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MANAGEMENT AND LANDSCAPE EFFECTS ON BENEFICIAL TALLGRASS
PRAIRIE INSECTS – A STUDY OF BEES AND BEETLES
BY
REID B. MILLER
A thesis submitted to the Faculty of Graduate Studies of the University of Manitoba in partial
fulfilment of the requirements of the degree of
MASTER OF SCIENCE
Department of Entomology
University of Manitoba
Winnipeg, Manitoba
Copyright © 2021 by Reid B. Miller
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ABSTRACT
The largest remnant tall grass prairie (TGP) in Canada is the Manitoba Tall Grass Prairie
Preserve, located in the Rural Municipality of Stuartburn in southeastern Manitoba. TGP is home
to several rare and endangered plants and animals, particularly insects, whose contributions to
prairie functioning too often go unnoticed. Beneficial insects in TGP include pollinating insects,
such as wild bees, predatory insects, and insects that aid in decomposition/nutrient cycling.
Efforts by prairie managers to maintain remnant prairie include planned disturbance via
controlled fires and cattle grazing, with an aim to prevent woody encroachment and maximize
prairie plant diversity. Unfortunately, the effects of these practices on beneficial prairie insects
are often not considered. Because of this, I decided to collect beneficial insects in prairie sites
that differed in the type of disturbance that they were exposed to, the focal and surrounding
landcover of prairie patches, and local ground cover. Wild bees were caught in bee bowls over
the course of two growing seasons, and with blue vane traps in the second growing season.
Haplogastran beetles, comprising rove beetles, scarab beetles, and their relatives, were caught in
baited pitfall traps through two growing seasons. Once the bees and beetles were identified,
analysis via generalized linear mixed effect models, rarefaction curves, and distance-based
redundancy analysis uncovered trends in how these groups, as well as within group nesting
(bees) and feeding (beetles) guilds differed by disturbance type, landscape context, and local
ground cover. Wild bees appear to be negatively affected by cattle grazing, whereas beetles,
especially decomposer beetles, show greatest abundance in grazed sites. Ground nesting bees and
predatory beetles were both more abundant on burned sites compared to sites that had been
grazed. Landscape context also appears to affect bee and beetle abundance and diversity, with
bees demonstrating greater abundance, richness, and diversity under greater landscape diversity,
and both bees and beetles demonstrating increased abundance and diversity with increased forest
and ditch cover in the landscape. Ground nesting bees and predatory beetles showed opposite
responses to local ground cover, with bees favouring increased forb and bare ground cover, and
predatory beetles favouring increased grass cover. This study recovered several insect species
that were previously unknown from the province, and at least one previously
uncaptured/undescribed beetle species. Finding such diversity in such a narrow span of habitat
highlights the need to further consider the effects of disturbance and landscape context on the
beneficial insects that rely on the threatened TGP. It is hoped that this study can better inform
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land managers and property owners on the best ways to conserve the hidden and fragile insect
diversity that still exists in remnant Manitoba prairies.
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ACKNOWLEDGMENTS
First and foremost, I must thank Jason for his help, feedback, and understanding. I also
owe a lot of gratitude to the rest of the Gibbs and Bobiwash labs for their feedback and
friendship. I am grateful for all the fieldwork help provided by Jason, Dave Holder, Olivia Lano,
Joel Gardner, Gina Karam, Bob Miller, Angela Reimer, and especially Alanna Shaw. For help in
the lab, I wish to thank Leah Irwin, Kathy Morgan, Amber Bass, Alanna Shaw, Syd Shukla -
Bergen, Joel Gardner, and Carl Dizon. Many thanks go to Dave Holder again for project design
and construction.
Several students in the department have been instrumental in supporting me throughout
this most formative part of my life, including Megan Colwell, Crystal Almdal, Gina Karam,
Emily Hanuschuk, Mike Killewald, and Massimo Martini, and all the other Entomology grad
students past and present. I am also very indebted to many of the Entomology/Animal Science
support staff, especially Kathy Graham, and the late Teresa Sitko, who was always very
welcoming on my bright and early starts.
I am also very privileged to have been able to interact and learn from all the Entomology
professors and instructors who have helped guide my path, including, but certainly not limited to,
Kateryn Rochon, Jordan Bannerman, Terry Galloway, Kyle Bobiwash, and Rob Currie.
There are also four people without whose friendship and mentoring I would not be where
I am today; Marianne Hardy, Joy Stacey, Bob Wrigley, and the late Nancy Loadman.
I must also acknowledge the help and academic support I received from my committee
members, Anne Worley, and Richard Westwood. I am also indebted to Richard for part of the
idea of this project, as well as for helping spark my passion for insects. I also thank Bethanne
Bruninga-Socolar for assistance.
Several people assisted with identification of my specimens, including Jason, Amber
Bass and Joel Gardner for my bees, and Adam Brunke, Stewart Peck, Don Chandler, Andrew
Smith, Serge Laplante, Anthony Davies, and Margaret Thayer for my beetles. I am very
fortunate to have your assistance, especially given the immense number of specimens and such a
tight deadline.
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I received funding from several sources throughout this program, and I am grateful to
each and every one, including funding from Jason Gibbs, the University of Manitoba Graduate
Fellowship, scholarships funded by Marlene Hoogmoed, and the Entomological Society of
Canada.
I must thank Nature Conservancy Canada, Nature Manitoba, The Manitoba Heritage
Corporation, and their partners for land access and research permits, especially Julie Pelc,
Melissa Grantham, and Tim Teetaert from the NCC for their assistance. I would also like to
thank the staff at the Glenlea dairy farm for collecting fresh cow dung, as well as the staff at
Freshwater Fish for providing me with fish skin.
I would like to thank my friends and family outside of school for their support during this
period of my life as well, including Larry Sereacki, Will Andrushko, Angela Reimer, Brenna
Sorokowski, as well as my mom, dad, sister, and cats, especially Earl.
Lastly, I would like to thank my partner Nabeel for being there for me through my ups
and downs and always cheering me up. This work would not be possible without your love and
friendship.
If I have forgotten people who have helped make this project, I am truly sorry. Please
know that I am nevertheless grateful for your assistance.
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TABLE OF CONTENTS
MANAGEMENT AND LANDSCAPE EFFECTS ON BENEFICIAL TALLGRASS
PRAIRIE INSECTS – A STUDY OF BEES AND BEETLES ............................................... i
ABSTRACT.......................................................................................................................... iii
ACKNOWLEDGMENTS ..................................................................................................... v
TABLE OF CONTENTS.................................................................................................... viii
LIST OF TABLES................................................................................................................. x
LIST OF FIGURES ............................................................................................................. xii
Summary of thesis ................................................................................................................. 1
Research objectives and hypotheses ...................................................................................... 2
Chapter 1: Literature Review................................................................................................ 4
1.1 Tallgrass Prairie ................................................................................................................ 4
1.2 Prairie Response to Disturbance .......................................................................................... 6
Burning ............................................................................................................................. 6
Grazing ............................................................................................................................. 7
Mowing/haying .................................................................................................................. 7
1.3 Insect Response to Prairie Disturbance ................................................................................. 8
1.3.1 Herbivores ................................................................................................................. 8
1.3.2 Predators/Scavengers ................................................................................................... 9
1.3.3. Pollinators................................................................................................................10
Butterflies.........................................................................................................................10
Flies ................................................................................................................................11
Bees ................................................................................................................................12
1.4 Landscape Effects on Bees and Beetles................................................................................13
1.5 Bees ...............................................................................................................................14
Bee Taxonomy, Diversity and Evolutionary History................................................................14
1.6 Haplogastran Beetles ........................................................................................................16
Beetle Taxonomy, Diversity, and Evolutionary History ...........................................................16
1.7 Overview of Thesis ..........................................................................................................18
1.8 References ......................................................................................................................18
Chapter 2: Spatially diverse, unmanaged sites contain greater wild bee richness and
diversity than grazed sites in the tallgrass prairie ecosystem .............................................. 30
2.0 Abstract ..........................................................................................................................30
2.1 Introduction ....................................................................................................................30
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2.2 Methods .........................................................................................................................35
2.2.1 Site selection .............................................................................................................35
2.2.2 Sampling Procedure ...................................................................................................36
2.2.3 Processing Bees .........................................................................................................38
2.2.4 Ground cover characteristics ........................................................................................38
2.2.5 Landscape mapping ....................................................................................................39
2.3 Data analyses ..................................................................................................................39
2.3.1 Bee diversity & community composition .......................................................................39
2.3.2 Modelling .................................................................................................................41
2.4 Results ...........................................................................................................................42
2.4.1. Bee captures .............................................................................................................42
2.4.2 Community Composition - Distance-based Redundancy Analysis & perMANOVA .............42
2.4.3. Abundance, Species Richness, and Hill’s Shannon Diversity Modeling .............................44
2.4.3.1. Effect of Disturbance Type ......................................................................................45
2.4.3.2. Effect of landscape characteristics .............................................................................50
2.4.3.3. Effect of groundcover characteristics .........................................................................50
2.4.4 Rarefaction ...............................................................................................................50
2.5 Discussion ......................................................................................................................54
2.6 Conclusion ......................................................................................................................60
2.7 References ......................................................................................................................60
2.8 Chapter 2 Supplementary Material ......................................................................................72
Bee Model Tables ..............................................................................................................74
Chapter 3: Relationship between the two data chapters (Chapters 2 and 4) ...................... 84
Chapter 4: Fire and grazing present trade-offs for an ancestrally detritivorous group of
beetles (Coleoptera: Haplogastra) in tallgrass prairie......................................................... 85
4.0 Abstract ..........................................................................................................................85
4.1 Introduction ....................................................................................................................85
4.2 Methods .........................................................................................................................89
4.2.1 Site selection .............................................................................................................89
4.2.2 Landscape Mapping ...................................................................................................91
4.2.3 Identification/Data analysis .........................................................................................92
4.3 Results ...........................................................................................................................94
4.3.1 Community Composition - Distance-based Redundancy Analysis/perMANOVA.................95
4.3.2 Models....................................................................................................................... 100
4.3.2.1 Disturbance effects ................................................................................................ 100
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4.3.2.2 Landscape effects .................................................................................................. 103
4.3.2.3 Ground cover effects .............................................................................................. 104
4.3.3 Rarefaction Curves ................................................................................................... 104
4.3.4 Indicator Species Analysis......................................................................................... 107
4.4 Discussion .................................................................................................................... 108
4.5 Conclusion .................................................................................................................... 115
4.6 References .................................................................................................................... 116
4.7 Chapter 4 Supplementary Materials .................................................................................. 127
Haplogastran Beetles Model Tables .................................................................................... 129
Chapter 5: Conflicting response of pollinator, decomposer, and predator insects to
disturbance and landscape in northern tallgrass prairie................................................... 139
5.0 Abstract ........................................................................................................................ 139
5.1 Introduction .................................................................................................................. 140
5.2 Disturbance Type Effects ................................................................................................ 140
5.3 Landscape Composition Effects........................................................................................ 143
5.4 Ground Cover Effects ..................................................................................................... 143
5.5 New and Interesting Records ........................................................................................... 144
5.6 Future Directions ........................................................................................................... 144
5.7 Conclusion .................................................................................................................... 145
5.8 References .................................................................................................................... 145
LIST OF TABLES
Table 2.1 Summary of perMANOVAs performed on the Bray-Curtis distance of different bee
communities ………………………………………………………………………………….. 44
Table 2.2 Results of GLMMs performed on bee bowl capture abundance, species richness, and
Hill’s Shannon Effective Species Number …………………………………………………... 74
Table 2.3 Results of GLMMs performed on ground-nesting bee bowl capture abundance, species
richness, and Hill’s Shannon Effective Species Number ………………….………………… 75
Table 2.4 Results of GLMMs performed on stem-nesting bee bowl capture abundance, species
richness, and Hill’s Shannon Effective Species Number …………………………………… 76
Table 2.5 Results of GLMMs performed on blue vane bee capture abundance, species richness,
and Hill’s Shannon Effective Species Number ……………………………………………... 77
Table 2.6 List of species caught in bee bowls in 2017 ……………..………………………. 79
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Table 2.7 List of species caught in bee bowls in 2018 ………………………………………. 80
Table 2.8 List of species caught in blue vane traps in 2018 …………………………………. 82
Table 2.9 List of study sites and coordinates ………………………………………………….83
Table 4.1 Summary of amount of variation explained by constrained (Disturbance type) factors
in dbRDA for the total beetle communities in both years …………………………………… 95
Table 4.2 Summary of the effect of ‘Disturbance Type’ on beetle dissimilarities in distance-
based redundancy analyses ………………………………………………………………….. 96
Table 4.3 Summary of perMANOVAs performed on the Bray-Curtis dissimilarity of different
beetle communities in 2017 & 2018 ……………………………………………………….. 98
Table 4.4 Results of Indicator Species Analysis on beetle species by disturbance type …… 107
Table 4.5 Results of GLMMs performed on haplogastran beetle pitfall trap captures …….. 129
Table 4.6 Results of GLMMs performed on predatory haplogastran beetle pitfall trap captures
………………………………………………………………………………………………. 130
Table 4.7 Results of GLMMs performed on decomposer haplogastran beetle pitfall trap captures
………………………………………………………………………………………..…….. 131
Table 4.8 Results of a GLMM performed on aleocharine beetle abundance ……..………. 132
Table 4.9 Results of Indicator Species Analysis on beetle species by site using the Indval.g
method ……………………………………………………………………………………... 133
Table 4.10 Results of Indicator Species Analysis on beetle species by site using the r.g. method
……………………………………………………………………………………………… 133
Table 4.11 List of species caught in pitfall traps in 2017 …………………………………. 134
Table 4.12 List of species caught in pitfall traps in 2018 …………………………………. 135
Table 4.13 List of study sites and coordinates ………………………………………………138
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LIST OF FIGURES
Figure 1.1 Map showing the distribution of the Northern Tall Grasslands ecoregion in North
America ……………………………………………………………………………………….. 5
Figure 1.2 Map showing the location of the Manitoba Tall Grass Prairie Preserve (MTGPP)
………………………………………………………………………………………………… 6
Figure 2.1 Location of the study sites showing the location of the Manitoba Tallgrass Prairie
Preserve ………………………………………………………………………………………. 36
Figure 2.2 Example of the ground level and elevated bee bowl station and blue vane
trap…………………………………………………………………………………………….. 37
Figure 2.3 Ordination plots of the Bray-Curtis distance-based redundancy analysis of bee bowl
community data ………………………………………………………………………………. 43
Figure 2.4 Ordination plot of the Bray-Curtis distance-based redundancy analysis of blue vane
trap captures …………………………………………………………………………………. 44
Figure 2.5 Effect plot showing the predicted effect of disturbance type on bee bowl trap
abundance, species richness, and Hill’s Shannon effective species number ………………… 46
Figure 2.6 Effect plot showing the predicted effect of disturbance type on ground nesting bee
species richness ………………………………………………………………………………. 47
Figure 2.7 Effect plot showing the predicted effect of disturbance type on stem nesting bee
abundance ……………………………………………………………………………………. 49
Figure 2.8 Effect plot showing the predicted effect of disturbance type on stem nesting bee
species richness ………………………………………………………………………………. 49
Figure 2.9 Rarefied curves of the entire bee bowl captured community, and the blue vane
captured community …………………………………………………………………………. 52
Figure 2.10 Rarefied curves of the ground nesting bee bowl captured community, and the stem
nesting bee bowl community ………………………………………………………………… 53
Figure 2.11 Graph showing the first two axes of a PCA performed on groundcover data …. 72
Figure 2.12 Graph of the first two axes of a principal coordinate analysis performed on percent
cover on the various landscapes found at 1 km from the centre of study sites ……………… 73
Figure 4.1 Map showing the distribution of the northern tall grasslands ecoregion in North
America ……………………………………………………………………………………… 86
Figure 4.2 Map of the distribution of the study sites relative to the town of Stuartburn …… 90
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Figure 4.3 Distance-based redundancy ordination of all 2017 haplogastran beetles, predatory
beetles, and decomposer beetles …………………………………………………………….. 97
Figure 4.4 Distance-based redundancy ordination of all 2018 haplogastran beetles, predatory
beetles, and decomposer beetles ……………………………………………………………. 99
Figure 4.5 Effect plots of the predicted effect of disturbance on haplogastran beetle abundance
Hill’s Shannon effective species number …………………………………………………… 101
Figure 4.6 Effect plots of the predicted effect of disturbance type on predatory haplogastran
beetle, and decomposer beetle abundance ………………………………………………….. 102
Figure 4.7 Effect plot of the predicted effect of disturbance type on aleocharine beetle
abundance …………………………………………………………………………………... 103
Figure 4.8 Rarefied diversity curves of haplogastran beetle captures (except the subfamily
Aleocharinae) ………………………………………………………………………………. 105
Figure 4.9 Graph of the first two axes of a principal coordinate analysis performed on percent
cover on the various landscapes found at 500 m from the centre of study sites …………… 127
Figure 4.10 Graph showing the first two axes of a PCA performed on groundcover data …. 128
Figure 5.1 Bar graph representing the effect of the three disturbance types on bee bowl caught
bee abundance, species richness, and Hill’s Shannon effective species number ……………. 141
Figure 5.2 Bar graphs representing the effect of the three disturbance types on beetle abundance
in 2017 and 2018 …………………………………………………………………………….. 142
Figure 5.3 Bar graphs representing the effect of the three disturbance types on beetle species
richness in 2017 and 2018, and on Hill’s Shannon effective species numbers in 2017 and 2018
………………………………………………………………………………………………... 142
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Summary of thesis
The focus of this thesis is primarily to understand how beneficial insect guilds respond to
common disturbance types in the endangered tallgrass prairie ecosystem. The thesis is organized
such that the first chapter presents a literature review concerning the current knowledge of how
disturbance/management techniques and landscape context affect prairie vegetation and insect
communities. The second chapter is in a manuscript format and is chiefly concerned with an
experiment I conducted that involved catching wild bees in sites that differed based on the
disturbance type that they were recently exposed to; with some sites having experienced a recent
burn, some sites being recently grazed, and other sites not experiencing a recent disturbance. I
also measured landscape and groundcover variables to understand what factors are influencing
the abundance, richness, and diversity of wild bees, and their differing nesting guilds in the
tallgrass prairie. The third chapter is a short explanation on how the two data manuscripts
(chapters 2 and 4) relate and compliment one another. Similar to the second, the fourth chapter
deals with haplogastran beetles, specifically looking at differences in response between predatory
and decomposer beetle guilds. The fifth chapter represents a summary of the previous chapters
and reports on general trends found in the proceeding experiments, as well as new provincial
beetle records.
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Research objectives and hypotheses
The primary goals of both research chapters (Chapters 2 and 4) are to understand the
combined and specific effects that prairie disturbance, regional landscape, and local scale
landcover characteristics have on two groups of beneficial insects. The second chapter examines
the background, methods, and results of an experiment designed to test these effects on wild
bees, which are one of the main groups of pollinators in the tallgrass prairie. The fourth chapter
explores the same questions aimed at an ancestrally detritivorous group of beetles that act as
either decomposers or predators. Furthermore, I wanted to understand if different guilds of wild
bees (ground nesters vs. stem nesters) and different guilds of beetles (decomposers vs. predators)
respond differently to disturbance type, landscape context, and local landcover effects.
I hypothesized that prairie sites that were exposed to fire within the last six years would
have more exposed ground and remnant wood/stems for wild bees to utilize. As well, since most
sites had gone several years since a fire, I suspected that any short-term negative effects of
burning on stem nesting bees would have since been reversed. I also suspected that increasing
amounts of forest surrounding my sites would benefit the abundance and diversity of stem
nesting bees. As bees require floral and nesting resources to survive and propagate, I suspected
that increasing amounts of blooming flowers, forbs, and bare ground around my sites would
increase bee diversity measures.
I hypothesized that beetles would be more abundant and diverse on recently grazed sites
due to suspected greater amounts of available detritus. As well, I predicted that like previous
studies, sites with greater surrounding landscape diversity would support a lower diversity of
decomposer beetles. I expected that predatory beetles would respond positively to increasing
grass cover within my sites, as such patterns have previously been established in grassland
systems.
I hope that these studies may be used by prairie land managers seeking to understand
patterns in disturbance and landscape context relating to beneficial insect guilds, which are
becoming increasingly recognized as invaluable components of prairie diversity and processes.
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Chapter 1: Literature Review
1.1 Tallgrass Prairie
The North American prairies were once a vast landscape that covered the interior of the
continent. The prairie ecozone exists as a gradient, but for convenience it is divided into three
grassland regions in Canada. Shortgrass prairie occurs east of the Rockies, mixed grass prairie
mainly in Saskatchewan and western Manitoba, and tallgrass prairie (TGP) from Manitoba to
Ontario, south to Oklahoma (Sveinson 2003). These regions differ in the amount of annual
precipitation they receive, which in turn creates differences in their vegetation communities
(Sveinson 2003). The prairies were formed and maintained by natural processes and human
activity, including large herbivores, such as the American bison, Bison bison (L.), and
Indigenous-set fires (Pyne 1986, Knapp et al. 1999). These disturbances prevent woody-plant
encroachment and are essential for increasing plant community diversity (Collins and Calabrese
2012). Tallgrass prairie is the most fertile prairie type (Joyce and Morgan 1989), and reaches its
northernmost extent in southeastern Manitoba (Figure 1.1). Tallgrass prairie is characterised by
plants such as big bluestem, Andropogon gerardii Vitman and Indian grass, Sorghastrum nutans
(L.) Nash, as well as rarer species such as the western prairie fringed orchid, Platanthera
praeclara Sheviak & M.L.Bowles (Joyce and Morgan 1989). Manitoba has lost over 99% of its
former tallgrass prairie range (Samson and Knopf 1994), and recent studies suggest that the
decline is continuing (Koper et al. 2010).
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Figure 1.1 Map showing the distribution of the Northern Tall Grasslands ecoregion in North America. Distribution is based on ecoregions defined by the World Wildlife Fund and seen in
Olson et al. (2001). Map created with SimpleMappr (Shorthouse 2010).
To curb declines, the Manitoba Tall Grass Prairie Preserve (MTGPP) has amassed over
2,000 hectares of prairie in the Rural Municipality of Stuartburn (Figure 1.2). Though this
constitutes the largest remnant of tallgrass prairie habitat in Canada, it is nevertheless
fragmented. It exists in a mosaic of agricultural land and semi-natural aspen tree stands. The
MTGPP is located adjacent to Sandilands Provincial Forest to the east and is bordered by the
Roseau River on the west. There is an extensive swamp along the northern limit, and the
southernmost extent approaches the American border. The Preserve is managed by a committee
consisting of Nature Conservancy Canada and its partners. Management practices at MTGPP
includes cattle grazing, prescribed fire and limited mowing and rarely, haying (Sveinson 2003).
Mowing occurs in other prairie preserves in addition to prescribed fires and cattle and bison
grazing (Santerre 2010).
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Figure 1.2 Map showing the location of the Manitoba Tall Grass Prairie Preserve (MTGPP) in
relation to Manitoba’s capital of Winnipeg and neighbouring states. Map was created using
SimpleMappr (Shorthouse 2010).
1.2 Prairie Response to Disturbance
Burning
Several biotic and abiotic changes to the prairie landscape accompany the different types
of management disturbance. Though burning leads to loss of aboveground biomass initially, it
ultimately results in greater plant productivity (Briggs and Knapp 1995, Wagle and Gowda
2018). Solar penetration is a main driver of productivity through increased temperature of soil
following litter removal. Increased soil temperature and decreased litter layer leads to earlier
greening compared to unburnt plots (Ehrenreich and Aikman 1963, Wagle and Gowda 2018).
Though burning can reduce the availability of soil nitrogen, prairie plants compensate for this by
increased root growth allocation in burned sites compared to controls (Johnson and Matchett
2001, Wagle and Gowda 2018). Fire can improve palatability to cattle and increase the width and
number of leaves on prairie grasses, which could affect herbivorous insects (Kansas State
College of Agricultural and Applied Science 1934, Wagle and Gowda 2018). The frequency and
timing of fires influence the ratios of C4/C3 grasses and forbs, along with plant species richness.
C3 and C4 grasses differ in their photosynthetic pathways and generally exhibit different
environmental preferences, with C4 grasses being favoured in hotter, drier environments
compared to C3 species (Pau et al. 2013). Forbs are non-woody, non-grass flowering plants that
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constitute the bulk of the floral diversity in TGP (Gibson and Hulbert 1987). Spring burning is
associated with a loss of species richness and abundance of dicot forbs (Gibson and Hulbert
1987, Fay 2003). Winter and fall burnings are better for forbs and C3 grasses than late spring
burns (Towne and Craine 2014, Wagle and Gowda 2018). Unburned sites are more buffered
against the effects of draught due to their litter layer providing protection from soil evaporation
(Weaver and Rowland 1952, Wagle and Gowda 2018). Burning can also reduce soil fungi
(Dooley and Treseder 2012, Wagle and Gowda 2018), which could affect the arthropods that
feed on them.
Grazing
Grazing increases plant species richness in tallgrass prairie (Hickman et al. 2004, Wagle
and Gowda 2018), though admittedly these results were obtained from more southerly TGP
remnants. This has been attributed to the changes in soil nutrients associated with grazing;
namely nitrogen and carbon availability (Manning et al. 2017, Wagle and Gowda 2018). Grazing
has been shown to reduce the dominance of grasses and increase the numbers of flowering forbs
in grassland ecosystems (Gibson and Hulbert 1987, Hartnett et al. 1997, Coppedge and Shaw
1998, Fay 2003). Plant response can vary depending on the interaction between fire and grazing,
and plant species richness is maximized with a combination of the two management practices,
namely grazing with infrequent fire (Collins and Calabrese 2012, Wagle and Gowda 2018).
Some studies suggest that the greater the stocking density in TGP, the greater the beneficial
effects of increasing plant species richness and ratios of forbs/C3 grasses : C4 grasses, though
this was achieved with bison grazing (Wagle and Gowda 2018).
Mowing/haying
Mowing is known to play a large role in plant species composition in TGP, with some
studies showing that mowing leads to increased levels of exotic species (Gibson et al. 1993).
Studies into the effects of mowing on vegetation diversity in TGP have produced mixed results.
In some studies, mowed plots experienced low levels of diversity compared to plowing or
burning (Netherland 1979). As well, making the switch from annual mowing to annual burning
leads to increases in C3 and C4 grasses, forb, and woody plant density in TGP (Rooney and
Leach 2010). However, mowing led to increased biomass and increased species richness in
seeded prairie restorations (Dowhower et al. 2020), and plant productivity is increased by both
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mowing and burning in TGP (Dickson 2019).Other studies show that late season mowing is
known to increase plant diversity in TGP (Dee et al. 2016). In fact, mowing has been shown to
increase TGP plant species richness negatively impacted by burning and fertilization (Collins et
al. 1998). While mowed sites tended to have less forb and plant cover than burned or untreated
sites in a TGP experiment, mowing eliminated woody plants as effectively as fire, and overall
plant diversity was not diminished (Van Dyke et al. 2004). Additionally, annual clipping has
been shown to be as effective as annual burning at promoting native warm season grasses over
exotic cool season grasses in TGP (Smart et al. 2013).
