Examining the Impacts of Wildfire on Throughfall andStemflow Chemistry and Flux at Plot and Catchment Scales

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Authors White, Alissa Marie

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EXAMINING THE IMPACTS OF WILDFIRE ON THROUGHFALL AND STEMFLOW

CHEMISTRY AND FLUX AT PLOT AND CATCHMENT SCALES

by

Alissa White

____________________________

A Thesis Submitted to the Faculty of the

DEPARTMENT OF HYDROLOGY AND WATER RESOURCES

In Partial Fulfillment of the Requirements

For the Degree of

MASTER OF SCIENCE

WITH A MAJOR IN HYDROLOGY

In the Graduate College

THE UNIVERSITY OF ARIZONA

2015

2

STATEMENT BY AUTHOR

The thesis titled Examining the Impacts of Wildfire on Throughfall and Stemflow

Chemistry and Flux at Plot and Catchment Scales prepared by Alissa White has been submitted

in partial fulfillment of requirements for a master’s degree at the University of Arizona and is

deposited in the University Library to be made available to borrowers under rules of the Library.

Brief quotations from this thesis are allowable without special permission, provided

that an accurate acknowledgement of the source is made. Requests for permission for

extended quotation from or reproduction of this manuscript in whole or in part may be

granted by the head of the major department or the Dean of the Graduate College when in

his or her judgment the proposed use of the material is in the interests of scholarship. In all

other instances, however, permission must be obtained from the author.

SIGNED: Alissa White

APPROVAL BY THESIS DIRECTOR

This thesis has been approved on the date shown below:

December 7, 2015

Jennifer McIntosh Date

Associate Professor of Hydrology

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ACKNOWLEDGEMENTS

This study was supported by the National Science Foundation funded Jemez River Basin

and Santa Catalina Mountains Critical Zone Observatory EAR-0724958 and EAR-1331408. I

would like to thank my thesis advisors Drs. Jennifer McIntosh and Jon Chorover and my

committee members Drs. Tom Meixner and Paul Brooks for their guidance and valuable input. I

am also very grateful to Tyson Swetnam for help with the canopy height model, Rodrigo Andres

Sanchez, Mark Losleben, and Kate Condon for help with fieldwork and sample collection, and

Matej Durcik for help creating maps.

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TABLE OF CONTENTS

LIST OF FIGURES………………………………………………………………………... 5

LIST OF TABLES………………………………………………………………………….6

ABSTRACT………………………………………………………………………………...7

1.0 INTRODUCTION………………………………………………………………………9

2.0 BACKGROUND………………………………………………………………………..11

3.0 METHODS……………………………………………………………………………...14

3.1 Site Description……………………………………………………………....….14

3.2 Experimental Design…………………………………………………………….16

3.3 Sample Collection and Analysis…………………………………………………18

3.4 Data Analysis and Upscaling Solute Fluxes……………………………………..19

4.0 RESULTS………………………………………………………………………………..23

4.1 Volumetric Changes……………………………………………………………..23

4.2 Chemical Composition…………………………………………………………..24

4.2.1 Burned versus Unburned………………………………………………24

4.2.2 Stemflow versus Throughfall………………………………………….25

4.2.3 Solute Fluxes…………………………………………………………..26

5.0 DISCUSSION…………………………………………………………………………...28

6.0 CONCLUSION.………………………………………………………………………....33

7.0 FIGURES and TABLES………………………………………………………………...34

8.0 REFERENCES…………………………………………………………………………..46

9.0 SUPPLEMENTAL MATERIALS………………………………………………………51

9.1 Supplemental Figures and Tables………………………………………………..51

5

LIST OF FIGURES

Figure 1: Conceptual Model…………………………………………………………………..…34

Figure 2: Overview of study area……………………………………………..……………….....35

Figure 3: Burned, unburned, and open precipitation plots…………………….…………………36

Figure 4: Stemflow and throughfall volumes combined...…………………….…………………37

Figure 5: Stemflow and throughfall volumes by catchment…………………….……………….38

Figure 6: Ca and Sr volume weighted mean concentrations…………………….……………….39

Figure 7: PO4 and DIC volume weighted mean concentrations………………….……………...40

Figure 8: Burned and unburned throughfall volume weighted mean concentrations……………41

Figure 9: Burned stemflow and throughfall volume weighted mean concentrations……………42

Supplemental Figure 1: Stemflow and throughfall collectors…………………………………...49

6

LIST OF TABLES

Table 1: Solute Fluxes…………………………………………………………………………..44

Supplemental Table 1: Surface area solute flux calculations…………………………………...50

7

ABSTRACT

This study investigates the effects of fire on the chemistry and flux of precipitation

diverted to the forest floor as stemflow and throughfall by observing the impact of the June 2013

Thompson Ridge Wildfire in the Jemez River Basin of New Mexico. The loss of canopy cover

from wildfire drastically modifies landscapes and alters ecosystems as fire replaces leafy

canopies with charred branches and trunks, changes soil composition and erosion processes, and

affects hydrologic flow paths and water chemistry. In order to track these changes, throughfall

and stemflow collectors were installed beneath burned and unburned canopies in two catchments

impacted by the Thompson Ridge Fire. Throughfall, stemflow, and open precipitation samples

were analyzed for major cations, anions, dissolved inorganic and organic carbon, trace metals,

and rare earth elements to determine how fire affects the chemical composition of the

precipitation that interacts with burned canopies.

Precipitation samples collected from both burned and unburned sites during the 2014

summer monsoon season show variations across burn severity, specifically in calcium, strontium,

phosphate, and dissolved inorganic carbon concentrations, and across collector type with

stemflow concentrations generally higher than throughfall and open precipitation concentrations.

A stem count model was used to determine tree density for individual plots and catchments from

LiDAR images taken before the 2013 fire. The stem count model was used to upscale event and

monsoon season solute fluxes from plot to catchment scale. Higher nutrient concentrations

combined with higher volumes of precipitation diverted as stemflow in burned forests have a

multiplicative effect resulting in greater nutrient fluxes via stemflow creating nutrient hot spots

surrounding burned tree trunks. Upscaling these plot scale concentrations and solute fluxes

8

allows this study to represent changes to an entire catchment and quantify effects of wildfire on

chemical loads and water chemistry.

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1. INTRODUCTION

Wildfires are one of the largest disturbances in forested areas and there has been a

significant increase in the number, size, and severity of wildfires in the western United States

since 1990 (Joint Fire Science Program, 2004; Smith et al., 2011). Westerling et al. (2006) shows

a link between wildfire frequency and summer mean temperatures and the United States Forest

Service predicts that the frequency, severity, and area burned by wildfires will increase in the

Southwest United States with progressive droughts and warming (Peterson and Littell, 2012).

After fire, nutrients that were taken up by plants and used for biotic activity are released from the

burned vegetation and transported to the forest floor via washoff and leaching in stemflow and

throughfall. As wildfires burn more area and occur more frequently, it is important to understand

how those fires affect the flux of solutes available in the critical zone, the area ranging from the

top of the vegetation canopy to the bottom of free flowing groundwater where mass and energy

are exchanged between the regolith, biosphere, and atmosphere (Fields et al., 2015).

