A δ18O and
δ2H stable water isotope analysis of subalpine forest
water sources under seasonal and hydrological stress in the Canadian
Rocky
Mountains
SHORT RUNNING: Isotopic analysis of subalpine forest
water use in Canadian Rockies
AUTHORS: Lindsey E. Langs1,2, Richard M.
Petrone1*, John W. Pomeroy2
1Hydrometeorology Research Group, Dept. of Geography
& Environmental Management, University of Waterloo, Waterloo, Ontario,
Canada, N2L 3G1
2 Centre for Hydrology, University of Saskatchewan,
121 Research Drive, Saskatoon, Canada, S7N 5C8
* Contact: Richard M. Petrone (rpetrone@uwaterloo.ca)
Abstract
Subalpine forests are hydrologically important to the function and
health of mountain basins. Identifying the specific water sources and
the proportions used by subalpine forests is necessary to understand
potential impacts to these forests under a changing climate. The recent
‘Two Water Worlds’ hypothesis suggests that trees can favour tightly
bound soil water instead of readily available free-flowing soil water.
Little is known about the specific sources of water used by subalpine
trees Abies lasiocarpa (Subalpine fir) and Picea
engelmannii (Engelmann spruce) in the Canadian Rocky Mountains. In this
study, stable water isotope (δ18O and
δ2H) samples were obtained from Subalpine fir and
Engelmann spruce trees at three points of the growing season in
combination with water sources available at time of sampling (snow,
bound soil water, saturated soil water, precipitation). Using the
Bayesian Mixing Model, MixSIAR, relative source water proportions were
calculated. In the drought summer examined, there was a net loss of
water via evapotranspiration from the system. Results highlighted the
importance of tightly bound soil water to subalpine forests, providing
insights of future health under sustained years of drought and net loss
in summer growing seasons. This work builds upon concepts from the ‘Two
Water Worlds’ hypothesis, showing that subalpine trees can draw from
different water sources depending on season and availability. In our
case, water use was largely driven by a tension gradient within the soil
allowing trees to utilize tightly bound soil water and saturated soil
water at differing points of the growing
season.
KEY WORDS: subalpine forest; transpiration; evapotranspiration;
forest health; water use; Canadian Rocky Mountains
Introduction
Freshwater supplies in mountainous regions are at risk as snow and ice
stores continue to decline under rising global temperatures, earlier
winter snowmelt and changing regional climate regimes (Stewart, Cayan &
Dettinger, 2005; Whitfield & Cannon, 2000; Rasouli, Pomeroy, Janowicz,
Carey, & Williams, 2014). Subalpine forests are of particular
importance due to their hydrological connectivity within basins,
controlling groundwater baseflow fluctuations, influencing basin-wide
evapotranspiration (ET) and altering snow redistribution and storage
dynamics. A change in water availability to alpine vegetation could have
a significant effect on the health of these forests, in turn impacting
annual water budgets (Harder, Pomeroy, & Westbrook, 2015; Carroll,
Knapp, & Martin, 2017; Kelsey, Redmon, Barger, & Neff, 2018).
Quantifying and conceptualizing these changes is imperative to better
inform downstream water management, in addition to providing better
parameterization for climate models. Thus, understanding how subalpine
forests are obtaining and using water during the short mountain region
growing season must be improved.
Past research has conceptualized vegetation water use by a reservoir of
simple well-mixed subsurface storage, which is refilled by growing
season precipitation (P) and always available for transpiration (T) and
growth (Wigmosta, Vail, & Lettenmaier, 1994; Lawrence et al. ,
2011). However, recent research has proven water transport through soils
to vegetation is more complicated, with preferential pathways via
macropores and water storage occurring in the finer pore spaces (Barbeta
& Peñuelas, 2017; Sprenger et al. , 2018; Allen, Kirchner, Braun,
Siegwolf, & Goldsmith, 2019). Plant water use then, becomes a more
dynamic system involving soil pore spaces, preferential pathways and
rooting depth of vegetation (Brooks, Barnard, Coulombe, & McDonnell,
2010). In subalpine vegetation systems, this complexity intensifies with
high heterogeneity and anisotropy within the subsurface soil and bedrock
geology. Often, there are large differences in soil depths and storage
capacities further limiting available water during the growing season,
represented in surficial discontinuities and glacially formed landscape
features (Hood & Hayashi, 2015; Christensen, Hyashi, & Bentley 2016;
Harrington, Hyashi, & Kruylyk, 2017). Rooting structures of subalpine
forests are highly dependent on this subsurface structure, with
limitations in rooting depth due to shallow soils or limited access to
groundwater as a consequence of fractured bedrock. Many studies have
explored the relationship of rooting depth and water uptake in
generalized landscapes (Schenk & Jackson, 2002; West et al. ,
2012; Fan, Miguez-Macho, Jobbágy, Jackson, & Otero-Casal, 2017;
Dubbert, Caldeira, Dubert & Werner, 2019), but few have focused on
these processes in subalpine landscapes at higher altitudes (Jia, Lie,
Chen, & Yu, 2017).
With stable water isotopes (δ18O and
δ2H), it is possible to determine the origin of water
held within the xylem of plants, which is later transpired (Bertrand,
Masini, Goldscheider, & Meeks, 2014; Allen et al. , 2019). These
tracers have been used to show that plants draw water from a variety of
sources, visible through the isotopic signatures unique to each source.
