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  1. Abstract

    Ecologists have put forward many explanations for coexistence, but these are onlypartial explanations; nature is complex, so it is reasonable to assume that in any given ecological community, multiple mechanisms of coexistence are operating at the same time. Here, we present a methodology for quantifying the relative importance of different explanations for coexistence, based on an extension of theModern Coexistence Theory. Current versions of Modern Coexistence Theory only allow for the analysis of communities that are affected by spatialortemporal environmental variation, but not both. We show how to analyze communities with spatiotemporal fluctuations, how to parse the importance of spatial variation and temporal variation, and how to measure everything with either mathematical expressions or simulation experiments. Our extension of Modern Coexistence Theory shows that many more species can coexist than originally thought. More importantly, it allows empiricists to use realistic models and more data to better infer the mechanisms of coexistence in real communities.

     
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  2. Abstract

    Unexpected population crashes are an important feature of natural systems, yet many observed crashes have not been explained. Two difficulties in explaining population crashes are their relative rarity and the multi‐causal nature of ecological systems. We approach this issue with experimental microcosms, with large numbers of replicates of red flour beetle populations (Tribolium castaneum). We determined that population crashes are caused by an interaction between stochasticity and successive episodes of density dependence: demographic stochasticity in oviposition rates occasionally produces a high density of eggs; so high that there are insufficient flour resources for subsequent larvae. This mechanism can explain unexpected population crashes in more general settings: stochasticity ‘pushes’ population into a regime where density dependence is severely overcompensatory. The interaction between nonlinearity and stochasticity also produces chaotic population dynamics and a double‐humped one‐generation population map, suggesting further possibilities for unexpected behaviour in a range of systems. We discuss the generality of our proposed mechanism, which could potentially account for previously inexplicable population crashes.

     
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