Settlements related to the Deepwater Horizon Oil Spill (including those associated with the RESTORE Council) have brought unprecedented opportunity for conservation and restoration of Gulf of Mexico coastal ecosystems. However, a persistent challenge in any conservation endeavor is identifying optimal opportunities for land conservation. The Strategic Conservation Assessment of Gulf Coast Landscapes (SCA) project is an effort underway to integrate comprehensive, multi-state priorities and a multi-criteria decision analysis (MCDA) approach to assist Gulf stakeholders in assessing proposed areas for land conservation relative to RESTORE Council goals. We developed a suite of decision support tools that 1) coalesced land conservation priorities via an inventory of conservation plans and supplemented that information with feedback from a series of stakeholder meetings; 2) incorporated priorities into an online MCDA framework to assess relative strength of proposed projects; and 3) developed an optimized geospatial framework to aid users in identification of land conservation opportunities given varying conservation priorities. Here we specifically highlight the processes and outcomes from our work to identify shared stakeholder priorities for land conservation in the Gulf Coast region. We also describe the underlying geospatial data and MCDA analytical frameworks used in the Conservation Prioritization Tool and ultimate Strategic Conservation Assessment applications.
Results/Conclusions
Under the framework of RESTORE goals emphasizing habitat, water quality/quantity, living coastal and marine resources, coastal resilience, and Gulf economy, our team compiled an online mapping platform of >300 coastal conservation plans. We then met with 176 individuals representing 120 agencies and organizations in spring of 2018 to identify consistencies and inconsistencies among Gulf stakeholder priorities for land conservation. This combination of plan-derived and stakeholder informed feedback provided the basis for an online Conservation Prioritization Tool (CPT) in the R-Shiny platform that utilized underlying geospatial data for a suite of priority attribute measures aggregated within a 1 km2 continuous-surface hexagonal grid. Tool users input proposed project areas, and either implement a 100,000 iteration MCDA analysis to quantify rank acceptability of proposed projects, or define their own weighting scheme across RESTORE goals and associated priority attributes to compare relative strength of proposed project areas under specified goal and attribute weights. The CPT tool was tested in a series of stakeholder meetings in fall of 2018, incorporating feedback from 126 individuals representing 70 agencies and organizations. The hexagonal geospatial framework was then incorporated into an online R-Shiny mapping application that provides visual optimums for land conservation based on user-defined priorities.