Studies have shown that, despite being situated next to streams, many
plants were using an unidentified source with isotopically different
signatures than the ‘obvious’ source they were located next to (Brookset al. , 2010; Good, Noone, & Bowen, 2015; Bowling, Schuleze, &
Hall, 2017). McDonnell (2014) described this as the ‘two water worlds’
hypothesis, where streams and trees appear to evaporate different pools
of water back to the atmosphere. He called upon more research and
isotope-based tracer studies to be completed in forested catchments in
order to understand the tightly bound soil water and more mobile water
as sources for vegetation.
In mountainous environments that have limited growing seasons and water
availabilities, subalpine forests rely strongly upon soil moisture
stores to sustain growth (Day, DeLucia, & Smith, 1990; Small &
McConnell, 2008). Current research on dominant alpine forest species
(i.e. Abies lasiocarpa (subalpine fir, hereafter fir) andPicea engelmannii (Engelmann spruce, hereafter spruce)) has
focused on physiological and biological differences by elevation and
climate (Sowell & Spomer, 1986; Sala, 2006; Kueppers et al. ,
2017), and species management (Alexander, 1987). However, there are
limited studies of ET and water use (Brodersen, 2006). Most Rocky
Mountain forest research has been conducted in the United States, with
limited research programs conducted in the Canadian Rocky Mountains,
highlighting a gap in knowledge of these species in northern latitudes.
Determining the water sources of these Canadian Rocky Mountain species
is important to understanding tree growth and T throughout the shoulder
and growing seasons to understand the hydrological connectivity of
mountain basins (Kräuchi, Brang, & Schonenberger, 2000; Matyssek,
Wieser, Patzner, Blaschke, & Haberle, 2009), and how these behaviours
could be altered under long-term climate change.
This study aims to identify and characterize subalpine forest water use
at an elevation of 2100 m in the Canadian Rocky Mountains by addressing
three main objectives through a δ18O and
δ2H stable water isotope analysis on trees: I)
determine subalpine forest source water during pre-, mid- and end- of
the growing season; II) partition relative source water contributions of
xylem water within fir and spruce using the Bayesian mixing model
MixSIAR; and III) evaluate which source waters are most important for
subalpine tree T, and how long-term climate pattern changes could affect
forest health.
2 Materials and Methods
2.1 Study Site Description
The data for this study was collected at Fortress Mountain Snow
Laboratory (FMSL) in the Kananaskis River Valley of the Canadian Rocky
Mountains, Alberta. FMSL is part of the Canadian Rockies Hydrological
Observatory
(https://research-groups.usask.ca/hydrology/science/research-facilities/crho.php)
of high elevation hydrometeorological stations and research basins and
is near the long studied Marmot Creek Research Basin (Rothwell et al.,
2016). A research campaign was conducted from May - September 2017, from
the beginning of snowmelt until the end of the growing season in order
to obtain hydrometric and isotopic data. Fortress Mountain has a highly
variable climate depending on season, but typically has long cold
winters and cool wet summers, falling in the humid continental category
(Beckstead & Veldman, 1985; Alberta Environment and Sustainable
Resource Development, 2014).
Two adjacent subalpine sites at Fortress Mountain were used in this
study to accurately represent the diverse forest structure at this
elevation, hereafter referred to as ‘Tower’ and ‘Powerline’. They are
close in proximity (115 m apart) and sit on a low gradient rolling bench
at elevations of 2079 m and 2083 m, respectively (Figure 1). The sites
differ primarily by tree age and density, with Tower having the younger
and higher population density, and Powerline the older and lower
population density (Figure 3). The subalpine forest at this elevation
consists of coexisting subalpine fir and Engelmann spruce tree species.
Species proportions are similar between both sites, with subalpine fir
being the dominant species and Engelmann spruce making up the remainder
(71.9 % and 29.5 %, respectively). There are only coniferous tree
species at this elevation, with the remaining 1.4 % of the population
consisting of lodgepole pine (Pinus contorta ) and alpine larch
(Larix lyalli ). A transect system with arms spanning
approximately 50 m in each cardinal direction, and 10 sampling locations
along each segment was established at each site (Figure 1) and used to
collect forest inventory characteristics (DBH, height, population
density and leaf area index (LAI)).
Hydrometric Data
Collection
Shallow groundwater wells were installed at both study sites to
understand early season snowmelt and the ephemeral water table it
generates. A total of five wells were installed at each site (10 total)
(Figure 1). Between Tower and Powerline, 6 auto-logging water level
transducers (HOBO U20 Water Level Logger; OnSet, MA, USA) were
distributed, with a barometric data logger (HOBO U20 Water Level Logger;
OnSet, MA, USA) installed at Cutline for atmospheric water level
compensation for all loggers. Atmospheric compensation was corrected
using Onset HOBOware Pro 3.7.12 data processing software.
The vadose zone was instrumented for characterization of moisture
dynamics after precipitation (P) events (Figure 2). Three soil moisture
stations were distributed among different cover types: an open tree
canopy, a closed canopy, and a semi-open tree canopy with ample ground
vegetation. Each station was instrumented with two CS650 Soil Moisture
probes at a depth of 30 cm (Campbell Scientific Inc., UT, USA). Soil
temperature (type K thermocouple; Omega, CT, USA) was also measured in
the same pits at 5, 10, 15 and 30 cm depths. Both CS650’s and
thermocouples were logged on a CR1000 data logger (Campbell Scientific
Inc., UT, USA), sampled every 30 seconds and averaged over 30 minutes.
Soil tensiometers (2725ARL Jet Fill Tensiometer; Soil Moisture, CA, USA)
were setup adjacent to the three existing soil moisture stations, each
setup comprised of three tensiometers at depths of 10, 20 and 30 cm.
Tensiometer data was collected by manual measurement 25 times from June
22nd to August 10th, during the
snow-free growing season.