1.3 Insect Response to Prairie Disturbance
Insects are the dominant form of animal life in terrestrial ecosystems, thus, naturally
many ecological processes are insect mediated. Of these processes, those that directly benefit
humanity have been dubbed ecosystem services (Harrington et al. 2010). Various insect groups
have been shown to respond to the disturbances that form and maintain the tallgrass prairie,
largely, but not exclusively linked to their feeding guild.
1.3.1 Herbivores
Herbivores can strongly influence plant communities, and they are a large component of
the insect biodiversity in prairies. Herbivore response to management depends on the taxon and
type of disturbance. Cicada nymphs in the soil respond differently to burns by genus, with
Cicadetta preferring burned plots, whereas Tibicen heavily favoured unburned plots (Callaham et
al. 2003). Free-living hemipterans in an Illinois prairie show the greatest species richness on
unburned sites, which led to recommendations that burns should be applied only once every 3 –5
years (Wallner et al. 2012). Grasshoppers have been the subject of numerous studies in the
prairies, due to their potential economic importance. Evans (1984) found that grasshopper
diversity peaks at sites with intermediate fire frequencies i.e. spring burning every 2 or 4 years.
In mixed grass prairie, Branson and Vermeire (2016) found that late summer fire leads to a 36 –
53% decrease in grasshopper density, however responses are species dependent. Forb -feeding
and mixed-feeding grasshopper assemblages increase under infrequent fire intervals, and overall
species richness of grasshoppers is greatest at infrequent fire frequencies relative to annual or
biennial burning (Evans 1988). In contrast, Joern (2005) found that fire frequency does not affect
grasshopper species richness, but rather it is grazing that exerts a significant influence.
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Bison grazing has been shown to increase the abundance and richness of tallgrass prairie
herbivorous arthropods (Moran 2014). Sites grazed by bison show significantly higher species
richness and Shannon diversity of grasshoppers compared to ungrazed sites (Joern 2005).
Ungulate grazing provides grasshoppers a form of resilience to the loss of host species by
increasing the complexity of grasshopper-plant networks (Welti et al. 2019). Herbivorous beetle
larvae are more prevalent when nutrients associated with animal dung (nitrogen and phosphorus)
are added to the soil (Callaham et al. 2003).
Mowing resulted in lower density of herbivorous beetle larvae and reduced the
abundance of Cicadetta spp. nymphs in TGP soil (Callaham Jr et al. 2002, 2003). As well,
mowing has been shown to reduce other soil dwelling hemipteran densities (Seastedt and Reddy
1991). Herbivorous and carnivorous insect densities have been shown to decline with increasing
mowing intensity in TGP, though interestingly, saprophagous insect densities were not affected
(Todd et al. 1992).
1.3.2 Predators/Scavengers
Ground beetles (Carabidae) have been the focus of several studies aimed at understanding
how insect communities respond to disturbance. Barber et al. (2017) concluded that prescribed
burning negatively affects large species of ground beetles. Cook and Holt (2006) demonstrated
that fire frequency has negligible effects on overall ground beetle diversity, but does alter the
relative frequency of common species. Ground beetle abundance and species richness peaks in
the year after a spring burn, with abundance diminishing year after year (Larsen and Work
2003). However, when compared to remnant prairie, diversity is highest after many years post-
fire (Larsen and Work 2003). Similarly, research conducted in a European grassland found a
three-fold increase in ground beetles in plots that had been burned, though the composition was
simpler overall and consisted of a high number of pioneer species (Samu et al. 2010). A
Manitoba study by Roughley et al. (2010) found that ground beetle species responded
individually to fire treatments and overall community composition was not affected in the long
term. They also found that it took the ground beetle community four years to completely recover
and suggest that using fire as a conservation tool should be deployed at different scales and
seasons to maximize species diversity. An experiment on an oats planting found that burning
negatively affected species diversity of herbivorous beetles, but had no effect on carnivorous
10
beetles (Bulan and Barrett 1971). Loss of litter has been shown to reduce the abundance of
detritivores in the months following a fire (Seastedt 1984, Seastedt et al. 1986, Kral et al. 2017).
However other studies have found that reduced litter led to greater numbers of largely predatory
beetles (Tester and Marshall 1961). Rove beetles have been found to be more numerous on
burned sites in TGP (Van Amburg et al. 1981, Warren et al. 1987), which is consistent with the
finding that generalist predators respond positively, and are drawn to sites that have recently
experienced a fire (Kral et al. 2017).
Several studies have been conducted on grassland ants (Hymenoptera: Formicidae) and
their response to disturbance. Moranz et al. (2013) looked at ant functional groups and found that
generalist ant species were more abundant on sites subjected to both grazing and burning, than to
burning alone. They also found that one ant species achieved competitive dominance in sites that
had been burned. Another study found that neither ant community composition nor species
richness could be characterized by the amount of time since last fire in the prairie ecosystem
(Menke et al. 2015).
Moran (2014) found that arthropod carnivores were more abundant and speciose under
bison grazing. In a study of macroinvertebrates, beetle abundance (including predators,
scavengers, and herbivores) was higher in grazed plots than in plots that experienced both fire
and grazing, while hymenopteran abundance (which included predators, parasitoids, and
herbivores) was similar between the two (Doxon et al. 2011). Leiodids, or round fungus beetles
are predicted to be more abundant at sites with greater litter depth because of the abundance of
food resources present (Chandler and Peck 1992). Beetles associated with decomposition rely on
the availability of the scarce resource of decomposing organic matter to feed and reproduce. The
focus of grazing regime studies has been largely focused on herbivores and pollinators, and thus
there are obvious gaps in our understanding on if and how grazing affects predatory and
saprophilic insects in the tall grass prairie.
1.3.3. Pollinators
Butterflies
11
Butterflies are the most well-studied pollinator in tallgrass prairies, although their role is
perhaps better characterised as herbivores. There is a lack of consistency in prairie butterfly
disturbance findings. Moranz et al. (2014) report that prescribed burning is compatible with
conservation efforts, while grazing reduced nectar sources and regal frittilary, Speyeria idalia
(Drury), density. Butterfly abundance was lowest on sites that were subjected only to a burn and
highest in sites that experienced both fire and grazing, though species diversity was highest on
burned sites (Vogel et al. 2007). For butterflies, diversity and type of disturbance is key. Grazing
affected the abundance of individual species and likely added to the broadscale diversity of the
butterfly community (Bendel et al. 2018). Prescribed fires every 3–5 years increases habitat
quality and abundance of regal fritillaries (Henderson et al. 2018). Furthermore, fire can generate
an emergent population of milkweed for migrating monarch butterflies, Danaus plexippus (L.)
(Baum and Sharber 2012). Man-made disturbances can lead to generalist species becoming more
abundant than specialists (Swengel et al. 2011). For this reason, consistency and diversity of
disturbance types are necessary for conserving specialist butterflies in tallgrass prairie habitats
(Swengel 1998). Generalist butterflies have been shown to respond best to frequent and intense
management, while random, infrequent wildfires are more useful than rotational fires for
specialists (Swengel 1998). Sites without fire disturbance are important as they house a greater
abundance of specialist butterfly species (Swengel and Swengel 2007).
Mowing, at least at infrequent intervals has been shown to positively affect prairie
butterflies. Infrequent mowing resulted in increased abundance, richness, and Shannon diversity
of grassland butterflies than continuously grazed sites in the southern Appalachians (Smith and
Cherry 2014). Mowing has also been shown to positively affect monarch butterflies, with
mowing twice leading to greater egg numbers being laid on the host milkweed (Fischer et al.
2015). While mowing is known to be preferable to grazing and burning in conserving specialist
prairie butterflies (Swengel 1996, 1998), it can nonetheless lead to reductions in extremely
endangered specialists such as the Dakota Skipper, Hesperia dacotae (Skinner) (McCabe 1981).
Overall, it is recommended that large mows be avoided in favour of localized smaller cuts
(Swengel 2001).
Flies
12
Pollinating flies are an important component of TGP, accounting for 60% of all floral
visits in Manitoba TGP (Robson 2008). In fact, differences in climate and pollinator preferences
has led to floral morphological and community differences that help distinguish the largely bee-
pollinated drier fescue and mixed grass prairie, and the wetter, largely syrphid pollinated TGP
(Robson et al. 2019). Unfortunately, flies are often neglected in grassland insect studies because
of their difficult taxonomy and incredible abundance (Paiero et al. 2010). In more southerly
prairie, syrphids (Diptera: Syrphidae) appear to be more important pollinators to annual flowers
than perennials, but still account for 9% of all floral visits in an Illinois prairie (Parrish and
Bazzaz 1979). Studies examining the role of prairie management on flies have produced mixed
results (Panzer 2002). Some studies have shown negative, or slightly negative effects of fire on
fly abundance (Rice 1932, Anderson et al. 1989). Others have shown that fire has positive effects
on abundance (Nagel 1973) and species richness (Hartley et al. 2007) of prairie flies. Globally,
pollinating fly abundance and richness tends to respond positively to intermittent fires, especially
to wildfires (Carbone et al. 2019). In TGP, flies that develop in the soil were more abundant after
a summer burn than a spring burn (Kirkwood et al. 2000). Interestingly, experimental
suppression of mycorrhizal symbiotes of grassland plants created a shift of the pollinator
community via differences in floral morphology from large bodied bees to smaller bees and flies
(Cahill Jr. et al. 2008). Under grazing, flies may be of greater importance as pollinators due to
the presence of cow dung serving as larval substrate (Vanbergen et al. 2014).
Bees
Fire may cause direct mortality on nesting bees. Nests greater than 10 cm below ground
should be safe from fire (Cane and Neff 2011), but shallow nests and stem nesters are less
protected. However, burning sites has been shown to prolong the flowering season, which may
balance out the initial high mortality (Wrobleski and Kauffman 2003, Mola and Williams 2018).
A few studies have found no difference in bee abundance between grazing and burning
disturbances, however studies comparing disturbance treatments to undisturbed reference sites
are lacking (Smith et al. 2016, Pennarola 2019). There is some indication that stocking rate of
cattle may affect bee nutrition via potential changes in quantity or quality of floral resources
(Smith et al. 2016). There is a lot of overlap in dietary requirements amongst native bees and
grazing ungulates such as cattle (Debano et al. 2016). In Missouri, grazing and haying had
detrimental effects on both the bee community and the soil and floral resources required by bees
13
(Buckles and Harmon-Threatt 2019). Kimoto et al. (2012) showed grazing intensity did not
affect bee abundance, although it did affect species composition. A recent study on bees in
tallgrass prairie found that neither fire nor grazing affected composition of bee communities
(Pennarola 2019). Grazed habitats offer pollinators a greater number of flower species, while
simultaneously increasing the size and diversity of floral visitation networks (Vanbergen et al.
2014). However, networks have less nestedness in grazed habitat, and thus they are more prone
to loss of specialist pollinator and plant species (Vanbergen et al. 2014). Though not directly tied
to the management of tallgrass prairie, introduced, stocked bees, such as the western honey bee
(Apis mellifera L.) may negatively impact wild bees via resource competition, pathogen
transmission, and change in plant community competition (Mallinger et al. 2017). As the
MTGPP exists in an agricultural mosaic, it is not unreasonable to assume that honey bees may be
affecting the wild prairie bees in one or more ways.
1.4 Landscape Effects on Bees and Beetles
Areas dominated by simplified, conventional agricultural landscapes have been shown to
negatively impact wild bee abundance and diversity (Kennedy et al. 2013, Connelly et al. 2015).
Urban and agricultural habitats support fewer rare species, which can have a large effect on
overall diversity (Harrison et al. 2017). The diversity and composition of native bee communities
vary according to proximity to forested areas in tallgrass prairie systems, with rarified species
richness increasing with increasing percentage of woodlands within a 500 m radius (Griffin et al.
2017). Olynyk (2017) found that increasing unusable habitat within the landscape negatively
affected bee abundance in a prairie/agricultural landscape. Lane et al. (2020) found that
increasing levels of surrounding agricultural landscape did not negatively affect wild bee β -
diversity. Configuration at the local scale, but not at the landscape scale, was important for bee
abundance (Graham et al. 2017, Graham and Nassauer 2019). Pollinating flies and bees respond
positively to landscape heterogeneity (Denning and Foster 2018). In Europe, impervious
surfaces, such as those encountered with urbanization, negatively affect wild bee abundance and
richness (Geslin et al. 2016). In restored grasslands, bee species richness increased with forb
cover, as well as the amount of semi-natural landscapes surrounding the grassland (Crist and
Peters 2014). Bumble bee diversity is most strongly correlated with the floral availability at a
scale of 500 m, while their abundance was linked to a scale of 700 m in the tallgrass prairie
(Hines and Hendrix 2005). It will thus be useful to determine if proximity to both natural and
14
anthropogenically modified habitat, such as those found in simple agricultural landscapes, affects
wild bee diversity and abundance in the Manitoba Tallgrass Prairie Preserve. Of different insect
feeding guilds in the tall grass prairie, predators may be more susceptible to regional (patch
shape) landscape change than lower trophic levels (Stoner and Joern 2004).
Bossenbroek et al. (2004) found that beetle community composition was affected by
environmental variables at both local and landscape scales in North American grasslands;
however, they point out that the influence of the scale factors were less consistent in explaining
beetle community composition in tall grass prairie due to its comparatively more heterogenous
makeup. Predatory beetles in restored grasslands had greater species richness as grass cover
increased at the local scale, and as semi-natural habitats surrounding the grassland increased at
the landscape scale (Crist and Peters 2014). Dung beetle species richness responds negatively to
greater landscape variety (Reynolds et al. 2018).
1.5 Bees
Bee Taxonomy, Diversity and Evolutionary History
Bees first appeared in the Cretaceous Period following the evolution of angiosperms, on
which they rely for pollen and nectar (Danforth et al. 2013). Bees are believed to have arisen
from within the apoid wasp family Crabronidae (Branstetter et al. 2017, Peters et al. 2017, Zheng
et al. 2018). Bees are composed of two or three clades split either with the long-tongued bees
(Apidae + Megachilidae) separated from the short-tongued bees (Andrenidae + Colletidae +
Halictidae + Melittidae (Zheng et al. 2018) or with Melittidae being sister to the other two
groups (Danforth et al. 2013, Branstetter et al. 2017, Peters et al. 2017). The sister group to the
Colletidae are the Stenotritidae (Branstetter et al. 2017), which is the smallest family of bees and
is restricted to Australia.
Bees vary greatly in their nesting, provisioning, and social structures (Michener 1974).
Most bees are solitary ground-nesters who provision their larvae with pollen and nectar from a
wide variety of flowering plants (Danforth et al. 2019). Some are pollen specialists dependent on
one (monolectic) or few (oligolectic) species of plants (Cane and Sipes 2006, Fowler 2016).
Some solitary nests are found in aggregations. “Communal” nests have multiple females, but
each provision only for their own offspring. Reproductive division of labour such that one
female, the queen, dominates egg laying is characteristic of semisocial and eusocial nests. Nests
15
are “semisocial”, when the worker caste are sisters of the queen (Michener 1974). Matrilineal
nests with a queen and daughter worker(s) are termed “eusocial”. “Primitively” eusocial nests
have queens (gynes) that could theoretically survive on her own, and “highly” eusocial nests
have a queen that cannot survive unassisted and requires workers to help found a new colony
(Michener 1974, 2007). Some species appear to produce a specialized male “soldier” caste with
large heads and short wings to guard the nest, however this has only been documented in a few
species (Michener 1974, Danforth et al. 2019). Many species do not nest in the ground, but
instead nest in natural cavities such as those found in hollowed out stems or reeds. Brood
parasitism has evolved in many bee lineages and can include species that lay eggs in solitary bee
nests (cleptoparasites), or social parasites who lay their eggs and take over social colonies
(Michener 2007).
Manitoba is home to six of the seven families that comprise the extant bees. Only one
species of melittid is recorded from Manitoba, Macropis nuda (Provancher). Unlike most bees,
Macropis spp. specialize on collecting floral oil in addition to pollen from yellow loosestrife ,
Lysimachia spp., to provision their larvae (Rozen and Jacobson 1980).
The family Apidae includes the honey bee, Apis mellifera, and the bumble bees, Bombus.
Apidae is the largest bee family, with a remarkable diversity including the small carpenter bees,
Ceratina spp., long-horned bees of the recently erected subfamily Eucerinae (Bossert et al.
2019), and a myriad of cuckoo bees found in the subfamily Nomadinae. The family
Megachilidae includes the leaf-cutter bees, Megachile spp., which derive their common name for
the habit of some species lining their nests with sections of leaves that they have chewed off. The
family also includes the mostly spring flying Osmia spp., resin bees (Dianthidium spp.), as well
as two genera in Manitoba that are strictly cleptoparasitic, Stelis and Coelioxys.
Of the short-tongued bees, some of the most abundant belong to the family Halictidae,
which are known as sweat bees because of their habit of landing on skin and lapping up salt-rich
excretions. Members of the nominate subfamily are mostly pollen generalists (Wcislo and Cane
1996), such as most Lasioglossum and Halictus, however some halictids are specialists, such as
Dufourea spp. (Dumesh and Sheffield 2012). Members of one genus in Canada, Sphecodes, or
blood bees, are exclusively cleptoparasitic (Michener 1978). Andrenidae includes many spring-
flying bees and many pollen specialists (Danforth et al. 2019). These bees most often nest
16
solitarily, or in aggregations in the soil (Wilson and Messinger Carril 2016). The family
Colletidae is represented by two genera in Manitoba that both line their nest with a naturally
produced cellophane-like material (Wilson and Messinger Carril 2016), Colletes spp. are usually
honey bee sized, and are superficially similar to Andrena spp. The other genus, Hylaeus, are
quite distinct from Colletes and are known as masked bees because of the yellow markings on
their face. Hylaeus have a unique way of transporting the pollen they collect, storing it in an
internal crop as opposed to carrying it on scopa like most other bees (Michener 2007).
1.6 Haplogastran Beetles
Beetle Taxonomy, Diversity, and Evolutionary History
Haplogastra is a proposed clade that includes the clades Staphyliniformia and
Scarabaeiformia. The Haplogastra are thought to have evolved as detritus feeders, which is a
habit and lifestyle retained in most of its lineages (McKenna et al. 2015). This clade is supported
by molecular and morphological evidence (Kolbe 1908, McKenna et al. 2015) (but see Beutel
and Leschen 2005). Staphyliniformia includes the rove beetles (Staphylinidae), the largest family
of beetles (and perhaps all living things) in the world, as well as the carrion beetles (Silphidae),
round fungus beetles (Leiodidae), feather-winged beetles (Ptiliidae), clown or hister beetles
(Histeridae), and water scavenger beetles (Hydrophilidae). The Scarabaeiformia includes scarabs
(Scarabaeidae), stag beetles (Lucanidae), bess beetles (Passalidae), and hide beetles (Trogidae)
and several other families.
The rove beetles (Staphylinidae) are so diverse it is difficult to describe them as a whole,
however generally the majority are predacious or saprophagous (Bohac 1999). The most visible
of the rove beetles, and those most readily sampled, are those that are quick running and live
above the soil surface (Irmler and Lipkow 2018). The rove beetles are now believed to be
paraphyletic in regards to the carrion beetles (Silphidae), with molecular evidence placing
silphids well within the Staphylinidae (McKenna et al. 2015). Carrion beetles are divided into
two subfamilies, the Silphinae, and the Nicrophorinae. The Silphinae are adapted for feeding on
large vertebrate carcasses and developing in the soil nearby (Anderson and Peck 1985). The
Nicrophorinae are known as the burying, or sexton beetles, and have shorter elytra and are
generally more streamlined. The majority are adapted to finding small vertebrate carcasses and
as a team dragging and burying it under the surface, where they remove the fur or feathers and
17
lay their eggs to develop inside the carrion (Anderson and Peck 1985). Interestingly, the
nicrophorines engage in parental care, tending and feeding the developing larvae, a trait not often
seen in insects, dubbed ‘subsocial’ behaviour (Costa 2006). Other members of the
Staphylinoidea include the feather-winged beetles (Ptiliidae) and the round fungus beetles
(Leiodidae). The feather-winged beetles include the smallest of all beetles. Their winged forms
are characterised by unique plumose wings not seen in other beetles. Most ptiliids are believed to
feed on the microflora present on rotting organic matter (Dybas 2014). Round fungus beetles
include some of the most specialized of all beetles, including the ‘Beaver Parasite Beetle’,
Platypsyllus castoris Ritsema, that lives and feeds on skin excretions on beavers. Many others
are associated with mammal nests (Krinsky 2019). In general, leiodids feed on fungal hyphae,
which are often present on rotting substrate (Grimaldi and Engel 2005).
The Hydrophiloidea includes the water scavenger beetles (Hydrophilidae). The clown
beetles (Histeridae) and closely related families belong to the Hydrophiloidea but have
sometimes treated separately as Histeroidea. The water scavenger beetles are largely aquatic,
however the subfamily Sphaeridinae is mostly terrestrial and includes forms that regularly occur
in cow pats and other rotting material (Short and Fikacek 2013). The clown or hister beetles
(Histeridae) are rather unique looking predatory beetles that occur in such substrates as dung,
carrion, and rotting cacti, while others live as inquilines in mammal nests or ant colonies, or
under bark (Bousquet and Laplante 2006). The Scarabaeiformia are believed to have descended
from within the Hydrophiloidea, or as sister group to them (McKenna et al. 2015).
The Scarabaeoidea includes the scarabs and their close relatives. The scarabs
(Scarabaeidae) are divided into several subfamilies, with some being largely herbivorous, while
two are dung feeders (Scarabaeinae and Aphodiinae). The Scarabaeinae includes such familiar
beetles as the sacred scarab, Scarabaeus sacer L., worshipped in ancient Egypt, as well as
several local species often found in and around dung. The Scarabaeinae tend to be “rollers”, or
“tunnelers”, with some species rolling pieces of dung away to a separate location, while others
create tunnels under the dung to provision their larvae (Helgesen and Post 1967, Halffter and
Edmonds 1982). The Aphodiinae includes the genus Aphodius, which has recently been split into
several different genera, as well as several other related groups. Aphodiine dung beetles are
generally smaller and more elongate than the Scarabaeinae. They tend to be “dwellers” that
18
complete their entire life cycle within a cow pat or rich humus source (Helgesen and Post 1967,
Halffter and Edmonds 1982). The Scarabaeoidea also includes other dung feeding groups (some
Geotrupidae), as well as some that develop in rotting wood (Passalidae, Lucanidae), and one
group that specializes on the keratin left over after animal decomposition (Trogidae).
1.7 Overview of Thesis
Both bees and haplogastran beetles have been suggested as indicator species of the
quality and characteristics of the landscape due to their sensitivity to disturbance and ties to
specific landscapes (Klein 1989, Schindler et al. 2013, Dorneles Audino et al. 2014,
Klimaszewski et al. 2018, Vieira et al. 2018). The following chapters provide an overview and
discussion on the findings of an experiment designed to test the response of bee and beetle
communities to disturbance type and landscape characteristics in the tallgrass prairie. Chapter 2
will be in a manuscript format and will focus on the response of bees to prairie disturbance,
environmental variables, and landscape characteristics. Chapter 3 will be in a manuscript format
and focus on the same characteristics applied to haplogastran beetles. Finally, chapter 4 will tie
together the findings of chapters 2 and 3 and discuss implications for prairie management going
forward.
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Chapter 2: Spatially diverse, unmanaged sites contain greater wild bee richness and
diversity than grazed sites in the tallgrass prairie ecosystem
2.0 Abstract
Tallgrass prairie is an increasingly rare environment that houses a variety of uncommon
and vulnerable plants and animals. Prairie management includes prescribed burns and cattle
grazing, which prevent woody encroachment and support diverse plant communities. Forbs,
which drive plant diversity in the prairie, proliferate with animal pollination. Management
directed at plant communities may affect pollinators differently. A survey of wild bees was
conducted on tallgrass prairie sites that had recently experienced burns, grazing, or no
disturbance, using ground and elevated bowl traps, as well as blue vane traps. Satellite imagery
and ground surveys were used to model how landscape context affects wild bee abundance and
diversity in tallgrass prairie. Most results imply that unmanaged sites had greater abundance and
diversity of bees than grazed sites, while burned sites were often intermediate. Rarefied richness
of ground-nesting bee diversity was greatest in burned sites, but stem-nesting bee diversity had
conflicting results, with abundance and species richness significantly greater in burned sites, but
rarefied diversity negatively affected by burns. Landscape diversity, at scales around that of the
typical foraging range for solitary bees, was often part of the best models of bee abundance and
diversity for bowl captured bees. Bowl traps were better than blue vane traps at detecting effects
of disturbance type, landscape diversity, and ground cover on bee diversity. These results suggest
that grazing of tallgrass prairie should be minimized for the proper preservation of vulnerable
wild bee communities.
2.1 Introduction
Tallgrass prairie (TGP) is the most productive grassland in the Great Plains (Joyce and
Morgan 1989). Southern Manitoba represents the northernmost extent of TGP, where less than
0.05% remains due to large scale conversion to agricultural land (Joyce and Morgan 1989),
making it one of the most endangered ecosystems in North America (Samson and Knopf 1994).
TGP is home to several rare or endangered species, such as the Powesheik Skipperling, Oarisma
poweshiek (Parker), and the Western Prairie Fringed Orchid, Platanthera praeclara Sheviak &
M.L.Bowles. These rare species, and others, have helped influence conservation efforts to focus
on the possibility of long-term viability through public interest. This has largely been through
recreation and ecotourism in the TGP (Costanza et al. 1997, Veech 2006, Gerla et al. 2012,
31
Berger et al. 2020). Alarmingly, the amount of TGP in Manitoba continues to decline (Koper et
al. 2010), and decreases in precipitation due to climate change threaten to further change the
prairie (Craine et al. 2011). Studies on remnant prairie in Manitoba suggest that smaller prairie
patch sizes tend to decrease in quality over time, possibly due to increased edge effects (Koper et
al. 2010).
TGP remnants in Manitoba are managed by burning, cattle grazing, mowing (more
prevalent recently due to inability to burn because of precipitation extremes and too much soil
moisture), and, minimally, haying (Sveinson 2003, A. R. Westwood (pers. comm.) 2021). These
practices aim to simulate the natural and Indigenous set fires and ungulate grazing that created
and maintained the TGP (Pyne 1986). These practices are typically focussed on plant diversity,
and have been much better studied in more southerly American TGP remnants, but animals are
also critical for the ecological function of TGP (Knapp et al. 1999). Bees are important
pollinators in grasslands that depend directly on floral diversity (Roulston and Goodell 2011).
Suppression of naturally occurring fire and grazing can lead to dominance of C4 grasses and loss
of forb diversity. Forbs are crucial for wild bee abundance, and bumble bee diversity in the
tallgrass prairie (Howe 1994, 2011, Hines and Hendrix 2005, Kelleher and Choi 2020). Burning
the prairie reduces the litter layer, which leads to increased soil temperatures, and subsequently
earlier plant growth (Ehrenreich and Aikman 1963). However, in Kansas TGP, topography may
play a role in plant biomass, with lowland sites accumulating significantly greater live biomass
compared to upland sites in a 10-year study (Abrams et al. 1986). As well, forb and woody plants
had 200–300% greater biomass in fire free sites compared to those that were annually burned
(Abrams et al. 1986). In more easterly TGP, increasing fire frequency has been shown to
increase the species richness of summer blooming forbs (Bowles and Jones 2013). Increased soil
temperature has been shown to lead to greater nesting rates in tallgrass prairie (Buckles and
Harmon-Threatt 2019). Fire also extends the flowering season in grasslands (Mola and Williams
2018).
