Soil and water acidification was internationally
recognised as a severe environmental problem in the late 1960s. The
interest in establishing “critical loads” led to a peak in weathering
research in the 1980s and 1990s, since base cation weathering is the
long-term counterbalance to acidification pressure. Assessments of
weathering rates and associated uncertainties have recently become an area
of renewed research interest, this time due to demand for forest residues to
provide renewable bioenergy. Increased demand for forest fuels increases the
risk of depleting the soils of base cations produced in situ by weathering.
This is the background to the research programme Quantifying Weathering
Rates for Sustainable Forestry (QWARTS), which ran from 2012 to 2019. The
programme involved research groups working at different scales, from
laboratory experiments to modelling. The aims of this study were to (1) investigate the variation in published weathering rates of base cations from
different approaches in Sweden, with consideration of the key uncertainties
for each method; (2) assess the robustness of the results in relation to
sustainable forestry; and (3) discuss the results in relation to new insights
from the QWARTS programme and propose ways to further reduce uncertainties.
In the study we found that the variation in estimated weathering rates at
single-site level was large, but still most sites could be placed reliably
in broader classes of weathering rates. At the regional level, the results
from the different approaches were in general agreement. Comparisons with
base cation losses after stem-only and whole-tree harvesting showed sites
where whole-tree harvesting was clearly not sustainable and other sites
where variation in weathering rates from different approaches obscured the
overall balance. Clear imbalances appeared mainly after whole-tree
harvesting in spruce forests in southern and central Sweden. Based on the
research findings in the QWARTS programme, it was concluded that the
PROFILE/ForSAFE family of models provides the most important fundamental
understanding of the contribution of weathering to long-term availability of
base cations to support forest growth. However, these approaches should be
continually assessed against other approaches. Uncertainties in the model
approaches can be further reduced, mainly by finding ways to reduce
uncertainties in input data on soil texture and associated hydrological
parameters but also by developing the models, e.g. to better represent
biological feedbacks under the influence of climate change.
Introduction
Acidification of soils and water, caused by long-range transport of acidic
compounds, was recognised as an environmental problem in Europe in the late
1960s (Odén, 1968). In subsequent decades, extensive research examined
processes that acidify and counteract acidification (Reuss and Johnson,
1986). Two key research programmes were the Surface Water Acidification
Programme (1985–1990, Mason, 1990) funded by the UK (GBP 5 million) and the
National Acid Precipitation Assessment Program (1980–1990, Irving, 1991)
funded by the US government (USD 17 million). At the end of the 1980s, the
critical load concept was developed as an effect-based approach for emission
reductions (Nilsson and Grennfelt, 1988) and served as a link between
science and policy within the framework of the UNECE–CLRTAP (the United
Nations Economic Commission for Europe – Convention on Long-Range Transport
of Air Pollutants) (Lidskog and Sundqvist, 2002). A critical load is defined
as “a quantitative estimate of an exposure to one or more pollutants below
which significant harmful effects on specified elements do not occur according
to present knowledge” (UNECE, 1994). To calculate critical loads of acidity
and their exceedance, mass balance calculations of acidity are used together
with a critical limit for a chemical criterion, defining the maximum acidity
of soil/runoff water that can be allowed without a risk of negative effects
on a chosen biological indicator (Sverdrup and de Vries, 1994).
Base cation (BC) mass balance for the rooting zone of a
well-drained forest soil. ΔSoil BC is the sum of the net change in
BC in soil solution, the net change in soil exchangeable BC and the net
change in soil organic material BC.
Estimates of base cation weathering (Ca, Mg, K, Na) play a key role in all
kinds of mass balance calculations related to acidity, e.g. the mentioned
critical load calculations, as weathering is an important long-term natural
source of base cations and as such a sink of acidity. The net accumulation
or depletion of soil base cations in the soil is the result of the mass
balance between inputs (atmospheric deposition and weathering) and outputs
(losses through leaching and harvesting) of base cations (Fig. 1).
Atmospheric deposition depends on external factors and can vary in time
(Hedin et al., 1994). The leaching term is directly dependent on the mass
balance as it mirrors the aqueous pool of base cations in the soil. Harvest
losses are predefined following forest management. Finally, weathering is
the long-term source of base cations, depending largely on soil mineral
content and soil texture. In areas that have been covered by ice, like
Scandinavia, the soil properties at a specific site depend on the parent
material from which the glacial till originates. When trees and forest soils
are in focus, the weathering term refers to the weathering products in the
rooting zone, i.e. the base cations available for trees.
Due to its central role in mass balance and acidity calculations, weathering
was studied extensively during the 1980s and 1990s, to enable accurate
weathering quantifications. Weathering rates are, however, difficult to
quantify through direct measurements in the field due to the complexity of
base cation dynamics in soil. There are several different pools of base
cations in soil and also several different flows, e.g. decomposition,
uptake, ion exchange and weathering, and it is difficult to distinguish
between these different sources and sinks (Rosenstock et al., 2019) and
to define the pools accurately (van der Heijden et al., 2018). Therefore, a
number of indirect methods to quantify weathering rates have been developed:
process-based modelling (Sverdrup and Warfvinge, 1993); soil measurements
where the depletion of weathering products in different soil layers is
determined in order to assess average weathering rates since soil formation
(Olsson et al., 1993); and budget calculations where the flows in the mass
balance, except weathering, are measured (Lundström, 1990; Jacks and
Åberg, 1987; Wickman and Jacks, 1991; Sverdrup et al., 1998).
The political and scientific agreement on the critical load concept as a
basis for managing acidic deposition was a major factor in subsequent policy
success on limiting acidifying emissions (Lidskog and Sundqvist, 2002).
Major acidic deposition reductions occurred, and some recovery of soils and
surface waters has been noted by the monitoring operations put in place by
the UNECE–CLRTAP (Graf Pannatier et al., 2011; Pihl Karlsson et al., 2011;
Akselsson et al., 2013). The uncertainties in weathering rates were, during
the times of high deposition, less important. Therefore, the interest waned
in further weathering research that might revise these weathering estimates.
As the severity of climate change became fully recognised, policies for
mitigation of climate change led to increased demand for renewable fuels,
thereby increasing the pressure on forests. Whole-tree harvesting, here
defined as harvesting of stems and branches, was seen as an important source
of renewable fuel. Since 2000 in Sweden, the proportion of clearcuts
involving whole-tree harvesting has increased from around 15 % to
25 %–35 %, according to statistics from the Swedish Forest Agency, except
for 2014–2016, when the proportion was temporarily between 15 % and 25 % due to
lower energy prices. Demand is likely to increase in the future
(Börjesson et al., 2017). Harvesting of branches and the nutrient-rich
needles also means a substantially increased removal of base cations
compared to conventional stem harvesting, which may counteract the recovery
from acidification. Thus, whereas the weathering rates in the past mainly
were compared with deposition, which at that time (1970–1980) was much
greater than estimated weathering and critical loads of acidic deposition,
the interesting comparison in today's policy context is
between base cation weathering rates and base cation losses through
harvesting, to assess sustainable forest management. Accordingly, mass
balance calculations, with weathering and deposition as inputs and harvest
losses and losses through leaching as outputs (Akselsson et al., 2007) (Fig. 1), as well as simplified calculations, where weathering rates are compared
with base cation losses through harvesting (Olsson et al., 1993), have been
used during the last decades for forest sustainability assessments. The
conclusions from these studies were that base cations may be depleted in
spruce forests in certain regions if whole-tree harvesting is applied.
The prospect of increasing demand for forest biomass, and particularly
concerns about the effects of whole-tree harvesting on nutrient
sustainability, renewed the interest in weathering in Scandinavia for new
forest policy issues. The accuracy of the weathering calculations and the
conclusions about the long-term sustainability of forests were questioned
by Klaminder et al. (2011), who compared estimations of weathering rates for
Ca and K from different approaches at a site in northern Sweden. These
estimates differed widely, and the study concluded that nutrient budgets,
based on calculations including weathering rates, are too uncertain to be
useful in shaping forest policies regarding harvest practices. Futter et al. (2012) suggested that some of this variation is due to differences in
boundary conditions, for example the depth to which weathering had been
calculated. They examined weathering estimates from 82 sites, with up to
eight different weathering estimates per site, and found considerable
variability in weathering rates estimated with different methods, often with
results differing on the same site by several hundred percent. They
identified uncertainties in input data as the largest contributor to the
variability, but differences in the soil depth for which weathering was
calculated also contributed, in the same way as in Klaminder et al. (2011).
Futter et al. (2012) concluded that the uncertainties are large and that at
least three independent methods should be used when making management
decisions.
In 2012, a SEK 25 million research programme, Quantifying Weathering Rates
for Sustainable Forestry (QWARTS), was started in Sweden. The programme,
which focused on weathering rates for the base cations Ca, Mg, Na and K in
Sweden, included approaches covering the whole spectra from laboratory-scale
experiments, through plot- and catchment-scale experiments in the field, to
extensive weathering modelling. Different approaches were compared at
different scales and were in some cases refined (Stendahl et al., 2013;
Casetou-Gustafson et al., 2018, 2019a, b; Akselsson et al., 2016; Belyazid et
al., 2019; Kronnäs et al., 2019; Erlandsson et al., 2016). The
input data were also examined for uncertainties relating to the
generalisations made when estimating normative mineralogy based on total
chemical analyses (Casetou-Gustafson et al., 2018,
2019a). Two other potential sources of uncertainties that have been explored,
but that are still widely discussed, were revisited: (1) the role of
biological weathering that might generate weathering not included in the
current generation of biogeochemical models (Banfield et al., 1999; Finlay
et al., 2009, 2019) and (2) model simplifications
related to base cation exchange and aluminium complexation (Gustafsson et
al., 2018; van der Heijden et al., 2018). Furthermore, the weathering
kinetics used in models were revisited (Sverdrup et al., 2019), and
weathering rates representing not only the rooting zone but the full
catchment scale were studied to assess the export of weathering products
to surface waters (Ameli et al., 2017; Erlandsson Lampa et al., 2019).
The aims of this study were to (1) investigate the variation in published
weathering rates from different approaches in Sweden, with consideration of
the key uncertainties for each method; (2) assess the robustness of the
results in relation to sustainable forestry; and (3) discuss the results in
relation to new insights from the QWARTS programme and propose ways to
further reduce uncertainties. While weathering is important for
understanding the acidification of both soils and surface waters, this paper
focuses on soils, and specifically the rooting zone (approximately 50 cm).
Sites included in the study, where at least two well-documented
approaches for estimating weathering rates have been applied to the same
depth.
SiteDepthMethodsReferencesGårdsjön A0.5 mbPROFILE, depletionStendahl et al. (2013)Gårdsjön B (F1)0.67 ma,cPROFILE, depletion, budget, total analysis regression, budget (MAGIC)Sverdrup et al. (1998), Köhler et al. (2011)Gårdsjön C0.47 maPROFILE, budget, budget (Sr), total analysis regression,Sverdrup et al. (1998)Svartberget A0.5 mbPROFILE, depletionStendahl et al. (2013)Svartberget B0.8 maPROFILE, depletion, budget, budget (Sr)Sverdrup and Warfvinge (1991, 1993), Lundström (1990)Vindeln0.5 mbPROFILE, depletionStendahl et al. (2013)Risfallet A0.5 mbPROFILE, depletionStendahl et al. (2013)Risfallet B1.0 mbPROFILE, budget (Sr)Sverdrup and Warfvinge (1991, 1993), Jönsson et al. (1995), Maxe (1995)Fårahall1.0 mbPROFILE, depletionSverdrup and Warfvinge (1991, 1993), Jönsson et al. (1995), Maxe (1995)Stubbetorp1.0 maPROFILE, total analysis regression, budget (MAGIC)Maxe (1995), Gardelin and Warfvinge (1992)Flakaliden0.5 mbPROFILE, depletion, budgetCasetou-Gustafson et al. (2019a)Asa0.5 mbPROFILE, depletion, budgetCasetou-Gustafson et al. (2019a)Bodafors0.5 mbPROFILE, depletionStendahl et al. (2013)Hjärtasjö0.5 mbPROFILE, depletionStendahl et al. (2013)Hässlen0.5 mbPROFILE, depletionStendahl et al. (2013)Kloten0.5 mbPROFILE, depletionStendahl et al. (2013)Kullarna0.5 mbPROFILE, depletionStendahl et al. (2013)Lammhult0.5 mbPROFILE, depletionStendahl et al. (2013)Skånes Värsjö0.5 mbPROFILE, depletionStendahl et al. (2013)Stöde0.5 mbPROFILE, depletionStendahl et al. (2013)Söderåsen0.5 mbPROFILE, depletionStendahl et al. (2013)Västra Torup0.5 mbPROFILE, ForSAFEKronnäs et al. (2019)Hissmossa0.5 mbPROFILE, ForSAFEKronnäs et al. (2019)
a Including the O layer.b Not including the O layer.c For MAGIC the weathering rate was calculated to 0.6 m, including the O layer.
