Drivers of metacommunity dynamics in river-floodplain fish: A path modeling approach

Metacommunity theory offers a compelling framework for understanding the processes that govern biodiversity patterns across space and time. Yet, a persistent challenge remains: integrating the wide array of ecological drivers into a unified model using observational data from complex, dynamic ecosystems. In this study, we present a novel, process-explicit path modeling approach that bridges recent theoretical advances in metacommunity ecology with empirical data. Focusing on fish communities in the floodplains of the Danube River, we leverage environmental DNA (eDNA) metabarcoding to characterize community composition across a spatiotemporal network of sites. We partition beta diversity into its species replacement and richness difference components and apply structural equation modeling to evaluate the relative influence of multiple ecological drivers—including spatial and temporal dispersal, demographic stochasticity, abiotic filtering, and interspecific interactions. Our results reveal that river-floodplain fish metacommunities are shaped by a complex web of interacting processes. Notably, we find that species replacement is primarily driven by spatial distance and environmental filtering, while richness differences are more influenced by biotic interactions and community size. Lateral hydrological connectivity emerged as a pivotal landscape feature, governing beta diversity both directly and indirectly through its modulation of local environmental conditions. This connectivity acted as a structural conduit, mediating dispersal, environmental heterogeneity, and biotic interactions. By disentangling the contributions of multiple processes, our model underscores the dominant role of spatial structuring and abiotic filtering over temporal dynamics and biotic interactions in shaping metacommunity assembly. The model also demonstrates improved explanatory power and stronger model fit, outperforming previous studies. These findings underscore the need for integrative frameworks that consider the simultaneous influence of multiple ecological processes, particularly in highly dynamic systems like river-floodplains. Our conceptual and modeling approach advances metacommunity theory by offering a robust, data-driven means to assess complex assembly mechanisms and by emphasizing the critical role of connectivity and habitat complementarity in sustaining biodiversity within dynamic landscapes.