Basic meteorological (MET) data was collected by instrumentation mounted
on a 15.5 m tower, approximately 1.5 m above the top of the forest
canopy. MET data collected included net radiation via sensors at the top
(15.5 m) and bottom (1.4 m) of the tower (NR Lite2; Kipp & Zonen, VA,
USA), relative humidity at a height of 15 m (HMP 155; Vaisala, Finland),
and wind speed and direction using a CSAT3 sonic anemometer. P was
collected at the Powerline site using an Ott Pluvio2(Ott Hydromet, CO, USA) wired to a CR3000 data logger (Campbell
Scientific Inc. UT, USA) with a wind protection shield, and was
additionally corrected for wind undercatch.
Isotope Sample
Collection
All potential sources for tree water use, including snow, P, saturated
and bound soil water, were sampled for analysis of
δO18 and δH2. There was no surface
water at the study site to sample. Water samples were collected during
pre-, mid- and post growing seasons from May-September in 2017.
Snowpack samples were collected for both the pre- and end- growing
season sampling periods. In the pre- period, the spring snowpack was
approximately 1.2 m deep at the time of sampling. Snowpack cores were
taken with a 4.1 cm diameter PVC pipe, and melted at room temperature to
ensure complete mixing and limited phase changes before being
sub-sampled into 20 mL glass poly-seal sampling bottles. A total of 6
cores were taken on two different dates, May 23rd and
June 3rd. Snow was additionally sampled during the
end- growing season collection period due to an early season snowfall
just prior to September 26th, the sampling date.
P (rain) was collected throughout the entire study period
(May-September) after every major storm event when possible, and less
frequently from July-September due to extremely dry conditions and
minimal major P events. Samples were collected nine times, and were
sub-sampled into 20 mL glass poly-seal containers. The P collector was
built to collect and limit evaporation of samples between sampling
periods. A plastic hose was watertight sealed to the bottom of a funnel,
which was then sealed to the top of a water reservoir container. The
hose was cut with enough length to coil on the bottom of the reservoir
to ensure the water level of collected samples topped over the hose,
limiting evaporation and phase changing of the sample. A Ping-Pong ball
was placed in the top of the funnel to further limit evaporation.
Saturated soil (pore) water was sampled during the snowmelt period
starting in May until the snowmelt groundwater table dissipated. The
geology at this site consists of fractured bedrock and glacial till, and
no constant water table persists during the growing season (Christensenet al. , 2016). All saturated soil water samples were taken from
10 wells ranging from 71 - 132.5 cm in depth, which falls within the
maximum rooting depth of Abies lasioscarpa and Engelmann
spruce. Sampling procedure consisted of purging the entire well volume
3 times before sampling into a 20 mL glass poly-seal container. Water
samples were bottled with minimal headspace and stored at room
temperature (never refrigerated or frozen to limit phase changing)
before processing. Saturated soil water was sampled a total of 13 times
from 15 May to 19 June.
Bound soil water samples were taken at every tree sampled for stem
water. Two samples were taken at each tree during every pre-, mid- and
end- growing season sampling campaign totaling 48 overall samples.
Samples were taken with a 1-inch soil auger at a depth of 35 - 45 cm and
stored in a thick poly-plastic bag. Soil samples were refrigerated
during storage and transportation to ensure no evaporation or phase
change occurred before azeotropic distillation.
Eight trees were sampled for each pre-, mid- and end- growing season
sampling period for a total of 24 tree stem water samples. Trees were
sampled from the Tower and Powerline sites, which each contributed 4
samples each to a single sampling period. Each set of 4 trees was
selected first by species and then by size class (Figure 1). At both
Tower and Powerline, two fir and two spruce were sampled. The two trees
from each species were sampled according to the forest survey conducted
in 2015, ensuring trees from above and below the median species DBH and
height were sampled. The same trees were sampled during each sampling
event.
Tree water was sampled from fir and spruce trees by harvesting older
growth (no current year growth) from stem sections by cutting branch
sections from the top, middle and bottom of each tree. Small stem
sections were snipped from the mid-point of the branches. Needles were
stripped from the stem samples before being placed in 30 mL
vaccutainers. As many stems as possible were stored in the containers to
limit potential phase changing headspace until azeotropic distillation
analysis occurred. For each tree, 10 vaccutainers were filled in order
to obtain an adequate sample size for distillation. After sampling,
samples were placed in the freezer for storage and transport until
analysis in order to further limit evaporation or phase changes from
occurring.
Isotope Sample Processing and
Distillation
All samples collected were submitted and processed by the Environmental
Isotope Laboratory (EIL) at the University of Waterloo, Ontario. Snow,
saturated soil water and P water samples were processed using the
δO18 and δH2 LGR-OA-ICOS Laser
System as described in the methods used by EIL, University of Waterloo
(LGR, 2010; Penna et al. , 2012; Berman, Levin, Landais, & Owano,
2013). Soil and tree samples were first processed by azeotropic
distillation (Dewar & McDonald, 1961; Revesz & Woods, 1990) using
toluene to extract pure water from the sample. The bound soil water
samples were then run on the LGR-OA-ICOS Laser System at Environmental
Isotope Lab (EIL), University of Waterloo (2013), while tree water
samples were run using the EA/HT Mircomass IsoPrime system as described
in the methods by EIL, University of Waterloo (Drimmie, Shouaker-Stash,
Walters, & Heemskerk, 2001; Morrison, 2001). The EA system was used
over the LGR-OA-ICOS Laser System due to better accuracy and analysis of
organically derived water contents (Drimmie et al. , 2001).