In contrast, grazing is known to have several detrimental effects on prairie vegetation.
Cattle grazing leads to soil compaction, and favours some exotic species over native grasses
(Ehrenreich and Aikman 1963, Walters and Martin 2003). However, both cattle and bison
grazing increase forb cover in TGP (Towne et al. 2005). Forbs are the main driver of plant
32
biodiversity in TGP (Whiles and Charlton 2006). Grazers increase the nitrogen content of the
soil and preferentially feed on grasses over forbs, which can lead to increased plant nutrient
quality, reduced grass cover, and more prominent forbs (Moran 2014). Conversely, overgrazing
has been shown to reduce soil moisture, nitrogen, and organic matter in a fertile South Dakota
grassland (Beebe and Hoffman 1968). A study in Kansas TGP found that increased native plant
diversity was best promoted using high stocking rate intensities (Hickman et al. 2004). Similarly,
in Iowa and Missouri, combination fire and cattle grazing management has been shown to restore
exotic plant laden grasslands to become similar to TGP remnants (Delaney et al. 2016).
However, changes in management practices are known to affect relative frequencies of moisture
related forb communities in TGP, with a change from haying to burning corresponding to a shift
from more dry adapted plants to increasing frequency of mesic species (Dornbush 2004). A more
recent, large scale study examining the effects of burning versus grazing on Minnesota TGP
plant and soil characteristics found that management type did not affect vegetation communities,
and grazed sites differed from burned sites primarily due to increased soil density and soil
nitrogen content (Larson et al. 2020). Overall, a combination of infrequent burning and grazing
has been shown to maximize plant diversity in TGP (Collins and Calabrese 2012), but this is not
universally implemented (Wright Morton et al. 2010). This combination does not however
appear to be beneficial to wild bees in TGP (Buckles and Harmon-Threatt 2019).
Bees forage from a centralized nest, which make them ideal bioindicators for the quality
of their local environment (Gathmann and Tscharntke 2002, Schindler et al. 2013). Furthermore,
bees have a high genetic load, making them particularly sensitive to habitat degradation (Zayed
and Packer 2005). In the short-term, fire is predicted to negatively affect stem-nesting bees and
ground-nesting bees within 10 cm of the soil surface (Cane and Neff 2011). Due to the nature of
grassland fires, however, soils as close to the surface as 2 cm can remain at moderate
temperatures during wildfire events unless conditions allow the wildfire to remain in place for
some time (Neary and Leonard 2020). Burned sites experience a prolonged flowering period and
increased amount of bare soil and dead wood for nesting (Wrobleski and Kauffman 2003, New
2014, Mola and Williams 2018). Previous management and fuel load on the prairie can however
affect the community composition of the recovering plant species following a wildfire (Ewing
and Engle 1988). Grazing could affect the ability of ground-nesting bees to successfully nest due
to increased soil compaction (Trimble and Mendel 1995), and cattle may consume some floral
33
resources used by bees (Debano et al. 2016). Several recent studies have examined the response
of bees to management practices and landscape characteristics in American TGP. Studies in
Minnesota and Iowa/Missouri found that management type did not affect bee abundance (Smith
et al. 2016, Pennarola 2019), or richness and diversity (Pennarola 2019) but demonstrated that
decreased floral abundance and increased cattle stocking rate did negatively nutritional status of
bees and had marginally significant effects on abundance (Smith et al. 2016). Buckles and
Harmon-Threatt (2019) found that grazing in TGP negatively impacted the soil and floral
resources required for bees, and bee abundance and richness trended negatively (non-
significantly) under grazing compared to burning. Most recently, Griffin et al. (2021) found that
bison grazing had a negative effect on TGP bee abundance.
Bees are diverse in semi-natural landscapes (Le Feon et al. 2010), and respond negatively
to agricultural (Connelly et al. 2015, Harrison et al. 2017) and urban intensification (Harrison et
al. 2017). Bees respond positively to increased habitat heterogeneity in TGP (Denning and Foster
2018). Wooded area in the landscape surround TGP positively affects bee communities (Griffin
et al. 2017, 2021). However, bees respond differently to management practices and landscape
fragmentation based on their life history traits such as nesting strategy (Williams et al. 2010).
There are few published studies of bees in the Canadian Prairies. Patenaude (2007) and Olynyk
(2017, Olynyk et al. 2021) examined the diversity of bees, and their response to management
respectively in mixed-grass prairie. Robson (2008) studied the structure of insect pollinator floral
visits in TGP, while Semmler (2015) studied a similar framework but with fire providing an
opportunity to test for the effect of disturbance on pollinator communities. Further afield, Evans
(2013) demonstrated that landscape context was more important than grazed status of sites on
wild bee communities in fescue prairie in Alberta (2013). Vickruck et al. (2019) examined the
benefits of wetlands to wild bees in the Alberta prairie pothole region. Similarly, further studies
in the pothole region have demonstrated that prairie reclamation from agriculture in these areas
can return bee communities back to an undisturbed state (Purvis et al. 2020). Also in Alberta,
Kohler et al. (2020) studied the effects of prairie ecoregion on bee community properties.
Sheffield et al. (2014) produced a large review of the bee species occurring in the prairie
ecoregion, which has greatly assisted in understanding known species and their ranges in the
prairie provinces. Further work on the xeric hypothesis of bee distribution has been conducted
using field studies from Manitoba, and have demonstrated that while short-tongued bees do not
34
fluctuate greatly between different prairie/moisture level types, long-tongued bees are much
more abundant/important pollinators of the forb community in mixed grass prairie than in the
relatively wet tallgrass prairie (Robson et al. 2019).
I conducted a study in the Manitoba Tall Grass Prairie Preserve (MTGPP) that had three
key objectives, 1) determine the effects of disturbance type (burning vs. grazing vs. no recent
disturbance) on abundance, richness, and diversity of bees in TGP, 2) examine the effect of
landscape and ground cover characteristics on bee abundance, richness, and diversity in TGP,
and 3) compare responses of ground and stem-nesting bees to disturbance type, landscape, and
ground cover factors. I predict that disturbed sites, burned or grazed, will increase overall wild
bee diversity relative to undisturbed controls. Sites that experienced a semi-recent fire (1–6 years
post-fire) will likely have more bare ground and dead branches for ground and stem-nesting bees
to use, as well as greater forb diversity owing to fire negating the ability of few dominant plant
species taking over and reducing overall plant diversity (Towne and Kemp 2003, Howe 2011). I
expect semi-recent cattle grazing (0–11 years post-graze) to remove dominant C4 grasses leading
to more floral diversity for bees to use to have greater plant species richness (Hickman et al.
2004, Veen et al. 2008, Wagle and Gowda 2018). Bees often have greater or similar diversity in
burned sites than grazed ones (Buckles and Harmon-Threatt 2019, Pennarola 2019), so I predict
a similar pattern in my sites. I expect landscape heterogeneity to increase bee diversity across
disturbance types (Denning and Foster 2018). Although stem-nesters are susceptible to fire, the
time since fire in my systems should not lead to differences in ground and stem-nesting bees in
burned sites (Williams et al. 2010). Griffin et al. (2017) demonstrated that bee communities on
restored prairies reach an equilibrium within 2–3 years of seeding compared to remnant prairies.
Thus, the length of time since the fire in most of my sites should have little effect. However, a
study in Minnesota found that the frequent burns that characterize early restorations of TGP have
a randomizing effect on the associated bee communities (Tonietto et al. 2017). Buckles and
Harmon-Threatt (2019) found that grazing negatively affected the soil characteristics essential
for ground nesting bees, namely moisture content, compactness, and temperature. Stem-nesters
may be positively affected by the extent of forested habitat in the landscape (Main et al. 2019).
Decreases in several pollinator populations worldwide have been well documented (Potts et al.
2010, Jacobson et al. 2018, Mathiasson and Rehan 2019). As such, I hope that this study gives
35
insight into steps that policy makers can take that safeguard bee populations, and the grasslands
that depend on their pollination services.
2.2 Methods
2.2.1 Site selection
The study was conducted at 18 sites within the Manitoba Tallgrass Prairie Preserve
(Figure 2.1), Rural Municipality of Stuartburn, in southeastern Manitoba. MTGPP is the largest
remnant TGP in Canada. The preserve is divided into a south block 8 km north o f the
U.S./Canada border, and a much wetter north block, which is bounded to the north by a large
swamp, and to the west by the Roseau River. This study took place solely in the north block. The
MTGPP exists in an agriculture/aspen forest matrix and contains over 2,000 ha of remnant TGP.
Sites were selected in consultation with Nature Conservancy Canada based on fire and
grazing history, and ease of access. The minimum distance between sites ranged from
approximately 700–1,800 m. Typical foraging ranges for solitary bees are between 150 and 600
m (Gathmann and Tscharntke 2002) with maximum foraging ranges not greatly exceeding 1 km
(Zurbuchen et al. 2010). Sites were divided into three disturbance type groups. i) Six grazed sites
were used as cattle pasture at least once since 2007 but not burned since 1993 . One site was
grazed in 2006 and 2007; one site was grazed every year between 2008–2011; two sites were
grazed in 2011 and 2012, and two sites were grazed every year 2012–2016. One site was grazed
in 2018, with an enclosure placed around my sampling area to prevent disturbance. ii) Five
burned sites that were not used for cattle grazing since at least 1993. Four sites experienced a
2012 wildfire burn and one had a controlled burn in 2016. Drought conditions during the study
period prevented the use of controlled burns, so wildfire sites were used as a proxy for fire
disturbance. iii) Seven unmanaged sites that were not grazed or burned since at least 1993. I
grouped sites of each category into six separate blocks for sampling (one block had an extra
unmanaged site and no burned site due to fewer available burned sites). Site names, disturbance
type, and coordinates can be found in the supplementary material (Table 2.9).
36
Figure 2.1 Location of the study sites showing the location of the Manitoba Tallgrass Prairie
Preserve in context to Southern Manitoba and the adjacent province and states, with an insert of the layout of the locations of the 18 study sites and their disturbance grouping, with an insert showing the design set up of each study site, with yellow circles representing bee bowl stands, and blue triangles representing blue vane traps. Maps were made using ‘SimpleMappr’
(Shorthouse 2010).
2.2.2 Sampling Procedure
In each site, a 3 x 3 array of collection stations were set up, minimally spaced 15 m apart
(Figure 2.1). Collecting stations each include a pole with a central wooden platform holding
three bee bowl traps. The platform was raised to a height of approximately 1 m. Three additional
bowls were placed on the ground at the base of each pole, for a total of 54 bowls per site (Figure
2.2). A combination of ground-level and elevated traps is effective for catching a variety of wild
bees in tallgrass prairie (Geroff et al. 2014). Pre-painted 3.5 oz bowls were purchased from New
Horizons Supportive Services Inc. (Upper Marlboro, Maryland, USA), in three colours white,
30 m N 49.18
N 49.10
W 96.74 W 96.65
Provincial Rd 201
37
fluorescent blue and fluorescent yellow. These colours are commonly used in bee surveys
(Leong and Thorp 1999).
Bee bowls were ¾ filled with a 1:1 mixture of propylene glycol and water. Traps were
deployed for 48 h. A block of three sites were sampled simultaneously. Collections were made
every two to four weeks. Three samples were taken in 2017 maintaining the order of sampling
blocks in each sample (6–29 July, 1–13 August, and 17 August-5 September). Four samples
were taken in 2018.
Figure 2.2 (Left) Example of the ground level and elevated bee bowl station. Bowls placed in the foreground for the purpose of the photograph. (Right) Photo of a blue vane trap showing the
collecting chamber (yellow) and the trapping vanes (blue) (photo courtesy of Emily Hanuschuk).
(12–22 May, 3–11 June, 3–21 July, and 15–20 August). In 2018, four blue vane traps (BVTs)
(SpringStar Inc.) were deployed spaced equidistant from neighbouring bowl stations (Figure 2.1,
2.2), BVTs were filled with a few centimetres of the propylene glycol/water mixture. BVTs have
38
been shown to be very effective at catching wild bees (Stephen and Rao 2005), and catch many
large-bodied bees in greater numbers than bee bowls (Geroff et al. 2014, Joshi et al. 2015). BVTs
were only used in the last two rounds of sampling to avoid catching bumble bee gynes. In total
there were 126 observations for bee bowl caught bees, and 36 for BVTs.
2.2.3 Processing Bees
Bees were stored in the propylene glycol/water mixture and placed in the freezer until
processing. Bees were then washed and dried following the guidelines of Droege (2008). Bees
were placed in a detergent bath and mixed using a stirring rod before being transferred to 70%
ethanol. Bees were dried using a combination of a hair dryer and paper towel. Bees were th en
pinned, labeled, and databased. All vouchers are deposited at the J.B. Wallis/R.E. Roughley
Museum of Entomology at the University of Manitoba.
Bees were identified to genus (Packer et al. 2007) and then species using published
taxonomic revisions and keys (LaBerge 1956a, 1956b, 1961, Laverty and Harder 1988, Gibbs
2011), and keys hosted on DiscoverLife.org (Andrus and Droege 2018a, 2018b, 2018c, Griswold
et al. 2018, Droege & Rehan 2019). Joel Gardner and Amber Bass (University of Manitoba)
assisted with Lasioglossum and Melissodes identifications, respectively. Bee species were
categorized based on their nesting habitat (ground vs. stem nesting) using published literature
(Sheffield et al. 2014, Gibbs et al. 2017) to test for differing guild responses to disturbance type,
landscape, and ground cover features.
2.2.4 Ground cover characteristics
To account for local effects of floral diversity on my bee captures, ground cover was
assessed twice in 2018 at each site, during the second and fourth round of bee sampling. The
average of the two assessments was used as a measure of local floral diversity in models. A 1 x 1
m quadrat was thrown haphazardly forward a few metres into the sampling area 16 times. The
proportions of non-forb cover, flowering shrub and forb cover, and bare ground were estimated
based on ground cover percentages illustrated in Folk (1951). Woody shrubs and non-woody
forbs were all included in the percent shrub/forb value. The non-forb category included grasses
and vascular plants that do not flower such as Equisetum spp. The average percent covers of the
16 replicates were taken. The number of inflorescences were recorded. Then, a principal
39
coordinate analysis was used to extract the first axis using the ‘res.pca’ function of the package
‘FactoMineR’ (Le et al. 2008) ) (Figure 2.11).
2.2.5 Landscape mapping
Landscape data for MTGPP managed sites was provided by Nature Conservancy Canada
and its partners through a licensing agreement. Landcover within a 2 km radius of the study sites
that was not included in the NCC data were hand-digitized based on satellite imagery at a
1:5,000 scale in ArcMAP v. 10.6 (ESRI 2018). Buffers with radii of 250, 500, 1000, 1500, and
2000 m were created around the centroid of the study sites. The identity of the polygons present
in the NCC data layer were simplified to correspond to readily observable features in the satellite
imagery, thus prairie subcategories were all merged as ‘prairie’, marshes, wetlands, and swamps
were all merged in to one category, and different categories of forest were merged. The
following categories were used to represent different polygons: forest, peri-urban, structure,
savannah, water, swamp, prairie, pasture, crop, river, roadside ditch (‘edge’ in Figure 2.12), road,
and other.
Each buffer for each site was intersected to extract the polygons within the radius. I used
Patch Analyst v. 5.2 (Rempel et al. 1999) to calculate landscape metrics, including the Shannon
diversity index and the mean shape index. The Shannon diversity index is a measure of patch
diversity. Shannon diversity increases as the number and proportion of different patches increase
in the buffer and is maximized when all patch types are of equal proportions (Rempel et al. 1999,
McGaril & Marks 1994). The landscape mean shape index is a measure of patch shape
complexity. It has a value of one when all patches are perfectly compact (circular in shape when
using vector data) and increases as patch shape becomes more complex. The percent of different
covers were also extracted, and then submitted to principal coordinate analysis to extract the first
axis of ‘landcover’ at different buffer ranges.
2.3 Data analyses
2.3.1 Bee diversity & community composition
All analyses were performed in R (R Core Team 2017). Spatial autocorrelation was
checked in R using the ‘DHARMa’ package (R Core Team 2017, Hartig and Lohse 2020). All
bee bowl data were combined into a site x species matrix. BVT captures were analyzed
separately. I pooled samples from a given year and included communities from both years in
40
analyses. I expected that additional species collected in spring and possibly reduced captures
from competition with blue vane traps in the summer would affect the communities recorded in
2018. Community composition was compared across sites using distance-based redundancy
analysis (dbRDA) with the Bray-Curtis index in the package vegan (Legendre and Anderson
1999, Oksanen et al. 2018). The distance-based redundancy analyses were applied with
‘Disturbance Type’ and ‘Year’ as constraints and summarized, then visualised with the ‘ordiplot’
function of the vegan package (Oksanen et al. 2018). Permutational multivariate analysis of
variance (perMANOVA) was used to test for effects of disturbance type on bee communities
using the Bray-Curtis index in the ‘adonis’ function of the vegan package (Oksanen et al. 2018).
If a significant result (p<0.05) was received for the effect of disturbance type on bee community
distances, a post-hoc test was performed using the ‘pairwise.adonis’ function of the
pairwiseAdonis package (Martinez Arbizu 2017). The betadispersion among disturbance types
was also tested using the ‘betadisper’ function of the vegan package (Oksanen et al. 2018) to
ensure that disturbance types were equally dispersed so as not to violate the assumption of equal
dispersion of perMANOVA.
Rarefied species curves were made with the iNEXT package (Hsieh et al. 2019) to
compare species richness and other diversity indices corrected to the least abundant disturbance
type. This allows a visualization of the true and extrapolated diversity at a given abundance, and
corrects for the unequal sample sizes of the disturbance types (Chao et al. 2014). I used Hill
numbers, which are measures of the effective number of species in each disturbance type (Chao
et al. 2014). These are a unified group of indices based on the Rényi entropy (Rényi 1961) and
put forth by Hill (Hill 1973). The Hill numbers include q=0, which is simply the number of
species, q=1 which is the Hill’s Shannon number of effective species, it takes abundance into
account, but still weighs rare species quite heavily compared to q=2, the inverse Simpson’s
number of effective species, which puts more weight towards more abundant species (Chao et al.
2014). To understand how Hill numbers correspond to rarefied species curves, it is useful to note
that the Shannon and Simpson’s curves produce what is essentially an “effective species
number”, which is based on comparing the number of species recovered given the abundance of
the sample and translating that to give the number of species required to produce that same
number if all species were equally abundant (Chao et al. 2014). As noted by Chao et al. (2014),
the use of these Hill numbers in biodiversity studies solves many problems that have been raised
41
in the literature. A notable improvement is that these Hill values behave more intuitively. For
example, they double when two communities are combined that have no species in common but
the same abundance distribution.
2.3.2 Modelling
Generalized linear mixed-effects models (package glmmADMB (Skaug et al. 2012))
were used to test for differences between abundance and diversity (species richness and the
Hill’s Shannon number of effective species) among disturbance types (Jost 2007, Fournier et al.
2012, Skaug et al. 2012). I examined several explanatory variables including, year and day-of-
year. Meteorological data from a nearby weather station (Emerson MB, Environment and
Climate Change Canada) were included (average temperature and average precipitation of the
days the traps were out). Landcover data were included in a PCA and the first axis used in
models (Figure 2.12). The first axis of a ground cover PCA was also used in the models. Site was
used as a random effect in all models.
We first ran five global models that differed only by buffer size of the landscape data and
decided to analyse all models using the model with the lowest Akaike Information Criterion with
small sample size correction (AICc) score for bee abundance, which was the 1 km buffer. I then
created a model that included only year, BVT presence, average temperature, average
precipitation, and day of year. I then used the ‘dredge’ function of the MuMin package (Barton
2018) to see which of these variables appeared important based on their presence or absence in
the model with the lowest AICc. The variables that were part of the best model (based on lowest
AICc) using only those factors were kept in my base model for additional analyses. The
landscape variables, landcover PCA 1st axis, landscape mean shape index, landscape Shannon
diversity, groundcover PCA 1st axis, and disturbance type were added to the base model. The
model was then dredged again, and the model with the lowest AICc was chosen as the best
model.
Because all response variables were positive numbers, for discrete models, the negative
binomial, quasi-Poisson, or Poisson distributions were used based on which had the lower AICc
score and lower dispersion parameter (for negative binomial vs. quasi-poisson), or based on
whether or not they were overdispersed (Poisson) using the ‘check_overdispersion’ function of
the ‘performance’ package (Ludecke et al. 2020) (using the equivalent glmmTMB model). For
42
continuous models, the gamma distribution was used, except for the blue vane species richness
model, which fit a gaussian distribution. Models were checked for collinearity in their
explanatory variables, and their residual plots examined by using the ‘check_model’ function of
the ‘performance’ package (Ludecke et al. 2020), with correlations greater than (-) 0.75
considered highly correlated. The models and their alternate distributions were also ranked using
the ‘compare_performance’ function, but their dispersion parameters were the deciding factor if
negative binomial and quasi-Poisson distributions were approximately equivalent.
2.4 Results
2.4.1. Bee captures
I collected 1,562 bees in bee bowls over two years, representing 76 species in 20 genera
(Table 2.6, 2.7). The most efficient bee bowls, based on number of captures, were blue ground
bowls, and the least efficient were yellow elevated bowls. The majority of bee captures belonged
to the genus Lasioglossum (955 specimens), mostly in the subgenus Dialictus. I found one
provincial record, Lasioglossum (Dialictus) michiganense (Mitchell), a rare social parasite on
other Dialictus. The earlier start in the second field season allowed for more representation from
typically spring flying genera such as Osmia and Andrena. Blue vane traps caught 2,040 bees
representing 45 species in 17 genera (Table 2.8). Blue vane captures were dominated by
Melissodes spp. (1,238 specimens) and Bombus spp. (321 specimens). One bee species in the
blue vane captures, Triepeolus helianthi (Robertson), is previously unrecorded from the
province. One specimen of the oil collecting bee, Macropis nuda (Provancher), was found in the
blue vane trap captures.
2.4.2 Community Composition - Distance-based Redundancy Analysis & perMANOVA
Bee bowl community composition was significantly affected by disturbance history
(Figure 2.3, Table 2.1). Burned sites differed from grazed ones, but neither differed from
undisturbed sites. No difference in community composition was found when blue vane trap data
were analyzed. Disturbance and year explained approximately 19% of the variation in the total
bee communities, and approximately 16% of the variation in the ground nesting bee
communities. Burned and grazed bee communities may be marginally different when all bee
bowl captures are considered together.
43
Figure 2.3 Ordination plots of the Bray-Curtis distance-based redundancy analysis of bee bowl community data (all bees, left; ground-
nesting bees, centre; stem nesting bee communities, right) constrained by disturbance type and year. Each point represents a site in a
given year (2017 or 2018). Disturbance type had a significant effect on the combined community composition in both the
perMANOVA (Table 2.2, F = 1.75, R2 = 0.09, p = 0.017) and dbRDA (F = 1.6548, p = 0.034), resulting from a difference between
grazed and burned sites according to the perMANOVA (Tukey’s post-hoc test with a Bonferroni correction p = 0.078). In the ground
nesting bee communities, disturbance type had a significant effect according to perMANOVA (Table 2.2, , F = 1.76, R 2 = 0.09, p =
0.032) and dbRDA (F = 1.6280, p = 0.049), however a post-hoc test on the perMANOVA results did not uncover a significant
difference between any two disturbance types. Stem-nesting bee communities were not found to be significantly different by
disturbance type in either perMANOVA or dbRDA.
44
Figure 2.4 Ordination plot of the Bray-Curtis distance-based redundancy analysis of blue vane
trap captured bee communities constrained by disturbance type. Samples were combined by site
to avoid pseudo-replication. perMANOVA on the Bray-Curtis distances between disturbance
types revealed that they were not significantly distant from each other (p = 0.962) (Table 2.2).
Similarly, dbRDA did not uncover a significant effect of disturbance type.
Table 2.1 Summary of perMANOVAs performed on the Bray-Curtis distance of different bee communities. The Post-hoc column represents the results of a Tukey’s post-hoc test with a Bonferroni correction. B = ‘Burned’, G = ‘Grazed’, U = ‘Undisturbed’.
Community F model R2 p value Post-hoc
All bee bowl captures
1.7489 0.08763 0.017 B-G: 0.078 B-U: 0.291 G-U: 0.546
Blue vane trap captures
0.429 0.05411 0.962
Ground-nesting bee bowl captures
1.7565 0.09052 0.032 B-G: 0.141 B-U: 0.198
G-U: 0.720 Stem-nesting bee
bowl captures
1.3924 0.06548 0.126
2.4.3. Abundance, Species Richness, and Hill’s Shannon Diversity Modeling
45
2.4.3.1. Effect of Disturbance Type
All models used land cover variables at the 1 km radius based on that distance producing
the lowest AICc score in my global abundance model. Disturbance type was never among the
best models for blue vane trap captures. However, my best-fit model for bee bowl abundance
found a significant effect of disturbance type. Data were over-dispersed, so a negative binomial
distribution was used. Grazed sites supported significantly fewer bees than undisturbed sites
(Figure 2.5). Similarly, disturbance type was a significant variable in my best fitting model for
species richness (Figure 2.5). The data were over-dispersed, and a quasi-Poisson distribution
resulted in a lower dispersion parameter than a negative binomial distribution. In the case of
species richness, grazed sites were less species rich than both burned and undisturbed sites.
Disturbance type was also recovered in the best model to explain Hill’s Shannon effective
species number (Figure 2.5). The effective species number model was fit with a gamma
(link=log) distribution. Once again, grazed sites supported less diversity than undisturbed sites.
For ground nesting bees caught in bee bowls, disturbance type was not part of the best
model for bee abundance (Table 2.2). However, disturbance type was a signif icant variable in the
model that best explained ground nesting bee species richness (Figure 2.6). The model was
overdispersed and conformed approximately to a quasi-Poisson distribution (Table 2.3). Grazed
sites had significantly less species richness than undisturbed sites, however ground nesting bee
Hill’s Shannon (q=1) diversity was not significantly affected by disturbance type (Table 2.3).
46
Figure 2.5 Effect plot showing the predicted effect of disturbance type on bee bowl trap abundance (left), species richness (centre),
and Hill’s Shannon effective species number (right) when all other variables in the GLMM are held at their average or default state.
Different letters above the disturbance types represent significantly different results (p = less than 0.05) based on a GLMM where site
was used as a random effect. Points represent the median value of the predictor variable of the disturbance type subset , and whiskers
represent 95% confidence intervals.
47
Stem-nesting bee abundance was significantly affected by disturbance type, with burned
sites supporting significantly more stem nesting bees than grazed sites (Figure 2.7). The model
was over-dispersed and fit with a negative binomial distribution. Stem-nesting bee species
richness was also affected by disturbance type, with burned sites having greater species richness
than grazed sites (Figure 2.8). Stem-nesting bee effective species numbers were not significantly
different between disturbance types (Table 2.4).
Figure 2.6 Effect plot showing the predicted effect of disturbance type on ground nesting bee
species richness when all other variables in the GLMM are held at their average or default state.
