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.

The spread of invasive species may be greatly affected by human responses to prior species spread, but models and estimation methods seldom explicitly consider human responses. I investigate the effects of management responses on estimates of invasive species spread rates. To do this, I create an agent-based simulation model of an insect invasion across a county-level citrus landscape. My model provides an approximation of a complex spatial environment while allowing the "truth" to be known. The modeled environment consists of citrus orchards with insect pests dispersing among them. Insects move across the simulation environment infesting orchards, while orchard managers respond by administering insecticide according to analyst-selected behavior profiles and management responses may depend on prior invasion states. Dispersal data is generated in each simulation and used to calculate spread rate via a set of estimators selected for their predominance in the empirical literature. Spread rate is a mechanistic, emergent phenomenon measured at the population level caused by a suite of latent biological, environmental, and anthropogenic. I test the effectiveness of orchard behavior profiles on invasion suppression and evaluate the robustness of the estimators given orchard responses. I find that allowing growers to use future expectations of spread in management decisions leads to reduced spread rates. Acting in a preventative manner by applying insecticide before insects are actually present, orchards are able to lower spread rates more than by reactive behavior alone. Spread rates are highly sensitive to spatial configuration. Spatial configuration is hardly a random process, consisting of many latent factors often not accounted for in spread rate estimation. Not considering these factors may lead to an omitted variables bias and skew estimation results. The ability of spread rate estimators to predict future spread varies considerably between estimators, and with spatial configuration, invader biological parameters, and orchard behavior profile. The model suggests that understanding the latent factors inherent to dispersal is important for selecting phenomenological models of spread and interpreting estimation results. This indicates a need for caution when evaluating spread. Although standard practice, current empirical estimators may both over- and underestimate spread rate in the simulation.

Climate and land use change are projected to threaten biodiversity over the coming century. However, the combined effects of these threats on biodiversity and the capacity of current conservation networks to protect species' habitat are not well understood. The goals of this study were to evaluate the effect of climate change and urban development on vegetation distribution in a Mediterranean-type ecosystem; to identify the primary source of uncertainty in suitable habitat predictions; and to evaluate how well conservation areas protect future habitat in the Southwest ecoregion of the California Floristic Province. I used a consensus-based modeling approach combining three different species distribution models to predict current and future suitable habitat for 19 plant species representing different plant functional types (PFT) defined by fire-response (obligate seeders, resprouting shrubs), and life forms (herbs, subshurbs). I also examined the response of species grouped by range sizes (large, small). I used two climate models, two emission scenarios, two thresholds, and high-resolution (90m resolution) environmental data to create a range of potential scenarios. I evaluated the effectiveness of an existing conservation network to protect suitable habitat for rare species in light of climate and land use change. The results indicate that the area of suitable habitat for each species varied depending on the climate model, emission scenario, and threshold combination. The suitable habitat for up to four species could disappear from the ecoregion, while suitable habitat for up to 15 other species could decrease under climate change conditions. The centroid of the species' suitable environmental conditions could shift up to 440 km. Large net gains in suitable habitat were predicted for a few species. The suitable habitat area for herbs has a small response to climate change, while obligate seeders could be the most affected PFT. The results indicate that the other two PFTs gain a considerable amount of suitable habitat area. Several rare species could lose suitable habitat area inside designated conservation areas while gaining suitable habitat area outside. Climate change is predicted to be more important than urban development as a driver of habitat loss for vegetation in this region in the coming century. These results indicate that regional analyses of this type are useful and necessary to understand the dynamics of drivers of change at the regional scale and to inform decision making at this scale.