Introduction
In continuously eroding landscapes, the mass loss of particles by erosion and
solutes by drainage needs to be balanced over a ∼ ka timescale by the conversion of rock into regolith, where we define
regolith as the entire weathering zone above bedrock, including topsoil. The
advance of the weathering front at depth is thus coupled to surface
denudation (Brantley and Lebeveda, 2011). It has been hypothesised that
biotic processes contribute towards this coupling (Brantley et al., 2011). If
the nutrient demand of plants and soil microbes is linked to the advance of
the weathering front, investigating the dependence of nutrient fluxes on the
weathering regime allows for a test of this “biogenic weathering”
hypothesis.
The way weathering systems operate can be characterised by two endmembers,
each associated with a specific pattern of nutrient dynamics. In the
supply-limited regime, the transfer of nutrient-bearing mineral grains from
rock into the regolith is so slow that their complete dissolution makes the
mineral nutrient status of the regolith very low, such that plants and soil
microbes are rather nourished by recycling of nutrients extracted from plant
litter (Lang et al., 2016; Vitousek and Farington, 1997) and by atmospheric
inputs (Vitousek and Farington, 1997). In the kinetically limited regime,
erosion rejuvenates the regolith (Porder et al., 2007), such that the rate
of supply outpaces the weathering of minerals (West et al., 2005). In the
kinetically limited system, the supply of solutes by chemical weathering
into soil solutions ensures that nutrients are readily available for plant
uptake from regolith water, and a fraction of these nutrients is lost after
bio-utilisation in plant debris such as leaf litter and coarse woody debris
(CWD). The plant litter can also be “re-mineralised” (meaning oxidation of
plant litter), so that nutrients are lost by drainage in the dissolved form.
If erosion of plant debris outpaces nutrient leaching, nutrients are eroded
in leaf litter by erosion or stochastically as woody matter in landslides.
To replace either loss, nutrients should be uplifted from subsoil layers
(Jobbagy and Jackson, 2001; Bullen and Chadwick, 2016). To facilitate the
uplift from subsoil in the kinetically limited regime, plants and soil
microbes could stimulate chemical weathering rates by decreasing the
rhizospheric pH through respiration and excretion of weathering agents
(Brantley et al., 2011). Moreover, the symbiosis of roots with mycorrhiza
fungi (Landeweert et al., 2001) could enable plants to directly assimilate
nutrients from primary minerals (Jongmans et al., 1997). Here we explore
this set of hypotheses in a kinetically limited mountain setting using
isotopic and geochemical techniques.
The stable isotopes of magnesium (Mg) – a macronutrient for plants
(Marschner, 2011) and a major constituent of the bulk silicate Earth – are
suited to trace these cycles. Unless the formation of secondary minerals is
significant (Wimpenny et al., 2014), the main shift affecting the
26Mg / 24Mg ratio in weathering systems is the isotopic
fractionation towards high ratios during nutrient uptake by plants (Black et
al., 2008; Bolou-Bi et al., 2012; Mavromatis et al., 2014), such that the
residual dissolved Mg is shifted towards the complementary low ratio. These
two isotopically distinct compartments will remain separated if a fraction
of the Mg accumulates in wood of a regrowing forest after clear cutting or
if a fraction of the Mg is eroded after utilisation and is not released back
into solution. In that case the isotope ratio serves as a proxy for the
catchment-wide net nutrient uptake flux, where “net” excludes dissolution
from biomass and recycling. Here we use an isotope mass balance model
(Bouchez et al., 2013) to quantify the relative fluxes of Mg transfer in the
ecosystem after Mg release by rock weathering: uptake into plants, export as
solute or erosion in particles including minerals and a substantial CWD
fraction at three forested headwater catchments.
Methods
Study site
Our study sites comprise three catchments at Providence Creek, Sierra
Nevada, USA, and are part of two monitoring programs: Kings River
Experimental Watersheds (KREW) and Southern Sierra Critical Zone Observatory
(SSCZO). The extensive monitoring dataset is highly suited for nutrient
cycling studies in forest ecosystems and provides evidence that rock
phosphorus (P) might be growth limiting (Hahm et al., 2014). Our study sites
are underlain by granodiorite bedrock (Bateman and Wones, 1972) and mantled
by weakly developed soils comprising entisols and inceptisols (Bales et al.,
2011). The main vegetation cover is Sierran mixed conifer comprising Pinus ponderosa,
Pinus lambertiana, Abies concolor and Libocedrus decurrens (McCorkle et al., 2016).
Soil water and stream water pH ranges from 5.5 to 7. We estimate the soil
production rate from the total denudation rate from cosmogenic nuclides,
which is ∼ 220 t km-2 yr-1 (Dixon et al., 2009).
This weathering regime is kinetically limited and soils are only partially
depleted in mineral nutrients. Concerning dust inputs, Aciego et al. (2017)
recently suggested that P supply by dust deposition outpaces local
bedrock-derived P supply at the SSCZO for ecosystems developed over P-poor
bedrock. However, estimates of the influence of dust inputs on nutrient
dynamics are minor compared to the total denudation rate at our sites, with
inputs of 3 to 36 t km-2 yr-1 (Aciego et al., 2017). Importantly,
the total denudation rate of 220 t km-2 yr-1 (Dixon et al., 2009)
measured at this site is higher than the range of denudation rates of
103–175 t km-2 yr-1 used in Aciego et al. (2017), and the P
bedrock concentrations are higher in the Providence catchments studied here.
We excluded the catchment comprising P-poor bedrock at site D102 (Duff
Creek). The ratio of elemental dust deposition to the local,
bedrock-derived elemental supply flux (referred to as RPX in the
following) amounts to less than 4 % for K, Ca and Mg and to 5.3 % for
P at our sites and agrees with data shown in Aciego et al. (2017) for the
P-rich bedrock. Therefore, the atmospheric supply flux of mineral nutrients
can be considered to be insignificant relative to the local long-term supply
fluxes from weathering.
