upstream ( 31 ) (fig. S8). Another potential caveat
is that paleoprecipitation rates and paleovege-
tation cover could differ in magnitude from the
modern values. However, paleo-precipitation
gradients (from Pliocene to modern time) in the
region are similar to modern precipitation
gradients along the Andean Western Cordil-
lera ( 32 ) (fig. S5), and latitudinal variations in
paleovegetation cover in north-central Chile are
estimated to be within 5 to 15% of the present-
day values ( 33 ). Finally, this study focuses on
regional-scale variations in vegetation cover and
catchment erosion. This simplified approach
highlights the need to evaluate how individual
plant functional types (e.g., trees, shrubs, grasses),
and not just total vegetation cover, could affect
biotic weathering and erosional processes
[e.g., (2, 20, 33)].
Our observations have broader implications
for the vegetation cover effects on erosion. The
latitudinal variations that we identified in
the correlation strength between vegetation,
precipitation, and erosion imply that studies
conducted on a smaller spatial scale could
poorly resolve vegetation-erosion interactions.
For example, Fig. 3 shows that over the entire
study area, the magnitude, and variance, of
erosion rates observed decrease with increased
vegetation cover. If we take a subset of samples
from the catchments shown in Fig. 3, then
recovering correlations between vegetation
and erosion would be difficult, particularly
in regions with low (≲60%) vegetation cover,
where the variance in erosion rates is high.
This conclusion helps explain the diversity of
vegetation-erosion relationships synthesized
in previous work ( 34 , 35 ). Results from previous
studies ( 15 , 26 , 36 ) have shown both positive
and negative correlations between vegetation
cover, precipitation, and erosion rates. These
seemingly conflicting results may have occurred
in areas that are located at, or straddle, the
diverse range of climate and vegetation cover
regions identified here (Figs. 2E and 3).
In conclusion, we found that correlations be-
tween catchment erosion and vegetation cover
spanning 30° latitude varied in their direction
(positive or negative) and strength (very weak
to very strong). These observations, taken toge-
ther with previous modeling results, indicated
a bidirectional relationship between vegetation
cover and catchment erosion. The source of this
nonlinearity is due to competing, and latitudi-
nally varying, interactions between precipitation
and vegetation on erosion. Results presented
here provide a regional context for future (smaller
scale) studies investigating similar interactions
over a narrower range of vegetation cover and
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ACKNOWLEDGMENTS
We thank D. Kost and L. Michel for laboratory and field assistance,
respectively. We also thank three anonymous reviewers and
R. Drews for their thoughtful comments.Funding:This study was
funded by a European Research Council (ERC) consolidator
grant (CoG 615703) and the German Science Foundation (DFG)
priority research programEarthShape(EH329/17-2) to T.A.E.
Author contributions:T.A.E. and J.S. planned the study. J.S. was
responsible for all sample collection and calculations. J.S. and
M.S. performed the laboratory analysis. All authors contributed to
manuscript and figure preparation.Competing interests:The
authors have no competing financial conflicts of interest with this
study.Data and materials availability:Data reported in the paper
are presented in the supplementary materials.SUPPLEMENTARY MATERIAL
science.sciencemag.org/content/367/6484/1358/suppl/DC1
Materials and Methods
Figs. S1 to S9
Tables S1 to S6
Google Earth kmz file of catchment properties
References ( 37 – 68 )
10 August 2019; accepted 24 February 2020
10.1126/science.aaz0840area (region B2) indicated that dense vegeta-
tion cover of 50 to 85% hindered erosion such
that the correlation coefficient between vege-
tation and erosion decreased ( 24 ). We also found
that vegetation cover greater than 50% leads
to a maintenance of steep mean slopes (25° to
30°; fig. S6). By contrast, regions A and B1 had
lower mean slope angles between 5° and 25°.
Our observations are consistent with coupled
vegetation-landscape evolution modeling work
that investigated the effects of varying precip-
itation and vegetation cover on catchment erosion
in Chile ( 25 ). More specifically, Schmid et al.
[see figure 17 in ( 25 )] applied a nonlinear pa-
rameterization for vegetation cover–dependent
fluvial erodibility and hillslope diffusivity. They
found an inverse relationship (negative corre-
lation) between catchment erosion and vege-
tation cover for sparsely vegetated areas (~10%
vegetation cover) due to small increases in
precipitation in an arid setting resulting in
an increase in vegetation cover that reduced
erosion. The negative vegetation-erosion cor-
relation and positive precipitation-erosion cor-
relation that we observed in region A (Fig. 2, D
and E) are comparable to this modeling result
( 25 ). By contrast, in more vegetated regions
(~70% vegetation cover), the model results sug-
gest that precipitation and vegetation cover are
positively correlated with catchment erosion.
This trend is caused by the high precipitation
rates required to sustain dense vegetation cover
having a stronger impact on runoff-related
erosion and biotic weathering than the stabi-
lizing effects of vegetation cover on erosion.
This prediction is consistent with the positive
vegetation-erosion and precipitation-erosion cor-
relations that we observed in regions C (~10°S
to 14°S, 50 to 70% vegetation cover, Fig. 2E). The
northward decrease in the vegetation-erosion
correlation (region B2) that we observed -re
flects that above ~50 to 70% vegetation cover,
vegetation effects on inhibiting erosion outpace
increases in the precipitation rates that pro-
mote erosion. Thus, both the observations pre-
sented here and landscape evolution model
results ( 25 ) confirm a bidirectional response of
vegetation cover and precipitation effects on
catchment erosion. Similar findings have been
reported for smaller geographic areas in both
East Africa ( 26 ) and the Himalaya ( 27 ), as well as
globally for differing amounts of tree cover ( 20 ).
Complications associated with our interpre-
tations could result from latitudinal variations in
tectonic activity, paleoclimate, and paleovege-
tation cover. However, the regions of vegetation-
erosion interactions that we identified (Fig. 2)
do not correspond to known patterns of upper
plate seismicity or subducting oceanic ridges
( 28 ) (fig. S7). The main phases of mountain
building in the Andean Western Cordillera were
from 20 to 10 million years ago (Ma) and ter-
minatedaround9Ma( 29 , 30 ), near the time
when river knick-points initiated and migrated
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