Despite the importance of vegetation uptake of atmospheric gaseous elemental
mercury (Hg(0)) within the global Hg cycle, little knowledge exists on the
physiological, climatic, and geographic factors controlling stomatal uptake
of atmospheric Hg(0) by tree foliage. We investigate controls on foliar
stomatal Hg(0) uptake by combining Hg measurements of 3569 foliage samples
across Europe with data on tree species' traits and environmental conditions.
To account for foliar Hg accumulation over time, we normalized foliar Hg
concentration over the foliar life period from the simulated start of the
growing season to sample harvest.
The most relevant parameter impacting daily foliar stomatal Hg uptake was
tree functional group (deciduous versus coniferous trees). On average, we
measured 3.2 times higher daily foliar stomatal Hg uptake rates in deciduous
leaves than in coniferous needles of the same age. Across tree species, for
foliage of beech and fir, and at two out of three forest plots with more
than 20 samples, we found a significant (p<0.001) increase in
foliar Hg values with respective leaf nitrogen concentrations. We therefore
suggest that foliar stomatal Hg uptake is controlled by tree functional
traits with uptake rates increasing from low to high nutrient content
representing low to high physiological activity. For pine and spruce
needles, we detected a significant linear decrease in daily foliar stomatal
Hg uptake with the proportion of time during which water vapor pressure
deficit (VPD) exceeded the species-specific threshold values of 1.2 and
3 kPa, respectively. The proportion of time within the growing season during
which surface soil water content (ERA5-Land) in the region of forest plots
was low correlated negatively with foliar Hg uptake rates of beech and pine.
These findings suggest that stomatal uptake of atmospheric Hg(0) is
inhibited under high VPD conditions and/or low soil water content due to the
regulation of stomatal conductance to reduce water loss under dry
conditions. Other parameters associated with forest sampling sites (latitude
and altitude), sampled trees (average age and diameter at breast height), or
regional satellite-observation-based transpiration product (Global Land Evaporation Amsterdam Model: GLEAM) did not
significantly correlate with daily foliar Hg uptake rates. We conclude that
tree physiological activity and stomatal response to VPD and soil water
content should be implemented in a stomatal Hg model to assess future Hg
cycling under different anthropogenic emission scenarios and global warming.
Introduction
Mercury (Hg) is a toxic pollutant that is emitted by anthropogenic and
geogenic activities into the atmosphere, where it can be transported over
large distances and is eventually transferred to terrestrial and ocean
surfaces by dry or wet deposition (Bishop et
al., 2020). From a public health perspective, transfer rates of Hg to
aquatic ecosystems are particularly relevant within this cycle since Hg
bioaccumulation in fish for consumption represents the most important Hg
exposure pathway to many communities internationally
(UN Environment, 2019). In order to constrain
future Hg levels in edible fish and to assess how Hg exposure responds to
curbed anthropogenic Hg emissions under the policies implemented by the 2017
UN Minamata convention on mercury, it is essential to understand and
quantify all major net deposition fluxes within the global Hg cycle. Wet
deposition occurs when water-soluble oxidized Hg(II) is washed out from the
atmosphere with rainwater (Driscoll et
al., 2013; Sprovieri et al., 2017) or by cloud water interception
(Weiss-Penzias et al.,
2012). In a dry deposition process, gaseous elemental Hg(0) and Hg(II)
directly bind to surfaces (Bishop et al.,
2020), or Hg(0) is taken up by plants (Zhou et al., 2021). For more than 2 decades, vegetation has been recognized as an important vector for Hg(0) dry
deposition within the terrestrial Hg cycle
(Rea
et al., 1996, 2002; Grigal, 2003). Based on this seminal work, researchers
have since highlighted that vegetation impacts Hg levels of all other
environmental compartments within the active Hg cycle
(AMAP and UNEP,
2019; Bishop et al., 2020; Zhou et al., 2021). Vegetation uptake of Hg(0)
governs the seasonality of atmospheric Hg(0) in the Northern Hemisphere with
concentration minima in summer at the end of the growing season
(Jiskra et al.,
2018). Thus, vegetation has been suggested to operate like a global Hg pump
(Obrist, 2007;
Jiskra et al., 2018). Atmospheric Hg(0) taken up by vegetation is oxidized
to Hg(II) within the plant tissue
(Manceau et al., 2018) and
transferred to soils via litterfall
(Iverfeldt,
1991; Schwesig and Matzner, 2000; Rea et al., 2001; Graydon et al., 2008;
Risch et al., 2012, 2017; Jiskra et al., 2015; Wright et al., 2016; Wang et al.,
2016). Moreover, in forests, Hg deposition to the ground
may occur by wash-off of Hg(0) from plant surfaces via throughfall and by
Hg(0) uptake into woody tissues, lichen, mosses, and soil litter
(Wang et al.,
2020; Obrist et al., 2021). Mercury sequestered by forest ecosystems
accumulates in soil and may subsequently be transported from watersheds to
streams, rivers, and the ocean, where it can bioaccumulate in fish
(Drenner
et al., 2013; Jiskra et al., 2017; Sonke et al., 2018).
Concerning the mechanism of Hg accumulation in foliage, there are multiple
lines of evidence that leaf stomata control the foliar Hg(0) uptake flux to
terrestrial ecosystems: (i) Hg concentrations were found to be higher in
internal foliar tissues than on leaf surfaces
(Laacouri et al., 2013); (ii) experiments
revealed that isotopic Hg tracers are transferred from the air to the leaf
interior
(Rutter
et al., 2011); (iii) foliar Hg concentrations are associated with leaf
stomatal density and net photosynthesis
(Laacouri et
al., 2013; Teixeira et al., 2018); (iv) the isotopic composition of foliage
is discriminated in heavy isotopes compared to atmospheric Hg(0)
(Demers
et al., 2013; Enrico et al., 2016; Yu et al., 2016; Jiskra et al., 2019); and
(v) temporal and vertical variations in net foliar Hg(0) uptake fluxes in
trees agree with the mechanism of stomatal Hg(0) uptake
(Wohlgemuth et al., 2020). While
there is increasing consensus that vegetation uptake of atmospheric Hg(0)
occurs via the stomatal pathway, there remain research gaps regarding
parameters regulating this stomatal Hg(0) uptake
(Zhou et al., 2021). Consequently, the Hg(0) dry
deposition flux to terrestrial surfaces in Hg Earth system models is
generally parametrized by static inferential or resistance-in-series
approaches (Travnikov et al.,
2017). Ecosystem processes, including canopy gas exchange, are sensitive to
climate conditions (Running and Coughlan,
1988) and vary between different plant species
(Reich et al., 2003). Trees
control leaf diffusive gas fluxes through their stomata in order to optimize
the diffusive influx of carbon dioxide for photosynthesis while averting
excessive loss of water vapor to the atmosphere
(Körner, 2013). The regulation of stomata allows
trees to dynamically adjust their metabolism to climatic conditions
(temperature, atmospheric humidity, water vapor pressure deficit, solar
radiation) and site-specific limitations (soil moisture, nutrient
availability) under the constraints of tree-specific prerequisites (leaf
structure, leaf life span, water use efficiency).
