 -2.65 Riffle L P dupe n/a 2.807 49.53 1.18 -29.54 -1.57 Riffle L P n/a 2.582 42.48 1.13 -29.89 -0.67 Riffle L P n/a 2.233 41.84 1.16 -30.04 0.73 Riffle L P n/a 2.240 49.13 1.33 -28.81 -0.93 Riffle L P n/a 2.894 Sample Lost Sample Lost
Riffle L P dupe n/a 2.634 Sample Lost Sample Lost
Riffle L P n/a 2.188 38.68 2.15 -29.87 1.89 Riffle L P dupe n/a 2.707 39.28 2.19 -29.98 1.83 Riparian MOSS n/a 2.983 7.43 0.54 -28.44 1.05
164
Sample Wt. Total %C Total %N δ13C δ15N LOCATION SAMPLE NUMBER (mg) vs. PDB vs. Air Riparian MOSS n/a 2.609 4.110 0.29 -29.53 -0.45 Riparian MOSS n/a 4.426 7.31 0.55 -28.04 -0.04 Riparian MOSS n/a 2.819 16.50 0.63 -30.43 -0.93 Riparian MOSS n/a 2.699 7.32 0.50 -30.39 -0.17 Riparian MOSS dupe n/a 1.661 3.53 0.32 -30.21 1.74 Riparian MOSS n/a 1.926 Sample Lost Sample Lost
Pool NAUCORIDAE 1 1.539 48.48 10.60 -25.95 1.15 Riffle NAUCORIDAE 1 1.134 48.722 10.37 -27.28 1.21 Pool PERIPHYTON n/a n/a 6.821 0.97 -26.51 5.11 Pool PERIPHYTON dupe n/a n/a 5.700 0.78 -26.61 4.24 Pool PERIPHYTON n/a n/a 19.11 2.73 -25.10 1.75 Pool PERIPHYTON n/a n/a 9.62 1.56 -26.19 1.71 Pool PERIPHYTON n/a n/a Sample Lost Sample Lost
Riffle PERIPHYTON n/a n/a 15.36 2.28 -25.96 0.84 Riffle PERIPHYTON n/a n/a 12.15 1.97 -24.39 2.02 Riffle PERIPHYTON n/a n/a 11.42 1.78 -26.61 2.06 Riffle PERIPHYTON n/a n/a 23.20 3.76 -25.44 4.85 Riffle PERIPHYTON n/a n/a 8.38 1.20 -26.53 2.88 Riffle PERIPHYTON n/a n/a 7.767 1.19 -27.92 2.31 Pool PERLIDAE 1 1.158 Sample Lost Sample Lost
Riffle PERLIDAE 2 1.072 49.10 10.34 -26.64 2.81 Riffle PERLIDAE 5 1.451 49.58 10.90 -25.93 2.97 Riffle PERLIDAE 2 2.765 59.55 11.92 -26.65 3.13 CH 0 RIPARIAN n/a 2.224 41.42 1.34 -32.68 -2.23 Riparian RIPARIAN n/a 2.368 43.872 2.10 -30.70 1.00 Riparian RIPARIAN dupe n/a 2.093 44.764 2.10 -30.75 1.09 Riparian RIPARIAN n/a 2.976 35.93 1.79 -33.79 0.07 Riparian RIPARIAN n/a 3.131 42.07 2.32 -32.67 1.62 Riparian RIPARIAN n/a 2.319 Sample Lost Sample Lost
Riparian RIPARIAN n/a 2.334 43.10 3.03 -30.88 0.64 Riparian RIPARIAN dupe n/a 2.724 42.96 3.12 -31.30 0.62 Riffle SESTON n/a n/a 8.09 0.77 -29.18 5.88 Riffle SESTON n/a n/a 4.836 0.39 -28.13 4.87 Pool SHRIMP IX 1 1.959 38.72 8.37 -28.74 5.94 Pool VELIIDAE 1 0.921 49.67 10.75 -26.22 3.12 Riffle CALOPTERYGIDAE 1 1.415 43.238 10.48 -26.12 2.25
165
Stable Isotope Data Fortuna - September ‘04
LOCATION SAMPLE NUMBER Sample
Wt. Total %C delta N15 δ13C δ15N (mg) vs. Air vs. PDB vs. Air Riffle ADULT COL 1 1.073 52.14 2.14 -26.82 2.14
Riffle ADULT COL 1 1.365 52.16 1.89 -26.27 1.89
Riffle BAETIDAE 2 1.012 55.36 -0.84 -26.33 -0.84
Riffle CRAB I 1 1.047 33.50 2.55 -26.67 2.55
Riffle CRAB I 1 1.207 35.61 1.84 -25.52 1.84
