HESSHydrology and Earth System SciencesHESSHydrol. Earth Syst. Sci.1607-7938Copernicus PublicationsGöttingen, Germany10.5194/hess-20-2745-2016A post-wildfire response in cave dripwater chemistryNagraGurinderg.nagra@unsw.edu.auTreblePauline C.https://orcid.org/0000-0002-1969-8555AndersenMartin S.FairchildIan J.ColebornKatieBakerAndyhttps://orcid.org/0000-0002-1552-6166Connected Waters Initiative Research Centre, University of New South Wales, Sydney, NSW, 2052, AustraliaInstitute for Environmental Research, Australian Nuclear Science and Technological Organisation, Lucas Heights, NSW, 2234, AustraliaSchool of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UKGurinder Nagra (g.nagra@unsw.edu.au)21July2016207274527583January201619January201610May201619June2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://hess.copernicus.org/articles/20/2745/2016/hess-20-2745-2016.htmlThe full text article is available as a PDF file from https://hess.copernicus.org/articles/20/2745/2016/hess-20-2745-2016.pdf
Surface disturbances above a cave have the potential to impact cave
dripwater discharge, isotopic composition and solute concentrations, which
may subsequently be recorded in the stalagmites forming from these
dripwaters. One such disturbance is wildfire; however, the effects of
wildfire on cave chemistry and hydrology remains poorly understood. Using
dripwater data monitored at two sites in a shallow cave, beneath a forest,
in southwest Australia, we provide one of the first cave monitoring studies
conducted in a post-fire regime, which seeks to identify the effects of
wildfire and post-fire vegetation dynamics on dripwater δ18O
composition and solute concentrations. We compare our post-wildfire
δ18O data with predicted dripwater δ18O using a forward
model based on measured hydro-climatic influences alone. This helps to
delineate hydro-climatic and fire-related influences on δ18O.
Further we also compare our data with both data from Golgotha Cave – which
is in a similar environment but was not influenced by this particular fire – as
well as regional groundwater chemistry, in an attempt to determine the
extent to which wildfire affects dripwater chemistry. We find in our
forested shallow cave that δ18O is higher after the fire relative
to modelled δ18O. We attribute this to increased evaporation
due to reduced albedo and canopy cover. The solute response post-fire
varied between the two drip sites: at Site 1a, which had a large tree above
it that was lost in the fire, we see a response reflecting both a reduction
in tree water use and a removal of nutrients (Cl, Mg, Sr, and Ca) from the
surface and subsurface. Solutes such as SO4 and K maintain high
concentrations, due to the abundance of above-ground ash.
At Site 2a, which was covered by lower–middle storey vegetation, we see a
solute response reflecting evaporative concentration of all studied ions
(Cl, Ca, Mg, Sr, SO4, and K) similar to the trend in δ18O
for this drip site. We open a new avenue for speleothem science in
fire-prone regions, focusing on the geochemical records of speleothems as
potential palaeo-fire archives.
Introduction
Caves are observatories, that preserve invaluable geochemical archives of
past-climates; in the form of speleothems (stalagmites, stalactites and
flowstones). The existing paradigm in speleothem science has largely focused
on establishing palaeoclimate proxies in stalagmites (e.g. McDermott et al.,
2001; Treble et al., 2008; Woodhead et al., 2010). While these proxies are
useful for reconstructing palaeoclimates, their interpretations may hold a
predisposed bias towards using these proxies as indicators of palaeoclimate only.
To avoid this bias, we need to consider the sensitivity of these proxies to
the effects of local environmental factors like in our case, fire. This is
especially important as incorporating this perspective may not only be used
to correct the climate proxy interpretation, but also yield novel
information about palaeo-environments. Palaeo-environmental proxies are
verified by conducting process-based in-cave monitoring studies. However,
in-cave monitoring has predominantly focused on understanding the extent to
which dripwater δ18O (Lachniet, 2009), dripwater solute concentrations
(Fairchild and Treble, 2009), speleothem calcite growth (Wong et al., 2011), and cave CO2
processes (Breecker et al., 2012), are affected by climate. Further, such
studies have largely been restricted to mid- to high latitude climate regions
where precipitation (P) is larger than actual evapotranspiration (AET), and
climate is likely to be a major control on dripwater composition.
In water-limited regions, dripwater chemistry is influenced to a greater
extent by environmental factors such as evaporation (E) (Pape et al., 2010;
Cuthbert et al., 2014; Rutlidge et al., 2014) and transpiration (T),
(Tremaine and Froelich, 2013; Treble et al., 2016). Wildfires, common in
water-limited regions, are agents of change that can dramatically alter
evaporation and transpiration rates by destroying vegetation. The potential
impacts of vegetation loss from fire are both short-term and long-term. The
short-term impacts could include (1) an increase in evaporation rates due
to changes in albedo and/or lack of shading (Silberstein et al., 2013);
(2) a reduction in transpiration from reduced tree water use; (3) a reduction in
soil microbial and root CO2 production (Coleborn et al., 2016); (4) a
decrease in cave CO2 due to the destruction of vegetation (Wong
and Banner, 2010), which could influence in-cave prior calcite
precipitation (PCP); (5) the addition of plant ash to the soil profile,
increasing concentrations of Ca, K, Mg, and S (Grove et al., 1986; Yusiharni and
Gilkes, 2012a); and (6) altered infiltration patterns (González-Pelayo et al., 2010). The long-term
impacts include (1) the spatial redistribution of nutrients (Abbott and
Burrows, 2003); (2) regrowth impacts on water balance and nutrient flux
(Treble et al., 2016); and (3) a reduction in total soil CO2 due to the
destruction of CO2 sequestering microbial communities and plant roots,
both significant sources of soil CO2 (Coleborn et al., 2016). Despite
the fact that wildfires regularly affect water-limited regions, their
impacts on δ18O and solute concentrations in cave dripwater
have not been reported.
