Habitat degradation and climate change are generally considered the greatest threats to biodiversity globally. Together, these processes pose an urgent challenge to conservation science, requiring ever increasing efficiency in ecologically-based decision making, to slow down, and hopefully eventually reverse, the ongoing global loss of biodiversity. In responding to this challenge, I am proposing a project in which the over-arching goal is to provide improved conservation-oriented analytical methods and tools to underpin knowledge-based land-use planning and associated political decision making. The proposed work builds on a broad established history of research in the field of spatial ecology and conservation prioritization.Specific components of the proposal include: (i) developing the general conceptual, ecological, methodological and statistical basis of environmental and conservation resource allocation: (ii) combining species and community-level prioritization approaches for data-poor areas of the world; (iii) developing methods for alleviating the negative ecological consequences of climate change, based on connectivity both in geographic and environmental space; (iv) developing an uncertainty-analytic method for the planning of habitat restoration and calculation of compensation ratios for habitat that will be impacted due to economic activity, (v) developing methods for allocating alternative conservation actions (protection, maintenance, restoration) in combination with habitat-specific loss rates in spatial conservation prioritization, and (vi) implementing the proposed methods as publicly available, efficient and well-documented software packages. Particular emphasis will be placed on solving the algorithmic challenges involved in analyzing the large data sets that are becoming increasingly available as the distributions of environmental conditions and biodiversity features are derived from large-scale high-resolution remote-sensing data.