Analytical methods
The chemical composition of soil, saprolite and rock samples were analysed by
X-ray fluorescence spectrometry (XRF, Panalytical Axios Advanced) on fused
tablets at GFZ Potsdam or by Acme Labs, Canada, with uncertainties better
than 10 % relative. Additional concentration data were compiled from Hahm
et al. (2014) and Riebe and Granger (2013). Element concentrations in plant
material were analysed by an inductively coupled plasma optical emission
spectrometer (ICP-OES, Varian 720ES) with uncertainties better than 15 %,
after complete dissolution in HNO3/H2O2 in PFA vials on a
hotplate or using a microwave digestion system as successfully applied in
previous Mg isotope studies (e.g. Bolou-Bi et al., 2012). Dissolved element
concentrations in water samples were analysed by ICP-OES following the
procedure described in Schuessler et al. (2016), inductively coupled plasma
quadrupole mass spectrometry (Q-ICP-MS, Thermo iCAP-Q) and ion chromatography
(Thermo Dionex DX-120) with uncertainties better than 10 %, respectively.
All data of samples and reference materials (for assessment of analytical
uncertainties) are reported in Tables S1, S2 and S3a–c in Uhlig et
al. (2017).
Mg isotope analyses by MC-ICP-MS
Mg stable isotope analyses have been performed at GFZ Potsdam, Helmholtz
Laboratory for the Geochemistry of the Earth Surface (HELGES). Samples and
reference materials were digested in PFA vials using ultra-pure acid
mixtures (HF, HCl, HNO3, H2O2). The exchangeable Mg fraction
of soil and saprolite samples was obtained by a 1 M NH4OAc extraction
(Arunachalam et al., 1996). This procedure was specifically tested for Mg
isotope measurements (Bolou-Bi et al., 2012). After extraction, the residual
solids were analysed after HF/HNO3 total digestion. Before isotope
analysis, Mg was separated from other matrix elements by column
chromatography (AG50W-X12 resin) following the procedure described in Pogge
von Strandmann et al. (2011). Matrix elements were eluted with 1 M
HNO3, and then Mg was collected by elution with 2 M HNO3. Purity
of the Mg solutions as well as Mg yields were verified by analyses of final
Mg-containing solutions using ICP-OES or Q-ICP-MS. Mg isotope ratios were
measured with a multicollector inductively coupled plasma mass spectrometer
(MC-ICP-MS, Thermo Neptune). All sample solutions were diluted in 0.3 M
HNO3, where the sampled Mg concentration was closely matched to those
of the bracketing standard DSM-3. Results are expressed as the
‰ difference of the Mg isotope ratio of the sample
relative to the DSM-3 isotope reference material (Galy et al., 2003) using
the delta notation: δ26Mg = [(26Mg / 24Mg)sample/(26Mg / 24Mg)DSM3-1]×1000.
The uncertainty is estimated to be ±0.10 ‰ (2SD)
for δ26Mg, respectively, based on repeat measurements on
reference materials (Tables S1, S2, S3c).
Mg isotopic composition measured by fsLA-MC-ICP-MS.
(a) Repeat measurements of BHVO-2G. Solid black circle and solid
line represent the mean value of all BHVO-2G measurements with the 2SD range
represented by dashed lines. Published literature data (Dai et al., 2016) is
shown for comparison. (b) Biotite and amphibole of sample BP-0c
measured by fsLA-MC-ICP-MS. Bulk rock was measured by solution MC-ICP-MS.
Mg isotope analyses by fsLA-MC-ICP-MS
The micro-scale Mg isotope composition of individual minerals (amphibole and
biotite) was determined on a thin section of sample BP-0c (from the
bedrock–saprolite interface) by UV femtosecond laser ablation coupled to a
Thermo Neptune MC-ICP-MS (fsLA-MC-ICP-MS, Fem2) at GFZ Potsdam.
Instrumentation, data acquisition and evaluation procedures are described in
detail in Schuessler and von Blanckenburg (2014). Laser ablation was
performed on individual mineral grains with a spatial resolution of less than
200 × 200 µm surface area with less than 10 µm
crater depth. The laser beam with a diameter of about 25 µm was
scanned across the mineral surface to adapt to the irregular shape of the
grains and cracks with repetition rates between 13 and 20 Hz. The
high-mass-resolution mode of the MC-ICP-MS was used for Mg isotope ratio
measurements. With high mass resolution, isobaric interferences
(52Cr2+ on 26Mg+, 50Ti2+ and 50Cr2+
on 25Mg+, or 48Ca2+ and 48Ti2+ on
24Mg+) can be resolved from Mg isotopes (Dai et al., 2016; Oeser et
al., 2014). Mass bias correction was performed using the komatiite glass
GOR132-G as bracketing standard. Using a δ26Mg value for GOR132-G
of -0.17 ‰ relative to DSM-3 (Oeser et al., 2014), we converted
results to δ values relative to DSM-3. Based on our current
experience, we conservatively estimate the uncertainty of the fsLA-MC-ICP-MS
method for Mg isotope ratios to be better than ±0.25 ‰ (2SD) for
δ26Mg. Repeat measurements on reference material BHVO-2G (basaltic
glass) (average δ26Mg =-0.07±0.18 ‰, 2SD, n=18) agree within uncertainties to published values (Fig. 1) for this
reference material (-0.20 ± 0.07 ‰; Dai et al., 2016).
Results of biotite and amphibole analyses are presented in Fig. 1.
Photomicrographs (Fig. 2) show representative analysis locations in amphibole
and biotite before and after laser ablation.
Discussion
Mg isotope fractionation by clay formation
Neoformation of Mg clays is a mechanism that preferentially removes 26Mg
from soil solution and enriches this heavy isotope in Mg clays such as
smectite, illite or vermiculite (Wimpenny et al., 2014; Ryu et al., 2016).