Data Processing
Isotopic Framework
Development
An isotopic framework for the 2017 study year was developed to generate
a local meteoric water line (LMWL) and local evaporation line (LEL)
specific to the Fortress Mountain, Kananaskis, AB region (Table 1). This
local framework was necessary to analyze the stable water isotope
samples obtained. To properly develop a framework, past climate normals
(relative humidity and temperature) for the study region were determined
from long-term Environment Canada data along with records from Fortress
Mountain since 2014 (Environment Canada, 2015). In addition to relative
humidity and temperature, normal established individual framework
parameters were calculated specific to the Kananaskis region using
Brock, Wolfe, and Edwards (2007) as a guide (refer for framework
parameter terminology).
Once calculated, the LEL was determined as the intersection of the
calculated δ*, δssl and δP points in
δ18O and δ2H space. The LMWL for the
framework was determined by plotting all sampled source water on the
δ18O and δ2H plot (P, saturated soil
water, snow), then obtaining the R2 value generated by
a linear regression. The LMWL generated had an R2value of 0.99, and equation of δ2H =
7.78δ18 + 0.17 (Figure 4), which indicates a strong
relationship adequate for LMWL representation of the Fortress Mountain,
Kananaskis area. All calculated parameters, LEL, LMWL, Global Meteoric
Water Line (GMWL) and processed isotope samples were subsequently
plotted on a δ18O and δ2H plot.
MixSIAR Bayesian Mixing
Model
In order to partition the relative source water contributions of
sub-alpine forest xylem water the R package MixSIAR, a Bayesian mixing
model (BMM) that runs the Markov Chain Monte Carlo (MCMC) method, was
used. MixSIAR is the latest iteration of a series of mixing models
(MixSIR, SIAR) designed to analyze biotracer and isotope data to
determine relative proportions of a mixture and its sources (Stock &
Semmens, 2016). MixSIAR successfully incorporates the uncertainties
associated with stable water isotope compositions, multiple sources,
error terms, priors and varying data structures allowing for analysis of
covariates and multiple variables at once. For this study, the GUI
version of MixSIAR was used within the R console (Stock & Semmens,
2016; R Core Team, 2019). MixSIAR was chosen over simple linear mixing
models and previous versions of compartment mixing models due to its
performance partitioning source water from multiple sources while
including error terms and statistical checks for competency (Stocket al. , 2018; Wang, Lu, & Fu, 2019). Importantly, the BMM
assumes uncertainty and variability associated with stable water isotope
sources are normally distributed. Along with the residual error term,
the model will find a solution even if it is nonsensical. This was
avoided by ensuring the proper checks and δ18O and
δ2H biplot analysis was followed as suggested within
the MixSIAR GUI operation guidelines (Stock & Semmens, 2016).
Two separate BMM runs (with the same parameters) were completed,
analyzing the covarying effects of: (1) time of season and species, and
(2) time of season and tree age. Time of season was always considered a
‘random’ variable, while age and species were always considered ‘fixed’
(Semmens, Ward, Moore, & Darimont, 2009). Run lengths were set at a
chain length of 1,000,000 iterations to ensure the Gelman-Rubin and
Geweke statistical diagnostic checks were met and the MCMC chains had
converged. The error structure used in the model was ‘residual *
process’, as listed in the model GUI and instructions (Parnell, Inger,
Bearhop, & Jackson, 2010). Both tropic enrichment factor and
concentration dependence were set to 0. A non-informative prior
(uniform) distribution was chosen based on insights of the MCMC method
and observations drawn from the δ18O and
δ2H biplot (Newsome, del Rio, Bearhop, & Phillips,
2007).
Results
Isotopic Characteristics of Sub-alpine Trees and their
Source
Waters
The isotopic compositions of tree source water (excluding bound soil
water) varied extensively between P, snow and saturated soil water
throughout the three seasonal sampling periods (pre-, mid-, end-)
(Figure 5). The δ18O value of P ranged from -19.99 to
-12.59 (± 1 SD) ‰ with a mean of -15.28 (± 2.38) ‰.
δ2H value of P ranged from -150.44 to -96.49 (± 1 SD)
‰ with a mean of -177.31 (± 17.93) ‰. Both δ18O and
δ2H P values varied significantly over the growing
season (p = 0.040 for both when p <0.05 at 95%
confidence). P isotopic signatures typically vary greatly, influenced by
the temperature of P condensation, and the ratio of P being condensed to
the P already condensed in the air mass. Successful creation of a LMWL
specific to the Kananaskis region (R2 0.99, Figure 4)
was dependent on the variation in P signatures over the growing season,
from snow melt to the end of senescence, in order to provide confidence
and a strong linear relationship. The δ18O value of
snow water ranged from -23.52 to -21.79 (± 1 SD) ‰ with a mean value of
-22.48 (± 0.54) ‰. Where the δ2H value of snow water
ranged from -180.83 to -166.67 (± 1 SD) ‰ with a mean value of -173.40
(± 4.59) ‰. Both δ18O and δ2H snow
water values varied significantly between May, June and September
(p = 0.021 and p = 0.003 when p < 0.05 at
95% confidence, respectively). Like rain, snow isotopic signatures also
varied due to similar atmospheric processes governing particle
formation. The δ18O value of saturated soil water
ranged from -21.75 to -18.33 (± 1 SD) ‰ with a mean value of -20.03 (±
0.91) ‰. The δ2H value of saturated soil water ranged
from -166.08 to -141.56 (± 1 SD) ‰ with a mean value of -153.08 (± 6.91)
‰. The δ18O and δ2H saturated soil
water values did not vary significantly during the snowmelt period,
while a water table was present and accessible to trees (p> 0.05). There was no significant difference due to the
saturated soil water pool being generated from the spring snowpack melt
over a concentrated time period.
