Changes in the ecosystem functions along the elevation
gradients.
Since most prior studies have largely focused on the influence of PTE
transport on biodiversity in polluted areas with a single natural
habitat30,31,
the correlation between ecological functions and PTE transport has never
been fully analyzed at multiple spatial scales (i.e., across climate
zones). However, in the natural habitats of the Qilian Mountains, most
soil and plant-mediated functions varied linearly along the elevation
gradients. For the natural ecosystem functions mediated by plants and
soil, climate and topography jointly predicted the changes in habitat
and ecosystem functions (Fig. 3). On average, these factors explained
65% (± 23% (s.d.), ranging from
20% to 99%; Supplementary materials Table 4) of the changes in the
ecosystem functions for the natural habitats over all the elevation
gradients. Most soil- and plant-mediated functions peaked at lower, and
middle elevations (2370-3051 m a.s.l), where the highest MAP
(353.91~445.93 mm year-1), and
relatively low MAT (4.42~6.02℃) were recorded (Fig. 4).
In contrast, pH, electrical conductivity (EC ), and total salt
content declined with elevation, whereas alkaline N peaked at
lower-middle elevations (Fig. 4). For the natural ecosystem functions,
the effect of topography (i.e., slope and aspect) was less important
than that of climatic heterogeneity (MAT, win10, and ET0) in predicting
ecosystem functions (Fig. 3). For the plant-mediated ecosystem
functions, the absolute effect strength values were, on average, higher
for climate change (i.e., ET0, MAT, and win10), whereas the
soil-mediated ecosystem functions were strongly explained by both
topography (i.e., slope and elevation) and climate change (i.e., MAT,
win10, and ET0) (linear mixed effect model, P < 0.05).
———————-
Place Fig 3 here
———————-
The majority of the ecosystem functions (explanatory variable = 92% ±
5% (SD), P < 0.005) were altered by the presence of PTEs,
with the interaction of topographic heterogeneity and climate change
(Fig. 5a). In most cases, the presence of PTEs varied with both the
climate and topography of the study sites in different climate zones
(Supplementary materials Table 2). The two-way interaction models
(PTEs-topography and PTEs-climate) for different elevations explained
most of the 21 ecosystem functional variables (explanatory variable =
39% ± 20% (s.d.), P < 0.005, explanatory variable = 47% ±
26% (s.d.), P < 0.005) (Supplementary materials Table 2). In
the three-way interaction models (climate-PTEs-topography), both
climatic and topographic variables were input, causing the explained
variation in ecosystem functions to increase to 53% ± 26% (s.d.) and
indicating that the interactive model supported the empirical data more
strongly (Supplementary materials Table 2). The climate zones in which
the strongest effects of PTE intensity on ecosystem functions were
observed varied for different response variables (Fig. 4). For example,
the C/N content of the plants in the PTE-polluted habitats decreased as
the elevation increased, which occurred especially in the mine areas of
the warm and relatively humid low-elevation mountain grasslands
(2370-2500 m a.s.l) (residual effect = 0.21, R2 =
0.57, P < 0.005). The NDVI of the PTE-polluted habitats in the
arid low-elevation mountain desert steppe (1000-1500 m a.s.l) changed
significantly, as explained by the local climate (residual effect =
-0.21, R2 = 0.90, P < 0.005; Supplementary
materials Tables 2, 3). The large degree of support for the
climate-PTEs-topography interaction models across ecosystem functions
was robust to different PTEs criteria (Supplementary Note 1,
Supplementary materials Tables 5, 6 and Supplementary Materials Figs. 8,
9) and allowed us to consider potentially confounding environmental
variables that systematically change with elevation (Supplementary Note
1 and Supplementary materials Tables 5, 6). As plant species and
ecosystem functions may respond more strongly to certain factors related
to the ecological risk induced by PTE transport, we tested whether the
uncertainty of ecological risk was affecting the prediction of the
response variables. Our results showed that most of the models equally
supported the prediction of the response variables with or without
considering the uncertainty of ecological risks. Furthermore, we also
tested three models incorporating only a subset of the original data,
and the results supported the complete three-way interaction models
(climate-PTEs-topography) in most cases (explanatory variable = 63% ±
23% (s.d.), P < 0.005; Supplementary Materials Figs. 2-4 and
Supplementary Materials Tables 6, 7, 8).
———————-
Place Fig 4 here
———————-