Clay formation is thus a potential cause for the low δ26Mgdiss observed in the Providence Creek streams. Three
independent lines of evidence all suggest that this effect is insignificant
at our site. First, Mg-clay abundances are beneath the 5 % detection
limit of X-ray diffraction (XRD) analysis. Second, their absence was confirmed by thermodynamic
modelling (PhreeqC). Third, we use an isotope mass balance based on bulk soil
Mg isotope composition to evaluate whether the low δ26Mg of
dissolved Mg could nevertheless be due to preferential incorporation of
26Mg into small amounts of Mg clay. In an isotope mass balance (Eq. 1)
we assign δ26Mgbulksoil the value of the isotopically
heaviest soil sample (-0.05 ‰, see Table S3c), which has the
potential to be most affected by Mg-clay formation; for primary minerals
δ26Mgprim we use the rock mean
δ26Mgrock (-0.22 ‰, Table S3c).
δ26Mgbulksoil=δ26Mgsec×fsecMg+δ26Mgprim×1-fsecMg
We first solve Eq. (1) for δ26Mgsec with
fsecMg; the fraction of Mg borne by
secondary minerals is estimated to be 4 %, which is contained in an upper
possible limit of 5 % Mg clay (XRD detection limit) relative to 20 %
amphibole/biotite in bulk soil (Appendix B). Soil Mg isotopes can only be
explained if δ26Mg in secondary minerals (δ26Mgsec)≥4 ‰. To our knowledge, such
high clay δ26Mg values have never been reported to date
(Wimpenny et al., 2014). These clay δ26Mg values would require
that Mg clays precipitate from dissolved Mg with a δ26Mg of
∼ 3.5 ‰, which has never been observed
either (Tipper et al., 2012, and references therein). Second, we solve Eq. (1) for fsecMg by using the maximum
published δ26Mgsec of 0.5 ‰ (Ryu et
al., 2016 and references therein). This clay value is also consistent with a
Rayleigh-type mass balance constrained by the δ26Mg of measured
stream water and bulk rock as source Mg using αsolid-solution=1.00054 (Ryu et al., 2016). In this case the bulk
soil Mg-clay content was 30 %, far in excess of our XRD analyses
(Appendix B).
Therefore, incorporation of Mg into clays does not drive the low δ26Mg of dissolved Mg. The remaining process that depletes soil water
in 26Mg is the preferential uptake of 26Mg by plants (Black et
al., 2008; Bolou-Bi et al., 2012) associated with an isotope fractionation
factor between plant Mg and dissolved Mg in the soil solution, expressed as
Δ26Mgplant-diss.
Mg tree uptake fractions from an isotope mass balance
We quantify the fraction of Mg uptake by higher plants
(fuptakeMg) by an equation frequently
used in stable isotope geochemistry (e.g. Black et al., 2008; Johnson et
al., 2004) to calculate the partitioning of an element between two distinct
compartments (Eq. 2). This equation is derived from a simple “closed
system” mass balance model, where the element can freely exchange between
the two compartments (which are in turn isolated from any other
compartment) and fractionate isotopically between these compartments.
Δ26Mgplant-diss is the isotope difference
between Mg in plants and dissolved Mg in soil water.
fuptakeMg=δ26Mgrock-δ26MgdissΔ26Mgplant-diss
In Eq. (2) we use the isotopic difference between the “initial” δ26Mgdiss and δ26Mgdiss that has been modified
from the initial soil solution by Mg uptake into plants. Since we do not
know the initial δ26Mgdiss we use δ26Mgrock as a proxy for this weathering solution, assuming
congruent rock dissolution (Bouchez et al., 2013). It can be excluded that
differences in primary mineral δ26Mg lead to preferential
release of specific δ26Mg, based on fs-laser ablation data of
biotite and amphibole, the main Mg carriers, which are similar to δ26Mg of bulk bedrock (Sect. 2.4 and Fig. 1). The
fuptakeMg calculated here presents a
minimum estimate (“net”) of the total uptake fraction, as it does not
include a fraction of Mg that is potentially recycled back into solution
after uptake through Mg release from plant litter. We note that
fuptakeMg calculated by Eq. (2) is
mathematically equivalent to the results of the steady-state flow-through
reactor model of Bouchez et al. (2013) (see below), but here
fuptakeMg reflects an instantaneous mass
balance and does not depend on a steady state of fluxes but applies only to
an idealised closed system where plants exchange Mg with regolith water.
We can also describe both uptake and removal of Mg by a flow-through reactor
isotope model (Bouchez et al., 2013), where the isotope ratios are
modelled as a function of elemental fluxes. Combining Eqs. (3c), (3d) and
(5e) from Bouchez et al. (2013) and assuming that no Mg is incorporated into
secondary minerals leads to Eqs. (3) and (4):
δ26Mgrock-δ26MgdissΔ26Mgplant-diss=UMg-SorgMgSrockMg+SprimMg,δ26Mgrock-δ26MgdissΔ26Mgplant-diss=EorgMgSrockMg+SprimMg.
The denominator in the right-hand terms of Eqs. (3) and (4) represents the
sum of the Mg supply fluxes from rock dissolution
(SrockMg) at the weathering front and
from primary minerals remaining in the regolith
(SprimMg). In Eq. (3) the flux term
UMg quantifies the Mg uptake flux by trees.
SorgMg represents the flux of Mg from
leaching of plant litter that is either recycled back into the plants or
discharged into the river. The difference UMg-SorgMg is therefore the net Mg
accumulation in the “organic” compartment, combining living biomass and
plant litter. The use of Eq. (3) does not rely on any steady-state
assumption regarding this organic compartment, meaning that the equation
applies even if this pool grows, for example during forest growth after
deforestation or climate change. If the organic Mg pool is at steady state,
the difference UMg-SorgMg is
equal to EorgMg, where
EorgMg refers to the particulate
organic Mg export by erosion (Eq. 4). The isotope ratios are thus set by
the Mg uptake flux by trees relative to the solubilisation flux of Mg by
chemical weathering. Note that the left-hand term of Eqs. (3) and (4) is
identical to the one used for the determination of the relative Mg uptake
flux fuptakeMg by a closed system mass
balance (Eq. 2). As the formation of Mg clays and the dissolution of
carbonates do not affect Mg fluxes at our study sites (Sect. 4.1, Bateman
and Wones, 1972), an isotope difference between rock and dissolved Mg only
emerges if a substantial fraction of isotopically fractionated Mg
accumulates in wood of a regrowing forest after clear cutting or is
exported in plant litter or CWD.