We analyse the composition of cave dripwater over 5 years (August 2005–March 2011)
of cave monitoring in Yonderup Cave, a shallow cave system, in
southwest Australia. Our monitoring followed an intense wildfire in February 2005
that burnt 1200 ha of Yanchep National Park. The fire was hot enough to
calcine and fracture the limestone observed at the caves entrance
(Fig. S1 in the Supplement). We compare our monitoring data to the regional
groundwater geochemistry and published monitoring data (Treble et al., 2015)
from Golgotha Cave in southwest Australia (lat. 36.10∘ S,
long. 115.05∘ E). Our analysis provides one of the first analyses of the
response of dripwater δ18O and solute concentrations to
post-wildfire conditions in shallow caves located in the tree rooting zone.
Geographical location of our study site (a), a post-fire
photograph of the area (b) taken in August 2005 (a photo of recovering shrubs
and grass post-wildfire), and (c) a map of Yonderup cave to scale originally
surveyed by Watts and Henley (1973).
Site description
Our study was conducted in Yonderup Cave in Yanchep National Park
(lat. 31.5475∘ S, long. 115.6908∘ E), 20 km north of Perth, southwestern
Australia (Fig. 1a). This region has a Mediterranean climate characterized
by dry hot summers and cold wet winters with a 25-year (1990 to 2015)
average annual surface temperature of 15.1 ∘C and rainfall of 664 mm
with 85 % of rainfall falling between May and October. Yonderup Cave is
located in the young Quaternary Tamala Limestone Formation, a porous,
partially lithified calcareous coastal dune sand. This karst process is said
to be “syngenetic” with karstification occurring simultaneously with
lithification of the host rock (Jennings, 1964; Fairchild and Baker, 2012).
Yonderup Cave is situated in a tuart forest (Eucalyptus gomphocephala), with mature tuart trees 30 m
high, and an understory of shrubs and trees standing 5–10 m high, Sheoak
trees (Allocasuarina fraseriana) ∼ 5–15 m high, and Balga trees
(Banksia attenuata, Banksia menziesii, Banksia grandis,
Allocasuarina fraseriana, Xanthorrhoea pressii). Tree roots are exposed
in the cave, both in the roof (fine roots), and cave floor (thick tap
roots). In February 2005, the area above the cave was burnt in an intense
wildfire (Fig. 1b; Department of Parks and Wildlife, personal communication, 2015),
substantially modifying vegetation above the cave including the death of
mature trees and complete removal of canopy and understorey.
Over the period of August 2005 to March 2011, two drip sites in Yonderup
Cave (Site 1a and Site 2a), were monitored for their chemical and
hydrological variations. These two sites are 22.8 m apart (Site 2a east of
Site 1a, ∼ 1 m slope towards the East), located at similar
depths below the surface (∼ 4 m) within the same chamber
(∼ 7 m height) and partially separated by a large boulder
fall-in. We use an existing cave survey to determine the location of each
cave drip site relative to the ground surface (Fig. 1c). A soil depth survey
was conducted within 5 m of each site (Table S3 in the Supplement), along with visual
vegetation/ground surface observations post-fire. Soil depths were measured
every metre with a dynamic soil penetrometer in north, south, east and west
directions and averaged soil depth above each site were calculated.
Site 1a, 30 m from the cave entrance, has a drip source within a large
cluster of soda-straw stalactites known as the “Wheatfield” (Fig. S2b).
This circular feature is approximately 1 m across and as it appears in
an otherwise very sparsely decorated part of the ceiling, suggesting that it
represents a focused flow path into the cave. The land surface above this
site is flat with 70 % coverage by shallow soil (average 124 mm thickness)
and the remaining surface is exposed bedrock (∼ 30 %). A tuart tree,
located directly above Site 1a, burnt and collapsed during the 2005 wildfire,
which resulted in the entire removal of canopy cover above Site 1a. No other
trees are close enough to provide shade on the surface above Site 1a.
In contrast, Site 2a situated 50 m from the cave entrance is in a highly
decorated part of the cave known as the “Cathedral” characterized by large
icicle shaped stalactites. Above Site 2a, the soil cover is thicker (200 mm)
and more homogenous with no bedrock exposure, and no trees directly above;
however, there is a partial canopy cover from adjacent trees ∼ 15 m away.
Data collection
Cave dripwater was collected from 1 L high-density polyethylene (HDPE)
collection vessels at two sites Site 1a and Site 2a between August 2005
and March 2011 (∼ 5.5 years) at approximately bi-monthly
intervals. The water was separated into three aliquots: two aliquots were
filtered with 0.45 µm mixed-cellulose filters into two 50 mL
polypropylene bottles for major and minor ion determination; the third was
stored with zero-headspace in a 12 mL amber glass bottle for stable
isotopes. All aliquots were refrigerated below 5 ∘C until
analysis. Anion concentrations (Cl and SO4) were determined using a
Dionex DX-600 ion chromatograph with self-regenerating suppressor on one
aliquot. The second aliquot was acidified to 2 % HNO3 in the
collection bottle and used for cation concentrations (Ca, K, Mg, Na, Si and
Sr) using a Thermo Fisher inductively coupled plasma atomic emission spectrometer (ICP-AES) ICAP7600 at the Australian Nuclear Science and
Technology Organisation (ANSTO) facility. An internal standard with
concentrations approximating the cave waters was included in each cation
batch to check for between-run reproducibility.
Dripwaters collected between August 2005 and May 2008 were analysed for
δ18O using isotope-ratio mass spectrometry (IRMS) at the
Australian National University (see Treble et al. (2013)
for method). The remaining dripwaters were analysed for δ18O
and δ2H at ANSTO using the cavity ring-down spectroscopy (CRDS) method. Additionally, as there was sufficient remaining
water in the stored aliquots analysed by IRMS for Site 2a, these were also
re-analysed using CRDS to obtain a complete time series for δ2H.
After January 2007 dripwater volume at Site 1a became insufficient to
collect all three aliquots. Collections of aliquots were prioritized in the
following order: (1) stable isotopes, (2) cations, and (3) anions.