A limited number of studies observing prescribed burns and wildfires (Chorover et al.,

1994; Soto and Diaz-Fierros, 1997; Vega et al., 2005) have shown that the volume and chemistry

of throughfall in burned forests is altered by interaction with burned forest stands, despite the

lack of foliage after fire (Figure 1). However, more extensive work is required to gain a better

understanding of changes in throughfall water and solute fluxes after fire (Levia and Frost,

2006). Variation in stemflow yield and/or ionic composition from dead or dying trees has

recently emerged as a new focus of stemflow studies (Watters and Price, 1988; Hauck et al.,

2002; Frost and Levia, 2014). However, no studies to date have investigated variation in

stemflow volumes and chemical fluxes from burned trees. These burned stemflow and

throughfall knowledge gaps combined with the understanding that solutes are leached in greater

10

concentrations from stemflow than throughfall (Levia and Frost, 2003; Germer et al., 2012) and

recent findings suggesting that standing dead trees can persist in forests for decades (Aakala et

al., 2008; Angers et al., 2010) motivate this study.

In order to inform our understanding of wildfire induced tree mortality on nutrient

availability via stemflow and throughfall this study seeks to answer the following questions: 1)

How do forest fires change the volumetric partitioning of precipitation in burned forest stands?

2) How are the solutes that leach from burned forests different from the solutes leached from

unburned forests? And 3) Based on differences in volume and solute concentration, how does

wildfire affect the fluxes of those solutes to the critical zone? In order to address these questions,

this study observes the effects of wildfire on the chemistry and flux of stemflow and throughfall

at plot and catchment scales.

11

2. BACKGROUND

Throughfall refers to the precipitation that interacts with the forest canopy before falling

to the forest floor. Stemflow refers to the precipitation that is funneled down tree stems and

trunks before reaching the forest floor. In this study, leaching during throughfall and stemflow

refers both to washoff of exogenous elements and release of endogenous soluble elements. In an

extensive review of the throughfall literature, Levia and Frost (2003 and 2006) demonstrated that

throughfall water and solute inputs are highly variable and may change temporally and spatially

as a function of latitude, seasonality, precipitation event magnitude, event intensity, event

duration, wind speed and direction during precipitation events, vegetation cover, plant species,

canopy structure, plant area index, and interception storage. Levia and Frost (2003) and Levia

and Germer (2015) also showed in stemflow literature reviews that stemflow water and solute

inputs vary across sites, tree species, meteorological conditions, canopy structure, seasonality,

and precipitation events. Due to the wide range of variability in stemflow and throughfall fluxes,

it is important to note that this study focuses solely on differences in stemflow and throughfall

water and solute fluxes due to wildfire. Therefore, it is assumed that tree size and canopy

structure do not vary significantly within catchments and that meteorological conditions are

consistent throughout the monsoon season over which samples were collected.

It is understood that the chemistry of throughfall and stemflow are different from that of

open precipitation in live forest stands (Parker, 1983; Pyatt, 1992; Li et al., 1997; Levia and

Frost, 2003; Levia and Frost, 2006; Germer et al., 2007; Zimmermann et al., 2008; Germer et al.,

2012; Levia and Germer, 2015). Throughfall chemistry is commonly enriched in dissolved

organic carbon (DOC), K+, Ca2+, Mg2+, Na+, and Cl- compared to open precipitation chemistry as

solutes are leached from live canopies (Parker, 1983; Li et al., 1997; Levia and Frost, 2006) and

12

may be depleted in NH4+ and NO3

- relative to open precipitation chemistry as N is taken up and

used by plants (Li et al., 1997). Stemflow chemistry is often enriched in K+, Cl-, NO3-, and Ca2+

compared to the chemistry of open precipitation as solutes are leached from stems and trunks

(Parker, 1983; Pyatt, 1992; Levia and Frost, 2003; Germer et al., 2012; Levia and Germer, 2015).

Stemflow nutrient deposition is typically more concentrated than throughfall and open

precipitation because of the longer contact time of precipitation over stems and trunks (Levia and

Frost, 2006). Stemflow deposition is also localized to a relatively small area encircling the tree’s

trunk producing hot spots of greater nutrient availability extending from and surrounding

individual trees (Levia and Germer, 2015) while throughfall contributes to the creation of

heterogeneous nutrient pools across forests. Parker (1983) discusses the importance of nutrient

recycling via the uptake and release of nutrients in forests. He stresses the central role that

stemflow and throughfall have in nutrient recycling as a major pathway of solutes, specifically

N, P, K+, Ca2+, Mg2+, and Mn, to the forest floor.

Limiting nutrients such as N and P are commonly taken up by plants for biotic use. Nezat

et al. (2010) suggest that Ca2+ may also become a limiting nutrient for vegetation. After tree

death, in the absence of biotic activity, these nutrients are released to the forest floor via leaching

from stemflow and throughfall. Watters and Price (1988) suggested that stemflow from standing

dead trees may contribute a very significant transfer of PO43- and NO3

- to the forest floor and

greatly affect nutrient availability. The release of macronutrients like P and Ca2+ from burned

trees via stemflow and throughfall may help to replenish the nutrient pool and may create

nutrient stores in the absence of live, healthy plants.

In an effort to examine wildfires as a disturbance affecting hydrologic and chemical

fluxes and storage dynamics (Ebel and Mirus, 2014), this study observes wildfire’s effects one

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year after containment of the Thompson Ridge Fire in the Valles Caldera National Preserve

located in northern New Mexico. Therefore, this study is more indicative of continuing changes

to nutrient load and release of lithogenic elements from biomass combustion than immediate

wildfire effects. Chorover et al. (1994) found that concentrations of bivalent cations, such as

Ca2+ and Mg2+ in soil solutions remained elevated over longer periods of time after fire

compared to highly mobile monovalent cations like K+, NH4+, and Na+ because of their higher

affinity for adsorptive retention on ion exchange sites. Therefore, leaching of major monovalent

cations likely occurred immediately after fire and cannot be wholly accounted for in this study.

This study also focuses solely on precipitation in the form of rain during the North American

Monsoon season and examines the nutrient load and release of lithogenic elements mobilized

from those intense storms.

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3. METHODS

3.1 Site Description

This study focuses on the effects of the Thompson Ridge Fire (Figure 2) which burned

approximately 24,000 acres around Redondo Peak within the Valles Caldera National Preserve

(VCNP) during June 2013 (Lujan, 2013). The preserve is located in the Jemez Mountains in

northern New Mexico northwest of Albuquerque. Redondo Peak stands at an elevation of 3,432

m and is the site of the Jemez River Basin Critical Zone Observatory (JRB-CZO) which has been

characterized in previous studies (Broxton et al., 2009; Perdrial et al., 2014; Swetnam and Falk,

2014; Vazquez-Ortega et al., 2015; Zapata-Rios et al., 2015). This region is located in the

transition zone between the snow dominated Rocky Mountains and the monsoon dominated

deserts of the southwestern United States (Broxton et al., 2009; Huckle, In Review). The VCNP

is in a montane, continental, semi-arid climate characterized by a bimodal precipitation pattern.

The average annual precipitation is 711 mm, of which approximately half falls as snow and rain

during the winter months and the other half falls as brief but intense rainfall associated with the

North American Monsoons during the summer months. The average summer and winter

temperatures are 10.7oC and -1.1oC, respectively (Zapata-Rios et al., 2015). The geology of

Redondo Peak is dominated by Pleistocene aged Bandelier Tuff, rhyolite, and andesitic rocks

(Broxton et al., 2009; Vazquez-Ortega et al., 2015).