To estimate a range for fuptakeMg
(Eq. 2) or, at steady state, EorgMg (Eq. 3), we applied Eqs. (2) and (4) to all individual Providence
Creek water samples by using a minimum and maximum Δ26Mgplant-diss of 0.50 ‰ (Opfergelt et al.,
2014) and 0.68 ‰ (Black et al., 2008), respectively, and
considered the analytical uncertainty on δ26Mg of
0.10 ‰ (2SD). The difference of
0.50 ‰ we found between δ26Mgdiss
and δ26Mgrock shows that 50 to 100 % of the Mg
initially released by chemical weathering is taken up by trees and
accumulates in growing forest biomass, or it is eventually eroded in plant
litter and CWD. Consequently, because of the high fraction of Mg uptake, the
mean weighted δ26Mgtree is identical to bulk rock (Fig. 3). Therefore, at Providence Creek Mg is strongly bio-utilised.
Glossary of symbols.
Total mass fluxes (e.g. in t km-2 yr-1)
D
Denudation rate; e.g. the sum of chemical and physical denudation; Eq. (7); Sect. 4.4
Elemental fluxes FX (e.g. in mol km-2 yr-1)
RPX
Regolith production flux of element X; transfer of X from bedrock to regolith at the weathering front; Eq. (7); Sect. 4.4
WriverX
Dissolved river flux of element X; Eq. (6); Sect. 4.4
WregolithX
Net solubilisation flux of element X; release flux of X from minerals minus the flux of incorporation of X into secondary minerals; Eq. (9); Sect. 4.5
LX
Litter fall flux of element X; sum of leaf, trunk and root litter flux of X from trees to topsoil through litter fall; Eq. (14); Sect. 4.7
EorgX
Erosion flux of element X in particulate organic matter or phytoliths; Eq. (4); Sect. 4.2
Normalised elemental fluxes fX
wisotopeX
Dissolved export flux of element X relative to the regolith production flux of element X, calculated from isotopes; Eq. (5); Sect. 4.3
wriverX
Dissolved export flux of element X relative to the regolith production flux of element X, calculated from river loads; WriverX/RPX; Eq. (8), Sect. 4.4
wregolithX
Normalised net solubilisation flux of element X; WregolithX/RPX; Eq. (11), Sect. 4.5
DEEX
Dissolved export efficiency of element X; WriverX/WregolithX; Eq. (12), Sect. 4.6
DEENaX
Dissolved export efficiency of element X; Na-normalised WriverX/WregolithX; Eq. (13), Sect. 4.6
RecX
Nutrient recycling factor; number of passages X takes through the vegetation after its initial release from rock; LX/WregolithX; Eq. (14), Sect. 4.7
Elemental mass fractions
fsecMg
Fraction of Mg carried by secondary minerals relative to total soil Mg; Eq. (1), Sect. 4.1
fuptakeMg
Fraction of Mg taken up by plants relative to Mg available in soil solution; Eq. (2), Sect. 4.2
τZrX
Loss fraction of element X; elemental loss or gain relative to unweathered bedrock; Eq. (10); Sect. 4.5
Mg stable isotope properties (in ‰)
δ26Mgcomp.
Normalised 26Mg / 24Mg isotope ratio in compartments (e.g. rock, sec, diss, reg, sed, topsoil, plant) relative to DSM-3
Δ26Mgplant-diss
Isotopic difference between δ26Mgplants and δ26Mgsoilwater
Mg isotopes are unevenly partitioned into the different tree compartments
comprising roots, trunk wood and non-woody foliage. Even though bulk tree
δ26Mg is higher than δ26Mgdiss, its
composition is close to that of the parent rock and soil (Fig. 3). The reason
is that during tree growth, the Mg taken up is partitioned into a
high-δ26Mg compartment in woody plant matter and a low-δ26Mg compartment in leaves and needles. However, to explain the deficit
in 26Mg in dissolved stream Mg, a high-δ26Mg compartment has
to accumulate in wood or be eroded as plant debris present on the forest
floor and then exported as river particulates. We analysed δ26Mg of
foliage, twigs and bark sampled from the forest floor and a sediment pond
containing the erosion products of the ecosystem. Forest floor and sediment
pond needles (Fig. 3, Table S2) are isotopically light as expected given
that needles become isotopically lighter as they age (Bolou-Bi et al., 2012).
Fine twigs (Fig. 3, Table S2) are isotopically light too. This finding is in
contrast with the isotope composition we found in living wood (Fig. 3) and
isotopically heavy Mg published for wood (Black et al., 2008; Bolou-Bi et
al., 2012). The low δ26Mg of the fine twigs (diameter
∼ 3 mm) is explained by their Mg isotopic composition being dominated
by bark for which we also found low δ26Mg (Fig. 3), consistent
with Chapela Lara et al. (2017). Regardless, the compartment containing the
required high-δ26Mg fraction is not contained in fine plant matter
present on the forest floor, making CWD a more likely vector of export for
this high-δ26Mg component. However, the high-δ26Mg
fraction is found in the wood of tree trunks (Fig. 3, Table S2). Our isotope
mass balance allows for two explanations: transient growth of tree biomass
following logging and mechanical removal of tree trunks (Eq. 3); or natural
erosion of coarse woody debris (CWD), at steady state with its uptake, with
only minor leaching of Mg (Eq. 4). We return to discussing these mechanisms
in Sect. 4.8.
Mg weathering fluxes from an isotope mass balance
The fact that Mg is highly bio-utilised and most likely eroded as CWD
dictates that the dissolved Mg export flux is low relative to other Mg
fluxes in the ecosystem. We use the isotope mass balance model (Bouchez et
al., 2013) to calculate the normalised dissolved Mg export flux
(wisotopeMg, Table 1) by Eq. (5) and
report the data in Table S4b:
wisotopeMg=δtopsoilMg-δrockMgδtopsoilMg-δdissMg.
