10.5061/DRYAD.XSJ3TX9CR
Stuble, Katharine
0000-0001-5655-983X
Holden Arboretum
Bewick, Sharon
Clemson University
Fisher, Mark
Boyd Deep Canyon Desert Research Center
Forister, Matthew
University of Nevada Reno
Harrison, Susan
University of California, Davis
Shapiro, Arthur
University of California, Irvine
Latimer, Andrew
0000-0001-8098-0448
University of California, Davis
Fox, Laurel
University of California, Santa Cruz
The promise and the perils of resurveying to understand global change impacts
Dryad
dataset
2020
2020-08-21T00:00:00Z
2020-08-21T00:00:00Z
en
44781 bytes
3
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Historical datasets can be useful tools to aid in understanding the
impacts of global change on natural ecosystems. Resampling of historically
sampled sites (“snapshot resampling”) has often been used to detect
long-term shifts in ecological populations and communities, because it
allows researchers to avoid long-term monitoring costs and investigate a
large number of potential trends. But recent simulation-based research has
called the reliability of resampling into question, and its utility has
not been comprehensively evaluated. Here we combine long-term empirical
datasets with novel community-level simulations to explore the accuracy of
snapshot resampling of both population- and community-level metrics under
a variety of conditions. We show that snapshot resampling often yields
spurious conclusions, but the accuracy of results increases when
inter-annual variability in the response variable is low or the magnitude
of change through time is high. Snapshot resampling also generally
performs better for community-level metrics (e.g. species richness) as
opposed to population-level metrics pertaining to a single species (e.g.
abundance). Finally, we evaluated strategies to improve the accuracy of
snapshot resampling, including sampling multiple years at the end of the
study, but these produced mixed results. Ultimately, we found that
snapshot resampling should be used with caution, but under certain
circumstances, can be a useful for understanding long-term global change
impacts.