Bound soil water and tree xylem water were analyzed separately, as they
both had potential for species and growing season variation and were
sampled concurrently during each sampling period. The
δ18O value of bound soil water ranged from -20.47 to
-13.40 (± 1 SD) ‰ with a mean value of -17.40 (± 1.38) ‰, where the
δ2H value ranged from -158.44 to -133.63 (± 1 SD) ‰
with a mean value of -146.30 (± 6.48) ‰. There was no statistically
significant difference in the δ18O and
δ2H isotopic signature of bound soil water samples of
different tree species (p > 0.05). There was,
however, a significant difference in the δ18O values
in bound soil water obtained over the growing season (p = 0.037
when p < 0.05, 95% confidence interval). Small
differences between δ2H in sampled bound soil water
indicates minimal evaporative influence causing isotopic enrichment
during the sampling process. However, the bound soil water line plotted
below the LMWL (δ2H = 4.22 δ18 –
72.95, R2 = 0.81) indicating bound soil water
experienced evaporative enrichment naturally, before collection (Figure
6). Differences in δ18O values indicate replenishment
from a variable source, P was consistently available throughout the
growing season and was isotopically variable over the growing seasons.
Limited availability of saturated soil water after June meant that this
source was likely not the key influencer of δ18O
variation.
The δ18O mean value of tree xylem water was -18.04 (±
1.27) ‰, ranged from -20.22 to -13.94 (± 1 SD) ‰. The
δ2H value of tree xylem water ranged from -154.31 to
-134.82 ‰ with a mean value (± 1 SD) of -146.55 (± 4.08) ‰. There was no
statistically significant difference in xylem water
δ18O and δ2H values between species
(p > 0.05), nor in xylem water
δ18O distribution between sampled growing season
stages (p > 0.05). However, there was a significant
seasonal difference (p = 0.025 when p < 0.05,
95% confidence interval) in δ2H values. Differences
in δ2H between soil and xylem water are indicative of
evaporative influence causing isotopic enrichment, where
δ2H fractionation was displayed in 8 of 25 tree xylem
water samples (Figure 6). δ2H fractionation in
vegetation is calculated as δ2HSOIL -
δ2HTREE. A positive difference
indicates fractionation, where a negative, or 0 difference indicates no
fractionation. Most vegetation are assumed to not
H2/H1 fractionate when using and
transpiring water, although it has been observed in some cases (Dawson
and Ehleringer, 1992; Evaristo et al , 2017). When partitioned
over the growing season incorporating soil and groundwater,
δ2H values of tree xylem water showed seasonal
variation in sources used (Figure 7). Although a large overlap between
bound soil water and saturated soil water signatures were observed
(δ2H -158.44 to -143.56 ‰), a pattern was noticeable
between the three sampling periods. Pre- season trees appeared to use a
mixture of sources, having access to the water table during spring
snowmelt, while in the mid-season bound soil water was predominantly
used, with some retention and storage of saturated soil water from the
beginning of the growing season. End-season xylem water
δ2H values again incorporated more saturated soil
water, lessening dependencies on bound soil water only. The increase
δ2H signatures similar to groundwater may be explained
by an increase in P and snow near the end of the growing season,
replenishing soil moisture and deep saturated soil water stores after a
summer season of no recharge (Figure 2). Snow δ2H
values during the end- period were -169.29, helping to support the
recharge utilization theory. End- season was the only sampling period to
observe a trend in tree age and water source, with smaller trees
utilizing more bound soil water than larger trees.
Quantifying Relative Source Water
Partitioning
Results for the MixSIAR BMM are partitioned into growing season stage
and species (spruce and fir), and growing season stage and tree age.
Tree age is based on the size class separations chosen for initial tree
xylem isotope sampling. The lower size class of both species is
hereafter the ‘young’ category, and the upper size of both species the
‘old’ category. Growing season stage is partitioned by the three major
sampling events of tree xylem and bound soil water, pre-, mid- and
end-growing season. The MixSIAR R package is not able to run more than
two constraining variables at one time, although specializing in
multiple source partitioning, which is why runs of species and age were
separated.
The growing season stage and species BMM analysis showed differences
across time and within spruce and firs (Figure 8). Although both species
had different source water proportions, they both followed similar water
use and source trends. For firs, the proportions of water sources during
the pre- period were predominantly bound soil water (50.1 %, SD ± 20.5
%) and saturated soil water (36.5 %, SD ± 23.0 %) (Figure 8a). This
shifted to mainly bound soil water (71.0 %, SD ± 17.6 %) in the
mid-period, with only 11.3 % from saturated soil water (SD ± 11.5 %).
During this period firs only used approximately 13.4 % of water from P
(SD ± 7.9 %). During the end- period bound and saturated soil water
were the dominant fir source with 57.6 % (SD ± 20.7 %) and 28.5 % (SD
± 20.6 %), respectively (Figure 8a). In spruce, the largest proportion
of source water was during the pre- period was saturated soil water
(69.3 %, SD ± 8.4 %), which transitioned to bound soil water (79.2 %,
SD ± 14.4 %) in the mid-period (Figure 8b), and remain the primary
source in the end- period at 74.7% (SD ± 15.1 %) (Figure 8b).
