Raw sequencing data for assembly processes inferred from eDNA surveys of a pond metacommunity are consistent with known species ecologies

Technological advances are enabling ecologists to conduct large-scale and
structured community surveys. However, it is unclear how best to extract
information from these novel community data. We metabarcoded 48 vertebrate
species from their eDNA in 320 ponds across England and applied the
'internal structure' approach, which uses joint species
distribution models (JSDMs) to explain compositions as the result of four
metacommunity processes: environmental filtering, dispersal, species
interactions and stochasticity. We confirm that environmental filtering
plays an important role in community assembly, and find that species'
estimated environmental preferences are consistent with known ecologies.
We also detect negative biotic covariances between fish and amphibians
after controlling for divergent environmental preferences, consistent with
predator-prey interactions (likely mediated by predator avoidance
behaviour), and we detect high spatial autocorrelation for the palmate
newt, consistent with its hypothesised relict distribution. Promisingly,
ecologically and spatially distinctive sites are better explained by their
environmental covariates and geographic locations, respectively, revealing
sites where environmental filtering and dispersal limitation act more
strongly. These results are consistent with the recent proposal that
applying JSDMs to species distribution patterns can help reveal the
relative importance of environmental filtering, dispersal limitation and
biotic interaction processes for individual sites and species. Our results
also highlight the value of the modern interpretation of metacommunity
ecology, which embraces the fact that assembly processes differ among
species and sites. We discuss how novel community data allow for several
study design improvements that will strengthen the inference of
metacommunity assembly processes from observational data.