Well-investigated sites where weathering rates have been
calculated for the same soil depth with at least two different approaches.
See also Table 1.
Methods
Weathering rates from different approaches were compared on a site level on
well-investigated sites, and on a regional level on a larger number of sites
but with more generalised input data. For the comparison of weathering rates
on single sites, weathering estimates of base cations (Ca, Mg, K and Na)
from Swedish forest sites, where at least two well-described approaches had
been applied to the same soil depth, were compiled from literature and
compared (Table 1; Fig. 2). The 23 sites found were located on till soils,
with a mineralogical composition characterised by granitic and gneissic
bedrock, i.e. with mainly quartz, orthoclase and plagioclase, and small
amounts of mafic minerals such as amphibole and epidote (Table 2). A total of 13 of the sites were taken from Stendahl et al. (2013). Of the originally 16
sites in that study, 3 were excluded, since site conditions were not
appropriate for using the depletion method (two of the sites) or PROFILE
(one of the sites) (Stendahl et al., 2013). For each of the 23 sites found,
medians of the different approaches were calculated along with maximum
deviation from the median (Table 3). The different approaches are described
in Sect. 2.1–2.4.
Mineral content in soil at 50 cm depth (weight %) used as input
for modelling weathering rates for the different sites: Qz (quartz), Or
(orthoclase), Pl (plagioclase), Am (amphibole), Ep (epidote). Bi (biotite),
Ap (Apatite), Mu (Muscovite), Ch (chlorite), Il (illite), Ve (vermiculite),
and Hy (hydrobiotite). Minerals occurring in very small amounts, with minor
effect of weathering rates, are not included in the table. Input data were
not found for Gårdsjön C. The mineralogy has in some cases been
slightly simplified to make it fit in one table. For detailed mineralogy,
see original references (Table 1).
a Mineralogy has been calculated with multiple models, but only the X-ray powder diffraction (XRPD)
results are presented here.b Muscovite and illite could not be separated with the XRPD method.
Weathering rates (meqm-2yr-1) and statistics at the
sites described in Table 1. Values in parentheses after the intervals
represent the middle of the intervals.
a Maximum difference from median (+ indicates that the maximum
difference is higher than the median, – indicates that it is lower than the
median, and ± indicates that it is as big a difference to the maximum
and minimum values).
For the regional-level comparison, three published approaches for
calculating weathering rates of the nutrient base cations (Ca, Mg, K) on a
regional level in Sweden were revisited, harmonised and compared: PROFILE,
ForSAFE and the depletion method combined with the total analysis regression
approach (Sect. 2.1–2.3). Na was not included, since there were no
estimates for Na from the latter approach. Weathering rates were compared in
346 sites in the SAFE database (Alveteg, 2004), which were the sites of the
in total 640 sites in the database for which all methods could be applied
successfully and where data on stones and boulders were available (Stendahl
et al., 2009). For a regional comparison, the sites were divided into seven
climate regions, simplified from 19 weather forecast regions used by the
Swedish Meteorological and Hydrological Institute (SMHI) (Fig. 4). One of
the regions, northwestern Sweden, only contained one site and was therefore
excluded from the analysis. The regional approaches are further described in
Sect. 2.1 and 2.3.
To put the weathering estimates in a sustainability perspective, simplified
base cation mass balance calculations were performed for the single sites,
where weathering rates, the most important natural long-term source of base
cations, were compared with harvest losses of base cations, which is the one
of the outputs that can be anthropogenically controlled (Fig. 1; Sect. 2.5). Finally, the results from the studies in QWARTS, on biological
weathering and on the representation of base cation exchange and aluminium
complexation in the models, were synthesised; main uncertainties were
highlighted; and ways to reduce them were proposed.
Modelling based on weathering kinetics
Due to the difficulties in measuring field weathering rates, weathering
kinetics have been frequently studied in laboratory environments (Brantley
et al., 2008). Mechanistic modelling of weathering rates, based on
laboratory-determined weathering kinetics, is one of the most widely used
approaches for estimating field weathering rates (Warfvinge and Sverdrup,
1992; Godderis et al., 2006; Maher et al., 2009). The PROFILE model
(Warfvinge and Sverdrup, 1992) is a steady-state soil chemistry model where
weathering is derived from the breakdown of minerals, based on
process-oriented descriptions of chemical weathering and solution
equilibrium reactions. Weathering rates are calculated for different layers,
with different soil properties, using transition state theory and the
geochemical properties of the soil system, such as soil wetness,
temperature, mineral surface area and mineral composition, and organic acid
concentrations. Deposition of sulfur, nitrogen and base cations, as well as
net losses of base cations and nitrogen through harvesting, is used as
input for modelling of pH and base cation concentrations in soil water,
which is required for the weathering modelling. Weathering rates are
calculated for each mineral separately, using rate coefficients from
laboratory studies for four reactions: with H+, water, CO2 and
dissolved organic carbon (DOC) (Sverdrup and Warfvinge, 1993). PROFILE has
been used widely for estimating weathering in Europe (Akselsson et al.,
2004, 2016; Stendahl et al., 2013; Holmqvist et al., 2003; Koptsik et al.,
1999; Langan et al., 1995), the US (Phelan et al., 2014) and Asia (Fumoto et
al., 2001). At all 23 sites in the single-site comparison in this paper,
weathering estimates from PROFILE were available (Table 3).
The weathering submodel in PROFILE was later built in to the dynamic version
SAFE (Alveteg et al., 1995), which was mainly used for acidification
assessments, but has also been used for studying the dynamics of weathering
rates (Warfvinge et al., 1995). Later, the SAFE model was coupled with the
tree growth model PnET (Aber and Federer, 1992), the decomposition model
DECOMP (Walse et al., 1998; Wallman et al., 2004) and the hydrological model
PULSE (Lindström and Gardelin, 1992), resulting in the forest ecosystem
model ForSAFE (Wallman et al., 2005; Belyazid et al., 2006). The ForSAFE
model simulates the integrated biogeochemical processes of a forest
ecosystem. It covers the processes of photosynthesis, allocation and growth,
water and nutrient uptake, litterfall, organic matter decomposition and
mineralisation, ion exchange, chemical speciation of and reactions between
different elements, and hydrological transport. All process rates are
internally regulated by microenvironmental conditions such as acidity, water
availability, temperature and element concentrations. The model requires
inputs of external drivers in the form of climate, atmospheric deposition
and forest management, as well as inputs on the properties of the forest ecosystem,
such as soil texture, mineralogy and tree species. ForSAFE is used for
studying the effects of climate change, atmospheric deposition and forest
management on tree growth, soil chemistry and runoff water quality. Although
the weathering module is the same in PROFILE and ForSAFE, some differences
can be expected since ForSAFE includes dynamics, which means that weathering
is affected by other processes over time and that soil moisture, which is
an input in PROFILE, is dynamically modelled in ForSAFE. In the single-site
comparisons in this paper, weathering estimates from ForSAFE were available
at two sites (Table 3).
For the regional comparison of weathering rates of nutrient base cations
(Ca, Mg, K), regional runs from both PROFILE and ForSAFE where included.
Regional PROFILE weathering estimations for Sweden were taken from Akselsson
et al. (2016), where weathering rates for the upper 50 cm of the soil
(including the organic layer) have been modelled based on data from 17 333
Swedish National Forest Inventory (NFI) sites (Fridman et al., 2014). Within
QWARTS, weathering rates to 50 cm depth (including the organic layer) were
modelled also with the ForSAFE model (Belyazid et al., 2019) on sites
in the SAFE database. The SAFE database is a subset, consisting of 640
sites, of the NFI sites used for PROFILE modelling.
The depletion method
Another widely used approach for estimating weathering rates is the
depletion method (e.g. Olsson et al., 1993; Starr et al., 1998; Stendahl et
al., 2013). The method estimates historical weathering, i.e. the average
weathering rate since the last deglaciation, of mobile (weatherable)
elements, based on element concentrations in weathered soil horizons as
compared to unweathered parent material. The method accounts for the general
losses of soil material in a horizon by including an immobile (recalcitrant)
element in the estimation. Concentrations of mobile elements will decrease
as a result of weathering, while the immobile element will be enriched
towards the soil surface. The concept has a long history (Marshall and
Haseman, 1942), while the theoretical framework was later formalised by
Brimhall and Dietrich (1987) and Brimhall et al. (1991). The most commonly
used immobile element is zirconium, which is found in the resistant mineral
zircon (ZrSiO4) with negligible weathering (Hodson, 2002). The assumptions
for the depletion method are as follows: (1) there is no weathering of the immobile
element; (2) the soil pedon consists of homogeneous soil, where the deep
soil constitutes the parent material; and (3) no weathering occurs beyond a
certain depth. The average annual weathering rate is calculated from the
soil age, i.e. the time since deglaciation or since the land rose from the
sea due to glacio-isostatic uplift. The average rate may deviate from
current levels depending on the variation in weathering rates over time
(Taylor and Blum, 1995). Weathering rates from the depletion method were
available for 18 of the 23 sites in the single-site comparison (Table 3).The
depletion method has been used, in combination with the total analysis
regression approach, for regional applications (see Sect. 2.3).
Total analysis regression approach
The total analysis regression approach is a derivative from the depletion
method, which requires much less soil data than the depletion method. It is
based on the fact that weathering rates of different elements have been
found to correlate with total content of the elements in soil and
temperature (Olsson and Melkerud, 1990). Based on weathering estimates from
the depletion method, linear regressions containing total chemical contents
for base cations in the C horizon (either separately or lumped together),
and temperatures or temperature sums (i.e. daily mean temperature above a
threshold value, summarised for the growing season), have been produced for
a number of sites, and the regressions have then been applied to other sites
(Sverdrup et al., 1998; Maxe, 1995; Olsson et al., 1993). In the single-site
comparison, estimates based on the total analysis regression approach were
available for three sites (Table 3).
On a regional level in Sweden, weathering rates for Ca, Mg and K have been
calculated based on the depletion method in combination with the total
analysis regression approach, as a basis for assessments of nutrient
sustainability after whole-tree harvesting (Olsson et al., 1993). In the
study from 1993, regressions between weathering rates calculated with the
depletion method and different site factors were analysed on 11 sites. The
strongest relationships were found between weathering rates of an element
and the product of the concentration of the element in the C horizon and the
temperature sum. In the present study, the regression functions in Olsson et
al. (1993) were used to calculate weathering rates of Ca, Mg and K at the
sites from the SAFE database that were modelled with both PROFILE and
ForSAFE (see above), for a proper comparison. The temperature sum was
calculated based on latitude and altitude according to Morén and Perttu
(1994). Some of the calculations gave negative results for one of the base
cations. This can be explained by the fact that the regressions are used for
a new dataset, covering a broader range of temperature sums than the
original dataset, which illustrates a limitation of the method. The
estimations apply down to the weathering depth, which means different soil
depths on different sites but normally between 40 and 70 cm in the mineral
soil (Mats Olsson, personal communication, 2002).