Fir trees used the highest proportion of saturated soil water in the
pre-period, utilizing increased water tables due to spring snowmelt
(Figure 8). Bound soil water and P proportions were highest in the
mid-period, due to tree reliance on soil moisture as the water table
receded and was eventually no longer available. What little P fell
recharged shallow soil moisture layers, becoming available for the
trees. There was a slight increase in proportion of saturated soil water
used, due to late growing season P recharging deeper soil moisture
stores (Figure 8). As highlighted earlier, the δ2H
signatures of late growing season snow likely influenced the increase in
saturated soil water signatures observed in xylem water. With similar
source usage throughout the growing season as fir, spruce relied upon
bound soil water more heavily with a minimum difference of 8.2 % at the
mid- sampling points and a maximum spread of 19.2 % at the pre-growing
season sampling (Figure 8). Spruce relied less upon initial saturated
soil water stores and end of season recharge with differences of 16.0 %
and 13.8 %, respectively (Figure 8).
The BMM analysis of growing season stage and ages showed minimal water
source differences across time, but similarities in behaviour between
age groups (Figure 9). Slight differences between young and old were
noticeable in the overall source partition spreads, in the mid- and end-
period specifically. In the young group, pre-season water used was
primarily bound (76 %, SD ± 16.9 %), followed by saturated soil water
(15.0 %, SD ± 14.4 %) (Figure 8a). In the mid-period, dominant
proportions were bound soil water (76.4 %, SD ± 13.5 %) and P (11.5
%, SD ± 6.0 %) (Figure 9a). Finally, the end-period water was
primarily bound (78.4, % SD ± 14.7 %) and saturated soil water (12.1
%, SD ± 11.0 %) (Figure 9a). For the older tree group, pre-period
proportions were dominated by 61.8 % (SD ± 21.4 %) bound soil water
and 24.1 % (SD ± 19.2 %) saturated soil water (Figure 9b). In the
mid-period, water was primarily from 58.7 % (SD ± 18.2 %) bound soil
water, 20.7 % P (SD ± 8.3 %), and15.3 % (SD ± 15.2 %) saturated soil
water (Figure 9b). Lastly, end-period proportions were largely 60.8 %
(SD ± 20.7 %) bound soil water and 23.2% (SD ± 18.8 %) saturated soil
water (Figure 9b).
The young group, showed a very slight increase in bound soil water use
over the growing season (2.4 %), while relying upon this source for
over 75 % of its water needs (Figure 9). Interestingly, despite an
available water table at the beginning of the growing season, this only
slightly influenced the saturated soil water source portion compared to
the other growing season stages (15 % in the pre- stage and 8.6 %
during mid-), but most reliance remained on bound soil water (Figure 9).
This may be explained by less established rooting systems of younger
trees, which do not have as much access to the water table as their
larger counterparts. Like the young group, the old tree group had a
steady proportion of bound soil water use throughout the growing season,
although of a smaller magnitude (16.5 % less on average) (Figure 9). In
this age group, saturated soil water reliance was 7.8 % more on
average, with higher values at the start and end of the season, during
snowmelt and end of growing season recharge (Figure 8). Both age groups
utilized P more during the mid- period, while there was no water table
present, with older trees using twice as much P as younger trees during
this period (20.7 % vs 11.5 %) (Figure 9). Generally, older trees used
more saturated soil water when it was available than did younger trees,
but both relied mostly upon soil moisture.
The MixSIAR BMM also generated source water proportions for the entire
season, with runs also split into species and age-based groups (Figure
10). For spruce, season long proportions were: 15.4 % (SD ± 14.1 %)
saturated soil water, 15.7 % (SD ± 15.4 %) P, 8.8 % (SD ± 12.5 %)
snow and 60.1 % (SD ± 21.8 %) bound soil water (Figure 10a). For fir,
26.5 % (SD ± 16.9 %) saturated soil water, 16.3 % (SD ± 12.9 %) P,
11.3 % (SD ± 11.8 %) snow and 45.9 % (SD ± 18.6 %) bound soil water
(Figure 10a). Overall, fir had a larger reliance on saturated soil water
with almost 10 % more coming from this source. Bound soil water was
equally important to both species, being the highest proportion of
sources, but spruce placed a higher reliance upon this source by
approximately 15 % (Figure 10). Both species used P and snow sources
similarly. When examining season long trends in water source among tree
age, the proportions for the young group were: 19.3 % (SD ± 15.1 %)
saturated soil water, 15.2 % (SD ± 13.5 %) P, 10.8 % (SD ± 11.9 %)
snow and 54.8 % (SD ± 21.5 %) bound soil water (Figure 10b). For the
old group, 28.4 % (SD ± 21.6 %) saturated soil water, 21.6 % (SD ±
13.8 %) P and 36.2 % (SD ± 20.8 %) bound soil water (Figure 10b).
Older trees were less reliant upon bound soil water, with a proportion
of only 36.2 %, a 18.6 % difference between the young group (Figure
10). Older trees appear to pull similarly from many different sources,
while younger trees are much more reliant on soil moisture stores.
Discussion
Effectiveness of MixSIAR
BMM
With the emergence of δ18O and δ2H
use in vegetation water sourcing, there are many active discussions
regarding collection and processing of organic materials (soil and tree
xylem water) (Orlowski, Pratt, & McDonnell, 2016; Barbeta, Ogee, &
Peñuelas, 2018; Millar, Pratt, Schneider, & McDonnell, 2018) in
addition to presentation of results and data analysis related to
partitioning models (Barbeta & Penuelas; Wang et al. , 2019).