This fraction reflects the Mg solute export from the whole system relative
to the total Mg export of solutes and particulates as primary and secondary
minerals plus organic material. Estimating
wisotopeMg does not depend on knowing
isotope fractionation factors, but it assumes a steady state of fluxes.
We use the mean δ26Mg of unweathered rock, spatial- and
time-integrated creek water of the individual Providence Creek sites (P301,
P303, P304) and mean bulk soil and saprolite from the P301 soil profile and
the soil–saprolite balsam profile (Fig. 3). The mean δ26Mg of bulk soil and saprolite was chosen as soil and saprolite samples vary
insignificantly in their δ26Mg (similar results would be
obtained if we had used the topsoil signature only, where topsoil is the
compartment that is undergoing erosion at our sites). We consider the
isotope composition of this soil–saprolite average to be more representative
for exported particulate matter than samples from sediment ponds, because
hydrodynamic sorting in the creek channel does not allow representative
sampling of sediment from these ponds, where coarse, dense particles are
enriched. δ26Mg of topsoil, saprolite and bulk rock is
identical within their analytical uncertainties. Therefore only a potential
upper boundary of the relative Mg weathering flux
wisotopeMg can be estimated by
propagating the analytical uncertainties as in Bouchez et al. (2013).
Our results show that according to Eq. (5) only 11±13 % of Mg is
exported from the weathering zone in the dissolved form (Fig. 5). Therefore,
the complementary 89 % of Mg is exported predominantly in primary
minerals and in a substantial proportion of CWD.
Elemental dissolved river fluxes
Next, we calculate an independent estimate of the relative dissolved Mg river
flux (wriverMg) that allows comparison with the
isotope-based dissolved Mg export (wisotopeMg).
We also calculate the dissolved river flux wriverX for the
macronutrients (X) K, Ca, P and the plant-beneficial element Si (hereafter
we call these elements “bio-elements”). The absolute (non-normalised)
dissolved annual river fluxes for these elements (WriverX,
Fig. 4, Table 1) are derived from Eq. (6), which is the sum of the catchment
area (A) normalised products of daily dissolved creek water concentrations
(Xriveri) and daily discharge (Qi) of
one hydrological water year:
WriverX=∑i=1365Xriveri×QiA.
Since we lack daily resolution [X]river data and our sampling
years (2010–2014) differ from the hydrological water years (2004–2010) for
which daily discharge is available
(http://criticalzone.org/sierra/data), we use the
[X]river-Q linear regression to determine daily Xriveri. We calculate mean discharge values from
15 days before to 15 days after each of our seven [X]river data
points for all hydrological water years 2004–2010 and calculate annual
WriverX for the individual hydrological water years
2004–2010 by applying Eq. (6). We calculate an average of all hydrological
water years 2004–2010 to derive WriverX (Table S4a). For
example, catchment average WriverMg ranges from
about 7700 to 28 000 mol km-2 yr-1.
Schematic figure illustrating the metrics used in our flux model.
“Org” refers to the sum of coarse woody debris (CWD), litter and trunk wood
erosion. RecX refers to the nutrient recycling factor of element X,
UX refers to the nutrient uptake flux of element X, LX refers to
the litter flux of element X, RPX refers to the regolith production
flux of element X, WriverX refers to the dissolved river
flux of element X and WregolithX refers to the net
solubilisation flux of element X.
Comparison of the relative weathering flux derived from Mg isotopes
(wisotopeMg, Table S4b), dissolved river loads
(wriverMg, Table S4b), and net solubilisation
fluxes (wregolithMg, Table S4b) for the
individual Providence Creek sub-catchments. The ca. 4-fold higher
wriverMg of the smallest watershed P304 compared to the
larger watersheds P301 and P303 might be the result of the relatively high
discharge record caused by higher baseflow (Eagan et al., 2007) for such a
small watershed. For that reason we consider this catchment to be
unrepresentative.
To allow comparison between flux estimates of different elements, we
normalise the measured fluxes using the elemental regolith production rate
(RPX, Fig. 4, Tables 1, S4a), which quantifies the total transfer
of an element X from bedrock to regolith at the weathering front,
partitioned into secondary minerals, solutes and remaining primary minerals
(Bouchez et al., 2013) by Eq. (7):
RPX=D×Xrock.
Here, we use the total denudation rate (D, Table 1) from cosmogenic in situ
10Be concentration from Dixon et al. (2009). Using D of 220 t km-2 yr-1 for all catchments and [Mg]rock of
1.9 weight-%, RPMg is about 175 000 mol km-2 yr-1. The normalised dissolved river fluxes
(wriverX) are calculated by Eq. (8)
(Bouchez et al., 2013) and reported in Table S4b:
wriverX=WriverXRPX.
wriverMg amounts to 4–16 % (Fig. 5) of
Mg fluxes and is similarly low as
wisotopeMg of ca. 11 %. Thus, in
the absence of Mg-containing secondary minerals, Mg is exported
predominantly in remaining primary minerals or, after uptake by plants, in
the form of CWD or remains in the wood of a growing forest.
Net elemental solubilisation fluxes in the weathering zone
To test the interpretation that a substantial fraction of Mg and other
bio-elements (X) initially solubilised from rock accumulate in wood (with or
without subsequent export as plant litter and CWD), we compare the relative
dissolved export fluxes of Mg
wriverMg and
wisotopeMg to the normalised net
solubilisation flux (wregolithMg, Table S4b). The non-normalised net solubilisation flux
(WregolithX, Fig. 4, Table 1) is
determined by Eq. (9) and reported in Table S4a:
WregolithX=RPX×-τZrX.
WregolithX is defined as the flux of release of X from
minerals undergoing weathering minus the flux of incorporation of X into
new minerals potentially formed during weathering reactions (e.g. clays) over
the regolith profile. WregolithX thus quantifies the net
release of X from the bedrock–regolith system.