Different letters above the disturbance types represent significantly different results (p = less
than 0.05) based on a GLMM where site was used as a random effect. Points represent the
median value of the predictor variable of the disturbance type subset, and whiskers represent
95% confidence intervals.
48
49
Figure 2.7 Effect plot showing the predicted
effect of disturbance type on stem nesting bee
abundance when all other variables in the GLMM
are held at their average or default state. Different
letters above the disturbance types represent
significantly different results (p = less than 0.05)
based on a GLMM where site was used as a
random effect. Points represent the median value
of the predictor variable of the disturbance type
subset, and whiskers represent 95% confidence
intervals.
Figure 2.8 Effect plot showing the predicted
effect of disturbance type on stem nesting bee
species richness when all other variables in the
GLMM are held at their average or default state.
Different letters above the disturbance types
represent significantly different results (p = less
than 0.05) based on a GLMM where site was used
as a random effect. Points represent the median
value of the predictor variable of the disturbance
type subset, and whiskers represent 95%
confidence intervals.
50
2.4.3.2. Effect of landscape characteristics
Of the three landscape characteristics I analysed, the landscape Shannon diversity and
the landcover PCA appeared most consistently in the best models for bee bowl trap captures . The
landcover PCA had several landcover types along the primary axis, including prairie, water,
savannah, and swamp grouping along the negative side of the first axis, and forest, pasture, ditch,
and road on the positive side of the first axis. The first axis of the landcover PCA accounted for
over 40% of the variation in the measured landcover types. Both Shannon diversity and the
landcover PCA had a positive effect on abundance, richness, and Hill’s Shannon effective
species number, implying that more diverse landscapes support greater wild bee diversity in the
prairie, and that increased cover of variables like forest and ditch (‘edge’ in Figure 2.12) had a
positive effect, while increased prairie, savannah, and swamp cover had a negative effect on bee
diversity. The mean shape index, which approximates the amount of edge in the environment,
also had a positive effect on bee effective species number for bee bowl captured bees. The trend
was the same when looking at only the ground nesting captures, however only the stem nesting
bee abundance and richness responded significantly to increasing landscape Shannon diversity.
The blue vane trap captures did not pick up on any landscape effects, except for a
positive effect of the landcover PCA on the number of effective species.
2.4.3.3. Effect of groundcover characteristics
The combined bee bowl captures, as well as the ground nesting captures responded to the
groundcover PCA in several models. The groundcover PCA had percent grass cover positioned
on the negative aspect of the first axis, while percent forbs, number of flowers, and to a lesser
extent percent bare ground grouped on the positive side of the first axis. The first axis of the
groundcover PCA accounted for over 64% of the variation in the measured ground
characteristics. In all cases, the groundcover PCA had a positive effect, which goes in the
direction of increased forb cover, number of flowers, and slightly towards more increased bare
ground in the environment, and away from increasing grass cover (Figure 2.11). Neither stem
nesting bees, nor blue vane captures responded to the groundcover PCA.
2.4.4 Rarefaction
Grazed sites had significantly less rarefied diversity for each of the first three Hill
numbers. This pattern was less evident in blue vane captures, which only showed an effect
51
between grazed (less diverse) and undisturbed (more diverse) sites when q=2 and dominant
species are given greater weight in the analysis. Ground-nesters and stem-nesters differ in their
rarefied diversity when q=1 and 2. Ground-nesters are like the total community and accumulate
diversity more rapidly in burned sites. But stem-nesters show the greatest rarefied diversity in
undisturbed sites and burned sites are lowest, though this may be driven by high abundance of
common species in burned sites lowering the diversity (Figure 2.9, Figure 2.10).
52
Figure 2.9 Rarefied curves of the entire bee bowl captured community (top), and the blue vane captured community (bottom). The Q
numbers represent the different Hill numbers, with q=0 representing rarefied species richness, q=1 representing rarefied Hill’s
Shannon effective species number, and q=2 representing rarefied Inverse Simpson’s effective species number.
S
pec
ies
Div
ersi
ty
Q=0 Q=1
Q=2
S
pec
ies
Div
ersi
ty
Q=0 Q=1
Q=2
53
Figure 2.10 Rarefied curves of the ground nesting bee bowl captured community (top), and the stem nesting bee bowl community
(bottom). The Q numbers represent the different Hill numbers, with q=0 representing rarefied species richness, q=1 representing
rarefied Hill’s Shannon effective species number, and q=2 representing rarefied Inverse Simpson’s effective species number.
S
pec
ies
Div
ersi
ty
S
pec
ies
Div
ersi
ty
Q=0
Q=0
Q=1
Q=1
Q=2
Q=2
54
2.5 Discussion
I found significantly greater abundance and diversity in undisturbed sites of the TGP than
in grazed sites. Burned sites were intermediate. Pollinator abundance is positively correlated with
TGP plant diversity (Kelleher and Choi 2020). Floral richness in TGP is maximized under
disturbance at intermediate timescales (burning only once every four years) in Kansas TGP, but
too frequent disturbances act as extinction causing events (Collins et al. 1995). Alternatively, the
litter accumulation in undisturbed sites itself acts as a form of disturbance, leading to increased
plant diversity (Bascompte and Rodríguez 2000). The latter theory could explain the increased
abundance and diversity of bees on my undisturbed sites compared to my grazed sites if they are
directly responding to greater floral richness, although it is not entirely clear if greater floral
diversity predicts wild bee status in TGP (Griffin et al. 2021). Conversely, bumble bees are
known to be more diverse in TGP sites with greater floral diversity (Hines and Hendrix 2005).
These conflicting results could be because increased floral diversity does not necessarily equate
to benefits for bees if the increased richness comes at the cost of less coverage of a more
rewarding abundant floral source. As well, not all floral resources can be used by bees in TGP
due to floral morphology, for example the Western Prairie Fringed Orchid, which is adapted
solely for moth pollinators. The greater rarefied richness of bees in my burned, or even the
greater abundance of bees in my undisturbed sites, could be in response to these mechanisms.
Hymenopteran pollinators have been shown to respond positively, via increased abundance and
species richness, to wildfire events (Carbone et al. 2019), which characterized the majority of my
burned sites. Pollinator communities are known to show greatest abundance and diversity under
wild, but infrequent (10-12 year gaps) (Carbone et al. 2019), high intensity fires (Galbraith et al.
2019). Prescribed fires do not reflect the real intensity of once more common tallgrass prairie
fires, which may be artificially affecting studies on prairie ecosystem functioning (Twidwell et
al. 2016).
Though undisturbed sites may have overall higher plant diversity, woody encroachment,
a potential consequence of fire suppression, can reduce abundance and diversity of perennial
dicot forbs and legumes, many of which are likely bee pollinated (Taft and Kron 2014).
Increasing shade brought on by woody plant encroachment decreased plant-pollinator
interactions in Illinois prairie, with more shaded flowers receiving less pollen input from
pollinators, ultimately affecting their ability to propagate (Chi and Molano-Flores 2015).
55
Conversely, greater woody encroachment increased the amount of bare ground in the
environment (Taft and Kron 2014), which could explain my positive effect of forest in the
landscape on ground nesting bees.
A review on the effect of grazing on grassland plants and arthropods found that plants
were not affected by increasing grazing pressure, however arthropods were often negatively
affected by increased grazing intensity (van Klink et al. 2015). Even relatively infrequent
trampling events on soil can negatively affect grassland arthropods, much less than what is
required to affect grassland plant communities (Duffey 1975, van Klink et al. 2015). Grazing is
known to compact the soil in grassland environments (Trimble and Mendel 1995). This could
make it more difficult for ground nesting bees to dig nests, though as Sardiñas and Kremen
(2014) point out, compaction preference is likely context dependent. It also reduces water
infiltration (Trimble and Mendel 1995), which could presumably have a positive effect if there is
no standing water, or a very detrimental effect on ground nesting bees if water is allowed to
collect above nest entrances, which was very likely the case in all of my sites, where the water
table was at the surface of the soil in the North block of the MTGPP, where I was sampling, until
early July (personal observation). This despite the fact that early season conditions in both 2017
and 2018 were drier than usual in Southern Manitoba (Manitoba Conservation and Water
Stewardship 2017, 2018). This could also explain why increasing road and ditch cover in the
environment, which are well drained, increased bee abundance, richness, and diversity in my
combined and ground nesting bee models.
This study supports a few recent studies that point to the negative effects that grazing has
on wild bee populations in tallgrass prairie (Buckles and Harmon-Threatt 2019, Griffin et al.
2021). Another study compared TGP specifically with grazed bison and cattle pastures and found
that restored TGP housed a greater abundance and richness of wild bumble bees, however they
unfortunately did not disclose how or if the TGP in their study was actively managed
(Rosenberger and Conforti 2020). Some grassland studies have found positive effects of grazing
on bee abundance and species richness compared to abandoned and undisturbed sites (Kormann
et al. 2015), however they did find a negative effect of grazing on red-listed species richness
across multiple taxa. In grassland sites exposed to differing levels of number of mowing regimes,
wild bee richness, the number of insect-flower interactions, and plant species richness were all
56
greater in sites with a history of lower intensity mowing (Weiner et al. 2011), which could
explain my grazing effects if they are acting equivalently and occurring too frequently or under
too much intensity. Unfortunately, grazing intensity records at my sites were not available.
Stem-nesting bees had lower rarefied diversity in my burned sites, though greater Hill’s
Shannon diversity in my models. This seemingly conflicting result is likely the result of a high
abundance of Hoplitis pilosifrons (Cresson 1864) in burned sites lowering the rarefied diversity.
Above-ground nesting bees are more susceptible to nest destruction from disturbances than
below-ground nesting species (Spiesman et al. 2019). Insects tracked in a burned TGP recovered
within two years, however inability to move away from the fire, such as the case of larval and
pupal stem nesting bees, was a significant determinant of initial negative effects (Panzer 2002).
Most of my burned sites were subjected to a high intensity fire in 2012, which could have
contributed to the high proportions of ground nesting to stem nesting bees found in this study, as
well as a previous study on the effects of wildfire in MTGPP (Semmler 2015). However, a global
synthesis failed to find a difference in response to fire between abundance and richness of
ground nesting and stem nesting hymenopterans, though all hymenopterans had a more positive
response to wildfires than to prescribed fires (Carbone et al. 2019).
Decreased landscape diversity reduces wild bee species richness in grassland ecosystems
(Jauker et al. 2013, Hopfenmuller et al. 2014). Greater landscape heterogeneity in Kansas TGP
increased wild bee diversity (Denning & Forster 2018). My results suggest that bees respond
negatively to increasing prairie and savannah landcover, and benefit from greater crop and
pasture lands. This contrasts with other studies that have found that bees respond positively to
increasing grassland cover in the environment, both in the tallgrass prairie ecoregion (Denning
and Foster 2018, Evans et al. 2018, Griffin et al. 2021) and in other grassland systems (Sjödin et
al. 2008). Bees are negatively impacted by increased crop cover in the environment (Holzschuh
et al. 2010, Kohler et al. 2020, Shaw et al. 2020), but my results suggest that pasture and crop
areas in the landscape benefitted bees, but this could be due to bees being more concentrated in
my prairie patches when crop and pasture were present in the surroundings, or pasture and crop
areas, which together accounted for an average of 21.73 +/- 15.01% of cover type, may be more
well drained than the relatively wet prairie. Open water and swamp are correlated with prairie
and savannah in the landscape surrounding my study sites. Alternatively, pasture and crop area
57
may be correlated with a cover type such as ditch that is the actual source of beneficial area to
bees. However, pastures can benefit wild bees in agriculturally intensive areas (Morandin et al.
2007), and should perhaps be included in future studies in TGP given their ubiquity, at least for
the purposes of comparison to remnant sites.
The areas adjacent to prairie fields are known to influence prairie bee communities.
Positive effects of forest cover (Evans et al. 2018, Griffin et al. 2021) or forest edge (Neumüller
et al. 2020, Rivers-Moore et al. 2020) on wild bee communities in grasslands, have been found
previously, although successional stage of the forest may be an important, overlooked factor
(Odanaka and Rehan 2020). Neumüller et al. (2020) found a positive effect of ruderal areas on
wild bees, which could be equivalent to my positive effect of ditches/road verges, as both are
characterised by high numbers of dicot forbs, although I did not quantify this in my study. Prairie
road verges seeded with prairie plants are known beneficial resources for bees owing to their
floral and ground nesting opportunity resources (Hopwood 2008). Another study in Manitoba
prairies found a negative effect of proximity to road edges on wild bees, though specifically only
on social bees (Olynyk et al. 2021). One large, multi-national study confirmed that diverse
landscapes had positive effects on wild bees, but did not uncover significant effects of a
landscape variable that included a patch shape index (Kennedy et al. 2013). In contrast, one
study in TGP did find a positive effect of edge density on wild bees (Denning and Foster 2018),
consistent with my findings.
Several studies have successfully demonstrated that bees are positively affected by
increased flower or forb abundance (Sjödin et al. 2008, Crist and Peters 2014), and specifically
by native flowering plant abundance in TGP (Stein et al. 2020). It has also been shown that bee
richness is positively affected by increased flowering plant richness (Batáry et al. 2010, Lane et
al. 2020). On the other hand, other studies demonstrate a clear effect of disturbance type with no
effects of flower abundance or richness on wild bees in TGP (Davis et al. 2008, Griffin et al.
2021). My results, along with another recent grassland study (Rotchés-Ribalta et al. 2018),
suggest that both disturbance type and, though my groundcover measurements were very
preliminary, local landscape factors are at play in shaping wild bee communities. Future studies
should analyse a much greater suite of soil and grass/forb vegetation factors to determine how
these factors may be behind the conflicting results found in studies of how disturbance drives
58
prairie insect composition (A. R. Westwood (pers. comm.) 2021). Reduction in floral availability
is proposed to be one of the most important contributors to the worldwide decline of wild bees
(Goulson et al. 2015). Pollinator visitation rates are known to be maximized under low intensity
management, and pollinator species richness is likewise maximized with high flowering plant
richness and cover in grassland ecosystems (Hudewenz et al. 2012). A study on bumblebee
abundance and diversity found that both measures were influenced by local and landscape scale
features in small TGP remnants (Hines and Hendrix 2005).
Functional traits may mediate pollinator responses to management (Rotchés-Ribalta et al.
2018). I found that both ground nesting bees and stem nesting bees appear to generally respond
positively to burning, at least relative to grazing. However, rarefaction analysis suggest that
stem-nesting bees accumulate diversity more slowly in burned sites. A study on uncultivated
strips in European agricultural grasslands found that only above ground nesting bumblebees
responded positively to increasing landscape heterogeneity (Ekroos et al. 2013), which agrees
with my models. Studies in European grasslands have reported significant effects of landscape
composition and diversity on wild stem-nesting bees (Steckel et al. 2014), but I failed to see this
pattern in my data. It is possible that I simply did not capture enough stem nesting bees in my
study to generate conclusive results on the effects of landscape and groundcover in my stem
nesting bee GLMMs. Alternatively, the randomizing effect of disturbance of TGP management
on bee communities, as demonstrated by high beta diversity of the bee communities between
restored sites in Tonietto et al. (2017), could be a significant factor in shaping the bee
communities that I caught. This is explained by disturbance leading to a somewhat random
founding population occurring in sites after disturbance, with sites becoming more similar with
increasing time since disturbance (Tonietto et al. 2017).
More general pollinator assessments should include syrphid flies, as flies are more
frequent flower visitors in northern TGP (Robson 2008). My sites were in wet prairies that may
have limited nesting for bees but would benefit moisture-dependent syrphids. Indeed, a previous
study in the MTGPP found that there was increased syrphid abundance at wetter sites (Semmler
2015). Furthermore, some large syrphids carry as much pollen as honey bees, but they are too
often ignored in pollination studies (Chisausky et al. 2020). Other flies are even more neglected
59
as pollinators although collectively they may transport five times more pollen than syrphid flies
in agricultural settings (Orford et al. 2015).
Trap type can influence bee samples in TGP, but context matters (McCravy et al. 2019).
In my study, blue bowl traps were the most successful, and yellow bowl traps the least
successful, at catching bees. In contrast, yellow traps were most effective in an Iowa TGP study
(Kwaiser and Hendrix 2008). This variability is an important justification for using traps of
multiple colours in surveys. However, combining trap types may not always improve clarity.
Bowl traps showed significantly lower species richness when BVT were present in my study.
Furthermore, BVTs failed to detect effects of disturbance type, local groundcover, and landscape
level composition and configuration, which were evident in the bowl data. One study found that
BVTs are more accurate at representing captures that are driven by usable habitat in the area, but
worse at reflecting the importance of local scale factors (Rhoades et al. 2017). This somewhat
agrees with my finding that landcover mattered in the case of bee Hill’s Shannon diversity in my
BVT captures and that groundcover effects were not present in any of my BVT models. BVTs
have also been shown to bee poor proxies for net collections from targeted plant species (Gibbs
et al. 2017). This suggests that BVTs should be used with caution when assessing endangered
area biodiversity, as they may fail to pick up on significant threats to wild pollinators and may
interfere with other trapping methods.
Future studies should measure soil properties, including litter depth, as increased litter
depth is known to have negative effects on wild bees in Manitoba prairies (Olynyk et al. 2021).
This could be an important factor explaining why grazed sites were overall worse for bees, and
potentially why grazed sites showed significantly less rarefied richness than burned sites in both
the total bee and ground nesting bee communities.
I caught a single Macropis nuda female in one of my blue vane traps, and I observed their
host plant, Lysimachia at some of my sites. Two other M. nuda specimens are known from the
preserve and its immediate vicinity (Gibbs et al. 2021). Macropis nuda is a host of the federally
endangered cuckoo of this bee, Epeoloides pilosulus (Cresson), which has been recently
collected near the preserve (Gibbs et al. 2021). Additional efforts to locate this rare species in
MGTPP and determine effects of disturbance type on its survival would be warranted.
60
My study sites were relatively close together due to constraints of the MGTPP and areas
within it that had been with burns and grazing allow sufficient time to conduct this study along
with a parallel study using pitfall traps. I found no evidence of spatial autocorrelation, but it
would be beneficial to sample a wider breadth of TGP remnants in the province to see if my
results are consistent across different regions. Comparison to sites with prescribed fires would be
important to determine if my wildfire sites are useful proxies for this disturbance type.
My sites were quite depauperate and variable of flowers, as demonstrated by the average
number and standard deviation in my quadrat samples, 23.75 (±20.71), but other areas of the
MGTPP can have locally dense flower patches (pers. obs.). Bowl trapping alone may be
sufficient in sampling bee communities when floral abundance is low (Roulston et al. 2007).
However, passive sampling is worse at capturing abundance and richness of wild bees compared
to net sampling (Prendergast et al. 2020), suggesting that a follow up study should incorporate
net sampling in the TGP, at least at the relatively flower rich roadsides.
Given the conflicting results obtained among several TGP bee studies, it appears likely
that differences in burn season/intensity and grazing intensity can create quite dissimilar
conditions between studies. Therefore, as many land use history, vegetation, and soil variables as
possible should be collected during future research to try and unravel the seeming discrepancies
between studies.
2.6 Conclusion
My study shows that different disturbance practices can lead to significant changes in
TGP bee communities, and that cattle grazing should be minimally implemented to best preserve
wild bee abundance and diversity. My results also demonstrate that landscape diversity in TGP
benefits bees, as well as suggesting that broader landcover, and local ground cover influence bee
bowl captures in TGP. As well, this study highlights the potential hazards of sampling solely
with blue vane traps, as they failed to pick up on the patterns observed in the bee bowl captures.
My rarefied curves also highlighted the differential response to disturbance type between ground
nesting and stem nesting bees, implying that refugia should be maintained, when possible, to
maximize TGP bee diversity.
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2.8 Chapter 2 Supplementary Material
Figure 2.11 Graph showing the first two axes of a PCA performed on groundcover data obtained
by averaging two rounds of quadrat sampling performed in 2018. 16 quadrats were recorded
from each study site and then averaged by site. This was done twice, once in June, and once in
August. The site averages of the two rounds were once again averaged to obtain the results put in
to the PCA.
73
Figure 2.12 Graph of the first two axes of a principal coordinate analysis performed on percent cover on the various landscapes found at 1 km from the centre of study sites.
74
Bee Model Tables
Table 2.2 Results of GLMMs performed on bee bowl capture abundance, species richness, and Hill’s Shannon Effective Species Number. Site was used as a random effect in all models. In total there were 126 observations, with 18 observations of ‘Site’. Landcover variables were
measured using a 1 km radius. The first axis of PCAs for landcover and groundcover were used. The models represent the submodel with the lowest AICc score.
Response Variable
Fixed Effects Est. Std. Error z value p value
Abundance
Intercept 1.905 1.042 1.83 0.067
Year (2017) 0.693 0.168 4.13 <0.001
Day-of-year -0.02 0.002 -8.93 <0.001
Avg. Temp. 0.077 0.035 2.19 0.028
Avg. Precip. -0.14 0.056 -2.55 0.011
Shannon Div. 1.894 0.447 4.23 <0.001
Landcover PCA 0.135 0.044 3.04 0.002
Treatment: Grazed -0.31 0.199 -1.57 0.116
Treatment: Undisturbed 0.071 0.221 0.32 0.747
Groundcover PCA 0.109 0.044 2.48 0.013
Species Richness
Intercept -0.17 0.524 -0.33 0.745
Year (2017) -0.49 0.105 -4.64 <0.001
BV (Yes) -0.70 0.125 -5.64 <0.001
Avg. Precip. -0.10 0.056 -1.86 0.062
Shannon Div. @ 1 km 1.424 0.310 4.59 <0.001
Landcover PCA @ 1 km 0.109 0.032 3.37 <0.001
Treatment: Grazed -0.28 0.137 -2.07 0.038
Treatment: Undisturbed 0.108 0.147 0.73 0.463
Hill’s Shannon
Effective Species Number
Intercept -0.67 0.576 -1.16 0.246
Year (2017) -0.34 0.117 -2.89 0.004
BV (Yes) -0.49 0.128 -3.81 <0.001
Shannon Div. @ 1 km 1.243 0.307 4.04 <0.001
Landcover PCA @ 1 km 0.088 0.031 2.89 0.004
Landscape MSI @ 1 km 0.156 0.10 1.57 0.116
Treatment: Grazed -0.23 0.139 -1.65 0.098
Treatment: Undisturbed 0.10 0.156 0.64 0.522
Model Distribution Dispersion Parameter
Random Effect S.D.
AIC Log
Likelihood R2C
75
Abundance Negative Binomial
2.52 (+/- 0.43) 0.103 827.2 -401.588 0.219
Sp. Rich. Qausi-
Poisson 1.42 (+/- 0.20) 0.061 612.2 -296.115 0.672
Hill’s Shannon
Gamma (Log Link)
3.43 (+/- 0.41) <0.001 551.9 -265.948 0.273
Table 2.3 Results of GLMMs performed on ground-nesting bee bowl capture abundance, species richness, and Hill’s Shannon Effective Species Number. Site was used as a random effect in all
models. The models represent the submodel with the lowest AICc score.
Response
Variable Fixed Effects Est. Std. Error z value p value
Abundance
Intercept 1.397 1.208 1.16 0.248
Year (2017) 0.722 0.180 4.00 <0.001
Day-of-year -0.02 0.003 -7.41 <0.001
Avg. Temp. 0.083 0.039 2.14 0.032
Avg. Precip. -0.14 0.061 -2.28 0.023
Shannon Div. @ 1 km 1.646 0.552 2.98 0.003
Landcover PCA @ 1 km 0.154 0.045 3.42 0.001
Groundcover PCA 0.121 0.056 2.16 0.030
Species
Richness
Intercept -0.89 0.572 -1.55 0.120
Year (2017) -0.19 0.119 -1.60 0.109
BV (Yes) -0.36 0.137 -2.66 0.008
Avg. Precip. -0.12 0.059 -1.95 0.051
Shannon Div. @ 1 km 1.517 0.339 4.47 <0.001
Landcover PCA @ 1 km 0.130 0.036 3.59 <0.001
Treatment: Grazed -0.25 0.150 -1.68 0.094
Treatment: Undisturbed 0.114 0.163 0.70 0.485
Groundcover PCA 0.034 0.033 1.02 0.307
Intercept -2.19 0.765 -2.87 0.004
76
Hill’s
Shannon
Effective
Species
Number
Year (2017) -0.57 0.251 -2.29 0.022
Day-of-year 0.007 0.003 2.43 0.015
BV (Yes) -0.63 0.218 -2.89 0.004
Shannon Div. @ 1 km 1.023 0.330 3.10 0.002
Landcover PCA @ 1 km 0.105 0.028 3.71 <0.001
Landscape MSI @ 1 km 0.243 0.109 2.23 0.026
Model Distribution Dispersion
Parameter
Random
Effect S.D. AIC
Log
Likelihood R2C
Abundance Negative
Binomial 2.20 (+/- 0.39) 0.239 786.2 -383.114 0.231
Sp. Rich. Qausi-
Poisson 1.22 (+/- 0.19) 0.019 545.2 -261.582 0.440
Hill’s Shannon
Gamma (Log Link)
3.65 (+/- 0.47) 0.131 469.9 -225.971 0.265
Table 2.4 Results of GLMMs performed on stem-nesting bee bowl capture abundance, species richness, and Hill’s Shannon Effective Species Number. Site was used as a random effect in all models. The models represent the submodel with the lowest AICc score.
Response
Variable Fixed Effects Est. Std. Error z value p value
Abundance
Intercept 2.680 1.283 2.09 0.037
Day-of-year -0.02 0.003 -7.45 <0.001
BV (Yes) -0.51 0.271 -1.87 0.062
Shannon Div. @ 1 km 1.761 0.725 2.43 0.015
Treatment: Grazed -0.80 0.312 -2.55 0.011
Treatment: Undisturbed -0.29 0.288 -0.99 0.323
Species
Richness
Intercept 1.927 0.913 2.11 0.035
Day-of-year -0.02 0.002 -6.29 <0.001
BV (Yes) -0.46 0.265 -1.73 0.083
77
Groundcover 0.082 0.056 1.46 0.143
Treatment: Grazed -0.51 0.230 -2.23 0.026
Treatment: Undisturbed -0.17 0.206 -0.84 0.399
Hill’s
Shannon
Effective
Species
Number
Intercept 2.433 0.237 10.27 <0.001
Day-of-year -0.01 0.001 -8.21 <0.001
Avg. Precip. -0.10 0.037 -2.62 0.009
Model Distribution Dispersion Parameter
Random Effect S.D.
AIC Log
Likelihood R2C
Abundance Negative Binomial
1.62 (+/- 0.43) 0.239 464.2 -224.076 0.432
Sp. Rich. Quasi-
Poisson 1.50 (+/-0.22) 0.015 398.8 -190.395 0.671
Hill’s
Shannon
Gamma
(Log Link) 4.89 (+/- 0.64) 0.197 294.3 -142.132 0.471
Table 2.5 Results of GLMMs performed on blue vane bee capture abundance, species richness, and Hill’s Shannon Effective Species Number. Site was used as a random effect in all models. The models represent the submodel with the lowest AICc score.