Riffle CRAB I dupe 1 1.215 24.69 1.72 -23.53 1.72
Riffle CRAB I 1 1.174 39.79 3.53 -26.34 3.53
Riffle CRAB I 1 2.277 37.32 3.39 -26.25 3.39
Riffle CRAB I 1 1.240 34.82 3.54 -25.73 3.54
Riffle CRAB II 1 2.328 27.86 2.60 -23.88 2.60
Riffle CRAB II 1 2.139 28.40 2.81 -23.93 2.81
Riffle CRAB II dupe 1 2.039 26.35 2.83 -23.32 2.83
Riffle CRAB III 1 2.341 26.72 3.05 -24.02 3.05
Riffle CRAB VI 1 2.768 21.84 4.81 -22.33 4.81
Riffle EPHEMEROPTERA 3 1.016 44.98 -1.54 -28.74 -1.54
Pool GERIDAE 1 1.442 45.54 3.30 -26.32 3.30
Riffle GYRINIDAE LARVA 1 1.634 46.88 1.31 -25.77 1.31
Riffle GYRINIDAE LARVA dupe 1 1.382 44.30 1.91 -25.76 1.91
Riffle GYRINIDAE LARVA 1 1.672 45.70 1.56 -25.51 1.56
Riffle HYDROPSYCHIDAE 3 1.338 47.75 1.42 -27.32 1.42
Riffle HYDROPSYCHIDAE 3 1.739 50.92 1.44 -28.33 1.44
Riffle HYDROPSYCHIDAE 3 1.138 50.50 1.65 -28.21 1.65
Riffle HYDROPSYCHIDAE 1 1.331 47.00 1.56 -27.46 1.56
Riffle HYDROPSYCHIDAE dupe 1 1.039 46.65 2.05 -27.68 2.05
Riffle HYDROPSYCHIDAE 1 1.359 48.24 1.50 -27.14 1.50
Riffle HYDROPSYCHIDAE 1 1.249 48.57 1.09 -28.18 1.09
Riffle HYDROPSYCHIDAE 1 1.502 47.15 2.05 -27.47 2.05
Riffle HYDROPSYCHIDAE 1 1.179 50.72 2.26 -27.98 2.26
Riffle HYDROPSYCHIDAE 1 1.659 49.73 1.89 -28.02 1.89
Riffle HYDROPSYCHIDAE dupe 1 1.748 46.53 1.57 -27.46 1.57
Riffle HYDROPSYCHIDAE 1 1.507 48.53 1.94 -27.10 1.94
Riffle HYDROPSYCHIDAE 1 1.924 49.98 1.00 -27.48 1.00
Riffle HYDROPSYCHIDAE 1 1.145 46.87 2.25 -27.08 2.25
Riffle HYDROPSYCHIDAE 1 1.156 48.69 1.97 -27.14 1.97
Riffle HYDROPSYCHIDAE 1 1.041 51.62 2.46 -28.13 2.46
Riffle HYDROPSYCHIDAE dupe 1 2.252 51.44 1.43 -28.21 1.43
Riffle HYDROPSYCHIDAE 1 1.021 46.05 1.08 -27.79 1.08
Riffle HYDROPSYCHIDAE 3 1.771 52.12 1.16 -27.69 1.16
Riffle HYDROPSYCHIDAE 3 2.045 48.01 0.98 -27.86 0.98
Riffle LIBELLULIDAE 3 1.389 47.93 1.54 -27.07 1.54
Riffle LIBELLULIDAE 2 1.733 47.35 0.48 -24.41 0.48
Riffle LIBELLULIDAE dupe 2 1.622 48.26 0.85 -24.69 0.85
Riffle LIBELLULIDAE 1 1.517 47.84 0.66 -27.12 0.66
Riffle LIBELLULIDAE 1 1.399 47.01 0.65 -26.74 0.65
Pool NAUCORIDAE 1 1.285 45.30 1.58 -26.07 1.58
166
LOCATION SAMPLE NUMBER Sample
Wt. Total %C delta N15 δ13C δ15N (mg) vs. Air vs. PDB vs. Air Pool NAUCORIDAE 1 1.615 48.13 2.36 -26.17 2.36
Riffle PERLIDAE 1 1.223 51.68 2.87 -27.02 2.87
Riffle PERLIDAE dupe 1 1.468 51.17 2.68 -27.00 2.68
Riffle PERLIDAE 3 1.339 48.16 3.69 -26.10 3.69
Riffle PERLIDAE 2 1.050 48.14 4.41 -25.86 4.41
Riffle PERLIDAE 1 2.957 53.60 2.07 -28.51 2.07
Riffle PERLIDAE 1 1.298 53.81 2.31 -27.82 2.31
Riffle PERLIDAE 1 1.666 53.26 2.63 -27.62 2.63
Riffle PERLIDAE dupe 1 1.603 54.32 2.78 -27.70 2.78
Riffle PERLIDAE 1 1.583 53.23 2.61 -27.74 2.61
