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The relative arrival time of species can affect their interactions and thus determine which species persist in a community. Although this phenomenon, called priority effect, is widespread in natural communities, it is unclear how it depends on the length of growing season. Using a seasonal stage-structured model, we show that differences in stages of interacting species could generate priority effects by altering the strength of stabilizing and equalizing coexistence mechanisms, changing outcomes between exclusion, coexistence and positive frequency dependence. However, these priority effects are strongest in systems with just one or a few generations per season and diminish in systems where many overlapping generations per season dilute the importance of stage-specific interactions. Our model reveals a novel link between the number of generations in a season and the consequences of priority effects, suggesting that consequences of phenological shifts driven by climate change should depend on specific life histories of organisms. 

Climate change is shifting the phenological timing, duration, and temporal overlap of interacting species in natural communities, reshaping temporal interaction networks worldwide. Despite much recent progress in documenting these phenological shifts, little is known about how the phenologies of species interactions are tracked across different life history stages. Here we analyze four key phenological traits and the pairwise interaction potential of nine amphibian species for the adult (calling/breeding) and subsequent larval (tadpole) stage at eight different sites over six years. We found few strong correlations among phenological traits within species, but the strength of these correlations varied across species. As a consequence, phenological trait combinations of both stages varied substantially across species without clear signs of multidimensional clustering, indicating a distinct and diverse range of species‐specific phenological strategies. Despite this considerable variation in the phenologies across species, the temporal overlap between species was largely preserved through the two life history stages. Further, we also detected significant correlations among the duration and temporal overlap of interactions with other species across stages in five species, demonstrating that temporal patterns of species interactions are mirrored across life history stages. For these species, these results indicate a strong tracking of phenologies and species interactions across life history stages even in species with complex life cycles where stages occupy completely different environments. This suggests that phenological shifts in one stage can impact the temporal dynamics and structure of interaction networks across developmental stages. 

Co-infections of hosts by multiple pathogen species are ubiquitous, but predicting their impact on disease remains challenging. Interactions between co-infecting pathogens within hosts can alter pathogen transmission, with the impact on transmission typically dependent on the relative arrival order of pathogens within hosts (within-host priority effects). However, it is unclear how these within-host priority effects influence multi-pathogen epidemics, particularly when the arrival order of pathogens at the host-population scale varies. Here, we combined models and experiments with zooplankton and their naturally co-occurring fungal and bacterial pathogens to examine how within-host priority effects influence multi-pathogen epidemics. Epidemiological models parametrized with within-host priority effects measured at the single-host scale predicted that advancing the start date of bacterial epidemics relative to fungal epidemics would decrease the mean bacterial prevalence in a multi-pathogen setting, while models without within-host priority effects predicted the opposite effect. We tested these predictions with experimental multi-pathogen epidemics. Empirical dynamics matched predictions from the model including within-host priority effects, providing evidence that within-host priority effects influenced epidemic dynamics. Overall, within-host priority effects may be a key element of predicting multi-pathogen epidemic dynamics in the future, particularly as shifting disease phenology alters the order of infection within hosts.