Redondo peak is surrounded by multiple catchments and this study focuses on two

catchments of different aspect, north facing Upper Jaramillo and south facing La Jara (Figure 2).

Both catchments have similar mean slopes and are situated at similar elevations with Upper

Jaramillo catchment ranging in elevation from 2,723 to 3,324 m with a mean slope of 14.7o and

La Jara catchment ranging in elevation from 2,702 to 3,429 m with a mean slope of 15.7o. Upper

15

Jaramillo catchment drains an area of 3.06 km2 while La Jara catchment drains an area of 2.66

km2. Upper Jaramillo catchment has 46% forest cover while La Jara catchment has 57% forest

cover (Perdrial et al., 2014). Both catchments include mixed-conifer forests dominated by a

range of fir and spruce species including blue spruce (Picea pungens), Douglas fir (Pseudotsuga

menziesii), white fir (Abies concolor), and Engelmann spruce (Picea engelmannii) (Muldavin et

al., 2006; Broxton et al., 2009; Perdrial et al., 2014; Swetnam et al., 2014).

The Thompson Ridge Wildfire began May 31, 2013 when a tree collapsed into a power

line in Sulfur Canyon. The fire burned up and over Thompson Ridge before ascending the

western slope of Redondo Mountain where it progressed eastward just short of the boundary of

the 2011 Las Conchas Fire perimeter at the Valles Grande. It burned about 24,000 acres before

its containment July 1, 2013 (Lujan, 2013). According to the relativized differenced normalized

burn ratio (RdNBR) obtained from Monitoring Trends in Burn Severity, the burn severity of the

Thompson Ridge Fire varied throughout the VC (Figure 2; MTBS). According to the Burned

Area Emergency Response Assessment completed immediately after the fire’s containment, 74%

of land within the fire perimeter was classified as unburned or low severity burn, 23% was

classified as moderately burned, and 3% was noted as severely burned (Lujan, 2013).

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3.2 Experimental Design

Two locations (La Jara catchment and Upper Jaramillo catchment; Figure 3) within the

burn perimeter of the Thompson Ridge Fire (Figure 2) were chosen based on the tree type,

density, average diameter at breast height (DBH), and burn severity in order to observe the

effects of wildfire on the chemistry and flux of stemflow and throughfall. One unburned and one

burned plot (0.01 ha) of mixed conifer forest (fir and spruce) were equipped with stemflow and

throughfall collectors at each location. Burned trees were dead and standing with charred black

bark and no leaves while unburned trees were alive with branches and green leaves. A third

unforested plot within each location was equipped with open precipitation collectors. Six

stemflow collectors and eight throughfall collectors (24 total stemflow and 32 total throughfall)

were installed in each burned and unburned plot while three open precipitation collectors (six

total open precipitation) were installed in each open precipitation plot in June 2014.

Stemflow collectors (Supplemental Materials Figure 1) were constructed from vinyl

tubing wrapped around tree trunks over an approximate vertical length of 1 m (from 1.5 to 0.5 m

above base of tree) with approximately 1 cm opening between tubing and tree to collect

precipitation as it descended the tree trunk, following methods similar to those described by

Thimonier (1997), Williams (2004), and Benham (2007). The tubing directed stemflow into a

sealed two gallon bucket below lined with a Teflon bag. Stemflow collectors were secured to

trees with galvanized steel nails and a watertight seal was created using silicone sealant to ensure

that precipitation was diverted into the tubing and subsequent bucket collector.

Throughfall and open precipitation collectors were constructed from two gallon buckets

sealed with a lid whose center was cut to securely fit the tip of an 8.7 cm diameter Teflon funnel.

Teflon funnels were secured to the buckets using silicone sealant and collectors stood at an

17

approximate height of 0.4 m above the ground surface. Open precipitation collectors were

situated in a clearing away from trees at a distance of at least twice the height of the surrounding

forest. Throughfall collectors were situated beneath the tree dripline, approximately 1 m from the

base of tree to provide consistent measurements across burned and unburned plots (Supplemental

Materials Figure 1). Cardinal directions of collector placement relative to tree base varies.

Throughfall and stemflow collectors were randomly spaced in fixed locations on and around

trees representative of the whole plot.

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3.3 Sample Collection and Analysis

Precipitation samples were collected on an individual storm event basis. Fresh Teflon

bags were placed in buckets before monsoon storm events and immediately removed the

subsequent day. Samples were collected from four summer 2014 monsoon storm events, two

early in the monsoon season and two late in the monsoon season. Precipitation samples were

combined by collector type on an event basis due to volume constraints of chemical analysis.

Therefore, eight samples of each collector type (stemflow, throughfall, and open precipitation)

were collected during the span of this study.

Samples were packed on ice and shipped back to the University of Arizona where they

were stored at 4oC in their respective Teflon bags until prompt filtration and analysis. Samples

were weighed using a mass balance before filtration to determine the total volume collected from

each collector type at each plot on an event basis. Samples were filtered for anion, cation, trace

metal, and rare earth element concentrations through 0.45 µm nylon filters and cation splits were

acidified with optima grade concentrated nitric acid. Samples used for dissolved organic carbon

(DOC), dissolved inorganic carbon (DIC), and total dissolved nitrogen (TDN) analyses were

filtered through combusted 0.7 µm glass fiber filters. Cation, trace metal, and rare earth element

concentrations were measured on an inductively coupled plasma mass spectrometer (ICP-MS)

(ELAN DRC-II, Perkin Elmer, Shelton, CT) in the Arizona Laboratory for Emerging

Contaminants (ALEC). Anion concentrations were measured using ion chromatography (Dionex

Ion Chromatograph DX-500, Sunnyvale, CA) at the University of Arizona. DOC, DIC, and TDN

were measured using catalytic oxidation at 720oC using a Shimadzu TOC-VCSH with a TNM-1

nitrogen measuring unit (Shimadzu, Columbia, MD).

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3.4 Data Analysis and Upscaling Solute Fluxes

Two tailed t-tests with a confidence interval of 95% were used to determine significant

differences in concentration and volume across burn severity and collector type. Due to

volumetric constraints of chemical analysis, samples from each plot were combined based on

collector type; therefore, volumes of stemflow and throughfall are not known for individual

trees/collectors. Volume weighted mean (VWM) concentrations were calculated for all solutes

analyzed in samples as follows:

𝑉𝑊𝑀𝑥 = ∑ 𝐶𝑥𝑉𝑛

𝑛1

∑ 𝑉𝑛𝑛1

(1)

where Cx denotes the concentration of each solute, x, and Vn represents the volume of each

sample, n.

Individual tree distributions of the mixed conifer plots and catchments instrumented as

part of this study were derived from aerial Light Detection and Ranging (LiDAR) high density

(>12 pulses per square meter) pre-fire images taken in 2010 and 2012 which were used to

produce a canopy height model and were run through a variable-area local maxima algorithm in

MATLAB 2013a (The Mathworks, 2013). The algorithm was based on ground observations

from the VCNP and isolates local maxima pixels of the canopy height model and incorporates

allometric predictions of the Metabolic Scaling Theory to differentiate individual canopies from

stems and understory and predict DBH from canopy radius and height (Swetnam and Falk, 2014;

Swetnam et al., 2014). Linking the model with vegetation map types of the preserve (Muldavin

et al., 2006) also produced individual existing vegetation types (EVT) of each tree within the

instrumented plots and catchments.

