Supplementary Information
Material and methods
5
Study floodplains
The Val Roseg catchment is situated in the eastern Swiss Alps and belongs to the lower
austroalpine Bernina nappe (9°53’53’’E, 46°29’24’’N). Geology consists of crystalline bedrock
composed mainly of diorite and granite (Malard et al., 1999). It covers an area of 66.5 km2 from
which 30.1% is glaciated. Annual precipitation rates are approximately 1.6 m, with around 50%
10
as snow. The altitude of the catchment ranges from 1766 to 4049 m a.s.l., and the study area
ranged from 2009 to 2336 m a.s.l.
The Roseg River is an 11.3-km long second-order tributary of the river Inn, which drains
into Danube. Average annual discharge and water temperature are 28.5 m3 s-1 and 3.6 °C
(range0.1 to 12.6°C). Approximately 30% of the water volume of the Roseg River is fed by water
15
from two valley glaciers, the Roseg glacier and Tschierva glacier, both of which have retreated
continuously over the last century (Maisch 1988, Tockner et al., 1997, Malard et al., 2000,
Tockner et al., 2002, BAFU 2010). Permanent flowing first-order tributaries contribute
groundwater and snowmelt to the Roseg with peak flows during June and August (Malard et al.,
2000). The channel network within the floodplain shows a distinct contraction in October caused
20
by the freezing of glacial water.
The Loetschental catchment is in the Rhone-Valley in the southwest part of the Swiss
Alps (07°49'03''E, 46°25'08''N), harboring the second-order kryal stream Lonza which drains into
the Rhone. It is part of the old crystalline Aare massif that is dominated by amphibolite and
gneiss (Labhart 1998). The altitude of the 77.8 km2 valley ranges from 1375 to 3200 m a.s.l.
25
(Schmidt et al., 2009, BAFU 2010), and the study area was located between 1929 to 2210 m
a.s.l. Approximately 36.5% of the valley is glaciated by the Lang glacier and the Jegi glacier. The
1
River Lonza shows an average discharge and water temperature of 37.2 m3 s-1 and 4.0 °C
(range of 0.1 to 10.9 °C)(BAFU 2010). The kryal tributary fed by the Jegi glacier (Anunbach) and
several first-order krenal tributaries drain into the Lonza within the study area. Most tributaries
30
run dry during October and the channel network experiences a similar periodical contraction as
the Roseg cannel network.
The Macun Lakes region is a high alpine cirque situated in the Swiss National Park, and
located in the mid-eastern part of the Swiss Alps (10°07'31''E, 46°43'51''N). It belongs to the
upper austroalpine Silvretta nappe and geology consists mainly of crystalline rock dominated by
35
orthogneiss. The catchment is divided into a southern and northern basin that differs in their
water source (Robinson and Matthaei 2007). The northern basin is mainly groundwater and
snowmelt fed, whereas the southern basin is fed mostly by rock glaciers. This catchment also
experiences contraction of surface channels in October (Robinson and Matthaei 2007).
40
Details on bacterial total cell numbers
A 0.5 ml aliquot of collected sediment (n=3) was suspended in 1.11 ml paraformaldehyde
(2%, final concentration) in an Eppendorf tube and fixed for 24 h at 4°C followed by three
washing steps with 1 x PBS and 5 min centrifugation at 10,000 g between washing steps.
Samples were then stored at -20°C in a 1:1 mix of PBS/ethanol until further processing
45
(Pernthaler et al., 2001). Weight of the sediment, tube and the storage solution was measured.
Attached bacteria were brought into suspension by sonication (Branson Digital Sonifier 250,
Danbury, USA, 5-mm tapered microtip, actual output of 20 W) using 1-s sonication pulses for 30
s. After vortexing the sample for 7 s, a short spin centrifugation using a table top centrifuge for 5
s was performed to remove coarse particles interfering with downstream sample processing.
50
The supernatant was transferred into a new Eppendorf tube and served as a template for total
cell counting of 4’,6-diamidino-2-phenylindole (DAPI) (Sigma-Aldrich Co) stained cells. The
remaining sediment was dried for 24 h at 60°C and weighed with and without the Eppendorf.
2
A 10 to 60 µl aliquot of template solution was pipetted into 5 ml sterile ultrapure water
(MQ) and stained with DAPI (1 µg ml-1 final concentration) for 7 min followed by filtration onto a
55
black polycarbonate filter (0.2-µm pore size, 25-mm diameter, Millipore, Molsheim, GTBP02500)
by applying a gentle vacuum (Porter and Feig 1980). Filters were air-dried and embedded into
citifluor AF1 (Linaris Biologische Produkte, Wertheim,Bettingen). An epifluorescence microscope
(Leica Micorsystem, DMI6000b) was used to take a minimum of 16 photographs of each stained
filter to ensure an equal distribution and an appropriate number of bacterial cells (800+) for
60
counting. Photographs were analyzed using the CellC software (Selinummi et al., 2005) or
counted manually if background fluorescence interfered with the automated counting routine.
Cell numbers were then standardized to the dry mass of the initially suspended sediment by
using the weights determined during procession.
65
Details on enzyme assays
Approximately 10 g of sediment sample (n=3 per sample) were dissolved in 10 ml MQ
and vortexed for 1 min to suspend the associated biofilms. A 150-µl aliquot was then transferred
into a 96 well microplate and 100 µl of a 1 mM substrate stock solution was added to get a final
substrate concentration of 400 µM (Findlay et al., 2001). The remaining sediment and MQ were
70
dried at 60°C for 48 h to measure the dry weight subsequently used to calculating the OM
content. Fluorimetric enzyme assays were performed directly after adding the substrate for up to
24 h using a microplate reader (Tecan Infinite® 200, Switzerland). The excitation wavelength
was set at 365 nm and fluorescence emission was measured at 445 nm. Plates were incubated
on a plate shaker at 15°C between measurements. All fluorescence values were corrected for
75
quenching by adding known quantities of free Methylumbelliferone (MUF) to the samples and to
MQ and bicarbonate buffer blanks. Reaction rates were calculated using the linear part of the
fluorescence reaction curve. Potential enzyme activities were standardized to nmol substrate g-1
OM h-1.
3
Details on bacterial community fingerprinting
80
Bacterial community structure was assessed by ARISA. Frozen samples (n=2 per
sample) were extracted using the PowerSoil DNA isolation Kit (MoBio, Carlsbad) following
manufacturer’s instructions. DNA was amplified using the fluorescein (6-FAM) labeled universal
forward primer 1406f-6FAM (16S rRNA gene, 5’-FAM-TGYACACACCGCCCGT-3’, Y=T,C) and
the
85
bacteria
specific
reverse
primer
23Sr
(5’-GGGTTBCCCCATTCRG-3’,
B=G,T,C,
R=G,A)(Yannarell et al., 2003). PCR was performed using a TProfessionalthermocycler
(Biometra GmbH, Göttingen) in a final reaction volume of 25 µl with a mix of 1x GoTaq®Flexi
buffer, 3 mM MgCl2, 0.25 mM each of dNTP, 0.05 U µl-1 of GoTaq®Flexi DNA Polymerase
(Promega, Switzerland), 0.25 mg ml-1 bovine serum albumin (Sigma-Aldrich, Switzerland), 0.4
µM of each primer (Microsynth, Switzerland), and 1 µl of template DNA. The reaction mix was
90
initially denatured for 2 min at 94°C followed by primer annealing at 55°C for 35 s and extension
of 2 min at 72°C. Denaturation time was then reduced to 35 s and the cycle was repeated 29
times followed by a final extension for 2 min at 72°C. ARISA fragment analysis was performed
as described in Bürgmann et al. (2011). Briefly, a 1 µl aliquot of PCR product was mixed with 9
µl of HiDi formamide and 0.5 µl Liz1200 size standard (Applied Biosystems, Switzerland) and
95
denatured prior to capillary electrophoresis on a PCR thermocycler for 3 min at 95° C and
subsequently placed on ice. Denaturing capillary electrophoresis was performed on a 3130XL
Capillary Genetic Analyzer (Applied Biosystems, Switzerland) equipped with a 50-cm capillary
using POP-7 polymer. ARISA fragments were analyzed with the Southern size-calling method
with a background cut-off level of 50 fluorescence units. Binning of peak areas was done with
100
automatic and interactive binning R scripts (Ramette 2009) leading to relative fluorescence
intensities (peak areas) between 197 and 1400 bp. The mean of the relative fluorescence
intensities of the extracted samples (n=2) was used for subsequent analysis. These
fluorescence intensities were Wisconsin double standardized prior to analysis (relative peak
4
area of an operational taxonomic unit (OTU) of a sample is first standardized by maxima peak
105
area of this OTU within all samples and then by site total OTUs relative fluorescence intensity).
Details on data analysis
Environmental factors, cell abundance was tested for homogeneity using a Bartlett-Test.
Comparison of environmental variables, cell abundance and enzymatic activity between
110
catchments, water source and sampling date were done using three-factor ANOVA (Type I SS)
followed by Tukey’s HSD when differences were significant. Catchment, water source and
sampling date were treated as fixed factors in the ANOVA. Akaike information criterion (AIC)
model reductions were performed for confirmation of non-significant model terms. Normality of
residuals was assured by performing a Shapiro Willk’s test and examining the QQ-plot of the
115
residuals. If one of the assumptions was violated, data were transformed, after checking with the
Box-Cox-Method (Krambeck 1995), by ln x  1 or x  Max log Likelihood . Percentage values were
arcsin
 x  transformed prior to analysis. In case of non-conformity after transformation, a non-
parametric Kruskal-Wallis test followed by multiple comparisons was performed instead of
ANOVA. Tukey like Post-hoc tests were performed for boxplots independent of conformity based
120
on linear models compared with the glht() function available in the mulitcomp package in R.
P-values were holmes adjusted.
Community fingerprinting results, enzymatic activities and environmental data were
analyzed using NMDS in combination with vector and factor fitting. Untransformed enzyme
activities and environmental parameters were used. Significance of fitted vectors and factors
125
was tested by a permutation test (999 permutations) and visualized as biplots and dispersion
ellipses in the NMDS ordinations (Figures S4 and S5). Generalized additive models were fitted
on the NMDS for raw physico-chemical data to check linearity of fitted vectors (biplots) and used
to assess the importance of single physico-chemical variables potentially constraining the BCC
or EF pattern (Appendix Tables 6 and 7) (Bennion et al., 2011). Physico-chemical variables were
5
130
therefore interpolated with the function ordisurf() from the vegan package in R (Oksanen et al.,
2011). Shortly, the function fits a smooth surface using thinplate splines and the percentage of
variance of each factor explained by the surface can be seen as a measure of how well an
environmental variable explains the a priori and unconstraint NMDS pattern. The advantage of
this approach is that linear projections of environmental variables (biplots) in the ordination
135
space may not be de facto ideally linear as i.e. in constraint ordinations, thus takes non-linear
relationships better into account.
The totally explained variance of the physico-chemical factors on BCC and EF was
assessed by a global RDA model incorporating all samples and physico-chemical parameters.
Canonical coefficients (i.e. the regression coefficients) of the first two axes and R2 of forward
140
selected explanatory variables were calculated. This allows assessing which variables are most
important to explain EF or BCC structure on these two axes and can be qualitatively compared
to the explained deviance of the respective GAM model (Appendix Tables 6 and 7). RDA based
variation partitioning were performed to evaluate the influence of assessed chemical and
physical (temperature and D90D10) factors on bacteria structure and function as a whole and
145
within the specific water systems. For both approaches, variation inflation factors were
calculated and physico-chemical factors which had a value above 20 were removed before a
forward selection was performed. This minimizes collinearity of respective variables with other
variables included in the analysis. Unique fractions of RDA were tested by an ANOVA like
permutation test. Reported are the adjusted R2 (Peres-Neto et al., 2006, Blanchet et al., 2008).
150
RDA based analysis were performed with Hellinger transformed ARISA and enzymatic activity
data.
Permutational multivariate analysis of variance (PERMANOVA) was used to assess the
influence of water source, catchment and sampling date (full factorial model) on community and
enzyme activity structure (Anderson 2001). Additionally, a factor fitting for water source,
155
catchment and sampling date ordinations was performed for the NMDS ordinations and tested
6
with a permutation test (999 permutations) leading to the r2correlation coefficient (Appendix
Tables 6 and 7).
Correlation of single enzymes to physico-chemical factors were tested by multiple linear
regression. The models were selected by AIC, significance of single predictors was tested by
160
permutational ANOVA (Type III SS) and relative importance of predictors in the linear model was
assessed using the lmg metric (Chevan and Sutherland 1991, Grömping 2006). The enzymatic
activities standardized to OM were used for the models without OM as a predictor incorporated.
This prevents autocorrelation. Physico-chemical factors were ln x  1 transformed.
A pairwise comparison between a specific water source in a specific catchment between
165
specific sampling dates was also performed for EF and BCC by the means of PERMANOVA.
These results were then used as a measure for the coupling of BCC and EF. This was done by
giving pairwise PERMANOVAS with P-values lower then 0.05 (i.e. significant differences due to
a temporal shift in EF or BCC) a value of 0 and PERMANOVAS with P-values higher then 0.05
(i.e. no differences in EF or BCC between two sampling dates) a value 1, respectively, and then
170
summing the corresponding pairs of structure and function. Sums of zero and 2 indicate a
potential coupling of structural and functional measures, whereas a value of 1 indicates a
decoupled relationship. I.e. if BCC shifts (=0) and EF stays stable between two sampling dates
(=1) we would detect this as an uncoupling of BBC and EF (sum=1) (Appendix Table 4). This
assessment was supported by a Mantel test and a procrustes analysis. The Mantel test between
175
ARISA and enzyme activities was based on 999 permutations (Mantel 1967). The procrustes
analysis of the corresponding NMDS ordinations leads to m2 statistic, which is used as a
measure of congruence of the two ordinations, and the procrustes correlation r  1  m 2 .
Configurations of NMDS were scaled to equal dispersion. Non-randomness between the two
configurations was tested with the function protest by 999 permutations (Gower 1975, Digby and
180
Kempton 1987, Jackson 1995, Peres-Neto and Jackson 2001). Procrustes analysis was
7
additionally performed for ARISA and enzymatic activities vs. environmental variables NMDS
ordinations (Appendix Table 8).
Multivariate homogeneity of groups dispersion (MHGD), as an analogue of Levene’s test
for homogeneity of variance, was performed to assess changes in beta diversity (i.e. changes of
185
the changes in community structure; 2nd order variation) of fingerprinting profiles and the
changes in variation of enzyme activities, and physico-chemical characteristics. Generally,
multivariate dispersion (variance) can be calculated by the distances of group members to a
group centroid in multivariate space. Differences in dispersions can then be tested by ANOVAs.
Bray-Curtis dissimilarities of transformed and standardized datasets were reduced from their
190
original distances to principal coordinates (PcoA) which embeds them within an Euclidian space.
