Perturbation responses in co‐evolved model meta‐communities

Abstract

Anthropogenic impact on the natural environment is a pressing concern for the preservation of global biodiversity (Pimm & Raven, 2000), resulting in the need to understand how ecosystems will respond to the loss or invasion of species and the fragmentation or removal of habitats in order to manage sustainable land use. Given the practical and ethical obstacles to direct experimentation, predicting the impact of perturbations may be undertaken using mathematical models of community ecology (Keddy, 1992), but there remains a need for improved understanding of the mechanisms at work in such complex systems (Montoya, 2021). The use of models to inform population management is well established in fisheries, illuminating how overharvesting impacts the size structure of marine communities (Fung et al., 2013) and how species loss corresponds to the degradation of ecosystem services (Keyes et al., 2021). For terrestrial ecosystems, strategic placement of nature reserves will be essential to maximally preserve threatened species (Venter et al., 2014), with a preference for one large or many small reserves dependent on whether migration between reserve fragments is possible (Pelletier, 2000).Conservation studies may use GIS data to identify optimal wildlife corridors for mammals (Penjor et al., 2021) in forests (Yemshanov et al., 2021) and urban ecological networks (Zhao et al., 2019).To simulate habitat degradation, fragmentation, or removal it is necessary to represent spatial structure and processes within ecological models (Howell et al., 2018). Landscape ecology (Erös & Lowe, 2019) utilizes detailed and continuous models of the physical landscape. Alternatively, meta-population models divide the environment into discrete habitat units where sub-populations operate, facilitating the study of colonization-extinction dynamics.Single-species models are frequently used to study the role of dispersal rates, environmental heterogeneity (McManus et al., 2021), and trade-offs between specialist and generalist strategies (Szép et al., 2021). These techniques can further extend community