Lynn et al., 2019
jueves, 20 de junio de 2019
Context‐dependent biotic interactions predict plant abundance across altitudinal environmental gradients
Lynn et al., 2019
Lynn et al., 2019
Many biotic interactions influence community structure, yet most
distribution models for plants have focused on plant competition or used
only abiotic variables to predict plant abundance. Furthermore, biotic
interactions are commonly context‐dependent across abiotic gradients.
For example, plant‐plant interactions can grade from competition to
facilitation over temperature gradients. We used a hierarchical Bayesian
framework to predict the abundances of 12 plant species across a
mountain landscape and test hypotheses on the context‐dependency of
biotic interactions over abiotic gradients. We combined field‐based
estimates of six biotic interactions (foliar herbivory and pathogen
damage, fungal root colonization, fossorial mammal disturbance, plant
cover, and plant diversity) with abiotic data on climate and soil depth,
nutrients, and moisture. All biotic interactions were significantly
context‐dependent along temperature gradients. Results supported the
stress gradient hypothesis: As abiotic stress increased, the strength or
direction of the relationship between biotic variables and plant
abundance generally switched from negative (suggesting suppressed plant
abundance) to positive (suggesting facilitation/mutualism). For half of
the species, plant cover was the best predictor of abundance, suggesting
that the prior focus on plant‐plant interactions is well‐justified.
Explicitly incorporating the context‐dependency of biotic interactions
generated novel hypotheses about drivers of plant abundance across
abiotic gradients and may improve the accuracy of niche models.
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