The average distances to centroids were then calculated within groups, thus are based on
principal coordinate axes rather than the original distances. Differences between groups were
assessed using a permutational ANOVA test (999 permutations) followed by a Tukey’s HSD
(Figures S3, S9) (Anderson et al., 2006). NMDS, MHGD and PERMANOVA were all based on
195
Bray-Curtis dissimilarity matrices calculated from the Wisconsin double standardized relative
fluorescence intensity of ARISA profiles, Wisconsin standardized square-rooted enzyme
activities and ln(x+1) transformed environmental variables (Bray and Curtis 1957). Shannon
diversity index was calculated for OTU’s (operational taxonomic units).
All analyses were done using the vegan, relaimpo, stats and mgcv package in R (R
200
Development Core Team, 2011, Oksanen et al., 2011).
Results
Detailed results of physico-chemical parameters
205
Additional physico-chemical variables are depicted in Figure S2.There was a strong
influence of catchment, water source and sampling date on water temperature (ANOVA:
8
F2,89=18.53, F1,89=32.98 and F2,89=8.40, respectively, P<0.001). Water temperatures in the three
catchments showed similar patterns. Kryal (glacial) systems were colder (range: 0.3 to 11.9°C,
mean: 4.3°C) during the study period than groundwater (krenal) systems (range: 2.3 to 20.7°C,
210
mean: 8.5°C, Tukey’s HSD: P<0.001). Val Roseg streams were generally colder than streams in
the other two catchments (Tukey’s HSD: P<0.001). Temperature was lower in October
compared to August and June (Tukey’s HSD: P<0.05). The krenal system in Val Roseg had the
lowest mean temperatures compared to Macun and Loetschental krenal sites, which did not
differ (5.8 vs. 10.1 and 10.5°C, respectively, ANOVA: F2,52=5.91, P<0.001, Tukey’s HSD:
215
P<0.05).
Conductivity showed significant interactions between catchment and water source,
catchment and sampling date and water source and sampling date (ANOVA: F2,89=5.70 and
F3,89=2.90 and F2,89=5.80 respectively, P<0.05). There were significant differences in conductivity
between kryal and krenal systems in the Loetschental (mean krenal: 89.9±48.5, mean glacial
220
water: 44.74±23.3 µS cm-1, Tukey’s HSD: P<0.01). Lowest conductivity values were found in the
Macun catchment (mean: 7.9 ± 3.4µS cm-1, Tukey’s HSD: P<0.01) and highest values in
Loetschental and Val Roseg, which did not differ (69.8 ± 44.9 and 62.6 ± 34.5 µS cm -1,
respectively, ANOVA: F2,89=200.76, P<0.001, Tukey’s HSD: P=0.64).
The three catchments were clearly distinct in respect to sediment pH with lowest mean
225
pH measured in Macun followed by Loetschental and Val Roseg (mean: pH 4.86, 6.64 and 7.27,
respectively, ANOVA: F2,89=558.08, P<0.001, Tukey’s HSD: P<0.001). Sediment pH showed a
significant interaction between catchments and water source with a significant difference
between water systems (kryal vs. krenal) only in Val Roseg (ANOVA: F2,89=6.82, P<0.01,
Tukey’s HSD: P<0.001).
230
Macun had higher amounts of OM (mean: 2.54 ± 2.43% OM dw-1) in the sediment
compared to the other two catchments, which were similar (Loetschental: 0.53 ± 0.36% OM dw-1,
Val Roseg: 0.55 ± 0.64% OM dw-1, Kruskal-Wallis: H=46.7, df=2, P<0.001, multiple comparison:
9
P<0.01). OM was generally lower in the kryal than in the krenal system (mean: 0.76 and 1.32%
OM dw-1, respectively, Kruskal-Wallis: H=19.07, df=1, P<0.01, multiple comparison: P<0.01).
235
DOC was lower in Val Roseg compared to Macun but not to Loetschental, whereas
Macun and Loetschental did not differ from each other (mean: 0.95 ± 1.55 mg DOC ml -1, 2.16 ±
3.51 and 2.37 ± 3.93 mg DOC ml-1, respectively, Kruskal-Wallis: H=10.59, df=2, P<0.01, multiple
comparison: P<0.01). There was no significant difference in DOC between the two water types
in each catchment (Kruskal-Wallis: H=3.33, df=1, P=0.07). October DOC concentrations were
240
higher compared to those in August (Kruskal-Wallis: H=24.69, df=2, P<0.001, multiple
comparison: P<0.01). Loetschental kryal DOC concentrations were higher in June than the ones
in August (Kruskal-Wallis: H=61.43, df=15, P<0.001, multiple comparison: P<0.01)
POC concentrations in Val Roseg differed from Macun but not from Loetschental,
(Kruskal-Wallis: H=12.22, dF=2, P<0.01, multiple comparison: P<0.01). More detailed, there was
245
a significant difference in POC in krenal sites between Macun and Val Roseg (mean: 1.22 ±1.34
and 0.21 ± 0.12 mg C l-1, respectively, Kruskal-Wallis: H=21.96, df=5, P<0.001, multiple
comparison: P<0.01).
There was a significant interaction between catchment and sampling date in TIC
concentrations (ANOVA: F3,89=10.26, P<0.001). The Val Roseg catchment showed temporal
250
differences with lower TIC concentrations in August than in October and June (Tukey’s HSD:
P<0.01). TIC differed between catchments and was lowest in Macun (mean: 1.77 ± 1.2 mg C l-1)
and highest in Roseg and Loetschental (mean: 5.39 ± 2.33 mg C l-1 and 4.02 ± 1.43 mg C l-1,
respectively, ANOVA: F2,89=67.90, P<0.001, Tukey’s HSD: P<0.05). Krenal systems had higher
TIC values than kryal systems (ANOVA: F1,89=8.12, P<0.01).
255
NH4-N showed no differences between catchments (Kruskal-Wallis: H=0.48, df=2,
P=0.79), but lower values for krenal than kryal channels in Val Roseg (Kruskal-Wallis: H=22.63,
df=1, P<0.001).
10
NO2-Ndiffered between the two water sources in Val Roseg (krenal mean: 0.53 ± 0.12 µg
N l-1, kryal mean: 2 ± 1.04 µg N l-1, Kruskal-Wallis: H=52.66, df=5, P<0.001, multiple comparison:
260
P<0.01).
NO3-N did not significantly differ between sites, sampling date and catchments.
Macun had highest DON concentrations in the kryal system in October (Kruskal-Wallis:
H=41.57, df=15, P<0.001).
Macun had higher PN concentrations compared to the other catchments (Kruskal-Wallis:
265
H=19.01, df=2, P<0.001, multiple comparison: P<0.01) and also differences between the two
water systems (Kruskal-Wallis: H=9.1, df=1, P<0.01) with highest values in krenal streams.
Water systems in Val Roseg also differed in PN concentrations (Kruskal-Wallis: H=10.54, df=1,
P<0.01), except that PN was higher in kryal channels.
No difference was detected in DP between catchments (Kruskal-Wallis: H=1.78, dF=2,
270
P=0.41). Glacial waters showed highest concentrations of DP (Kruskal-Wallis: H=10.69 ,dF=1,
P<0.01), except for Macun where DP was the same for both systems (Kruskal-Wallis: H=0.45,
df=1, P=0.50).
PP was lower in Macun kryal waters than in the other two catchments (Kruskal-Wallis:
H=14.29, df=2, P<0.001, multiple comparison: P<0.01). Kryal systems had higher PP
275
concentrations compared to krenal systems in the Roseg catchment (Kruskal-Wallis: H=22.05,
df=1, P=<0.001). Krenal sites had higher PP in Loetschental than in Roseg (Kruskal-Wallis:
H=12.93, df=2, p<0.01, multiple comparison: P<0.01). A peak in PP in August was visible in Val
Roseg (Kruskal-Wallis: H=8, df=2, p<0.05, multiple comparison <0.05).
No difference in PO4-P concentrations was detected between catchments (Kruskal-
280
Wallis: H=2.63, df=2, P=0.27), although glacial waters generally had highest PO 4–P levels in Val
Roseg (Kruskal-Wallis: H= 13.88, df=1, P<0.001).
The D90/D10 sorting coefficient did not show a significant difference between the
catchments, water source or the sampling date respectively (ANOVA: P>0.05).
11
The MHGD analysis showed difference in variation of physico-chemical characteristics
285
between groupings of same water source, sampling date and catchment (Permutation test:
F15,89=4.16, P<0.001, Figure S3). There was an interaction of catchment, water source and
sampling date on distances to centroids (ANOVA: F3,89=5.71, P<0.01) as well as an interactive
effect of catchment and sampling date (ANOVA: F3,89=5.32, P<0.01). Catchment, water source
and sampling date had also an effect on the distance to centroids (ANOVA: F2,89=7.16, P<0.01,
290
F1,89=10.98, P<0.01, F2,89=3.77, P<0.01, respectively). In particular, Roseg kryal waters showed
higher variation in October compared to most krenal sites, except for Loetschental June and
October and Macun August (Tukey’s HSD: P<0.05). Roseg kryal variation in October was also
higher than the Val Roseg kryal systems in June and August and the Macun October kryal
system (Tukey’s HSD: P<0.05).
295
Ordination of environmental parameters (Figure S1) revealed differences in physicochemical characteristics between water sources, catchments and dates (PERMANOVA:
F1,89=21.22, F2,89=24.59 and F2,89=8.89, respectively, P<0.001). An interaction between
catchment and dates, and catchment and water source was apparent (PERMANOVA:
F3,89=5.04, and F2,89=8.52, P<0.001). Physico-chemical characteristics were not different
300
between Loetschental and Val Roseg krenal waters in August and October (PERMANOVA:
F1,13=2.31, P=0.06 and F1,13=3.37, P>0.59, respectively). Macun showed no significant difference
between water systems in August or October (PERMANOVA: F1,17=1.33, P=0.24 and F1,8=3.18,
P=0.054, respectively). Loetschental krenal systems did not significantly differ from kryal waters
in October and June (PERMANOVA: F1,6=0.23, P=0.872, F1,9=1.26, P=0.297, respectively).
305
Loetschental krenal systems did not differ between June and August (PERMANOVA: F1,11=1.67,
P=0.147). Val Roseg showed no shift in physico-chemical characteristics between October and
June in krenal systems (PERMANOVA: F1,13=.16, P=0.375).
12
310
Detailed results of enzymatic activities
The total activity of the enzyme set showed a difference between catchments and water
source (ANOVA: F2,89=29.53, P<0.001, F1,89=5.20, P<0.05, respectively). A post-hoc test
revealed generally highest mean enzyme expressions in krenal systems (Tukey’s HSD: P<0.05)
and highest mean values in Roseg, intermediate values in Loetschental and lowest values in
315
Macun (Tukey’s HSD: P<0.01). There was also a significant interaction between water source
and sampling date (ANOVA: F2,89=3.66, P<0.05),
Alph had highest activities in krenal systems (ANOVA: F1,89=28.87, P<0.001, Tukey’s
HSD: P<0.001) and lowest activities in Macun (ANOVA: F2,89=17.70 P<0.001, Tukey’s HSD:
P<0.001).
320
Bet had a significant interaction between catchment, water and sampling date (ANOVA:
F3,89=3.64, P<0.05 ), with krenal sites being more active than kryal sites in June and August in
Val Roseg (Tukey’s HSD: P<0.05). Roseg had higher Bet activities than the other two
catchments (Tukey’s HSD: P<0.05).
Xyl had a significant interaction between water, catchment and sampling date, being
325
higher in Roseg krenal sites than in Macun krenal sites in August (ANOVA: F3,89=2.94, P<0.05,
Tukey’s HSD: P<0.05). In June, kryal sites in Val Roseg were lower in activities than krenal sites
(Tukey’s HSD: P<0.001). There was generally less Xyl activity in krenal sites in Macun than in
the other catchments (ANOVA: F2,89=4.98, P<0.01, Tukey’s HSD: P<0.05), and krenal sites were
more active than kryal sites in Loetschental (Tukey’s HSD: P<0.05). Roseg and Loetschental
330
had more Xyl activity than Macun (ANOVA: F2,89=6.01, P<0.001, Tukey’s HSD: P<0.05), and
krenal sites had more activity then kryal sites (ANOVA: F1,89=43.64, P<0.001, Tukey’s HSD:
P<0.001).
Est had different activities between the three catchments, being highest in Roseg,
intermediate in Loetschental and lowest in Macun (ANOVA: F2,89=85.93, P<0.001, Tukey’s HSD:
335
P<0.005).
13
Nac was lower in Loetschental compared to Val Roseg in August (ANOVA: F3,89=4.61,
P<0.05, Tukey’s HSD: P<0.05). In Val Roseg, krenal sites had higher activity than kryal sites,
and also higher activity than krenal and kryal sites in Macun and kryal sites in Loetschental
(ANOVA: F2,89=5.66, P<0.01, Tukey’s HSD: P<0.001, P<0.01,
340
P<0.05 and P<0.001,
respectively). The krenal systems showed generally higher Nac activity (ANOVA: F1,89=33.14,
P<0.001, Tukey’s HSD: P<0.001).
Leu had different activities between water systems with higher values occurring in krenal
sites (ANOVA: F1,89=19.87, P<0.01) and highest activities in Roseg followed by Loetschental and
Macun (ANOVA: F2,89=25.24, P<0.001, Tukey’s HSD: P<0.05).
345
End was highest in Val Roseg, intermittent in Loetschental and lowest in Macun
(ANOVA: F2,89=65.86, P<0.001, Tukey’s HSD: P<0.001). Kryal systems had the highest End
activities (ANOVA: F1,89=14.85, P<0.001, Tukey’s HSD: P<0.001).
In Val Roseg krenal sites Phos activity was higher compared to all other water systems
within the three catchments except for Macun krenal system which did not differ (ANOVA:
350
F2,89=6.02, P<0.01, Tukey’s HSD: P<0.05). Val Roseg and Macun were generally more active for
Phos compared to Loetschental (ANOVA: F2,89=4.73, P<0.05, Tukey’s HSD: P<0.05), and krenal
sites showed higher Phos activity then kryal sites (ANOVA: F1,89=48.07, P<0.001, Tukey’s HSD:
P<0.001).
MHGD revealed a difference in variation of enzymatic activity patterns between
355
groupings of same water source, sampling date and catchment (Permutation test: F15,89=7.13,
P<0.001, Figure S3). An interaction of distance to centroids with catchment, water source and
sampling date was apparent (Anova: F3,89=2.72, P<0.05). An interaction of distance to centroid
with catchment and water source with low variability (Anova: F1,89=15.17, P<0.001), water
source and sampling date (Anova: F1,89=4.86, P<0.01) as well as catchment and sampling date
360
(Anova: F1,89=2.86, P<0.05) was apparent. There was also an influence of water source (Anova:
F1,89=20.46, P<0.001). In Loetschental and Val Roseg there was low turnover between
14
enzymatic activity patterns within the krenal sites (Tukey’s HSD: P<0.05). Macun had similar
enzymatic turnover on the sampled dates in both water systems (Tukey’s HSD:
P<0.05).Loetschental kryal sites had much higher turnover in EF in June and August compared
365
to the other sites at any time, except for Loetschental kryal sites in October and Val Roseg
krenal sites in August and October and Val Roseg kryal site in June (Tukey’s HSD: P<0.05). The
Val Roseg kryal sites in June had higher enzymatic turnover compared to Macun kryal channels
during October, Val Roseg kryal channel during August and all krenal channels except for Val
Roseg krenal sites in August and October (Tukey’s HSD: P<0.05).