In this study we aim to improve the process understanding of the stomatal
Hg(0) uptake with the long-term goal of advancing the parameterization of the
foliar Hg(0) uptake in Hg Earth system models. The objectives of the study
were (i) to investigate how foliar Hg(0) uptake depends on the
physiological traits of tree species and (ii) to study how the stomatal
response of trees to climate conditions controls foliar Hg(0) uptake. We
address these objectives by analyzing a large dataset of foliar Hg uptake
rates, tree functional traits, and climate conditions across natural
gradients in European forests covering various tree species and climate
conditions.
Material and methodsFoliage sampling and dataset description
The final dataset for this study comprises Hg concentrations of 3569
foliage samples from 2015 and 2017, of which 2129 samples were provided by
17 participating countries of the United Nations Economic Commission for Europe (UNECE) International Cooperative Programme
on Assessment and Monitoring of Air Pollution Effects on Forests (ICP
Forests). The samples include sun-exposed leaves and needles from the upper
third of the tree canopy of five trees (Austrian Bio-Indicator Grid: two trees)
of the main species on the plot taken during full development in summer
(deciduous species) or at the onset of dormant season in autumn (evergreen
species) using harmonized national methods according to the ICP Forests
Manual (Rautio et al., 2016) as described, for example, in
Jonard et al. (2015). Around 10 % of
samples were taken during winter needle sampling campaigns (December until
March). Sample preparation procedure typically includes separation of needle
age classes, drying, milling and chemical analyses for macronutrients, and
further drying of a subsample at 105 ∘C to constant weight for the
determination of dry weight. The participating ICP Forests countries
harvested and carried out these preprocessing steps and collected the
associated metadata. Hg measurements of samples from ICP Forests Level II
plots were performed at the University of Basel. Additional foliar Hg
concentration data of 1440 samples from the Austrian Bio-Indicator Grid
organized by the Austrian Federal Research Center for Forests (German
acronym BFW) (Austrian Bio-Indicator Grid, 2016) were included in the
analysis. The combined dataset consists of 3569 foliage samples
encompassing 23 species of coniferous and deciduous trees (Table S1 in
the Supplement). The
most frequent (number of samples >100) species within the
dataset are Norway spruce (Picea abies; n=2073), Scots pine (Pinus sylvestris; n=413), European
beech (Fagus sylvatica; n=372), silver fir (Abies alba; n=162), sessile oak (Quercus petraea; n=133),
Austrian pine (Pinus nigra; n=125), and common oak (Quercus robur; n=101). We pooled
individual tree species into groups of tree species genera (e.g., beech, oak,
pine, spruce; see Table S1). Coniferous samples consist of needles of
different age classes: most of the needle samples (n=1958) flushed in
the sampling season (current season; y0), 600 samples are 1-year-old
(y1), 121 samples are 2-year-old (y2), 125 are 3-year-old
(y3), 22 samples are 4-year-old (y4), 60 samples are 5-year-old (y5), and 3 samples are 6-year-old (y6) needles. All data
analysis of this study concerning tree species, foliage structure, nutrient
contents, and meteorological and site-specific parameters (Sects. 3.1–3.6)
is based on Hg values of current-season (y0) foliage. Foliage samples
originate from 995 European sites: 232 sites are ICP Forests Level II forest
monitoring plots, 737 locations are sampling sites of the Austrian
Bio-Indicator Grid, and the remaining sites (26) are not classified within
the ICP Forests program. See Fig. 1 for a
geographic overview of foliage sampling sites from the sampling year 2017.
Overview of forest plots at which Hg foliage samples were
harvested from different tree species groups during the sampling year 2017.
At around 12 % of plots in 2017, foliage from more than one tree species
group was sampled. Geographic distribution of sampling sites in 2015 is
similar, except there were no samples from the ICP Forests partners
Brandenburg (Germany), Baden-Württemberg (Germany), and Poland, and there
were samples from five additional plots in North Rhine-Westphalia (Germany);
see Fig. S1 in
the Supplement. The enlarged map view at the top right depicts sampling
locations of the Austrian Bio-Indicator Grid in 2015 and 2017. Use of base
map authorized under European Commission reuse policy (EU, 2011).
We assembled the foliar Hg concentration dataset including the following
metadata: sampling date, needle age class, leaf mass per area (LMA; 19 %
of samples), drying temperature, leaf nitrogen (N), and organic carbon
(Corg) concentration. Foliage concentrations of N and Corg were
measured in laboratories in respective ICP Forests countries following
strict quality assurance (QA) procedures. The tolerable quality limit for N concentration
measurements is ±15 % (for N concentration >5mgg-1) of the mean inter-laboratory N concentration in foliar reference
material distributed for ICP Forests laboratory comparison tests
(Rautio et al., 2016).
The measurements and observation from ICP Forests Level II forest plots
additionally included the beginning of the growing season for the sampling
years 2015 and 2017 (where available)
(Vilhar et al., 2013), main tree species on
the plot, mean age of trees on the plot (estimated during system
installment), basal area and trees per hectare on the plot
(Dobbertin and Neumann, 2016), soil texture of the upper
soil layer (mineral soil between 0–5 cm or 0–10 cm from the survey
years 2003–2019) (Fleck et al., 2016; Cools
and De Vos, 2020), altitude, and geographic coordinates. At the
tree level, metadata consist of tree species, tree number, and diameter at
breast height (Dobbertin and Neumann,
2016). Meteorological in situ measurements of hourly temperature and
relative humidity (Raspe et al., 2013)
were available for 82 forest Level II plots for both 2015 and 2017.
Furthermore, we amended the dataset with satellite-based values of
transpiration from the Global Land Evaporation Amsterdam Model (GLEAM)
(Miralles
et al., 2011; Martens et al., 2017) and of hourly soil water (layer 1, 0–7 cm) and surface air temperature (2 m height) from ERA5-Land
(Muñoz Sabater, 2019) for the respective regions of
every forest plot. GLEAM (v. 3.3a) data were available at daily resolution
and on a 0.25∘ latitude–longitude regular grid. ERA5-Land values
were available at hourly resolution and on a 0.1∘
latitude–longitude regular grid. For each forest plot, we calculated average
daily GLEAM (v.3.3a) transpiration within the life period of foliage
samples from the beginning of the growing season to harvest. Similarly,
from ERA5-Land values, we calculated the average 2 m air temperature within
respective sample life periods. We detected outliers of time-normalized
foliar Hg concentrations (see Sect. 2.3) within each tree species and needle
age class by applying the modified Z score method according to
Iglewicz and Hoaglin (1993) using an absolute threshold value of
3.5, above which a modified Z score value was considered an outlier. As a
result, 3.2 % of values within the dataset were removed as outliers.