Budget approach
Weathering rates can also be estimated through the budget approach (Paces,
1986; Lundström, 1990; Sverdrup and Warfvinge, 1991; Sverdrup et al.,
1998). In the budget approach, sources and sinks of base cations are
considered, and weathering is calculated as the difference between sinks and
sources. However, one difficulty is to distinguish between weathering,
changes in the exchangeable pool and net mineralisation, so a steady state is
often assumed, and the weathering rates are calculated as leaching + net
uptake - deposition. The budget approach has been applied at five of the
sites in the site-level comparison (Table 3). In Svartberget in northern
Sweden the simplified approach assuming steady state was used
(Lundström, 1990). On two sites in Gårdsjön in southwestern
Sweden, net mineralisation was estimated and considered in the weathering
estimations, but changes in the exchangeable pool were disregarded (Sverdrup
et al., 1998). Casetou-Gustafson et al. (2019b) estimated weathering
rates based on measurements of atmospheric deposition, leaching,
accumulation in biomass and changes in the soil exchangeable pool for
control plots of long-term fertilisation experiments in young Norway spruce
forests in Asa and Flakaliden, in southern and northern Sweden,
respectively. When using weathering estimates from the budget approach, the
assumptions used must be carefully evaluated (Sverdrup and Warfvinge, 1991;
Rosenstock et al., 2019).
The budget approach can also be applied by using the MAGIC model (Cosby et
al., 2001), which was developed to predict effects of acidic deposition on
surface water acidification. Weathering is not mechanistically modelled as
in the models described above; instead, weathering rates are calculated
internally using mass balances (Maxe, 1995; Köhler et al., 2011). MAGIC handles input fluxes – atmospheric deposition and base cation weathering – and output fluxes – net uptake in biomass and runoff losses. These fluxes
govern processes in the soil, e.g. cation exchange, with the pool of
exchangeable base cations in the soils at the centre. When the fluxes change
over time, it affects the chemical equilibria between soil and soil
solution, which has an impact on surface water chemistry. Observed values of
surface water and soil chemistry are used to calibrate the model. Weathering
rates from MAGIC were available at two of the sites in the site-level
comparison (Table 3).
Another way of applying the budget approach is to use the strontium (Sr)
isotope ratio. In weathering estimations based on Sr isotope ratios, the
difference in the ratio 87Sr/86Sr in bedrock and in atmospheric
deposition is used (Wickman and Jacks, 1991). Since soil water is a mixture
of what comes from deposition and what comes from weathering, the weathering
rate of Sr can be estimated. Ca and Sr follow each other closely in forests
(Wickman and Jacks, 1991), so the weathering of Ca is assumed to be linearly
correlated to the weathering of Sr in the calculations. This method was used
at three sites in the site-level comparison (Table 3). The base cation/Ca
fraction was assumed to be constant in all three studies.
Assessment of forest sustainability
Simplified budget calculations based only on weathering rates and harvest
losses (Olsson et al., 1993; Klaminder et al., 2011; Stendahl et al., 2013)
were performed for a selection of the sites in Table 3. The criteria that
had to be fulfilled for inclusion of a site were (1) availability of
weathering rate assessments for the root zone which in Swedish forest soils
is often defined as 0.5 m (Rosengren and Stjernquist, 2004) but in this study
included depths down to 0.7 m and (2) access to data on site quality.
Calculations were made for sites in spruce and pine forest.
The calculations of harvest losses were based on the site quality of the
forest (average growth rate per year during a forest rotation at optimal
conditions), reduced by 20 % to mimic actual conditions, and generalised
densities and nutrient base cation concentrations in different tree parts.
Two types of harvesting were considered, conventional stem-only harvesting
and whole-tree harvesting, where, in addition to stem, tops and branches are
removed for biofuel. It was assumed that, in whole-tree harvesting, all
stems and 60 % of the branches were harvested and that 75 % of the
needles were removed with the harvested branches. The methodology along with
densities and base cation concentrations used is more thoroughly described
in Akselsson et al. (2007).
Base cation weathering rates (sum of Ca, Mg, Na and K) for sites
where different methods have been applied for the same depth on the same
site (Fig. 2). The soil depth is around 0.50 m (with or without organic
layer; see Table 1), except for a few cases where greater depths are given.
The four spans to the right are intervals that were commonly used in the
critical load work of CCE (Coordination Centre for Effects) within the UNECE
Convention on Long-range Transboundary Air Pollution (LRTAP convention) (de
Vries, 1994; Umweltsbundesamt, 1996). The intervals correspond to weathering
rates for different parent material classes – acidic, intermediate and mafic – and different texture classes – coarse, medium (including the mix between
medium and course material) and fine (including the mix between fine and
medium material).
Results and discussionWeathering rate comparisons at the site level
The single-site comparison enabled us to quantify the span of base cation
weathering rates produced by the different approaches (Fig. 3, Table 3). The
median weathering rates for the 23 sites spanned between 22 and 61 meqm-2yr-1 (Table 3). For two of the six sites where at least three
approaches had been applied, the weathering rate spans were narrow:
Gårdsjön B (49–62 meqm-2yr-1 and a maximum deviation
from the median of +15 %) and Gårdsjön C (36–40 meqm-2yr-1 and a maximum deviation from the median of ±5 %). The
span was somewhat wider in two of the other well-investigated sites:
Stubbetorp (35–67 meqm-2yr-1 and a maximum deviation from the
median of +56 %) and Flakaliden (34–61 meqm-2yr-1 and a maximum deviation from the median of +42 %). The weathering rate spans
in Svartberget B and Asa, with four and three weathering estimates
respectively, were remarkably wide: 31–85 meqm-2yr-1 and a maximum deviation from the median of +121 % in Svartberget B and 11–131 meqm-2yr-1 and a maximum deviation from the median of 254 % in
Asa. The wide spans in Asa and Svartberget B were mainly due to
substantially higher weathering rates according to the budget approach as
compared with the other methods. Also, in Flakaliden, the span was expanded
by the budget approach.
In Svartberget B, the weathering estimates from the budget approach can be
expected to be overestimated for several reasons (Lundström, 1990). The
method does not distinguish between weathering, base cation exchange and
base cation release through decomposition. The measurements were carried out
in the 1980s when the acidification process was taking place, leading to
base cation release from the exchangeable pool, although this effect was
much more pronounced in southern Sweden. Finally, dry deposition was not
included in the calculations due to lack of data. In Flakaliden and Asa,
base cation accumulation in biomass was the major sink in the mass balances.
The high weathering rates produced by the mass balances, especially in Asa,
were largely explained by the measured depletion of base cations in the soil
being much lower than the accumulation in the young Norway spruce stands
(Casetou-Gustafson et al., 2019b). The very high estimated weathering
rates, especially in Asa, indicate that flows are described inadequately.
Uptake occurring below the defined rooting zone could be one contributing
factor (Casetou-Gustafson et al., 2019b). In Asa, very low weathering
rates from the depletion method contributed to the wide span. The low
weathering rates originated from a fairly flat Zr depth gradient in the
soil, which indicates that the soil had probably been disturbed, so the
necessary assumptions for the depletion method were not satisfied
(Casetou-Gustafson et al., 2019b).
In Stubbetorp, the PROFILE estimates were substantially higher (67 meqm-2yr-1) than the estimates from the total analysis regression
approach and MAGIC (35–43 meqm-2yr-1). Maxe (1995) noted that the
PROFILE weathering rate was higher than expected, given the soil properties
in Stubbetorp, and argued that it may be due to unreasonably high specific
surface area of the soil as input to PROFILE on the site. Specific surface
area has been determined by BET analysis and could, according to Maxe
(1995), be overestimated due to a large occurrence of Al and Fe
precipitates.
Whereas weathering rates in the different sites in Gårdsjön (A, B
and C) and Svartberget (A and B) were generally on the same level, except
for the budget approach in Svartberget B as discussed above, the two sites
in Risfallet (A and B) gave quite different weathering rates: 29–68 meqm-2yr-1 in Risfallet A (0.5 m) and 25–29 meqm-2yr-1 in
Risfallet B (1 m). It could be expected that the weathering rates were
higher in the deeper soil profile, but instead it was the other way around.
The PROFILE-modelled weathering rate in Risfallet A is one of the highest of
all sites reported in Stendahl et al. (2013), which can be explained by a
relatively high clay content (7 %) and high soil bulk density. In
contrast, Risfallet B (1 m) has a very low specific surface area (Sverdrup
and Warfvinge, 1993), which can explain the low weathering rate produced by
the model.
In five of the 17 cases where only two methods per site were applied,
the maximum difference between the calculated median and the estimated
weathering rates was less than ±10 % (Table 3). In the other end,
five sites showed a corresponding difference between ±40 % and
±64 %. The results show that the width of the span varies
substantially between sites, and to explain these differences the sites and
the methods need to be studied in detail.
The weathering rates calculated with the depletion method for the 13 sites
from Stendahl et al. (2013) were generally lower than the PROFILE-modelled
weathering rates (Table 3). The two sites with largest difference,
Skånes Värsjö and Kloten, with a maximum difference between the
median and the estimated weathering rate of around ±60 %,
distinguished themselves with very low rates estimated with the depletion
method: 8 and 11 meqm-2yr-1. This is contrary to what was
expected, since the weatherability of the soil is believed to decrease over
time due to the depletion of more easily weathered minerals and formation of
resistant coatings on the mineral surfaces (Taylor and Blum, 1995). The
reasons for this discrepancy are not fully known, but one reason could be
that the original till partly comprises already weathered till from previous
glaciations (Stendahl et al., 2013). Moreover, it is likely that declining
weatherability over time is less pronounced in these young glacial till
profiles, where the easily weathered minerals remain in the profile.
Furthermore, some drivers of weathering, such as forest growth, are more
prominent today, which may overshadow long-term decline in soil
weatherability. For the total sum of base cations there was a tendency
towards higher modelled rates when the rates from the depletion method were
higher, but the relationship was weak (r2=0.20) on the 13 sites
(Stendahl et al., 2013). However, for Ca and Mg there was a much stronger
relationship: r2=0.46 for Ca and r2=0.64 for Mg. Thus, based
on current knowledge and models, it seems possible to identify a narrow
weathering rate interval for Ca and Mg weathering rates, but it seems
difficult for K and Na, as discussed in Stendahl et al. (2013).
At Västra Torup and Hissmossa, weathering rates produced by PROFILE and
ForSAFE were compared in detail for the first time. The results at
Västra Torup showed that the maximum difference between the modelled
weathering rates and the median was ±4 %. At Hissmossa, the
corresponding difference was ±9 %. Much of the difference could be
attributed to the difference between soil moisture input data in PROFILE and
modelled soil moisture in ForSAFE. The sandy soil in Hissmossa gave
substantially lower modelled soil moisture than the moisture estimates based
on field observations used as inputs to PROFILE, resulting in lower
weathering rates (Kronnäs et al., 2019).
The intervals of all sites were compared with four reference weathering
intervals, based on weathering rate approximations frequently used in the
critical load work (Fig. 3; de Vries, 1994; Umweltsbundesamt, 1996). The
majority of weathering rate estimates was within or close to the interval
outlined for acidic/intermediate parent material with coarse texture.
The weathering rates for the sites with 0.5 m soil depth (including
Gårdsjön G1 where the soil depth is 0.47 m) can roughly be divided
into four different groups depending on the intervals, except for four sites
with contradictory results (Table 4).
Classification of the sites with soil depth of approximately 0.5 m,
in four classes, based on intervals used in the critical load work of CCE
(Coordination Centre for Effects) within the UNECE Convention on Long-range
Transboundary Air Pollution (LRTAP convention) (de Vries, 1994;
Umweltsbundesamt, 1996): very low, low, and intermediate weathering rates
and a group with non-conclusive results, i.e. that did not fit into any of
the other groups. Sites were placed in one of the three weathering groups if
the median fell within the main interval given and if the maximum and
minimum values fell within the extended interval (±5). A and C refer
to different profiles, with different soil depths.