370
Ordination of enzyme activities showed strong separation between the two water
systems, catchments and their interactions (Figure 4, Figure S4), (PERMANOVA: F1,89=40.51,
P<0.001, F2,89=18.92, P<0.001 and F2,89=5.11, P<0.01, respectively) with clear separation of the
three catchments and separation of kryal from krenal in Val Roseg and Loetschental. A temporal
shift in EF was partially present in Val Roseg in the pairwise comparison model, although not or
375
only marginally significant in the complete model (PERMANOVA: F2,89=2.02, P=0.08, appendix
Table 4). Macun showed no functional separation between water sources (Figures 4 and S4,
appendix Table 4). The Macun catchment differed in both water systems from krenal systems of
the other catchments in all sampling dates (PERMANOVA: Macun vs. Roseg: F1,48=13.64,
P<0.001, Macun vs. Loetschental: F1,41=25.88, P<0.001). Macun water systems were not
380
significantly different in activity patterns (PERMANOVA: F2,26=1,27, P=0.26), whereas the other
two catchments showed strong separation in activity structures between krenal and kryal sites
(PERMANOVA: Roseg: F1,50=25.85, P<0.001, Loetschental: F1,26=7.42, P<0.01). No differences
could be detected between Loetschental and Roseg activities within each water system within
any sampling date (appendix Table 1). A temporal shift in enzymatic pattern was present only in
385
Roseg for both water systems (PERMANOVA: F2,28=2.645, P<0.05 and F2,21=2.137, P<0.05,
respectively, appendix Table 1).
15
RDA analysis accounted 55.8% of variation in EF to physico-chemical factors
(R2adj=0.558, F6,98=22.85, P<0.001). See appendix Table 6 for canonical coefficients of the first
two constraint axes and the R2 values of the forward selected environmental parameters (R2
390
were not adjusted, thus values are slightly higher). Variation partitioning revealed that the total
contribution of chemical/physical factors on enzymatic activity was 42.6% / 0.3% of explained
variation. The shared fraction explained 13.1% of the variation in EF (Total R2adj=0.560,
F7,97=19.94, P<0.01, chemical fraction: R2adj=0.426 F6,97=17.65, P<0.01, physical fraction R2adj
=0.003, F1,97=1.62, P=0.18, joint fraction R2adj=0.133, not testable). When variation partitioning
395
was assessed for the two water sources independently, there was 48 % of variation in EF
explained by chemical factors, 0% by physical factors and 7.4 % by the shared fraction in the
kryal systems (Total R2adj=0.553, F6,43=11.09, P<0.01, chemical fraction: R2adj=0.479,
F5,43=11.29, P<0.01, physical fraction R2adj =-0.001, F1,43=0.90, P=0.50, joint fraction R2adj=0.074,
not testable). The variation partitioning within the krenal system revealed that none of the
400
physical factors were kept in the model after forward selection. Thus, forward selected chemical
factors were tested independently and explained 47.9% of the variation of enzymatic activities
(Chemical factors: R2adj=0.479, F3,51=17.35, P<0.001).
Detailed results of cell abundance
405
Bacteria cell abundance in sediments ranged from 1.66x106 to 4.44x109 (mean: 2.53
x108±6.75x108, n=105) cells per g sediment dry weight (dw) and differed between the three
catchments (ANOVA: F2,89=71.45, P<0.001). Loetschental had the lowest mean cell densities
(range: 2.65 x106 to 1.90x108 cells g-1 dw, mean: 3.47 x107±4.82 x107 cells g-1 dw, n=27)
followed by Val Roseg (range 1.67x106 to 2.75x109 cells g-1 dw, mean: 1.36 x108±4.02
410
x108cells g-1 dw, n=51) and then Macun (range: 5.25 x107 to 4.44x109 cells g-1 dw, mean:
6.92x108±1.11 x109 cells g-1 dw, n=27). Krenal systems had generally higher cell numbers
((ANOVA: F1,89=90.56, P<0.001, Tukey’s HSD: P<0.001). There were higher cell abundances in
16
August than in October (ANOVA: F2,89=3.93, P<0.05, Tukey’s HSD: P<0.05). There was a
significant interaction between water source and catchment, with lower cell abundances in kryal
415
sediments in Loetschental and Val Roseg (ANOVA: F2,89=14.45, P<0.001, Tukey’s HSD:
P<0.001, appendix Table 1). An interaction of water source and sampling date was also
apparent with lowest cell abundance in kryal systems in June and October, intermediate in kryal
systems in August and generally higher abundances in krenal systems during all sampling dates
with the August samples being significantly higher than the kryal August ones (ANOVA:
420
F2,89=3.56, P<0.05, Tukey’s HSD: P<0.0).
Detailed results of bacterial community structure and linked functions
The number of all 191 detected OTUs ranged from 28 at site VR12 in June to 127 at site
M13 in August. There was a significant interaction between catchment and water source on OTU
425
richness (ANOVA: F2,89=4.19, P<0.05). The number of OTUs differed between water source in
Val Roseg with a higher number of OTUs in krenal than kryal sites (Tukey’s HSD: P<0.001).
Loetschental had a lower number of OTUs in krenal sites than Val Roseg (Tukey’s HSD:
P<0.05) and a lower number of OTUs in kryal sites compared to krenal sites in Macun and Val
Roseg (Tukey’s HSD: P<0.05). Diversity (Shannon index) was highest in krenal systems
430
(ANOVA: F1,89=24.19, P<0.001)
NMDS ordination showed a differentiation in BCC between the two water sources and
the three catchments, but a less pronounced effect of sampling date (PERMANOVA:
F1,89=13.21, P<0.001, F2,89=6.36, P<0.001, and F2,89=1.57, P<0.05, respectively, Figure 5 and
S6). There was also an interaction between water source and catchment (PERMANOVA:
435
F2,89=4.5, P<0.001). Krenal BCC were similar in Loetschental and Val Roseg in August and June
(PERMANOVA: F1,13=0.90, P=0.709, F1,13=1.07, P=0.378, respectively). Otherwise, there was
always a significant catchment difference in BCC for the same water source within the same
sampling dates (PERMANOVAs: P<0.05, appendix Table 4). Macun was more separated from
17
the other two catchments in the NMDS, and showed a less pronounced separation of kryal and
440
krenal sites, although they still were significantly different (PERMANOVA: F1,26=2.09, P<0.01,
Figures 5 and S6). Krenal systems showed no temporal pattern compared to the temporal shift
in BCC in kryal sites in Val Roseg (PERMANOVA: F2,21=0.64, P=0.96, F2,28=2.39, P<0.001,
respectively). Temporal BCC changes were not significant in Loetschental krenal and kryal sites
(PERMANOVA: F2,14=0.70, P=0.896, F2,11=0.82, P=0.610, respectively). Macun BCC showed no
445
temporal pattern in kryal sites but did in krenal sites (PERMANOVA: F1,8=0.77, P=0.791,
F1,16=1.75, P<0.05, respectively).
MHGD showed a significant difference in dispersion between groupings of the same
water source, sampling date and catchment (Permutation test: F15,89=3.53, P<0.001, Figure S3).
Distances to centroids differed between water sources (Anova: F1,89=12.53, P<0.001) and
450
sampling date (Anova: F2,89=4.64, P<0.05) Tukey’s HSD revealed lower beta diversity in Val
Roseg kryal sites in October compared to all krenal systems except to Macun and Val Roseg
krenal systems in October. It was also different to Macun and Val Roseg August kryal systems
(Tukey’s HSD: P<0.05).
RDA revealed that 19.9% of total variation in BCC was explained by forward selected
455
environmental factors (physico-chemical, R2adj=0.199, F8,96=4.23, P<0.001). See appendix table
7 for canonical coefficients of the first two constraint axes and the cumulative R2 values of the
forward selected variables. Variation partitioning showed that the total contributions of
chemical/physical factors on BCC were 13.5% / 1.6% of total variation. The shared fraction
explained 5.2% of the variation (Total R2adj=0.202, F9,95=3.93, P<0.01, chemical fraction:
460
R2adj=0.135, F8,95=3.17, P<0.01, physical fraction R2adj =0.016, F1,95=2.91, P<0.01, joint fraction
R2adj=0.052, not testable). Variation partitioning of physical and chemical parameters applied to
the kryal systems showed 23.2% of the variation in community structure was accounted for
solely by water chemistry (Total R2adj=0.288, F8,41=3.47, P<0.01, chemical fraction: R2adj=.0.232,
F7,41=3.23, P<0.01, physical fraction R2adj =0.014, F1,41=1.81, P<0.05, joint fraction R2adj=0.042,
18
465
not testable). Krenal systems, in contrast, had just 10.9% of the variation in BCC explained by
water chemistry (Total R2adj=0.128, F6,48=2.32, P<0.01, chemical fraction: R2adj=0.109, F5.48=2.33,
P<0.01, physical fraction R2adj =0.016, F1,48=1.88, P<0.01, joint fraction R2adj=0.003, not
testable).
Enzyme activities of Phos and Alph were significantly situated towards krenal bacterial
470
communities (fitting significance: P<0.01 and P<0.05 respectively, based on 999 permutations,
Figure S6). Gradient directions tended towards Roseg and Loetschental for Alph and towards
Macun for Phos. Xyl and Leu also were situated more towards krenal systems, but in a less
pronounced manner (fitting significance: P<0.1, based on 999 permutations). Bet and Nac were
not fitted significantly in the ordination (P=0.391 and P=0.252, respectively), although they have
475
a weak gradient towards the Macun kryal system. Est and End enzyme activity fitted different
from the other tested enzymes with a gradient direction towards kryal systems.
Ordination of enzyme activity structure underlines this functional separation between
water sources, except for Macun (Figures 4 and S4). The tendency of generally higher Phos and
Nac activity was apparent for the Macun catchment. Bet activity centroid, which showed a
480
gradient towards Macun kryal systems in the community structure NMDS, was situated more
near the Roseg and Loetschental krenal systems. This result is probably due to the weak
environmental fitting power in the community structure ordination.
Relating enzyme activity patterns to BCC by means of pairwise comparison of
PERMANOVA’s (appendix Table 4) revealed a link between changes in assemblage structure
485
and function in 63.3% of all pairwise comparisons. A low 16.7% of all pairwise comparisons were
significant in Macun, indicating a weak linkage between structure and function. Roseg and
Loetschental had linkages in 80.0% and 66.7% of all cases, respectively. Procrustes analysis of
community and function NMDS showed linkage between BCC and EF (r=0.639, p<0.001) when
performed with all catchments included. Correlation of single catchments in the same ordination
490
showed differences in strength of association with maximum correlations for Val Roseg,
19
intermediate correlation for Loetschental, and minimal correlation for Macun. Mantel tests
supported these findings.
Relating enzyme activity patterns to BCC by means of Mantel tests showed the same
trend as the procrustes analysis and the pairwise PERMANOVA comparison: Correlation of
495
structure and function of all catchments was 0.363 (P<0.01). The single catchments showed
correlations of 0.561 (P<0.01) in Val Roseg, 0.389 (P<0.01) in Loetschental, and -0.102
(P=0.79) in Macun.
Procrustes analysis for community structure and environmental variables were correlated
(r=0.601, P<0.01) when performed with all catchments. Correlation of single catchments of the
500
same ordination showed maximum correlations for Val Roseg (r=0.600, P<0.001), minimum for
Loetschental (r=0.425, P<0.05) and intermediate for Macun (r=0.521, P<0.01). Correlations
between enzymatic structure and environmental structure were for 0.58 for all catchments,
(r=0.584 P<0.001), 0.62 for Loetschental (kryal and krenal: r=0.623, P<0.001; kryal: r=0.846,
P<0.001; krenal r=0.295, P=0.789), 0.52 for Val Roseg and (kryal and krenal: r=0.519, P<0.001;
505
kryal: r=0.331, P=0.088; krenal r=0.2865, P=0.534) and 0.32 for Macun (kryal and krenal:
r=0.320, P=0.149; kryal: r=0.344, P=0.802; krenal r=0.409, P=0.121). See also table 4.
Refinement of individual dependency of enzymatic activity on environmental variables by
multiple linear regression and relative importance metrics revealed that PP and NO 2-N had a
negative influence (or correlation) on most of enzymes, whereas pH, D90D10, PN, PO4-P,
510
alkalinity and temperature positively influenced enzyme activities (Table 5).
Fitting single OTU’s on the community function NMDS outcropped 108 OTU’s out of 191
OTU’s that could have been fitted with a permutation power of P<0.05, 74 OTU's with a power
<0.01, 50 with power <0.001, 30 OTU's with power <0.0001, and 17 OTU's with a power of
<0.00001 (100000 permutations). OTU's with fitting power <0.01 were split into a fraction
515
showing a direction of gradient towards the kryal systems of Val Roseg and Loetschental and a
fraction towards the Macun catchment. Only 4 OTU’s showed a gradient towards Roseg and
20
Loetschental krenal system with power P<0.001. One OTU could be fitted with a power below
P<0.0001 towards this system (appendix Figure S4).
