A JSDM with zero-inflation to increase the ecological relevance of analyses of species distribution data.

This study introduces a novel Joint Species Distribution Model (JSDM) called ZIPLN-network that directly models count data while accounting for the ubiquitous zero-inflation in species occurrence datasets. By addressing this long-standing challenge, the ZIPLN-network approach extracts more of the ecological signal, providing deeper insights into the mechanisms structuring species distributions across landscapes. The researchers demonstrate the utility of this method using data from tropical freshwater fish communities, showcasing its ability to generate testable hypotheses and enhance our understanding of the complex interactions within ecological communities. This innovative modeling technique represents a significant advancement in the field, paving the way for more ecologically relevant analyses and improved predictions of community responses to environmental changes.