Correction of foliar Hg concentrations for drying temperature
Drying and grinding of foliage samples were carried out by ICP Forests
laboratories and BFW. All foliar concentration values (Hg, N and Corg)
within the dataset are normalized to dry weight for a sample drying
temperature of 105 ∘C in order to make values internally
consistent. The actual drying temperature differed between foliage samples
(40–80 ∘C). In order to adjust for actual drying
temperature, the laboratories determined the drying factor to correct for
water content of each sample by drying an aliquot of foliage sample at
actual drying temperature and subsequently at 105 ∘C. The drying
factor was available for 62 % of samples within the dataset. For the rest
of the samples an average drying factor per tree species and needle age
class was applied for drying temperature correction. The smallest average drying
factor was 1.03±0.003 (mean ± sd) for 1-year-old (y1)
Pinus pinaster needles, and the biggest average drying factor was 1.07±0.02 (mean ± sd) for Quercus robur leaves. Previous studies did not detect Hg losses with
drying temperature in foliage
(Wohlgemuth
et al., 2020; Pleijel et al., 2021), wood (Yang et al.,
2017), or moss (Lodenius et al., 2003).
Foliage Hg analysis
Total Hg concentrations in foliage samples from ICP Forests Level II plots
were measured at the University of Basel using a direct mercury analyzer
(Milestone DMA-80, Heerbrugg, Switzerland). Standard operation procedure
involved measuring a pre-sequence of four blanks (three empty sample holders
and wheat flour) and three liquid primary reference standards (50 mg of 100 ngg-1 NIST-3133 in 1 % BrCl). If the three liquid primary reference
standards were within 90 %–110 % of expected value, we corrected all
measurement results of the respective sequence accordingly. Otherwise, we
discarded the sequence and re-calibrated the instrument. Standard reference
materials (SRMs) (NIST-1515 apple leaves and spruce needle sample B from the
19th ICP Forests needle–leaf interlaboratory comparison test: ILC) were
measured in each sequence (four SRMs in a sequence of 40 samples), and the
sequence was discarded if the measured SRM value was outside the certified
uncertainty range (NIST-1515) or outside ±10 % of the expected
concentration (ICP Forests spruce B). Absolute Hg content in wheat blanks
within the sequence had to be <0.3 ng. We successfully participated
in the 21st (2018/2019), 22nd (2019/2020), and 23rd
(2020/2021) ICP Forests needle–leaf ILC test.
Total Hg concentrations in foliage samples from the Austrian Bio-Indicator
Grid were measured using a Hg analyzer (Altec AMA 254 HCS, Prague, Czech
Republic). Standard operation procedure at BFW involved a pre-sequence of
five blanks (empty nickel boats) and measurements of three samples of
reference material (BCR-62 olive leaves or spruce needle samples from the
17th or 19th ICP Forests needle–leaf ILC test) after every
40th sample within a sequence. If the measurement results of the three
reference samples were outside of 93 %–107 % of expected value, a
drift correction was performed. Final foliage Hg concentrations within the
Austrian Bio-Indicator Grid represent average values of at least two replicates.
Determination of the beginning of the growing season for calculating daily foliage Hg uptake rates
Mercury concentrations in leaves and needles have been demonstrated to
increase linearly over the course of the growing season
(Rea
et al., 2002; Laacouri et al., 2013; Blackwell et al., 2014; Wohlgemuth et
al., 2020). In this study, foliage samples within the dataset were
harvested at various points in time, making a direct comparison of measured
Hg concentrations unfeasible. We therefore calculated foliar Hg uptake rates
(in ngHggd.w.-1d-1) of current-season samples by
normalizing foliar Hg concentrations to their respective life period in days
from the beginning of the growing season (emergence of new foliage) to date
of harvest. These resulting foliar Hg uptake rates are net Hg accumulation
rates per gram dry weight on a leaf basis and should not be confused with
foliar Hg fluxes on a whole-tree basis. Please also note that daily foliar
Hg uptake rates in this study represent average values over the growing
season. The actual daily foliar Hg uptake on a given day might differ from
the average value depending on the time period within the growing season
(e.g., early season versus peak season)
(Laacouri et al., 2013). Needles 1 year of age or older were excluded from calculating daily foliage Hg uptake fluxes
since Hg uptake might slow down in physiologically less active older needles
(Wohlgemuth et al., 2020), and it
is unclear to what extent Hg uptake occurs in older needles in winter and
in early spring before the emergence of new foliage. While dates of harvest
were available for all samples, we determined the start of the growing
season of current-season foliage by combining available data sources with
start-of-season modeling. These data sources comprise in situ phenological
observations, which were available for 15 % of samples, and observations
of the emergence of current-season needles of coniferous tree species from
the Pan European Phenological database PEP725
(Templ et al., 2018). We assigned
observations from PEP725 to the corresponding closest forest plot of the
respective sampling year (2015 or 2017) by using the nearest neighbor
function matchpt from the Biobase package in R (Huber et
al., 2015) such that differences between PEP725 observation and forest
plots did not exceed 3∘ in latitude or 30 m in altitude but matched longitude as closely
as possible. For details on the matching procedure and
results see Sect. S3.1 in
the Supplement. To model the beginning of
the growing season for deciduous trees, we utilized the leaf area index
(LAI) product of Copernicus Global Land Service based on PROBA-V satellite
imagery at a resolution of 300 m and 10 d
(Dierckx
et al., 2014; Fuster et al., 2020) following a recommendation by
Bórnez et al. (2020).
For information on the model and quality assurance, refer to Sect. S3.2 in
the Supplement.
Evaluation of data on water vapor pressure deficit (VPD)
At 82 ICP Forests Level II plots (in total from both sampling years 2015 and 2017),
in situ meteorological data at an hourly resolution were recorded in 2015
and 2017, for which we calculated hourly water vapor pressure deficit (VPD)
values for daytime (06:00–18:00 LT). The VPD represents the difference
between the water vapor pressure at saturation and the actual water vapor
pressure. We calculated saturated water vapor pressure from average hourly
air temperature using the August–Roche–Magnus formula
(Yuan et al., 2019) and actual water
vapor pressure as the saturation water vapor pressure multiplied by the
average hourly relative humidity. These VPD values were calculated
exclusively for daytime hours (06:00–18:00 LT) because both Hg(0) and
photosynthetic CO2 uptake by trees are at maximum during the day
(Obrist et al., 2021). From these
daytime hourly VPD values at each forest plot, we calculated the proportion
of hours within the daytime life period of the samples (from the beginning
of the growing season to sampling day), during which VPD exceeded the four
threshold values of 1.2, 1.6, 2, and 3 kPa, respectively. We
chose these four VPD thresholds as test values because they were reported in the
literature to incrementally induce leaf stomatal closure of temperate forest
trees, ranging from initial stomatal closure (around 0.8–1 kPa;
Körner, 2013) to maximum stomatal closure (at
around 3–3.2 kPa; CLRTAP, 2017). We calculated the
average proportion of daily daytime exceedance hours of VPD > respective threshold value by normalizing the total number of respective daytime
VPD exceedance hours with the total number of daytime hours during the
corresponding sample life period.