Very low weathering ratesLow weathering ratesIntermediate weathering ratesNon-conclusive resultsInterval10–37.5a (±5) meqm-2yr-137.5–60b (±5) meqm-2yr-1≥60cmeqm-2yr-1SitesVindelnGårdsjön A (0.5 m)FårahallHässlenHjärtasjöGårdsjön C (0.47 m)Risfallet ASöderåsenVästra TorupAsaStödeFlakalidenKullarnaSvartberget ABodaforsLammhultSkånes VärsjöKlotenHissmossa
a Corresponding to the lowest span in Fig. 3,
“acidic/intermediate parent material, coarse-textured”.b Corresponding to the lower part of the two
spans “acidic/intermediate parent material, medium-textured” and “basic
parent material, all grain sizes” in Fig. 3.c Corresponding to the upper part of the span
“acidic/intermediate parent material, medium-textured” and the
lower-intermediate part of the span “basic parent material, all grain sizes”
in Fig. 3.
The assessment of whether the weathering rate intervals are accurate enough
depends on their intended use. The weathering rates in relation to forest
sustainability assessments are analysed in Sect. 3.3.
Weathering rates on a regional scale on 346 National Forest
Inventory (NFI) sites, calculated with the depletion method/total analysis
regression approach (a), modelled with PROFILE (b) and with ForSAFE (c), in seven climate regions in Sweden, delimited by black lines.
Box plots for the three methods and for the climate regions: (2) inner part of northern Sweden, (3) coastal part of northern Sweden, (4) western part of central Sweden, (5) eastern part of central Sweden, (6) southwestern Sweden, and (7) southeastern Sweden. The Northwestern mountain
region (1) was excluded since it only contained one site.
Weathering rate comparisons at a regional scale
The weathering rates for the nutrient base cations Ca, Mg and K varied
widely within the regions for all methods, but there were no large
systematic differences between the medians or ranges for the different
methods (Figs. 4–5). However, PROFILE gave generally somewhat lower
weathering rates than ForSAFE and the depletion method/total analysis
regression approach, with overall medians of 14.3 mekvm-2yr-1
(PROFILE) and 17.8 mekvm-2yr-1 (ForSAFE and the depletion
method/total analysis regression approach).
For ForSAFE, this difference was most distinct in the northern regions. One
explanation regarding the difference between PROFILE and ForSAFE could be
differences in the method for estimating mineralogy from total chemistry,
where possible minerals have to be set by the modeller. Since qualitative
data on mineral contents in soils in most cases are not available at the
modelling sites, the mineralogy has to be estimated based on a number of
assumptions. In the ForSAFE database, limestone seems to have been set as a
possible mineral more often than in the PROFILE database, due to differences
in the assumptions made. Since even a small amount of limestone has a large
effect on weathering rates, the modelled Ca weathering rates were
substantially higher at some sites in the ForSAFE results.
The difference between PROFILE and the depletion method/total analysis
regression approach was contradictory to the site-level comparisons, where
PROFILE generally gave substantially higher weathering rates than the
depletion method (Table 3). This can partly be explained by the site-level
comparisons being made for the same depths (50 cm), whereas the regional
calculations with the depletion method/total analysis regression approach
gave the weathering to the maximum weathering depth, which is often more
than the 50 cm (including a 10 cm organic layer) used for PROFILE.
Methodological differences between the old and the new calculations for the
depletion method/total analysis regression approach can also be part of the
explanation, e.g. concerning how the weathering depth has been defined based
on curves of the elemental variation with depth, which is partly a
subjective operation. Finally, the fact that the regional calculations
combine two methods (depletion method and total analysis regression
approach), whereas the site-level estimates are based only on the depletion
method, may contribute to the differences.
In most cases, the width of the weathering rate intervals showed no major
differences between the regions. The difference between the 25th and the
75th percentile was generally 10 to 20 meqm-2yr-1 (Fig. 5). An
exception was region 5, the eastern part of central Sweden, where the
corresponding interval was up to 100 mekvm-2yr-1. In region 5,
lime-rich soils are common, which can explain this pattern. Other minor
differences were that the weathering rates in the southern regions were
generally on a somewhat higher level than the others (medians: 14–24 meqm-2yr-1), whereas the weathering rates in the western part of
central Sweden were towards the lower end (medians: 9–14 meqm-2yr-1).
Weathering rates of base cations calculated with different methods
on spruce sites, compared with harvest losses of base cations at whole-tree
harvesting (100 % of the stems and 60 % of the branches harvested, and
75 % of the needles on the branches removed). The horizontal dashed lines
in the harvesting bars show the levels for stem-only harvesting. The sites
are ordered from north to south.
Weathering rates of base cations calculated with different methods
on pine sites, compared with harvest losses of base cations at whole-tree
harvesting (100 % of the stems and 60 % of the branches harvested,
and 75 % of the needles on the branches removed). The horizontal dashed lines
in the harvesting bars show the levels for stem-only harvesting. The sites
are ordered from north to south.
Weathering in a sustainability perspective
Although the difference in weathering rates between methods is large on
several sites, a number of general conclusions could be drawn from the
comparison with harvest losses. For the stem-only harvesting scenario, the
harvest losses were generally at the same level or lower than PROFILE
weathering rates (Figs. 6–7). The harvest losses at stem-only harvesting were lower or at the same level as weathering rates according to the depletion
method in the northern sites but in most cases higher in the southern
sites.
Weathering rates estimated with different approaches and harvest
losses at conventional harvesting (CH, only stems) and whole-tree harvesting
(WTH, stems and branches) (meqm-2yr-1).
SiteTree speciesHarvest losses Weathering rates estimated with different methods CHWTHPROFILEDepletionBudgetTotal analysis regressionSvartberget ASpruce13213817FlakalidenSpruce1219433461StödeSpruce19324118KullarnaSpruce18303616HjärtasjöSpruce33552920Gårdsjön ASpruce33555241Gårdsjön BSpruce315257535448.5BodaforsSpruce37624122LammhultSpruce34563533AsaSpruce42703711131Skånes VärsjöSpruce4167378VindelnPine10133013RisfalletPine20256829KlotenPine17224211
In five of the seven spruce forests in southern and central Sweden (the
sites to the right in Fig. 6), the harvest losses in the whole-tree
harvesting scenario were higher than the weathering rates (5 %–740 %),
regardless of the method used to calculate weathering rates (Table 5, Fig. 6). The exceptions were Asa, where the weathering rates from the budget approach
gave a many times higher weathering rate than the other methods, and
Gårdsjön, where the weathering rates from most of the methods were
of a similar size to the harvest losses. Despite the variation between
methods, the results clearly indicate that whole-tree harvesting is not
sustainable in the long term in spruce forests in southern and central
Sweden, since the weathering rates generally are substantially lower than
the base cation losses at whole-tree harvesting.
On the four spruce sites in northern Sweden (to the left in Fig. 6), PROFILE
gave 20 %–130 % higher weathering rates than harvest losses after whole-tree
harvesting, whereas the depletion method gave 20 %–50 % lower weathering
rates than harvest losses for three of the four sites (Table 5, Fig. 6). The
budget approach in Flakaliden gave 220 % higher weathering rates than the
harvest losses after whole-tree harvesting. Despite the difference between
the methods, the results clearly indicate that the effects of whole-tree
harvesting in spruce forests in northern Sweden are substantially smaller
than for spruce forests in southern and central Sweden.
All pine sites where comparisons could be made in this study were situated
in northern or central Sweden (Fig. 2; Table 1). For all three sites, the
PROFILE weathering rates were substantially higher than the harvest losses,
both for the stem-only (150 %–240 %) and whole-tree harvesting scenario
(90 %–170 %) (Table 5, Fig. 7). Weathering rates calculated with the
depletion method were of a similar size to the harvest losses at whole-tree
harvesting, except for Kloten where the weathering rate was 50 % lower.
Thus, the conclusions about pine forests are similar to those for spruce
forests in northern Sweden, i.e. that long-term losses are less of a
concern, although the variation in weathering rates makes it difficult to
say whether the weathering rates are higher or lower than the harvest losses
in those forests.
In the above assessment, the extent to which whole-tree harvesting itself
affected the weathering rates was not explicitly considered. As an increased
forest harvest intensity leads to slightly more acidic conditions, it could
be hypothesised that increased intensity leads to an increased
proton-promoted dissolution of minerals, thereby providing a feedback
mechanism in which increased weathering could partially alleviate the effect
on soil acidity and base cation status. However, according to recent
HD-MINTEQ modelling in which PROFILE was used to simulate weathering, the
weathering rate was largely unaffected by soil solution pH and by the
harvesting method used (McGivney et al., 2019). This was explained as being
the net result of the opposing effects of pH and dissolved Al on the
weathering rate. While a decreased pH itself leads to an increased
weathering rate, it also leads to increased levels of dissolved Al, which is
a potent weathering “brake”, offsetting the pH effect. Another source of
uncertainties is the potential effect of whole-tree harvesting on mycorrhiza
activity, which is further discussed in Sect. 3.4 and in Finlay et al. (2019).
In the assessments of base cation sustainability, it is not only important
to focus on uncertainties in the actual soil weathering rates. Other
important topics are how much of the weathered material the tree roots can
reach; the size of the base cation deposition; the uncertainties in the
assessment of base cations through harvesting; and how the base cation
losses are distributed between soil, biomass and runoff water. The use of a
constant and static rooting depth introduces uncertainties in the
sustainability assessments, since root depth varies both spatially and
temporally, depending on variations in site conditions (Hodge, 2013;
Rosengren and Stjernquist, 2004). The base cation deposition in Sweden is
assessed to be of a similar size to the base cation weathering (Akselsson et
al., 2007), but a national survey of total base cation deposition, including
dry deposition, is not available, so uncertainties of base cation deposition
are large. The uncertainties in the assessments of base cation losses at
harvesting can be divided in uncertainties in the amount of biomass
extracted and the concentration of BC in biomass (Akselsson, 2005). A
sensitivity analysis for Ca showed that the lack of site-specific nutrient
concentration data was the main source of uncertainties in calculations of
harvest losses of Ca, whereas the estimations of biomass available for
extraction, and the amount of branches left on the ground, contributed less
to the uncertainties (Zetterberg et al., 2014). Finally, the effect of base
cation losses in soil is reduced by the fact that the rates of tree growth
and leaching decline after whole-tree harvesting, mitigating some of the
impacts of harvest on soil base cation status (Zetterberg et al., 2013;
Egnell, 2016).
Potential for biological weathering
Biological weathering often takes place in conjunction with physical and
chemical processes, but there is still disagreement over the extent of its
quantitative contribution to overall weathering (Finlay and Clemmensen,
2017; Leake and Read, 2017; Smits and Wallander, 2017). Insufficient
representation of biological weathering in weathering models such as
PROFILE, and its effects of weathering rate uncertainties, has been
frequently discussed (Finlay et al., 2009). Below, a description of how
biological weathering is presently represented in the PROFILE/ForSAFE models
is given, followed by a discussion about potential shortcomings in the light
of the latest research about biological weathering. A more thorough
description of the state of knowledge and a more comprehensive discussion
can be found in the article by Finlay et al. (2019).
Although the four weathering pathways, upon which PROFILE is built (the
reaction with H+, CO2 and DOC) are chemical (the dismantling of
mineral matrices by charged or dissolving particles to produce free
elements), their drivers are strongly dependent on biological activity in
the soil (Sverdrup and Warfvinge, 1993). Soil solution H+ is determined
by the charge balance resulting from uptake, ion exchange, mineralisation of
organic matter (solid and dissolved) and hydrological transport, all of
which are affected by biological activity. Water availability is directly
controlled by water uptake. The partial pressure of dissolved CO2 stems
from root and root symbiont respiration, decomposition and hydrological
transport. Finally, DOC is directly and indirectly produced by plants. The
transition state theory, governing the weathering kinetics in
PROFILE/ForSAFE, dictates that the net weathering rates should decline
towards zero near equilibrium. This is represented in the model by
retardation factors that increase in strength with the concentrations of the
weathering products (Erlandsson et al., 2016). These concentrations are in
turn dependent on biological activity, such as uptake reducing nutrient base
cation concentrations or the mobilisation of aluminium through biological
acidification.