The algorithm was used to generate the number of trees, DBH, EVT, canopy diameter,

and height of each tree in each instrumented plot. Applying this model to burned plots and

20

overlaying the RdNBR to determine burn severity of each plot relies on the assumption that tree

trunks seen in pre-fire LiDAR within the instrumented plots were moderately burned and remain

as standing charred dying trunks after fire. Based on the principles of allometry and

modifications to the representative area method and tree/stemflow correlation method created by

Hanchi and Rapp (1997), the above parameters were used to calculate the surface area of each

tree by treating each tree as a cylinder.

Relationships between diameter at breast height (DBH) and stemflow volume are

commonly observed (Strigel et al., 1994; Hanchi and Rapp, 1997; Aboal et al., 1999; Dezzeo and

Chacón, 2006; Germer et al., 2012). However, determining this specific relationship by fitting a

regression to stemflow volume and DBH data was not an option in this study because samples

were combined due to volumetric constraints of chemical analysis. Therefore, two DBH based

methods are considered when estimating solute fluxes: cross sectional basal area associated with

stemflow volumes and cylindrical surface area associated with available leaching area. The

solute fluxes calculated using the sum of the cross sectional basal area of each tree within

sampled plots were compared to the solute fluxes calculated using the sum of surface area

calculated by treating each tree in the sampled plots as a cylinder without bases (Supplemental

Materials Table 1). Solute fluxes at the plot scale in kg/ha/monsoon event of each solute at

significant concentrations were calculated according to the following equations:

𝐹𝑙𝑢𝑥𝐵𝐴_𝑆𝐹,𝑥,𝑝 = 𝑉𝑝

∑ 𝐵𝐴𝑡,𝑝𝑡1

∗ 𝑆𝐹𝑠ℎ𝑎𝑟𝑒 ∗ 𝑉𝑊𝑀𝑥,𝑝 (2)

𝐹𝑙𝑢𝑥𝑆𝐴_𝑆𝐹,𝑥,𝑝 = 𝑉𝑝

∑ 𝑆𝐴𝑡,𝑝𝑡1

∗ 𝑆𝐹𝑠ℎ𝑎𝑟𝑒 ∗ 𝑉𝑊𝑀𝑥,𝑝 (3)

where Vp is the volume of stemflow collected per plot, BAt,p is the basal area of each tree, t, SAt,p

is the surface area of each tree treated as cylinder without bases, VWMx,p is the VWM

21

concentration of each element, x, for each plot, p, and SFshare refers to the ratio of stemflow

collectors to trees in each plot. The surface area is calculated by treating each tree as a cylinder

without bases because of the increased surface area available for direct contact with the

precipitation because of lack of foliage and reduced stems after fire.

Throughfall depths were calculated by dividing the volume of throughfall collected

within each plot per event by the total area of the funnels over which that throughfall was

collected. The throughfall solute flux at the plot scale in in kg/ha/monsoon event of each solute

shown to have significant concentrations was calculated as follows:

𝐹𝑙𝑢𝑥𝑇𝐹,𝑥,𝑝 = 𝑉𝑝

∑ 𝐴𝑓𝑓1

∗ 𝑉𝑊𝑀𝑥,𝑝 (4)

where Vp is the volume of stemflow collected per plot, p, Af is the cross sectional area of each

funnel, f, and VWMx,p is the VWM concentration of each element, x.

Throughfall volumes have been linked to canopy characteristics, such as canopy area and

basal area (Molina and del Campo, 2012; Trinh and Chui, 2013). A wildlife management

comparison of basal area and canopy cover found that basal area gives greater emphasis to the

cover of large diameter trees (Cade, 1997); therefore, canopy area was used to relate plot and

catchment solute fluxes to avoid weighting larger trees. Throughfall solute fluxes at the

catchment scale in kg/ha/monsoon event were calculated according to the following equation:

where Ap/c is the ratio of plot to catchment area, CAp/c is the ratio of canopy area within each plot

and catchment, and Treesc is the number of mixed conifer trees within each catchment.

Statistical analysis of solute concentrations from July compared to August showed no

significant temporal difference in solute concentrations. Therefore, solute fluxes were scaled up

𝐹𝑙𝑢𝑥𝑇𝐹,𝑥 = 𝑉𝑝

∑ 𝐴𝑓𝑓1

∗ 𝑉𝑊𝑀𝑥 ∗ 𝑇𝑟𝑒𝑒𝑠𝑐 ∗𝐴𝑝/𝑐

𝐶𝐴𝑝/𝑐 (5)

22

from individual monsoon events (kg/ha/monsoon event) to the full monsoon season solute flux

(kg/ha/monsoon season) by multiplying each event flux by a precipitation depth scaling factor,

Pshare calculated as follows:

𝑃𝑠ℎ𝑎𝑟𝑒 =∑ 𝐷𝑛

1 𝑡𝑦𝑝𝑒,𝑛∗𝐷𝑝𝑝𝑡,𝑠𝑒𝑎𝑠𝑜𝑛,𝑀𝐸𝑇

𝐷𝑝𝑝𝑡,𝑒𝑣𝑒𝑛𝑡𝑠,𝑀𝐸𝑇 (6)

where Dtype,n is the sum of the depth of each precipitation type (stemflow or throughfall) from

each event, n, Dppt,season,MET is the depth of open precipitation over the whole monsoon season,

and Dppt,events,MET represents the depth of open precipitation from the dates of the events collected.

The depth of open precipitation from monsoon events from July 1, 2014 to September 30, 2014

was calculated based on data recorded at the Redondo Peak Valles Caldera New Mexico

Meteorological Station (35o53’02’’ N, 106o33’13’’ W; 3231 masl), located roughly between the

two catchments at a similar elevation.

The algorithm was also run for La Jara and Upper Jaramillo catchments in which the

collector plots were situated. The flux of solutes at the plot scale were scaled up to calculate the

flux of solutes to the catchment scale (kg/ha/monsoon event) based on collector type and burn

severity by multiplying the number of spruce, fir, or mixed conifer trees (EVT 1, 2, 4, and 5)

within each catchment (Treesc) by the flux of solutes to the plot, assuming the DBH and canopy

diameter of spruce and fir trees does not vary significantly across the catchment. Post-fire

LiDAR are not publicly available yet, so the number of burned and unburned trees cannot be

distinguished in each catchment. Therefore, catchment scale fluxes assume all trees are burned in

burned catchment solute flux calculations and that all trees are healthy and unburned in unburned

catchment flux calculations. Thus, catchment fluxes represent the maximum impact of wildfire to

a whole watershed.