Evaluation of ERA5-Land volumetric soil water contents
We calculated the time proportion within sample life periods during which
the volumetric soil water content in the region of the respective forest
plots fell below a soil-texture-dependent threshold value (PAWcrit)
in which plants are expected to close their stomata due to limited water
availability. To this, we used the satellite-derived ERA5-Land data of
hourly soil water in soil layer 1 (vertical resolution: 0–7 cm;
horizontal resolution: 0.1∘×0.1∘)
(Muñoz Sabater, 2019) and data on soil texture of
the respective forest plots, where available (Fleck et
al., 2016). Field data from literature suggest that plant stomata start to
close once the plant available water (PAW) in the soil falls below a
critical value (PAWcrit)
(Domec
et al., 2009; Grünhage et al., 2011, 2012). The soil PAW represents the
difference between soil water at field capacity (SWFC) and soil water
at the permanent wilting point (SWPWP). We calculated PAWcrit=0.5×PAW+SWPWP following a recommendation by
Büker
et al. (2012) and used PAWcrit as the threshold value to calculate the
proportion of hours within the respective sample life periods during which
soil water <PAWcrit. See Fig. S11 in
the Supplement for an exemplary time
series of ERA5 soil water in the region of a forest plot in France in 2015.
Soil-texture-specific values for SWFC and SWPWP (Table S4 in
the Supplement) were
obtained from Saxton and Rawls (2006).
Results and discussionVariation in foliar Hg concentrations with foliar life period
Average foliar Hg concentrations (mean ± sd) differed between tree
species groups (see Table S1 for definition of tree species groups). Ash
leaves exhibited the highest Hg concentrations (32.2±5.7ngHggd.w.-1; n=10),
followed by beech leaves (25.5±9.6ngHggd.w.-1; n=372),
current-season Douglas fir needles (22.9±6.7ngHggd.w.-1; n=27),
hornbeam leaves (32.2±5.7ngHggd.w.-1; n=10),
oak leaves (20.8±9.1ngHggd.w.-1; n=287),
larch needles (13.4±3.4ngHggd.w.-1; n=3),
current-season spruce needles (11.8±3.4ngHggd.w.-1; n=1509),
current-season fir needles (11.4±2.8ngHggd.w.-1; n=66), and
current-season pine needles (11.0±5.1ngHggd.w.-1; n=344). For all tree
species sampled at more than 20 forest plots, we found significant (p<0.05) positive trends of foliar Hg concentrations with respective
sampling date within the growing season (see Fig. 2 for beech and oak and Fig. S4 in
the Supplement for pine and spruce).
Average leaf Hg concentrations (ngHggd.w.-1) in beech
and oak samples at multiple ICP Forests plots versus sampling dates (day of
year: DOY) of respective samples. Sampling took place both in 2015 and 2017.
Two plots of holm oak (Quercus ilex) are located in Greece and were sampled in December
2015 (DOY=348) and December 2017 (DOY=346). Error bars denote ± 1 standard deviation between multiple samples at each forest plot.
Increasing foliar Hg concentrations with progressing sampling date are in
line with previous observations demonstrating that at individual sites Hg
concentrations increased linearly over the growing season
(Rea
et al., 2002; Laacouri et al., 2013; Wohlgemuth et al., 2020; Pleijel et
al., 2021). To make Hg levels in foliage sampled at different times
comparable, we calculated daily foliar Hg uptake rates by normalizing foliar
Hg concentrations with the life period of samples. These daily foliar Hg
uptake rates represent average values over the life period. The average life
period (mean ± sd) of samples was 104±30 d for beech, 104±24 d for oak, 159±12 d for pine, and 148±14 d for
spruce. At 5 % of spruce plots sampling took place in winter
(December until March). Spruce and pine trees have been found to reduce
their physiological activity (transpiration, net photosynthesis) at low soil
temperatures (<8–10 ∘C), potentially impacting
stomatal Hg(0) uptake in winter
(Schwarz et al.,
1997; Mellander et al., 2004). The average daily Hg uptake rates of
current-season spruce needles sampled during peak season (0.084 ngHggd.w.-1d-1)
and sampled during winter (0.067 ngHggd.w.-1d-1) were significantly different (Welch two-sample
t test; p=0.015 at 95 % confidence level). If spruce trees continue to
accumulate Hg throughout the winter, Hg needle concentrations should be
higher in winter samples than in samples harvested earlier during the
growing season, and Hg uptake rates per day should be comparable between
winter and growing season samples. Thus, the difference of average daily Hg
uptake between winter and growing season spruce needle samples indicates a
decrease in Hg accumulation in spruce needles during winter. However, the
potential of needle Hg uptake in winter needles requires further
investigation, for example, by performing a full winter sampling at multiple forest
plots. For this study, we shortened the calculated life period of spruce
needles from winter sampling plots to 15 November
(Rötzer and Chmielewski, 2001) to improve comparability
of spruce needle Hg uptake rates within the dataset.
Variation in foliar Hg uptake rates with tree species groups
Median daily foliar Hg uptake rates (Fig. 3) in decreasing order are ash
(0.26 ngHggd.w.-1d-1), beech (0.25 ngHggd.w.-1d-1),
oak (0.22 ngHggd.w.-1d-1), hornbeam (0.20 ngHggd.w.-1d-1),
larch (0.14 ngHggd.w.-1d-1),
current-season Douglas fir needles (0.13 ngHggd.w.-1d-1),
current-season spruce needles (0.07 ngHggd.w.-1d-1),
current-season fir needles (0.07 ngHggd.w.-1d-1), and
current-season pine needles (0.05 ngHggd.w.-1d-1). The
range of daily foliar Hg uptake of beech (0.12–0.42 ngHggd.w.-1d-1) is in agreement with the daily foliar Hg uptake
rate of 0.35±0.03ngHgg-1d-1, which
Bushey et al.
(2008) had determined in beech leaves growing in New York State in 2005.
There are distinct differences in median daily Hg uptake rates between
current-season foliage of tree species groups (Fig. 3). The median daily
foliar Hg uptake rate of deciduous leaf samples is 0.23 ngHggd.w.-1d-1, a factor of 3.2 larger than the median daily
foliar Hg uptake rate of current-season conifer needle values (0.07 ngHggd.w.-1d-1). The difference between deciduous and
coniferous leaves in the European dataset is smaller than a previous
observation from a mixed forest site in Switzerland in 2018, where Hg uptake
rates of coniferous species were reported to be 5 times lower than those of
deciduous trees (Wohlgemuth et
al., 2020). Similarly,
Navrátil et al.
(2016) reported higher foliar Hg concentrations in beech leaves (36.3 ngHgg-1) than in current-season
spruce needles (14.1 ngHgg-1) of two
adjacent forest plots sampled during peak season (August). Higher Hg
concentrations in deciduous leaves (median: 28 ngHgg-1 from 341
remote sites) than in composite multi-age coniferous needles (median: 15 ngHgg-1 from 535 remote sites) were also reported in a global literature
compilation (Zhou et al., 2021). Differences in
daily foliar Hg uptake between tree species within one genus (e.g., Quercus petraea and
Quercus robur) were negligible (see Fig. S5 in
the Supplement). We were not able to normalize daily foliar
Hg uptake rates with atmospheric Hg(0) concentrations at each respective
sampling site and sample life period as air Hg(0) measurements were
unavailable for our sampling sites. The relative standard deviation of
average air Hg(0) concentrations at six European measurement sites within the
EMEP network
(Tørseth
et al., 2012; EMEP, 2021) between May and September 2015 and 2017 (see Table S2 in
the Supplement
for details) was 0.06, which is lower than the relative standard deviation
of the average daily Hg uptake rates between tree species and forest plots
of 0.64 (Fig. 3). We therefore argue that the
pronounced differences in median daily foliar Hg uptake rates between tree
species cannot exclusively be explained by differences in atmospheric Hg(0)
concentrations, but we rather suggest a tree physiological cause. However,
foliar Hg uptake rates should be normalized to ambient atmospheric Hg(0)
concentrations, in particular when comparing foliar Hg observation between
the Northern Hemisphere and Southern Hemisphere or over multi-decadal timescales.