Although the weathering process is strongly affected by biological processes
in the current generation of the PROFILE/ForSAFE family of models, the
models still fail to capture the biological feedback mechanisms in their
entirety. The possible roles of fungi, especially ectomycorrhizal fungi, in
biological weathering in boreal forests were summarised by Finlay et al. (2009) and have been the subject of many subsequent studies (Finlay et al.,
2019). These fungi can acidify their surrounding environment and
release organic acids and siderophores, which may enhance weathering. They
can also exert biomechanical forcing and alter interlayer spacing associated
with depletion of potassium from biotite (Bonneville et al., 2009).
Furthermore, recent work with atomic force microscopy has demonstrated
nanoscale alteration of surface topography of minerals and attachment and
deposition of organic biolayers by fungal hyphae (McMaster, 2012; Gazzè et
al., 2012, 2013; Saccone et al., 2012). Many fungal hyphae produce
extracellular polysaccharides (EPS) at their hyphal tips, providing an
interface that ensures intimate contact between the hyphae and mineral
substrates. The contact area between hyphae and mineral surfaces is
increased by EPS haloes (Gazzè et al., 2013), and many fungal exudation
products such as organic acids and siderophores may be released into
polysaccharide matrices (Flemming et al., 2016) in close proximity to
mineral surfaces. Here, they are effectively isolated from the bulk soil
solution and may be protected from microbial decomposition by antibiotic
compounds also produced by the fungi. This is in contrast to the assumption
in the models that soil solution is homogeneous at any given depth, not
discerning bulk solution from the said EPS haloes. This may increase the
effective concentrations of organic weathering agents at sites of active
weathering and structure the bacterial communities associated with
particular mycorrhizal fungi (Marupakula et al., 2016).
The potential mechanisms for biological enhancement of mineral weathering
and the current debate about the importance of these processes for overall
weathering are discussed in detail by Finlay et al. (2019). The
biological activity of symbiotic ectomycorrhizal fungi and the evolution of
their interactions with their tree hosts have led to systems that are highly
adapted to efficient recycling of plant nutrients from organic matter, as
well as the release of base cations from mineral substrates through weathering.
Ectomycorrhizal mobilisation of N and P through decomposition of organic
residues is dependent on carbon supplied from tree hosts. Mycorrhizal
weathering of minerals is also dependent on carbon supply from trees, and
ongoing experiments (Finlay et al., 2019) suggest that depletion of
organic substrates (containing N) will restrict tree growth and therefore
also reduce the carbon supply to ectomycorrhizal fungi colonising mineral
substrates, with concomitant, negative effects on base cation release from
biological weathering. Existing models are therefore probably sufficient to
give guidelines about sustainable forestry, including the prediction that,
under intensive forestry with removal of organic residues, base cation
supply will not be sustainable in the long term. However, the biological
feedbacks during transition from one state to another may not be fully
covered by the models. For instance, a forest exposed to N deposition may
pass from N limitation to limitation by another nutrient, which may have
consequences for belowground carbon allocation. Ectomycorrhizal fungi are
dependent on carbon supplied from their host plants and can be expected to
exert a stronger effect on mineral weathering if they have access to more
carbon, which may influence mobilisation of nutrients that are limiting. A
possible way to include the biological effects on mineral weathering would
be to better describe belowground carbon allocation in the models. Enhanced
weathering rates of apatite have been seen when host trees suffer from P
shortage, which is known to enhance belowground carbon allocation (Smits et
al., 2012). More elasticity in carbon allocation in the models is needed to
capture these empirical observations. Furthermore, carbon allocation will
also regulate exudation from roots and associated mycorrhizal fungi, which
is another process involved in mineral weathering that is not covered in the
models.
Implications of improved model descriptions of base cation exchange and
aluminium complexation
Aluminium (Al) and base cation concentrations are the primary weathering
brakes in unsaturated soil (Warfvinge and Sverdrup, 1992). Higher
concentrations of these elements have a negative effect on the dissolution
rates of the minerals containing the elements (Sverdrup et al., 2019).
It is therefore imperative to correctly simulate the concentrations of Al
and base cations in the soil solution.
Different soil chemical models simulate the dynamics of inorganic Al and
base cations in different ways. These can be classified into two categories:
(1) simpler ion-exchange equations (e.g. Gaines–Thomas or Gapon) that
conceptualise sorption and desorption of Al3+, H+ and base cations
as a series of ion-exchange reactions; and (2) more advanced organic
complexation models such as WHAM, NICA-Donnan or SHM (Tipping, 2002;
Kinniburgh et al., 1999; Gustafsson, 2001) that treat organic matter as the
main cation sorbent, where proton dissociation over a wide pH range drives
complexation and exchange of Al and base cations.
In general, the use of organic complexation models to simulate base cation
and Al dynamics is strongly supported by empirical evidence (e.g. Tipping,
2002), but for a long time, the simpler ion-exchange equations have been more
widely used in popular biogeochemical models such as MAGIC, PROFILE and
ForSAFE. However, in 1996, the CHUM model was introduced, which incorporates
a version of WHAM (Tipping, 1996), and today SMARTml and HD-MINTEQ provide
additional examples of (bio)geochemical codes that employ organic
complexation models (Bonten et al., 2011; Löfgren et al., 2017).
Gustafsson et al. (2018) investigated the implications of using the two
model approaches on the dynamics of Al, base cations and acidity. Overall,
the two model approaches provided the same type of response to changes in
input chemistry, implying that, in many cases, there may be a rather limited
benefit from using organic complexation models when calculating weathering
rates. However, although these results suggest that the current model setup
in for example ForSAFE may be sufficient in many cases, certain differences remain
between the two categories of models. The Gaines–Thomas and Gapon exchange
equations produce a relatively stronger buffering of soil solution pH over a
relatively narrow pH range. Together with the general oversimplification of
the cation binding process this also causes the ion-exchange equations to
overestimate the historical levels of exchangeable base cations (Gustafsson
et al., 2018). Consequently, it may be necessary to include organic
complexation under such conditions as prolonged or substantial changes in
acidic input, such as in the case of sea spray events. Not explicitly
simulating organic complexation may require additional coefficients that
account for temporal changes in cation selectivity to correctly predict pH,
base cations and Al, thereby entailing more uncertainty. Excluding organic
complexation can bring into question the ability of biogeochemical models to
predict the effect of large changes in acidic input on weathering rates
(Gustafsson et al., 2018).
Prospects for method development
Since quantifying uncertainties for weathering rates is difficult, the use
of multiple methods is often proposed as a way of increasing the robustness
of weathering rate estimates. However, the number of available methods is
low, and all are burdened with different types of limitations and
uncertainties. In the review of weathering studies in this paper, only six
locations could be found where at least three methods had been implemented
and where the criterion of the same depth was fulfilled. Thus, the
recommendation in Futter et al. (2012), that at least three independent
methods should be used to quantify weathering rates on a site for
sustainability assessments, is unrealistic. Nevertheless, comparisons between
weathering rates from different approaches for the same sites, and
continuous development of the different approaches, will contribute to more
robust sustainability assessments. In the next sections, the main uncertainties
and development potential related to process descriptions and input data for
PROFILE/ForSAFE are discussed, followed by uncertainties and potential
development areas for the depletion method/total analysis regression
approach and the budget approach.
PROFILE/ForSAFE – process descriptions
By far the most widely used, and most evaluated, method for estimating
weathering rates for soils in Sweden is the PROFILE model. The successful
testing of weathering rate modelling with ForSAFE (Kronnäs et al., 2019)
in QWARTS will be the starting point for more studies on weathering
dynamics, using ForSAFE. To better represent ectomycorrhizal fungi processes
in the PROFILE/ForSAFE models, and thus reduce uncertainties in modelled
weathering rates, three main improvements need to be made: (1) the EPS
microenvironments, described in Sect. 3.4, need to be determined in the field
and considered in models; (2) methods to distinguish between roots and
mycorrhizal hyphae need to be developed, to be able to better represent the
process of nutrient uptake and translocation towards the plant root; and (3) more elasticity in carbon allocation in the models is needed to be able to
better describe the carbon availability for fungi and to represent the
regulation of exudation from roots and associated hyphae.
The uncertainties in the simplified description of base cation exchange and
aluminium complexation were generally small, according to studies in QWARTS
(Gustafsson et al., 2018). However, we note that a modification would be
desirable concerning (1) long-term simulations over hundreds of years when
large changes occur in the chemical drivers and (2) sites experiencing
frequent or strong sea salt episodes causing large changes in the chemical
composition of the influent water.
Based on the assumption that weathering retardation is mainly caused by
elevated concentrations of base cations and aluminium, PROFILE/ForSAFE
produces reasonable weathering rates in the unsaturated rooting zone
(Sverdrup and Warfvinge, 1993; Erlandsson et al., 2016). However, moving
into the saturated zone, the strength of the usual weathering brakes fails
to slow down the mineral dissolution, which leads to grossly overestimated
rates of weathering (Stendahl et al., 2013; Erlandsson Lampa et al. (2019). In this environment, soil solution silicate concentrations play a
central role in hindering mineral dissolution (Sverdrup et al., 2019).
For this reason, the kinetics of silicate release from mineral dissolution
has been added to the traditional elements, as well as the dynamics of
silicate concentrations in the soil solution. Erlandsson Lampa et al. (2019) tested a prototype of this addition, and the results proved
promising in keeping weathering rates within observation levels in the
saturated zone, but this is yet to be implanted and tested in
PROFILE/ForSAFE.
Lateral flow has recently been included in ForSAFE, and a new version,
ForSAFE-2D, has been developed (Zanchi et al., 2016). The model has been
evaluated on the basis of hydrological flows and chloride concentrations and
transport, with good results. Evaluating the modelled base cation
concentrations in surface water highlighted the need for adjusting the
weathering brakes (see discussion above about silicate brakes) and also a
need to revisit the decomposition process descriptions, thereby validating
them for the saturated zone. Further development of ForSAFE-2D has the
potential to provide a mechanistic tool for assessing weathering rates also
for surface water applications. The importance of correctly defining the
flow pathways and residence times for the delivery of weathering products to
the surface waters, and the potential value of concentration–discharge
relationships for calibrating biogeochemical models, was explored by Ameli et
al. (2017).
PROFILE/ForSAFE – input data
Although continuously improved process descriptions are desirable to get
more robust weathering estimates, improvements related to input data are
more urgent. Mineralogy, specific surface area and soil moisture are of key
importance in weathering modelling but are often burdened with high
uncertainties. To reduce input data uncertainties, a focus should be placed
on those three parameters.
Mineralogy inputs to PROFILE/ForSAFE are often estimated from total
chemistry with the A2M model (“Analysis to Mineralogy”, Posch and Kurz,
2007), since direct mineralogy measurements are not available on most sites.
To accurately estimate a probable mineralogy, not only are good soil
chemistry measurements required, but also information about which minerals
can be expected in the soil. In Sweden, four different geographical
mineralogy regions have been used since the 1990s to assign qualitative
mineralogy to a site (Warfvinge and Sverdrup, 1995). Casetou-Gustafson et
al. (2019a) compared weathering rates calculated based on three sets of
mineralogies: one based on direct measurements of quantitative mineralogy,
one based on normative modelling with A2M using direct measurements of
qualitative mineralogy, and one based on normative modelling with A2M using
data from the regions mentioned above. It could not be concluded that the
A2M runs based on direct measurements of qualitative mineralogy gave better
results. Although these results strengthen the credibility for the normative
mineralogy regions, Casetou-Gustafson et al. (2019a) recommend continued work
to reduce uncertainties related to mineralogy, mainly by revisiting and, if
appropriate, updating mineral rate coefficients. More comparisons of
weathering rates from normative mineralogies based on generalised and
site-specific quantitative mineralogy are needed to adequately assess
whether the regional divisions need to be revised and refined in order to
further reduce the uncertainties in the mineralogy estimates.
A2M gives as output a multidimensional space of solutions, all of which have
the same probability. Often, the centre point of the space is used for
weathering calculations. However, the span can be quite broad, which leads
to uncertainties in the calculated weathering rates (Casetou-Gustafson et
al., 2019a). Future research focusing on constraints that could help to
narrow the space of possible solutions that A2M creates, e.g. based on the
grain size distribution, could reduce those uncertainties.