21
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24
Supplementary Tables
Appendix Table 1 Physico-chemical parameters, given are the average ± standard deviation, N = number of sampled sites
Physico-chemical and microbial parameters
Catchment
595
Samping
Date
A
Val Roseg
O
J
A
Loetschental
O
J
600
A
Macun
O
Catchment
Samping
Date
A
Val Roseg
O
J
A
Loetschental
O
J
A
Macun
O
Stream type N
Temperature
[°C]
Conductivity
[µS cm -1]
pH
D90D10
OM
[g 100g-1dw]
DOC
[mg C L-1]
POC
[mg C L-1]
TIC
[mg C L-1]
kryal
krenal
kryal
krenal
kryal
krenal
10
8
10
6
9
8
3.12
6.98
2.46
3.65
3.69
6.23
±
±
±
±
±
±
2.16
1.96
1.73
0.55
2.27
2.64
25.12
44.20
58.97
72.57
102.91
78.54
±
±
±
±
±
±
1.83
27.96
17.42
22.74
14.87
41.03
7.51
7.00
7.58
6.93
7.48
6.90
±
±
±
±
±
±
0.34
0.38
0.41
0.30
0.32
0.38
71.99
111.26
48.67
36.48
56.12
156.26
±
±
±
±
±
±
51.69
126.51
43.22
23.57
74.65
267.12
0.31
0.49
0.35
0.87
0.31
1.10
±
±
±
±
±
±
0.10
0.22
0.05
0.84
0.09
1.20
0.77
0.39
1.47
1.00
0.37
1.69
±
±
±
±
±
±
1.66
0.20
1.02
0.53
0.24
3.18
0.36
0.27
1.58
0.16
0.27
0.20
±
±
±
±
±
±
0.10
0.17
2.60
0.10
0.10
0.05
2.78
5.12
5.79
7.58
5.60
6.51
±
±
±
±
±
±
0.30
2.80
1.94
1.81
0.99
2.62
kryal
krenal
kryal
krenal
kryal
krenal
4
6
3
4
4
6
6.20
13.67
5.00
6.43
5.40
9.43
±
±
±
±
±
±
2.86
5.63
2.03
3.25
1.92
4.63
27.63
76.38
40.25
102.67
66.20
96.88
±
±
±
±
±
±
6.99
28.97
11.44
87.36
27.84
48.09
6.79
6.51
6.40
6.53
7.05
6.53
±
±
±
±
±
±
0.35
0.26
0.32
0.27
0.40
0.24
14.41
58.77
57.41
27.81
14.30
97.42
±
±
±
±
±
±
3.02
65.82
75.49
15.83
2.88
122.04
0.33
0.74
0.88
0.65
0.14
0.51
±
±
±
±
±
±
0.04
0.33
0.58
0.38
0.04
0.22
0.13
0.48
3.59
1.06
5.70
3.38
±
±
±
±
±
±
0.04
0.34
3.87
0.61
5.58
5.64
0.42
0.27
0.44
1.89
0.34
0.61
±
±
±
±
±
±
0.32
0.09
0.36
3.14
0.13
0.60
2.66
4.69
4.12
4.74
3.25
4.33
±
±
±
±
±
±
0.57
1.54
0.75
1.06
1.00
1.93
kryal
krenal
kryal
krenal
6
11
3
7
7.08
13.75
4.20
4.45
±
±
±
±
5.13
3.01
0.14
0.90
6.45
7.20
12.00
9.04
±
±
±
±
3.18
2.85
1.41
3.74
4.80
4.79
4.80
5.03
±
±
±
±
0.24
0.35
0.09
0.25
63.71
48.10
24.24
44.26
±
±
±
±
66.58
27.24
19.52
22.97
2.64
3.28
1.14
1.81
±
±
±
±
2.74
3.72
0.06
1.47
0.45
1.23
1.08
4.98
±
±
±
±
0.09
1.04
0.18
5.56
0.37
0.92
0.34
1.53
±
±
±
±
0.26
1.44
0.28
1.12
2.29
2.13
0.83
1.16
±
±
±
±
1.46
1.37
0.02
0.21
Stream type N
NH4-N
[µg L-1]
NO2-N
[µg N L-1]
NO3-N
[mg N L-1]
DN
[mg N L-1]
PN
[mg N L-1]
PO4 -P
[µg P L-1]
DP
[µg P L-1]
PP
[µg P L-1]
kryal
krenal
kryal
krenal
kryal
krenal
10
8
10
6
9
8
22.12 ± 15.28
2.64 ± 0.40
0.13 ± 0.00
0.25 ± 0.00
0.03 ± 0.00
5.29 ± 2.41
5.71 ± 2.83
219.05 ± 81.59
2.50 ± 0.00
1.01 ± 0.04
0.15 ± 0.07
0.25 ± 0.00
0.02 ± 0.02
2.50 ± 0.00
2.50 ± 0.00
10.93 ± 14.28
7.35 ± 5.95
1.89 ± 1.38
0.13 ± 0.00
0.26 ± 0.02
0.06 ± 0.06
7.94 ± 7.02
9.10 ± 8.79
3.02 ± 1.27
1.00 ± 0.00
0.15 ± 0.06
0.26 ± 0.02
0.01 ± 0.01
2.50 ± 0.00
2.97 ± 1.14
11.23 ± 6.76
1.64 ± 0.45
0.22 ± 0.11
0.25 ± 0.00
0.04 ± 0.01
3.21 ± 1.45
4.30 ± 2.19
40.78 ± 37.04
2.50 ± 0.00
1.00 ± 0.00
0.20 ± 0.09
0.25 ± 0.00
0.03 ± 0.02
2.50 ± 0.00
2.50 ± 0.00
0.79 ± 0.54
kryal
krenal
kryal
krenal
kryal
krenal
4
6
3
4
4
6
6.80 ± 5.28
1.03 ± 0.05
0.13 ± 0.00
0.25 ± 0.00
0.02 ± 0.01
2.50 ± 0.00
2.50 ± 0.00
7.27 ± 6.15
1.00 ± 0.00
0.13 ± 0.00
0.25 ± 0.01
0.02 ± 0.01
2.50 ± 0.00
2.50 ± 0.00
2.50 ± 0.00
1.00 ± 0.00
0.13 ± 0.00
0.25 ± 0.00
0.02 ± 0.01
3.33 ± 1.28
3.25 ± 1.14
62.68 ± 79.16
2.50 ± 0.00
1.00 ± 0.00
0.13 ± 0.00
0.25 ± 0.00
0.17 ± 0.29
2.50 ± 0.00
2.50 ± 0.00
56.79 ± 96.08
20.30 ± 14.07
1.25 ± 0.50
0.13 ± 0.00
0.25 ± 0.00
0.04 ± 0.01
7.05 ± 6.55
8.65 ± 9.65
41.60 ± 52.78
11.35 ± 8.92
1.17 ± 0.41
0.13 ± 0.00
0.25 ± 0.00
0.06 ± 0.05
4.58 ± 2.89
4.77 ± 3.23
14.26 ± 10.24
kryal
krenal
kryal
krenal
6
11
3
7
5.22 ± 4.26
1.00 ± 0.00
0.16 ± 0.03
0.25 ± 0.00
0.03 ± 0.01
6.18 ± 4.80
7.50 ± 5.31
2.45 ± 1.94
9.76 ± 13.44
1.00 ± 0.00
0.13 ± 0.00
0.25 ± 0.00
0.07 ± 0.05
4.39 ± 3.11
6.48 ± 5.11
2.80 ± 2.96
2.50 ± 0.00
1.00 ± 0.00
0.26 ± 0.11
0.39 ± 0.11
0.06 ± 0.04
2.50 ± 0.00
2.50 ± 0.00
6.07 ± 7.16
1.00 ± 0.00
0.13 ± 0.00
0.25 ± 0.00
0.11 ± 0.07
2.50 ± 0.00
2.93 ± 1.06
2.83 ± 3.30
10.13 ± 14.79
25
Bacteria abundance
2.01E+07 ± 1.44E+07
1.20E+08 ± 1.34E+08
454.72 ± 722.43 4.68E+06 ± 2.31E+06
3.12E+08 ± 2.56E+08
1.68 ± 1.49
5.72E+06 ± 4.86E+06
4.73E+08 ± 9.31E+08
154.91 ± 165.75 1.11E+07 ± 6.00E+06
20.77 ± 19.74 5.46E+07 ± 6.80E+07
5.99E+06 ± 2.24E+06
7.72E+07 ± 7.44E+07
9.22E+06 ± 5.88E+06
4.54E+07 ± 4.30E+07
5.84E+08 ± 8.51E+08
1.14E+09 ± 1.46E+09
1.30E+08 ± 3.42E+07
1.85E+08 ± 1.21E+08
Appendix Table 2 Summary of ANOVA analysis for the eight measured enzymes, given are F-ratios, see text for enzyme abbreviations
Source of variation
df
Alph
Bet
Xyl
Est
Function
Nac
Catchment (C)
2
17.69***
11.13***
6.01*
85.93***
0.51
25.24***
65.86***
4.73*
32.51***
Watersystem (W)
1
28.87***
28.77***
43.64***
3.10
33.15***
19.87***
14.85***
48.07***
17.43***
Sampling Date (S)
2
1.35
2.08
1.71
1.38
0.85
1.29
1.51
1.21
1.45
CxW
2
2.37
3.33*
4.98**
1.96
5.66**
1.94
2.84
6.02**
1.60
CxS
3
0.68
1.94
2.72*
1.15
4.61**
2.04
0.41
1.94
2.18
WxS
2
0.19
0.06
0.17
1.00
1.84
2.11
0.76
0.80
0.92
CxW xS
3
1.56
3.64*
2.94*
0.29
1.26
1.24
0.55
1.16
1.67
*
P<0.05
**
P<0.01
*** P<0.001
605
26
Leu
End
Phos
total activity
610
615
Appendix Table 3 Enzymatic activities (average±SD), N = number of sampled sites, n= 3 replicates per site, see main text for abbreviations
Enzymatic activities [n mol substrate g-1 h-1]
620
Catchment
Sampling
Stream type
Date
A
625
Val Roseg
O
J
A
Loetschental
O
J
A
Macun
O
N
kryal
krenal
kryal
krenal
kryal
krenal
10
8
10
6
9
8
kryal
krenal
kryal
krenal
kryal
krenal
4
6
3
4
4
6
kryal
krenal
kryal
krenal
6
11
3
7
Alph
Bet
Xyl
Nac
Est
Leu
End
24.11 ± 14.56
85.36 ± 64.65
194.75 ± 260.11
629.57 ± 1045.99
Phos
10.31 ± 6.37
27.18 ± 19.89
679.99 ± 530.18
1091.97 ± 827.63
880.27 ± 953.79
80.25 ± 41.35
54.42 ± 58.97
213.43 ± 292.18
2482.50 ± 1652.01
1511.02 ± 1895.75
269.63 ± 476.81
561.26 ± 782.69
1811.76 ± 1965.82
88.42 ± 134.36
390.61 ± 287.01
23.75 ± 15.44
108.41 ± 52.80
6.77 ± 5.68
9.69 ± 14.22
955.08 ± 2076.65
562.01 ± 1121.61
101.72 ± 107.00
190.64 ± 138.20
18.99 ± 6.17
58.16 ± 38.16
312.95 ± 284.42
5692.19 ± 6424.34
184.59 ± 174.02
56.08 ± 79.42
94.39 ± 87.16
5.57 ± 5.18
16.43 ± 26.58
839.19 ± 909.04
750.85 ± 852.35
1342.77 ± 1332.85
89.84 ± 102.64
141.64 ± 97.72
1333.22 ± 2927.52
114.14 ± 198.01
330.36 ± 777.92
354.15 ± 364.27
3439.80 ± 3840.35
179.37 ± 210.42
914.21 ± 1756.86
9.62 ± 6.43
14.56 ± 15.53
2.52 ± 2.24
11.41 ± 19.24
371.30 ± 523.01
215.43 ± 90.65
357.01 ± 412.59
45.31 ± 12.96
71.58 ± 68.39
153.83 ± 120.23
26.32 ± 30.07
34.73 ± 41.15
109.92 ± 98.30
524.60 ± 392.76
64.03 ± 66.92
153.34 ± 126.01
7.70 ± 4.02
14.59 ± 6.46
3.38 ± 2.19
5.93 ± 5.24
219.38 ± 263.20
191.66 ± 92.50
168.47 ± 204.89
19.83 ± 7.79
91.32 ± 74.85
215.83 ± 227.00
38.00 ± 39.87
104.15 ± 71.68
104.10 ± 86.64
1841.93 ± 2358.75
47.08 ± 40.37
325.85 ± 328.77
44.96 ± 24.29
197.70 ± 173.35
24.48 ± 14.46
73.88 ± 103.59
4307.61 ± 7921.58
1201.03 ± 669.86
2967.09 ± 5375.57
139.74 ± 67.23
114.60 ± 145.52
385.09 ± 571.94
57.60 ± 76.13
124.53 ± 157.96
205.81 ± 281.25
1696.96 ± 2981.65
109.16 ± 143.18
269.46 ± 307.60
9.45 ± 8.06
72.82 ± 75.30
7.21 ± 5.43
44.40 ± 59.93
9.37 ± 3.74
241.19 ± 208.81
50.30 ± 44.86
9.12 ± 9.18
22.03 ± 19.73
6.80 ± 2.88
10.02 ± 10.49
181.24 ± 131.34
10.09 ± 10.67
298.79 ± 272.60
4.08 ± 6.12
279.09 ± 195.58
5.40 ± 3.45
27.92 ± 15.91
3.58 ± 2.34
16.26 ± 12.23
4.74 ± 0.65
111.82 ± 54.57
3.01 ± 5.14
79.66 ± 35.70
8.83 ± 10.53
52.07 ± 51.89
12.21 ± 5.74
553.61 ± 383.06
1.82 ± 2.53
404.74 ± 278.47
26.28 ± 36.88
114.85
± 171.65
27
Appendix Table 4 F-Values of pairwise PERMANOVA comparisons of community structure and enzymatic activities. Groups are split by catchments, water source and season, dF tot are given in parentheses
Catchment
630
Season
Catchment
Season
Summer
krenal
kryal
Macun
635
Water
Winter
krenal
kryal
Summer
krenal
kryal
640
Val Roseg
Winter
krenal
kryal
Spring
krenal
kryal
Summer
645
krenal
kryal
Loetschental
Winter
krenal
kryal
Spring
krenal
kryal
Macun
Summer
Val Roseg
Winter
Summer
ARISA
(17)0.89
(17)0.99
(14)0.82
(19)3.11* (21)41.96*** (17)9.13*** (21)31.67***(19)10.48***(20)27.84***
(11)1.55
(8)0.68
(13)2.18 (15)29.24*** (11)6.7** (15)19.41*** (13)7.08** (14)14.72**
(11)8.08**
(9)4.86**
(8)3.71*
(9)6.03**
(8)1.04
(13)2.05 (15)39.43*** (11)5.89** (15)22.74*** (13)8.30** (14)17.29***
(11)13.13** (9)5.75**
(8)4.75*
(9)7.75** (11)16.44**
(14)1.52*
(8)0.77
(8)1.79*
(10)0.85
(10)1.75*
(21)7.41*** (15)4.50*** (15)5.16** (12)3.43**
(17)2.37***
(11)1.90** (11)2.20**
(8)2.04*
(21)11.75*** (15)7.91*** (15)8.56*** (12)6.51**
(19)2.78*** (13)2.29*** (13)2.26*** (10)1.96**
(20)9.14*** (14)5.98*** (14)6.25** (11)4.86**
(17)2.47***
(11)1.68** (11)1.98**
(12)25.02**
(8)3.91*
krenal
(12)11.48** (10)3.88*
(17)14.55*** (13)2.48* (17)11.51*** (15)1.17
(17)3.98***
(13)0.63
(15)4.63***
(15)5.85**
(17)4.59***
(13)0.78
(16)4.61*** (18)2.77** (14)5.71***
(13)2.85*
(18)1.56
(16)5.32***
(13)0.90
(15)2.87***
(11)1.32
(15)4.76***
(13)1.13
krenal
kryal
(5)3.33
(6)3.75
(8)9.64*
(6)3.54*
(10)1.09
(11)2.50*
(13)2.12
(11)2.52
(12)8.71**
(13)0.87
(8)2.33
(9)1.57
(14)7.54*
(15)20.42** (13)0.60
(11)4.24**
(9)1.95
(15)10.10*** (13)1.29
(12)9.28**
(10)0.82
(11)3.00*
(14)8.58**
(12)0.89
(11)6.87*
(12)1.86
(9)2.10
(8)2.32
(9)2.54
(11)1.14
(9)2.01
(6)2.00
(7)0.18
(9)3.16
(7)0.13
(6)2.44
(8)1.80
(6)1.71
(9)4.29*
(7)0.08
(9)2.03*
Enzymes
(14)3.48**
(13)3.19** (11)2.40*** (12)2.53*
(9)1.69*
(14)2.41**
(8)1.73*
(8)1.81*
(5)1.55
(10)1.19
(12)1.65
(8)1.52*
(12)2.44*
(11)1.85
(8)0.83
(6)1.31
(15)4.60***
(9)3.30**
(9)3.72**
(6)3.06*
(11)2.28*
(13)2.87**
(9)3.20**
(13)3.32** (11)2.59*** (12)2.62*
(9)2.11*
(7)0.61
(6)1.58
(13)0.91
(15)3.37**
(11)1.20
(15)6.11***
(14)4.25***
(11)0.56
(9)1.90*
(8)0.75
(9)2.61**
(11)2.24** (13)3.15**
