A framework for species conservation by managed relocation: quantifying risks, uncertainties, and alternatives

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If environmental changes such as habitat loss, or changes in temperature and precipitation threaten a species' ability to thrive in a given geographic area, conservation biologists might promote their survival by moving individuals of that species to more appropriate environments. However, this approach, called managed relocation, entails a number of risks, such as moving organisms at the wrong time or to the wrong location or introducing species that may become problematic in their new environments. This project will examine the risks and benefits of moving species to more appropriate locations as opposed to simply protecting their current habitats. A key part of this project will be to explore how the uncertainty of available environmental information might influence the decision making process used by wildlife managers. The outcomes from this study will benefit society by informing conservation planning decisions across a variety of plant and animal species and will advance science education by combining basic research with its direct application. The goal of this project is to quantify how the potential benefits and risks of managed relocation strategies compare to protection and restoration programs under different sources of uncertainty and decision-making processes. A suite of dynamical modeling frameworks will be employed to model managed relocation, which is defined as the purposeful movement of both species (assisted migration) and genotypes (assisted gene flow) beyond their historical range, with the intention of supporting population persistence under different models of changing environmental conditions. Competitive metacommunity models will model assisted migration accounting for the risk of accidentally introducing invasive species that negatively impact recipient communities, and coupled genetic-demographic models will examine the risk of loss of local adaptation and metapopulation-level genetic diversity. All models will quantify how risks and benefits depend on the demographic and environmental indicators used, with associated uncertainty, to decide when, where, and how many individuals to relocate. In turn, this study will also address how local-scale rescue and global-scale homogenization trade-off in determining the effects of connectivity on diversity. Finally, this project will advance the understanding of how conservation associated decision-making should be approached given ongoing global change and different levels of uncertainty.