Advances in Decision Support Platforms for Prioritizing Investments in Forest and Rangeland Restoration, Risk Reduction and Biodiversity Conservation

The growing interest in spatial prioritization models and their deployment to support forest restoration and conservation efforts is substantiated by the emergence of many new landscape planning platforms. In this paper we review selected landscape planning and prioritization platforms and their application in diverse ecosystems and operational environments. We define platforms as integrated solutions that leverage one or more technology building blocks including big data, spatial optimization algorithms, geospatial technology, and cloud computing. We pay particular attention to contrasting platforms developed to prioritize active forest management as part of restoration and risk reduction efforts on western US landscapes, versus other systems that were developed to identify efficient conservation reserve designs to protect biodiversity and carbon in temperate and tropical ecosystems. The models examined represent an array of planning systems with a common thread in all the platforms of the use of spatial optimization to find efficient solutions in terms of minimizing the cost per unit of progress towards stated targets. Divergence in platform designs, data usage, scale, resolution, and intended users was expected given the diversity of spatial planning problems for which they were developed. Highlighting the design differences among these platforms provided insights on the contribution of specific features to their functionality. One major finding was that the spatial planning problem and its formulation diverge significantly between widely used “top-down” conservation platforms and “bottom-up” tools in current use to optimize investments in active forest management as part of wildfire risk reduction and restoration programs. We conclude that the uptake of these newer platforms and underlying science by public and private entities is not keeping pace with technology, and thus the bottleneck in application and realizing potential benefits rests with institutional capacity to absorb and implement new technologies rather than the design, development, and deployment of them.