(9)3.5**
(13)4.86*** (11)2.52*** (12)3.36**
(9)2.01*
(7)0.82
(6)1.43
(7)1.06
(8)1.42
(6)3.54*
*
P<0.05
** P<0.01
*** P<0.001
28
(13)1.07
(9)1.59
(11)3.34
(9)2.88**
(1)1.71*
(11)5.90**
(13)1.01
(13)1.85*
(9)3.24**
(15)35.46** (13)0.094
(13)1.23 (15)15.99*** (13)0.80
(11)1.94*
(11)1.45*
(9)5.37*
(6)2.52
(6)2.54*
(9)3.12***
(9)4.26**
(11)2.62
(9)3.19**
(15)4.27**
(11)8.56**
(13)1.95
(9)2.84**
(17)1.98**
kryal
(17)12.57*** (15)8.98*** (14)5.38** (15)9.84** (17)2.79*** (15)7.85***
(15)4.17***
(10)1.45*
krenal
(8)5.90**
(16)12.92**
(8)1.52*
kryal
(11)8.16*
(17)12.48*** (18)2.91
(17)7.44***
krenal
(16)11.17**
(15)9.38*** (19)2.72* (17)21.34*** (18)2.27
(17)6.47*** (19)2.71** (15)7.87***
(15)0.54
kryal
Spring
kryal
(19)2.54*** (13)2.04*** (13)2.23**
kryal
Winter
krenal
(11)1.97**
krenal
Summer
kryal
(17)1.75*
kryal
Loetschental
Spring
krenal
(17)1.41*
krenal
Winter
(13)0.80
(11)2.83
(14)11.58** (12)1.09
(9)2.84
Appendix Table 5 Model parameters of AIC selected multiple linear regression between enzymatic activity and physicochemical parameters and its relative importance metrics. Models are based on enzyme activities standardized to OM
650
Enzyme
655
660
Relative importance metrics
Multiple linear regression
Alph
Bet
Xyl
Nac
Est
Leu
End
Phos
AIC modell
parameters
8
7
7
6
7
7
7
8
dF
Residual
SE
multiple
R2adj
F-stat
P-Value
96
97
97
98
97
97
97
96
1.007
1.022
0.933
1.236
0.936
1.082
1.213
1.11
0.442
0.444
0.371
0.218
0.757
0.411
0.75
0.356
11.3
12.84
9.76
5.825
47.21
11.37
45.59
8.196
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
29
Total
responce
variance
1.818
1.877
1.384
1.952
3.597
1.987
5.89
1.916
Proportion
explained
by model
48.49%
48.10%
41.33%
26.29%
77.31%
45.08%
76.69%
40.58%
Appendix Table 6 Left side: explained deviance (Dev) of the response surface (generalized additive models) of the
2
environmental variables and fitted factors with their squared correlation coefficients (r ) on the EF NMDS. Right side:
Canonical coefficients from the of forward selected physico-chemical parameters incorporated into the global RDA model
2
explaining EF. Given are the first two constraint axes. Explained variations of the constraint axes and R of selected model
2
parameters are based on unadjusted R
RDA canonical
coefficients
NMDS
Variables
dF
F
Dev
P
Temperature
Conductivity
pH
D90D10
OM
DOC
POC
TIC
NH4-N
NO2-N
NO3-N
DON
PN
PO4-P
DP
PP
Factors
5.21
6.22
8.64
2.45
7.17
2.84
6.25
4.20
2.00
6.98
7.96
2.00
2.00
7.08
6.79
6.96
6.55
7.22
32.55
0.17
4.69
0.23
1.07
5.14
12.16
8.22
2.37
0.39
1.30
3.06
2.65
4.39
26.8%
32.5%
74.8%
0.8%
<0.001
<0.001
<0.001
0.88
<0.001
0.87
0.39
<0.001
<0.001
<0.001
<0.05
0.68
0.28
<0.01
<0.05
<0.001
P
27.9%
1.2%
8.9%
18.5%
19.3%
38.7%
19.7%
0.8%
2.5%
20.5%
17.9%
Catchment
25.7%
r2
0.31
Sampling Date
0.07
<0.05
Water
0.26
<0.001
<0.001
30
R2 of forward
selected variables
RDA1
(52.52%)
RDA2
(3.80%)
R
-0.08
0.44
0.37
0.08
-0.11
0.10
0.03
0.04
0.07
0.07
-0.06
-0.04
0.27
-0.11
0.01
0.01
0.08
-0.06
2
Appendix Table 7 Left side: explained deviance (Dev) of the response surface (generalized additive models) of the
environmental variables and fitted factors with their squared correlation coefficients (r 2) on the BCC NMDS. Right side:
Canonical coefficients from the of forward selected physico-chemical parameters incorporated into the global RDA model
2
explaining BCC. Given are the first two constraint axes. Explained variations of the constraint axes and R of selected model
2
parameters are based on unadjusted R
RDA canonical
coefficients
NMDS
Variables
dF
F
Dev
P
Temperature
Conductivity
pH
D90D10
OM
DOC
POC
TIC
NH4-N
NO2-N
NO3-N
DON
PN
PO4-P
DP
PP
Factors
6.06
7.28
8.29
2.00
8.58
4.04
6.81
6.90
7.34
5.01
6.53
2.00
5.52
7.81
8.28
6.82
8.22
3.95
17.21
0.50
10.74
1.23
1.34
1.93
4.22
9.15
1.39
2.56
1.65
2.88
3.65
3.50
34.9%
25.8%
60.4%
1.0%
50.5%
6.7%
11.1%
14.4%
26.6%
32.6%
10.7%
4.8%
10.3%
23.1%
28.0%
<0.001
<0.001
<0.001
0.61
<0.001
0.30
0.24
0.07
<0.001
<0.001
0.22
0.08
0.15
<0.01
<0.001
<0.01
P
Catchment
22.0%
r2
0.27
Samling Date
0.06
<0.05
Water
0.30
<0.001
<0.001
31
R2 of forward
selected
variables
RDA1
(14.7%)
RDA2
(3.7%)
R
-0.04
0.01
-0.01
-0.06
-0.02
-0.41
0.02
0.02
0.10
-0.03
0.04
0.01
-0.07
0.04
-0.04
-0.01
0.01
0.02
0.08
0.13
0.05
0.03
0.01
0.02
2
Appendix Table 8 Procrustes analysis of community-, functional- and physico-chemical characteristics based NMDS. Given
are r-values (correlations) of the symmetric procrustes rotation, EF = enzymatic functioning, Env = physico-chemical
parameters, BCC = bacterial community composition
Val Roseg
Loetschental
Macun
Total
Total
Total
EF
Env
EF
Env
EF
Env
BCC
0.668*** 0.600***
0.551*** 0.425*
0.431* 0.521**
kryal
krenal
kryal
krenal
kryal
krenal
EF
Env
EF
Env
EF
Env
EF
Env
EF
Env
EF
Env
BCC
0.558*** 0.375*
0.332
0.482* 0.84*** 0.695**
0.43
0.51
0.358
0.538
0.506* 0.606***
665
*
P<0.05
**
P<0.01
*** P<0.001
32
Appendix Figure S1
NMDS of physico-chemical parameters. Dots indicate individual sites. Coding is equal to sites in
figure 1 in the main manuscript, suffix letter indicate sampling date (August: A, October: O, June:
670
J). Dark grey dots correspond to kryal sites and light grey dots to krenal sites. Dispersionellipses depict the standard error of weighted average scores of water source within catchment
grouping (confidence limit=0.95).
Appendix Figure S2
Boxplots of environmental variables. Whiskers indicate 1.5x interquartile range. Groups are split
675
by water source (brackets), catchments and sampling dates.
Appendix Figure S3
Boxplots of multivariate homogeneity of community and enzymatic structure and physicochemical characteristics. Boxes summarize the distances to group centroids on the first two
PCoA axes as assessed by MHGD. Whiskers indicate 1.5x interquartile range. Upper panel
680
shows group distances of physico-chemical characteristics, middle panel distances of the
community structure (ARISA), and lower panel the distances of bacteria function (Enzymes).
Groups are split by water source, catchments and sampling dates Letters show significant
differences based on Tukey’s HSD (P<0.05).
685
Appendix Figure S4
NMDS of enzymatic activities. Upper panel: Dots indicate individual sites. The size of dots is
relative to the sum of logarithms of all measured enzymes standardized to OM. Orange dots
correspond to kryal sites and yellow dots to krenal sites. Dispersion-ellipses depict the standard
error of weighted average scores of catchment groupings (confidence limits = 0.95).
690
Environmental variables and bacterial OTU’s are fitted as arrows. Projections of sites on fitted
environmental vectors (arrows) show maximum correlation with the corresponding variable and
vector lengths indicate strengths of gradient. Significantly fitted vectors are indicated by blue
33
arrows for environmental variables (P<0.05 = dark blue, P<0.05 = light blue) and grey arrows for
bacterial OTU's (P<0.001). Lower panel: Dots depicts individual sites. Coding is equal to sites
695
in figure 1 in the main manuscript, suffix letter indicate sampling date (August: A, October: O,
June: J).
Appendix Figure S5a to S5c
NMDS of enzymatic activities with response surface as assessed by generalized additive
models (GAM) for the measured physico-chemical variables. The size of dots is relative to the
700
number of OTU’s at a site. Each contour line is annotated with the specific value of the variable.
The percentages of variances explained by variables are given and correspond to the values
from appendix table 6.
Appendix Figure S6
NMDS of ARISA profiles. Upper panel: Dots indicate individual sites. The size of dots is relative
705
to the number of OTU’s at a site. Bright blue dots correspond to kryal sites and dark blue dots to
krenal sites. Dispersion-ellipses depict the standard error of weighted average scores of water
source (kryal, krenal) within catchment groupings (Macun = M, Loetschental = L, Val Roseg =
VR) (confidence limits = 0.95). Environmental variables and enzyme activity are fitted as arrows.
Projections of sites on fitted environmental vectors (arrows) show maximum correlation with
710
corresponding variable and vector lengths indicate strengths of gradient. Significantly fitted
vectors (P<0.05) are indicated by blue arrows for environmental variables, orange for enzymatic
activities and red for bacterial domain and groups. Lower panel: Dots depict individual sites.
Coding is equal to sites in figure 1 in the main manuscript, suffix letter indicate sampling date
(August: A, October: O, June: J).
715
Appendix Figure S7a to S7c
NMDS of ARISA profiles with response surface as assessed by generalized additive models
(GAM) for the measured physico-chemical variables. The size of dots is relative to the number of
34
OTU’s at a site. Each contour line is annotated with the specific value of the variable. The
720
percentages of variances explained by variables are given and correspond to the values from
appendix table 7.
Appendix Figure S8a to S8p
Bubble maps of physico-chemical variables. Sizes of the bubbles are standardized by the
margin maximum value of distinct variable. Grey dots correspond to krenal sites and green dots
725
to kryal sites. Coding is equal to sites in figure 1 in the main manuscript, suffix letter indicate
sampling date (August: A, October: O, June: J).
Appendix Figure S9 a to S9c
PcoA of (a) physico-chemical, (b) enzymatic activities and (c) community structure. Colors depict
the different sites split by catchment, water sources and sampling date. Coding is equal to sites
730
in figure 1 in the main manuscript, suffix letter indicate sampling date (August: A, October: O,
June: J). MHGD analysis (i.e. distances to centroids) were based on these ordinations.