Pool PTILODACTILIDAE 1 1.307 49.65 0.96 -25.96 0.96
Riffle PTILODACTILIDAE 1 1.510 47.66 1.52 -27.43 1.52
Riffle TRICH SMALL 2 0.929 47.94 2.09 -27.68 2.09
Riffle TRICH SMALL 2 1.235 47.90 1.41 -27.51 1.41
Riffle TRICH SMALL dupe 2 1.191 47.65 1.29 -27.70 1.29
Riffle TRICH SMALL 2 1.277 47.32 1.35 -27.93 1.35
Riffle TRICH SMALL 3 1.331 41.41 2.17 -27.44 2.17
Riffle TRICH SMALL 3 1.398 46.17 2.23 -26.84 2.23
Riffle TRICH SMALL 3 1.362 45.16 1.73 -27.43 1.73
Riffle TRICH SMALL 3 1.222 50.37 2.19 -26.63 2.19
Riffle TRICH SMALL dupe 3 1.178 48.65 2.12 -27.33 2.12
Pool VELIIDAE 4 1.422 50.17 3.11 -26.25 3.11
Riffle ZYGOPTERA 3 1.475 52.14 2.95 -26.73 2.95
Pool LP n/a 2.775 46.77 0.97 -29.37 0.97
Riffle LP n/a 3.526 41.32 2.27 -30.07 2.27
Riffle LP n/a 3.568 24.43 0.89 -29.86 0.89
Riffle LP dupe n/a 3.621 33.32 0.97 -29.89 0.97
Riffle LP n/a 3.021 45.70 0.23 -29.46 0.23
Riffle LP n/a 4.202 43.49 2.05 -28.43 2.05
Pool LP n/a 3.566 45.65 1.71 -29.48 1.71
Riffle LP n/a 3.740 47.22 1.96 -30.72 1.96
Pool LP n/a 2.652 38.01 0.99 -29.79 0.99
Pool LP dupe n/a 2.449 45.26 0.98 -30.10 0.98
Pool LP n/a 2.556 42.70 2.35 -30.44 2.35
Riffle LP n/a 3.230 44.23 2.18 -31.17 2.18
Riparian MOSS n/a 3.364 19.77 0.62 -30.29 0.62
Riparian MOSS n/a 3.111 39.97 -1.68 -30.24 -1.68
Riparian MOSS n/a 2.680 44.72 -0.98 -30.23 -0.98
Riparian MOSS dupe n/a 2.463 45.32 -0.81 -30.13 -0.81
Riparian MOSS n/a 3.057 12.31 0.06 -29.34 0.06
Riparian MOSS n/a 3.526 15.66 0.89 -30.26 0.89
Riparian MOSS n/a 3.391 13.05 1.59 -30.41 1.59
Riparian RIPARIAN n/a 2.490 40.65 1.74 -32.73 1.74
Riparian RIPARIAN n/a 2.459 42.47 0.41 -32.05 0.41
Riparian RIPARIAN dupe n/a 2.749 41.40 0.40 -32.06 0.40
Riparian RIPARIAN n/a 2.297 42.94 0.74 -32.17 0.74
167
LOCATION SAMPLE NUMBER Sample
Wt. Total %C delta N15 δ13C δ15N (mg) vs. Air vs. PDB vs. Air Riparian RIPARIAN n/a 2.306 39.13 2.45 -32.36 2.45
Riparian RIPARIAN n/a 3.192 42.29 1.16 -33.45 1.16
Riparian RIPARIAN n/a 3.150 39.21 1.83 -34.29 1.83
168
Stable Isotope Data Fortuna - May ‘05 LOCATION SAMPLE NUMBER Sample Wt. Total %C Total % N δ13C δ15N (mg) vs. PDB vs. Air
R. war 1 1.980 12.97 2.69 -26.39 4.28 R. war 1 1.195 39.41 9.51 -26.40 5.50 R. war - dupe 1 1.297 19.74 4.02 -28.19 5.59 Riffle ADULT COL 1 0.611 48.90 11.26 -26.82 2.14 Riffle ADULT COL 1 1.369 48.71 10.06 -26.24 -0.31
Riffle ADULT COL - dupe 1 1.263 51.61 10.55 -26.40 -0.18
