Determinism and stochasticity in the spatial-temporal continuum of ecological communities: the case of tropical mountains

Ecological communities are assembled in a spatial-temporal continuum.
However, we still have a poor understanding of the relative importance of
different mechanisms structuring community composition (i.e.,
beta-diversity) in space and time. In this study, we start by introducing
a conceptual model that capitalizes upon the core-occasional species
concept to predict that the assembly process in tropical mountains is
driven by the deterministic turnover of core species in space via habitat
sorting, but the turnover of occasional species through time via
stochastic events of colonization and local extinctions. We then propose a
general analytical framework that allows assessing these predictions by
partitioning the total variance of a species-by-site-by-time matrix (i.e.,
total beta-diversity) among its purely spatial (variation in space
independent of time), purely temporal (variation in time independent of
space), and spatiotemporal (i.e., variation across different sites across
different moments in time) components. Through simulation models, we
provided theoretical support that the proposed analytical framework is
suitable to test the predictions derived from our conceptual model. We
then used this framework to identify general patterns and quantify the
relative importance of processes underlying the spatial and temporal
organization of ten distinct insect metacommunities along a tropical
elevational gradient. As predicted, we found that, across taxa, spatial
beta-diversity was mainly explained by environmental variation alone: a
pattern that indicates the spatial turnover of core species. In contrast,
temporal beta-diversity could not be distinguished from the expectation of
null models where communities are simply represented by random draws from
species pools: a pattern that indicates a temporal turnover of occasional
species within communities. Taken together, our findings illustrate how
our conceptual model and quantitative framework can articulate a better
understanding of community assembly in space and time.