With stable water isotopes, care must be taken to prevent evaporation
and subsequent phase changing of sampled organic materials in order to
prevent isotopic enrichment and fractionation viewable in
δ2H results. It is generally believed that trees do
not fractionate water during uptake (Dawson & Ehleringer, 1992),
although it has been observed in trees within a few studies (Lin & da
Sternberg, 1993; Newsome et al., 2007). Magnitude of isotopic
separation between H2/H1 can be
tested in comparison to bound soil water isotopic signatures (Ellsworth
& Williams, 2007). Eight (of 25) subalpine trees sampled in this study
displayed potential H2/H1fractionation, when compared to bound soil water values. This
discrepancy could be a product of sampling difficulty, with tree stem
segments experiencing some evaporation or phase changing before
analysis. Primarily, H2/H1fractionation is most important when considering linear mixing models.
Fractionation can cause discrepancies when only considering
δ2H in calculations, skewing relative source water
proportions incorrectly. As addressed by Evaristo, McDonnell, and
Clemens (2017), when using two isotopes together in analysis, such as a
BMM, the potential fractionation of δ2H does not
hinder outputs. The authors further suggest that if uncertainties exist
in sources and mixtures (xylem water), the BMM approach is the most
appropriate method. With this in mind, for this study the MixSIAR BMM
was the most suitable method to capture relative source contributions
with multiple source inputs and one mixture (xylem water) and was
effective in representing source water throughout the growing season.
Relative Source Water
Partitioning
Stable water isotope identification of source water in vegetation is
becoming a more commonly utilized method in ecohydrology (Goldsmithet al. , 2012; Bertrand et al. , 2014; Barbeta & Peñuelas,
2017; Liu, Yu, & Jia, 2017; Allen et al. , 2019). In this study,
δ18O and δ2H stable water isotopes
were used in order to help determine subalpine tree source water during
three points in the growing season (pre-, mid-, end-), and to partition
the relative contributions of sources to tree xylem composition. Through
creation of an isotopic framework and generation of the LMWL and LEL for
the FMSL area, δ18O and δ2H stable
water isotopes provided an understanding of subalpine forest water
sources. The isoplot produced in this study, in addition to the BMM
source water-partitioning model, identified subalpine tree source water
for three periods of the growing season. The δ18O and
δ2H isoplot in addition to the seasonal
δ2H xylem water plot highlight that overall, bound
soil water is the most utilized resource. Saturated soil water is also
an important resource, utilized primarily during the beginning of
growing season snowmelt period. The δ18O and
δ2H isoplot and the seasonal δ2H
xylem water plot were used to gain a special understanding of isotopic
signatures within the system, where the BMM source water- partitioning
model generates and calculates the proportion of each source utilized.
Both methods are important for a complete understanding of
δ18O and δ2H in the subalpine forest
examined.
Recently, several studies have analyzed the efficiency and adequacy of
using more complex mixing models, in particular the MixSIAR BMM package,
to answer questions similar to the aim of this study (Rothfuss &
Javaux, 2017; Wang et al. , 2019). Wang et al. (2019) found
that MixSIAR and SIAR had better source water appointment performances
due to inclusion of error terms and uncertainties associated with
varying isotopic compositions. Evaristo et al. (2017) discussed
uncertainties in different models and their proportion predictions. They
highlighted in a source water study like theirs, the BMM approach may
prove useful to quantify source water appointment, especially between
the vadose and saturated zones. BMM results in this study indicate that
between both tree species and age classes, subalpine trees switched
reliance on source water throughout the growing season, mainly between
the two subsurface compartments (saturated/ unsaturated). Numerous
studies have sought to understand physiological characteristics behind
tree water use in co-occurring fir and spruce subalpine forests
(Kaufmann, 1982; Boyce & Saunders, 2000; Sala, 2006; Andrus, Harvyem
Rodman, Hart & Veblen, 2018; Davis & Gedalof, 2018), but limited
studies have considered season long source water identification in Rocky
Mountain regions.
Species Differences and Water Use
Behaviours
Saturated soil water supplied via snowmelt is an important source,
primarily at the beginning of the growing season. This source
replenishes early season bound soil water supplies by increasing soil
moisture levels via an increased water table. Saturated soil water
levels then recede below a tree-accessible level after the snowmelt
period concludes. Towards the end of the growing season, nearing
senescence, both fir and spruce show increases in saturated soil water
isotope signatures, likely due to increased P levels slowly increasing
soil moisture stores and recharging saturated soil water at the end of
the growing season in 2017. Saturated soil water signatures differ from
P due to the extended residence time within the soil, allowing for
fractionation. Unlike the drought conditions of the summer, in which P
evaporated and transpired within a few days, increased amounts of P at
the end of the growing season allow for recharge in the saturated zone.
End of season snowfall also influenced source water proportions,
appearing isotopically distinct in tree xylem water. Bound soil water
was the most important water source for both subalpine tree species,
regardless of age class, although there were distinct differences when
examining species and tree age relating to source water proportion.
Overall, spruce were more reliant on bound soil water, with fir trees
using less bound soil water and utilizing more saturated soil water.
Interestingly, subalpine fir show greater levels of drought stress while
spruce are more resilient (Veblen, 1986; Kelsey et al. , 2018).
Observing seasonal water source partitioning of fir, it appears that in
the mid- season they retain, or store, more saturated soil water than
their counterparts. This highlights differences in physiology and
rooting structures between fir and spruce, with fir rooting deeper and
relying less upon vadose zone water compared to spruce. Fir and spruce
rooting systems vary extensively with dependencies on subsurface geology
and soil structure. Both species in subalpine environments more commonly
have shallow rooting systems, with deeper taproots more commonly in
well-draining deep soils (Alexander, 1987). Is it possible that with fir
being more abundant at the study location (70 % of population), their
rooting systems could be more established and reach deeper depths due to
successional dominance.