WregolithX is derived from the total denudation rate (D,
Table 1) bedrock concentrations ([X]rock) following Eq. (7),
combined with mass transfer coefficient (hereafter elemental loss fraction) (τX, Table 1). The loss fraction (τX) quantifies
the depletion (τX < 0) or
enrichment (τX > 0) of an
element X relative to unweathered bedrock (Anderson et al., 2002; Brimhall
and Dietrich, 1987). τZrX is
determined by Eq. (10):
τZrX=ZrunweatheredbedrockZrweatheredregolith×XweatheredregolithXunweatheredbedrock-1.
Zr is used as the immobile element. In addition to the dataset of this
study, published data (Hahm et al., 2014; Riebe and Granger, 2013) have been
used to obtain the most representative bedrock concentrations and are
reported with our data in Table S3a–c.
The net solubilisation flux WregolithX is determined by
Eq. (9) for each of the Providence Creek catchments and ranges from 41 000
to 75 000 mol km-2 yr-1 for Mg. Since τZrX is relatively
uniform across the sampled soil–saprolite profile (Fig. 7), mean
τZrX values based on soil and saprolite data from Hahm et al. (2014)
and Riebe and Granger (2013) (Table S3) have been used. Only τZrP is strongly depth dependent (Fig. 7). Hence we used the most
negative τZrP from the dataset from Hahm et al. (2014) and Riebe
and Granger (2013) (Table S3). The normalised net solubilisation flux
(wregolithX) is determined by Eq. (11). The comparison to
Eqs. (7) and (9) shows that wregolithX is actually equal
to -τZrX:
wregolithX=WregolithXRPX=-τZrX.
wregolithMg amounts to ∼ 40 % (Fig. 5), meaning that in the regolith 40 % of the Mg supplied
from rock is transferred into the dissolved form and is made available for
plant uptake. Because wregolithMg is
much higher than wisotopeMg and
wriverMg (Sect. 4.3 and 4.4), this calculation
shows that a substantial fraction of Mg once released by chemical weathering
is taken up into the biomass without subsequent redissolution.
Dissolved export efficiency
To confirm that Mg is not the only element that is strongly bio-utilised, we
compared the dissolved river flux
(WriverX) with the net solubilisation
flux (WregolithX) by its ratio
WriverX/WregolithX for the other bio-elements (K, Ca, P, Si). Because this ratio quantifies
the dissolved riverine loss of X from the ecosystem relative to its net
release from the regolith we call the ratio the “dissolved export
efficiency” (DEEX, Eq. 12, Fig. 6, Table 1):
DEEX=WriverXWregolithX.
If the DEEX is larger than 1, input sources other than rock weathering
are supplying X, such as atmospheric deposition (see Sect. 5). The
DEEX is less than 1 if some of the released element is partitioned into
a plant uptake flux during forest growth or is eroded as plant litter or CWD
(including eroded phytoliths in the case of Si). The DEEX can also
differ from 1, because WriverX and
WregolithX integrate over entirely
different timescales.
The inferred DEEX (∼ 0.40 for K, ∼ 0.60 for Ca, ∼ 0.30
for Mg, ∼ 0.05 for P and ∼ 0.10 for Si) of each nutritive element
is less than 1 (Fig. 6), suggesting that some fractions of bio-elements once
released by chemical weathering are bio-utilised and remain in regrowing
forest biomass after clear cutting or are eventually eroded as CWD. The
DEEX of the non-nutritive element Na is < 1 too and amounts to
0.68 (Table S4d). Thus, DEENa suggests that 32 % of Na, which
has been released by chemical weathering, is missing in the dissolved river
flux. This result is unexpected because Na behaves conservatively, meaning Na
is neither incorporated into secondary minerals nor taken up as a nutrient by
plants. Measured Na in pine tree wood amounts to 3–8 ppm (Table S2) and in
shrub wood to ∼ 40 ppm (Table S2). These low Na contents in plants
translate into a plant uptake flux of about 2 % relative to the
solubilisation flux, far lower than the ∼ 1/3 of
WregolithNa estimated from DEENa.
This observation agrees well with the fact that Na is only a plant-beneficial
element in halophilic and C4/CAM plants (Marschner, 2011) and plays no
significant nutritive role in pine trees representing the prevailing plant
species at SSCZO. We argue that the supposed deficit in
WriverX relative to
WregolithNa is a timescale effect as
WriverX integrates over annual and
WregolithX over millennial timescales.
Dissolved export efficiency (DEEX, left y axis, Table S4d–e)
and nutrient recycling factor (RecX, right y axis, Table S4f) for
macronutrients and the plant-beneficial element Si. The DEEX quantifies
the dissolved riverine loss of X from the ecosystem relative to its net
release from the regolith. DEEX refers to the pure ratio
WriverX/WregolithX (Eq. 12).
DEENaX refers to the ratio
WriverX/WregolithX normalised over its
corresponding Na fluxes (Eq. 13). RecX (Eq. 14) quantifies how often an
element X is bio-utilised by plants after its release by chemical
weathering.
Elemental loss fraction (mass transfer coefficient) (τZrX)
for macronutrients, the plant essential element Si and Na of the
soil–saprolite depth profile BP. A τZrX value
< 0 indicates elemental loss in soil/saprolite relative to
unweathered bedrock.
To obtain a metric that is independent of timescale effects, we normalised
the fluxes WriverX and
WregolithX over their respective Na
fluxes (Eq. 13) and rearranged the right-hand term of Eq. (13):
DEENaX=WriverXWriverNaWregolithXWregolithNa=[X]river[Na]river/[X]rock[Na]rockτZrXτZrNa.
This approach has a fundamental benefit, as knowing the denudation rate D
(Eq. 9) from cosmogenic nuclides and the discharge Q (Eq. 6) from
long-lasting gauging programs is not required. However, we note that the Na
normalisation may also introduce bias into the
DEENaX (Table 1). This might be the case if, for example,
changes in water flow during the development of the profile over a few
thousand years result in a change in the stoichiometry of rock dissolution.
