Attending to spatial social–ecological sensitivities to improve trade‐off analysis in natural resource management. Issue 1 (30th September 2019)

• Record Type: Journal Article
• Authors: Okamoto, Daniel K.; Poe, Melissa R.; Francis, Tessa B.; Punt, André E.; Levin, Phillip S.; Shelton, Andrew O.; Armitage, Derek R.; Cleary, Jaclyn S.; Dressell, Sherri C.; Jones, Russ; Kitka, Harvey; Lee, Lynn C.; MacCall, Alec D.; McIsaac, Jim A.; Reifenstuhl, Steve; Silver, Jennifer J.; Schmidt, Jörn O.; Thornton, Thomas F.; Voss, Rüdiger; Woodruff, John
• Is Part Of: Fish and fisheries. Volume 21:Issue 1(2020)
• Page Start: 1
• Page End: 12
• Publication Date: 2019-09-30
• Subjects: fisheries -- management strategy evaluation -- metapopulations -- social–ecological systems -- spatial planning -- trade‐offs; Fisheries -- Periodicals; Fishes -- Periodicals; 639.2
• DOI: 10.1111/faf.12409
• Languages: English
• ISSNs: 1467-2960

Abstract

Abstract: Balancing trade‐offs amongst social–ecological objectives is a central aim of natural resource management. However, objectives and resources often have spatial dimensions, which are usually ignored in trade‐off analyses. We examine how simultaneously integrating social–ecological benefits and their spatial complexities can improve trade‐off analysis. We use Pacific herring ( Clupea pallasii, Clupeidae)—an ecologically important forage fish with social, cultural and economic value to communities and commercial fisheries—as a case study. By combining spatial management strategy evaluation with social benefits analysis, we illustrate when policies aimed at aggregate stocks versus spatially segregated substocks of fish fail to balance trade‐offs amongst social–ecological objectives. Spatial measures (e.g. area‐based closures) may achieve some objectives but produce alternative trade‐offs that are sensitive to assumptions about fish population dynamics and social complexities. Our analyses identify policies that are inefficient (e.g. yielding economic costs without producing social or ecological gains), highlight management strategies that generate trade‐offs and indicate when costs are distributed unequally for different user groups. We also point to strategies with outcomes that are robust to spatial uncertainties and reveal research priorities by identifying which performance metrics exhibit sensitivity to spatial ecological assumptions. Collectively, our analyses demonstrate how incorporating social objectives and spatial dynamics into management strategy evaluation can reveal trade‐offs and the implications of management decisions.