Assessing the effects of institutional and spatial arrangements in analytical and computational models of conservation

This work is an assemblage of three applied projects that address the institutional and spatial constraints to managing threatened and endangered (T & E) terrestrial species. The first project looks at the role of the Endangered Species Act (ESA) in protecting wildlife and whether banning non–conservation activities on multi-use federal lands is socially optimal. A bioeconomic model is used to identify scenarios where ESA–imposed regulations emerge as optimal strategies and to facilitate discussion on feasible long–term strategies in light of the ongoing public land–use debate. Results suggest that banning harmful activities is a preferred strategy when valued species are in decline or exposed to poor habitat quality. However such a strategy cannot be sustained in perpetuity, a switch to land–use practices characteristic of habitat conservation plans is recommended. The spatial portion of this study is motivated by the need for a more systematic quantification and assessment of landscape structure ahead of species reintroduction; this portion is further broken up into two parts. The first explores how connectivity between habitat patches promotes coexistence among multiple interacting species. An agent–based model of a two–patch metapopulation is developed with local predator–prey dynamics and density–dependent dispersal. The simulation experiment suggests that connectivity levels at both extremes, representing very little risk and high risk of species mortality, do not augment the likelihood of coexistence while intermediate levels do. Furthermore, the probability of coexistence increases and spans a wide range of connectivity levels when individual dispersal is less probabilistic and more dependent on population feedback. Second, a novel approach to quantifying network structure is developed using the statistical method of moments. This measurement framework is then used to index habitat networks and assess their capacity to drive three main ecological processes: dispersal, survival, and coexistence. Results indicate that the moments approach outperforms single summary metrics and accounts for a majority of the variation in process outcomes. The hierarchical measurement scheme is helpful for indicating when additional structural information is needed to determine ecological function. However, the qualitative trend between network indicator and function is, at times, unintuitive and unstable in certain areas of the metric space.