23

4. RESULTS

4.1 Volumetric Changes

Collected volumes of burned stemflow were 2.8 times greater than volumes of burned

throughfall and volumes of unburned stemflow were 1.3 times greater than those of unburned

throughfall averaged over both catchments suggesting that precipitation is intercepted by tree

canopies in both burned and unburned areas (Figure 4). However, quantitative analysis of

interception volumes is outside of the scope of this study as open precipitation volumes were

lower than all other sample volumes collected suggesting that the Teflon funnels used for open

precipitation collectors were too small to completely capture precipitation in open areas away

from tree cover. In the La Jara catchment, average volumes of burned stemflow were 3.9 times

greater than average volumes of unburned stemflow and average volumes of burned throughfall

were 1.6 times greater than average volumes of unburned throughfall (Figure 5). In the Upper

Jaramillo catchment, average volumes of burned stemflow were 3.7 times greater than average

volumes of unburned stemflow and average volumes of burned throughfall were 2.0 times

greater than average volumes of unburned throughfall (Figure 5) showing that less precipitation

was lost as interception and more precipitation made its way to the forest floor after interacting

with burned forest stands compared to healthy, unburned forests.

24

4.2 Chemical Composition

4.2.1 Burned versus Unburned

Volume weighted mean concentrations of PO43-, Ca2+, and Sr2+ are significantly higher (p

< 0.05) in burned stemflow relative to unburned stemflow. Ca2+ concentrations are 2.4 times

higher in burned stemflow than in unburned stemflow (Figure 6). Sr2+ concentrations are 2.8

times higher in burned stemflow than in unburned stemflow (Figure 6). PO43-

concentrations are

3.2 times higher in burned stemflow than in unburned stemflow (Figure 7). Concentrations of all

other solutes analyzed were not significantly different (p > 0.05) between burned and unburned

stemflow.

VWM concentrations of DIC, Ca2+, and Sr2+ were significantly higher (p < 0.05) in

burned throughfall than in unburned throughfall. Ca2+ content was found to be 1.5 times higher

in burned throughfall than unburned throughfall (Figure 6). Sr2+ concentrations were 2.6 times

higher in burned throughfall than unburned throughfall (Figure 6). DIC concentrations were 2.0

times higher in burned throughfall than unburned throughfall (Figure 7). Differences between

burned and unburned throughfall concentrations of all other solutes analyzed were not

statistically significant (p > 0.05).

VWM concentrations of DOC, Cl-, K+, Al, Mn, and Ni are statistically higher (p < 0.05)

in unburned throughfall compared to burned throughfall (Figure 8). DOC concentrations are 2.1

times higher in unburned throughfall than burned throughfall. Unburned throughfall Cl-

concentrations are 1.7 times higher than burned throughfall. K+ content is 1.9 times greater, Al

concentrations are 1.5 times higher, Mn concentrations are 8.2 times higher, and Ni is 2.3 times

greater in unburned throughfall than burned throughfall. No solutes were found to have

statistically higher concentrations (p > 0.05) in unburned stemflow than burned stemflow.

25

4.2.2 Stemflow versus Throughfall

VWM concentrations of DOC, Ca2+, Sr2+, Mn, Zn, Ba, Si, Al, Cu, Ni, Pb, Cl-, and K+ are

statistically higher (p < 0.05) in burned stemflow than in burned throughfall (Figure 6 and 8).

DOC concentrations are 28.9 times greater in burned stemflow than burned throughfall. VWM

concentrations of Ca2+ and Sr2+ are 3.6 and 3.4 times higher, respectively. Zn concentrations are

42.5 times greater, Ba content is 6.4 times higher, Cu is 4.3 times greater, and Ni content is 5.9

times greater in burned stemflow than burned throughfall. Si concentrations are 2.5 times greater

and Pb content is 8.5 times higher in burned stemflow relative to burned throughfall. K+ content

is 14.9 times greater, Al concentrations are 5.9 times higher, B concentrations are 5.7 times

higher, and Cl- content is 3.5 times greater in burned stemflow than burned throughfall. Mn

concentrations are 264.9 times greater in burned stemflow than burned throughfall. However, it

should be noted that the contribution of Si, Pb, and Zn from collector materials (i.e. silicone

sealant and galvanized nails) is still being investigated. Finally, VWM concentrations of all rare

earth elements (La, Ce, Pr, Nd, Sm, Gd, Tb, Dy, Y, Ho, Er, Tm, Yb, and Lu) except Eu are

statistically higher in burned stemflow than in burned throughfall, as well, suggesting the

immediate release of Eu after fire (Figure 9).

26

4.2.3 Solute Fluxes

Estimation of fluxes of solutes previously shown to have statistically higher volume weighted

mean concentrations in burned and unburned plots was conducted for stemflow and throughfall

at the plot and catchment scale (Table 1). Trends seen in event and seasonal fluxes are consistent

with those seen in VWM concentrations. The event and seasonal fluxes in kg/ha of Ca2+, Sr2+,

PO43-, and DIC are highest in burned stemflow and lowest in unburned throughfall. Solute fluxes

follow the general trend of Ca2+ > DIC > PO43- > Sr2+ in burned and unburned stemflow whereas

solute fluxes in burned and unburned throughfall follow the general trend of Ca2+ > Sr2+ > PO43-

~ DIC. The fluxes of Ca2+, Sr2+, PO43-, and DIC are slightly greater in the south facing La Jara

plots than the north facing Upper Jaramillo plots for stemflow and throughfall.

Solute fluxes from burned stemflow and throughfall are greater relative to unburned

stemflow and throughfall. Ca2+ fluxes from burned throughfall are 10.3 and 11.2 times greater

than from unburned throughfall in Upper Jaramillo and La Jara catchments, respectively. Sr2+

fluxes are 8.6 and 8.2 times higher from burned throughfall than unburned throughfall in Upper

Jaramillo and La Jara catchments. DIC fluxes are 5.7 and 7.6 times larger in burned throughfall

compared to unburned throughfall in Upper Jaramillo and La Jara catchments. Basal area method

Ca2+ fluxes from burned stemflow are 18.9 and 11.8 times larger than fluxes from unburned

stemflow in Upper Jaramillo and La Jara catchments. Sr2+ fluxes calculated from basal area are

23.8 and 8.2 times greater in burned stemflow compared to unburned stemflow in Upper

Jaramillo and La Jara catchments. Finally, PO43- fluxes calculated from the basal area method are

28.0 and 45.3 times greater in Upper Jaramillo and La Jara catchments, respectively. The

calculations of seasonal solute flux from stemflow at the catchment scale differ by approximately

27

2 orders of magnitude based on method, as the basal area estimations are significantly larger than

the cylindrical surface area estimations (Supplemental Materials Table 1).

28

5. DISCUSSION

In both catchments, volumes of stemflow collected in burned forests from standing, dead

trees were significantly greater than volumes of stemflow collected in unburned forests from live

trees. Throughfall volumes in burned forests beneath standing dead trees were also significantly

greater than volumes of throughfall collected beneath live, unburned forests. These volumetric

trends contrast with trends in volumes collected from stressed and standing, dead but not burned

trees in previous studies which found smaller volumes of stemflow collected from dead and

dying trees than from live trees (Watters and Price, 1988; Hauck et al., 2002; Frost and Levia,

2014). This volumetric difference is likely because burned trees in this study were surrounded by

other burned trees that experienced little loss of precipitation via interception at the stand scale

whereas the unburned but dead and dying trees sampled in previous studies were interspersed

within live, healthy forest stands in which live trees intercept precipitation and limit its

interaction with dead trees. It is also important to note that charred bark observed after the

Thompson Ridge Fire was visibly smoother than unburned bark which likely increased the

volume of stemflow diverted down stems as Parker (1983) noted that nutrient deposition via

stemflow is greater in smooth bark stems. Further research is needed to investigate the roughness

of burned bark and its direct influence on stemflow generation.