Minerals are assumed to be evenly distributed among grain sizes in PROFILE
and ForSAFE. The effect of this assumption has not been fully analysed. The
most obvious example showing that minerals are not evenly distributed among
grain sizes is clay minerals, which are found in the clay fraction. The
extremely high surface area of clays leads to very high base cation
weathering rates when the clay fraction is high, although the content of
base cations is low. Due to this, Phelan et al. (2014) introduced a
correction factor. A thorough analysis of all grain size fractions can help
to further refine these methods.
The surface area of soils is often calculated with regressions based on old
BET measurements (Warfvinge and Sverdrup, 1995). The regressions reveal that
the uncertainties are large. Revisions of the regressions, based on a larger
data material, could reduce the uncertainties.
The soil moisture is one of the most important factors that introduces large
uncertainties in the results, both in PROFILE where it is an input (Rapp and
Bishop, 2003) and in ForSAFE where it is modelled based on hydrological
parameters (Kronnäs et al., 2019). Improved input data quality for soil
moisture would substantially reduce uncertainties in PROFILE, and, even more
importantly, soil moisture modelled by ForSAFE needs to be evaluated, and
the sensitivity to soil input data needs to be examined.
The depletion method and the total analysis regression approach
Next to the PROFILE model, the depletion method is the most used method in
Sweden, often in combination with the total analysis regression approach. To
further evaluate the accuracy of results from the depletion method, as a
proxy for the weathering rates of today, the reliability of the assumptions
needs to be further evaluated, and the relationship between the average
weathering rate since the last glaciation and today's weathering rate needs
to be assessed. The latter can be done by performing ForSAFE modelling on a
site where the depletion method has been applied. A similar exercise has
been done with the SAFE model (Warfvinge et al., 1995), but the inclusion of
tree growth and decomposition in ForSAFE can be expected to improve the
results. Furthermore, standardised methods for setting the weathering depth
based on the elemental content curve and for the analysis of fulfilment of
the requirements in the soil profile would enable objective and comparable
estimates, including requirements that must be fulfilled for soil profiles
to be regarded as undisturbed. The total analysis regression approach will
give more robust results if more depletion method estimates are available
for the regressions.
The budget approach
Different applications of the budget approach handle the distinction between
sources of base cations in the soil in different ways, affecting the
uncertainties in the estimated weathering rates. The uncertainties in base
cation deposition add to the overall uncertainties. For a fair comparison
between weathering rates from the budget approach and from other methods,
ways to distinguish between different sources and sinks need to be further
developed.
An advantage of the budget approach using the Sr isotope ratio is that it
can distinguish between weathering and release from the exchangeable pool.
As for all budget approaches, deposition and leaching measurements are
required as inputs. The few comparisons made in this study show promising
results, and we therefore encourage estimates on more sites to enable
evaluation of the budget approach based on the Sr isotope ratio.
In the MAGIC model, the release from the exchangeable pool is thoroughly
modelled, but for other sources and sinks of base cations, the same problems
apply as for other budget approaches, e.g. uncertainties in base cation
deposition. These uncertainties exacerbate the uncertainties in weathering
rates that derive from the mass balances in MAGIC. Nevertheless, MAGIC
theoretically provides a good basis for conducting independent weathering
rate assessments. On sites with relatively small input data uncertainties,
our recommendation is to carry out such comparisons.
Conclusions
Uncertainties in weathering rates have often been presented as an obstacle
in the assessment of sustainable forestry. The comparison between approaches
in this paper, on a regional level as well as on a site level, suggests that
both weathering rate gradients and approximate weathering rate levels can be
captured with available methods. Although the variation in weathering
estimates was large on single sites, most of the sites could be grouped into
broader classes representing very low, low and intermediate weathering
rates, which can be used for general, but not specific, weathering rate
assessments at the site level. The more and better input data that are available, and the more methods that are applied and compared for a single site, the more robust the overall assessments that can be done at the site level are, provided that the conceptual differences, boundary conditions and assumptions between methods are kept in mind.
Based on the results from this study, we argue that modelled weathering
rates can be used for sustainability assessments, as long as the
uncertainties, i.e. the intervals on single sites presented in this paper,
are recognised. The ability to draw conclusions about sustainable forestry
at the site level depends not only on uncertainties in weathering rates, but
also on other site properties, related to forest properties and other base
cation flows, such as base cation deposition, and the associated
uncertainties. Irrespective of the uncertainties related to the
sustainability assessments, a robust conclusion was that weathering rates in
spruce forests in southern and central Sweden generally were substantially
lower than the harvest losses at whole-tree harvesting, indicating that
whole-tree harvesting without nutrient compensation is not sustainable in
these areas. There is less risk of a negative effect for spruce forests in
northern Sweden, as well as pine forests in central and northern Sweden.
The research performed in the five years of the QWARTS programme supports
the continued use of the PROFILE/ForSAFE models. ForSAFE is the only method
that gives time-resolved results, i.e. the only method that can be used to
study dynamic effects of changing climate and changing management methods.
Although there is still scope for improving process understanding and
incorporation of that understanding into PROFILE and ForSAFE, e.g. regarding
biological weathering and weathering brakes, the most important way to
reduce uncertainties in modelled weathering rates is to reduce input data
uncertainties, mainly regarding soil texture and associated hydrological
parameters. However, it is also important to continue to compare with
results from the depletion method and the budget approach.
Data availability
Weathering data presented in this synthesis paper are compiled from other studies, which are published in other papers and referred to in the paper.
Author contributions
CA planned and led the work, performed most of the calculations
and wrote most parts of the paper. KB and SB were highly
involved in the planning and writing of the paper from the start. SB
particularly contributed to the parts about modelling, including the
chapters about biological weathering and the implications of higher-resolution chemical reactions. JS mainly contributed to parts about
the depletion method and the total analysis regression approach, including
the recalculation of weathering rates on a national scale using those
methods. RF was the main author of the chapters about biological
weathering, to which HW and SB also substantially
contributed. BAO contributed to the methods descriptions, results
and discussions concerning the budget approach. JPG wrote about
the implications of higher-resolution chemical reactions together with SB and contributed to other parts in the paper where the chemistry in
the weathering models was discussed. MEL's main contributions
concerned the modelling parts and the parts about weathering brakes.
Competing interests
The authors declare that they have no conflict of interest.
Special issue statement
This article is part of the special issue “Quantifying weathering rates for sustainable forestry (BG/SOIL inter-journal SI)”. It is not associated with a conference.
Acknowledgements
This study was funded by the Swedish Research Council Formas (reg. no. 212-2011-1691) within the strong research environment Quantifying weathering
rates for sustainable forestry (QWARTS).
Financial support
This research has been supported by the Swedish Research Council Formas (reg. no. 212-2011-1691).
Review statement
This paper was edited by Suzanne Anderson and reviewed by two anonymous referees.
ReferencesAber, J. D. and Federer, C. A.: A generalized, lumped-parameter model of
photosynthesis, evapotranspiration and net primary production in temperate
and boreal forest ecosystems, Oecologia, 92, 463–474,
10.1007/BF00317837, 1992.
Akselsson, C.: Regional Nutrient Budgets in Forest Soils in a Policy
Perspective, PhD thesis, Department of Chemical Engineering, Lund
University, Lund, Sweden, 2005.Akselsson, C., Holmqvist, J., Alveteg, M., Kurz, D., and Sverdrup, H.:
Scaling and mapping regional calculations of soil chemical weathering rates
in Sweden, Water Air Soil Pollut.-Focus, 4, 671–681,
10.1007/978-94-007-0952-2_46, 2004.Akselsson, C., Westling, O., Sverdrup, H., Holmqvist, J., Thelin, G., Uggla,
E., and Malm, G.: Impact of harvest intensity on long-term base cation
budgets in Swedish forest soils, Water Air Soil Pollut.-Focus, 7,
201–210, 10.1007/978-1-4020-5885-1_22, 2007.Akselsson, C., Hultberg, H., Karlsson, P. E., Pihl Karlsson, G., and
Hellsten, S.: Acidification trends in south Swedish forest soils 1986–2008:
slow recovery and high sensitivity to sea salt episodes, Sci.
Total Environ., 444, 271–287, 10.1016/j.scitotenv.2012.11.106, 2013.Akselsson, C., Olsson, J., Belyazid, S., and Capell, R.: Can increased
weathering rates due to future warming compensate for base cation losses
following whole-tree harvesting in spruce forests?, Biogeochemistry, 128,
89–105, 10.1007/s10533-016-0196-6, 2016.Alveteg, M.: Projecting regional patterns of future soil chemistry status in
Swedish forests using SAFE, Water Air Soil Pollut.-Focus, 4, 49–59,
10.1007/978-94-007-0952-2_4, 2004.Alveteg, M., Sverdrup, H., and Warfvinge, P.: Regional assessment of the
temporal trends in soil acidification in southern Sweden, using the SAFE
model, Water Air Soil Pollut., 85, 2509–2514,
10.1007/BF01186211, 1995.Ameli, A. A., Beven, K., Erlandsson, M., Creed, I. F., McDonnell, J. J., and
Bishop, K.: Primary weathering rates, water transit times, and
concentration-discharge relations: A theoretical analysis for the critical
zone, Water Resour. Res., 53, 942–960, 10.1002/2016WR019448,
2017.Banfield, J. F., Barker, W. W., Welch, S. A., and Taunton, A.: Biological
impact on mineral dissolution: application of the lichen model to
understanding mineral weathering in the rhizosphere, P.
Natl. Acad. Sci. USA, 96, 3404–3411,
10.1073/pnas.96.7.3404, 1999.Belyazid, S., Westling, O., and Sverdrup, H.: Modelling changes in forest
soil chemistry at 16 Swedish coniferous forest sites following deposition
reduction, Environ. Pollut., 144, 596–609,
10.1016/j.envpol.2006.01.018, 2006.Belyazid, S., Akselsson, C., and Zanchi, G.: Water limitation may restrict the positive effect of higher temperatures on weathering rates in forest soils, Biogeosciences Discuss., 10.5194/bg-2019-44, in review, 2019.Bonneville, S., Smits, M. M., Brown, A., Harrington, J., Leake, J. R.,
Brydson, R., and Benning, L. G.: Plant-driven fungal weathering: Early
stages of mineral alteration at the nanometer scale, Geology, 37, 615–618,
10.1130/G25699A.1, 2009.Bonten, L. T. C., Groenenberg, J. E., Meesenburg, H., and de Vries, W.: Using
advanced surface complexation models for modelling soil chemistry under
forests: Solling forest, Germany, Environ. Pollut., 159, 2831–2839,
10.1016/j.envpol.2011.05.002, 2011.Börjesson, P., Hansson, J., and Berndes, G.; Future demand for
forest-based biomass for energy purposes in Sweden, Forest Ecol.