At each cave visit for dripwater sampling, drip rates were manually recorded
using a stopwatch and the level of water accumulated in the bottles was
recorded to the nearest 100 mL. Weekly discharge was estimated using a drip
volume of 0.2 mL per drip (Collister and Mattey, 2008). When timing drip
intervals became impractical, only the bottle level was recorded. Thus, in
order to represent the data in common units we needed to use the Collister
and Mattey (2008) drip volume in order to convert all our discharge data into
volume data. We use both sets of measurements from the overlapping period to
convert volume to discharge for when direct measurements for drip interval
using the stop watch were lacking. The calculations are provided in the
supplementary info as excel sheets.
To distinguish dry and wet periods, we applied a residual mass curve (RMC),
(Hurst, 1951) to monthly P- AET data. The RMC is the cumulative sum of the
monthly anomaly calculated from the 22-year mean and used to generate a time
series of cumulative potential water surplus or deficit starting from
January 2000, highlights trends in above-average or below-average P- AET, we
refer to this calculation as cumulative water balance (CWB) throughout the
rest of this paper.
Unpublished monthly δ18O and δ2H rainfall data
(2005–2011) from Perth were obtained from ANSTO. We used modelled
regional precipitation (P) and actual evapotranspiration (AET/FWE is
the sum of soil evaporation and transpiration by vegetation based on
Priestly–Taylor equations) from the Australian Water Availability
Project (AWAP) (Raupach et al., 2009, 2011) with monthly parameters, to determine P- AET. AWAP
P, AET/FWE, and rainfall δ18O
data were then used as input to the forward model (detailed in the next
section) to predict cave dripwater δ18O composition under
various hydro-climatic scenarios. Predictions are based solely on P- AET
data, which are then compared to the dripwater observations.
Monthly rainfall δ18O and δ2H compositions were
amount weighted and fitted with a linear regression (Hughes and Crawford,
2012) and compared to the long-term groundwater mean obtained from Turner
and Thorpe (2001) and the cave dripwater to determine whether evaporation
has affected cave dripwater isotopic composition (see Sect. 4).
Post-fire solute and δ18O data from Yonderup Cave dripwater are
also compared to other relevant published data. These include, long-term
Perth rainfall δ18O from Turner and Thorpe (2001), and local
Yanchep rainfall solute data from Hingston and Gailitis (1976), and
published dripwater data from Golgotha Cave, located 300 km south of
Yanchep. Golgotha Cave has been monitored since 2005 (Treble et al., 2013;
2015, 2016; Mahmud et al., 2016). The climate at Golgotha Cave is also
Mediterranean, but receives annual mean rainfall of ∼ 795 mm, which is
23 % higher than Yanchep. Both caves are located within the Tamala
Limestone Formation; however, the caves vary in depths: Golgotha Cave is
significantly deeper than Yonderup ∼ 30–35 m. Golgotha Cave is
covered by a more extensive forest of mixed marri/karri
(Eucalyptus calophylla / Eucalyptus diversicolor) trees and this
site has not experienced an intense wildfire since 1992 and no prescribed
burns since 2006. We note, the prescribed burn at Golgotha Cave was much
less intense and it was more controlled than the fire that is reported in our study.
Forward model
We use the forward model employed by Baker et al. (2010). This model uses
monthly rainfall δ18O, monthly (P- AET) from 2003 to 2011
(we use 2003 to 2005 data as a “warm-up” period to avoid edge effects), and
adjustable bedrock flow thresholds for seepage flow and fracture flow to
predict dripwater δ18O based on hydro-climatic influences.
Seepage flow and fracture flow thresholds are hydrological P- AET
thresholds for the amount of infiltrating water that is required to enter seepage or
fracture reservoirs (for further details see Baker and Bradley, 2010). The
Tamala Limestone, retains high primary porosity thus seepage flow is likely
to be dominant, whereas fracture flow is less dominant and only likely to be
activated during high infiltration (Treble et al., 2013; Mahmud et al., 2016).
Water that enters the seepage reservoir is modelled as a Gaussian
distribution. A maximum residence time of 3 years is set; this reflects the
dominating seepage or matrix flow type at our site, the shallow depth (4 m)
and the potential for capillary barrier effects to impact hydrology in this
region (Mahmud et al., 2016). Further a minimum residence time of 10 months
is required, to maintain the observed year round discharge at both sites.
The model allows for the mean and standard deviation to be specified for
these functions. Being conservative we specify the minimum residence time of
10 ± 2 months. In contrast, the fracture-fed flow is
instantaneously passed through the system (i.e. with a travel time of less
than 1 month). In the model we can adjust the (P- AET) thresholds
required for flow into the seepage reservoir and the threshold required for
it to spill into the fracture flow. The seepage and fracture-fed components
are mixed in the overlying bedrock reservoir, before predicting dripwater
δ18O composition. By request the authors can supply the forward
model as a spread sheet.
We tested a full range of seepage and fracture possibilities. This suite of
model runs helps to place constraints on δ18O variability that
can be explained only by hydro-climatic variablity. We compare these
scenarios to the observed dripwater δ18O at our sites, to
assist in our interpretation of the post-fire dripwater δ18O response.
Results
A time series of monthly P- AET, CWB,
discharge, dripwater δ18O, and ion concentrations for Sites 1a
and 2a from August 2005 to March 2011 is shown in Fig. 2.
A post-fire time series of data from Site 1a and Site 2a.
Note: Site 1a dries up in June 2007. (a) Precipitation – actual
evapotranspiration (P- AET), shows seasonal variations of excess (above
threshold) and deficiency (below threshold) on a monthly scale overlayed
with cumulative surface water balance. (b) Discharge is given in mL week-1.
Actual measured discharge data are given in blue (Site 1a) and black (Site 2a)
while estimated data are given in red, which is then inferred to give
measured discharge. Site 1a shows a spike in measured discharge in August 2006
and a consequent decrease until the site is dry, while Site 2a shows
little variability in discharge throughout the monitoring period. (c) Shows
observed δ18O composition of cave dripwater from Site 1a and
Site 2a with the forward modelled δ18O (red), mean modelled
δ18O (orange), and long-term groundwater δ18O mean
(pink). (d) Cl declines at Site 1a until February where it shows a slight
increase until the drip becomes dry, while Site 2a shows a steady increase
until in July 2007 where it stabilizes for the remainder of the monitoring
period. (e) Post-fire response shows a decline in Mg at Site 1a until dry
and a steady increase at Site 2a until in December 2007 where it remains stable.