Response
Variable Fixed Effects Est. Std. Error z value p value
Abundance
Intercept -7.92 1.401 -5.65 <0.001
Day-of-year 0.040 0.006 6.29 <0.001
Avg. Temp. 0.163 0.058 2.82 0.005
Avg. Precip. 0.287 0.077 3.75 <0.001
Intercept 18.287 4.662 3.92 <0.001
78
Species
Richness
Day-of-year -0.05 0.021 -2.22 0.027
Avg. Precip. 0.735 0.238 3.08 0.002
Hill’s
Shannon
Effective
Species
Number
Intercept 8.287 0.687 12.07 <0.001
Day-of-year -0.02 0.002 -9.17 <0.001
Avg. Temp. -0.14 0.024 -5.79 <0.001
Landcover PCA @ 1 km 0.049 0.019 2.56 0.010
Model Distribution
Dispersion
Parameter/Residual Variance
Random
Effect S.D.
AIC Log
Likelihood R2C
Abundance Negative Binomial
5.41 (+/- 1.42) 0.001 328.9 -158.447 0.109
Sp. Rich. Gaussian 1.63 (+/- 0.26) 0.038 147.6 -68.7832 0.501
Hill’s Shannon
Gamma (Log Link)
27.07 (+/- 8.52) 0.105 113.9 -50.9339 0.793
79
Table 2.6 List of species caught in bee bowls in 2017 along with their nesting guild (G = ground,
S = stem (above ground) and distribution of numbers caught between the three treatments: B =
burned, G = grazed, U = undisturbed. The other columns represent the types of bee bowls they
were caught in, with B.G. = blue ground bowl, Y.G. = yellow ground, W.G. = white ground,
B.E. = blue elevated, Y.E. = yellow elevated, and W.E. = white elevated.
Species Author Nest B G U B.G. Y.G. W.G.
B.E. Y.E. W.E. Total
Agapostemon
texanus
Cresson 1872 G 0 0 1 1 0 0 0 0 0 1
Agapostemon
virescens
(Fabricius 1775) G 0 0 1 0 0 0 1 0 0 1
Anthophora
terminalis
Cresson 1869 S 6 3 7 8 0 2 5 1 0 16
Augochlorella aurata (Smith 1853) G 3 1 4 4 2 2 0 0 0 8
Bombus borealis Kirby 1837 G 9 6 3 11 1 0 6 0 0 18
Bombus fervidus (Fabricius 1798) G 6 3 8 4 0 0 4 6 3 17
Bombus griseocollis (De Geer 1773) G 0 0 1 0 0 0 1 0 0 1
Bombus rufocinctus Cresson, 1863 G 5 1 5 4 0 1 5 1 0 11
Bombus sandersoni Franklin 1913 G 1 0 2 0 0 1 1 0 1 3
Bombus ternarius Say 1837 G 2 2 3 1 0 1 4 1 0 7
Bombus vagans Smith 1854 G 7 8 11 4 0 0 15 4 3 26
Ceratina mikmaqi Rehan & Sheffield
2011
S 0 0 1 1 0 0 0 0 0 1
Coelioxys porterae Cockerell 1900 S 0 0 1 0 0 0 0 0 1 1
Dianthidium pudicum (Cresson 1879) Surf. 0 1 0 1 0 0 0 0 0 1
Halictus confusus Smith 1853 G 0 4 2 3 3 0 0 0 0 6
Halictus rubicundus (Christ 1791) G 3 0 4 0 2 2 0 1 2 7
Heriades carinata Cresson 1864 S 1 1 0 0 0 0 0 2 0 2
Heriades variolosa (Cresson 1872) S 1 1 2 0 0 1 1 0 2 4
Hoplitis pilosifrons (Cresson 1864) S 5 4 2 4 1 5 0 1 0 11
Hoplitis producta (Cresson 1864) S 1 0 2 0 1 2 0 0 0 3
Hoplitis spoliata (Provancher 1888) S 1 1 5 0 4 3 0 0 0 7
Hylaeus affinis (Smith 1853) S 0 0 2 1 1 0 0 0 0 2
Hylaeus annulatus (Linnaeus 1758) S 0 0 1 0 0 0 1 0 0 1
Lasioglossum admirandum
(Sandhouse 1924) G 19 13 17 17 1 11 13 0 7 49
Lasioglossum albipenne
(Robertson 1890) G 0 0 1 0 0 0 1 0 0 1
Lasioglossum cinctipes
(Provancher 1888) G 0 0 1 0 0 0 0 1 0 1
Lasioglossum leucocomus
(Lovell 1908) G 0 1 0 0 0 0 1 0 0 1
Lasioglossum leucozonium
(Schrank 1781) G 2 1 7 1 0 0 3 2 4 10
Lasioglossum nigroviride
(Graenicher 1910) S 0 1 0 1 0 0 0 0 0 1
Lasioglossum novascotiae
(Mitchell 1960) G 1 0 0 0 0 0 0 0 1 1
Lasioglossum paraforbesii
McGinley 1986 G 1 0 0 0 0 1 0 0 0 1
Lasioglossum pilosum (Smith 1853) G 0 0 1 1 0 0 0 0 0 1
Lasioglossum planatum
(Lovell 1905) G 4 18 5 12 3 7 2 1 2 27
Lasioglossum sagax (Sandhouse 1924) G 1 0 1 0 1 1 0 0 0 2
Lasioglossum semicaeruleum
(Cockerell 1895) G 2 1 0 2 0 1 0 0 0 3
Lasioglossum viridatum
Lovell 1905 G 58 90 104 124 4 30 60 5 29 252
Lasioglossum zonulum
(Smith 1848) G 5 10 16 11 1 8 6 3 2 31
Megachile gemula Cresson 1878 S 0 0 1 0 0 0 0 1 0 1
Megachile inermis Provancher 1888 S 1 0 0 0 0 0 1 0 0 1
Megachile latimanus Say 1823 G 1 0 0 1 0 0 0 0 0 1
Megachile relativa Cresson 1878 S 0 1 0 0 0 0 1 0 0 1
Melissodes agilis Cresson 1878 G 2 2 5 4 0 0 4 0 1 9
Melissodes druriellus (Kirby 1802) G 0 0 2 0 0 0 2 0 0 2
Melissodes illatus Lovell & Cockerell 1906
G 1 0 2 0 0 1 1 0 1 3
Melissodes rivalis Cresson 1872 G 0 0 1 0 0 0 1 0 0 1
Melissodes trinodis Robertson 1901 G 3 2 5 3 0 0 4 3 0 10
Osmia atriventris Cresson 1864 S 1 0 0 1 0 0 0 0 0 1
Osmia proxima Cresson 1864 S 0 0 1 1 0 0 0 0 0 1
Osmia simillima Smith 1853 S 1 0 1 2 0 0 0 0 0 2
Osmia tersula Cockerell 1912 S 1 0 0 0 0 1 0 0 0 1
Stelis labiata (Provancher 1888) S 1 1 0 0 0 1 0 1 0 2
Total: 51 Species Total
156 177 239 228 25 82 144 34 59 572 Avg. Total per site
31.2
0 29.5
0 34.1
4 374 150 264 110 33 59
Number of Species
32 25 38 602 175 346 254 67 118
80
Avg. Number spp. per site
6.40 4.17 5.43
Table 2.7 List of species caught in bee bowls in 2018 along with their nesting guild (G = ground,
S = stem (above ground), U = unknown) and distribution of numbers caught between the three
disturbance types: B = burned, G = grazed, U = undisturbed. The other columns represent the
types of bee bowls they were caught in, with B.G. = blue ground bowl, Y.G. = yellow ground,
W.G. = white ground, B.E. = blue elevated, Y.E. = yellow elevated, and W.E. = white elevated.
Species Author Nest B G U B.G. Y.G. W.G.
B.E. Y.E. W.E. Total
Agapostemon texanus
Cresson 1872 G 2 0 3 1 0 2 1 0 1 5
Andrena algida Smith 1853 G 1 0 1 0 1 0 1 0 0 2
Andrena commoda Smith 1879 G 1 0 0 1 0 0 0 0 0 1
Andrena cressonii Robertson 1891 G 6 1 1 1 3 4 0 0 0 8
Andrena persimulata Viereck 1917 G 0 1 0 0 1 0 0 0 0 1
Anthophora bomboides
Kirby 1838 G 1 0 1 0 0 0 1 1 0 2
Anthophora
terminalis
Cresson 1869 S 7 7 10 14 3 4 3 0 0 24
Augochlorella aurata (Smith 1853) G 13 5 6 6 7 10 0 1 0 24
Bombus bimaculatus Cresson 1863 G 1 0 1 0 0 0 1 0 1 2
Bombus borealis Kirby 1837 G 4 1 0 3 0 0 1 0 1 5
Bombus fervidus (Fabricius 1798) G 1 3 2 1 0 0 2 0 3 6
Bombus rufocinctus Cresson, 1863 G 2 2 0 1 1 2 0 0 0 4
Bombus sandersoni Franklin 1913 G 1 0 0 0 0 0 0 0 1 1
Bombus ternarius Say 1837 G 1 3 1 1 0 0 3 0 1 5
Bombus vagans Smith 1854 G 7 3 7 4 0 0 7 2 4 17
Ceratina calcarata Robertson 1900 S 0 0 1 0 0 1 0 0 0 1
Ceratina dupla Say 1837 S 1 2 4 1 2 4 0 0 0 7
Ceratina mikmaqi Rehan & Sheffield 2011
S 6 3 8 9 0 8 0 0 0 17
Colletes kincaidii Cockerell 1898 G 0 0 1 0 0 0 1 0 0 1
Dufourea marginata (Cresson 1878) G 0 0 1 0 0 0 1 0 0 1
Halictus confusus Smith 1853 G 4 6 5 3 6 6 0 0 0 15
Halictus ligatus Say 1837 G 1 0 0 0 1 0 0 0 0 1
Halictus rubicundus (Christ 1791) G 9 7 9 8 3 12 1 0 1 25
Heriades carinata Cresson 1864 S 1 0 1 0 0 0 0 1 1 2
Hoplitis pilosifrons (Cresson 1864) S 34 12 15 29 14 17 1 0 0 61
Hoplitis producta (Cresson 1864) S 1 0 2 1 0 2 0 0 0 3
Hoplitis spoliata (Provancher 1888) S 2 1 3 1 2 3 0 0 0 6
Hylaeus affinis (Smith 1853) S 1 1 1 2 1 0 0 0 0 3
Hylaeus annulatus (Linnaeus 1758) S 1 0 0 0 0 0 0 1 0 1
Hylaeus mesillae (Cockerell 1907) S 1 2 1 1 2 1 0 0 0 4
Lasioglossum admirandum
(Sandhouse 1924) G 89 17 23 58 6 29 21 4 11 129
Lasioglossum coriaceum
(Smith 1853) G 2 1 0 2 0 1 0 0 0 3
Lasioglossum inconditum
(Cockerell 1916) G 1 0 1 1 1 0 0 0 0 2
Lasioglossum laevissimum
(Smith 1853) G 0 1 0 0 1 0 0 0 0 1
Lasioglossum leucocomus
(Lovell 1908) G 1 0 1 1 0 0 1 0 0 2
Lasioglossum leucozonium
(Schrank 1781) G 7 5 13 6 9 1 5 0 4 25
Lasioglossum michiganense
(Mitchell 1960) G 1 0 0 0 0 1 0 0 0 1
Lasioglossum pectorale
(Smith 1853) G 1 0 0 0 0 1 0 0 0 1
Lasioglossum perpunctatum
(Ellis 1913) G 2 0 2 0 3 1 0 0 0 4
Lasioglossum planatum
(Lovell 1905) G 4 15 4 11 5 7 0 0 0 23
Lasioglossum sagax (Sandhouse 1924) G 4 11 9 14 2 1 6 1 0 24
Lasioglossum subviridatum
(Cockerell 1938) S 2 0 0 1 0 0 1 0 0 2
Lasioglossum viridatum
Lovell 1905 G 65 96 81 106 16 78 19 11 12 242
Lasioglossum zonulum
(Smith 1848) G 25 31 59 35 19 33 12 6 10 115
Megachile inermis Provancher 1888 S 2 0 3 4 0 0 1 0 0 5
Megachile latimanus Say 1823 G 0 0 1 0 0 0 1 0 0 1
Megachile melanophaea
Smith 1853 G 1 0 0 0 0 0 1 0 0 1
Megachile pugnata Say 1837 S 0 0 1 0 0 0 0 1 0 1
Megachile relativa Cresson 1878 S 0 1 2 0 0 1 0 0 2 3
81
Melissodes agilis Cresson 1878 G 3 6 4 1 0 1 9 1 1 13
Melissodes druriellus (Kirby 1802) G 0 0 1 0 0 0 0 0 1 1
Melissodes trinodis Robertson 1901 G 4 0 3 0 0 2 1 1 3 7
Osmia atriventris Cresson 1864 S 6 15 16 15 11 10 0 1 0 37
Osmia bucephala Cresson 1864 S 5 3 5 4 5 2 2 0 0 13
Osmia lignaria Say 1837 S 0 0 1 0 1 0 0 0 0 1
Osmia proxima Cresson 1864 S 2 5 7 3 5 4 2 0 0 14
Osmia simillima Smith 1853 S 4 5 12 11 5 4 1 0 0 21
Osmia subarcticus Cockerell 1912 U 0 0 3 1 1 1 0 0 0 3
Osmia tersula Cockerell 1912 S 19 7 12 11 13 10 3 0 1 38
Sphecodes pecosensis Cockerell 1904 G 1 0 0 1 0 0 0 0 0 1
Stelis labiata (Provancher 1888) S 0 1 0 0 0 0 0 1 0 1
Total: 61 Species Total
361 280 349 374 150 264 110 33 59 990 Avg. Total per site
72.2
0 46.6
7 49.8
6
Number of Species 49 33 46
Avg. Number of Species per site
9.80 5.50 6.57
82
Table 2.8 List of species caught in blue vane traps in 2018 along with their nesting guild (G =
ground, S = stem (above ground) and distribution of numbers caught between the three
disturbance types: B = burned, G = grazed, U = undisturbed.
Species Author Nest B G U Total
Agapostemon texanus Cresson 1872 G 0 0 1 1
Agapostemon virescens (Fabricius 1775) G 0 1 1 2
Anthophora terminalis Cresson 1869 S 10 22 17 49 Anthophora walshii Cresson 1869 G 1 0 0 1
Augochlorella aurata (Smith 1853) G 0 1 0 1
Bombus bimaculatus Cresson 1863 G 0 0 2 2
Bombus borealis Kirby 1837 G 49 53 70 172 Bombus fervidus (Fabricius 1798) G 22 15 28 65
Bombus griseocollis (De Geer 1773) G 0 0 1 1
Bombus nevadensis Cresson 1874 G 1 2 0 3
Bombus rufocinctus Cresson, 1863 G 6 6 14 26 Bombus ternarius Say 1837 G 7 8 9 24
Bombus terricola Kirby 1837 G 0 2 0 2
Bombus vagans Smith 1854 G 11 6 9 26
Ceratina mikmaqi Rehan & Sheffield 2011 S 0 1 1 2 Colletes kincaidii Cockerell 1898 G 0 0 1 1
Dianthidium pudicum (Cresson 1879) Surf. 0 1 0 1
Halictus parallelus Say 1837 G 0 0 1 1
Halictus rubicundus (Christ 1791) G 6 6 4 16 Heriades variolosa (Cresson 1872) S 1 0 0 1
Hoplitis pilosifrons (Cresson 1864) S 5 2 4 11
Hoplitis spoliata (Provancher 1888) S 0 0 1 1
Hylaeus annulatus (Linnaeus 1758) S 1 3 12 16 Hylaeus mesillae (Cockerell 1907) S 10 1 3 14
Lasioglossum admirandum (Sandhouse 1924) G 1 0 0 1
Lasioglossum laevissimum (Smith 1853) G 0 3 1 4
Lasioglossum leucocomus (Lovell 1908) G 0 2 0 2 Lasioglossum leucozonium (Schrank 1781) G 0 1 1 2
Lasioglossum planatum (Lovell 1905) G 5 1 1 7
Lasioglossum truncatum (Robertson 1901) G 1 0 0 1
Lasioglossum viridatum Lovell 1905 G 20 31 51 102 Lasioglossum zonulum (Smith 1848) G 15 42 167 224
Macropis nuda (Provancher 1882) G 0 0 1 1
Megachile inermis Provancher 1888 S 0 2 2 4
Megachile latimanus Say 1823 G 0 1 0 1 Megachile montivaga Cresson 1878 S 1 0 0 1
Megachile relativa Cresson 1878 S 2 1 1 4
Melissodes agilis Cresson 1878 G 227 331 356 914
Melissodes desponsus Smith 1854 G 1 1 0 2 Melissodes druriellus (Kirby 1802) G 1 1 2 4
Melissodes illatus Lovell & Cockerell 1906 G 2 1 2 5
Melissodes trinodis Robertson 1901 G 82 106 125 313
Osmia atriventris Cresson 1864 S 2 0 0 2 Osmia simillima Smith 1853 S 1 1 4 6
Triepeolus helianthi (Robertson 1897) G 0 0 1 1
Total = 45 species Total 491 655 894 2040
Avg. Total per site 98.2 109.1667 127.71429
Number of Species 27 31 32
Avg. Number of Species per site 5.4 5.166667 4.5714286
83
Table 2.9 List of study sites with corresponding disturbance type and coordinates.
Site Disturbance Type Latitude (° N) Longitude (° W) Stefanchuk 2 Undisturbed 49.134385 -96.740645
Smook SW Undisturbed 49.1677425 -96.74031
Smook NW Undisturbed 49.17568 -96.740368
Townsend Undisturbed 49.163795 -96.67451
Forrester & Casson Undisturbed 49.1185725 -96.66499
Dykun Undisturbed 49.1049425 -96.649898
Clough Undisturbed 49.1576575 -96.649858
Stefanchuk Grazed 49.1553 -96.739845
Nickel Grazed 49.1629125 -96.716645
Fisher Grazed 49.149765 -96.695408
Fisher 2 Grazed 49.1416775 -96.695463
Penner Grazed 49.1205975 -96.654183
Storoschuk Grazed 49.13253 -96.650598
Singh NW Burned 49.148185 -96.74066
Saranchuk Burned 49.179495 -96.67225
Rose Burned 49.171915 -96.672625
Kai Kwong Lee Burned 49.17512 -96.650273
Bott Burned 49.16934 -96.65027
84
Chapter 3: Relationship between the two data chapters (Chapters 2 and 4)
The preceding chapter explored the effects of prairie disturbance and land use on wild
bees; an important group of beneficial insects in the tallgrass prairie. I found that burned and
grazed sites differed in bee community composition, and that grazed sites supported less
abundance, richness, and diversity of bees compared to burned and undisturbed sites. Ground-
nesting bees had less species richness in grazed sites compared to undisturbed sites. Stem-nesting
bees increased in abundance and species richness in burned sites compared to grazed sites. Wild
bee diversity responded positively with increasing amount of forest, ditch, and pasture in the
surrounding landscape. As well, increasing amount of bare ground, forbs, and blooming flower
numbers in the local groundcover positively affected the entire bee community, as well as the
ground-nesting bee community specifically. My results provide insight into how prairies and the
surrounding landscape can be best managed to benefit wild bees.
I performed a parallel study to examine potential trade-offs in management by examining
the effects of prairie disturbance and land use on haplogastran beetles. These beetles provide
different ecological services important to the prairie, especially decomposition and predation of
pest insects. Haplogastran beetles have different habitat requirements to bees and may not
respond in similar fashion to disturbance and land use.
The following chapter focuses on these decomposer and predatory beetles using a similar
experimental design to the preceding bee chapter. By examining the effects of disturbance,
landscape, and landcover on two groups (wild bees and haplogastran beetles) that are essential to
the tallgrass prairie, it is hoped that management policies that favour multiple groups of
beneficial insects can be implemented, while avoiding short sighted decisions that may benefit
one group at the expense of another.
85
Chapter 4: Fire and grazing present trade-offs for an ancestrally detritivorous group of
beetles (Coleoptera: Haplogastra) in tallgrass prairie
4.0 Abstract
Tallgrass prairie is an increasingly rare ecoregion that reaches its northernmost extent in
the province of Manitoba. There are efforts to restore and preserve this culturally and
economically significant habitat. Few insects are considered in prairie management. I examined
the effects of grazing and burning on two beneficial guilds of beetles at the Manitoba Tall Grass
Prairie Preserve (the largest remnant of tallgrass prairie in Canada). I sampled haplogastran
beetles using baited pitfall traps in sites that recently experienced burns, grazing, or no
disturbance. I found grazing supported overall greater abundance of total haplogastran beetles,
and specifically decomposer beetles. However, predatory beetles were more abundant in burned
sites. Species richness and Hill’s Shannon diversity were not affected by disturbance type.
Landscape diversity and composition were important for beetle abundance, richness, and
diversity. Rarefaction demonstrated that burned sites support more effective species than
undisturbed or grazed sites. Indicator species analysis highlighted several beetles that were
associated with one or more disturbance types. I discuss the effects of tallgrass prairie
disturbance type on often overlooked components of the beneficial prairie insect community.
4.1 Introduction
Tallgrass prairie (TGP) is the easternmost and most productive ecoregion within the
Great Plains and Canadian Prairies (Joyce and Morgan 1989). Tallgrass prairie once spanned
from Texas to southern Canada but was dramatically reduced during colonization and western
agricultural expansion (Samson and Knopf 1994). TGP was created and maintained through a
combination of large ungulate (i.e., bison) grazing, and natural and Indigenous-set fires (Pyne
1986). These processes prevented forest encroachment (Pyne 1986). The prairie’s rich, black soil
made for ideal conditions to grow crops. Largescale conversion to monoculture crops supplanted
the natural diversity of the prairie and transformed 99% of it into simplified habitats (Samson
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and Knopf 1994, Koper et al. 2010). Southern Manitoba represents the northernmost extent of
TGP (Figure 4.1), though less than 0.1% of the former breadth of the prairie remains intact in the
province (Samson and Knopf 1994), with that number continuing to decrease (Koper et al.
2010). Rare, charismatic species occur in the Manitoba TGP, such as the eastern tiger
salamander, Ambystoma tigrinum Green, and the small white lady slipper, Cypripedium
candidum Muhl. ex Willd. Public outreach and ecotourism have led to increased funds for the
preservation of TGP through land purchases and targeted management (Costanza et al. 1997,
Veech 2006, Gerla et al. 2012, Berger et al. 2020).
Figure 4.1 Map showing the distribution of the northern tall grasslands ecoregion in North
America. Distribution is based on ecoregions as defined by the World Wildlife Fund and Olsen
et al. (2001).
TGP is often managed by mimicking historical disturbances of the Prairies, through
prescribed fires, cattle grazing, mowing, and haying (Sveinson 2003). These techniques are
chiefly applied to alter vegetation communities (Sveinson 2003). Burning the prairie reduces leaf
litter, which raises soil temperature by increasing solar absorption (Ehrenreich and Aikman
1963). Higher soil temperatures lead to an earlier growing season and greater flower production
(Ehrenreich and Aikman 1963). Faunal elements are rarely considered when planning
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management, however periodic fires also benefit higher trophic levels in prairies (Grant et al.
2010).
Both management and landscape context can influence the positive effects that TGP can
have on the greater environment. The ecological functions provided by TGP include carbon
sequestration (Baer et al. 2002, McLauchlan et al. 2006, Adler et al. 2009, An et al. 2013), soil
erosion prevention, and water pollutant filtration (Tomer et al. 2019, Nelson et al. 2020) .
Arthropod communities also provide ecological functions in the TGP, including decomposition
and predation (Whiles and Charlton 2006). Unfortunately, arthropods are rarely considered when
planning TGP management, but see Westwood et al. (2020).
Beetle community composition is affected by environmental variables at both local and
landscape scales in North American grasslands. However, the scale of influence varies due to the
heterogenous makeup of TGP (Bossenbroek et al. 2004). Predatory beetles in restored grasslands
have greater species richness as grass cover increases at the local scale, and as semi-natural
habitats surrounding the grassland increases at the landscape scale (Crist and Peters 2014).
Predators may be more susceptible to regional (patch shape) landscape change than lower trophic
levels in the TGP (Stoner and Joern 2004). Detritivorous dung beetle species richness responds
negatively to greater landscape variety (Reynolds et al. 2018).
Haplogastra is a proposed clade that includes the proposed clades Staphyliniformia and
Scarabaeiformia (Kolbe 1908, McKenna et al. 2015) (but see Beutel and Leschen 2005).
Staphyliniformia includes the rove beetles (Staphylinidae), carrion beetles (Silphidae), round
fungus beetles (Leiodidae), feather-winged beetles (Ptiliidae), clown or hister beetles
(Histeridae), and water scavenger beetles (Hydrophilidae), among many other smaller f amiles.
The Scarabaeiformia includes scarabs (Scarabaeidae), stag beetles (Lucanidae), bess beetles
(Passalidae), and hide beetles (Trogidae), as well as several other smaller families. The
Haplogastra are thought to have evolved as detritus feeders, which is a habit and lifestyle
retained in most of its lineages (McKenna et al. 2015).
Haplogastran beetles are ideal bioindicators owing to their immense diversity (rove
beetles and scarabaeoids account for 110,000+ described species (Marshall 2018)), ease of
sampling, close associations with prey/feeding substrate, short lifespan, and low economic
importance, thus not causing concern from mass removal (Leivas and Carneiro 2012, Vieira et
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al. 2018). However, haplogastrans are ecologically important and may have indirect economic
benefits, for example scarabs who remove cattle gastrointestinal parasite larvae from around cow
pats (Sands and Wall 2017). Haplogastrans have recently become much more common in
biodiversity studies (Hansen et al. 2018, Vieira et al. 2018). Rove beetles are increasingly
replacing carabids for environmental impact studies due to their immense diversity and close
association with certain habitats (Bohac 1999, Klimaszewski et al. 2018a).
Rove beetles are functionally diverse, but the majority are predacious or saprophagous
(Bohac 1999). Rove beetles are readily sampled using pitfall traps, especially those that are quick
running and live above the soil surface (Irmler and Lipkow 2018). Carrion beetles are likely
derived from within the Staphylinidae (McKenna et al. 2015).
The water scavenger beetles are largely aquatic, however the subfamily Sphaeridinae is
mostly terrestrial and regularly occur in cow pats and other rotting material (Short and Fikacek
2013). Hister beetles are predators that occur in dung, carrion, and rotting cacti, while others live
as inquilines in mammal nests or ant colonies, or under bark (Bousquet and Laplante 2006).
Scarabs are divided into several subfamilies, with some being largely herbivorous, while two are
dung feeders (Scarabaeinae and Aphodiinae). Scarabaeinae tend to be “rollers”, or “tunnelers”,
either rolling pieces of dung away to a separate location, or tunneling under the dung to
provision their larvae (Helgesen and Post 1967, Halffter and Edmonds 1982). The Aphodiinae
are “dwellers” that complete their entire life cycle within dung or rich humus source (Helgesen
and Post 1967, Halffter and Edmonds 1982).