Concentrations of DIC, Ca2+ and Sr2+ were elevated in burned throughfall compared to

unburned throughfall. Limiting nutrients, namely PO43-, Ca2+, and Sr2+, were leached in

significantly higher concentrations from burned stemflow relative to unburned stemflow. Pyatt

(2007) noted that Ca2+ is important for plant growth and Ulrich (1983) described how trees take

up Ca2+ from the soil to recharge exchange sites on their cell walls. Sr2+ is thought to behave

similarly to Ca2+ during nutrient uptake because of their similar ionic radii and positive ionic

29

charge and is known to replace Ca2+ at ionic exchange sites (Miller et al., 1993; Nezat et al.,

2010). Dasch et al. (2006) showed biologic uptake of both Ca2+ and Sr2+ in three tree species in a

study conducted in the Hubbard Brook Experimental Forest. Regardless of species, they found

increasing uptake of Ca2+ compared to Sr2+ into trees over time and with increasing elevation and

internal ion exchange favoring Sr2+ over Ca2+.

Raison et al. (1985) refers to Ca2+ as nonvolatile because of its very high vaporization

temperature and suggests that Ca2+ loss after fire can be attributed solely to particulate transport.

Elevated Ca2+ concentrations in burned stemflow and throughfall can likely be attributed to the

bonds formed between orthophosphate and Ca2+ to create calcium phosphate which is more

likely to precipitate at higher temperatures as its solubility decreases with increasing

temperature. Ranalli (2004) suggests that burning of plant cell water greatly concentrates those

elements taken up for biotic use which explains greater leaching of Ca2+, Sr2+, and PO43- from

burned trees than unburned trees observed in this study. Certini (2005) surmised that burning

converts P to orthophosphate which is the sole form of P available to biota. In acid soils, this

orthophosphate binds to Al, Fe, and Mn oxides but binds to Ca2+ in neutral or alkaline soils. The

pH of precipitation events sampled during this study were near neutral and ranged from 6 to 7

suggesting that calcium phosphate likely precipitated on burned trees after fire. It has also been

suggested that spruce can directly access calcium phosphate to retrieve nutrients (Blum et al.,

2002). The biologic uptake of Ca2+ and Sr2+ and the likely presence of calcium phosphate after

fire explains why higher concentrations of these solutes were leached in burned stemflow

relative to unburned stemflow and burned throughfall compared to unburned throughfall. Hauck

et al. (2002) also found significant increases in PO43- concentrations leached from stemflow of

30

decomposing trees compared to live trees, which agrees with findings of elevated PO43- found

leaching from burned trees.

Finally, concentrations of divalent cations, such as Ca2+ and Sr2+, are significantly higher

in burned plots than unburned plots while significant differences are not observed in

concentrations of monovalent cations one year after fire. The persistence of bivalent cations over

monovalent cations has also been noted in previous wildfire studies because of their higher

selectivity for ion exchange sites (Chorover et al., 1994; Ranalli, 2004). The absence of

significantly different concentrations of nutrients like NH4+ and NO3

- as well as monovalent

cations such as K+ and Na+ between burned and unburned samples suggest that immediate

effects of wildfire were not captured in this study and future work should explore wildfire’s

immediate effect on stemflow and throughfall leaching.

VWM concentrations of DOC, Ca2+, Sr2+, Mn, Zn, Ba, Si, Al, Cu, Ni, Pb, Cl-, and K+ are

statistically higher (p < 0.05) in burned stemflow than in burned throughfall. Higher solute

concentrations in burned stemflow relative to burned throughfall are likely due to the longer

contact time of precipitation diverted down the trunk compared to precipitation falling through

the canopy. Previous studies comparing stemflow and throughfall solute concentrations from

unburned trees have also noted this trend of greater solute concentrations leached from stemflow

compared to throughfall (Levia and Frost, 2003; Germer et al., 2012). Studies of post-fire surface

water chemistry also noted trace element enrichment in burned watersheds, specifically Ba, Cu,

Ni, Pb, Zn, Al, and Mn, as compared to unburned conditions. Elevated trace element

concentrations were attributed to release from vegetation (Smith et al., 2011; Burke et al., 2013)

which corresponds with the increased trace element release observed in burned stemflow in this

study. Elevated B concentrations, as seen in this study, were not found in fire previous studies;

31

however, the International Plant Nutrition Institute notes its importance as a micronutrient

(Nutri-Facts-North American Edition, 2015). Mn concentrations were also exceptionally high in

burned stemflow samples analyzed in this study and were found to be 264.9 times greater in

burned stemflow than burned throughfall. Hauck et al. (2002) noted higher K+, Ca2+, Mn, Zn and

Pb concentrations in stemflow from dying trees compared to healthy trees. Gonzalez Parra et al.

(1996) also observed elevated Mn concentrations in burned soils as compared to unburned soils

and accredits this Mn increase to ash from burned vegetation and complexes with organic matter.

It appears that the rare earth element Eu was also immediately released after fire. Marked

increases in the positive Eu anomalies (normalized to the upper continental crust; Taylor and

McLennan, 1981) of soil solutions from burned soil pits and stream waters collected in La Jara

and Upper Jaramillo flumes immediately after fire also suggest that Eu was immediately released

from burned plants in contrast to other REYs. The immediate release of Eu after fire is also the

likely cause of the differences in Eu anomalies seen in open precipitation, stemflow, and

throughfall samples. Both open precipitation and unburned stemflow have similar Eu anomalies

around 30 suggesting that stemflow on live trees does not affect the Eu anomaly already present

in open precipitation through leaching or preferential uptake. However, unburned throughfall has

a lower Eu anomaly of about 8 suggesting that Eu is preferentially taken up by the leaves of

living trees. Finally, the Eu anomalies of burned stemflow (approximately 3) and burned

throughfall (approximately 8) are also lower than those of open precipitation and unburned

stemflow even though Eu cannot be taken up in these dead trees and more immediate leaching

took place from stemflow than from throughfall.

Chemical fluxes of Ca2+, Sr2+, PO43-, and DIC from burned trees are significantly larger

than fluxes of those solutes from unburned trees because of greater volumes and higher solute

32

concentrations in burned sites compared to unburned sites. Estimated stemflow solute fluxes

from burned trees in this study are also greater than those from healthy and dead trees (Watters

and Price, 1988) burned throughfall solute fluxes from a prescribed burn that did not combust the

canopy (Chorover et al., 1994), and unburned stemflow solute fluxes (Germer et al., 2007)

observed in previous throughfall and stemflow studies. However, because of the large variability

of stemflow and throughfall water and solute inputs previously described, direct comparisons

between solute fluxes observed in this study and previous studies is not possible (Figure 1).