(f) Site 1a shows stepwise decline in Ca at Site 1a until dry, while at
Site 2a a very gradual increase until June 2007 is seen while the remainder
of the monitoring period remains steady. (g) Response for Sr shows Site 1a
declining and Site 2a peaking in December 2007; an identical response to Mg and
at both sites. (h) K post-fire at Site 1a shows high concentrations, triple
that of Site 2a but stable, while at Site 2a shows a slight increase over
time. (i) SO4 both Site 1a and Site 2a show a slight increasing trend
over time. But Site 1a has more than double the initial absolute concentration
in comparison to Site 2a, similar to other solutes.
Water balance
First, we observe a distinct seasonality in the water availability
(P- AET) (Fig. 2a), where winter months generate an excess (P> AET),
while summer months generate a deficit (P< AET). Further, CWB shows
three distinct trends throughout the monitoring period: (1) a decline over
the period of January 2006 to June 2006, consistent with very low excess in
P- AET; (2) an overall rise from June 2006 to February 2010; and (3) a decrease
in P- AET from February 2010 to September 2010. Sites 1a and 2a display
moderate and similar discharge rates, at the start of the monitoring period
that continue until July 2006; Site 1a has an average of 90 mL ± 21 mL per
week while Site 2a has an average of 92 mL ± 23 mL per week. This coincides
with the positive CWB (Fig. 2b). In July 2006, Site 1a
dramatically increased discharge 5-fold to 468 mL week-1 on one cave visit,
but decreased to 55 mL ± 3 mL per week on the subsequent visit 2
weeks later and was completely dry, 3 months later. This site has not
re-activated since (Department Parks and Wildlife, personal communication, 2015). Site 2a
shows much less variation in discharge overall, but contains smooth
long-term trends. Two periods of higher discharge are observed in August 2005
to May 2006 (average 92 mL ± 23 mL per week) and April 2008 to
February 2009 (average 93 mL ± 29 mL per week), both coincide with
positive trends in CWB.
Water isotopes
Dripwater δ18O from Site 1a (Fig. 2c) shows no seasonal pattern
but we see a steady increase of 1 ‰ to January 2007, then
a further steeper rise of 1.5 ‰ in June 2007, after which
the drip ceases. Dripwater δ18O from Site 2a presents an
overall increasing trend rising from -3 ‰to
+0.7 ‰ over the monitoring period with a 6-month
quasi-seasonal signal (∼ 2 ‰ range) that peaks in
cooler months (June to October) coinciding with infiltration from rainfall in wet months.
We hypothesize that the P< AET
environment in drier summer months isotopically enriches soil water, but
this only arrives at the cave when seepage thresholds are exceeded in
periods of P> AET (winter months).
Modelled dripwater δ18O outputs under varying
thresholds in our forward model (model from Baker et al., 2010) which
accounts for climatic and various epikarst threshold values that control
isotopic values. Given no output matches observed dripwater composition, we
can infer that a localized factor has influenced isotopic compositions.
We forward modelled our rainfall isotopic data in order to predict
drip-water δ18O under various hydro-climatic scenarios (Fig. 3).
Our sensitivity analyses of hydrological residence times and thresholds
showed that seepage residence times, less than 10 months resulted in the
seasonal cessation of dripwater, which is not observed at our sites.
Therefore, a minimum seepage residence time is required to match our
observations. Further, seepage threshold values greater than 40 mm (P- AET)
also resulted in the cessation of our drip site. Thus, seepage threshold
must be below 40 mm (P- AET) to match our observation. Next we varied the
fracture threshold between 15 and 1000 mm, the wide range reflecting our
uncertainty over this parameter. However, we know that seepage flow is
dominant at these sites (Mahmud et al., 2016). This suggests two things,
first, the seepage threshold is low, second, the threshold required for
water to “overflow” from the seepage reservoir to fracture reservoir must be
significantly higher than the seepage threshold. We note that scenarios with
a lower fracture threshold (10–15 mm) show high variability in comparison
to sites with a seepage dominated flow and no fracture flow (10–1000 mm).
Based on the variable morphology of stalactites and stalagmites at our sites,
we interpret discharge to be a combination of seepage and fracture flow, but
with seepage clearly dominating. Hence, we chose the 15–100 mm scenario to
represent the hydrology at our cave site (Fig. 3). Our forward-modelled
dripwater δ18O mean is -4.1 ‰, slightly
less than the mean of Perth rainfall (-3.1 ‰). The time
series of modelled dripwater δ18O (Fig. 2c) starts and remains
at ∼-4.2 ‰ until February 2006 where it
dips slightly before rising sharply to -3 ‰ where it
remains steady until February 2007. Here it begins a stepwise decline;
declining from February to March 2007 by 0.5 ‰ and
remaining stable again until February 2008. It then shows a further
steep decline in March 2008 to -4.5 ‰, where it remains
at approximately this value, albeit with a few small variations on
timescales of months, until the end of the monitoring period.
In all meaningful modelled scenarios, i.e. ones that have full-year flow and
test the full range of hydrological variability, estimated dripwater
δ18O cannot replicate the higher observed dripwater δ18O,
which are +1 to +3 ‰ higher compared to modelled δ18O (Fig. 3). This clearly suggests another factor is
affecting dripwater δ18O composition: likely near-surface evaporation.
Shows compositions of δ2H against δ18O
of our rainfall data (blue) during the monitoring period (ANSTO,
unpublished), cave dripwater (red), long-term local groundwater mean (black)
(0–10 ka, n= 43, southern Perth Basin from Turner and Thorpe (2001)),
and rainfall mean (red). A least squares regression (LSR) is plotted for
cave dripwater (red line) and falls close to the local meteoric water line
(LMWL, black), which is calculated using a weighted least squares regression (WLSR)
using Hughes and Crawford (2012).