Median daily foliar Hg uptake (ngHggd.w.-1d-1) between different tree species groups (see Table S1 for
definition of tree species groups) arranged from highest to lowest value.
Error bars give the value range within each tree species group, and n
indicates the number of sites at which the respective tree species were
sampled in both the years 2015 and 2017. Foliar samples of evergreen
coniferous tree species (Douglas fir, spruce, fir and pine) consist of
needles of the current season.
Foliar Hg uptake and sample-specific N concentration
Foliar N concentration serves as a surrogate for the maximum photosynthetic
capacity of foliage (Reich
et al., 1998) as the bulk amount of foliar N is contained in the
photosynthetic systems like chlorophylls, thylakoid proteins, and RuBisCO
(Evans, 1989; Körner, 2013;
Loomis, 1997). Furthermore, foliar N represents an indirect proxy for foliar
maximum stomatal diffusive conductance for water vapor, independent of tree
species
(Körner
et al., 1979; Bolton and Brown, 1980; Schulze et al., 1994; Reich et al.,
1999; Meziane and Shipley, 2001; Körner, 2013, 2018). Note that for
this analysis we solely compared N and Hg concentrations for foliage samples
harvested within a period of the growing season, during which leaf N
concentrations are relatively stable (July–August for broadleaves: Wilson et al., 2000;
Mediavilla and Escudero, 2003; and September–March for conifer needles:
Adams et
al., 1987; Hatcher, 1990). To assess the possibility of physiological
factors controlling the large variation in foliar Hg(0) uptake between
different tree species groups (Fig. 3), we compared average daily foliar Hg
uptake rates per tree species group with respective average foliar N
concentrations. We found a positive linear correlation between foliar N
concentration and Hg uptake rates as tree species groups with high average
foliar N exhibited higher daily foliar Hg uptake rates (Table 1). This observation supports the notion that the
physiological activity of trees controls foliar Hg(0) uptake, thereby
explaining the large variation among tree species groups
(Wohlgemuth et al., 2020). We
compared foliar Hg uptake rates and leaf N concentrations with values of
median stomatal conductance for beech, oak, pine, and spruce included in a
global leaf-level gas exchange database compiled by
Lin et al. (2015) (see description of
database calculation in Sect. S7 in
the Supplement). Albeit stomatal conductance measurements
for tree species of interest within the database
(Lin et al., 2015) originated from
one or only a few sites (n=1–5; Table 1), beech
and oak exhibited higher median stomatal conductance values than spruce and
pine, corresponding to higher daily Hg uptake rates and foliar N
concentrations in beech and oak compared to spruce and pine. Thus, we
observed a strong control of plant functional traits on foliar Hg(0) uptake
with tree species of high photosynthetic activity (high N concentration) and
stomatal conductance exhibiting the highest foliar Hg(0) uptake rates.
Mean ± standard deviation of daily Hg uptake and foliar N
concentration per tree species group from a subset of foliage samples
harvested during July–August (broadleaf samples) or September–March
(coniferous needle samples). Values are ordered from highest to lowest mean
daily Hg uptake. All values from evergreen tree species groups (Douglas fir,
fir, pine, spruce) were evaluated in current-season needles. Median stomatal
conductance values (min–max) were calculated from a global database of
leaf-level gas exchange parameters compiled by
Lin et al. (2015).
Tree speciesDaily Hg uptakeFoliar N conc.n samplesMedian stomatal conductancen sitesgroup(ngHggd.w.-1d-1)(mgNgd.w.-1)(molm-2s-1) (Lin et al., 2015)(Lin et al., 2015)Beech0.25±0.0523.1±2.93120.10 (0.03–0.31)2Oak0.20±0.0525.1±2.82520.15 (0.01–0.35)1Hornbeam0.19±0.0319.4±2.110Douglas fir0.13±0.0217.0±3.526Spruce0.08±0.0212.9±1.715090.05 (0.01–0.16)1Fir0.07±0.0213.0±1.766Pine0.06±0.0214.4±3.03550.06 (0.00–0.33)5
Within tree species groups, linear regression coefficients of daily Hg
uptake and foliar N concentration were significant (p<0.001) for
beech (R2=0.15; n=312) and fir (R2=0.27; n=66).
Corresponding statistical significance for hornbeam, oak, pine, and spruce
could not be evaluated since the respective data used for the linear
regression was heteroscedastic.
Blackwell and Driscoll (2015) found a
significant relationship between foliar Hg concentration and foliar N percentage
for yellow birch, sugar maple, and American beech but not for pine (red pine
and white pine), red spruce, or balsam fir. We examined whether unaccounted
site-specific differences (e.g., soil N concentration) between forest
plots could have caused the variability (low R2) in daily Hg uptake
versus foliar N concentration within tree species by individually analyzing
foliar Hg concentration versus foliar N concentration at two oak and one
beech forest plot, from which 20 or more foliage samples were available.
Linear regression coefficients of foliar Hg concentrations versus foliar N
concentrations were significant (p<0.001) at two (oak and beech)
of the three plots but not at the third plot (p=0.1, oak) (see Fig. S7 in
the Supplement).
This finding suggests that foliar N concentrations represent an indicator
of foliar Hg concentrations at individual forest sites, as it does for
foliar Hg uptake of different tree species (Table 1). However, given the heterogeneity of nutrient availability between sites
(Vesterdal et al., 2008) and the
complexity of internal foliar allocation of N to different parts of the
photosynthetic apparatus (Hikosaka, 2004), a
generally valid correlation of foliar Hg uptake versus foliar N may not
exist.
Foliar Hg uptake and leaf mass per area
Within the whole dataset, leaf mass per area
(LMA; gd.w.mleaf-2) data were available in a subset of 349 foliage samples
from 48 sites (from both 2015 and 2017). LMA is an important parameter in
plant ecophysiology because carbon gains of plants via photosynthetic
activity and gas diffusion are optimized per unit of leaf area as plants
adapt their LMA, i.e., their foliage thickness and/or tissue density, to the
availability of sunlight during growth
(Ellsworth
and Reich, 1993; Niinemets and Tenhunen, 1997; Rosati et al., 1999). This
LMA adaptation of foliage to sunlight had been suggested to be more
effective for optimizing photosynthetic capacity than within-leaf N
partitioning of photosynthesizing biomass
(Evans and Poorter, 2001). Therefore, we
analyzed the connection of foliar Hg uptake to LMA across tree species.
