Meta-analysis on pulse disturbances reveals differences in functional and compositional recovery across ecosystems
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https://datadryad.org/dataset/doi:10.5061/dryad.cz8w9gj09
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资源简介:
Most ecosystems are affected by anthropogenic or natural pulse
disturbances, which alter the community composition and functioning for a
limited period of time. Whether and how quickly communities recover from
such pulses is central to our understanding of biodiversity dynamics and
ecosystem organization, but also to nature conservation and management.
Here, we present a meta-analysis of 508 (semi-)natural field experiments
globally distributed across marine, terrestrial and freshwater ecosystems.
We found recovery to be significant yet incomplete. At the end of the
experiments, disturbed treatments resembled controls again when
considering abundance (94%), biomass (82%), and univariate diversity
measures (88%). Most disturbed treatments did not further depart from
control after the pulse, indicating that few studies showed novel
trajectories induced by the pulse. Only multivariate community composition
on average showed little recovery: disturbed species composition remained
dissimilar to the control throughout the experiment. Still, when
experiments showed a higher compositional stability, they tended to also
show higher functional stability. Recovery was more complete when systems
had high resistance, whereas resilience and resistance were negatively
correlated. The overall results were highly consistent across studies, but
significant differences between ecosystems and organism groups appeared.
Future research on disturbances should aim to understand these
differences, but also fill obvious gaps in the empirical assessments for
regions (especially the tropics), ecosystems and organisms. In summary, we
provide general evidence that (semi-)natural communities can recover from
pulse disturbances, but compositional aspects are more vulnerable to
long-lasting effects of pulse disturbance than the emergent functions
associated to them.
提供机构:
Dryad
创建时间:
2019-12-19