My goal was to determine the effects of prairie disturbance type and landscape factors on
predacious and saprophagous (decomposer) beetles. I used baited pitfall traps to capture beetles
in TGP sites that differed in their history of disturbance. My three main objectives were to: i)
determine the effects of fire and grazing disturbance on predator and decomposer haplogastran
beetle communities, ii) examine how landscape scale and local scale features relate to diversity
of these haplogastran beetles and iii), determine how disturbance, landscape level, and local scale
factors differentially affect decomposers and predators. I predict that grazed sites will have
higher haplogastran diversity and abundance compared to burned sites due to increased quality
and abundance of detritus (e.g., remnants of cow dung). Grazed grasslands have faster
decomposition rates than burned ones (Hofstede 1995), which I speculate is related to abundance
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and diversity of decomposer beetles. I predict that TGP with lower landscape diversity will have
a greater diversity of decomposer beetle captures. I predict that increasing grass cover will
benefit abundance and diversity of predacious beetles (Crist and Peters 2014). With an increasing
shift towards understanding whole communities and ecosystem processes, the underlying aim in
conducting this study is to catalogue an often overlooked but immensely diverse component of
the prairie fauna, as well as attempt to uncover patterns that may protect them and the valuable
prairie services they provide.
4.2 Methods
4.2.1 Site selection
I chose 18 sites in the Manitoba Tall Grass Prairie Preserve, the largest remnant tallgrass
prairie in Canada (headquartered at 49.1548, -96.7299). Sites were chosen based on landcover
data and management history provided by Nature Conservancy Canada (NCC) and its partners.
The preserve is surrounded by agricultural land and is divided into a North and South block.
Sites were chosen in the North block, as management strategies were more discreet (grazed or
burned, not both) and it allowed for multiple sites to be easily visited quickly. The North block is
a relatively wet, boggy prairie, with the water table being near the surface until about the end of
June. My sites fell into three distinct categories: i) grazed sites (n=6) have had cattle on them at
least once since 2007, but were not burned in at least 24 years, the ranges of recent grazes were
one site that was grazed in 2006 and 2007, one site that was grazed annually from 2008-2011,
two sites were grazed in both 2011 and 2012, and two sites were grazed annually from 2012-
2016. One site was also grazed during my 2018 field season, however my study area had an
enclosure around it to prevent disturbance; ii) burned sites (n=5) experienced a burn at least once
since 2012 but have not been grazed in at least 24 years, with ranges of four sites being burned in
an unplanned wildfire in 2012, and one site experiencing a controlled burn in 2016; and iii)
undisturbed sites (n=7) that have not been grazed or burned in at least 24 years.
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Figure 4.2 Map of the distribution of the study sites relative to the town of Stuartburn. Burned
sites are represented by red triangles, grazed sites by green circles, and undisturbed sites by blue
squares. The insert shows an example of the Latin square design of the baited pitfall traps, with
gingerbread men representing ginger baited traps, cows representing cow dung traps, apples
representing EtOH + amyl acetate traps, and fish representing fish skin baited traps.
At each site, I deployed 16 pitfall traps in a 4 x 4 matrix with a minimum separation of 15
m. Pitfall traps are frequently used in biodiversity studies, and are effective at catching ground
dwelling beetles (The Biological Survey of Canada 1994). Four distinct baits were chosen to
attract haplogastran beetles to the pitfall traps: i) 30 mL of cow dung, ii) 30 mL of 99:1 mixture
of 95% ethanol: amyl acetate (Anderson and Nelson 1993), iii) 30 g of cut and peeled ginger
root, and iv) 30 g of walleye (Sander vitreus (Mitchill)) skin and scales. Four of each bait were
used at each site arranged in a Latin square design. This design ensures that each bait appeared
only once in each row and column of my sampling grid (Figure 4.2). Dung was obtained fresh
from dairy cows at Glenlea Research Station, south of Winnipeg. It was put into vials and frozen
until use. Amyl acetate attracts detritivores including some flies and haplogastran beetles
(Anderson and Nelson 1993, White 1998). Ginger was obtained in bulk from a local
supermarket. Ginger mimics the smell of wood volatiles and has been shown to successfully
attract stag beetles (Harvey et al. 2011). Walleye skin and scales were provided by Freshwater
Fish, a federal government agency located in Winnipeg, Manitoba.
The baits were placed in 50 mL centrifuge tubes and placed within a 1 L plastic cup filled
with 2–3 cm of 1:1 propylene glycol: water mixture. This cup was then placed in a second cup in
the ground such that both cups together were flush with the ground. A metal grid with 2.54 2 cm
N 49.18
N 49.10
W 96.74 W 96.65
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holes was then placed overtop to try and exclude vertebrates from accidentally falling into the
pitfall. A wooden rain cover was placed 2–3 cm above the trap to prevent the trap from
overflowing.
Samples were taken in a way that one of each group (grazed, burned, and undisturbed)
were sampled at the same time, except for one group that consisted of a grazed and two
undisturbed sites. In both years, each site was sampled three times. In the summer of 2017, the
traps were run for two days, with the baits taken out of the freezer in the morning, and placed in
the field before noon, and then the captures collected 48 hours later. In 2018, traps were run for
one week to increase the number of beetles captured. Baits were removed from the freezer the
night before deployment to ensure they were attractive as soon as they were put in the field. The
traps were run for longer in the second year to attract a more diverse and abundant beetle
assemblage, as the majority of rove beetles arrive at dung after the third day (Guimarães and
Mendes 1998), and at decomposing flesh after the fourth day (Cruise et al. 2018). Once the traps
were retrieved, beetles were frozen until they were washed with soapy water and then stored in
70% ethanol. Beetles were then dried and pinned or point mounted. Specimens which could not
be placed to species were sent to the Canadian Museum of Nature (2017 scarabs), the Canadian
National Collection of Insects, Arachnids, and Nematodes in Ottawa, Ontario (2017 captures,
2018 rove beetles) for expert identification, or to Carleton University in Ottawa, Ontario (2018
round fungus beetles). Specimens are deposited in the J.B. Wallis-R.E. Roughley Museum of
Entomology at the University of Manitoba. Duplicate vouchers are deposited at the Canadian
National Collection and at the Canadian Museum of Nature in Ottawa.
4.2.2 Landscape Mapping
Landcover data surrounding my sites was obtained via a usage agreement with Nature
Conservancy Canada and their partners. Areas adjacent to the preserve were hand digitized based
on satellite imagery. I extracted radii of 250, 500, 1000, 1500, and 2000 m p laced around the
centre of each site in ArcMap v.6.2 (ESRI 2018). Polygon data were extracted to determine what
land use types dominated the varying ranges of buffers. Land cover was grouped into the
following categories: forest, peri-urban, structure, savannah, water, swamp, prairie, pasture, crop,
river, edge (ditch), other, and road. These categories were created based on what is readily
visible in satellite imagery and NCC categories, though the latter were largely combined into
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single categories, such as different prairie subcategories and different forest types. Patch Analyst
v. 5.2 (Rempel et al. 1999) was used to calculate Shannon diversity of the landscape and the
mean shape index for each buffer radius. Shannon diversity increases as different patch types are
added to the landscape and is maximized when all patch types are of equal proportion (Rempel et
al. 1999, McGaril & Marks 1994). The mean shape index starts at one, a situation in which all
patches are perfectly circular, and increases as the complexity of patch shapes increase (Rempel
et al. 1999). Individual landcover proportions were also extracted. These portions were then put
in to a principal coordinate analysis (PCA) using the ‘FactoMineR’ package (Husson et al.
2020). The first principal coordinate axis was used for subsequent models. In 2018, 1 x 1 m
quadrats were also used to measure percent cover of bare ground, grass, and forb/woody cover
and number of inflorescences (intended for a parallel study examining bees). Quadrats were
tossed overhead 16 times twice in 2018. The average of the 16 times was recorded, and the
average of both rounds was used per site. A PCA was then performed to extract the first axis
coordinate for each site (Figure 4.10).
4.2.3 Identification/Data analysis
Haplogastran beetles were identified using reference collections and several published
keys (Helgesen and Post 1967, Campbell 1968, Smetana 1971, Campbell 1979, Watrous 1980,
Campbell 1983, 1984, Anderson and Peck 1985, Smetana 1988, Campbell 1991, Baranowski
1993, Campbell 1993a, 1993b, Smetana 1995, Peck and Stephan 1996, Newton et al. 2001, Peck
and Cook 2002, Bousquet and Laplante 2006, Gordon and Skelley 2007, Peck and Cook 2009,
Brunke et al. 2011, Peck and Cook 2013). Beetles were analysed both together and separated by
feeding guild (predator and decomposer). Feeding guild was established via published studies
(Helgesen and Post 1967, Anderson and Peck 1985, Smetana 1988, Dennis et al. 1990, Good and
Giller 1991, Jo and Smitley 2003, Bousquet and Laplante 2006, Majka and Klimaszewski 2008,
Thayer 2016). Omnivores were included in both guilds, and species with unknown feeding
habits/non decomposer or predator beetles were excluded from both. All statistical analyses were
performed in R (R Core Team 2017). Beetle community composition was examined using
distance based redundancy analysis (Legendre and Anderson 1999) using the ‘capscale’ function
of the ‘vegan’ package (Oksanen et al. 2018). For the redundancy analysis, the 2017 and 2018
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data were analysed separately. I used permutational multivariate analysis of variance
(perMANOVA) to test for effects of disturbance type on beetle communities using the ‘adonis’
function in the ‘vegan’ package (Oksanen et al. 2018). I used the Bray-Curtis dissimilarity for
community composition analyses.
Mixed-effects models with site as a random effect were used to test for differences in
abundance and diversity between disturbance types. I used the first two Hill numbers—species
richness and the Hill’s Shannon index—as measures of diversity (Jost 2007). Hill numbers
include species richness (q=0), Hill’s Shannon effective species number (q=1), and the Inverse
Simpson’s effective species number (q=2). These differ in the amount of weight placed on
species abundance, with species richness being independent of abundance, the Hill’s Shannon
being weighted toward rare species, and the Inverse Simpson’s being weighted to more abundant
species (Chao et al. 2014). The ‘q’ numbers are derived from Hill (1973), who used the notation
devised by Rényi (1961).
I used a model selection approach using Akaike Information Criterion with a small
sample size correction (AICc). Models were built gradually, first by including average
temperature, average precipitation, day of year, and year. Then, the model was dredged using the
‘dredge’ command of the ‘MuMIn’ package to determine which variables to keep going forward
(Sakamoto et al. 1986, Barton 2018). Based on early model selection, I determined that the
beetles responded most to the 500 m buffer size, which is also supported by other investigations
on predatory and decomposer beetles in grassland ecosystems (Liu et al. 2014), so this scale was
used in subsequent models. Landscape metrics, disturbance, and groundcover variables were
added to the base model. I then compared my global model to simpler models and selected the
best model using the AICc. Preferred models were assessed using the ‘check_model’ f unction of
‘performance’ package (Ludecke et al. 2020) to determine how well the models fit assumptions
and their distributions, and whether collinearity between fixed effects was present. Abundance
models were initially built with a negative binomial distribution, species richness models with a
quasi-Poisson, and Hill’s Shannon models with a Gamma distribution. However, models were
re-built under an alternate distribution (such as the Gaussian) if the package ranked it as better
performing using the ‘compare_performance’ command. In cases where the Gaussian
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distribution was used, a Shapiro-Wilk test was performed on the residuals to test for the
assumption of normality (Royston 1982a, 1982b, 1995).
Indicator species analysis was performed to test if certain species were strongly tied to a
certain disturbance type and site(s) (De Cáceres and Legendre 2009, De Cáceres et al. 2010, De
Cáceres and Jansen 2016). Two methods were used, both from the ‘indicspecies’ package (De
Cáceres and Jansen 2016); the ‘Indval.g’ method, which stands for the group equalized indicator
value and does not consider absences from sites as being evidence against a species being an
indicator, and the ‘r.g.’ method, which stands for the group equalized point biserial correlation
and considers abundances outside of the group which a species may be an indicator for as weight
towards whether or not to classify a species as an indicator (De Cáceres et al. 2010). The ‘.g’
suffix allows for assumed variability within disturbance types to be proportional to the group size
(De Cáceres et al. 2010). Indicator species analysis was performed by ‘Disturbance Type’, the
focus of my study, as well as by ‘Site’, which used the six samples as replicates. I felt this would
be useful information for land managers in case rare/endangered/new species are among the
indicators, which could lead to more careful or more targeted management of certain sites.
Species diversity is sensitive to sample size. Rarefaction allows for fair comparison
between samples with different abundances and different sampling efforts. I generated rarefied
diversity values using Hill numbers for each site type by collapsing each individual sample into
its disturbance type. I used the package ‘iNEXT’ (Hsieh et al. 2019) to generate graphs showing
the interpolated and extrapolated rarefied diversity (represented by q=0 (species richness), q=1
(Hill’s Shannon effective species number), and q=2 (inverse Simpson’s effective species
number) of the three disturbance types.
4.3 Results
I caught a total of 19,448 haplogastran beetles over my two years of study, including
10,483 in the rove beetle subfamily Aleocharinae, which were not identified further. The
remaining 8,965 specimens represented 124 species from 70 genera. There were 1,351 predatory
beetles caught representing 69 species. There were 7,628 decomposer beetles from 55 species.
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Of these two guilds, eight were omnivorous species, accounting for 64 specimens. Besides the
aleocharines, there were eight species totaling 50 specimens that could not be placed into my
predator or detritivore categories. There were 3,634 (1,931 non aleocharine) beetles caught on
burned sites, 9,293 (3,659 non aleocharine) caught on grazed sites, and 6,521 (3,375 non
aleocharine) caught on undisturbed sites. In 2017, when traps were left out for only 48 hours,
853 (483 non aleocharine) beetles were caught. In 2018, when traps were left out for 7 days,
18,595 (8,482 non aleocharine) beetles were caught. Cow dung baits caught 1,825 beetles (474
non aleocharine), EtOH + Amyl Acetate baits caught 2,025 (928 non aleocharine) beetles, ginger
root caught 2,372 (440 non aleocharine) beetles, and fish skin caught 13,226 (7,123 non
aleocharine) beetles. Nineteen species represent new provincial records for Manitoba, including
one likely undescribed species of Stenus.
4.3.1 Community Composition - Distance-based Redundancy Analysis/perMANOVA
The total haplogastran beetle communities (including the aleocharine captures) differ
between the three categories of disturbance, but communities of predatory and decomposing
beetles did not differ. Disturbance constraints on the dbRDA explained 25% of the variation in
2017, and 24% of the variation in 2018 (Table 4.1, Table 4.2).
Table 4.1 Summary of amount of variation explained by constrained (Disturbance type) factors
in dbRDA for the total beetle communities in both years.
Inertia Proportion
2017 - Total 3.5602 1.000
2017 – Constrained 0.8993 0.2526
2017 - Unconstrained 2.6609 0.7474
2018 - Total 1.876 1.000
2018 - Constrained 0.454 0.242
2018 - Unconstrained 1.422 0.758
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Table 4.2 Summary of the effect of ‘Disturbance Type’ on beetle dissimilarities in distance -
based redundancy analyses using the ‘anova’ function with ‘by= “terms”’ specified. Results were
obtained by running 999 permutations.
Community Year F model p value
All haplogastran
beetles 2017 2.5348 0.006
Predator beetles 2017 0.8057 0.759
Decomposer beetles 2017 1.4695 0.111
All haplogastran
beetles 2018 2.3928 0.012
Predator beetles 2018 1.3342 0.091
Decomposer beetles 2018 1.2154 0.264
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Figure 4.3 Distance-based redundancy ordination of all 2017 haplogastran beetles (left) (F = 2.5348, p = 0.006), predatory beetles
(centre) (F = 0.8057, p = 0.759), and decomposer beetles (right) (F = 1.4695, p = 0.111), constrained by disturbance type using the
Bray-Curtis method. The three sampling rounds were combined in to one value per site to avoid pseudo-replication. The red triangles
represent ‘burned’ sites, green circles represent ‘grazed’ sites, and blue circles represent ‘undisturbed’ sites. Ellipses re present 95%
confidence intervals around the disturbance types.
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PerMANOVA allowed for numerical post-hoc comparison among disturbance groups
(Table 4.3). Grazed site beetle communities were significantly different from burned sites in both
years (Table 4.3, Figure 4.3, Figure 4.4), but only differed from undisturbed sites in 2017, though
this was confounded by the fact that they had unequal dispersion, though as Figure 4.3 shows,
the differences are likely real. In 2017, grazed and undisturbed sites had significantly different
dispersions, but they also show little overlap in the ordination. The predatory and decomposer
communities did not differ among disturbance categories.
Table 4.3 Summary of perMANOVAs performed on the Bray-Curtis dissimilarity of different
beetle communities in 2017 & 2018. The Post-hoc column represents the results of a Tukey’s
post-hoc test with a Bonferroni correction. B = ‘Burned’, G = ‘Grazed’, U = ‘Undisturbed’. *
refers to an instance where disturbance types were determined to have unequal dispersion
parameters, thus this result should be interpreted with caution.
Community Year F model R2 p value Post-hoc
All haplogastran beetles 2017 2.5375 0.2528 0.007
B-U: 1
B-G: 0.018
G-U: 0.042*
Predator beetles 2017 0.6983 0.08518 0.836 N/A
Decomposer beetles 2017 1.4906 0.16579 0.096
B-U: 1
B-G: 0.264
G-U: 0.288
All haplogastran beetles 2018 2.4721 0.2479 0.018
B-U: 1
B-G: 0.012
G-U: 0.066
Predator beetles 2018 1.3514 0.15267 0.1
B-U: 0.564
B-G: 0.039
G-U: 1
Decomposer beetles 2018 1.2082 0.13874 0.278 N/A
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Figure 4.4 Distance-based redundancy ordination of all 2018 haplogastran beetles (left) (F = 2.3938, p = 0.012), predatory beetles
(centre) (F = 1.3342, p = 0.091), and decomposer beetles (right) (F = 1.2154, p = 0.264), constrained by disturbance type using the ‘Bray-Curtis’ method. The three sampling rounds were combined in to one value per site to avoid pseudo -replication. The red triangles represent ‘burned’ sites, green circles represent ‘grazed’ sites, and blue circles represent ‘undisturbed’ sites. E llipses represent 95% confidence intervals around the disturbance types.
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4.3.2 Models
4.3.2.1 Disturbance effects
When all haplogastran beetles are treated together, disturbance type has a significant
effect on abundance (Figure 4.5). Grazed sites host a significantly greater abundance of beetles
than either burned or undisturbed sites. Disturbance type was not a significant variable in the best
model for species richness, however it was for the Hill’s Shannon model, where I see the
opposite effect of disturbance than abundance, where burned sites host significantly more
effective species than grazed or undisturbed sites (Figure 4.5).
When beetles were separated based on feeding guild, only abundance was affected by
disturbance type. Burned sites had greater abundance of predatory beetles than grazed and
undisturbed sites (Figure 4.6). Conversely, grazed sites support the greatest abundance of
decomposer beetles, having significantly more than undisturbed sites, but not significantly more
than burned sites (Figure 4.6). When looking at aleocharine abundance alone, grazed sites had
significantly more aleocharines than burned or undisturbed sites (Figure 4.7).
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Figure 4.5 Effect plot of the predicted effect of disturbance on haplogastran beetle abundance (left), and on the effect of Hill’s
Shannon effective species number (right) when all other variables part of the best fitting GLMMs are held at their average or default.
Different letters above the disturbance types represent significantly differences based on GLMMs (p<0.05). Points represent the
median value of the predictor variable of the disturbance type subset, and whiskers represent 95% confidence intervals.
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Figure 4.6 Effect plot of the predicted effect of disturbance type on predatory haplogastran beetle (left), and decomposer beetle (right)
abundance when all other variables part of the best fitting GLMMs are held at their average or default. Different letters abo ve the
disturbance types represent significantly differences based on GLMMs (p<0.05). Points represent the median value of the predictor
variable of the disturbance type subset, and whiskers represent 95% confidence intervals.
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Figure 4.7 Effect plot of the predicted effect of disturbance type on aleocharine beetle
abundance when all other variables part of the best fitting GLMM is kept at their average or
default value. Different letters above the disturbance types represent significantly differences
based on a GLMM (p<0.05). Points represent the median value of the predictor variable of the
disturbance type subset, and whiskers represent 95% confidence intervals.
4.3.2.2 Landscape effects
The PCA for the landcover types at 500 m was part of the best model for combined beetle
abundance, where it had a positive effect. The first axis of the PCA was related to forest, ditch,
and pasture cover on beetle abundance, with a negative effect of increasing prairie and swamp
cover (Figure 4.9). This positive effect was also observed in the species richness, and Hill’s
Shannon models.
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No landscape factors were recovered in the best models for predatory beetles or
aleocharine beetles. The preferred model for decomposer abundance included positive effects of
the landcover PCA and the landscape mean shape index. The latter implies that increased patch
shape complexity and greater amount of edge in the landscape has a positive effect on
decomposer beetle abundance. Landcover PCA was also included in the best model for
decomposer beetle species richness, again demonstrating a positive effect along the first axis. No
landscape factors were part of the best model for decomposer beetle Hill’s Shannon effective
species number.
4.3.2.3 Ground cover effects
The ground cover PCA (Figure 4.10) was part of the best model for combined beetle
species richness, where it had a negative effect, implying that lesser amounts of forbs, and
greater amounts of grass cover were beneficial to beetle species richness.
The ground cover PCA was also part of all three predatory beetle models, again showing
a negative effect of forbs, and a positive effect of increased grass cover on abundance, richness,
and diversity. Ground cover was not part of any of the decomposer beetle models or the
aleocharine abundance model.
4.3.3 Rarefaction Curves
Burned sites had greater rarefied effective species than grazed and undisturbed sites using
Hill numbers q=1 and q=2. This pattern was present in the combined beetle (with aleocharines
excluded) and the decomposer beetle data, but not present for predatory beetles (Figure 4.8).
Undisturbed sites also demonstrated significantly greater effective species numbers compared to
grazed sites in the same pattern. Undisturbed sites support greater species richness than grazed
sites for predatory beetles.
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Q=0
Q=0
Q=1
Q=1
Q=2
Q=2
S
pec
ies
Div
ersi
ty
S
pec
ies
Div
ersi
ty
106
Figure 4.8 Rarefied diversity curves of haplogastran beetle captures (except the subfamily Aleocharinae), with the top row
representing all beetles combined, the middle row representing predatory beetles, and the bottom row representing decomposer
beetles. The columns represent the q numbers, where left represents q = 0 = species richness, centre represents q = 1 = Hill’s Shannon
effective species number, and right represents q = 2 = Inverse Simpson’s effective species number.
S
pec
ies
Div
ersi
ty
Q=0 Q=1 Q=2
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4.3.4 Indicator Species Analysis
The two methods used for the indicator species analysis returned some of the same
beetles as indicators for certain disturbance types but differed for others. Burned sites have four
indicator species, two of which are decomposers, and two of which are predatory. Bledius
strenuus Casey feeds on algae (Thayer 2016), which were potentially more abundant on the
surface in burned sites due to greater light availability and less trampling on their burrows.
Grazed sites have four indicator species, two decomposers and two predators. Two of the
indicator species of burned and grazed sites are shared between the two, implying that they may
be indicators of disturbance in general. Undisturbed sites did not have any indicator species
(Table 4.4).
Table 4.4 Results of Indicator Species Analysis on beetle species by disturbance type. Guild
refers to feeding guild that beetle belongs to, with P = predator and D = decomposer. Analyses
were run for 999 permutations. Only indicators with more than 10 specimens caught are here
reported.
Species Guild # Disturbance Type Method Statistic p-value
Bledius strenuus
Casey D 19 Burned
Indval.g,
r.g.
Indval.g =
0.441
r.g. = 0.334
Indval.g =
0.001
r.g. = 0.004
Anotylus niger
(LeConte) P 72 Grazed Indval.g 0.477 0.047
Heterosilpha
ramosa
(Say)
D 261 Burned +
Grazed Indval.g 0.588 0.036
Neobisnius
jucundus
(Horn)
P 74 Burned +
Grazed
Indval.g,
r.g.
Indval.g =
0.517
r.g. = 0.301
Indval.g =
0.002
r.g. = 0.003
Philonthus
schwarzi
Horn
P 128 Burned r.g. 0.262 0.022
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Nicrophorus
hebes Kirby D 1,044 Grazed r.g. 0.297 0.008
Indicator species was also run by site instead of disturbance type and the results are
included in the supplementary material (Tables 4.9, 4.10).
4.4 Discussion
The intensity and frequency of fire may play a role in determining the effect on arthropod
communities. A study in Manitoba TGP found that optimal fire season for promoting diversity
and evenness differed between spiders and the floral community (Wade 2002). Burn season had
no effect on ground beetle communities (Roughley et al. 2010). While the literature is scant for
beetle fauna, studies on open habitat butterflies provide evidence that single, infrequent, high
intensity wildfires are more beneficial than maintenance prescribed fires for butterfly
conservation (reviewed in Swengel 2001).
Though studies suggest that burn management history has negligible effects on
decomposition rates in TGP (Reed et al. 2009), drought conditions, like those experienced in
2018, do start to produce decomposition differences between burn/cessation regimens (Reed et
al. 2009). Whether abundance or diversity of decomposer haplogastran beetles influence this
process is unclear, however studies in agricultural settings suggest that low organic nutrient
availability at the surface in summer conditions lead to decreased numbers of rove beetles
(Brunke et al. 2014).
Other studies have noted detrimental effects on a coprophagous haplogastran beetle and
dung removal rate via presence of predatory haplogastran beetles (Wu et al. 2011), which could
potentially explain my large differences in decomposer and predator beetle abundances in my
different disturbance types. This same experiment saw negative effects of predators on plant
biomass, implying that sites with large amounts of predators could negatively impact the floral
component of grasslands (Wu et al. 2011).
The results of the dbRDA and perMANOVA imply that the type of disturbance can
greatly influence the total beetle community composition. This has important implications for
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managing the prairie going forward. Ideally, it would be useful to compare these communities to
sites that are managed with a combination of burning and grazing to see if the combined
approach is intermediate between the two disturbance types, or if it creates a distinct assemblage
of its own.
Low intensity grazing, which increases soil compaction, has previously been reported to
increase rove beetle abundance (Hofmann and Mason 2006). However, rove beetle diversity
decreased with increasing soil moisture levels (Hofmann and Mason 2006), and this experiment
had confounding factors that the authors warn reduces the ability to generalize their results. This
exemplifies the need to measure soil variables if a similar experiment were to be conducted again
given that compaction, nutrient availability, soil acidity, and organic matter availability are all
known to be affected by features and age of burning and grazing in TGP, which would likely
also affect all higher trophic levels (reviewed in Faber 2008, A. R. Westwood (pers. comm.)
2021). Large herbivores can have detrimental effects on dung feeding insects through the use of
antihelminth medications (Wall and Strong 1987, Madsen et al. 1990, van Klink et al. 2015),
which could presumably also affect the predatory insects that feed on them. Unfortunately,
medication regimens of nearby farms that utilize the preserve were not considered in the
planning of this project. As well, trampling, even minimally, on grasslands has previously been
shown to negatively impact arthropod communities to a much greater degree than grassland plant
communities (Duffey 1975, van Klink et al. 2015). Grazed sites showed highest decomposer
abundance, but lowest rarefied decomposer diversity. Grazed sites did not however have lower
rarefied diversity of predatory beetles, which could suggest that increased decomposer
abundance can lead to increased predator diversity on grazed sites, which has been hypothesized
before (van Klink et al. 2015).
