200 likes | 337 Views
Stakeholders, Algorithms, and Marine Protected Area Design in California. Carissa Klein, University of Queensland c.klein@uq.edu.au Charles Steinback, Ecotrust charles@ecotrust.org. Marine Life Protection Act Initiative. Working Groups Blue Ribbon Task Force Stakeholder Group
E N D
Stakeholders, Algorithms, and Marine Protected Area Design in California Carissa Klein, University of Queensland c.klein@uq.edu.au Charles Steinback, Ecotrust charles@ecotrust.org
Marine Life Protection Act Initiative Working Groups • Blue Ribbon Task Force • Stakeholder Group • Science Advisory Team Pigeon Point Study Area Point Conception
MLPA Goals & Objectives Biodiversity Conservation • Habitats across depth zones • Areas of high species diversity • Populations of special status Socioeconomic Viability • Minimize negative socioeconomic impacts
Laura Francis Example Conservation Features Rocky reefs Kelp beds Estuaries Canyons Sandy bottom Surfgrass beds Sea otter habitat Mammal rookeries Bathymetric complexity Pinnacles Bird colonies Areas of high fish diversity Total = 47
Consumptive Socioeconomic Data • Recreational Fishing Effort Trips per planning unit • Commercial Fishing Effort Relative importance to fishermen
Expert Approach • Interest groups (fishing, conservation, etc.) developed proposals • Provided with biophysical data • Not provided with all fishing data • Proposals were evaluated by Scientific Advisory Team (biodiversity representation and impact to fisheries) • Using scientific feedback, stakeholders revised proposals
Four Proposals 1 2 3 4
Software Approach: MARXAN • 2.5 km2 planning units • Calculated how much of each feature was in each planning unit • Targeted same amount of each feature as stakeholder proposals • Minimize impact (“cost”) to 19 fisheries • Used BLM that gave solutions comparable in size to stakeholder proposals Monterey Morro Bay
Cost per Planning Unit • Relative impact reservation of a planning unit has on fishing effort • Equal weight to individual fisheries within commercial and recreational sector • Equal weight to sectors , , ,
Individual Summed Solutions = + 100 Solutions
Cost vs. MARXAN Output Monterey Monterey Cost: Area & Fishing Effort
Priority Areas Included? • Proposal 1 – 96.7% • Proposal 2 – 70.8% • Proposal 3 – 76.9% • Proposal 4 – 87.7%
Caveats • Marxan solutions assume exclusion of all fishing • Assumes that effort is not redistributed after conservation • Data quality and scale
Conclusions Fishermen designed the most cost-effective solutions • Local/Expert knowledge • Data availability may lead to more efficient proposals Marxan solutions were more efficient than stakeholder proposals Marxan solutions do not reveal sensitive socioeconomic information Good tool to support, NOT replace, stakeholder driven process Photo: Gretchen Hoffman
Acknowledgements Bruce Kendall, Satie Airamé, Astrid Scholz, Lindsay Kircher, Allison Chan, Amanda Cundiff, Nadia Gardner, Yvana Hrovat, Will McClintock, Fishermen, Fisherwomen, MLPA staff Photo: Gretchen Hoffman