vegetation and erosion rate was near 0 and
very weak to moderate (region B1, Fig. 2E).
Further north (region C, 14°S to 10°S), in the
more vegetated (50 to 60% vegetation cover)
and wetter (200 to 300 mm/year precipitation)
latitudes, a positive strong to very strong cor-
relation was found. We could not document a
similar maximum in the vegetation-erosion cor-
relation (or region C) in the south from 36°S
to 40°S because we lacked samples from the
region. In the most heavily vegetated (50 to
80% cover) and wettest (300 to 700 mm/year
precipitation) area north of 10°S (region B2),
the correlation strength is very weak and similar
to that in region B1 (Fig. 2E).
We interpreted latitudinal changes in the
vegetation-erosion correlation strength (regions
A to C, Fig. 2E) qualitatively on the basis of
abiotic and biotic factors that influence catch-
ment erosion. Region A (18°S to 32°S) has sparse
vegetation cover (<20%) and arid conditions.
Stochastic variations in precipitation occur in
this region over decadal time scales such that
we observed, with one exception, a positive cor-
relation with erosion rates and precipitation
(Fig. 2D). A moderate negative vegetation-erosion correlation occurred in region A, which
indicated that the sparse vegetation present
was sufficient to influence erosion rates by
increasing surface roughness for overland flow
(Fig. 2E). Region B1 (14°S to 18°S and 32°S to
36°S) has a vegetation cover of 20 to ~50% and
represents a transition zone where a very weak
to weak erosion-vegetation correlation occurs.
This weak vegetation-erosion correlation could
be due to competing processes such that in-
creased biotic regolith production associated
with higher vegetation cover is offset by the
ability of vegetation cover to retard the physical
transport of sediment. Alternatively, the weak
correlation between erosion rates and vegeta-
tion in region B1 (and also B2) could reflect
areas where landscapes were closer to steady
state with the rock uplift rate. In steady-state
landscapes, correlations between erosion rate
and vegetation, or precipitation, are expected
to be weak. In this case, erosion rates should be
positively correlated with slope. This interpre-
tation is partially supported in regions B1 and
B2. In region C (14°S to 10°S, Fig. 2E), the
observed maximum in the erosion rate and
vegetation correlation indicated that vegetation
contributed to enhanced weathering and ero-
sion but was ineffective at stabilizing hillslopes
from erosion under the higher (~300 mm/year)
precipitation rates. Finally, the decrease in the
correlation to near zero in the northernmost1360 20 MARCH 2020•VOL 367 ISSUE 6484 SCIENCE
Fig. 2. Latitudinal variations in vegetation cover,
precipitation, slope, and their correlation with
erosion rates from the catchments shown in
Fig. 1A.(A) Vegetation cover and type plotted
versus latitude. Vegetation types shown in colored
zones are from MODIS 2012 vegetation continuous
field data (see also Fig. 1C). The vegetation
types represent mixed forest (I), grassland (II),
open shrubland (III), and barren or sparsely
vegetated areas (IV). (B) TRMM2b precipitation
versus latitude. (C) Mean catchment slope
(90 m window) versus latitude. All dashed lines
in (A) to (C) represent the three-point moving
averages of the 2svariation from the mean
of each value. Solid lines in (A) to (C) represent
the three-point moving averages of values.
(D) Correlation coefficients (R) versus latitude
for erosion rate and slope (red) and erosion rate
and precipitation (blue). Dots and color-shaded
regions show the mean and 1suncertainty
within each bin based on a Monte Carlo analysis
of the variability in erosion rates and precipitation
or slope within each 2° bin (see tables S3 to
S5 for all values plotted). (E) Correlation coefficient
versus latitude for erosion rates and vegetation
cover. Dots and color-shaded regions show
mean and 1suncertainty, as in (D.) The dashed
green line represents trends in the correlation
coefficient with latitude.
Fig. 3. Observed relation-
ship between erosion
rate, vegetation cover,
and mean annual
precipitation rate
(colors) for each
catchment in Figs. 1 and 2.
Black squares represent
outliers that are possibly
biased by glaciation in
the catchment. For com-
parison, fig. S6A is
identical but color-coded
by slope. Regions labeled
correspond to those
identified in Fig. 2E.
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