Figure 4 shows average LMA values (mean ± sd)
of the subset of samples in which LMA was reported, resolved by tree species,
along with respective average daily Hg uptake rates and associated foliar N
concentrations (all values displayed in Fig. 4 are listed in Table S3 in
the Supplement; see
Fig. S8 in
the Supplement for density plots of datasets from Table 1 and Fig. 4).
(a) Average daily Hg uptake rates (ngHggd.w.-1d-1),
(b) average foliar nitrogen concentrations (mgNgd.w.-1), and
(c) average LMA (gd.w.mleaf-2)
determined in 349 foliage samples and resolved by tree species group and
foliage type (leaf/needle). Error bars denote ± 1 standard
deviation. Number of samples (n) differs between tree species: beech (n=164), Douglas fir (n=2), hornbeam (n=9), oak (n=106), pine (n=35), and spruce (n=33).
Current-season needle samples of coniferous tree species groups (Douglas
fir, pine, spruce) exhibited higher median LMA values
(308 gd.w.mleaf-2), lower median daily Hg uptake rates (0.10 ngHggd.w.-1d-1), and lower median foliar N concentrations (15.4 mgNgd.w.-1) compared to leaf samples of deciduous tree species
groups (beech, oak, hornbeam) (Fig. 4). Wright
et al. (2004) illustrated that different evolutionary survival strategies
of plant species are positioned along a single axis of foliage
characteristics ranging from plant species with high photosynthetic capacity
and respiration, high foliar N concentration, low LMA, and short leaf life
spans to plant species with the respective opposite attributes. Comparison
of average daily foliar Hg uptake, LMA, and foliar N concentrations (Fig. 4)
across tree species in this study suggests that foliar Hg(0) uptake aligns
along this plant species economics spectrum, with deciduous leaves with high
leaf N concentrations and thus high physiological capacity (photosynthesis,
respiration) taking up more Hg(0) per gram dry weight over the same time
span than coniferous needles with low leaf N concentrations and
physiological capacity.
Foliar Hg uptake and water vapor pressure deficit (VPD)
Trees regulate their transpiration rates in response to temporary changes in
water vapor pressure deficit (VPD) by controlling leaf stomatal aperture
(Franks
and Farquhar, 1999; McAdam and Brodribb, 2015; Grossiord et al., 2020). When
a critical VPD threshold is exceeded, trees close their stomata to resist
cavitation and excessive water loss in conditions of high atmospheric
evaporative forcing (i.e., high VPD)
(Körner, 2013; Grossiord
et al., 2020). This decrease in leaf stomatal conductivity in response to
high VPD suppresses stomatal uptake fluxes of gaseous pollutants like ozone
(Emberson et al.,
2000; Körner, 2013). We investigated whether VPD impacts the foliar uptake
of gaseous Hg(0) by relating species-specific average daily foliar Hg uptake
rates to the proportion of daytime (06:00–18:00 LT) hours of an average
day within the respective sample life periods during which hourly daytime
VPD exceeded the threshold values of 1.2, 1.6, 2, and 3 kPa at all forest plots with hourly meteorological data (n=82
including both sampling years).
Average daily Hg uptake rates (ngHggd.w.-1d-1)
of current-season pine needles from multiple forest plots (n plots=19)
versus the proportion of daytime hours (06:00–18:00 LT) within an average
day of the respective sample life periods during which the hourly daytime
water vapor pressure deficit (VPD) exceeded a threshold value of 1.2 kPa.
Data points originate from both sampling years 2015 and 2017. All forest
plots are located in Central Europe (latitude 46–54∘), for which ambient air Hg(0) concentrations are relatively constant (see
Table S2 and Fig. S6 in
the Supplement). Error bars denote ± 1 standard deviation of
daily needle Hg uptake rates between multiple samples at each forest plot.
The linear regression coefficients of average daily Hg uptake versus daily
proportion of daytime hours during which VPD exceeded a threshold value
(1.2, 1.6, 2, or 3 kPa) were significant (p<0.01) for
pine at all VPD threshold values (Figs. 5 and S9 in
the Supplement) and for spruce at a VPD
threshold value of 3 kPa (R2=0.44; p=0.01; n=14) (Fig. S9),
and they were not significant for beech and oak at any VPD threshold value (Fig. S10 in
the Supplement).
Linear regression coefficients were negative for all species and VPD
threshold values; i.e., there is a tendency that average daily foliar Hg uptake rates
decreased with the average proportion of daytime hours during which VPD
> respective threshold value (1.2, 1.6, 2, or 3 kPa).
We excluded Douglas fir, fir, hornbeam, and larch from the regression
analysis due to a low number of forest plots (n=1–5). Average daily
needle Hg uptake rates of spruce needles were clustered between two groups
of forest plots with high and low daytime proportions of VPD > threshold (Fig. S9) relative to each other. The t test revealed a significant (p=0.008) difference in average daily spruce needle Hg uptake rates between
the two clusters for a VPD threshold value of 3 kPa and non-significant (p>0.05) differences for all other VPD threshold values. The
timing and degree of stomatal closure during dry conditions is specific to tree species (Zweifel
et al., 2009; Tsuji et al., 2020). Tree species like pine and spruce are
isohydric; i.e., they tend to respond to drought stress under high
evaporative demand by closing their stomata earlier than anisohydric species
like beech and oak
(Martínez-Ferri
et al., 2000; Zweifel et al., 2007; Carnicer et al., 2013; Coll et al.,
2013; Cárcer et al., 2018). Among isohydric species, pine has been
discovered to reduce tree conductance and stomatal aperture during the onset
of dry conditions earlier and at a greater rate than spruce
(Lagergren and
Lindroth, 2002; Zweifel et al., 2009). Spruce has been observed to keep
stomata almost completely closed under drought stress, i.e., high VPD and/or
soil water deficit (Zweifel et
al., 2009). We hypothesize that the significantly decreasing average foliar
stomatal Hg uptake rates with daytime proportion of VPD>1.2 kPa
for pine (Fig. 5) and of VPD>3 kPa for spruce (Fig. S9)
possibly reflect the early physiological response of pine and the high
degree of stomatal closure under drought stress of spruce. Oak exhibits
later stomatal closure at the onset of dry conditions and higher stomatal
aperture under drought stress than, for example, pine
(Zweifel
et al., 2007, 2009), which may be the reason why there was a tendency for a
negative but not significant correlation coefficient of average foliar Hg
uptake with a daytime proportion of VPD > any threshold value for
oak (Fig. S10).
Foliar Hg uptake and soil water content
Linear regression coefficients of average daily foliar Hg uptake rates at
each forest plot versus proportion of hours within sample life periods
during which ERA5-Land soil water fell below a soil-texture-specific
threshold value (PAWcrit) (see Sect. 2.6) were negative for all tree
species groups and significant for beech (p=0.036) and pine (p=0.031) (Fig. 6). The linear regression coefficient was not significant for
oak (p=0.169) and not available for spruce due to a low number of data
points.
