Combining observational and experimental data to estimate environmental and species drivers of fungal metacommunity dynamics

Abstract

Understanding the distribution and dynamics of species is central to ecology and important for managing biodiversity. The distributions of species in metacommunities are determined by many factors, including environmental conditions and interactions between species. Yet, it is difficult to quantify the effect of species interactions on metacommunity dynamics from observational data. We present an approach to estimate the importance of species interactions that combines data from two observational presence–absence inventories (providing colonization–extinction data) with data from species interaction experiments (providing informative prior distributions in the Bayesian framework). We further illustrate the approach on wood-decay fungi that interact within a downed log through competition for resources and space, and facilitate the succession of other species by decomposing the wood. Specifically, we estimated the relative importance of species interactions by examining how the presence of a species influenced the colonization and extinction probability of other species. Temporal data on fruit body occurrence of 12 species inventoried twice were jointly analyzed with experimental data from two laboratory experiments that aimed to estimate competitive interactions. Both environmental variables and species interactions affected colonization and extinction dynamics. Late-successional fungi had more colonization interactions with predecessor species than early-successional species. We identified several species interactions, and the presence of certain species changed the probability that later-successional species colonized by −81% to 512%. The presence of certain species increased the probability that other species went extinct from a log by 14%–61%. Including the informative priors from experimental data added two colonization interactions and one extinction interaction for which the observational field data was inconclusive. However, most species had no detectable interactions, either because they did not interact or because of low species occupancy, meaning data limitation. We show how temporal presence-absence data can be combined with experimental data to identify which species influence the colonization-extinction dynamics of others. Accounting for species interactions in metacommunity models, in addition to environmental drivers, is important because interactions can have cascading effects on other species.