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• W4386467181 abstract "While community synchrony is a key framework for predicting ecological constancy, the interplay between community synchrony and ecological invasions remains unclear. Yet the degree of synchrony in a resident community may influence its resistance and resilience to the introduction of an invasive species. Here we used a generalizable mathematical framework, constructed with a modified Lotka-Volterra competition model, to first simulate resident communities across a range of competitive strengths and species' responses to environmental fluctuations, which yielded communities that ranged from strongly synchronous to compensatory. We then invaded these communities at different timesteps with invaders of varying demographic traits, after which we quantified the resident community's susceptibility to initial invasion attempts (resistance) and the degree to which community synchrony was altered after invasion (resiliency of synchrony). We found that synchronous communities were not only more resistant but also more resilient to invasion than compensatory communities, likely due to stronger competition between resident species and thus lower cumulative abundances in compensatory communities, providing greater opportunities for invasion. The growth rate of the invader was most influenced by the resident and invader competition coefficients and the growth rate of the invader species. Our findings support prioritizing the conservation of compensatory and weakly synchronous communities which may be at increased risk of invasion." @default.
• W4386467181 created "2023-09-07" @default.
• W4386467181 creator A5039047132 @default.
• W4386467181 creator A5062454217 @default.
• W4386467181 date "2023-10-03" @default.
• W4386467181 modified "2023-10-14" @default.
• W4386467181 title "Resistance and resilience to invasion is stronger in synchronous than compensatory communities" @default.
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• W4386467181 doi "https://doi.org/10.1002/ecy.4162" @default.
• W4386467181 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37672010" @default.
• W4386467181 hasPublicationYear "2023" @default.
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