The summer growing season studied experienced drought with no saturated
soil water recharge during July and August. Soil moisture values are
half of the values observed the year before at the end of the growing
season. Despite small differences in source water spread, limitations in
bound soil water could affect both fir and spruce tree T, and long-term
health if there are successive summer drought seasons (Pataki, Oren, &
Smith, 2000; Adams et al. , 2009; Matyssek et al., 2009;
Tague, Keyn, & Christensen, 2009; Shafer, Bartlein, Gray & Peltier,
2015). Based on BMM results showing spruce placing more reliance on
bound soil water, spruce may show effects of drought stress before fir,
despite spruce having been observed to be a more resilient species in
past studies (Veblen, 1986). As indicated previously, this may be site
specific and based on the succession of species proportion, with fir
being the dominant species at this study location. Results also
highlighted different water source proportions with tree age, regardless
of species. Older trees, overall, tend to use more saturated soil water
compared to younger. A direct relationship is observed with rooting
depth and age, with younger spruce and fir typically displaying lateral
root spread and weak taproots (Alexander, 1987). These differing
behaviours may provide more physiological resilience to drought for
older subalpine trees, allowing them to use an additional water source.
Age and maturity also corresponds to increased storage, allowing trees
contain source signatures obtained earlier, throughout the length of the
growing season.
The three sampling periods were able to highlight the progression of
water uses; snowmelt finished and soil moisture stores lessened toward
senescence during the dry summer of 2017. The percentages developed also
indicate relative importance of these sources to the tree species
examined. Mid-summer, 71% and 79.5% of total xylem water for fir and
spruce, respectively, contained bound soil water signatures. Recent
studies examining the constraints on seedling and sapling growth in the
Rocky Mountain identified soil moisture as an important limiting factor
in successful establishment (Andrus et al. , 2018). In particular,
Davis and Gedalof (2018), found treeline advance and establishment of
co-occurring fir and spruce is unlikely considering earlier snowmelt and
longer snow-free growing seasons depleting soil moisture are expected to
become more frequent (Fang and Pomeroy, 2020). Hydrological conditions
of the growing season examined in this study were representative of
summer drought conditions, with no summer P recharging subsurface
storage. Only the first 30 cm of soil received percolated water before
being utilized by vegetation or evaporated within a few days (Figure 2).
Results showed younger trees relied upon soil moisture stores more than
their counterparts, who incorporated saturated soil water more into
their overall source use. These results, in conjunction with research
indicating poor success of sapling establishment and forest health with
lower soil moisture reliability (Cul & Smith, 1991; Harpold et
al. , 2014; Lazarus, Castanha, Germino, Kueppers, & Moyes, 2017; Andruset al. , 2018; Davis & Gedalof, 2018), could indicate younger
trees show more signs of stress in addition to potential die back if
drought conditions become more frequent in subsequent summer growing
seasons (Adams et al. , 2009). The ability of older trees to
spread their water source allocations differently, likely due to more
established rooting structures, may give them an edge in resilience to
less than favourable growing season conditions under a changing climate.
A growing season experiencing an extended snowmelt period due to a large
winter snowpack may help established subalpine forests experience less
drought stress by providing an extended saturated soil water source for
longer, despite drought conditions occurring later in the summer, such
as in 2017. This was evident in the MixSIAR model results, with
saturated soil water signatures being maintained throughout the entire
growing season despite the saturated soil water depletion after snowmelt
(after the pre- sampling period).
Conclusions
The aim of this study was to understand and partition subalpine forest
water sources during a growing season experiencing a drought period in
the Canadian Rockies. Development of an isotopic framework, LMWL, and
LEL were integral to the successful identification of tree water
sources. The LMWL was generated with an R2 value of
0.99, indicating a successful relationship and potential for use in
future δ18O and δ2H stable water
isotopes studies occurring on the eastern slopes of the Rocky Mountains.
Subsequent use of the MixSIAR BMM with source and xylem water samples
provided an understanding of water use behaviour at three points
throughout a growing season at 2100 m of elevation.
Tree species and age both displayed differences in water source
allocations, although all categories placed a higher reliance on bound
soil water. Saturated soil water supplied by snowmelt was highlighted as
an important source during the beginning of the growing season, and
closer to the end of the growing season with increased P in the fall.
Results highlighted the importance of soil moisture reserves to the
health of subalpine forests, and shed light upon future behaviours
should years of successive drought periods occur. These findings support
established literature that have indicated future success of
co-occurring fir and spruce forests could be limited should soil
moisture stores decrease. This moisture limitation has the ability to
limit tree line advance to higher elevations, which has the potential to
further limit forest population growth as valley bottoms experience die
backs with faster rates of change due to higher baseline temperatures
than the alpine. Successionally, sub-alpine forests could be nudged off
balance as older trees, able to utilize deeper groundwater, will have a
higher survival rate compared to their counterparts who may experience
increased levels of drought stress. Although soil moisture was
determined to be the most important source, extended snowmelt periods
supplied by large winter snowpacks could offset summer droughts by
supplying subalpine forests with an additional source for a limited
period of time. Extended growing seasons with rising temperatures could
cancel this effect, as trees will need to rely on soil moisture stores
for longer periods of time. A multi-year δ18O and δ2H stable water
isotope study could help provide further understanding of these
co-occurring subalpine forests under hydrologically variable mountain
growing seasons. Thus, this work suggests that two water worlds do not
exist as permanent distinct, isolated sources of water in this
environment, but that moisture in natural vegetated systems is really
just a gradient between water held under high (soil moisture) to low
tension (saturated soil water) and so the water worlds are more
endpoints on a gradient than distinctive reservoirs. Results here show
that trees can draw on both endpoints depending on season and
availability or antecedent and climatic conditions.