Riffle ANIS 1 2.192 49.14 11.74 -27.02 1.23 Riffle ANIS 1 1.246 48.63 11.84 -27.44 1.24 Riffle ANIS 1 0.922 53.10 12.82 -29.32 2.93 Riffle ANIS 1 1.976 50.42 11.62 -26.36 0.76 Riffle ANIS 1 1.560 48.95 11.54 -24.99 0.86 Riffle ANIS 1 1.020 48.71 10.95 -24.25 0.71 Riffle ANIS - dupe 1 1.165 48.12 11.08 -24.05 0.67 Riffle ANIS 1 1.179 45.46 11.59 -24.01 0.82 Riffle BS TRICH 1 1.148 46.97 9.65 -27.09 2.02 Riffle BS TRICH 1 1.256 46.18 9.11 -27.12 2.66 Riffle BS TRICH 1 1.347 46.02 8.07 -27.43 1.71 Riffle BS TRICH 1 1.434 46.82 10.24 -26.78 2.26 Riffle BS TRICH - dupe 1 1.309 46.15 10.87 -24.13 0.31 Riffle BS TRICH 1 2.062 52.14 9.97 -27.73 1.79 Riffle BS TRICH 1 1.129 52.48 9.74 -27.64 2.18 Riffle BS TRICH 1 1.177 50.46 9.28 -28.12 1.60 Riffle BS TRICH 1 2.233 51.12 9.40 -27.93 1.44 Riffle BS TRICH 1 1.991 36.34 7.45 -27.55 1.73 Riffle BS TRICH - dupe 1 1.917 49.82 9.85 -27.70 1.61 Riffle BS TRICH 1 1.559 48.27 9.71 -27.07 1.57 Riffle BS TRICH 1 2.634 47.33 10.82 -27.22 0.32 Riffle BS TRICH 1 1.167 45.43 8.89 -27.20 1.61 Riffle BS TRICH 1 1.517 43.84 8.95 -26.73 1.26 Riffle BS TRICH 1 1.226 44.88 8.76 -26.80 1.27 Riffle BS TRICH - dupe 1 1.236 44.67 9.21 -26.68 1.43 Riffle BS TRICH 1 2.382 46.76 10.29 -26.88 0.85 Riffle BS TRICH 1 1.361 47.60 10.39 -26.76 1.23 Riffle BS TRICH 1 1.538 47.42 9.70 -26.85 1.16 Riffle BS TRICH 1 1.436 44.14 10.77 -25.92 2.14 Riffle CRAB I 1 1.083 29.23 5.69 -24.15 4.17 Riffle CRAB I - dupe 1 1.548 28.42 5.28 -23.96 4.02 Riffle CRAB I 1 2.156 29.95 6.23 -24.27 3.00 Riffle CRAB I 1 2.094 30.02 5.55 -24.54 3.20 Riffle CRAB II 1 2.643 31.18 6.76 -24.50 3.00 Riffle CRAB II 1 2.560 26.02 5.28 -23.02 3.67 Riffle CRAB II 1 1.394 40.63 9.70 -25.87 3.14 Riffle CRAB II - dupe 1 1.130 41.58 9.31 -26.10 3.91 Riffle CRAB III 1 4.243 22.46 3.86 -22.97 2.76 Riffle CRABIII 1 2.395 38.47 8.80 -25.19 4.48
169
LOCATION SAMPLE NUMBER Sample Wt. Total %C Total % N δ13C δ15N (mg) vs. PDB vs. Air
Riffle ELMIDAE 1 1.283 42.28 9.63 -26.16 1.63 Riffle ELMIDAE 1 1.207 53.02 10.45 -27.33 0.96 Riffle ELMIDAE 1 1.032 50.30 9.24 -28.05 0.73 Riffle ELMIDAE - dupe 1 1.013 50.10 10.25 -27.62 0.76 Riffle ELMIDAE 1 0.989 49.46 8.94 -28.45 1.44 Riffle ELMIDAE 1 1.497 46.42 11.21 -26.60 0.47 Riffle ELMIDAE 1 1.046 48.34 10.31 -26.18 1.10 Riffle ELMIDAE 1 1.496 45.80 9.44 -26.76 1.53 Riffle ELMIDAE - dupe 1 2.239 46.07 10.29 -26.47 1.07 Riffle EPHEM 1 2.065 46.18 9.67 -26.65 1.23 Pool GERIIDAE 1 0.328 49.86 12.41 -25.54 3.94 Pool GERIIDAE 1 0.478 49.89 12.48 -25.97 3.93 Pool GERIIDAE 1 1.111 53.51 10.89 -26.63 5.10 Pool GERIIDAE 1 0.852 51.35 11.72 -26.16 4.98 Riffle GYR LARV 1 1.239 47.32 12.04 -25.88 2.89 Riffle GYR LARV 1 1.645 45.77 12.12 -26.08 2.07 Riffle GYR LARV - dupe 1 2.020 45.24 11.84 -26.22 2.25 Riffle HYDROPSY 1 1.517 49.57 11.08 -27.10 3.89 Riffle HYDROPSY 1 1.958 49.98 9.61 -27.67 4.16 Riffle HYDROPSY 1 1.777 49.05 10.57 -27.10 4.27 Riffle HYDROPSY 1 1.267 47.23 10.81 -26.81 4.46 Riffle HYDROPSY 1 2.115 50.69 10.31 -27.78 4.40 Riffle HYDROPSY 1 1.022 46.60 7.33 -27.96 0.98 Riffle HYDROPSY 1 1.353 52.96 9.23 -27.90 1.97 Riffle HYDROPSY 1 1.376 50.13 9.83 -27.26 1.41 Riffle HYDROPSY 1 1.922 50.17 10.71 -27.05 0.89 Riffle HYDROPSY 1 1.085 50.72 9.49 -27.78 1.17 Riffle HYDROPSY - dupe 1 1.281 50.62 9.38 -27.71 1.36 Riffle HYDROPSY 1 1.599 48.18 9.04 -27.44 1.15 Riffle HYDROPSY 1 1.226 45.36 8.78 -27.24 2.17 Riffle HYDROPSY 1 1.466 47.75 9.24 -27.18 0.92 Riffle HYDROPSY 1 1.105 48.15 9.72 -27.52 0.86 Riffle HYDROPSY 1 1.301 44.97 9.65 -26.15 1.25 Riffle HYDROPSY 1 1.124 46.98 10.46 -26.14 1.79 Riffle HYDROPSY 1 1.300 44.85 9.62 -26.58 1.62 Riffle HYDROPSY 1 1.628 46.53 11.49 -27.02 1.13 Riffle HYDROPSY - dupe 1 1.746 46.02 11.26 -27.03 1.00 Riffle HYDROPSY 1 1.409 47.47 9.99 -27.02 1.63 Riffle FIL ALGAE n/a 3.009 33.90 3.40 -25.51 0.13 Riffle FIL ALGAE n/a 2.506 32.55 3.13 -25.93 0.24 Riffle FIL ALGAE n/a 2.659 23.23 2.26 -26.73 0.64 Riffle FIL ALGAE n/a 3.353 26.02 2.48 -26.25 0.38 Riffle FIL ALGAE - dupe n/a 2.473 19.96 1.93 -26.00 0.14 Pool LP n/a 4.937 41.51 1.51 -27.55 1.96 Riffle LP n/a 3.230 41.06 1.46 -27.41 2.38 Riffle LP n/a 3.817 44.03 1.90 -30.32 0.46
170
LOCATION SAMPLE NUMBER Sample Wt. Total %C Total % N δ13C δ15N (mg) vs. PDB vs. Air
Pool LP n/a 2.663 44.72 1.89 -29.91 -0.01 Pool LP - dupe n/a 4.029 46.57 2.00 -30.22 -0.19 Riffle LP n/a 3.305 41.67 1.78 -27.67 2.15 Pool LP n/a 3.373 45.60 1.67 -29.27 1.72 Riffle LP n/a 3.746 46.03 1.47 -28.86 -1.57 Pool LP n/a 3.651 42.26 1.54 -30.01 0.20 Riffle LP n/a 4.848 43.00 1.65 -27.95 1.58 Riffle LP - dupe n/a 3.864 42.13 1.61 -27.44 1.90 Riffle LP n/a 3.606 47.26 0.95 -29.94 -0.65 Pool LP n/a 3.198 49.01 1.02 -30.43 0.79 Pool LP n/a 5.569 9.27 0.57 -27.12 0.42 Riparian MOSS n/a 3.560 7.28 0.43 -27.38 0.71 Riparian MOSS n/a 2.435 21.45 0.72 -30.61 0.59 Riparian MOSS n/a 3.613 26.53 0.76 -30.43 -0.18 Riparian MOSS - dupe n/a 4.118 44.10 1.44 -30.03 -1.64 Riparian MOSS n/a 4.478 16.92 0.78 -29.14 -0.54 Riparian MOSS n/a 2.455 45.84 1.35 -28.94 -0.53 Riparian MOSS n/a 5.294 21.46 1.17 -28.81 1.41 Riffle PERLIDAE 1 2.271 49.25 10.72 -26.86 2.73 Riffle PERLIDAE - dupe 1 1.217 50.56 10.38 -26.77 3.47 Riffle PERLIDAE 1 1.696 54.40 9.47 -27.04 3.77 Riffle PERLIDAE 1 2.719 51.82 11.66 -27.12 2.62 Riffle PERLIDAE 1 1.223 49.10 12.56 -24.40 2.34 Riffle PERLIDAE 1 1.700 52.54 9.58 -26.74 3.08 Riffle PERLIDAE 1 1.435 43.23 6.60 -27.14 2.88 Riffle PERLIDAE - dupe 1 1.148 47.90 9.73 -26.24 2.73 Riffle PERLIDAE 1 1.083 51.55 11.98 -26.63 3.23 Riffle PERLIDAE 1 1.327 49.47 