Average daily Hg uptake rates (ngHggd.w.-1d-1)
of beech, oak, and current-season pine foliage from multiple forest plots
(beech plots n=38; oak plots n=45; pine plots n=19; latitude:
41–55∘) versus the proportion of hours within the
respective sample life periods, during which the geographically associated
hourly soil water from the ERA5-Land dataset (Muñoz
Sabater, 2019) fell below a soil-texture-specific threshold value
PAWcrit (see Sect. 2.6). Data points originate from both sampling years
2015 and 2017. Error bars denote ± 1 standard deviation of daily
needle Hg uptake rates between multiple samples at each forest plot.
Linear regression results (Fig. 6) indicate that foliar Hg uptake rates
decrease at forest plots, where plant available water in the upper soil
layer (0–7 cm) falls below specific thresholds (PAWcrit) for a
relatively long time period over the growing season. Studies on the
atmosphere–plant transport of ozone have highlighted that plant stomatal
ozone uptake declines with increasing soil water deficit because drought
prompts stomatal closure
(Panek
and Goldstein, 2001; Simpson et al., 2003; Nunn et al., 2005). We
hypothesize that stomatal uptake of Hg(0) is impacted by soil conditions of
low plant available water in a similar way to ozone. In the future, in situ
soil matrix potential measurements should be used to better quantify the
response rate of foliar Hg(0) uptake to soil water content in order to
overcome the limitations of the coarse satellite-derived soil water
measurements used here. We also suggest determining the possible influence
of additional parameters like gravel content and density of soils, rooting
depth of trees, and atmospheric Hg(0), which could vary within the range of
latitude (41–55∘) of examined forest plots.
Foliar Hg uptake and geographic and tree-specific parameters
We performed linear regressions of average daily foliar Hg uptake rates per
forest plot and tree species group (beech, oak, pine, spruce) versus
geographic and tree-specific parameters. These parameters include altitude,
latitude, average age of trees on plot, average tree diameter at breast
height, average daily GLEAM transpiration values, and average ERA5-Land 2 m
air temperature over the course of the respective sample life periods (see
Sect. 2.1). None of the resulting 54 linear regression coefficients were
significant given a Bonferroni adjusted p value=0.000925. The
differences between 2015 and 2017 species-specific averages of daily foliar
Hg uptake rates from forest plots, at which foliage sampling took place
during both sampling years, were small compared to the standard deviation of
daily foliar Hg uptake rates within each sampling year and species (see
Table S5 in
the Supplement for average and standard deviation values). From the sampling year
2015 to the sampling year 2017 this difference was 0.04 ngHggd.w.-1d-1 for beech, 2×10-4ngHggd.w.-1d-1 for oak, 8×10-5ngHggd.w.-1d-1 for pine (current-season needles), and -3×10-3ngHggd.w.-1d-1 for spruce
(current-season needles). We therefore suggest that differences in daily
foliar Hg uptake rates between the sampling years 2015 and 2017 are
negligible. In agreement with previous studies
(Ollerova
et al., 2010; Hutnik et al., 2014; Navrátil et al., 2019; Wohlgemuth et
al., 2020; Pleijel et al., 2021), we found a trend of Hg concentrations in
differently aged spruce needles with older needles exhibiting higher Hg
concentrations (Fig. 7), demonstrating that Hg accumulation continues in
older needles. Annual Hg net accumulation seems to slow down in older spruce
needles of age classes y3–y6 in contrast to needles of age
classes y0–y2 (Fig. 7), albeit ranges of average Hg
concentrations ± standard deviation overlap among older and younger
spruce needles, which might be the result of relatively low sample numbers
of older needles compared to younger needles (e.g., 3 samples for y6 versus
301 samples for y1). A decline in foliar Hg uptake by older needles
could be caused by lower physiological activity, cuticular wax degradation,
or an increase in Hg re-emission with needle age
(Wohlgemuth et al., 2020).
Average Hg concentrations (ngHggd.w.-1) in spruce
needle samples of different ages. Needle age class y0 corresponds to
current-season needles flushed in the year of sampling, y1 corresponds
to 1-year-old needles, y2 corresponds to 2-year-old needles, etc.
Error bars denote ± 1 standard deviation between multiple samples, n
indicates number of samples.
Implications for Hg cycle modeling
Our findings suggest that VPD impacts stomatal Hg(0) uptake by isohydric
tree species due to stomatal closure during conditions of high VPD (Fig. 5).
Similarly, elongated time periods of low soil water content within the
growing season possibly result in a decrease in stomatal conductance to
Hg(0) and thus in less foliar Hg(0) uptake by tree species such as beech and
pine (Fig. 6). Other meteorological parameters such as temperature may also
have an effect on stomatal closure and consequently stomatal Hg(0) uptake
(Sect. 3.7). We therefore propose to refine existing stomatal uptake models
for the purpose of exploring the stomatal uptake flux of Hg(0) for common
vegetation types across different global regions over the course of the
growing season. For this, the sensitivity of species-specific foliar Hg
uptake normalized to air Hg(0) concentrations has to be determined in
laboratory experiments with regards to elevated VPD, low soil water content,
or temperature. Eventually, the effect of tree species, VPD, soil water, and
point in time within the growing season could be implemented in a stomatal
Hg deposition model. We propose that the stomatal flux module of the DO3SE
(Deposition of Ozone for Stomatal Exchange) model could serve as a prototype
for a stomatal Hg deposition model because DO3SE provides estimates of
stomatal ozone deposition based on plant phenological and meteorological
conditions
(Emberson
et al., 2000, 2018). Projections from stomatal Hg models are particularly
relevant for the evaluation of future global environmental Hg cycling as
the stomatal Hg(0) uptake flux exceeds direct Hg(II) wet deposition
(Wohlgemuth
et al., 2020; Obrist et al., 2021) and quantitatively represents the most
relevant deposition pathways to land surfaces, driving the seasonality of
Hg(0) in the atmosphere
(Obrist, 2007;
Jiskra et al., 2018). VPD is projected to increase with rising temperatures
under global warming
(Yuan et
al., 2019; Grossiord et al., 2020), potentially causing a decrease in
stomatal foliar Hg(0) uptake fluxes. A diminished global stomatal foliar
Hg(0) uptake flux would result in higher Hg(0) concentrations in the
atmosphere and higher Hg deposition fluxes to the ocean
(Zhou et al., 2021).