Such changes in the congruency in the dissolution of rock might result from
changes in the dissolution of Na-bearing primary minerals relative to other
primary minerals or from a changing rate of secondary mineral formation
relative to Na-bearing primary minerals. In that case the time-integrated
denominator in Eq. (13) does not reflect the present value.
The DEENaX values obtained (Fig. 6,
Table S4e) show that, of the elements solubilised from rock, ∼ 80 % of Ca, ∼ 60 % of K, ∼ 50 % of Si,
∼ 40 % of Mg and ∼ 10 % of P appear in
the streams dissolved load. The DEENaX
for Mg is in excellent agreement with the 50–100 % of Mg
bio-utilisation calculated independently by isotope mass balances (Eq. 2).
The high DEENaX for Ca can be
attributed to its high concentrations in rock combined with its high degree
of solubilisation by chemical weathering that results in excess availability
compared to the nutrient demand of trees. In contrast, the low
DEENaX for P is most likely due to its
high biological demand and low availability, resulting in high degree of
plant uptake and subsequent export in plant litter and CWD.
Nutrient recycling factor
After uptake and return to the forest floor, nutrients are not directly
discharged into the stream by litter dissolution or eroded as plant litter
or CWD. Rather, they are subject to recycling – defined here as uptake of
nutrients that are made bio-available again after their release from plant
litter. The recycling flux can be hypothesised to depend on the ratio of
nutrient demand to availability. We thus tested the hypothesis that in our
kinetically limited setting, unlike in the supply-limited regime, intense
nutrient recycling is not required as nutrient loss can be balanced by supply
from mineral dissolution in the regolith (Jobbagy and Jackson, 2001; Lucas,
2001). In other words, if nutrient supply from regolith
(WregolithX) is high, ecosystem nutrition can be satisfied
even if recycling is low (Lang et al., 2016). We quantified nutrient
recycling as the number of passages an element X takes through the
vegetation after its initial release from rock (quantified by the net
solubilisation flux WregolithX). We note that the nutrient
uptake–release loop is distinct and formally independent of other fluxes such
as regolith production, weathering and export fluxes calculated above
(Fig. 4). We call the number of passages in the loop the elemental recycling
factor (RecX, Fig. 4, Table 1). RecX is determined by Eq. (14) and
reported in Table S4f:
RecX=LXWregolithX.
The nutrient uptake flux is the product of net biomass productivity and
biomass nutrient concentration (UX, Fig. 4). Since UX is difficult
to determine, we use the sum of litter fluxes (LX; Table 1) comprising foliage
litter fall (LfoliageX, Table S4c), root
litter (LrootX, Table S4c) and trunk
litter (LtrunkX, Table S4c) instead,
assuming balanced uptake and litter fall fluxes (for input parameters see
Appendix C). LMg is 16 000, 10 000 to 20 000, and 28 000 mol km-2 yr-1 for foliage, stem and root, respectively. LX
represents a minimum estimate for UX and hence RecX is likely
underestimated because we did not consider return of growth-limiting
nutrients from foliage via phloem through roots back into soil during
senescence and return of nutrients from throughfall or stem flow.
With an average RecP of 13, P is the only bio-element that is
tightly recycled (Fig. 6) and becomes enriched in topsoil (Fig. 7). Aciego et
al. (2017) also compared the sum of dust and bedrock-derived P supply fluxes
with nutrient uptake fluxes at SSCZO, obtaining an order of magnitude higher
uptake than supply fluxes, and concluded too that P is recycled. With
RecK of ca. 4, K is also recycled. We note that RecK is likely
underestimated due to the lack of throughfall data, which are generally
highest for K compared to the other bio-elements (Boy and Wilcke, 2008). The
RecX for the macronutrients Ca and Mg is about unity (Fig. 6) and thus
these nutrients are not recycled by uptake after release from litter. This
means that uptake from regolith is their only source. The RecSi
of < 0.1 means that only a minor fraction of Si solubilised from
rock is bio-utilised. The low RecX values for all bio-essential elements
except P are in agreement with our observation that after uptake the largest
mass fraction of these bio-elements remains in wood or is disposed through
export of plant litter and CWD. Altogether, the overall high
DEENaX (Sect. 4.6) and low RecX are
consistent with the kinetically limited weathering regime of Providence Creek
in which mineral nutrients are supplied in sufficient demand, the ecosystem
is “acquiring” and thus the need for recycling is low (Lang et al., 2016).
Although RecX and DEENaX rely on
WregolithX we note that both metrics are
independent from each other. This independency arises because ecologic
stoichiometry enriches other mineral nutrients in plants than released from
mineral dissolution kinetics. Thus an element X can become recycled (meaning
uptake of nutrients released from plant litter) many times compared to this
element's weathering flux WregolithX.
This number of cycles as quantified by RecX can vary between 0 and a
large number. In contrast, DEENaX
quantifies the fraction of an element that is exported in the dissolved
river load rather than being contained in plant debris, relative to the
fraction of X that was initially solubilised by chemical weathering, and can
vary between 0 and 1 unless atmospheric input results in
DEENaX > 1.
Accumulation of bio-elements during forest growth or export in
coarse woody debris (CWD)?
In the preceding sections, we have suggested two mechanisms that potentially
explain the creek water being enriched in 24Mg and the deficit in the
dissolved river export fraction indicated by the
DEENaX: (1) bio-utilisation and accumulation of
bio-elements in wood of a regrowing forest after clear cutting on centennial
timescales or (2) solid export of nutrients in CWD by natural erosion in
pre-forest-management times and over weathering (kyr) timescales. Concerning
logging, in the late 19th century Pinus ponderosa forests became
nearly wholesale clear-cut (Graham and Jain, 2005) and our study sites
underwent continuous logging of some form through the 1960s
(Carolyn Hunsaker, personal communication, 2017). These logging activities
triggered the growth of today's forest at Providence Creek and might have
shifted the ecosystem from some quasi-steady state – where elemental input
fluxes equal elemental export fluxes, and where plant growth equals plant
mortality – into an ecosystem being in a transient state characterised by
the build-up of a pool of bio-elements (e.g. Sommer et al., 2013). Concerning
natural erosion, trunk wood that is enriched in 26Mg is not contained in
the sediment pond we sampled. Yet it is continuously removed from the
ecosystem by stochastic events, such as tree turnover after tree death
(Roering et al., 2010), wind throw or wildfires – which have been suppressed
since the late 19th century – after which ash is fast eroded.