There is evidence that smaller bodied beetles, which represent the bulk of the diversity in
my samples, but not so much the bulk of abundance in my study, fare poorer in grazed
grasslands compared to a lesser effect on larger bodied beetles (Dennis et al. 1998). Similar to
my findings in showing negative impacts of grazing, cattle grazing on grasslands in Europe has
been shown to negatively impact insect diversity compared to long undisturbed sites (Kruess and
Tscharntke 2002). However, they also found reduced insect abundance at intensively grazed
sites, which conflicts with my findings, though they were not sampling in the same manor and
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for the same functional groups that I was (Kruess and Tscharntke 2002). A study on coastal salt
marshes in the UK found significantly higher rove beetle abundance in several months on a site
with low intensity cattle grazing and an elevated water level (Hofmann and Mason 2006). They
also found evidence that suggests that rove beetle species turnover happens quickly following a
site shift from grazing to non-grazing (Hofmann and Mason 2006). Since most of my sites had
been a year or more since active grazing, this implies that my results may be interpreting the
outcome of a cessation of grazing rather than the direct effect of grazing, especially since no
dung feeding scarabs were recovered as indicators of grazed sites. Like my study, Doxon et al.
(2011), in a prairie system that historically was shaped by burning and grazing, found that
beetles were more abundant in traditional, graze only sites than those exposed additionally to
fire. Carrion-associated rove beetle species composition is known to be affected by
intensification of management, with generalist species replacing rare/specialist species under
increasing management intensity (Weithmann et al. 2020). This could explain my findings of
community composition differences between grazed and burned sites if cattle grazing has a more
intense effect on the rove beetle fauna in the TGP.
Herbaceous dicot forbs are the main source of plant species richness in TGP (Whiles and
Charlton 2006). Woody encroachment has known negative effects on the diversity of these forbs
(Taft and Kron 2014). Beetle family richness has been shown to be positively correlated to native
prairie plant abundance (Jonas et al. 2002). Increased plant diversity in grasslands increases
arthropod diversity (Siemann et al. 1998). As well, herbivorous arthropod diversity was also
codependent on predacious invertebrate diversity (Siemann et al. 1998), implying that
management that promotes greater plant diversity can have cascading effects on the diversity of
several invertebrate feeding guilds. Though increased litter layer, which would be associated
with my undisturbed sites (not measured, pers. obs.), has been shown to increase predatory
arthropod abundance (Langellotto and Denno 2004, van Klink et al. 2015), I did not see this
pattern in my results.
Studies on ground beetles, a predominantly predatory beetle guild, in TGP have shown
negligible effects of frequent burning on community assemblage (Cook and Holt 2006). The
authors note however, that as ground beetles are comparatively unspecialized predators, their
conclusions cannot be extrapolated to other predatory guilds (Cook and Holt 2006). A study in a
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grassland ecosystem found that livestock stocking rate negatively affected aggregation of a
predatory rove beetle, thought to possibly be due to less plant litter on grazed sites (Dennis et al.
2002). Some studies have found increased predatory beetle abundance on open sites during the
recovery phase post-fire (reviewed in Swengel 2001). As well, reduced litter levels following a
fire are known to reduce decomposer abundance (Seastedt 1984, Seastedt et al. 1986, Kral et al.
2017), while simultaneously increasing predatory beetle abundance (Tester and Marshall 1961).
This is consistent with my findings of increased predator fauna on my burned sites since all but
one experienced fire several years prior, as well as my increased decomposer numbers on my
grazed sites.
The trampling associated with grazing can have direct lethal effects on large dung beetles
(Negro et al. 2011, van Klink et al. 2015), and though herbivores supply the main food source to
many decomposers in the form of dung, studies suggest that high stocking rates can have
negative effects on dung beetle diversity and abundance in temperate grasslands (Negro et al.
2011, van Klink et al. 2015). Some have suggested that larger insects respond more positively to
the grass cover heterogeneity that grazing produces than smaller insects (Klink et al. 2013). This
could potentially help explain my findings of greater abundance of decomposers, many of which
were large species such as Nicrophorus spp. and Necrophila spp., on my grazed sites compared
to the other disturbance types. It could also explain the decreased richness on my grazed sites if
the smaller species, which made up the bulk of the species richness, respond more negatively to
grazing. It is has been suggested that decomposer beetles may be less abundant on burned sites
due to a lack of vegetation cover, leading to quick desiccation times of the carrion and dung that
they would typically feed on (Beucke 2009). Whether this theory is driving my findings is not
clear.
Aleocharines were assumed by me to be much more abundant on my grazed sites due to
large numbers of Aleochara spp., which are parasitoids on dung and carrion feeding Diptera
(Klimaszewski 1984), though I did not identify the genus of any of my aleocharine captures, and
it could instead be that grazed sites supported more abundance of aleocharines that depend on
organic matter that may be in greater supply on sites free from burns. This could include a
hidden source of diversity that would augment the species richness of grazed sites, as
demonstrated by recent studies in Manitoba recovering 120 species of aleocharine beetles present
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in the province (Klimaszewski et al. 2018b), however the number of grassland associated species
is much less than this, and without ID confirmations, I do not wish to speculate.
The greater amount of indicator species for the burned and grazed disturbance compared
to no indicators for undisturbed sites may hint that these beetle communities evolved in tandem
with the TGP to respond to frequent disturbance, however the species recovered have broader
distributions in Canada (Bousquet et al. 2013), so perhaps they are adapted to disturbance in
broader ecoregions. At the site level, several undisturbed sites were important for rare species,
implying that refugia should be maintained when possible.
There are conflicting results as to how decomposer beetles respond to landscape
diversity, with some studies finding a negative effect of increased diversity on richness
(Reynolds et al. 2018), while others find beneficial effects of increased landscape diversity on
beetle diversity (Rös et al. 2012). My study did not corroborate the findings of Liu et al. (2014)
who found a positive effect of landscape diversity on decomposer beetle abundance. My results
suggest that landscape diversity in TGP does not affect decomposer beetle abundance.
A previous study in Manitoba TGP found that predatory arthropods were more abundant
in the forest ecosystem adjacent to TGP (Roughley et al. 2006), which could explain the positive
effect of forest cover on my captures, though the pattern was not seen in my exclusively
predatory model. Increased pasture area has been implicated as increasing rare dung beetle
species richness in grazed ecosystems (Buse et al. 2015), which could be contributing to an
increase in species in areas with more pastural area in the environment. Though dung beetles
(Scarabaeidae: Scarabaeinae, Aphodiinae) made up only a minor part of my decomposer fauna,
they are known to exhibit intermediate characteristics of forest and pasture communities when
both landscapes are present in the surrounding environment (Somay et al. 2021). The presence of
both these habitats surrounding the prairie could lead to increased diversity, which could in turn
promote the many positive functions performed by the dung beetle community. However, a
study in Europe, where many dung beetles are native and tied to longstanding animal agricultural
practice, found that dung beetle richness severely declined in reclaimed forest sites compared to
preserved agricultural grasslands (Errouissi and Jay-Robert 2019). Another study examining the
differential response of dung beetle communities to different habitat types showed that dung
beetle abundance was maximized in mature, late succession forest, but richness and diversity
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were maximized in pastureland (Tocco et al. 2013). This could explain why the landcover
variable has a positive effect in both my abundance and diversity models, where both pasture and
forest sit in the positive aspect of the first axis of the PCA, however it must be stressed that dung
beetles made up a fairly small portion of my decomposer captures. Studies on rove beetles have
revealed positive effects of forest and forest edge in the landscape on abundance and richness
compared to grassland environments (Tóthmérész et al. 2014). This could explain my positive
effect of the amount of forest in the environment, and the negative effect of the amount of prairie
in the environment according to my landcover PCA, however the increased diversity may not
strictly be the goal of conserving the TGP if aiming to specifically conserve grassland associated
species. Contrary to this, however, is the finding that increased encroaching forest cover in
prairie grasslands lead to significant decreases in silphid abundance (Walker Jr and Hoback
2007).
My findings of decomposers responding positively to patch shape complexity contrasts
with another study that found that dung beetle richness decreased with increasing shape
complexity (Rocha-Ortega and Coronel-Arellano 2019), though my study areas are quite distinct,
and the taxonomic scope of my study is much broader, with dung beetles forming only a small
component. My results contrast to a previous study which found a negative effect of increasing
patch shape (more edge) on generic diversity of ground-dwelling arthropods, as well as
decreased richness of beetles compared to low edge patches (Orrock et al. 2011). Some studies
have found that decomposer beetles respond to landscape composition (Verdú et al. 2011,
Sánchez-de-Jesús et al. 2016, Rocha-Ortega and Coronel-Arellano 2019), sometimes pointing
out that they respond at landscape scales more than local cover scales (Rocha-Ortega and
Coronel-Arellano 2019), which is consistent with my findings, but other times pointing out that
both landcover and local patch attributes affect composition (Sánchez-de-Jesús et al. 2016).
Predator beetles, however, are known to respond to local ground cover, including positive effects
of increased grass cover on predatory beetle richness in grassland ecosystems (Crist and Peters
2014), which my results support.
Soil and vegetation characteristics have been implicated as being the most informative
variables explaining rove beetle community structure (Hofmann and Mason 2006), and diversity
(Weithmann et al. 2020). Soil characteristics are also known to influence the amount of
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ecological functions performed by dung beetle communities (Griffiths et al. 2015, Nunes et al.
2018), and the abundance of silphid communities (Jakubec and Růžička 2015, von Hoermann et
al. 2018). This makes it clear that these factors should be measured in a follow up study.
Increasing plant species richness is known to increase insect richness in TGP (Zavaleta et al.
2010), thus it would also be useful to measure overall plant diversity in follow up studies, even if
it seems that it would likely have little effect on predator and decomposer communities.
Unfortunately, the sheer abundance and morphological homogeneity of the aleocharines
(Staphylinidae: Aleocharinae) prevented us from identifying them beyond subfamily. They have
however been stored in case specialists wish to identify them for a re-examination of the effects
of disturbance type and landscape on TGP beetles down the road. There are notable limitations to
understanding my results in a large context, as most previous work on decomposers has focused
on dung beetles, often in very disparate landscapes. While scarabs were part of my captures, they
were far from the most abundant group. There have also been some studies on silphids, however
not many in the prairies, with the exception of investigations into the rare and endangered
American burying beetle, Nicrophorus americanus (Olivier).
Some studies suggest that it is the relative proportions of few efficient players that drive
decomposition as opposed to overall diversity (Tonelli et al. 2020). However other studies have
shown a clear effect of species richness, as opposed to increased abundance, on measured
decomposition (Farwig et al. 2014, Nunes et al. 2018). Some studies have suggested a middle
ground of measuring beetle functional diversity as opposed to relying on taxonomic diversity
(Griffiths et al. 2015). A general consensus, based on a broad meta-analysis, points to negative
implications of biodiversity and individual species loss, brought on by climate change, on the
process of decomposition (Hooper et al. 2012). Therefore, it is imperative that studies in the TGP
incorporate an ecosystem function aspect to future experiments to determine how species and
functional diversity loss impact decomposition rates in the prairie.
While it was a rare catch overall, no specimens of Staphylinus ornaticauda, a large
flightless, potentially vulnerable rove beetle, were found on burned sites, but were found on
multiple grazed and undisturbed sites. As well, a probably undescribed species of water skater,
Stenus sp. was found during this study, and was found on several sites, none of which were
burned. Burning the prairie likely removed the moss and litter layer necessary for water skater
115
development and for their prey. This may be a good example of the need to retain refugia in the
TGP, both from planned burns, and from wildfires when possible.
Though I did not detect spatial autocorrelation in any of my models, my sites were quite
clumped together out of time and travel necessity, as well as the limited size and disturbance
regimes of the preserve. Since I found a large number of new records for such a small area in the
province, it highlights the need to conduct further studies in other TGP remnants throughout the
province. To prevent destruction from animal or weather activity, I covered my pitfalls with a
rain cover. This probably had the undesired consequence of limiting the ability of the scent from
the baits to spread very far. As well, fish skin was responsible for most of the captures. Different
bait sources should be explored in subsequent studies to attract greater diversity of decomposers
and predators. It would also be interesting to compare bait efficiency of bison vs. cattle dung, as
native species may be more likely to respond positively to bison dung than that of cattle. Though
I performed a pilot test of measuring dung decomposition and comparing it to beetle diversity
(unpublished data), I ultimately decided to not report on it, as I determined that the size of the
dung pats I used were too small, and quickly desiccated before the decomposer fauna could
effectively start to displace it. If I or others were to try again, I would recommend large pats of
dung with regular measuring of water content. Dung beetles, and presumably other dung feeding
beetles, reduce greenhouse gas emissions, albeit very modestly in pastureland (Slade et al. 2016).
It is predicted that their contributions are increased when cattle, and by extension beetles, spend
more time out in a frost-free pasture, which could be predicted under increasing temperatures
expected with climate change. Detrital pathways are known to have significant effects on many
communities differing by ecological role in most food webs, not just directly on the decomposers
themselves (reviewed in Moore et al. 2004). Thus, it is imperative that abundance and diversity
of many trophic levels are related back to decomposition rates in the TGP to ensure proper
maintenance of its floral and faunal communities.
4.5 Conclusion
It is hoped that my study sparks an increase into the often-overlooked decomposer and
predatory insect communities in TGP and other grasslands. My study shows that though burning
and grazing have similar goals in shaping the prairie plant community, they have opposing
116
effects on beetle fauna. This can lead to deficits in the ecological functions performed by the
beetle community, including dung/carrion removal, pest fly suppression, moderation of
invertebrate herbivore populations, and nutrient cycling. Future studies should attempt to directly
measure the beneficial services of the decomposer beetle community. Since the TGP owes its
existence to both megafauna grazing and high intensity fires, it would be ideal for future studies
to examine the combined effect of both disturbance patterns on the prairie beetle fauna.
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4.7 Chapter 4 Supplementary Materials
Figure 4.9 Graph of the first two axes of a principal coordinate analysis performed on percent
cover on the various landscapes found at 500 m from the centre of study sites.
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Figure 4.10 Graph showing the first two axes of a PCA performed on groundcover data obtained
by averaging two rounds of quadrat sampling performed in 2018. 16 quadrats were recorded
from each study site and then averaged by site. This was done twice, once in June, and once in
August. The site averages of the two rounds were once again averaged to obtain the results put in
to the PCA.
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Haplogastran Beetles Model Tables
Table 4.5 Results of GLMMs performed on haplogastran beetle pitfall trap capture abundance,
species richness, and Hill’s Shannon Effective Species Number. Site was used as a random effect in all models. The models represent the submodel with the lowest AICc score.
Response
Variable Fixed Effects Est. Std. Error z value p value
Abundance
Intercept 7.551 0.602 12.55 <0.001
Year (2017) -3.08 0.111 -27.83 <0.001
Day-of-year -0.01 0.003 -2.92 0.004
Avg. Precip. -0.10 0.041 -2.53 0.012
Landcover PCA @ 500 m 0.123 0.038 3.23 0.001
Treatment: Grazed 0.483 0.158 3.06 0.002
Treatment: Undisturbed -0.20 0.164 -1.24 0.215
Species
Richness
Intercept 4.635 0.286 16.19 <0.001
Year (2017) -1.33 0.067 -19.78 <0.001
Day-of-year -0.01 0.001 -5.04 <0.001
Avg. Precip. -0.05 0.021 -2.26 0.024
Landcover PCA @ 500 m 0.037 0.016 2.30 0.021
Groundcover PCA -0.03 0.017 -1.69 0.091
Hill’s
Shannon
Effective
Species
Number
Intercept 1.932 0.085 22.66 <0.001
Year (2017) -0.27 0.062 -4.37 <0.001
Landcover PCA @ 500 m 0.044 0.026 1.70 0.090
Treatment: Grazed -0.36 0.107 -3.38 0.001
Treatment: Undisturbed -0.21 0.108 -1.96 0.050
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Model Distribution Dispersion Parameter
Random Effect S.D.
AIC Log
Likelihood R2C
Abundance Negative
Binomial 4.21 (+/- 0.70) 0.097 1079.7 -530.843 0.463
Sp. Rich. Poisson N/A 0.043 544.4 -265.2 0.874
Hill’s
Shannon
Gamma
(Log Link) 9.99 (+/- 1.47) 0.096 417 -201.48 0.318
Table 4.6 Results of GLMMs performed on predatory haplogastran beetle pitfall trap capture abundance, species richness, and Hill’s Shannon Effective Species Number. Site was used as a
random effect in all models. The models represent the submodel with the lowest AICc score.
Response
Variable Fixed Effects Est. Std. Error z value p value
Abundance
Intercept 8.060 0.596 13.51 <0.001
Year (2017) -1.66 0.118 -14.06 <0.001
Day-of-year -0.02 0.003 -7.77 <0.001
Avg. Precip. -0.12 0.043 -2.86 0.004
Treatment: Grazed -0.38 0.149 -2.54 0.011
Treatment: Undisturbed -0.47 0.145 -3.26 0.001
Groundcover PCA -0.08 0.036 -2.30 0.021
Species
Richness
Intercept 23.942 2.163 11.07 <0.001
Year (2017) -5.56 0.417 -13.32 <0.001
Day-of-year -0.07 0.010 -7.00 <0.001
Avg. Precip. -0.50 0.159 -3.15 0.002
Groundcover PCA -0.40 0.177 -2.26 0.024
Hill’s
Shannon
Effective
Species
Number
Intercept 16.086 1.718 9.36 <0.001
Year (2017) -3.55 0.331 -10.74 <0.001
Day-of-year -0.05 0.008 -5.63 <0.001
Avg. Precip. -0.26 0.126 -2.09 0.037
131
Groundcover PCA -0.23 0.149 -1.56 0.118
Model Distribution Dispersion
Parameter/Residual Variance
Random Effect S.D.
AIC Log
Likelihood R2C
Abundance Negative Binomial
6.88 (+/- 2.02) 0.117 631.9 -306.948 0.208
Sp. Rich. Gaussian 1.99 (+/- 0.15) 0.891 483.3 -234.667 0.744
Hill’s Shannon
Gaussian 1.58 (+/- 0.12) 0.787 435.4 -210.723 0.668
Table 4.7 Results of GLMMs performed on decomposer haplogastran beetle pitfall trap capture abundance, species richness, and Hill’s Shannon Effective Species Number. Site was used as a random effect in all models. The models represent the submodel with the lowest AICc score.
Response
Variable Fixed Effects Est. Std. Error z value p value
Abundance
Intercept 6.220 0.725 8.58 <0.001
Year (2017) -3.41 0.138 -24.69 <0.001
Avg. Temp -0.09 0.036 -2.36 0.018
Avg. Precip. -0.13 0.053 -2.44 0.015
Landcover PCA @ 500 m 0.307 0.048 6.37 <0.001
Landscape MSI @ 500 m 0.124 0.077 1.62 0.106
Treatment: Grazed 0.369 0.197 1.88 0.061
Treatment: Undisturbed -0.33 0.189 -1.72 0.085
Species
Richness
Intercept 22.029 1.964 11.22 <0.001
Year (2017) -10.85 0.383 -28.35 <0.001
Day-of-year -0.04 0.009 -4.32 <0.001
Avg. Precip. 0.268 0.144 -1.87 0.062
Landcover PCA @ 500 m 0.463 0.106 4.38 <0.001
Hill’s
Shannon
Effective
Intercept 6.63 2.936 2.26 0.024
Year (2017) -4.75 0.303 -15.67 <0.001
132
Species
Number
Day-of-year -0.01 0.009 -1.68 0.094
Avg. Temp. 0.183 0.088 2.08 0.037
Model Distribution Dispersion
Parameter/Residual Variance
Random Effect S.D.
AIC Log
Likelihood R2C
Abundance Negative
Binomial 2.85 (+/- 0.49) <0.001 890.9 -435.452 0.574
Sp. Rich. Gaussian 1.83 (+/- 0.14) 0.168 452.3 -219.144 0.903
Hill’s
Shannon Gaussian 1.54 (+/- 0.10) <0.001 412.1 -200.053 0.731
Table 4.8 Results of a GLMM performed on aleocharine beetle abundance. Site was used as a
random effect. The model represents the submodel with the lowest AICc score.
Response Variable
Fixed Effects
Estimate Std. Error z value p value
Abundance
Intercept 6.881 0.826 8.33 <0.001
Day of Year -0.01 0.004 -2.78 0.005
Year: 2017 -3.27 0.153 -21.41 <0.001
Treatment: Grazed
1.172 0.258 4.55 <0.001
Treatment: Undisturbed
0.175 0.252 0.70 0.486
Model Distribution Dispersion
Parameter/Residual
Variance
Random Effect
S.D.
AIC Log
Likelihood R2C
Abundance Negative Binomial
2.34 (+/- 0.44) 0.304 962.9 -474.431 0.632
Because of the amount of data required to run the ‘Indval.g’ command and allow species to be
indicators of multiple sites, the ‘duleg=T’ function was added to allow a species to only be an
indicator for one site. The ‘r.g.’ method, however, allowed for species to be indicators of
multiple combinations of sites.
133
Table 4.9 Results of Indicator Species Analysis on beetle species by site using the Indval.g method. Guild refers to feeding guild that beetle belongs to, with P = predator, O = omnivore, and D = decomposer. Analysis was run for 999 permutations. Only species caught 10 or more
times are included.
Species Guild # Caught Site Method Statistic p-value
Tachyporus canadensis
O 22 Clough Indval.g 0.477 0.039
Nitidotachinus tachyporoides
O 19 Forrester &
Casson Indval.g 0.530 0.004
Staphylinus ornaticauda
P 13 Forrester &
Casson Indval.g 0.519 0.009
Nicrophorus hebes D 1,044 Nickel Indval.g 0.412 0.049
Neobisnius jucundus P 74 Saranchuk Indval.g 0.458 0.042
Apocellus sp. P 98 Singh NW Indval.g 0.707 0.001
Heterosilpha ramosa
D 261 Singh NW Indval.g 0.621 0.006
Philonthus cognatus P 26 Smook SW Indval.g 0.453 0.039
Catops alsiosus D 1,451 Stefanchuk
2 Indval.g 0.456 0.034
Anotylus niger P 72 Storoschuk Indval.g 0.509 0.021
Table 4.10 Results of Indicator Species Analysis on beetle species by site using the r.g. method.
Guild refers to feeding guild that beetle belongs to, with P = predator, O = omnivore, and D = decomposer. Analysis was run for 999 permutations. Only species caught 10 or more times are included.
Species Guild # Caught Site(s) Method Statistic p-value
Nitidotachinus tachyporoides
O 19 Kai Kwong
Lee + Forrester & Casson
r.g. 0.465 0.033
Staphylinus
ornaticauda P 13
Forrester & Casson +
Stefanchuk r.g. 0.462 0.05
Stenus new sp. P 10 Smook NW + Stefanchuk +
Townsend r.g. 0.538 0.008
Apocellus sp. P 98
Dykun + Fisher +
Saranchuk + Sing
h NW + Storoschuk
r.g. 0.542 0.001
Neobisnius jucundus P 74 Fisher + Penner + Rose + Saranchuk
+ Singh NW r.g. 0.636 0.001
Anotylus niger P 72
Bott + Dykun +
Fisher + Fisher 2
+ Penner + Storoschuk + Townsend
r.g. 0.472 0.02
Heterosilpha D 261 Bott + Dykun + r.g. 0.446 0.033
134
ramosa Fisher + Fisher 2
+
Penner + Rose + Singh NW + Smo
ok NW + Smook
SW + Storoschuk
Table 4.11 List of species caught in pitfall traps in 2017 along with their feeding guild (P =
predator, D = decomposer, O = omnivore, N/A = unknown) and distribution of numbers caught
between the three disturbance types: B = burned, G = grazed, U = undisturbed. The other
columns represent the types of baits they were caught in, with C.D. = cow dung, A.A. = EtOH +
amyl acetate, F.S. = fish skin, and G.R. = ginger root.
Species Author Family Role B G U C.D. A.A. F.S. G.R. Total
Aleocharinae spp. Fleming 1821 Staph. N/A 52 227 91 89 83 135 63 370
Anacaena limbata (Fabricius 1792) Hydro. D 0 1 1 0 0 0 2 2
Anotylus niger (LeConte 1877) Staph. P 1 5 0 2 2 2 0 6
Aphodius fimetarius (Linnaeus 1758) Scarab. D 0 0 1 1 0 0 0 1
Apocellus sphaericollis (Say 1831) Staph. P 14 4 3 7 2 8 4 21
Baeocera sp. Erichson 1845 Staph. D 1 0 0 0 0 0 1 1
Bledius strenuus Casey 1889 Staph. D 2 0 0 1 1 0 0 2
Bryoporus rufescens LeConte 1863 Staph. N/A 0 0 2 1 0 1 0 2
Catops alsiosus (Horn 1885) Leiod. D 3 44 12 5 10 44 0 59
Colon tibiale Hatch 1957 Leiod. D 0 3 1 1 0 3 0 4
Creophilus maxillosus (Linnaeus 1758) Staph. P 1 0 0 0 0 1 0 1
Cymbiodyta minima Notman 1919 Hydro. D 0 0 2 0 1 0 1 2
Diapterna hyperborea (LeConte 1850) Scarab. D 3 1 2 2 0 3 1 6
Diapterna pinguella (Brown 1929) Scarab. D 4 13 28 1 38 3 3 45
Dinothenarus badipes (LeConte 1863) Staph. P 2 1 1 1 1 2 0 4
Erichsonius pusio (Horn 1884) Staph. P 0 1 0 0 0 1 0 1
Euspilotus assimilis (Paykull 1811) Hister. P 0 1 0 0 0 1 0 1
Gabrius nigritulus (Gravenhorst 1802) Staph. P 0 1 0 0 0 1 0 1
Gabrius picipennis (Mäklin 1852) Staph. P 1 2 1 1 0 1 2 4
Helophorus angusticollis
Orchymont 1945 Hydro. D 2 1 0 0 2 1 0 3
Heterosilpha ramosa (Say 1823) Silph. D 3 2 1 3 0 2 1 6
Hister paykullii Kirby 1837 Hister. P 1 0 1 0 2 0 0 2
Hydnobius substriatus LeConte 1863 Leiod. D 1 0 1 0 0 1 1 2
Ischnosoma undescribed species
Stephens 1829 Staph. N/A 0 0 1 0 0 0 1 1
Ischnosoma pictum (Horn 1877) Staph. N/A 2 1 4 1 2 4 0 7
Lathrobium sparsellum
Casey 1905 Staph. P 0 0 1 0 0 1 0 1
Leiodes assimilis (LeConte 1850) Leiod. D 6 3 7 2 2 10 2 16
Mycetoporus lucidulus LeConte 1863 Staph. N/A 0 0 2 0 0 0 2 2
Necrophila americana (Linnaeus 1758) Silph. D 1 23 6 3 4 23 0 30
Neobisnius jucundus (Horn 1884) Staph. P 0 3 0 0 2 0 1 3
Nicrophorus hebes Kirby 1837 Silph. D 14 43 19 9 36 30 1 76
Nicrophorus orbicollis Say 1825 Silph. D 0 3 1 0 0 3 1 4
Nicrophorus tomentosus
Weber 1801 Silph. D 1 1 0 0 0 2 0 2
Nitidotachinus tachyporoides
(Horn 1877) Staph. O 2 0 2 0 1 1 2 4
135
Oiceoptoma noveboracense
(Forster 1771) Silph. D 0 9 0 0 4 5 0 9
Olophrum rotundicolle Erichson 1839 Staph. P 1 0 0 0 1 0 0 1
Ontholestes cingulatus (Gravenhorst 1802) Staph. P 3 0 1 1 1 0 2 4
Onthophagus hecate (Panzer 1794) Scarab. D 0 0 3 2 0 1 0 3
Onthophagus nuchicornis
(Linnaeus 1758) Scarab. D 1 0 0 0 1 0 0 1
Pachystilicus hanhami (Wickham 1898) Staph. P 0 0 1 1 0 0 0 1
Paederus littorarius Gravenhorst 1806 Staph. P 10 5 8 7 4 7 5 23
Philonthus blossius Smetana 1995 Staph. P 1 0 0 0 0 0 1 1
Philonthus carbonarius
(Gravenhorst 1802) Staph. P 0 1 0 0 1 0 0 1
Philonthus cognatus (Stephens 1832) Staph. P 5 3 3 1 6 2 2 11
Philonthus couleensis Hatch 1957 Staph. P 1 0 0 0 1 0 0 1
Philonthus cruentatus (Gmelin 1790) Staph. P 0 1 1 2 0 0 0 2
Philonthus lomatus
Species Group
Erichson 1840 Staph. P 0 0 1 0 0 0 1 1
Philonthus nigrita Species Group
(Gravenhorst 1806) Staph. P 17 14 18 12 9 20 8 49
Philonthus schwarzi Horn 1884 Staph. P 16 5 4 5 3 11 6 25
Philonthus varians (Paykull 1789) Staph. P 8 3 2 7 4 0 2 13
Staphylinus ornaticauda
LeConte 1863 Staph. P 0 1 1 2 0 0 0 2
Stenus melanarius Stephens 1833 Staph. P 0 0 1 0 0 1 0 1
Stenus undescribed species
Latreille 1796 Staph. P 0 1 2 1 1 1 0 3
Tetartopeus furvulus Casey 1905 Staph. P 0 0 1 0 0 1 0 1
Thanatophilus lapponicus
(Herbst 1793) Silph. D 0 1 1 2 0 0 0 2
Tympanophorus puncticollis
(Erichson 1840) Staph. P 1 1 4 0 1 3 2 6
Total = 56 species Total
181 429 243 173 226 336 118 853 Avg. Total per site
36.2 72 34.7
Number of Species
32 34 40
Avg. Number of Species per site
6.4 5.7 5.71
Table 4.12 List of species caught in pitfall traps in 2018 along with their feeding guild (P =
predator, D = decomposer, O = omnivore, H = herbivore, N/A = unknown) and distribution of
numbers caught between the three disturbance types: B = burned, G = grazed, U = undisturbed.
