This dissertation aims to investigate how science can effectively inform management and policy decisions, leading to positive conservation outcomes for vulnerable wildlife communities. Successful conservation requires the incorporation of ecological uncertainty and socio-ecological complexity into the decision-making process. To navigate the uncertainty and complexity pertinent to landscape conservation, I demonstrate a multi-scaled approach to quantify, monitor, and manage amphibians in a case study of a regional network of national parks. In Chapter 1, I quantify biodiversity across multiple spatial scales by fitting a multi-region community occupancy model to regional amphibian monitoring data to elucidate the drivers and threats(s) to biodiversity and the relevant scale(s) to target management. In Chapter 2, I explore the efficacy of different monitoring programs and identify strategies to monitor biodiversity across multiple spatial scales to minimize uncertainty in system dynamics. In Chapter 3, I predict the impacts of, and then spatially prioritize, management to increase biodiversity across multiple spatial scales by incorporating governance complexity in the decision-making process. In Chapter 4, I synthesize findings from previously published studies to determine the extent, and conditions under which, decision support frameworks can lead to positive conservation outcomes. The chapters of this dissertation provide critical guidance on how to scale up conservation science to match the scope and scale of the ecological systems and governance structures it is meant to inform. The application of this knowledge can help conservation scientists, managers, and policy makers address the complex and multi-scaled biodiversity crisis.
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