Greater solute fluxes from stemflow and throughfall in the south facing La Jara catchment

compared to the north facing Upper Jaramillo catchment can likely be attributed to the southerly

storm direction of the North American Monsoon (Adams and Comrie, 1997). Chemical fluxes

from burned stemflow directly to the base of burned trees and throughfall inputs beneath tree

drip lines add significant loads of nutrients to burned watersheds which will likely help to

stimulate vegetation regrowth and soil microbial activity after fire. These nutrient loads may

have important implications for fire management, specifically the use of salvage logging after

fire. In future work, leaching of solutes from stemflow and throughfall will be important

components of understanding changes to the hydrologic system after fire as they are necessary to

understand nutrient pathways and how fire propagates through the critical zone.

33

6. CONCLUSION

Greater volumes of stemflow and throughfall were measured in burned stands compared

to unburned stands due to decreased interception in the absence of foliage and presence of

smooth, charred bark. Concentrations of DOC, nutrients (Ca2+), elements that commonly

substitute for Ca2+ (Sr2+ and Mn), several trace elements, and REYs except Eu are greater in

burned stemflow relative to burned throughfall due to longer contact time of precipitation with

stems producing greater leaching of elements taken up by plants for biotic use. Elevated

concentrations of Ca2+, Sr2+, and PO43- in burned stemflow relative to unburned stemflow can be

attributed to the similar behavior of Ca2+ and Sr2+ and the concentration of Ca2+, Sr2+, and PO43-

during the burning of plant cell water which leads to the precipitation of those elements as

calcium phosphate and their subsequent leaching from burned trees during monsoon events. The

persistence of divalent cations compared to monovalent cations in burned samples suggests the

immediate release of monovalent cations and Eu.

Finally, chemical fluxes from burned stemflow and throughfall observed after the

Thompson Ridge Fire are greater than fluxes estimated in previous studies. More specifically,

greater volumes of stemflow in burned forests combined with greater concentrations of leached

solutes from burned stemflow will have a multiplicative effect on burned stemflow fluxes. As

precipitation leaches nutrients from burned stems and releases them directly to the critical zone,

elevated nutrient deposition from burned stemflow may result in nutrient hot spots surrounding

burned trees. Substantial loads of potentially limiting nutrients, namely Ca2+, Sr2+, and PO43- will

likely have important implications for vegetation regrowth and biogeochemical processes within

the critical zone.

34

7. FIGURES and TABLES

Figure 1. Conceptual model of critical zone response to water partitioning and solute fluxes

in healthy (A) and burned (B) forests in stemflow (orange arrows), throughfall (grey arrows),

and open precipitation (blue arrows). Width of arrows corresponds to the amount of water

fluxes in those precipitation types.

A

B

Open Precipitation: Open Precipitation fluxes are not well understood from this study as not all precipitation was captured

35

Figure 2. Overview of study area shows the Jemez River Basin Critical Zone Observatory within

the Valles Caldera National Preserve located in northern New Mexico. The Thompson Ridge

Fire perimeter is shown in red and uses relativized differenced normalized burn ratio (RdNBR)

obtained from Monitoring Trends in Burn Severity (MTBS) to calculate burn severity. The black

lines around Redondo Peak delineate the La Jara and Upper Jaramillo catchments.

36

Figure 3. Burned, unburned, and open precipitation plots are shown within each catchment.

Insets show location of each plot type over a 1m resolution pre-burn digital Ortho rectified image

(USDA-FSA Aerial Photography Field Office, National Agriculture Imagery Program, 2009).

37

Figure 4. Median unburned throughfall and stemflow volumes lower than burned throughfall and

stemflow, respectively. Mean values are written above box plots.

0

500

1000

1500

2000

2500

Burned Stemflow UnburnedStemflow

Burned Throughfall UnburnedThroughfall

Vo

lum

e (m

L)

774

534

203

534

273

534 154

534

38

Figure 5. Burned forests showed higher mean and median volumes collected for stemflow (A)

and throughfall (B) than did unburned forests and much larger volume ranges were measured in

the La Jara catchment compared to the Upper Jaramillo catchment. Mean values written above

box plots.

0

100

200

300

400

500

600

700

UpperJaramilloBurned

UpperJaramillo

Unburned

La JaraBurned

La JaraUnburned

Thro

ugh

fall

Vo

lum

e (m

L)

225

111

321

196

0

500

1000

1500

2000

2500

3000

UpperJaramilloBurned

UpperJaramillo

Unburned

La JaraBurned

La JaraUnburned

Stem

flo

w V

olu

me

(mL)

534 145

1013

260

A

B

39

Figure 6. Greatest Ca2+ (A) and Sr2+ (B) volume weighted mean concentrations in burned

stemflow and lowest in unburned throughfall. * denotes statistically significant difference (p <

0.05) between burned stemflow and unburned stemflow VWM concentrations. ** denotes

statistically significant difference (p < 0.05) between burned throughfall and unburned

throughfall VWM concentrations. Error bar represent one standard deviation.

0

5000

10000

15000

20000

25000

Ca [ug/L]

Co

nce

ntr

atio

n (

ug/

L)

BurnedStemflow

UnburnedStemflow

BurnedThroughfall

UnburnedThroughfall

A

*

0

20

40

60

80

100

120

Sr [ug/L]

Co

nce

ntr

atio

n (

ug/

L) BurnedStemflow

UnburnedStemflow

BurnedThroughfall

UnburnedThroughfall

B

****

*

40

Figure 7. Greater PO43- and DIC volume weighted mean concentrations leached from burned

compared to unburned samples. * denotes statistically significant difference (p < 0.05) between

burned stemflow and unburned stemflow VWM concentrations. ** denotes statistically

significant difference (p < 0.05) between burned throughfall and unburned throughfall VWM

concentrations. Error bar represent one standard deviation.

0

500

1000

1500

2000

2500

3000

3500

4000

4500

Co

nce

ntr

atio

n (

ug/

L)

Burned Stemflow Unburned Stemflow

Burned Throughfall Unburned Throughfall

*

**

PO43- DIC

41

Figure 8. Significantly (p < 0.05) greater volume weighted mean concentrations of Al, Mn (A),

Cl-, K+ (B), DOC (C), Ni, and Pb (D) in unburned throughfall compared to burned throughfall.

Error bar represent one standard deviation.

05

101520253035404550556065

Al Mn

Co

nce

ntr

atio

n (

ug/

L)

Burned Throughfall Unburned Throughfall

A

0

1000

2000

3000

4000

5000

6000

7000

8000

Cl K

Co

nce

ntr

atio

n (

ug/

L)

Burned Throughfall Unburned Throughfall

B

0

5000

10000

15000

20000

25000

30000

DOC

Co

nce

ntr

atio

n (

ug/

L)

Burned Throughfall Unburned Throughfall

C

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Ni Pb

Co

nce

ntr

atio

ns

(ug/

L)

Burned Throughfall Unburned Throughfall

D

42

Figure 9. Statistically greater volume weighted mean concentrations of Ba, Zn, Mn, Si, Al, and B

leached from burned stemflow than from burned throughfall (A). Statistically significant

differences in VWM concentrations of REYs except Eu with higher concentrations leached from

burned stemflow compared to burned throughfall (B). Statistically greater volume weighted

mean concentrations of Cu, Ni, and Pb in burned stemflow relative to burned throughfall (C).

Statistically significant differences in VWM concentrations of DOC, K and Cl with higher

concentrations leached from burned stemflow relative to burned throughfall (D). Error bars

represent one standard deviation and statistical difference denotes p < 0.05. x denotes the lack of

a statistically significant difference in Eu volume weighted mean concentrations.