To investigate an evaporation effect, we plot cave dripwater along the local
meteoric water line (LMWL; weighted least squares regression) to test for isotopic enrichment
(Fig. 4). Figure 4 shows that while the least squares regression (LSR) for
cave dripwater falls within the standard error (±0.45 ‰) of the slope for the LMWL (weighted LSR), dripwater isotopic composition is concentrated
towards heavier δ18O and δ2H. These results are
consistent with evaporation in a high humidity environment as has been
observed in semi-arid cave environments elsewhere (e.g. Cuthbert et al.,
2014). Adopting Cuthbert's classification, our data falls under a type 1 scenario
reported in Cuthbert et al. (2014). In the type 1 scenario, δ18O and
δ2H do not deviate from the LMWL but are shifted along the LMWL
towards higher values (Fig. 4). This means
that our data are similarly impacted by evaporation occurring in a high
humidity environment.
A summary table comparing the hydrogeochemistry of (a) shallow
Yonderup Cave drip sites burnt in a 2005 wildfire to (b) deeper Golgotha
Cave sites burnt in a 1992 wildfire and a 2006 prescribed burn;
(c) unpublished Perth rainfall data during the monitoring period (ANSTO);
(d) rainfall isotopic composition (Turner and Thorpe, 2001); (e) groundwater
isotopic composition (Turner and Thorpe, 2001); and (f) Yanchep rainfall solute
composition (Hingston and Gailitis, 1976). SD is standard deviation.
There are significant differences in solute concentrations and trends
between the two sites (Fig. 2e–h). Solute concentrations are
typically higher at Site 1a vs. Site 2a and they demonstrate opposite
trends post-fire. At Site 1a, Cl, Ca, Mg, and Sr decline overall, although
this trend is stepwise for Ca, and reverses for Cl ∼ 6 months
before the drip ceases. The trends in these solutes at Site 1a are
inconsistent with the decline in CWB during this period (Fig. 2a), as we would
expect a drying trend to reflect the evaporative concentration of
solutes. In contrast at Site 2a, Cl and other solute concentrations show a
direct relationship to CWB (i.e. increasing solute concentration with
decreasing CWB from 2006 to mid-2008 followed by decreasing solute
concentrations with increasing CWB).
Trends in SO4 and K are more subtle than for other solutes: at Site 1a,
K shows a slight decline from the beginning of the monitoring until early 2007
and then a small rise prior the drips ceasing. Although harder to
judge in the shorter SO4 time series, SO4 also shows a small rise
before drips cease, similar to K. Trends in K and SO4 for Site 2a are
more subtle, although they both increase slightly over time. K and SO4
concentrations are two to three times higher at Site 1a vs. Site 2a and
are considerably higher than those recorded at Golgotha Cave (Table 1). We
also note that initial Cl and other solute concentrations at Site 1a are
twice that at Site 2a.
DiscussionPost-fire hydrology
Discharge at Site 1a is inconsistent with CWB: discharge rose as rainfall
fell below the long-term mean (P< AET) (Fig. 2a and b), suggesting
that Site 1a received a localized increase in discharge despite the
declining input from rainfall. In contrast, discharge at Site 2a is more
closely related to the CWB, with higher discharge
coinciding with periods of higher water surplus and lower discharge with
lower water surplus.
Chloride is a chemically conservative and highly soluble solute (Graedel and
Keene, 1996), its concentrations in dripwater will therefore reflect
concentration/dilution effects (Tooth and Fairchild, 2003; Tremaine and
Froelich, 2013). Chloride concentrations at Site 2a increase during the
period of declining CWB (2006 to mid-2008) suggesting that evaporation is
concentrating Cl. Rising δ18O and other solutes over this
period are also consistent with increased evaporation. From mid-2008
onwards, when CWB is positive (P> AET), Cl decreases, consistent
with an increase in infiltration and thus dilution (Fig. 2e).
Summary of differences in mean concentration of solutes and
isotopic composition of solutes among sites at Yonderup and Golgotha caves.
We see that Cl, SO4, K, and δ18O values, at both sites are
distinctly different. Specifically, the solutes have higher concentrations
and δ18O is higher at Yonderup Cave in comparison to Golgotha Cave. SD is standard deviation.
Site differences DischargeCaMgSrClSO4Kδ18O(mL day-1)(mmol L-1)(mmol L-1)(mmol L-1)(mmol L-1)(mmol L-1)(mmol L-1)(mmol L-1)Yonderup site differences in mean Site 1a and Site 2a6.10.220.090.022.190.110.11.72Golgotha site differences in mean Site 1a and Site 1b230.1000.0000.0000.0600.0000.0030.200Site 1a and Site 2a160.1000.0200.0000.2900.0500.0180.200Site 1a and Site 2b220.0200.0300.0001.1400.0180.018–Site 1a and Site 2e4610.7000.0100.0190.7600.0050.018–Site 1b and Site 2a70.0000.0200.0000.6500.0500.0130.000Site 1b and Site 2b270.1200.0300.0001.0800.0180.013–Site 1b and Site 2e4840.8000.0100.0190.7000.0500.013–Site 2a and Site 2b200.1200.0100.0001.7300.0320.000–Site 2a and Site 2e4770.8000.0200.0191.3500.0450.000–Site 2b and Site 2e4570.6800.0100.0190.3800.0130.000–Average Gol. difference199.4000.3440.0160.0080.8140.0280.0100.133SD of Gol. difference220.9070.3310.0090.0090.4880.0190.0050.200
At Site 1a higher discharge also coincides with falling Cl concentrations
also suggesting dilution (Fig. 2b and d). However, we note this high discharge coincides with
a highly negative CWB, i.e. drier than normal conditions. This suggests in
this case, a non-climatic driver has influenced infiltration. We propose
that a reduction in localized transpiration, following the 2005 fire, may be
driving this. Deeply rooted trees within the area have been reported to
produce high Cl concentrations in the unsaturated zone (Turner et al.,
1987). Site 1a had a tuart tree directly above it and tree roots are visible
above Site 1a in the cave, but not at Site 2a. The proximity of the tree to
Site 1a is the most likely explanation for the higher solute concentrations
here (Treble et al., 2016). The death of the tree in the 2005 fires would
remove the previous transpiration demand and hence result in effective
dilution of the solutes during infiltration, as observed. Although, this
reduction in transpiration would have been abrupt but we observe a response
lasting 1.5 years after the fire. This delay could be due to a number of reasons;
first, the minimum residence time is 10 months (for a year of continuous
discharge) so a delay in the response is to be expected. Second, this
occurred during a period in which the soil moisture deficit would have been
larger than average, so a larger volume of cumulative infiltration would be
needed to overcome this deficit and move the more dilute solute into the cave.