Manag., 383, 17–26, 10.1016/j.foreco.2016.09.018, 2017.Brantley, S. L., Kubicki, J., and White, A. F. (Eds.): Kinetics of Water-Rock
Interaction, Springer, New York, 858 pp., 10.1007/978-0-387-73563-4,
2008.Brimhall, G. H. and Dietrich, W. E.: Constitutive mass balance relations
between chemical composition, volume, density, porosity, and strain in
metasomatic hydrochemical systems: Results on weathering and pedogenesis,
Geochim. Cosmochim. Ac., 51, 567–587,
10.1016/0016-7037(87)90070-6, 1987.Brimhall, G. H., Lewis, C. J., Ford, C., Bratt, J., Taylor, G., and Warin,
O.: Quantitative geochemical approach to pedogenesis: importance of parent
material reduction, volumetric expansion, and eolian influx in
lateritization, Geoderma, 51, 51–91, 10.1016/0016-7061(91)90066-3,
1991.Casetou-Gustafson, S., Hillier, S., Akselsson, C., Simonsson, M., Stendahl,
J., and Olsson, B.: Comparison of measured (XRPD) and modeled (A2M) soil
mineralogies: A study of some Swedish forest soils in the context of
weathering rate predictions, Geoderma, 310, 77–88,
10.1016/j.geoderma.2017.09.004, 2018.Casetou-Gustafson, S., Akselsson, C., Hillier, S., and Olsson, B. A.: The importance of mineral determinations to PROFILE base cation weathering release rates: a case study, Biogeosciences, 16, 1903–1920, 10.5194/bg-16-1903-2019, 2019a.Casetou-Gustafson, S., Grip, H., Hillier, S., Linder, S., Olsson, B. A., Simonsson, M., and Stendahl, J.: Current, steady-state and historical weathering rates of base cations at two forest sites in northern and southern Sweden: A comparison of three methods, Biogeosciences Discuss., 10.5194/bg-2019-47, in review, 2019b.Cosby, B. J., Ferrier, R. C., Jenkins, A., and Wright, R. F.: Modelling the effects of acid deposition: refinements, adjustments and inclusion of nitrogen dynamics in the MAGIC model, Hydrol. Earth Syst. Sci., 5, 499–518, 10.5194/hess-5-499-2001, 2001.
de Vries, W.: Soil response to acid deposition at different regional scales.
Field and laboratory data, critical loads and model predictions,
Cip-Gegevens Koninklijke Bibliotheek, Den Haag, 1994.Egnell, G.: Effects of slash and stump harvesting after final felling on
stand and site productivity in Scots pine and Norway spruce, Forest Ecol. Manag., 371, 42–49, 10.1016/j.foreco.2016.03.006, 2016.Erlandsson, M., Oelkers, E. H., Bishop, K., Sverdrup, H., Belyazid, S.,
Ledesma, J. L. J., and Köhler, S. J.: Spatial and temporal variations of
base cation release from chemical weathering on a hillslope scale, Chem.
Geol., 441, 1–13, 10.1016/j.chemgeo.2016.08.008, 2016.
Erlandsson Lampa, M., Sverdrup, H. U., Bishop, K. H., Belyazid, S., Ameli,
A. A., and Köhler, S. J.: Catchment export of base cations: Improved
mineral dissolution kinetics influence the role of water transit time, Biogeosciences Discuss., in
review, 2019.
Finlay, R. D. and Clemmensen, K. E. Immobilization of carbon in mycorrhizal
mycelial biomass and secretions, in: Mycorrhizal Mediation of Soil
Fertility, Structure, and Carbon Storage, edited by: Johnson, N. C., Gehring,
C., and Jansa, J., Elsevier, Amsterdam, 413–440, 2017.Finlay, R. D., Wallander, H., Smits, M., Holmstrom, S., Hees, P. V., Lian,
B., Rosling, A., and Finlay, R. D.: The role of fungi in biogenic weathering
in boreal forest soils, Fungal Biol. Rev., 4, 101–106,
10.1016/j.fbr.2010.03.002, 2009.Finlay, R. D., Mahmood, S., Rosenstock, N., Bolou-Bi, E. B., Köhler, S. J., Fahad, Z., Rosling, A., Wallander, H., Belyazid, S., Bishop, K., and Lian, B.: Biological weathering and its consequences at different spatial levels – from nanoscale to global scale, Biogeosciences Discuss., 10.5194/bg-2019-41, in review, 2019.Flemming, H. C., Wingender, J., Szewzyk, U., Steinberg, P., Rice, S. A., and
Kjelleberg, S.: Biofilms: an emergent form of bacterial life, Nat. Rev.
Microbiol., 14, 563–575, 10.1038/nrmicro.2016.94, 2016.Fridman, J., Holm, S., Nilsson, M., Nilsson, P., Hedström Ringvall, A.,
and Ståhl, G.: Adapting National Forest Inventories to changing
requirements – the case of the Swedish National Forest Inventory at the
turn of the 20th century, Silva Fennica, 48, 1095,
10.14214/sf.1095, 2014.Fumoto, T., Shindo, J., Oura, N., and Sverdrup, H.: Adapting the Profile
Model to Calculate the Critical Loads for East Asian Soils by Including
Volcanic Glass Weathering and Alternative Aluminum Solubility System, Water
Air Soil Pollut., 130, 1247–1252, 10.1007/978-94-007-0810-5_55,
2001.Futter, M., Klaminder, J., Lucas, R., Laudon, H., and Köhler, S.:
Uncertainty in silicate mineral weathering rate estimates: source
partitioning and policy implications, Environ. Res. Lett., 7,
1–8, 10.1088/1748-9326/7/2/024025, 2012.
Gardelin, M. and Warfvinge, P.: Databas, in: Modelling groundwater response
to acidification, edited by: Sandén, P. and Warfvinge, P., Report from
the Swedish integrated groundwater acidification project, SMHI, Reports
Hydrology, 13–29, 1992.Gazzè, S. A., Saccone, L., Ragnarsdottir, K. V., Smits, M. M., Duran, A.
L., Leake, J. R., Banwart, S. A., and McMaster, T. J.: Nanoscale channels on
ectomycorrhizal-colonized chlorite: Evidence for plant-driven fungal
dissolution, J. Geophys. Res.-Biogeo., 117, G00N09,
10.1029/2012JG002016, 2012.Gazzè, S. A., Saccone, L., Smits, M. M., Duran, A. L., Leake, J. R.,
Banwart, S. A., Ragnarsdottir, K. V., and McMaster, T. J.: Nanoscale
observations of extracellular polymeric substances deposition on
phyllosilicates by an ectomycorrhizal fungus, Geomicrobiol. J., 30,
721–730, 10.1080/01490451.2013.766285, 2013.Godderis, Y., Francois, L. M., Probst, A., Schott, J., Moncoulon, D., Labat,
D., and Viville, D.: Modelling weathering processes at the catchment scale:
The WITCH numerical model, Geochim. Cosmochim. Ac., 70, 1128–1147,
10.1016/j.gca.2005.11.018, 2006.Graf Pannatier, E., Thimonier, A., Schmitt, M., Walthert, L., and Waldner,
P.: A decade of monitoring at Swiss long-term forest ecosystem research
(LWF) sites: can we observe trends in atmospheric acid deposition and in
soil solution acidity?, Environ. Monit. Assess., 174, 3–30,
10.1007/s10661-010-1754-3, 2011.Gustafsson, J. P.: Modeling the acid-base properties and metal complexation
of humic substances with the Stockholm Humic Model, J. Colloid
Interf. Sci., 244, 102–112, 10.1006/jcis.2001.7871, 2001.Gustafsson, J. P., Belyazid, S., McGivney, E., and Löfgren, S.: Aluminium and base cation chemistry in dynamic acidification models – need for a reappraisal?, SOIL, 4, 237–250, 10.5194/soil-4-237-2018, 2018.Hedin, L, Granat, L., Likens, G., Buishand, A., Galloway, J., Butler, T.,
and Rodhe, H.: Steep declines in atmospheric base cations in regions of
Europe and North America, Nature, 367, 351–354, 10.1038/367351a0, 1994.Hodge, A.: Plant Uptake, in: Reference Module in Earth Systems and
Environmental Sciences, edited by: Elias, S. A., Elsevier,
10.1016/B978-0-12-409548-9.05232-5, 2013.Hodson, M.: Experimental evidence for mobility of Zr and other trace
elements in soils, Geochim. Cosmochim. Ac., 66, 819–828,
10.1016/S0016-7037(01)00803-1, 2002.Holmqvist, J., Ögaard, A. F., Öborn, I., Edwards, A. C., Mattsson,
L., and Sverdrup, H.: Application of the PROFILE model to estimate potassium
release from mineral weathering in Northern European agricultural soils,
Eur. J. Agron., 20, 149–163,
10.1016/S1161-0301(03)00064-9, 2003.
Irving, P. M.: Acidic deposition: state of science and technology: summary
report of the US National Acid Precipitation Assessment Program, National
Acid Precipitation Assessment Program, Office of the Director, Washington D.C., USA, 1991.Jacks, G. and Åberg, G. Calcium budgets for catchments as interpreted by
strontium isotopes, in: Surface Water Acidification Programme, edited by:
Mason, B. J., The Royal Society, The Royal Swedish Academy of Sciences, The
Norwegian Academy of Science and Letters, London, Stockholm, Oslo, 120–131,
10.2166/nh.1989.0007, 1987.Jönsson, C., Warfvinge, P., and Sverdrup, H.: Uncertainty in predicting
weathering rate and environmental stress factors with the PROFILE model,
Water Air Soil Pollut., 81, 1–23, 10.1007/BF00477253, 1995.Kinniburgh, D. G., van Riemsdijk, W. H., Koopal, L. K., Borkovec, M.,
Benedetti, M. F., and Avena, M. J.: Ion binding to natural organic matter:
stoichiometry and thermodynamic consistency, Colloid. Surface A, 151,
147–166, 10.1016/S0927-7757(98)00637-2, 1999.Klaminder, J., Lucas, R. W., Futter. M. N., Bishop, K. H., Köhler, S.
J., Egnell, G., and Laudon, H.: Silicate mineral weathering rate estimates:
are they precise enough to be useful when predicting the recovery of
nutrient pools after harvesting?, Forest Ecol. Manag., 261, 1–9,
10.1016/j.foreco.2010.09.040, 2011.Köhler, S., Zetterberg, T., Futter, M., Fölster, J., and
Löfgren, S.: Assessment of Uncertainty in Long-Term Mass Balances for
Acidification Assessments: A MAGIC Model Exercise, AMBIO, 40, 891–905,
10.1007/s13280-011-0208-7, 2011.Koptsik, G., Teveldal, S., Aamlid, D., and Venn, K.: Calculations of
weathering rate and soil solution chemistry for forest soils in the
Norwegian-Russian border area with the PROFILE model, Appl. Geochem.,
14, 173–185, 10.1016/S0883-2927(98)00048-1, 1999.Kronnäs, V., Akselsson, C., and Belyazid, S.: Dynamic modelling of weathering rates – the benefit over steady-state modelling, SOIL, 5, 33–47, 10.5194/soil-5-33-2019, 2019.Langan, S., Sverdrup, H., and Coull, M.: The calculation of base cation
release from the chemical weathering of Scottish soils using the PROFILE
model, Water Air Soil Pollut., 85, 2497–2502,
10.1007/BF01186209, 1995.
Leake, J. R. and Read, D. J.: Mycorrhizal symbioses and pedogenesis
throughout Earth's history, in: Mycorrhizal Mediation of Soil Fertility,
Structure, and Carbon Storage, edited by: Johnson, N. C., Gehring, C., and
Jansa, J., Elsevier, Amsterdam, 9–33, 2017.Lidskog, R. and Sundqvist, G.: The Role of Science in Environmental Regimes:
The Case of LRTAP, Eur. J. Int. Relat., 8,
77–101, 10.1177/1354066102008001003, 2002.
Lindström, G. and Gardelin, M.: Modelling groundwater response to
acidification, in: Modelling groundwater response to acidification, edited
by: Sandén, P. and Warfvinge, P., Report from the Swedish integrated
groundwater acidification project, SMHI, Reports Hydrology, Norrköping, Sweden, 33–36, 1992.Löfgren, S., Ågren, A., Gustafsson, J. P., Olsson, B. A., and
Zetterberg, T.: Impact of whole-tree harvest on soil and stream water
acidity in southern Sweden based on HD-MINTEQ simulations and
pH-sensitivity, Forest Ecol. Manag., 383, 49–60,
10.1016/j.foreco.2016.07.018, 2017.
Lundström, U.: Laboratory and lysimeter studies of chemical weathering,
in: The surface water acidification programme, edited by: Mason, B. J.,
Cambridge University Press, Cambridge, UK, 267–274, 1990.Maher, K., Steefel, C. I., White, A. F., and Stonestrom, D. A.: The role of
reaction affinity and secondary minerals in regulating chemical weathering
rates at the Santa Cruz Soil Chronosequence, California, Geochim.
Cosmochim. Ac., 73, 2804–2831, 10.1016/j.gca.2009.01.030, 2009.