11.32 -27.02 2.46 Riffle PERLIDAE 1 1.367 51.45 10.78 -27.46 2.22 Riffle PERLIDAE 1 1.739 51.05 11.43 -26.28 2.86 Riffle PERLIDAE - dupe 1 1.500 52.12 9.62 -26.95 3.18 Riffle PERLIDAE 1 1.058 49.80 10.91 -26.51 2.79 Riffle PERLIDAE 1 1.927 54.16 10.32 -26.71 3.06 Riffle PERLIDAE 1 1.790 50.16 11.80 -27.29 2.58 Riffle PERLIDAE 1 1.157 48.53 9.92 -26.44 4.29 Riffle PERLIDAE 1 1.035 49.29 12.08 -26.50 3.63 Riffle PERLIDAE - dupe 1 1.342 48.90 11.90 -26.49 3.69 Riffle PERLIDAE 1 1.188 47.87 11.42 -26.16 2.29 Riffle PSEPHENIDAE 1 0.565 49.31 9.44 -25.00 -1.06 Riffle PTILO 1 1.381 52.27 9.62 -26.33 3.16 Riffle PTILO 1 1.293 51.17 9.85 -26.10 3.21 Riffle PTILO 1 0.610 53.16 9.42 -26.71 3.25 Riffle PTILO - dupe 1 0.986 38.02 6.78 -26.89 3.22 Riffle PTILO 1 1.010 42.51 9.74 -26.05 2.85 Riffle PTILO 2 1.098 50.94 9.82 -25.95 3.11 Riparian RIP n/a 3.185 43.96 1.99 -32.99 0.75
171
LOCATION SAMPLE NUMBER Sample Wt. Total %C Total % N δ13C δ15N (mg) vs. PDB vs. Air
Riparian RIP n/a 4.079 39.50 2.49 -34.69 1.31 Riparian RIP n/a 3.217 44.24 2.09 -32.42 0.22 Riparian RIP - dupe n/a 3.290 43.06 2.01 -32.33 0.38 Riparian RIP n/a 3.162 42.33 2.44 -30.08 -0.63 Riparian RIP n/a 3.339 36.93 2.04 -31.24 1.98 Riparian RIP n/a 4.221 44.99 2.87 -32.86 -0.04 Riffle SM TRICH 1 1.332 45.91 8.85 -27.44 1.94 Riffle SM TRICH 1 0.694 48.24 9.26 -27.57 1.74 Riffle SM TRICH - dupe 1 0.901 47.91 7.66 -28.18 1.43 Riffle SM TRICH 2 1.518 47.88 7.08 -28.18 0.86 Riffle SM TRICH 2 1.964 22.81 3.91 -27.59 1.62 Riffle SM TRICH 2 0.834 47.49 9.21 -27.33 1.68 Riffle SM TRICH 2 1.111 47.96 9.08 -27.88 1.11 Riffle SM TRICH 1 0.894 47.31 8.92 -27.31 1.33 Riffle SM TRICH - dupe 1 0.956 49.42 9.99 -27.12 1.35 Riffle SM TRICH 1 1.003 47.30 8.37 -27.42 1.12 Riffle SM TRICH 1 1.244 48.49 9.81 -26.88 1.45 Riffle SM TRICH 1 1.121 43.94 9.36 -26.99 1.83 Riffle SM TRICH 1 1.204 48.10 9.23 -27.35 1.07 Riffle SM TRICH 1 0.477 47.00 10.04 -27.51 2.08 Riffle SM TRICH - dupe 1 0.890 46.18 9.50 -27.35 2.07 Riffle SM TRICH 1 1.658 47.99 11.28 -26.41 1.57 Riffle SM TRICH 1 1.179 48.79 9.83 -26.98 1.50 Riffle SM TRICH 1 1.949 46.11 8.81 -27.42 1.10 Riffle VELIIDAE 2 1.167 51.70 10.62 -26.26 3.26 Pool VELIIDAE 1 0.304 50.98 11.92 -25.69 3.73 Riffle ZYG 1 1.470 48.24 11.46 -26.27 1.60 Riffle ZYG - dupe 1 1.418 49.07 10.73 -26.66 1.39 Riffle ZYG 1 1.175 48.27 11.27 -26.86 1.69 Riffle ZYG 1 1.351 48.31 10.90 -25.43 1.90 Riffle SESTON n/a n/a n/a n/a -28.38 1.43 Riffle SESTON n/a n/a n/a n/a -28.37 1.74 Riffle SESTON - dupe n/a n/a n/a n/a -28.49 0.46 Riffle SESTON n/a n/a n/a n/a -27.24 0.72 Pool FBOM n/a n/a n/a n/a -28.30 1.62 Pool FBOM n/a n/a n/a n/a -28.13 -0.36 Pool FBOM - dupe n/a n/a n/a n/a -28.04 3.78 Pool FBOM n/a n/a n/a n/a -29.00 2.68 Pool FBOM n/a n/a n/a n/a -29.10 1.55 Pool FBOM n/a n/a n/a n/a -28.69 2.22 Pool FBOM n/a n/a n/a n/a -29.12 1.56 Riffle LP SCRAP n/a n/a n/a n/a -29.44 1.72 Riffle LP SCRAP n/a n/a n/a n/a -29.37 1.42 Riffle LP SCRAP n/a n/a n/a n/a -27.22 2.77 Riffle LP SCRAP - dupe n/a n/a n/a n/a -27.06 3.76 Riffle LP SCRAP n/a n/a n/a n/a -27.14 2.30
172
LOCATION SAMPLE NUMBER Sample Wt. Total %C Total % N δ13C δ15N (mg) vs. PDB vs. Air
Riffle LP SCRAP n/a n/a n/a n/a -26.45 2.70 Riffle LP SCRAP n/a n/a n/a n/a -28.64 3.16 Riffle LP SCRAP - dupe n/a n/a n/a n/a -27.40 2.57 Pool LP SCRAP n/a n/a n/a n/a -27.46 1.98 Pool LP SCRAP - dupe n/a n/a n/a n/a -27.81 1.89 Pool LP SCRAP n/a n/a n/a n/a -27.36 2.61 Pool LP SCRAP n/a n/a n/a n/a -27.83 3.20 Pool LP SCRAP n/a n/a n/a n/a -27.94 2.25 Pool LP SCRAP n/a n/a n/a n/a -28.74 2.13 Pool LP SCRAP n/a n/a n/a n/a -28.62 2.38 Riffle PERIPHYTON n/a n/a n/a n/a -21.21 0.99 Riffle PERIPHYTON n/a n/a n/a n/a -23.89 1.71 Riffle PERIPHYTON n/a n/a n/a n/a -22.97 0.39 Riffle PERIPHYTON n/a n/a n/a n/a -23.58 0.23 Riffle PERIPHYTON n/a n/a n/a n/a -30.59 1.24 Riffle PERIPHYTON n/a n/a n/a n/a -29.74 2.40
Riffle PERIPHYTON - dupe n/a n/a n/a n/a -23.36 0.57
Pool PERIPHYTON n/a n/a n/a n/a -28.45 2.30 Pool PERIPHYTON n/a n/a n/a n/a -29.24 1.36 Pool PERIPHYTON n/a n/a n/a n/a -26.00 1.30
Shrimp Leaf Pack FBOM Periphyton Biofilm Seston Inverts Crabs Tads Fish Snakes Lizard Frogs Spiders
Pre Decline El Cope 6/03 12 3 10 0 4 59 4 0 30 0 0 0 3 El Cope 9/03 6 0 0 0 0 36 0 0 32 0 0 0 0 El Cope 1/04 13 5 14 0 0 27 2 0 5 0 0 0 0 El Cope 5/04 14 7 13 0 2 193 4 0 44 0 0 0 0 El Cope 9/04 1 0 0 0 0 0 76 3 50 71 0 0 0 0 Snakes 174 Frogs 3 204 TADS 0 0 0 0 0 0 0 48 0 0 0 0 0 SUM 1 45 15 37 0 6 391 13 98 182 174 3 204 3 Post Decline El Cope 2/05 2 0 0 0 0 0 38 3 0 11 0 0 0 7 El Cope 5/05 0 13 5 12 13 3 51 7 0 22 0 0 0 0 Fortuna 6/03 0 0 0 0 0 0 22 11 0 10 0 0 0 0 Fortuna 9/03 0 8 0 0 0 0 24 20 0 0 0 0 0 0 Fortuna 1/04 0 14 7 11 0 2 56 7 0 0 0 0 0 0 Fortuna 5/04 1 14 6 12 0 2 64 6 0 0 0 0 0 0 Fortuna 9/04 0 12 0 0 0 0 96 11 0 0 0 0 0 0 Fortuna 5/05 0 12 7 10 16 4 126 10 2 0 0 0 0 0 SUM 1 60 20 33 16 8 388 65 2 10 0 0 0 0
Table.A.2 N
umber of individuals collected in each taxon
173
174
Vita Name: Meshagae Endrene Hunte-Brown Place and Date of Birth: Manchester, Jamaica. August 11, 1974 Country of Citizenship: Jamaica
EDUCATION: Current Ph.D. Environmental Science, Drexel University, Philadelphia,
Pennsylvania The Effects of Extirpation of Frogs on the Trophic Structure in Montane Streams in Panama.