It is also possible the decrease in concentrations reflect the diminishing
element concentrations after an immediate flush of the more soluble
ash-derived material (i.e. the tail of a solute pulse). However, post-fire,
highly soluble solutes like Cl, will still reflect dilution due to increased
discharge. So, it is likely that we are seeing a decline in these elements
due to a combination of the removal of these nutrients from the surface and
subsurface, as well as dilution.
In the broader context we look at the differences in Cl at Yonderup Cave vs.
Golgotha Cave. Both caves are ∼ 5 km from the coastline, so
they likely have a similar amount of Cl aerosol deposition. Yet, post-fire
Cl values at Yonderup Cave are more than double the Cl concentrations from
Golgotha Cave (Table 1). Further, within-cave variability in Cl
concentrations at Yonderup Cave are twice that at Golgotha Cave (Table 2).
While variations in vegetation density (along with wildfire history) may
have some role to play in the difference in mean dripwater Cl at each
location, the higher within-cave variability at Yonderup Cave (Table 2),
suggests a post-fire setting increases variability in dripwater chemistry.
The impact of this is discussed further and a conceptual model (Fig. 6)
devised later in Sect. 6.3.
(a) A time series of ln(Sr/Ca) vs. ln(Mg/Ca). Site 1a shows a
clear enrichment in Mg/Ca and Sr/Ca, or an increase in PCP, post-2007,
driven by evaporation. Site 2a, on the other hand, shows quasi-seasonal
variational in ln(Mg/Ca) and ln(Sr/Ca), suggesting here PCP is likely
dominated by seasonality. (b) Shows that at both sites, ln(Mg/Ca)
vs. ln(Sr/Ca), fall within the diagnostic range of PCP (a slope of + or
-0.88) suggesting PCP is occurring.
Post-fire carbonate chemistry
Similar to Cl, concentrations of carbonate metals (Mg, Ca and Sr) at Site 1a
also decrease; this reflects solutes being diluted due to reduced tree
water use. However, we note that at Site 1a, Ca, for example, declines twice
as much (in concentration, ∼ 75 %) in comparison to Cl (∼ 30 %).
Thus, for Ca another mechanism along with dilution is required to explain
its non-linear step-like decline (Fig. 2g).
There are a number of mechanisms that could influence post-fire Ca
concentrations. First, we consider increased near-surface evaporation
inducing prior calcite precipitation (PCP). Increased evaporation, can
saturate solutes relative to calcite in karstic waters and promote
degassing. Further, evaporation will slow the flow and increase water–rock
interaction times. Both of these conditions are ideal
for PCP. Both our sites show evidence of PCP: the ln(Sr/Ca) vs. ln(Mg/Ca)
slopes in our data agree with the diagnostic range for PCP (a slope of
+ or -0.88; Fig. 5b) (Sinclair, 2011). Expressed as a time series
(Fig. 5a), we see ln(Sr/Ca) and ln(Mg/Ca) increase simultaneously with
δ18O and Cl (Fig. 2), suggesting that evaporation is indeed the
common driving mechanism inducing PCP at Site 1a. For further
information on PCP processes we recommend the reader to Fairchild et al. (2000),
Sinclair (2011), and Treble et al. (2015).
Evaporation (red) increases post-fire at both sites due to a
reduction in albedo and vegetation cover, whereas precipitation (blue) remains
the same and initial transpiration (green) decreases, but recovers over
time. Site 2a shows higher δ18O and an increase in
concentrations of solutes including SO4 and K (lime) due to
evaporation and slow increase in transpiration due to vegetation recovery,
with cumulative water balance (CWB) remaining the same. While Site 1a shows
higher δ18O in response to increased evaporation and a decline
in solute concentrations in response to increased discharge and a decrease
in transpiration and removal of nutrients from the surface and subsurface.
However, since SO4 and K are from biomass-sourced ash, the tuart tree
above this site acts as a source of increased SO4 and K. Discharge
increased immediately (blue). But the drip became inactive 1 year after
the fire due to an increase in evaporation, which outweighed the reduction
in transpiration (green), leading to depletion of the near-surface reservoir
feeding Site 1a and an inactive drip site.
A second mechanism influencing post-fire Ca concentrations may be the
addition of plant ash (Yusiharni and Gilkes, 2012a) and highly soluble CaO
(produced by the burning of exposed surface rock to the fire; Yusiharni and
Gilkes, 2012b). Further, it is possible that the Ca decline may also reflect
a decrease in Ca being leached post-fire that may have followed an earlier
spike in Ca concentrations from the above. The extent to which each process
is affecting the Ca concentration is difficult to assess in our data,
especially since our monitoring did not commence until 6 months after the
fire, and processes such as PCP and the addition of Ca from plant ash are
difficult to constrain.
We now consider other carbonate metals (Mg and Sr) at Site 1a to further
constrain our interpretation. We find Mg and Sr decline by
∼ 30 % (in terms of relative concentration). Thus, it is likely that the same
process affecting Cl is also affecting Mg and Sr, i.e. dilution, a
decline in leaching of biomass-sourced ash, or some combination of both. Ca
concentrations decline by a relatively larger amount (75 %) suggesting
that additional processes are specifically affecting Ca. The rise in Mg/Ca
at Site 1a strongly suggests that the remaining portion of the Ca decline
may be attributed to PCP (Fig. 5a).