Marshall, C. E. and Haseman, J. F.: The quantitative evaluation of soil
formation and development by heavy mineral studies: a Grundy silt loam
profile, Soil Sci. Soc. Am. Proc., 7, 448–453, 1942.Marupakula, S., Mahmood, S., and Finlay, R. D.: Analysis of single root tip
microbiomes suggests that distinctive bacterial communities are selected by
Pinus sylvestris roots colonized by different ectomycorrhizal fungi,
Environ. Microbiol., 18, 1470–1483, 10.1111/1462-2920.13102,
2016.
Mason, B. J. (Ed.): The Surface Waters Acidification Programme, Cambridge
University Press, Cambridge, UK, 1990.
Maxe, L. (Ed.): Effects of acidification on groundwater in Sweden.
Hydrological and hydrochemical processes, Report from the Swedish integrated
groundwater acidification project, Swedish Environmental Protection Agency,
Report 4388, 1995.McGivney, E., Gustafsson, J. P., Belyazid, S., Zetterberg, T., and Löfgren, S.: Assessing the impact of acid rain and forest harvest intensity with the HD-MINTEQ model – soil chemistry of three Swedish conifer sites from 1880 to 2080, SOIL, 5, 63–77, 10.5194/soil-5-63-2019, 2019.McMaster, T. J.: Atomic Force Microscopy of the fungi-mineral interface:
applications in mineral dissolution, weathering and biogeochemistry, Curr.
Opin. Biotech., 23, 562–569, 10.1016/j.copbio.2012.05.006,
2012.
Morén, A.-S. and Perttu, K.: Regional temperature and radiation indices
and their adjustment to horizontal and inclined forest land, Studia
Forestalia Suecica, No. 194, Swedish University of Agricultural Sciences, Uppsala, Sweden,
1994.
Nilsson, J. and Grennfelt, P.: Critical Loads for Sulphur and Nitrogen.
Report from a workshop held at Skokloster, Sweden, 19–24 March 1988,
Miljörapport 1988:15, 1988.
Odén, S.: Nederbördens och luftens försurning – dess orsak,
förlopp och verkan i olika miljöer. Bulletin nr. 1, Statens
Naturvetenskapliga Forskningsråd, Stockholm, Sweden, 1968.
Olsson, M. and Melkerud, P.-A.: Determination of weathering rates based on
geochemical properties of the soil, in: Proceedings of the Conference on
Environmental Geochemistry in Northern Europe, edited by: Pulkinene, E.,
Symposius series no. 34, Geological Survey of Finland, 45–61, 1990.Olsson, M., Rosén, K., and Melkerud, P.-A.: Regional modelling of base
cation losses from Swedish forest soils due to whole-tree harvesting,
Appl. Geochem., 2, 189–194, 10.1016/S0883-2927(09)80035-8, 1993.Paces, T.: Weathering rates of gneiss and depletion of exchangeable cations
in soils under environmental acidification, J. Geol.
Soc., 143, 673–677, 10.1144/gsjgs.143.4.0673, 1986.Phelan, J., Belyazid, S., Kurz, D., Guthrie, S., Cajka, J., Sverdrup, H.,
and Waite, R.: Estimation of Soil Base Cation Weathering Rates with the
PROFILE Model to Determine Critical Loads of Acidity for Forested Ecosystems
in Pennsylvania, USA: Pilot Application of a Potential National Methodology,
Water Air Soil Pollut., 225, 2109–2128,
10.1007/s11270-014-2109-4, 2014.Pihl Karlsson, G., Akselsson, C., Hellsten, S., and Karlsson, P. E.: Reduced
European emissions of S and N – effects on air concentrations, deposition
and soil water chemistry in Swedish forests, Environ. Pollut., 159,
3571–3582, 10.1016/j.envpol.2011.08.007, 2011.
Posch, M. and Kurz, D.: A2M – A program to compute all possible mineral
modes from geochemical analyses, Comput. Geosci., 33, 563–572,
2007.Rapp, L. and Bishop, K.: Modeling Surface Water Critical Loads with PROFILE:
Possibilities and Challenges, J. Environ. Qual., 32,
2290–2300, 10.2134/jeq2003.2290, 2003.Reuss, J. O. and Johnson, D. W.: Acid deposition and the acidification of
soils and waters, Ecological Studies 59, Springer Verlag, New York, USA,
10.1007/978-1-4419-8536-1, 1986.
Rosengren, U. and Stjernquist, I.: Gå på djupet! Om rotdjup och
rotproduktion i olika skogstyper, SUFOR – Sustainable forestry in Southern
Sweden, Alnarp, ISBN 9157666172 9789157666178, 2004.
Rosenstock, N., Stendahl, J., van der Heijden, G., Lundin, L., McGivney, E.,
Bishop, K., and Löfgren, S.: Base cations in the soil bank.
Non-exchangeable pools may sustain centuries of net loss to forestry and
leaching, Biogeosciences Discuss., in review, 2019.Saccone, L., Gazzè, S. A., Duran, A. L., Leake, J. R., Banwart, S. A.,
Ragnarsdottir, K. V., Smits, M. M., and McMaster, T. J.: High resolution
characterization of ectomycorrhizal fungal-mineral interactions in axenic
microcosm experiments, Biogeochemistry, 111, 411–425,
10.1007/s10533-011-9667-y, 2012.
Smits, M. M. and Wallander, H.: Role of mycorrhizal symbiosis in mineral
weathering and nutrient mining from soil parent material, in: Mycorrhizal
Mediation of Soil Fertility, Structure, and Carbon Storage, edited by:
Johnson, N. C., Gehring, C., and Jansa, J., Elsevier, Amsterdam, 35–46, 2017.Smits, M. M., Bonneville, S., Benning, L. G., Banwart, S. A., and Leake, J.
R.: Plant-driven weathering of apatite – the role of an ectomycorrhizal
fungus, Geobiology, 10, 445–456, 10.1111/j.1472-4669.2012.00331.x, 2012.
Starr, M., Lindroos, A.-J., Tarvainen, T., and Tanskanen, H.: Weathering
rates in the Hietajärvi Integrated Monitoring catchment, Boreal
Environ. Res., 3, 275–285, 1998.Stendahl, J., Lundin, L., and Nilsson, T.: The stone and boulder content of
Swedish forest soils, Catena, 77, 285–291,
10.1016/j.catena.2009.02.011, 2009.Stendahl, J., Akselsson, C., Melkerud, P.-A., and Belyazid, S.: Pedon-scale
silicate weathering: comparison of the PROFILE model and the depletion
method at 16 forest sites in Sweden, Geoderma, 211–212, 65–74,
10.1016/j.geoderma.2013.07.005, 2013.Sverdrup, H. and de Vries, W.: Calculating critical loads for acidity with
the simple mass balance method, Water Air Soil Pollut., 72, 143–162,
10.1007/BF01257121, 1994.
Sverdrup, H. and Warfvinge, P.: On the geochemistry of chemical weathering,
in: Chemical weathering under field conditions, edited by: Rosén, K.,
Reports from a Nordic seminar, 27–28 September 1990, Wik, Uppsala, Reports
in Forest Ecology and Forest Soils, Report 63, Swedish University of
Agricultural Sciences, 1991.Sverdrup, H. and Warfvinge, P.: Calculating field weathering rates using a
mechanistic geochemical model (PROFILE), Appl. Geochem., 8, 273–283,
10.1016/0883-2927(93)90042-F, 1993.
Sverdrup, H., Warfvinge, P., and Wickman, T.: Estimating the weathering rate
at Gårdsjön using different methods, in: Experimental Reversal of
Acid Rain Effects, edited by: Hultberg, H. and Skeffington, R., John Wiley
Sons Ltd, 1998.Sverdrup, H. U., Oelkers, E., Erlandsson Lampa, M., Belyazid, S., Kurz, D., and Akselsson, C.: Reviews and syntheses: Weathering of silicate minerals in soils and watersheds: Parameterization of the weathering kinetics module in the PROFILE and ForSAFE models, Biogeosciences Discuss., 10.5194/bg-2019-38, in review, 2019.Taylor, A. and Blum, J. D.: Relation between soil age and silicate
weathering rates determined from the chemical evolution of a glacial
chronosequence, Geology, 23, 979–982,
10.1130/0091-7613(1995)023<0979:RBSAAS>2.3.CO;2,
1995.Tipping, E.: CHUM – a hydrochemical model for upland catchments, J.
Hydrol., 174, 305–330, 10.1016/0022-1694(95)02760-2, 1996.
Tipping, E.: Cation Binding by Humic Substances, Cambridge University Press,
Cambridge, UK, 2002.
Umweltsbundesamt: Manual on methodologies and criteria for mapping critical
levels/loads and geographical areas where they are exceeded, UNECE
Convention On Long-range Transboundary Air Pollution, Texte 71/96, Berlin,
1996.
UNECE: Protocol to the 1979 Convention on Long-Range Transboundary Air
Pollution on Further Reductions of Sulphur Emissions, Article 1:8, 1994.van der Heijden, G., Bel, J., Craig, C. A., Midwood, A. J., Mareschal, L.,
Ranger, J., Dambrine, E., and Legout, A.: Measuring Plant-Available Mg, Ca,
and K Pools in the Soil – An Isotopic Dilution Assay, ACS Earth and Space
Chemistry, 2, 292–313, 10.1021/acsearthspacechem.7b00150, 2018.Wallman, P., Belyazid, S., Svensson, M., and Sverdrup, H.: DECOMP – a
semi-mechanistic model of litter decomposition, Environ. Modell.
Softw., 21, 33–44, 10.1016/j.envsoft.2004.09.026, 2004.Wallman, P., Svenssson, M., Sverdrup, H., and Belyazid, S.: ForSAFE – an
integrated process-oriented forest model for long-term sustainability
assessments, Forest Ecol. Manag., 207, 19–36,
10.1016/j.foreco.2004.10.016, 2005.Walse, C., Berg, B., and Sverdrup, H.: Review and synthesis of experimental
data on organic matter decomposition with respect to the effects of
temperature, moisture, and acidity, Environ. Rev., 6, 25–40,
10.1139/a98-001, 1998.Warfvinge, P. and Sverdrup, H.: Calculating critical loads of acid
deposition with PROFILE – A steady-state soil chemistry model, Water Air
Soil Pollut., 63, 119–143, 10.1007/BF00475626, 1992.
Warfvinge, P. and Sverdrup, S.: Critical load of acidity to Swedish forest
soils. Methods, data and results, Lund University, Department of Chemical
Engineering II, Lund, Sweden, 1995.Warfvinge, P., Sverdrup, H., Alveteg, M., and Rietz, F.: Modelling
geochemistry and lake pH since glaciation at lake Gårdsjön, Water
Air Soil Pollut., 85, 713–718, 10.1007/BF00476913, 1995.
Wickman, T. and Jacks, G.: Strontium isotopes as tools in weathering
research, in: Chemical weathering under field conditions, edited by:
Rosén, K., Reports from a Nordic seminar, 27–28 September 1990, Wik,
Uppsala, Reports in Forest Ecology and Forest Soils, Report 63, Swedish
University of Agricultural Sciences, 1991.Zanchi, G., Belyazid, S., Akselsson, C., Yu, L., Bishop, K., Köhler, S.,
and Grip, H.: A Hydrological Concept including Lateral Water Flow Compatible
with the Biogeochemical Model ForSAFE, Hydrology, 3, 1–19,
10.3390/hydrology3010011, 2016.Zetterberg, T., Olsson, B., Löfgren, S., von Brömssen, C., and
Brandtberg, P.-O.: The effect of harvest intensity on long-term calcium
dynamics in soil and soil solution at three coniferous sites in Sweden,
Forest Ecol. Manag., 302, 280–294,
10.1016/j.foreco.2013.03.030, 2013.Zetterberg, T., Köhler, S., and Löfgren, S. T.: Sensitivity
analyses of MAGIC modelled predictions of future impacts of whole-tree
harvest on soil calcium supply and stream acid neutralizing capacity,
Sci. Total Environ., 494–495, 187–201,
10.1016/j.scitotenv.2014.06.114, 2014.