Conclusions
We created a large European forest dataset for investigating the control of
tree physiology and climatic conditions on foliar stomatal Hg(0) uptake. We
observed that foliar Hg concentrations were highly correlated with foliage
sampling date (Fig. 2), confirming the notion that foliage takes up Hg(0)
over the entire growing season and over multiple growing seasons in the case
of coniferous needles (Fig. 7). Consequently, it is necessary to calculate
foliar Hg uptake rates by normalizing foliar Hg concentrations by the time
period of Hg(0) accumulation to make foliar Hg values from different sites
comparable. For reasons of comparability, foliar Hg uptake rates should
ideally be normalized to ambient air Hg(0) concentrations when large
variation in atmospheric Hg(0) is expected (e.g., between Northern Hemisphere and
Southern Hemisphere, in polluted regions or over long timescales). We found
notable differences in daily foliar Hg uptake rates between tree functional
groups (broadleaves versus coniferous needles); i.e., Hg uptake rates of
broadleaves were higher compared to coniferous needles of the same age by a
factor of 3.2 (Fig. 3). Across tree species and within beech and fir, the
linear regression coefficients of daily foliar Hg uptake rates versus foliar
N concentration were significant (Sect. 3.3). Tree species groups with
foliage of lower LMA exhibited higher daily rates of Hg uptake per dry
weight of foliage (Sect. 3.4). We set these results within the context of
stomatal foliar uptake of atmospheric Hg(0): deciduous tree species like
beech and oak, which exhibit functional traits of high physiological
activity (photosynthesis, transpiration) over the time span of one growing
season, as represented by high foliar N concentration and low LMA, retain a
higher stomatal conductance for diffusive gas exchange. Thus, beech and oak
leaves accumulate more Hg per unit dry weight over the same time span
relative to needles of coniferous tree species. In addition to tree-species-specific metabolism, climatic conditions like current VPD or soil
water content, which impacts stomatal gas exchange, can affect foliar Hg
uptake. For current-season pine needles, we found a significant negative
linear regression coefficient of daily Hg uptake rates versus the average
daily proportion of hours within sample life period, during which
atmospheric evaporative forcing was high (VPD>1.2 kPa) (Fig. 5), suggesting that a reduction in stomatal conductance during conditions
of high VPD suppresses foliar Hg(0) uptake. In a similar line of argument,
low surface soil water content lowers stomatal conductance and consequently
foliar stomatal Hg(0) uptake (Fig. 6). We therefore suggest that foliar Hg
measurements bear the potential to serve as a proxy for stomatal
conductance, providing a time-integrated measure for stomatal aperture when
taking into account the spatial and temporal variation in atmospheric Hg(0).
We call for the implementation of a stomatal Hg(0) deposition model that
takes tree physiology and environmental conditions like VPD or soil water
content into account in order to make projections about this important Hg
deposition flux under climate change. The diminution of the vegetation
mercury pump in response to drought stress as a result of climate change
could result in elevated Hg concentrations in the ocean and potentially in
marine fish in future, a potential risk which warrants further quantitative
studies.
Data availability
Foliar Hg concentrations, foliar Hg uptake rates, and Hg-related metadata
are available for download at 10.5281/zenodo.5495179. Please note that coordinates
(latitude, longitude) were rounded to minutes. R scripts for data analysis and
plots of this paper can be found at
https://github.com/wohle/Hg_Forests (Wohlgemuth, 2022).
ICP Forests proprietary data (N concentrations and forest plot attributes)
fall under the publication policy of ICP Forests (Annex II of
Seidling et al., 2017) and can be accessed from the
ICP Forests database (http://icp-forests.net/page/data-requests, ICP Forests, 2022)
upon request from the Programme
Co-ordinating Center (PCC) in Eberswalde, Germany. Foliar Hg concentration
values from the Austrian Bio-Indicator Grid can be obtained from BFW upon
request (https://bfw.ac.at/rz/bfwcms.web?dok=3687, BFW, 2022). ERA5-Land data (Muñoz Sabater, 2019) were
downloaded from the Copernicus Climate Change Service (C3S) Climate Data
Store (https://cds.climate.copernicus.eu/#!/home, Copernicus, 2022a). Data for the beginning
of the growing season of coniferous trees in 2015 and 2017 were provided by
members of the PEP725 project (http://www.pep725.eu/, PEP725, 2022). PROBA-V leaf area
index values of 300 m resolution and GLEAM transpiration values from 2015
and 2017 were obtained from the VITO Product Distribution Portal
(https://land.copernicus.eu/global/products/lai, Copernicus, 2022b) and the GLEAM server
(https://www.gleam.eu/, GLEAM, 2022), respectively.
The supplement related to this article is available online at: https://doi.org/10.5194/bg-19-1335-2022-supplement.
Author contributions
LW managed the project, coordinated foliar Hg measurements, assembled the
Hg dataset, performed the data analysis, and wrote the manuscript. PR, BA,
AR, LV, PW, VT, NE, MG, PR, AT, MN, AK, MI, PM, SB, DZ, and CI supplied foliage
samples and metadata and gave scientific input to the manuscript. AF
contributed foliar Hg concentrations from the Austrian Bio-Indicator Grid
and gave scientific input to the manuscript. GH and CA provided valuable
scientific support. MJ designed and set up the SNSF project (174101),
provided valuable scientific support, and contributed to manuscript writing.
Competing interests
The contact author has declared that neither they nor their co-authors have any competing interests.
Disclaimer
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
We thank Fabienne Bracher and Judith Kobler Waldis for assistance in
foliage sample analysis. The evaluation was based on data that were collected
by partners of the official UNECE ICP Forests network
(http://icp-forests.net/contributors, last access: 16 February 2022). We are grateful to all ICP Forests
participants who supported the project through foliage sampling, nutrient
analysis, and cooperation in the logistics of this project. In this context,
we particularly thank Martin Maier, Andrea Hölscher, and their team from
the Department of Soil and Environment at FVA Baden-Württemberg; Daniel
Žlindra from the Slovenian Forestry Institute; Nils König from
Northwest German Forest Research Institute (NW-FVA); Hans-Peter Dietrich and
Stephan Raspe from the Bavarian State Institute of Forestry (LWF Bayern);
Michael Tatzber from the Austrian Research Centre for Forests (BFW); Arne
Verstraeten and Luc De Geest from the Belgian Research Institute for Nature
and Forest (INBO); Sébastien Macé from the French National Forest
Office (ONF), and Panagiotis Michopoulos from the Forest Research Institute
of Athens (FRIA). We are grateful to Samantha Wittke and Christian Körner for their helpful advice and support on leaf area indices and
plant phenology. Special thanks go to Till Kirchner and Anne-Katrin Prescher
from Thünen Institute for their assistance in accessing the ICP Forests
Database.
Financial support
This research was funded by the Swiss National Science Foundation (SNSF
(grant no. 174101)). The participating countries from the UNECE ICP
Forests Network funded the sampling using national funding; among funding
agencies are the Natural Resources Institute Finland (Luke), Swiss Federal
Institute for Forest, Snow and Landscape Research (WSL), Norwegian Institute
of Bioeconomy Research (NIBIO), Norwegian Ministry of Agriculture and Food
(LMD), Polish Forest Research Institute (IBL), Polish Ministry of
Environment (grants no. 650412-650415), Northwest German Forest Research
Institute (NW-FVA), French National Forest Office (ONF), French Ministry of
Agriculture, French Agency for Environment and Energy (ADEME), Slovenian
Ministry of Agriculture, Forestry and Food (Public Forest Service,
Assignment 1.3), and National Institute for Research and Development in Forestry
“Marin Dracea” Romania (INCDS). Part of the data were co-financed by the
European Commission. The Austrian Bio-Indicator Grid is operated by BFW with
funding from the Austrian Ministry of Agriculture, Regions and Tourism.
Review statement
This paper was edited by Anja Rammig and reviewed by Håkan Pleijel, Frank Wania, and Charles T. Driscoll.
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