Data for Context-dependent biotic interactions control plant abundance across altitudinal environmental gradients, 2014, 2016, Colorado, USA

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.