Convergence of fishers' knowledge with a species distribution model in a Peruvian shark fishery. Issue 4 (19th March 2019)

• Record Type: Journal Article
• Authors: Mason, Julia G.; Alfaro‐Shigueto, Joanna; Mangel, Jeffrey C.; Brodie, Stephanie; Bograd, Steven J.; Crowder, Larry B.; Hazen, Elliott L.
• Is Part Of: Conservation science and practice. Volume 1:Issue 4(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-03-19
• Subjects: conservation planning -- epistemological pluralism -- generalized additive model -- juvenile shark habitat -- local ecological knowledge -- small‐scale fisheries -- Sphyrna zygaena; Biodiversity conservation -- Periodicals; Biodiversity conservation; Periodicals; 333.951605
• DOI: 10.1111/csp2.13
• Languages: English
• ISSNs: 2578-4854

Abstract

Abstract : Limited data on the spatial, environmental, and human dimensions of small‐scale fisheries hinder conservation planning, so the incorporation of fishers' local ecological knowledge may be a valuable way to fill data gaps while legitimizing management decisions. In Peru, vulnerable and poorly assessed juvenile smooth hammerhead sharks ( Sphyrna zygaena ) are the most commonly caught shark species in a small‐scale drift gillnet fishery. We conducted semistructured interviews with 87 hammerhead fishers in three major Peruvian ports to elucidate the spatiotemporal niche of the hammerhead fishery and environmental drivers of juvenile hammerhead catch. We also built a biophysical model of hammerhead distribution that correlated remotely sensed environmental variables with a spatially explicit fishery observer dataset. Overall, we found a consensus between fishers' knowledge and species distribution modeling. Sea surface temperature and chlorophyll‐a emerged as important environmental drivers of juvenile hammerhead catch, with both fishers' knowledge and the biophysical model identifying similar habitat preferences (~20–23°C and log chl‐a >−1.6 mg/m 3 ). Participatory mapping of fishing grounds also corresponded to the spatiotemporal patterns of predicted hammerhead distribution. This study points to the utility of combining fishers' knowledge and biophysical modeling for spatial, temporal, and/or dynamic management of these sharks in Peru and in other data‐poor fisheries globally.