1999 M.Phil. in Fresh Water Ecology, University of the West Indies – Mona Campus, Jamaica, W.I. The Longitudinal Zonation of Benthic Macroinvertebrates in the Buff Bay River, Jamaica W.I. (Master’s Thesis)
1996 B.S. In Zoology - Upper Second Class Honors University of the West Indies - Mona Campus, Jamaica, W.I. The Effects of Salt Spray on Coastal Plant Communities (Undergrad Research Project)
PROFESSIONAL EXPERIENCE: Present: Adjunct Professor Drexel University, Philadelphia, Pa 2003 - Present: Research Assistant Drexel University, Philadelphia, PA 1999 – 2000 Relief Manager Pierce Leahy Business Archives, Sharon Hill, Pa, East
Brunswick, NJ. ACADEMIC TEACHING EXPERIENCE: Winter 2005: Interim Instructor - Aquatic Ecology (Graduate Level) Drexel University, Philadelphia, PA 2002 -2003: Graduate Teaching Assistant - Drexel University, Philadelphia, PA 1996- 1999: Undergraduate Teaching Assistant - University of the West Indies, Jamaica AWARDS: 1993-1994 - Departmental prize for the highest mark in Botany for the academic year,
University of the West Indies, Jamaica
175
PUBLICATIONS: Whiles, M., Lips, K., Pringle, C., Kilham, S.S., Bixby, R.J., Brenes, R., Connelly, S., Colon Gaud, J.C., Hunte-Brown, M., Huryn, A. D., Montgomery, C., Peterson, S. 2006. The Consequences of Amphibian Population Declines to the Structure and Function of Neotropical Stream Ecosystems. Frontiers in Ecology and the Environment. 4 : 27-34.
PRESENTATIONS:
Hunte-Brown, M., Kilham, S. S., Whiles, M. R., Lips, K. Pringle, C., Colon Gaud, JC., Brenes, R., Connelly, S. The Role of Tadpoles in Food Web Structure and Function in Upland Streams of Panama: The Consequences Of Extinction. American Society of Limnology and Oceanography, Winter Conference 2005 Hunte-Brown, M., Kilham, S. S., Whiles, M. R., Lips, K. Pringle, C., Colon Gaud, JC., Brenes, R., Connelly, S. The Effects of Amphibian Extirpations on Food Web Structure and Function In Panamanian Highland Streams. North American Benthological Society, Summer Conference, 2005. Peterson, S.D., Colon-Gaud, J.C., Whiles, M.R., Hunte-Brown, M., Connely, S., Kilham, S.S., Pringle, C., Lips, K.R., Brenes R. Organic Seston Dynamics in Highland Neotropical Streams: Implications for Stream-Breeding Amphibian Declines. North American Benthological Society, Summer Conference, 2005. Connelly, S., Pringle, C M, Bixby, R J, Whiles, M R, Lips, K, Brenes, R, Colon-Gaud, J C, Kilham, S, Hunte-Brown, M. Neotropical Amphibian Declines Affect Stream Ecosystem Properties. North American Benthological Society, Summer Conference, 2005. Hunte, M., Kilham, S.S. The Role Of Tadpoles In Food Web Structure And Function In Upland Streams Of Panama: The Consequences Of Extinction. Drexel University Symposium, May 2004. Hunte, M., Hyslop, E. J. Longitudinal Zonation of Benthic Macroinvertebrates in the Buff Bay River, Jamaica. Proceedings of the Fourth Conference, Faculty of Pure and Applied Sciences, University of the West Indies, Mona Campus, Jamaica W.I. 1999