The other columns represent the types of baits they were caught in, with C.D. = cow dung, A.A.
= EtOH + amyl acetate, F.S. = fish skin, and G.R. = ginger root.
Species Author Family Role B G U C.D. A.A. F.S. G.R. Total
Aleocharinae spp. Fleming 1821 Staph. N/A 1651 5407 3055 1262 1014 5968 1869 10113
Acrotrichis sp. Motschulsky 1848 Ptil. D 0 0 1 0 1 0 0 1
Acylophorus pronus Erichson 1840 Staph. P 1 0 0 1 0 0 0 1
Anacaena limbata (Fabricius 1792) Hydro. D 2 6 11 3 7 7 2 19
Anotylus niger (LeConte 1877) Staph. P 8 49 9 16 22 18 10 66
Apocellus sphaericollis
(Say 1831) Staph. P 46 15 16 13 16 32 16 77
Arpedium brunnescens
J.R. Sahlberg 1871 Staph. P 0 0 1 0 0 0 1 1
Ataenius spretulus (Haldeman 1848) Scarab. D 0 0 1 1 0 0 0 1
Atholus falli (Bickhardt 1912) Hister. P 2 0 0 2 0 0 0 2
Bisnius instabilis (Horn 1884) Staph. P 0 1 0 0 0 1 0 1
136
Bledius strenuus Casey 1889 Staph. D 13 1 3 1 5 5 6 17
Bolitobius sp. 1 Leach 1819 Staph. N/A 0 0 1 0 0 0 1 1
Bolitobius sp. 2 Leach 1819 Staph. N/A 0 0 3 3 0 0 0 3
Bryoporus rufescens LeConte 1863 Staph. N/A 0 2 4 1 2 1 2 6
Carpelimus sp. 1 Leach 1819 Staph. D 0 1 0 0 0 1 0 1
Carpelimus sp. 2 Leach 1819 Staph. D 1 0 1 0 1 0 1 2
Catops alsiosus (Horn 1885) Leiod. D 237 520 635 9 1 1312 70 1392
Catops gratiosus (Blanchard 1915) Leiod. D 2 9 5 0 0 15 1 16
Cercyon roseni Knish 1922 Hydro. D 4 7 10 3 3 9 6 21
Colobopterus
erraticus
(Linnaeus 1758) Scarab. D 1 0 0 1 0 0 0 1
Colon near politum Peck and Stephan
1996
Leiod. D 2 9 2 2 10 0 1 13
Creophilus maxillosus (Linnaeus 1758) Staph. P 1 1 2 0 1 3 0 4
Cymbiodyta minima Notman 1919 Hydro. D 0 0 1 0 0 0 1 1
Cymbiodyta vindicata Fall 1924 Hydro. D 0 0 1 0 1 0 0 1
Cyrtusa subtestacea (Gyllenhal 1813) Leiod. D 0 1 1 2 0 0 0 2
Decarthron abnorme (LeConte 1849) Staph. P 0 1 1 1 0 1 0 2
Diapterna hyperborea (LeConte 1850) Scarab. D 11 5 19 11 6 11 7 35
Diapterna pinguella (W.J. Brown 1929) Scarab. D 44 145 170 24 290 33 12 359
Dinothenarus badipes (LeConte 1863) Staph. P 26 67 78 20 96 27 28 171
Erichsonius pusio (Horn 1884) Staph. P 2 1 0 1 0 2 0 3
Euconnus flavitarsis (LeConte 1852) Staph. P 1 0 2 0 1 1 1 3
Euspilotus assimilis (Paykull 1811) Hister. P 49 57 57 0 0 163 0 163
Gabrius picipennis (Mäklin 1852) Staph. P 18 12 16 13 8 12 13 46
Helophorus
angusticollis
Orchymont 1945 Hydro. D 3 6 4 5 3 2 3 13
Helophorus lacustris LeConte 1850 Hydro. D 1 0 0 0 0 1 0 1
Heterosilpha ramosa (Say 1823) Silph. D 171 68 16 65 52 118 20 255
Hister abbreviatus Fabricius 1775 Hister. P 3 1 2 0 0 6 0 6
Hister furtivus LeConte 1860 Hister. P 2 2 4 0 1 7 0 8
Hister paykullii Kirby 1837 Hister. P 1 3 3 0 1 5 1 7
Hydnobius substriatus
LeConte 1863 Leiod. D 0 0 1 0 1 0 0 1
Hydrochara obtusata (Say 1823) Hydro. D 0 1 0 0 1 0 0 1
Hydrochus granulatus Blatchley 1910 Hydro. D 1 0 0 0 1 0 0 1
Hydrochus neosquamifer
Smetana 1988 Hydro. D 0 1 7 0 0 7 1 8
Ischnosoma undescribed species
Stephens 1829 Staph. N/A 0 0 4 1 2 1 0 4
Ischnosoma pictum (Horn 1877) Staph. N/A 3 7 10 6 5 7 2 20
Lathrobium sparsellum
Casey 1905 Staph. P 0 1 1 0 1 0 1 2
Lathrobium sp. 1 Gravenhorst 1802 Staph. P 0 0 2 0 1 1 0 2
Lathrobium sp. 2 Gravenhorst 1802 Staph. P 1 0 1 0 0 1 1 2
Leiodes neglecta Baranowski 1993 Leiod. D 42 39 121 31 104 41 26 202
Margarinotus immunis
(Erichson 1834) Hister. P 0 1 0 1 0 0 0 1
Micropeplus sculptus LeConte 1863 Staph. D 0 4 0 0 1 1 2 4
Mycetoporus lucidulus
LeConte 1863 Staph. N/A 1 1 0 0 1 0 1 2
Necrophila americana (Linnaeus 1758) Silph. D 205 1142 933 2 3 2248 27 2280
Neobisnius jucundus (Horn 1884) Staph. P 53 16 2 16 23 15 17 71
Neohypnus obscurus (Erichson 1839) Staph. P 2 0 0 1 1 0 0 2
Nicrophorus defodiens
Mannerheim 1846 Silph. D 2 11 13 0 1 24 1 26
Nicrophorus hebes Kirby 1837 Silph. D 233 509 226 15 11 932 10 968
Nicrophorus hybridus Hatch & Angell 1925
Silph. D 4 0 1 0 0 5 0 5
137
Nicrophorus marginatus
Fabricius 1801 Silph. D 2 2 18 0 0 22 0 22
Nicrophorus obscurus Kirby 1837 Silph. D 0 3 2 0 0 5 0 5
Nicrophorus orbicollis Say 1825 Silph. D 127 178 177 1 0 478 3 482
Nicrophorus sayi Laporte 1840 Silph. D 0 1 3 0 0 4 0 4
Nicrophorus tomentosus
Weber 1801 Silph. D 30 60 97 0 0 186 1 187
Nitidotachinus tachyporoides
(Horn 1877) Staph. O 1 6 8 3 4 5 3 15
Oiceoptoma noveboracense
(Forster 1771) Silph. D 151 162 90 1 0 402 0 403
Omalium rivulare (Paykull 1789) Staph. D 1 0 0 0 0 1 0 1
Ontholestes cingulatus
(Gravenhorst 1802) Staph. P 0 6 2 0 3 5 0 8
Onthophagus hecate (Panzer 1794) Scarab. D 33 48 76 4 0 150 3 157
Onthophagus nuchicornis
(Linnaeus 1758) Scarab. D 11 7 22 1 1 37 1 40
Pachystilicus hanhami
(Wickham 1898) Staph. P 0 1 1 0 2 0 0 2
Paederus littorarius Gravenhorst 1806 Staph. P 35 31 45 30 30 34 17 111
Paracercyon
minisculus
(Melsheimer 1844) Hydro. D 0 0 1 0 0 1 0 1
Philonthus blossius Smetana 1995 Staph. P 9 8 4 2 6 10 3 21
Philonthus busiris Smetana 1995 Staph. P 3 9 2 2 1 10 1 14
Philonthis caeruleipennis
(Mannerheim 1830)
Staph. P 0 0 1 0 1 0 0 1
Philonthus carbonarius
(Gravenhorst 1802) Staph. P 1 0 0 0 0 1 0 1
Philonthus cognatus (Stephens 1832) Staph. P 5 3 7 2 9 0 4 15
Philonthus couleensis Hatch 1957 Staph. P 0 0 1 0 1 0 0 1
Philonthus cruentatus (Gmelin 1790) Staph. P 1 1 1 1 0 1 1 3
Philonthus lomatus Species Group
Erichson 1840 Staph. P 17 17 37 19 11 26 15 71
Philonthus
occidentalis
Horn 1884 Staph. P 0 2 0 0 0 2 0 2
Philonthus
opacipennis
Notman 1919 Staph. P 1 2 0 1 0 2 0 3
Philonthus palliatus (Gravenhorst 1806) Staph. P 0 1 1 0 0 2 0 2
Philonthus politus (Linnaeus 1758) Staph. P 2 1 1 0 0 4 0 4
Philonthus schwarzi Horn 1884 Staph. P 51 21 31 28 15 45 15 103
Philonthus sericinus Horn 1884 Staph. P 1 0 0 0 0 1 0 1
Philonthus validus Casey 1915 Staph. P 1 2 4 0 0 7 0 7
Philonthus varians (Paykull 1789) Staph. P 17 12 10 0 0 38 1 39
Phyllophaga sp. Harris 1827 Scarab. H 1 0 0 1 0 0 0 1
Pselaphus fustifer Casey 1894 Staph. P 0 0 1 0 0 0 1 1
Pycnoglypta
campbelli
Gusarov 1995 Staph. N/A 0 0 1 0 1 0 0 1
Rhyssemus sonatus LeConte 1881 Scarab. D 0 1 0 1 0 0 0 1
Rugilus biarmatus (LeConte 1880) Staph. P 1 0 1 1 0 1 0 2
Saprinus distinguendis
Marseul 1855 Hister. P 1 0 4 0 0 5 0 5
Saprinus oregonensis LeConte 1844 Hister. P 0 2 0 0 0 2 0 2
Sciodrepoides terminans
(LeConte 1850) Leiod. D 10 24 40 2 0 70 2 74
Sciodrepoides watsoni
(Spence 1815) Leiod. D 13 5 18 0 0 36 0 36
Sphaeridium scarabaeoides
(Linnaeus 1758) Hydro. P 1 0 0 0 0 0 1 1
Staphylinus ornaticauda
LeConte 1863 Staph. P 0 4 7 0 5 5 1 11
Stenus angustus Casey 1884 Staph. P 1 0 0 0 0 0 1 1
Stenus difficilis Casey 1884 Staph. P 1 0 0 1 0 0 0 1
138
Stenus melanarius Stephens 1833 Staph. P 0 2 3 2 0 2 1 5
Stenus morio Gravenhorst 1806 Staph. P 1 0 0 0 0 1 0 1
Stenus undescribed species
Latreille 1796 Staph. P 0 4 3 2 0 3 2 7
Stenus scabiosus Casey 1884 Staph. P 0 0 2 2 0 0 0 2
Stenus schwarzi Casey 1884 Staph. P 0 0 1 0 1 0 0 1
Stictolinus flavipes (LeConte 1863) Staph. P 0 0 2 0 0 2 0 2
Tachyporus atriceps Stephens 1832 Staph. O 0 0 1 0 0 0 1 1
Tachyporus borealis Campbell 1979 Staph. O 0 0 2 0 0 1 1 2
Tachyporus canadensis
Campbell 1979 Staph. O 6 0 16 4 5 3 10 22
Tachyporus nitidulus (Fabricius 1781) Staph. O 0 1 3 2 1 0 1 4
Tachyporus pulchrus Blatcheley 1910 Staph. O 0 0 1 0 0 1 0 1
Tachyporus
rulomoides
Campbell 1979 Staph. O 1 0 0 1 0 0 0 1
Tachyporus
transversalis
Gravenhorst 1806 Staph. O 2 8 4 4 3 5 2 14
Tertartopeus niger (LeConte 1863) Staph. P 0 0 1 0 0 0 1 1
Thanatophilus lapponicus
(Herbst 1793) Silph. D 63 98 67 0 0 228 0 228
Tympanophorus
puncticollis
(Erichson 1840) Staph. P 1 1 1 1 0 2 0 3
Total = 117 species Total
3453 8864 6278 1652 1799 12890 2254 18595
Avg. Total per site
690.6 1477 896.86
Number of Species
73 73 91
Avg. Number of Species per site
14.6 12.17 13
Table 4.13 List of study sites with corresponding disturbance type and coordinates.
Site Disturbance Type Latitude (° N) Longitude (° W) Stefanchuk 2 Undisturbed 49.134385 -96.740645
Smook SW Undisturbed 49.1677425 -96.74031
Smook NW Undisturbed 49.17568 -96.740368
Townsend Undisturbed 49.163795 -96.67451
Forrester & Casson Undisturbed 49.1185725 -96.66499
Dykun Undisturbed 49.1049425 -96.649898
Clough Undisturbed 49.1576575 -96.649858
Stefanchuk Grazed 49.1553 -96.739845
Nickel Grazed 49.1629125 -96.716645
Fisher Grazed 49.149765 -96.695408
Fisher 2 Grazed 49.1416775 -96.695463
Penner Grazed 49.1205975 -96.654183
Storoschuk Grazed 49.13253 -96.650598
Singh NW Burned 49.148185 -96.74066
Saranchuk Burned 49.179495 -96.67225
Rose Burned 49.171915 -96.672625
Kai Kwong Lee Burned 49.17512 -96.650273
Bott Burned 49.16934 -96.65027
139
Chapter 5: Conflicting response of pollinator, decomposer, and predator insects to
disturbance and landscape in northern tallgrass prairie
5.0 Abstract
Tallgrass prairie (TGP) management has typically focused solely on the maintenance and
proliferation of the floral community. There is now increased realization that arthropods in TGP
perform several beneficial tasks that increase the productivity and natural beauty of the prairie
landscape. It is not entirely clear if burning and grazing, two common management practices,
positively or negatively impact prairie arthropods, and whether these benefits or negative
responses are a result of direct effects or indirect effects via changes in floral/soil conditions. I
set out to test how pollinators, represented by ground and stem nesting wild bees; decomposers,
and predators, both represented by the haplogastran beetle community; respond to burning and
grazing in the TGP. As well, I measured landscape characteristics to determine how diversity,
composition, and edge amount in the environment affect these insect guilds. I found that
communities of both bees and beetles were distinct between burned and grazed sites. Overall,
bee abundance, richness, and diversity were all significantly higher in undisturbed sites
compared to grazed sites. Rarefied diversity measures revealed that burned sites were often more
diverse than grazed sites, except for stem nesting bees, which showed lowest diversity in burned
sites. For the entire beetle community, grazed sites supported greater abundance compared to
burned and undisturbed sites, but significantly fewer effective species than burned sites. When
separated by guild, predatory beetles were more abundant in burned sites, while decomposer and
unidentified aleocharine beetle abundance was significantly higher in grazed sites. While bees
responded positively to increased landscape diversity, beetles were unaffected. In both bees and
beetles, abundance, richness, and diversity were all positively influenced by the amount of forest,
ditch, and pasture in the surroundings, or negatively influenced by the amount of prairie and
savannah in the surroundings, though they responded at different scales. The ground cover of
sites influenced bee abundance, and ground-nesting bee abundance and richness, in all cases
responding positively towards increasing forb cover, number of flowers, and increasing bare
ground. These qualities are key elements to bee foraging and nesting. Conversely, beetle richness
and predatory beetle abundance, richness, and diversity were all influenced in the opposite
direction than the bees, towards increasing grass cover, which is consistent with life histories that
aren’t dependent on flowers and underground nests. Considering that most study sites were
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without management for several years prior to my study, my results seem to imply that
management decisions can have long lasting effects on bee and beetle communities beyond
active management years. The contrasting response of these guilds to disturbance type indicate
that it may be best to maintain a diversity of techniques but ensuring that there are fire and
grazing free refugia for especially vulnerable species. The discovery of new provincial records
and even one new species indicates how understudied the insect fauna of Manitoba remains, and
highlights the importance of maintaining large swaths of the ancestral tallgrass prairie.
5.1 Introduction
Insects perform a variety of beneficial services in tallgrass prairie (TGP) (Whiles and
Charlton 2006). These services include pollination, which influences the floral community
composition; predation, which influences the faunal community composition, and
decomposition, which influences nutrient cycling and how energy is converted in the prairie
(Whiles and Charlton 2006). TGP is commonly managed by several methods, including grazing
and prescribed fire (Sveinson 2003). To test how these disturbance types influence the
abundance and diversity of beneficial prairie insects, I conducted a two-part experiment where I
caught and identified wild bees and haplogastran beetles in sites that differed by their disturbance
history, as well as by their landscape diversity, landcover composition, and ground cover
characteristics. Here I summarize the main results of my findings.
5.2 Disturbance Type Effects
While disturbance type was an important variable in many of the bee models, it mostly
affected beetles via abundance, though for the combined beetle matrix, it also influenced
diversity. In the case of both bees and beetles, community composition was significantly
different between burned and grazed sites. For bees, undisturbed sites showed increased
abundance, richness, and diversity compared to grazed sites (Figure 5.1). When bees were
separated by nesting guild, undisturbed sites supported greater ground nesting species richness
than grazed sites, while burned sites supported greater abundance of stem nesting bees than
grazed sites. Rarefied richness curves demonstrated that grazed sites were overall worse for bee
diversity in most groups, while burned sites showed reduced diversity of stem nesters compared
to undisturbed sites according to the rarefied Hill’s Shannon and Inverse Simpson’s graphs. For
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beetles, grazed sites showed increased abundance of beetles compared to burned and undisturbed
sites for both the total haplogastran beetles (Figure 5.2) and the aleocharines, however, burned
sites housed significantly higher diversity of beetles compared to grazed and undisturbed sites
(Figure 5.3). When identified beetles were separated by feeding guild, burned sites had a greater
abundance of predatory beetles than either grazed or undisturbed sites, while grazed sites showed
higher abundance of decomposer beetles than undisturbed sites. The rarefied diversity curves
confirmed that burned sites were more diverse than grazed and undisturbed sites in all but the
predatory guild. It has been pointed out that the positive effects of grazing probably only extend
to those insect guilds which directly benefit from it through increasing dung input (van Klink et
al. 2015). Therefore, while decomposer beetles may have benefitted in abundance through cattle
grazing or through an increased organic matter litter layer in my study, it is important to not
extrapolate this positive effect to other trophic levels.
Figure 5.1 Bar graph representing the effect of the three disturbance types on bee bowl caught
bee abundance, species richness, and Hill’s Shannon effective species number. Error bars
represent the standard error. Different letters above bars represent significant differences based
on GLMs with disturbance type as the explanatory variable with a negative binomial
(abundance), quasi-Poisson (richness), and Gamma (Hill’s Shannon) distributions (alpha = 0.05).
a
a a
a a
b a b
ab
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Figure 5.2 Bar graphs representing the effect of the three disturbance types on beetle abundance
in 2017 (left) and 2018 (right). Error bars represent the standard error. Different letters above the
bars represent significant differences based on GLMs with disturbance type as the explanatory
variable with negative binomial distributions (alpha=0.05).
Figure 5.3 Bar graphs representing the effect of the three disturbance types on beetle species
richness in 2017 and 2018, and on Hill’s Shannon effective species numbers in 2017 and 2018.
a
b b
a a
a ab b
a
a a a
b
a a
a
b
c
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Error bars represent the standard error. Different letters above the bars represent significant
differences based on GLMS with disturbance type as the explanatory variable and Poisson
(richness) and Gamma (Hill’s Shannon) distributions (alpha=0.05).
5.3 Landscape Composition Effects
While bees responded most at scales of 1 km, which is at the high end of the typical
foraging range for wild bees (Gathmann and Tscharntke 2002, Zurbuchen et al. 2010), beetles
responded more at the 500 m scale, which might reflect some of the flightless or rare to fly
species. Bees universally responded positively to increased landscape diversity, while beetles did
not respond at all. Bees and beetles responded similarly to landcover composition, with both
having positive effects of the landcover PCA, indicating that they are either responding
negatively to increasing prairie and savannah in the environment, or positively to increasing
forest, ditch, and pasture cover. The northern block of the MTGPP is very wet, which could
explain a negative effect of increasing prairie cover. As well, bees are known to respond
positively to increasing forest cover in TGP (Griffin et al. 2017, 2021). Predatory beetles are also
known to be more diverse in forest adjacent to TGP (Roughley et al. 2006), though I found
positive effects mostly in my decomposer beetle models, which conflicts with another prairie
study that found decreased silphid abundance under increasing forest cover in a prairie
ecosystem (Walker Jr and Hoback 2007). There is some evidence that increased forest area and
edge benefits abundance and richness of rove beetles in grassland ecosystems (Tóthmérész et al.
2014), which could potentially explain my results. Decomposer beetle abundance was positively
affected by increased amount of edge in the environment. This conflicts with some other findings
that found negative (Rocha-Ortega and Coronel-Arellano 2019) or negligible (Sánchez-de-Jesús
et al. 2016) effects of patch shape, but they were conducted mostly in subtropical environments
and looking specifically at dung beetles.
5.4 Ground Cover Effects
Bees and beetles both responded to ground cover effects, but in opposite ways. When
present in bee models, the ground cover PCA had a positive effect, implying that increased forb
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cover, bare ground cover, number of flowers, and decreased amount of grass cover benefitted
bee abundance and diversity, especially for the ground nesting guild. Predatory beetles on the
other hand, showed a negative effect of the PCA in their models, implying that increased grass
cover positively affected their diversity and abundance. This is consistent with another grassland
study that found the same effect (Crist and Peters 2014).
5.5 New and Interesting Records
We caught at least two bee provincial records, Melissodes desponsus Smith, and
Lasioglossum (Dialictus) michiganense (Mitchell). The former is a pollen specialist on thistle,
Cirsium spp., while the latter is a social parasite of other Dialictus bees (Gibbs 2011). For
beetles, I caught 19 new records: two hydrophilids, three leiodids, and 14 staphylinids. I caught
one beetle that Adam Brunke (CNC) believes has not been previously noted or described from
the genus Stenus. Adam Brunke (CNC) also discovered a previously undescribed species of
Ischnosoma based on my collections, though it has previously been caught elsewhere and just
misidentified. A few of the records are of very minute rove beetles, including Micropeplus
sculptus LeConte, and Euconnus flavitarsis (LeConte). Four of the new records belong to the
large, predatory rove beetle genus Philonthus, which are largely unidentifiable without dissection
of male genitalia, so have perhaps previously been overlooked. I also caught 13 specimens of
Staphylinus ornaticauda LeConte, a species that has been suggested as being vulnerable to
extinction given that it is large and flightless and has a relatively narrow habitat range (Brunke et
al. 2011). It is also listed as critically imperiled in the province of Ontario according to
NatureServe, but it is unranked in Manitoba.
5.6 Future Directions
Since historically TGP experienced combinations of fire and grazing, a study in the
southern block of the MTGPP (where both practices are used in combination on individual sites)
should be undertaken to determine how bees and beetles respond when both practices are in use.
Future studies should also measure stocking rate and mowing/haying regimes of sites, to see if
they are confounding the results. As well, the preserve should attempt to allow bison to graze on
some sites, since they would have historically been present, and they are known to have different
effects on prairie floral (Towne et al. 2005) and faunal elements (Rosenberger and Conforti
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2020) than cattle. Where possible, other beneficial insect guilds should be studied on the prairie,
especially so in the case of syrphid flies, who act as both pollinators and predators (and
sometimes even as saprophages and pollinators) and are known to be the most important
pollination group in northern TGP (Robson 2008). Many studies mentioned the importance of
measuring soil characteristics to better understand grassland insect fauna, so future studies in
TGP should always collect as many soil characteristics as possible, as they may be playing a
large role in insect abundance and diversity.
5.7 Conclusion
It is imperative that habitat and ecosystem restoration programs move beyond a strictly
plant focused framework (Lengyel et al. 2020). Future conservation should focus on increasing
habitat diversity, via a range of different disturbances/lack of disturbances, to maximize TGP
animal diversity (Lengyel et al. 2020). This study shows that different beneficial insect taxa, and
discrete guilds therein, respond in diverse ways to disturbance, landscape, and ground cover.
While current management strategies may benefit one group, they may be inadvertently harming
another. It is hoped that this study can influence the MTGPP management committee, along with
other TGP preserves, to increase efforts to study the effects of management and landscape
context on insect fauna. Insects are too often neglected in restoration programs, despite the wide
variety of functions that they perform in the TGP (Whiles and Charlton 2006).
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