Conservation Planning - Overview
Overview
Over the past few weeks, we calculated a number of habitat patch metrics relating to patch size, shape, dispersion, connectivity, and threats. Combined, these can help in the decision on whether a given patch merits protection. It’s here in this section where we dig deeper into the process of making that decision.
We first review the concept of systematic conservation planning which strives to maximize the overall utility of landscape conservation through careful balancing of the many tradeoffs in protecting one area over another. We revisit the notion of the planning unit, the discrete area of land that is ultimately either included or excluded in an overall reserve design scenario. We examine different factors that go into selecting an effective planning unit scheme and also methods for scaling data up and down to the planning unit level. Then we tabulate additional criteria for each planning unit; specifically examine methods for computing the contingent benefit to overall biodiversity if a planning unit were included in the final reserve design. And finally, we apply MARXAN, and optimization program that goes far beyond the sorting and ranking of planning units and actually applies linear programming methods to converge on the overall most parsimonious set of planning units we’d want to protect, meaning the fewest (or least costly) planning units that achieves our overall conservation goal.
Learning Objectives
| Topic | Learning Objectives |
|---|---|
| § 5.1 Conservation Planning & Biodiversity [PPT | Recording ] |
• Outline the general steps of systematic conservation • Describe various schemes used for parsing a landscape into planning units • Upscale (or downscale) habitat patch metrics to the planning unit level • Compute species abundance, richness, and evenness for planning units • Articulate the difference of the terms mentioned in the last step • List data sources used to compute biodiversity, with their strengths & weaknesses • Create “biophysical zip codes” as a proxy for species data where data are lacking |
| § 5.2 Reserve Design & Optimization [PPT | Recording] |
• Describe landscape conservation as a “multi-attribute decision analysis” problem • Employ various methods of sorting & ranking to identify important planning units • Use weighted overlay to combine and rank multiple attributes at once • Articulate the drawbacks of the “greedy” approach of sorting and ranking • Describe the advantage of including “heuristics” in the greed approach • Explain the challenge in finding the “best” solution among multiple criteria • Explain how “simulated annealing” side-steps the above challenge • Generate the input’s required to run MARXAN from our data • Run various optimization scenarios with the MARXAN software • Map the optimized results generated from MARXAN |
| § 5.3 Monitoring & Change Detection [PPT] |
• Describe the role of remotely sensed data in monitoring landscapes • List the four types of resolution in remotely sensed data • Outline the process of discrete change detection • Outline the process of continuous change detection • Compare discrete with continuous change detection |