35
Appendix Figure S1
735
740
0.4
745
kryal
krenal
Stress:
12
PN
POC
750
M2O
M13A
M1A
M9O
0.2
M16A
NMDS2
755
VR13O
VR10A
VR9A
0.0
PP
VR11O
-0.2
VR14O
VR12A
VR13A
VR14A
VR17A
M5A
M15A
DP
NO2-N
PO4-P
NH4-N L7J
OM
M14A
M17A
M8A
M krenal M7A
M7O M10A
M3A
M9A
M8O
M6O
M3O
DOC M6A
M kryal
M11A
M2A
M4A
M14O
M10O M12A
M4O
Temp
D90D10
VR7A
L7O
VR2A
VR15A VR3A
L8J L7AVR18A
VR5A
VR11A
VR12O
DON
VR10O
M12O
L kryal L9A L8AL10A
L4O
VR18O
VR kryal L6A
VR8A
L10O
pH
L2J
VR18J
L4A
L5J
L10J VR15J
VR12J
VR6A NO3-N
L6O L3J L5A
L9O
VR9O
L1J
L
krenal
VR16AL9J
L3A
L4J
VR16O
L2A VR5J VR7O
VR
VR5OVR16J krenal
VR1A
VR14J
VR13J
VR15O L5OVR8O VR17J
VR10J
VR1O VR6J VR3J
VR9J VR7J L1A VR2J
VR2O
L6J
VR1J
VR8J
VR6O
TIC VR4O VR4A
Conductivity
L1O
-0.4
-0.2
0.0
NMDS1
36
VR4J
0.2
Appendix Figure S2
0.45
1
DON [mg N L ]
1
DOC [mg C L ]
15
10
5
0
0.35
0.30
0.25
L
M
VR
L
M
VR
L
M
VR
L
M
VR
L
M
VR
L
M
VR
L
M
VR
L
M
VR
0.5
0.4
7
4
0.30
0.25
1
1
PN [mg N L ]
2.5
POC [mg C L ]
0.40
2.0
1.5
1.0
0.5
0.20
0.15
0.10
0.05
0.0
0.00
L
M
VR
L
M
VR
400
300
8
D90D10
1
TIC [mg C L ]
10
6
200
4
100
2
0
L
M
VR
L
M
VR
kryal
1
NO3-N [mg N L ]
0.35
0.30
0.25
0.20
0.15
L
M
kryal
VR
L
M
VR
krenal
37
krenal
Appendix Figure S3
Distance to centroid
0.20
Sampling
Month
A
O
J
0.15
a
ac
ab
ab
bc
ab
ab
0.10
Physicochem ical
param eters
ab
bc
ab
bc
bc
bc
bc
b
b
0.05
c
c
Distance to centroid
0.30
ac
bc
0.25
ac
EF
ac
ab
ab
a
a
0.20
a
a
0.15
a ab
a
a
0.10
0.05
0.55
a
Distance to centroid
760
0.50
0.45
a
a
a
a
a
ab
ab
BCC
ab
a
ab
0.40
a
ab
ab
ab
b
0.35
0.30
0.25
L
M
VR
kryal
L
M
krenal
38
VR
Appendix Figure S4
765
0.6
kryal
krenal
Stress:
6.64
pH
770
CondX905
0.4
X1085
0.2
775
X1031
X1013
X269
X1121
X695
X1043
X1007
X953
NO3-N
PP
780
NMDS2
0.0
X305
X659
X551
X701
X413
Alph
DON
X923
X881
X1067 X911
X533
X569
TIC
X995
X1091
X599
X1175
VR kryal L kryal
X509
L krenal
Bet Xyl
Leu
VR krenal
PO4-P
X809
Est
End
X941
NO2-N X983
X1073
0.2
X989
DP
Nac
POC DOC
D90D10
PN
M kryal
X485 X647
M X443
krenal
X719 X521
X899
NH4-N
X563
X707
OM
X605
X203
X1079
X1127
X257
X665
X689
X239
X215 X965
X1283
X455
Phos
X425X641
X629
X587 X473 X713
X251
X329
X263
X1187
X419
X347
X317
X851
0.4
Temp
X209
X515X575
X1049
785
X773
X407
0.6
X449
X653
0.8
790
kryal
krenal
Stress:
-1.0
-0.5
0.0
0.5
0.4
0.2
NMDS2
0.0
VR14J
VR12J
0.2
L6J
VR13J
L6A
VR8J
L1O
VR6O
VR18A
VR17J
L8AL2AVR3J VR18J
VR13O
VR2J
L8J VR6JL9A L9J
VR2O
VR6A
VR18O
VR7O
VR9O
L7J L3J L5J L10J
VR12O
VR14O
L1J VR17AL10O VR15A
L1A
VR5J VR9J
VR4J
L3A
L5A L10A
VR10O
L9OL2JL7AL7O
VR10J VR10A
L4A
VR8A
VR13A VR7A
VR15JL5O VR3A
VR11O
VR4A M3O
VR16OM11A
VR14A L4O
VR9AVR5A
M4O M13A
VR4O
M17A
M9O
VR15O
L6O
VR1J M10O
M12A
VR5O VR16J
VR12A
M12O
M15A
M5A
VR11A
VR7J L4J
M1A
VR1O
M3A
M14O
M16A
M8A M4A
M7O
VR2A VR8O
M2A M8O
M7A
M14A
M9A
0.4
M2O
VR1A
M6O
VR16A
M6A
M10A
0.6
0.8
-1.0
-0.5
0.0
NMDS1
39
0.5
Appendix Figure S5a
1
0.6
Conductivity [ S cm ]
Sediment origin
26.8 %
Sediment origin
32.5 %
kryal
krenal
80
0.2
0.4
kryal
krenal
0.2
0.4
0.6
Temperature [°C]
70Loetsch.Ground
60
8
6
30
20
0.0
Macun.Glacial
Macun.Ground
10
-0.6
-0.6
0
7
5
4
50
-0.4
9
-0.2
Macun.Glacial
Macun.Ground
40
Roseg.Ground
Roseg.Glacial
Loetsch.Glacial
80
3
NMDS2
Roseg.Ground
-0.2
0.0
Roseg.Glacial
Loetsch.Glacial
-0.4
NMDS2
Loetsch.Ground
-0.5
0.0
-1.0
-0.5
0.0
NMDS1
pH
D90D10
0.6
NMDS1
Sediment origin
74.8 %
0.4
kryal
krenal
Sediment origin
0.8 %
kryal
krenal
55
0.2
7
0.2
0.4
0.6
-1.0
Stress:
6.64
-0.8
-0.8
Stress:
6.64
Loetsch.Ground
Loetsch.Ground
60
6
Macun.Glacial
Macun.Ground
7
Roseg.Ground
Roseg.Glacial
Loetsch.Glacial
0.0
5
4. 5
5.
5
7. 5
NMDS2
Roseg.Ground
65
Macun.Glacial
Macun.Ground
70
-0.2
0.0
Roseg.Glacial
Loetsch.Glacial
-0.2
NMDS2
6
.5
-0.4
-0.6
-0.6
-0.4
75
-0.5
0.0
-1.0
-0.5
NMDS1
1
1
0.6
DOC [mg C L ]
Sediment origin
27.9 %
5
Loetsch.Ground
0.0
1.4
1. 5
1.45
Macun.Glacial
Macun.Ground
1.
1.
1. 7
-0.6
-0.6
1.
1.65
85
-0.4
-0.4
2
75
1. 8
1.55
5
1.6
1. 9
NMDS2
3
-0.2
Macun.Glacial
Macun.Ground
Roseg.Ground
Roseg.Glacial
Loetsch.Glacial
-0.2
2.
5
0.0
Roseg.Ground
1.2 %
kryal
krenal
1.
Loetsch.Ground
0.5
1
Roseg.Glacial
Loetsch.Glacial
Sediment origin
0.2
0.4
kryal
krenal
0.2
0.4
0.6
Organic matter [g g dw]
-1.0
-0.5
Stress:
6.64
-0.8
Stress:
6.64
-0.8
NMDS2
0.0
NMDS1
9
-1.0
Stress:
6.64
-0.8
-0.8
Stress:
6.64
0.0
-1.0
NMDS1
-0.5
0.0
NMDS1
40
Appendix Figure S5b
1
1
0.6
TIC [mg C L ]
Sediment origin
8.9 %
Sediment origin
18.5 %
kryal
krenal
5.5
0.2
0.4
kryal
krenal
0.2
0.4
0.6
POC [mg C L ]
0.4
Loetsch.Ground
1
0. 8
NMDS2
Macun.Glacial
Macun.Ground
0. 6
0.9
7
4.5
Macun.Glacial
Macun.Ground
4
-0.4
3. 5
-0.5
0.0
-1.0
-0.5
2
0.0
NMDS1
1
1
NO3-N [mg N L ]
0.6
NH4-N [ g L ]
Sediment origin
19.3 %
0.2
0.4
kryal
krenal
Sediment origin
15.9 %
kryal
krenal
0. 12
0.2
0.6
5
Stress:
6.64
NMDS1
Loetsch.Ground
Roseg.Glacial
Loetsch.Glacial
0.0
4
Roseg.Ground
Macun.Glacial
Macun.Ground
0.
0.16
0. 2
6
Macun.Glacial
Macun.Ground
NMDS2
Roseg.Ground
20
-0.2
Loetsch.Ground
0.14
-0.2
Roseg.Glacial
Loetsch.Glacial
16
0.0
12
14
18
NMDS2
2.
-0.8
-0.8
Stress:
6.64
-1.0
0.4
3
-0.6
-0.6
0.8
-0.4
0.
5
0. 7
0.0
0.7
1
0.
Roseg.Ground
Roseg.Glacial
Loetsch.Glacial
-0.2
0. 3
Loetsch.Ground
5
0. 9
0. 5
Roseg.Ground
0.6
0.0
1.1
-0.2
NMDS2
Roseg.Glacial
Loetsch.Glacial
0. 1
-0.4
-0.4
14
8
-0.6
-0.6
10
-1.0
-0.5
0.0
-1.0
NMDS1
1
38.7 %
kryal
krenal
0.6
0.2
0.4
Sediment origin
0.0
1. 5
1. 3
4
1. 2
1. 6
1.
-0.4
Macun.Glacial
Macun.Ground
-0.6
NMDS2
-0.2
Roseg.Ground
1.9
1. 7
1
1.1
Loetsch.Ground
Roseg.Glacial
Loetsch.Glacial
1.8
Stress:
6.64
-1.0
-0.5
-0.5
0.0
NMDS1
NO2-N [mg N L ]
2
Stress:
6.64
-0.8
-0.8
Stress:
6.64
-0.8
795
0.0
NMDS1
41
Appendix Figure S5c
800
1
1
0.6
Sediment origin
0.8 %
0.4
kryal
krenal
0.0
54
Loetsch.Ground55
0. 2
0. 0
Roseg.Ground
0. 2
0. 2
56
57
58
5
0. 2
0. 2
9
6
0. 0
0. 0
-0.5
0.0
-1.0
5
0. 0
55
0. 0
-0.5
6
1
0.6
Sediment origin
20.5 %
0.4
kryal
krenal
Sediment origin
17.9 %
kryal
krenal
0.0
6
7
5
4.
Macun.Glacial
Macun.Ground
-0.4
3
-0.6
-0.6
2
4
-0.4
5
5
6.
5
3.
4
7. 5
5.
8.5
8
4. 5 5
2.5
5
-0.2
Macun.Glacial
Macun.Ground
5
Roseg.Ground
Roseg.Glacial
Loetsch.Glacial
9
5. 5
5.
6
4
6.5
NMDS2
Roseg.Ground
Roseg.Glacial
Loetsch.Glacial
-0.2
0.0
Loetsch.Ground
4.5
NMDS2
7. 5
3.5
4
5
0.2
0.2
3.
-0.5
0.0
-1.0
NMDS1
1
Sediment origin
25.7 %
0.2
kryal
krenal
0.0
Loetsch.Ground
Loetsch.Glacial
50Roseg.Glacial
Macun.Glacial
Macun.Ground
0
300
Roseg.Ground
15
-0.2
250
0
-0.6
50
-0.4
10
0
200
-0.8
Stress:
6.64
-1.0
-0.5
-0.5
0.0
NMDS1
PP [ g P L ]
3
Stress:
6.64
-0.8
-0.8
Stress:
6.64
-1.0
0.6
7
1
7
0.4
0. 0
DP [ g P L ]
5
NMDS2
65
0.0
Loetsch.Ground
3
825
0. 0
NMDS1
PO4-P [ g P L ]
0.6
Macun.Glacial
Macun.Ground
Stress:
6.64
NMDS1
0.4
45
4. 5
-1.0
820
Roseg.Ground
4
-0.8
Stress:
6.64
-0.8
815
0. 0
-0.6
-0.6
61
0. 2
Loetsch.Ground
35
Roseg.Glacial
Loetsch.Glacial
-0.4
-0.2
.2
Macun.Glacial
0Macun.Ground
-0.4
810
NMDS2
0. 2
Roseg.Glacial
Loetsch.Glacial
53
2.5 %
kryal
krenal
0.2
0. 2
Sediment origin
0.0
52
NMDS2
0. 2
0.2
805
PN [mg N L ]
-0.2
0.4
0.6
DN [mg N L ]
0.0
NMDS1
42
Appendix Figure S6
830
kryal
krenal
Stress:
15
NO2-N
OM
0.5
NH4-N
835
DP
PO4-P
PP
DON
M kryal
POC
Bet Nac
D90D10
NO3.N
VR kryal
Est
0.0
840
NMDS2
End
PN
Cyt.Flav
L kryal
TIC
845
Phos
M krenal
L krenal
VR krenal
DOC
Xyl
Leu
0.5
Cond
Temp
pH
Alph
850
-1.0
-0.5
0.5
VR11A
0.0
0.5
L1A
M14O
L6A
L3J
L3A
M16A
M17A
M5A
M1A
VR10A
VR12A
VR7A
M10O
M14A
VR5A
M9O
M9A
VR1J
VR11O
VR12O
M11A
VR1O VR4O
VR14A
L4A
M2A M12A
M15A
VR9O
VR13A
M12O
VR10O
VR4A
VR9A L1J
VR8A
VR10J
L4O
VR16J M2OVR16O
VR14J
VR1A
VR14O
VR13O
VR4J
M13A
VR8J
VR13J
L5A
VR12J
M7O VR18JL7J VR16A
VR7O
VR5O
M7A
L5J
VR18O
L1O
VR5J
M8A
L7A M3A
VR2O
L6O
VR6O
VR15J
VR6A
L6J
VR8O VR9J
L7O M6A
VR7J
M6O
VR2J
VR15O M3O
VR17A
VR3A VR15A
L8A
L4J
L8J
VR2A
L5O
VR18A VR6J
L9J
M4O
VR17J
L9O L10O
M8O
L10A
L10J
L2J
VR3J
L2A
L9A
M4A
0.0
0.5
NMDS2
M10A
-1.0
-0.5
0.0
NMDS1
43
0.5
Appendix Figure S7a
855
Temperature [°C]
1
Conductivity [ S cm ]
Sediment origin
Sediment origin
34.9 %
25.8 %
kryal
krenal
40
50
Macun.Glacial
Loetsch.Glacial
11
7
9
-0.5
8
-0.5
0.0
NMDS2
12
6
70
Loetsch.Glacial
5
Macun.Ground
Loetsch.Ground
Roseg.Ground
10
0.0
Stress:
15
-1.0
-0.5
0.0
Stress:
15
0.5
-1.0
0.0
NMDS1
pH
D90D10
Sediment origin
0.5
Sediment origin
60.4 %
kryal
krenal
1%
kryal
krenal
5
0.5
6.
7
0.5
-0.5
NMDS1
5
Macun.Glacial
6
4.
Macun.Glacial
5
0.0
Macun.Ground
Loetsch.Ground
Roseg.Ground
75
Roseg.Glacial
0.0
NMDS2
5
Macun.Ground
Loetsch.Ground
Roseg.Ground
Loetsch.Glacial
Loetsch.Glacial
60
50
-0.5
-0.5
45
Stress:
15
-0.5
0.0
Stress:
15
0.5
-1.0
-0.5
0.0
NMDS1
1
1
Organic matter [g g dw]
POC [mg C L ]
Sediment origin
Sediment origin
50.5 %
11.1 %
0.5
kryal
krenal
1
3.
Macun.Glacial
5
2
3
5
0.8
2.
5
0.5
0
Macun.Ground
Loetsch.Ground
Roseg.Ground
Roseg.Glacial
0.8
0.6
Loetsch.Glacial
Macun.Ground
Loetsch.Ground
Roseg.Ground
0. 6
1.
4
NMDS2
0
Roseg.Glacial
Macun.Glacial
5
0.0
0.5
kryal
krenal
0.0
0.5
NMDS1
1
-1.0
Loetsch.Glacial
0.4
-0.5
0.2
-0.5
NMDS2
70
65
55
1.2
NMDS2
5.
Roseg.Glacial
80
1.4
NMDS2
4
Roseg.Glacial
90
Macun.Ground
Loetsch.Ground
Roseg.Ground
80
Roseg.Glacial
3
Macun.Glacial
60
20
2
10
0.5
40
30
0.5
kryal
krenal
Stress:
15
-1.0
-0.5
0.0
Stress:
15
0.5
-1.0
NMDS1
-0.5
0.0
NMDS1
44
0.5
Appendix Figure S7b
1
1
DOC [mg C L ]
TIC [mg C L ]
Sediment origin
Sediment origin
6.7 %
14.4 %
kryal
krenal
3
0.5
0.5
kryal
krenal
0. 5
2.