At Site 2a, a rising trend, reflects the concentration of solutes due to a
rise in post-fire evapotranspiration, evidenced by increasing
δ18O and Cl, evaporation of near-surface water stores (Fig. 2f–h), and possibly, to some extent, an increase in transpiration
from vegetation recovery for Cl (Treble et al., 2016). Additionally, Ca
concentrations also show a quasi-seasonal response, interpreted from the
Mg/Ca time series to be driven by PCP, possibly due to seasonal P- AET
(supported by similar seasonality in dripwater δ18O; Fig. 2c)
although in-cave PCP could also be contributing (Treble et al., 2015).
Sulfate and K post-fire at Site 1a are abnormally high in concentration,
approximately 3 times higher in comparison to Site 2a (Fig. 2h and i;
Tables 1 and 2). This is counterintuitive to the initial dilution signal
(owing to a decrease in tree water use) interpreted for the other solutes.
While at Site 2a, SO4 and K increase similar to other solutes,
consistent with evaporative concentration (from post-fire conditions) and an
increase in transpiration (from vegetation recovery). These observations
suggest that there was an increase in the availability of SO4 and K
after the fire at Site 1a despite a decrease in tree-water use here (Fig. 2h and i).
We note the majority of above-ground SO4 is predominantly stored within
the lower to middle storey of the forest (O'Connell and Grove, 1996), and
post-fire soils contain 23 % more S and 16 % more K than pre-fire soils
due to biomass-sourced ash deposition (Grove et al., 1986). Therefore, SO4
and K concentrations at each site may respond differently since the amount
of available SO4 and K above each site is influenced by the amount of
biomass burnt above the site. Further, the dissolution rates of ash minerals
containing these elements could also affect the rate at which these
nutrients are leached from the surface and subsurface and subsequently their
concentrations in dripwaters. We propose that the large amount of biomass
burnt above Site 1a – the tuart tree – is responsible for the much higher
concentrations of SO4 and K at Site 1a dripwater relative to Site 2a.
We also propose that the increase in near-surface evaporation from 2007
onwards drives even higher concentrations of SO4 and K (Fig. 2h and i).
Site 2a, which has much less pre-fire biomass, has much lower SO4 and
K concentrations, consistent with our argument. Here, these solutes show a
steady increasing trend over the monitoring period. This is consistent with
increased evapotranspiration post-fire, which is also evident in the other solutes.
Now, we compare our Yonderup Cave results to those of Golgotha Cave to put
SO4 and K concentrations into context. Golgotha Cave, last experienced
a wildfire in 1992 and a controlled low-temperature prescribed burn in 2006,
while Yonderup experienced a high intensity burn in 2005. First, we
see 5 and 10 times higher within-cave differences in SO4 and K
(respectively) at Yonderup Cave than we do at Golgotha Cave (Table 2). Also,
concentrations at Yonderup Cave are up to 4 and 3 times higher in
SO4 and K, respectively, at Yonderup Cave than at Golgotha Cave (Table 1).
These results coupled with the difference between Cl compositions at
Yonderup vs. Golgotha presents a clear case for more variability in burnt
sites in comparison to unburnt sites.
A multi-proxy fire signal in dripwater
Here we propose post-fire scenarios for both sites at Yonderup Cave (refer
to conceptual model Fig. 6) that account for the altered dripwater chemistry
that is observed post-wildfire. A straight-forward relationship between
CWB, discharge, and Cl concentrations at Site 2a
suggests increased concentration of solutes (Ca, Mg, Sr, K, and SO4) in
response to an increase in near-surface evaporation (Fig. 2c and d).
In contrast solutes such as Cl, Mg, Sr, and Ca at Site 1a show a declining
trend. We have argued that this declining trend in these solutes is due to
two underlying processes. First, a decrease in tree water use
(transpiration) due to the death of the tuart tree in the wildfire. Tuart
trees are deeply rooted, having adapted their root systems to access water
from both the surface and subsurface. These roots have been found to
generate potential energy between the tree and the soil to extract water and
nutrients. Specifically, mature tuart trees generate a pressure gradient
ranging from -0.86 ± 0.11 MPa (summer) to -0.35 ± 0.02 MPa
(winter) (Drake et al., 2011). So the death of the tuart tree in the
wildfire had a significant local effect on hydrology at Site 1a resulting in
an increase in discharge and dilution of solutes (Cl, Mg, Sr, and Ca). Our
study suggests that the consequent reduction in transpiration may not be
immediately detected in dripwater, owing to transit time through the
limestone and the requirement for overcoming a soil moisture deficit during
drier than average climatic conditions. Hydrological effects, such as
“capillary barriers”, can also slow down vertical transport of infiltrating
waters at our site (Mahmud et al., 2016).
Second, the decline in solutes at Site 1a could be the result of a gradual
return to pre-fire concentrations following a pulse of increased input of
solutes from ash (e.g. Site 1a scenario). A contribution of SO4 and K
from burnt biomass may explain their relatively high concentrations.
Further, isotopic composition at Site 1a shows that δ18O is
offset from modelled hydro-climatic δ18O by
∼+1 ‰ suggesting increased near-surface evaporation
post-fire, which we attribute to the reduction of shading from the tuart tree
post-fire – even in P> AET periods (Fig. 2c); post-2007,
when P< AET conditions arrive, δ18O rises even higher
and discharge declines. Eventually, due to the persistent duration of
P< AET conditions, Site 1a ceased dripping owing to eventual depletion
of the near-surface reservoir feeding this drip.
Site 2a also shows higher δ18O during the post-fire period,
which we attribute to an increase in near-surface evaporation as a result of
low albedo and reduced vegetation cover. The case for evaporation at this
site is supported by the rise in Cl and other solutes. The possibility of an
immediate spike in solutes from ash and a long-term decline from leaching,
as was discussed for Site 1a, is limited here, as there was less biomass
available to burn above Site 2a. Therefore, we interpret increased
evaporation and transpiration from regrowth post-fire to be the dominant
forcing at this site, similar to the findings of Treble et al. (2016).
