Reserve design to optimize functional connectivity and animal density

Abstract

Ecological distance‐based spatial capture–recapture models (SCR) are a promising approach for simultaneously estimating animal density and connectivity, both of which affect spatial population processes and ultimately species persistence. We explored how SCR models can be integrated into reserve‐design frameworks that explicitly acknowledge both the spatial distribution of individuals and their space use resulting from landscape structure. We formulated the design of wildlife reserves as a budget‐constrained optimization problem and conducted a simulation to explore 3 different SCR‐informed optimization objectives that prioritized different conservation goals by maximizing the number of protected individuals, reserve connectivity, and density‐weighted connectivity. We also studied the effect on our 3 objectives of enforcing that the space‐use requirements of individuals be met by the reserve for individuals to be considered conserved (referred to as home‐range constraints). Maximizing local population density resulted in fragmented reserves that would likely not aid long‐term population persistence, and maximizing the connectivity objective yielded reserves that protected the fewest individuals. However, maximizing density‐weighted connectivity or preemptively imposing home‐range constraints on reserve design yielded reserves of largely spatially compact sets of parcels covering high‐density areas in the landscape with high functional connectivity between them. Our results quantify the extent to which reserve design is constrained by individual home‐range requirements and highlight that accounting for individual space use in the objective and constraints can help in the design of reserves that balance abundance and connectivity in a biologically relevant manner.

Amount and spatial distribution of habitats influence occupancy and dispersal of frogs at multiple scales in agricultural landscape

“…Our recommendations would guarantee 50% of pond occupancy probability by providing both local requirements and dispersal habitats for both species and possibly for other frogs with similar requirements. Such goals agree with the current understanding that the design of protected areas should balance local requirements to increase population density and connectivity that favours population persistence (Gupta et al 2019).…”

The value of considering demographic contributions to connectivity: a review

“…Such uncertainty and debate is fueled, in part, by a diversity of ecological sub‐disciplines and conservation applications that draw upon the concept and seek to quantify connectivity through a continually increasing array of models and metrics (Kindlmann and Burel 2008, Rayfield et al 2011, Fletcher et al 2016). Population dynamics (Clinchy et al 2002), disease networks (Margosian et al 2009), forestry planning (Banks et al 2005), wildlife management (Horváth et al 2019), conservation reserve design (Blowes and Connolly 2012, Gupta et al 2019), spatial conservation planning (Daigle et al 2020), invasive species mitigation (Drake et al 2017a), landscape genetics (Marrotte et al 2017) and more, all invoke the concept of connectivity, but often in different contexts and spatiotemporal scales. While we acknowledge that such context‐dependency makes it unrealistic to find a single connectivity metric that would satisfy all applications, idiosyncratic uses of connectivity have proliferated into a loosely related set of tools.…”

A review of spatial capture–recapture: Ecological insights, limitations, and prospects

“…Resource limitation may constrain the possibility of collaboration and exchange of skills required to analyze such data within an SCR framework. However, many species of conservation concern occur in developing regions (Jantz et al, 2015) and have been recently the focus of SCR studies to, for example, derive density estimates for conservation assessment (e.g., Gupta et al, 2019). Carnivores are the most targeted taxonomic groups in SCR studies (Figure 2) and the most studied species are charismatic species of conservation or management interest.…”