3.5
Macun.Glacial
Macun.Glacial
4
5
1. 5
Macun.Ground
Loetsch.Ground
Roseg.Ground
5
0.0
NMDS2
Roseg.Glacial
0.0
NMDS2
1
5.
4.5
Roseg.Glacial
Macun.Ground
Loetsch.Ground
Roseg.Ground
5
Loetsch.Glacial
2.
-0.5
2
3
-0.5
5
3
Loetsch.Glacial
Stress:
15
-1.0
-0.5
0.0
Stress:
15
0.5
-1.0
-0.5
0.0
NMDS1
0.5
NMDS1
1
1
NH4-N [ g L ]
NO3-N [mg N L ]
Sediment origin
Sediment origin
27 %
10.7 %
0.5
kryal
krenal
0.5
kryal
krenal
22
20
Macun.Glacial
Macun.Glacial
18
0.0
0.0
NMDS2
10
Loetsch.Glacial
0.16
8
Roseg.Glacial
0.16
Macun.Ground
Loetsch.Ground
Roseg.Ground
0. 15
Macun.Ground
Loetsch.Ground
Roseg.Ground
0.18
NMDS2
Roseg.Glacial
14
12
0.17
0.17
16
Loetsch.Glacial
0.15
4
0.14
6
0. 1
3
0.
-0.5
-0.5
2
12
Stress:
15
-1.0
-0.5
0.0
Stress:
15
0.5
-1.0
NMDS1
1
Sediment origin
32.6 %
0.5
kryal
krenal
2
2
0.0
Roseg.Glacial
Macun.Ground
Loetsch.Ground
Roseg.Ground
1. 6
Loetsch.Glacial
1.
4
1.
2
1
-0.5
NMDS2
Macun.Glacial
1. 8
0.
8
Stress:
15
-1.0
-0.5
0.0
NMDS1
NO2-N [mg N L ]
2.
-0.5
0.0
0.5
NMDS1
45
0.5
Appendix Figure S7c
860
1
1
DN [mg N L ]
PN [mg N L ]
Sediment origin
Sediment origin
4.8 %
10.3 %
0.268
0.266
0.26Macun.Glacial
4
0.06
Macun.Glacial
0.252
Loetsch.Glacial
0.2
5
Roseg.Glacial
Macun.Ground
Loetsch.Ground
Roseg.Ground
Loetsch.Glacial
0.03
0.04
0.246
-0.5
-0.5
0.248
0.244
0.08
0.254
0.05
0.26
0.258
0.256
Macun.Ground
Loetsch.Ground
Roseg.Ground
0.0
NMDS2
Roseg.Glacial
0.0
NMDS2
0.262
0.07
0.5
kryal
krenal
0.5
kryal
krenal
Stress:
15
-1.0
-0.5
0.0
Stress:
15
0.5
-1.0
-0.5
0.0
NMDS1
1
1
PO4-P [ g PL ]
DP [ g PL ]
Sediment origin
Sediment origin
23.1 %
kryal
krenal
28 %
kryal
krenal
5.
5
6
5
4
7
6.5
0.5
5
0.5
0.5
NMDS1
Macun.Glacial
6
8
Macun.Glacial
Roseg.Glacial
0.0
NMDS2
0.0
NMDS2
Macun.Ground
Loetsch.Ground
Roseg.Ground
5. 5
7
Loetsch.Glacial
4
3.5
2
2
-0.5
-0.5
Macun.Ground
Loetsch.Ground
Roseg.Ground
6
5
Loetsch.Glacial
4.5
2. 5
9
5
Roseg.Glacial
6
3
6.
3
Stress:
15
-1.0
-0.5
0.0
Stress:
15
0.5
-1.0
NMDS1
1
Sediment origin
22 %
0.5
kryal
krenal
Macun.Glacial
Roseg.Glacial
0
0.0
25
Macun.Ground
Loetsch.Ground
Roseg.Ground
0
0
15Loetsch.Glacial
0
50
-0.5
NMDS2
300
100
Stress:
15
-1.0
-0.5
0.0
NMDS1
PP [ g PL ]
200
-0.5
0.0
0.5
NMDS1
46
0.5
Appendix Figure S8a
784500
785500
786500
787500
784500
785500
786500
787500
784500
785500
786500
DOC
POC
TIC
785500
786500
x coordinate (km)
787500
785500
786500
144000
142000
143000
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
y coordinate (km)
144000
143000
784500
145000
x coordinate (km)
145000
x coordinate (km)
787500
784500
x coordinate (km)
785500
786500
143000
144000
145000
787500
784500
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
785500
786500
x coordinate (km)
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
x coordinate (km)
47
y coordinate (km)
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
x coordinate (km)
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
Organic matter
142000
142000
143000
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
144000
145000
D90D10
y coordinate (km)
145000
144000
143000
142000
y coordinate (km)
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
142000
144000
143000
142000
y coordinate (km)
145000
784500
Conductivity
y coordinate (km)
143000
144000
kryal
krenal
142000
y coordinate (km)
145000
Temperature
787500
787500
Appendix Figure S8b
784500
785500
786500
787500
784500
785500
786500
787500
784500
785500
786500
143000
y coordinate (km)
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
144000
145000
DN
142000
142000
143000
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
144000
145000
NO3.N
y coordinate (km)
145000
144000
143000
142000
y coordinate (km)
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
787500
784500
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
785500
786500
x coordinate (km)
PN
PO4.P
DP
PP
785500
786500
x coordinate (km)
787500
784500
785500
786500
787500
784500
x coordinate (km)
785500
786500
x coordinate (km)
865
48
144000
142000
143000
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
y coordinate (km)
144000
142000
143000
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
y coordinate (km)
144000
143000
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
145000
x coordinate (km)
145000
x coordinate (km)
145000
x coordinate (km)
142000
144000
143000
142000
y coordinate (km)
145000
784500
NO2.N
y coordinate (km)
144000
143000
142000
y coordinate (km)
145000
NH4.N
787500
784500
787500
VR8A
VR1A
VR2A
VR3A
VR5A
VR4A
VR18A
VR6A
VR17A
VR7A
VR16A
VR15A
VR14A
VR13A
VR12A
VR11A
VR10A
VR9A
785500
786500
x coordinate (km)
787500
Appendix Figure S8c
785500
786500
787500
784500
785500
786500
787500
784500
785500
786500
x coordinate (km)
DOC
POC
TIC
785500
786500
x coordinate (km)
787500
784500
785500
786500
144000
142000
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
143000
VR8O
VR1O
VR2O
y coordinate (km)
144000
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
143000
VR8O
VR1O
VR2O
145000
x coordinate (km)
145000
x coordinate (km)
787500
784500
x coordinate (km)
786500
145000
784500
VR8O
VR1O
VR2O
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
785500
786500
x coordinate (km)
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
x coordinate (km)
49
787500
VR8O
VR1O
VR2O
785500
144000
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
143000
VR8O
VR1O
VR2O
142000
142000
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
Organic matter
y coordinate (km)
y coordinate (km)
VR8O
VR1O
VR2O
144000
145000
D90D10
143000
145000
144000
143000
142000
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
142000
144000
y coordinate (km)
143000
142000
784500
y coordinate (km)
VR8O
VR1O
VR2O
145000
784500
Conductivity
y coordinate (km)
143000
144000
kryal
krenal
142000
y coordinate (km)
145000
Temperature
787500
787500
Appendix Figure S8d
785500
870
786500
787500
784500
785500
786500
787500
784500
785500
786500
145000
144000
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
143000
VR8O
VR1O
VR2O
142000
142000
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
DN
y coordinate (km)
y coordinate (km)
VR8O
VR1O
VR2O
144000
145000
NO3.N
143000
145000
144000
143000
142000
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
787500
784500
VR8O
VR1O
VR2O
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
785500
786500
x coordinate (km)
PN
PO4.P
DP
PP
785500
786500
x coordinate (km)
787500
784500
785500
786500
787500
784500
x coordinate (km)
785500
786500
x coordinate (km)
50
144000
142000
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
143000
VR8O
VR1O
VR2O
y coordinate (km)
144000
142000
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
143000
VR8O
VR1O
VR2O
y coordinate (km)
144000
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
143000
VR8O
VR1O
VR2O
145000
x coordinate (km)
145000
x coordinate (km)
145000
x coordinate (km)
142000
144000
143000
142000
y coordinate (km)
784500
y coordinate (km)
VR8O
VR1O
VR2O
145000
784500
NO2.N
y coordinate (km)
144000
143000
142000
y coordinate (km)
145000
NH4.N
787500
784500
787500
VR8O
VR1O
VR2O
VR5O
VR4O
VR18O
VR6O
VR7O
VR16O
VR15O
VR14O
VR13O
VR12O
VR11O
VR10O
VR9O
785500
786500
x coordinate (km)
787500
Appendix Figure S8e
784500
786500
787500
784500
786500
787500
784500
785500
786500
POC
TIC
785500
786500
x coordinate (km)
787500
VR10J
VR9J
785500
786500
144000
143000
142000
y coordinate (km)
144000
143000
784500
145000
DOC
145000
x coordinate (km)
VR10J
VR9J
787500
784500
x coordinate (km)
787500
VR10J
VR9J
785500
786500
144000
143000
784500
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
VR10J
VR9J
785500
786500
x coordinate (km)
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
x coordinate (km)
51
145000
VR10J
VR9J
x coordinate (km)
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
y coordinate (km)
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
x coordinate (km)
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
Organic matter
142000
142000
VR10J
VR9J
785500
143000
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
144000
145000
D90D10
y coordinate (km)
144000
145000
VR10J
VR9J
785500
143000
142000
y coordinate (km)
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
142000
144000
143000
142000
y coordinate (km)
145000
784500
Conductivity
y coordinate (km)
143000
144000
kryal
krenal
142000
y coordinate (km)
145000
Temperature
787500
787500
Appendix Figure S8f
784500
786500
787500
784500
786500
787500
784500
VR10J
VR9J
785500
786500
143000
y coordinate (km)
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
144000
145000
DN
142000
142000
VR10J
VR9J
785500
143000
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
144000
145000
NO3.N
y coordinate (km)
144000
145000
VR10J
VR9J
785500
143000
142000
y coordinate (km)
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
787500
784500
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
VR10J
VR9J
785500
786500
x coordinate (km)
PN
PO4.P
DP
PP
786500
x coordinate (km)
787500
786500
787500
x coordinate (km)
VR10J
VR9J
785500
786500
x coordinate (km)
52
144000
143000
y coordinate (km)
144000
784500
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
142000
VR10J
VR9J
785500
143000
y coordinate (km)
144000
784500
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
142000
VR10J
VR9J
785500
143000
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
145000
x coordinate (km)
145000
x coordinate (km)
145000
x coordinate (km)
142000
142000
143000
144000
145000
784500
NO2.N
y coordinate (km)
144000
143000
142000
y coordinate (km)
145000
NH4.N
y coordinate (km)
875
787500
784500
787500
VR8J
VR1J
VR2J
VR3J
VR5J
VR4J
VR18J
VR6J
VR17J
VR7J
VR16J
VR15J
VR14J
VR13J
VR12J
VR10J
VR9J
785500
786500
x coordinate (km)
787500
Appendix Figure S8g
633000
637000
633000
635000
POC
TIC
635000
x coordinate (km)
637000
633000
635000
637000
x coordinate (km)
635000
x coordinate (km)
880
53
145000
y coordinate (km)
L6A
L5A
L4A
L2A
L3A
L1A
633000
L6A
L5A
L4A
L2A
L3A
L1A
633000
635000
x coordinate (km)
L7A
L10A
143000
L6A
L5A
L4A
L2A
L3A
L1A
637000
L9A
L8A
144000
y coordinate (km)
L7A
L10A
143000
L6A
L5A
L4A
L2A
L3A
L1A
L9A
L8A
145000
DOC
145000
x coordinate (km)
L7A
L10A
143000
143000
L6A
L5A
L4A
L2A
L3A
L1A
L9A
L8A
144000
145000
144000
y coordinate (km)
L7A
L10A
x coordinate (km)
y coordinate (km)
144000
635000
Organic matter
L9A
L8A
x coordinate (km)
L7A
L10A
143000
145000
637000
L9A
L8A
633000
L6A
L5A
L4A
L2A
L3A
L1A
144000
145000
635000
L7A
L10A
143000
L6A
L5A
L4A
L2A
L3A
L1A
D90D10
L9A
L8A
144000
y coordinate (km)
L7A
L10A
144000
145000
L9A
L8A
633000
y coordinate (km)
Conductivity
kryal
krenal
143000
y coordinate (km)
Temperature
637000
637000
Appendix Figure S8h
633000
637000
633000
635000
145000
y coordinate (km)
L7A
L10A
L6A
L5A
L4A
L2A
L3A
L1A
143000
143000
L6A
L5A
L4A
L2A
L3A
L1A
L9A
L8A
144000
145000
L7A
L10A
144000
y coordinate (km)
L9A
L8A
637000
633000
635000
x coordinate (km)
PN
PO4.P
DP
PP
635000
x coordinate (km)
637000
633000
635000
637000
635000
x coordinate (km)
54
637000
637000
L9A
L8A
144000
L7A
L10A
L6A
L5A
L4A
L2A
L3A
L1A
143000
L6A
L5A
L4A
L2A
L3A
L1A
633000
x coordinate (km)
y coordinate (km)
L7A
L10A
143000
L6A
L5A
L4A
L2A
L3A
L1A
L9A
L8A
144000
y coordinate (km)
L7A
