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Aim: The abundance and distribution of multiple species are interconnected through various mechanisms (e.g. biotic interactions or common responses to the environment) shaping communities. Joint species distribution models (jSDM) have been introduced as a potential tool to integrate these mechanisms when modelling multiple species distributions, by inferring a residual matrix of species associations that could inform on biotic interactions. However, the direct link between these residual associations and biotic interactions has been challenged. Here, we test how the data type, resolution and sampling size affect the species associations identified by jSDMs and their benefits for predicting species given the known state of others (i.e. conditional prediction). Location: France. Taxon: Birds. Method: Utilizing standardized co‐abundances of 40 common bird species, across 7040 monitoring sites, and eight environmental variables at high resolution (200 m), we compared jSDM residual associations across data types (abundance vs. occurrence), resolution and sampling size. Additionally, we investigated correlations between residual associations and species functional similarities (eight traits). We then assessed to what extent residual associations contain valuable information for conditional predictions. Results: Our results show that species associations identified by jSDM are greatly influenced by data resolution and sampling size rather than data types (abundance vs. occurrence). We find positive correlations between species associations and functional similarity that challenges the inference of negative biotic interactions expected from niche partitioning. However, retrieving these high‐resolution residual species associations for conditional predictions enhanced predictive quality for all species (+235% on average), potentially synthesizing missing variables difficult to capture in the field. Main Conclusions: We highlight that species associations identified by jSDM using fine‐resolution co‐abundance datasets do not retrieve biotic interactions expected from niche partitioning (i.e. positive correlation with functional similarity) but probably missing environmental variables. Nonetheless, these residual associations contain valuable information to enhance predictive performance through currently underutilized conditional predictions. [ABSTRACT FROM AUTHOR]

Premise: Worldwide, ecosystems are threatened by global changes, including biological invasions. Invasive species arriving in novel environments experience new climatic conditions that can affect their successful establishment. Determining the response of functional traits and fitness components of invasive populations from contrasting environments can provide a useful framework to assess species responses to climate change and the variability of these responses among source populations. Much research on macrophytes has focused on establishment from clonal fragments; however, colonization from sexual propagules has rarely been studied. Our objective was to compare trait responses of plants generated from sexual propagules sourced from three climatic regions but grown under common environmental conditions, using L. peploides subsp. montevidensis as a model taxon. Methods: We grew seedlings to reproductive stage in experimental mesocosms under a mediterranean California (MCA) climate from seeds collected in oceanic France (OFR), mediterranean France (MFR), and MCA. Results: Seed source region was a major factor influencing differences among invasive plants recruiting from sexual propagules of L. peploides subsp. montevidensis. Trait responses of young individual recruits from MCA and OFR, sourced from geographically distant and climatically distinct source regions, were the most different. The MCA individuals accumulated more biomass, flowered earlier, and had higher leaf N concentrations than the OFR plants. Those from MFR had intermediate profiles. Conclusions: By showing that the closer a seedling is from its parental climate, the better it performs, this study provides new insights to the understanding of colonization of invasive plant species and informs its management under novel and changing environmental conditions. [ABSTRACT FROM AUTHOR]