0

200

400

600

800

1000

1200

1400

1600

1800

Ba Zn Mn Si Al B

Co

nce

ntr

atio

n (

ug/

L)

Burned Stemflow Burned Throughfall

0

50

100

150

200

250

300

350

400

450

500

La Ce Pr Nd Sm Eu Gd Tb Dy Y Ho Er Tm Yb Lu

Co

nce

ntr

atio

ns

(ng/

L)

Burned Stemflow Burned Throughfall

A

-500500

C

B

-500500

C

x

43

0

1

2

3

4

5

6

Cu Ni Pb

Co

nce

ntr

atio

ns

(ug/

L)

Burned Stemflow Burned Throughfall

1

10

100

1000

10000

100000

1000000

K Cl DOC

Co

nce

ntr

atio

n (

ug/

L)

Burned Stemflow Burned Throughfall

C

-500500

C

D

-500500

C

44

Table One. Solute fluxes from burned and unburned stemflow and throughfall for analytes that

have significantly different concentrations between burned and unburned samples. Event fluxes

are shown above italicized seasonal fluxes for each sample. Units are kg/ha/event for event

fluxes and kg/ha/monsoon season for seasonal fluxes.

Throughfall Fluxes Stemflow Fluxes from Basal Area Calculation

Ca2+ Sr2+ PO43- DIC Ca2+ Sr2+ PO4

3- DIC

Burned

Upper

Jaramillo

Plot

2.54E-01 1.57E-03 4.36E-02 1.72E-01 3.65E-01 2.29E-03 1.23E-01 1.27E-01

2.53E+00 1.56E-02 4.34E-01 1.71E+00 9.92E-01 6.22E-03 3.36E-01 3.46E-01

Burned

Upper

Jaramillo

Catchment

6.66E+03 4.12E+01 1.15E+03 4.51E+03 3.44E+04 1.66E-01 8.95E+00 9.23E+00

6.63E+04 6.77E+02 1.88E+04 7.41E+04 9.35E+04 4.51E-01 2.43E+01 2.51E+01

Unburned

Upper

Jaramillo

Plot

7.35E-02 3.72E-04 3.61E-02 6.16E-02 7.54E-02 3.77E-04 1.72E-02 4.69E-02

3.60E-01 1.82E-03 1.77E-01 3.02E-01 5.24E-02 2.62E-04 1.20E-02 3.26E-02

Unburned

Upper

Jaramillo

Catchment

1.31E+03 6.62E+00 6.44E+02 1.10E+03 7.10E+03 2.73E-02 1.25E+00 3.40E+00

6.42E+03 7.90E+01 7.68E+03 1.31E+04 4.94E+03 1.90E-02 8.68E-01 2.36E+00

Burned La

Jara Plot

3.59E-01 1.67E-03 4.45E-02 2.11E-01 5.92E-01 2.82E-03 3.41E-02 1.25E-01

5.09E+00 2.37E-02 6.31E-01 2.99E+00 1.55E+00 7.41E-03 8.97E-02 3.28E-01

Burned La

Jara

Catchment

3.35E+04 1.56E+02 4.16E+03 1.97E+04 6.99E+04 7.58E-01 9.18E+00 3.36E+01

4.75E+05 1.60E+03 4.26E+04 2.01E+05 1.84E+05 1.99E+00 2.41E+01 8.83E+01

Unburned

La Jara Plot

1.62E-01 3.34E-04 1.86E-02 4.52E-02 1.18E-01 4.69E-04 1.77E-03 6.89E-02

1.41E+00 2.90E-03 1.62E-01 3.93E-01 1.31E-01 5.24E-04 1.98E-03 7.70E-02

Unburned

La Jara

Catchment

4.90E+03 1.01E+01 5.61E+02 1.36E+03 1.39E+04 1.26E-01 4.76E-01 1.85E+01

4.25E+04 1.95E+02 1.09E+04 2.65E+04 1.55E+04 1.41E-01 5.33E-01 2.07E+01

45

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50

9. SUPPLEMENTAL MATERIALS

9.1 Supplemental Figures and Tables

Figure 1. Stemflow and throughfall collectors installed in burned and unburned plots.

51

Table 1. Comparison of stemflow solute fluxes calculated with basal areas and surface areas of

analytes that have significantly different concentrations between burned and unburned samples.

Event fluxes are shown above italicized seasonal fluxes for each sample. Units are kg/ha/event

for event fluxes and kg/ha/monsoon season for seasonal fluxes.

Stemflow Fluxes from Basal Area Calculation Stemflow Fluxes from Basal Area Calculation

Ca2+ Sr2+ PO43- DIC Ca2+ Sr2+ PO4

3- DIC

Burned

Upper

Jaramillo

Plot

3.65E-01 2.29E-03 1.23E-01 1.27E-01 1.36E-03 8.54E-06 4.61E-04 4.75E-04

9.92E-01 6.22E-03 3.36E-01 3.46E-01 1.38E-05 8.67E-08 4.68E-06 4.82E-06

Burned

Upper

Jaramillo

Catchment

3.44E+04 1.66E-01 8.95E+00 9.23E+00 1.28E+02 8.05E-01 4.34E+01 4.48E+01

9.35E+04 4.51E-01 2.43E+01 2.51E+01 1.30E+00 8.17E-03 4.41E-01 4.55E-01

Unburned

Upper

Jaramillo

Plot

7.54E-02 3.77E-04 1.72E-02 4.69E-02 4.35E-05 2.17E-07 9.95E-06 2.71E-05

5.24E-02 2.62E-04 1.20E-02 3.26E-02 2.07E-08 1.04E-10 4.74E-09 1.29E-08

Unburned

Upper

Jaramillo

Catchment

7.10E+03 2.73E-02 1.25E+00 3.40E+00 4.10E+00 2.05E-02 9.38E-01 2.55E+00

4.94E+03 1.90E-02 8.68E-01 2.36E+00 1.95E-03 9.77E-06 4.47E-04 1.22E-03

Burned La

Jara Plot

5.92E-01 2.82E-03 3.41E-02 1.25E-01 3.08E-03 1.47E-05 1.77E-04 6.49E-04

1.55E+00 7.41E-03 8.97E-02 3.28E-01 3.15E-05 1.50E-07 1.82E-06 6.66E-06

Burned La

Jara

Catchment

6.99E+04 7.58E-01 9.18E+00 3.36E+01 3.64E+02 1.73E+00 2.10E+01 7.68E+01

1.84E+05 1.99E+00 2.41E+01 8.83E+01 3.73E+00 1.78E-02 2.15E-01 7.87E-01

Unburned

La Jara Plot

1.18E-01 4.69E-04 1.77E-03 6.89E-02 4.48E-04 1.79E-06 6.75E-06 2.63E-04

1.31E-01 5.24E-04 1.98E-03 7.70E-02 1.91E-06 7.62E-09 2.88E-08 1.12E-06

Unburned

La Jara

Catchment

1.39E+04 1.26E-01 4.76E-01 1.85E+01 5.30E+01 2.11E-01 7.98E-01 3.10E+01

1.55E+04 1.41E-01 5.33E-01 2.07E+01 2.26E-01 9.01E-04 3.40E-03 1.32E-01