L10A
143000
L6A
L5A
L4A
L2A
L3A
L1A
L9A
L8A
145000
x coordinate (km)
145000
x coordinate (km)
y coordinate (km)
144000
635000
DN
x coordinate (km)
L7A
L10A
143000
145000
143000
637000
L9A
L8A
633000
L6A
L5A
L4A
L2A
L3A
L1A
145000
145000
635000
L7A
L10A
144000
y coordinate (km)
L6A
L5A
L4A
L2A
L3A
L1A
NO3.N
L9A
L8A
144000
145000
144000
L7A
L10A
633000
y coordinate (km)
NO2.N
L9A
L8A
143000
y coordinate (km)
NH4.N
633000
635000
x coordinate (km)
637000
Appendix Figure S8i
635000
633000
635000
637000
633000
TIC
635000
x coordinate (km)
637000
633000
635000
637000
L6O
L5O
L4O
L1O
633000
x coordinate (km)
635000
x coordinate (km)
55
145000
L6O
L5O
L4O
L1O
633000
635000
x coordinate (km)
L7O
L10O
143000
L1O
637000
L9O
144000
y coordinate (km)
L6O
L5O
L4O
143000
L1O
144000
y coordinate (km)
L6O
L5O
L4O
145000
POC
145000
DOC
145000
x coordinate (km)
L7O
L10O
L7O
L10O
143000
635000
x coordinate (km)
L9O
y coordinate (km)
L1O
L9O
144000
145000
L6O
L5O
L4O
143000
L1O
L7O
L10O
144000
y coordinate (km)
L6O
L5O
L4O
Organic matter
L9O
x coordinate (km)
L7O
L10O
144000
145000
637000
L9O
633000
L7O
L10O
143000
L1O
D90D10
L9O
144000
L6O
L5O
L4O
143000
y coordinate (km)
y coordinate (km)
L7O
L10O
144000
145000
L9O
633000
885
Conductivity
kryal
krenal
143000
y coordinate (km)
Temperature
637000
637000
Appendix Figure S8j
635000
637000
637000
633000
145000
L7O
L10O
L6O
L5O
L4O
L1O
143000
L1O
143000
635000
y coordinate (km)
L6O
L5O
L4O
L9O
144000
145000
L7O
L10O
144000
y coordinate (km)
L9O
635000
637000
633000
635000
PN
PO4.P
DP
PP
635000
x coordinate (km)
637000
633000
635000
637000
635000
x coordinate (km)
56
L7O
L10O
L6O
L5O
L4O
L1O
143000
L1O
637000
637000
L9O
144000
L6O
L5O
L4O
633000
x coordinate (km)
y coordinate (km)
L7O
L10O
143000
L1O
L9O
144000
y coordinate (km)
L6O
L5O
L4O
143000
L1O
L7O
L10O
144000
y coordinate (km)
L6O
L5O
L4O
L9O
145000
x coordinate (km)
145000
x coordinate (km)
145000
x coordinate (km)
145000
144000
L1O
DN
x coordinate (km)
L7O
L10O
143000
L6O
L5O
L4O
633000
L9O
633000
L7O
L10O
143000
L1O
145000
y coordinate (km)
L6O
L5O
L4O
NO3.N
L9O
144000
145000
144000
L7O
L10O
633000
y coordinate (km)
NO2.N
L9O
143000
y coordinate (km)
NH4.N
633000
635000
x coordinate (km)
637000
Appendix Figure S8k
635000
633000
637000
633000
635000
POC
TIC
635000
x coordinate (km)
637000
633000
635000
637000
x coordinate (km)
635000
x coordinate (km)
57
145000
y coordinate (km)
L6J
L5J
L4J
L2J
L3J
L1J
633000
L6J
L5J
L4J
L2J
L3J
L1J
633000
635000
x coordinate (km)
L7J
L10J
143000
L6J
L5J
L4J
L2J
L3J
L1J
637000
L9J
L8J
144000
y coordinate (km)
L7J
L10J
143000
L6J
L5J
L4J
L2J
L3J
L1J
L9J
L8J
145000
DOC
145000
x coordinate (km)
L7J
L10J
143000
143000
L6J
L5J
L4J
L2J
L3J
L1J
L9J
L8J
144000
145000
144000
L7J
L10J
x coordinate (km)
y coordinate (km)
144000
635000
Organic matter
L9J
L8J
x coordinate (km)
L7J
L10J
143000
145000
637000
L9J
L8J
633000
L6J
L5J
L4J
L2J
L3J
L1J
144000
145000
633000
L7J
L10J
143000
L6J
L5J
L4J
L2J
L3J
L1J
y coordinate (km)
L7J
L10J
D90D10
L9J
L8J
144000
y coordinate (km)
L9J
L8J
144000
145000
Conductivity
kryal
krenal
143000
y coordinate (km)
Temperature
y coordinate (km)
890
637000
637000
Appendix Figure S8l
633000
637000
633000
635000
145000
y coordinate (km)
L7J
L10J
L6J
L5J
L4J
L2J
L3J
L1J
143000
143000
L6J
L5J
L4J
L2J
L3J
L1J
L9J
L8J
144000
145000
L7J
L10J
144000
y coordinate (km)
L9J
L8J
637000
633000
635000
x coordinate (km)
PN
PO4.P
DP
PP
635000
x coordinate (km)
637000
633000
635000
637000
635000
x coordinate (km)
895
58
637000
637000
L9J
L8J
144000
L7J
L10J
L6J
L5J
L4J
L2J
L3J
L1J
143000
L6J
L5J
L4J
L2J
L3J
L1J
633000
x coordinate (km)
y coordinate (km)
L7J
L10J
143000
L6J
L5J
L4J
L2J
L3J
L1J
L9J
L8J
144000
y coordinate (km)
L7J
L10J
143000
L6J
L5J
L4J
L2J
L3J
L1J
L9J
L8J
145000
x coordinate (km)
145000
x coordinate (km)
y coordinate (km)
144000
635000
DN
x coordinate (km)
L7J
L10J
143000
145000
143000
637000
L9J
L8J
633000
L6J
L5J
L4J
L2J
L3J
L1J
145000
145000
635000
L7J
L10J
144000
y coordinate (km)
L6J
L5J
L4J
L2J
L3J
L1J
NO3.N
L9J
L8J
144000
145000
144000
L7J
L10J
633000
y coordinate (km)
NO2.N
L9J
L8J
143000
y coordinate (km)
NH4.N
633000
635000
x coordinate (km)
637000
Appendix Figure S8m
806000
806500
805500
806000
179000
805000
805500
806000
805000
805500
806000
x coordinate (km)
806500
M16A
M15A
805000
805500
806000
806500
178800
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
178600
178200
M10A
M13A
M12A
M14A M11A
M17A
178400
y coordinate (km)
178800
178600
178200
178400
y coordinate (km)
178800
M16A
M15A
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
M10A
M13A
M12A
M14A M11A
M17A
M16A
M15A
805000
x coordinate (km)
805500
806000
x coordinate (km)
59
178800
M10A
M13A
M12A
M14A M11A
M17A
M16A
M15A
805000
805500
806000
x coordinate (km)
179000
TIC
179000
POC
179000
DOC
806500
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
178600
178200
M16A
M15A
x coordinate (km)
M10A
M13A
M12A
M14A M11A
M17A
y coordinate (km)
178800
178600
806500
178400
179000
805000
178400
y coordinate (km)
M16A
M15A
M10A
M13A
M12A
M14A M11A
M17A
x coordinate (km)
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
Organic matter
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
x coordinate (km)
178600
178400
178200
M10A
M13A
M12A
M14A M11A
M17A
178200
M16A
M15A
805500
178800
178200
M10A
M13A
M12A
M14A M11A
M17A
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
178600
y coordinate (km)
178800
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
805000
y coordinate (km)
D90D10
179000
Conductivity
178400
kryal
krenal
178600
178400
178200
y coordinate (km)
179000
Temperature
806500
806500
Appendix Figure S8n
805500
806000
805000
805500
806000
806500
179000
M16A
M15A
805000
805500
178800
178200
M10A
M13A
M12A
M14A M11A
M17A
806000
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
178600
y coordinate (km)
178800
178600
178400
y coordinate (km)
M16A
M15A
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
178400
179000
DN
806500
M10A
M13A
M12A
M14A M11A
M17A
M16A
M15A
805000
805500
806000
PN
PO4.P
DP
PP
805000
805500
806000
x coordinate (km)
806500
805500
806000
806500
M16A
M15A
805500
806000
x coordinate (km)
60
806500
178800
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
178600
178400
M10A
M13A
M12A
M14A M11A
M17A
805000
x coordinate (km)
y coordinate (km)
178600
178800
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
178200
M16A
M15A
805000
178400
y coordinate (km)
178800
M10A
M13A
M12A
M14A M11A
M17A
178200
M16A
M15A
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
178600
178200
M10A
M13A
M12A
M14A M11A
M17A
178400
y coordinate (km)
178800
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
806500
179000
x coordinate (km)
179000
x coordinate (km)
179000
x coordinate (km)
179000
x coordinate (km)
178600
178400
178200
y coordinate (km)
178800
806500
M10A
M13A
M12A
M14A M11A
M17A
178200
M16A
M15A
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
178600
178200
M10A
M13A
M12A
M14A M11A
M17A
178400
y coordinate (km)
178800
178600
178400
178200
y coordinate (km)
M9A
M5A
M7A
M6A
M8A
M1A
M3AM4A
M2O
M2A
805000
900
NO3.N
179000
NO2.N
179000
NH4.N
M10A
M13A
M12A
M14A M11A
M17A
M16A
M15A
805000
805500
806000
x coordinate (km)
806500
Appendix Figure S8o
805500
806000
806500
805500
806000
806500
179000
805000
805500
806000
TIC
M10O
M12O
M14O
805500
806000
x coordinate (km)
806500
178800
178600
M3OM4O
M10O
M12O
M14O
178200
178200
805000
805000
805500
806000
806500
805000
x coordinate (km)
805500
806000
x coordinate (km)
61
178800
178600
M10O
M12O
M14O
805000
805500
806000
x coordinate (km)
M9O
M7O
M6O
M8O
178400
y coordinate (km)
178800
178600
M3OM4O
178400
y coordinate (km)
178800
178600
178200
178400
M10O
M12O
M14O
806500
179000
POC
179000
DOC
179000
x coordinate (km)
M9O
M7O
M6O
M8O
M3OM4O
178200
178200
805000
x coordinate (km)
M3OM4O
y coordinate (km)
178800
178600
M10O
M12O
M14O
M9O
M7O
M6O
M8O
178400
179000
M10O
M12O
M14O
M3OM4O
x coordinate (km)
M9O
M7O
M6O
M8O
Organic matter
M9O
M7O
M6O
M8O
178400
178800
M3OM4O
178200
178400
M10O
M12O
M14O
y coordinate (km)
178600
M3OM4O
M9O
M7O
M6O
M8O
178600
y coordinate (km)
178800
M9O
M7O
M6O
M8O
178400
kryal
krenal
805000
y coordinate (km)
D90D10
179000
Conductivity
178200
y coordinate (km)
179000
Temperature
806500
806500
Appendix Figure S8p
805500
806000
806500
179000
M10O
M12O
M14O
805500
806000
806500
178800
M10O
M12O
M14O
178200
178200
805000
M3OM4O
178600
y coordinate (km)
178800
178600
y coordinate (km)
M3OM4O
M9O
M7O
M6O
M8O
178400
179000
DN
M9O
M7O
M6O
M8O
178400
178800
M10O
M12O
M14O
178200
805000
805000
805500
806000
806500
805000
805500
806000
PN
PO4.P
DP
PP
805500
806000
x coordinate (km)
806500
805000
805500
806000
806500
805000
x coordinate (km)
805500
806000
x coordinate (km)
62
178800
178600
M3OM4O
M10O
M12O
M14O
178400
178800
M10O
M12O
M14O
M9O
M7O
M6O
M8O
178200
178200
805000
y coordinate (km)
M10O
M12O
M14O
M3OM4O
178600
178800
y coordinate (km)
M10O
M12O
M14O
M3OM4O
M9O
M7O
M6O
M8O
178200
178600
M3OM4O
M9O
M7O
M6O
M8O
178600
y coordinate (km)
178800
M9O
M7O
M6O
M8O
806500
179000
x coordinate (km)
179000
x coordinate (km)
179000
x coordinate (km)
179000
x coordinate (km)
178400
y coordinate (km)
178600
y coordinate (km)
178400
M10O
M12O
M14O
M3OM4O
178400
920
NO3.N
M9O
M7O
M6O
M8O
178400
179000
178800
178600
M3OM4O
178200
y coordinate (km)
M9O
M7O
M6O
M8O
178200
915
NO2.N
179000
NH4.N
910
178400
905
806500
805000
805500
806000
x coordinate (km)
806500
Figure S9a
925
0.2
Env PCoA
M14A
M17A
M8A
M10A
M9A
M7O
M7A
M3A
M6A
M3O
M6O M8O
M4A
M11A
M14O
M12A M2A
M10O M4O
M9O
M2O
M5A
M16A
M15A
VR13O
VR10A
VR12A
VR14A
VR13A
VR9A
VR11A
-0.1
0.0
VR17A
M12O
VR3A
L7J
L7O VR2A
VR15A
L7A
VR7A
VR18A
L8J
L10A L9A
VR5A
VR12O
VR18J
L10J
L9J
L6A
L9O VR18O
VR8A
L10O
L4A VR10O
L8A
L6O
L1J
L3J
L2J
L4O
L6J
L4JVR9O
L5A
VR15J
L5JL3A
VR12J
VR16A
VR9J
VR1A
VR6A
VR10J
VR16J
VR5O
VR16O
VR8O
VR7O VR5J L2A
L1A
L5OVR1O
VR14J
VR2J
VR13J
VR15O
VR17J
VR3J VR1J
VR7J
VR8J
VR2O
VR6J
VR11O
VR14O
VR4O
VR6O
VR4A
L1O
VR4J
-0.2
PCoA2
0.1
M1A
M13A
-0.1
0.0
0.1
PCoA1
63
0.2
Figure S9b
0.3
0.4
Enz PCoA
M10A
M6A
VR16A
M6O
M2O
M14A
0.2
VR1A
0.1
VR2A
L6A
VR14JL6J
M8O
M2A
M7O
VR8O
M14O M8A
M4A
M16A
M1A
M3A
VR1O
VR7JL4J
M5A
M15AM4O
M10O
L6O
VR11A
M13A
M12O
VR12A
VR16J
VR1J
M12A
VR15O
VR5O
VR16O
VR11O VR13A
M17A
VR4A
M9O
M11A
M3O
VR14AL4O
VR3A
VR4O
L4A
VR9A
VR5A
VR8A
VR7A
VR10A
L5O
VR10J
L3A
VR10O VR9J
L10A
L7A
L5A
VR4J
VR15J
L9O
VR18OVR6A
L5J
VR5J
VR7O
L10O
VR15A
L7O
VR14O
VR9OL1A
L1J
L10J
L7J
L3J
L2J
VR2O
L9A
VR12OVR8J VR17A
VR2J
VR6J
L8J
VR13O
VR18J
L2A
L8A VR18AL9J
VR3J
VR17J
L1O
VR6O
-0.2
-0.1
0.0
VR12J
VR13J
-0.3
PCoA2
M9A
M7A
-0.4
-0.2
PCoA1
64
0.0
0.2
930
Figure S9c
0.4
Com PCoA
L10O
L10J
L9JL9A
L10A
0.3
L9O
0.2
VR3J
VR3A
L2A
0.1
0.0
-0.1
-0.2
PCoA2
VR15A
L2J
VR15O
VR15J
VR2J
VR17J
VR6J
L5J
VR18A
L7A
VR4J
L8J
L5A
M4A
L7OL8A M8O
VR18O VR6A
VR16A
VR18J
VR6OM7O
VR16O
VR16J
M3OM4O
L7J
VR1A
VR1O
VR4A
L3J
M8A
M13A
VR1J
VR4O
M3A
M11A
M9O M6O
M15A
M12O
M9A
M2A
M12A
M2OM17AM16A
M7AM6A
M10A
M14O
M14A
M10O
M1A
VR5A
M5A
L4J
VR9J
VR2A
L6O
L5O
VR10J
VR8O
VR8J L1J VR17A
VR8A
VR5J
L1O
VR10O
L4O
VR5O
L4A VR2O
VR13J
VR13A
VR13O
VR7O
VR9A
VR7J
VR9O
VR14J
L3A
L1A
VR14O
VR14A
VR12O
VR7A
VR11O
VR12J
L6A
VR10A
L6J
VR12A
VR11A
-0.2
0.2
0.0
PCoA1
65
0.4