We propose that differences in surface vegetation above sites can influence
site specific drip chemistry. For example, we interpret Site 1a was
influenced by a reduction in transpiration after the fire, due to the
forcing biomass above the site, which may also have been a source of
post-fire ash at this site. At Site 2a the response to the fire was
primarily an increase in near-surface evaporation owing to changes in
surface albedo. This variability within the cave response at Yonderup Cave
is significant, so too is the comparison between Yonderup Cave drip
chemistry and the drip chemistry at Golgotha Cave. The latter more generally
highlights that an intense wildfire has variable yet multi-year effects on
dripwater composition in shallow caves.
From this we propose that post-fire condition persist up-to 5–10 years'
post-fire, affecting dripwater δ18O and solute concentrations.
We would expect a full recovery, of δ18O and solute
concentrations back to pre-fire levels within 10–20 years as a result of
revegetation growth (Treble et al., 2016) and re-establishment of vegetation
cover and pre-fire albedo.
Application for a speleothem palaeo-fire signal
Our post-wildfire dripwater response from δ18O was a
2 ‰ increase above that predicted by a hydro-climatic
model, and measured regional groundwater and Golgotha Cave δ18O
data. If this signal is preserved at equilibrium in speleothems this is
equivalent to some of the largest interpreted climatic changes seen in the
Quaternary record. This highlights the significance of the findings in our
study, which suggests a fire signal could in fact be misinterpreted as
climate variability. Furthermore, the impact of the decrease in Ca
dissolution from the limestone bedrock could have a significant effect on
speleothem growth rate.
However, before attributing δ18O and growth rate abnormalities
to fire, we must remember there are a number of processes that effect
speleothem δ18O. Thus, it is important that a multi-proxy
approach, which uses isotopic composition as well as a suite of trace
elements (sourced from both soil and bedrock), is used to separate fire from
other forcings such as climate and other local factors. Further, our study
was conducted in a shallow cave environment, where perhaps the overlying
vegetation can exert a more dominant forcing on dripwater hydrology and
chemistry relative to deeper caves. Deeper caves have more complex hydrology
(McDonald and Drysdale, 2007); this involves mixing
with other flow paths, which are possibly not fire affected. This may result
in the smoothing of the fire signal; making it harder to isolate. Further, a
fire signal in cave dripwater and stalagmites may be much subtler in
a grassland environment in comparison to a forested environment as changes in
the biomass would be smaller and vegetation recovery presumably faster
(Coleborn et al., 2016). We recommend searching for fire signals in shallow
cave environments in the tree rooting zone in forested areas.
One further approach that may help to differentiate fire and climate signals
in a stalagmite would be to use multivariate statistical techniques such as
principal component analyses (PCA). Using this technique, we would expect
one component to reflect a bedrock/hydro-climatic signal and another to
preserve a local soil/vegetative forcing. The soil/vegetative component
could preserve the impact of a fire on stalagmite composition, in trace
elements like S and K. Further, it is also possible an immediate spike in
solutes (Mg, Ca, Cl, Sr, S, K, and P) from post-fire ash may be preserved in
stalagmites and colloid-associated metals, such as Al, Fe, and Cu from an
increase in discharge post-fire. Future studies of this kind will open a new
avenue in speleothem research: speleothems as archives of palaeo-fire.
Conclusions
We isolate a post-wildfire response by comparing a recently burnt cave
monitoring site with forward modelled δ18O, which predicts
δ18O based on hydro-climatic factors, and nearby cave
monitoring and groundwater data. We provide a novel analysis of the
multi-year impacts wildfire has on cave dripwater. Our analysis shows a
strong hydrologic relationship between surface environments and shallow
caves that are located within the tree rooting zone. This finding is
especially important in water-limited environments (P< ET) as the
overlying vegetation can exert controls on the cave hydrogeochemical environment.
A post-wildfire dripwater response is clearest in δ18O and Cl
due to their sensitivity to variation in near-surface evaporation (both
δ18O and Cl) and transpiration (Cl). Cl is a conservative ion
and hence is driven mainly by dilution/evaporation. Cl declines post-fire
at Site 1a, which we interpret as dilution of the water store that the dead
tree previously exploited. In contrast, Cl increases at Site 2a,
sympathetically with δ18O, consistent with an increased
evaporative demand on shallow water stores driven by post-fire reduction in
shading and reduced albedo. SO4 and K are also important at sites
with abundant biomass as they can be leached at high concentrations because they are
made more abundant in post-fire soils due to the ash generated from a fire.
Other solutes such as Mg, Sr, and Ca support the dominant local forcing at
the site post-fire and can be extremely powerful when using a multi-proxy approach.
We propose a conceptual model for a multi-year post-wildfire cave dripwater
response in forested water-limited regions. This involves a 5–10-year
response of (1) higher δ18O and Cl in cave dripwater due to
increased evaporation and decreased shading after the wildfire; (2) increased
K and SO4 due to the leaching of biomass-sourced ash, particularly in
areas with large biomass; and (3) increased variability in Mg, Sr, and Ca due
to changes in evaporation, transpiration and water–rock interactions
post-fire. We may expect a recovery within 10–20 years after the wildfire
and a return to to pre-fire isotopic and trace element concentrations as a
result of increased bio-productivity from forest regrowth and a re-establishment
of canopy cover.
The Supplement related to this article is available online at doi:10.5194/hess-20-2745-2016-supplement.
Acknowledgements
Many thanks must go to the team at Yanchep National Park, especially Ciara McDuff,
Rob Foulds, and Gary Hunton for your assistance with the data
collection. We also acknowledge ANSTO staff: Alan Griffith (AWAP data
access), Suzanne Hollins for permission to use unpublished Perth rainfall
isotopic data, Henri Wong, Scott Allchin, and Barbora Gallager for dripwater
analyses, as well as Michael Gagan and Joan Cowley for assistance with water
isotopes at ANU. This research was in part funded by ARC Linkage LP13010017
and Land & Water Australia grant (ANU52) to Pauline C. Treble. The outcomes of this
study contribute to ARC Discovery Project DP140102059 awarded to Pauline C. Treble. This
research was also supported by the AINSE honours scholarship program awarded
to Gurinder Nagra. Finally, we also thank the three anonymous reviewers for their
constructive questions and suggestions.
Edited by: A. Butturini
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