To estimate whether tree trunk growth satisfies the elemental and isotopic
mass balance we estimated the budgets of bio-elements contained in
Pinus ponderosa trunk wood (see Sect. 4.7 and Appendix C). We find
that the litter fall fluxes (LX, Table S4c) that we use to estimate
uptake indeed are comparable with the deficit in the elemental dissolved
export flux as indicated by 1-DEENaX for Mg and
Ca. Both the P and K trunk wood fluxes are higher than the deficit in the
elemental dissolved export flux. This effect arises for strongly recycled
elements, because the uptake flux contains the fraction added by nutrient
recycling from the forest floor. However, for Si RecX amounts to
< 0.1 whereas the fraction not accounted for by dissolved loss
(1-DEENaX) is 0.54. A possible reason is that
pine needles can treble in Si concentrations as the needles
age (Cornelis et al., 2010) and that Si is
bio-utilised by shrubs whose leaves dispose phytoliths that are not accounted
for in our budget. Thus the Si concentrations used in our calculations might
be unrepresentative of those in aged leaf litter (Appendix C) and
RecSi might be an underestimate. If true, the
1-DEENaX of Si amounting to 50 % is a better
estimate for Si uptake.
Whether natural erosion of bio-elements by CWD is a feasible mechanism
depends on whether the erosional timescale out-competes the leaching timescale from CWD. Trunk wood decomposition fluxes have been quantified for
Fagus grandifolia, Acer saccharum and Betula alleghaniensis. About 25–50 % of Ca, 30–70 % of P, 5–20 % of K, 20–40 %
of Mg (Johnson et al., 2014) and 25–60 % of Si (Clymans et al., 2016)
remain in trunk wood after 16 years of decomposition. For comparison, after
2 years of Pinus ponderosa foliage litter decomposition ∼ 90% of Ca,
∼ 55 % of P, ∼ 20 % of K and ∼ 45 % of Mg (Klemmedson, 1992) remain in foliage litter. The dissolution
half-life of the bio-opal in phytoliths at the pH prevailing at Providence
Creek amounts to a few hundred days (Fraysse et al., 2009). Therefore,
bio-element leaching (except Ca) from foliage outpaces bio-element leaching
from wood. Hence, after tree death and after litter fall (Si contained in
phytoliths and Ca likely contained in oxalates) erosional removal must
occur within this decomposition timescales for CWD to be a feasible
mechanism.
Given the lack of information on the pre-logging fluxes and isotope ratios
at Providence Creek we have no means to assess whether the natural CWD
erosion mechanism has been in operation and caused the deficit in dissolved
elemental export rather than forest growth today. We can speculate, however,
that one effect has replaced the other with similar impact on fluxes. This
is because the natural erosion of mineral nutrients in tree trunks in the
form of CWD is ultimately limited by tree growth too. One other study, using
stable Sr isotopes in an unperturbed ecosystem in New Zealand, shows a
similar partitioning of Sr between plants and the river dissolved flux
(Andrews et al., 2016). Those data can be interpreted to imply natural
erosion of Sr in plant litter and CWD. The same interpretation is possible
for the data from the Shale Hills Critical Zone Observatory, where a similar
deficit in heavy Mg isotopes was found in stream and soil water (Ma et al.,
2015). In that study the bio-cycling hypothesis was dismissed on the grounds
of missing accumulation of Mg in the organic-rich portions of the soil. The
existence of a sub-micron pool enriched in 26Mg was hypothesised
instead. However, the Mg data at Shale Hills CZO are compatible with the
CWD export hypothesis too.
Nutrient uplift from the deep saprolite
We determined the depth from which these nutrients are uplifted. A first
indicator is the depth distribution of loss fractions τX
(Brantley and Lebedeva, 2011) that allows for the identification of
so-called biogenic profiles that are characteristically depleted at depth
and become enriched in topsoil, because nutrients are uplifted from
depth (Jobbagy and Jackson, 2001; Lucas, 2001; Bullen and Chadwick,
2016). Whereas P depletion amounts to 85 % at 3 m depth and increases
towards the surface, indicating biogenic uplift of P, the loss fractions of
Mg, K and Si amount to 20 to 40 % and show uniform depletion
along the entire depth of the weathering zone down to 7 m depth. The
traditional view is that this loss is induced by mineral dissolution and
removal by infiltrating water (Brantley and Lebedeva, 2011). We can
use Mg isotopes to explore an alternative hypothesis: these
bio-elements are taken up by tree roots or associated mycorrhiza fungi
(Jongmans et al., 1997; Landeweert et al., 2001; Lucas, 2001) at these deep
levels. In the absence of Mg clays and carbonates the isotopically light
composition of the exchangeable fraction throughout the regolith (δ26Mgexch, Fig. 3) can only be caused by the preferential uptake
of heavy Mg isotopes by trees. We can exclude that the development of such
an isotopically light exchangeable Mg compartment throughout the regolith is
due to fractionation during adsorption (Opfergelt et al., 2014) as the
associated fractionation factor is close to 0 ‰
(Wimpenny et al., 2014). Also, Bullen and Chadwick (2016) have shown that
isotopic fractionation during adsorption onto clay minerals is absent for
other bivalent cations. We can also exclude that low δ26Mgsoil water infiltrates to depth from the surface as this
δ26Mgsoil water would be masked by the high Mg
solubilisation flux from primary minerals at the considered depth (Fig. 5).
Deep water uptake from down to 6 m is supported by the rooting depth of
Pinus ponderosa, which can reach up to 24 m (Stone and Kalisz, 1991).