Landscape-scale social and ecological outcomes of dynamic angler and fish behaviours: processes, data, and patterns

Abstract

The first relatively complete landscape-scale social–ecological system (SES) model of a recreational fishery was developed and ground-truthed with independent angling effort data. Based on the British Columbia multistock recreational fishery for rainbow trout (Oncorynchus mykiss), the model includes hundreds of individual lake fisheries, hundreds of thousands of anglers, originating from tens of communities, connected by complex road and trail networks, all distributed over a landscape of approximately half a million square kilometres. The approach is unique in that it incorporates realistic and empirically derived behavioural interactions within and among the three key components of the SES: angler communities, fish populations, and management policies. Current management policies were characterized and alternate policies assessed by simulation. We examined spatial patterns in ecological and social properties of the SES and used simulations to investigate the impacts of alternate management policies on these patterns. Simulation outcomes strongly depended on the spatial redistribution of anglers across the landscape, existing road networks, heterogeneity in angler behaviours, and the spatial pattern of fish population productivity.

Social–ecological feedbacks drive spatial exploitation in a northern freshwater fishery: A halo of depletion

“…≥1,000 potential anglers in Figure ) could be managed with reduced fishing seasons, stringent length‐limits or effort control compared to populations outside the halo. Such approaches may better balance stakeholder needs with conservation goals for ecosystem‐based management (Carruthers et al, ; Matsumura et al, ).…”

“…Fishers of that landscape, in our case anglers, can vary in preferences and skill that may change with trip contexts (Dabrowska, Hunt, & Haider, ; Hunt, Camp, van Poorten, & Arlinghaus, ). Because anglers directly impact fish populations through catch and harvest (Lewin, Arlinghaus, & Mehner, ), their aggregate choices feedback through the system to structure macroscale outcomes and fishery resilience (Carruthers et al, ; Kaemingk, Chizinski, Hurley, & Pope, ; Matsumura, Beardmore, Haider, Dieckmann, & Arlinghaus, ). These behavioural feedbacks structure entire landscapes by prompting density‐dependent responses (e.g.…”

“…Understanding behavioural feedbacks between fish and anglers can help to predict effort dynamics and advise spatial management (Camp, Ahrens, Crandall, & Lorenzen, ; Carruthers et al, ; Matsumura et al, ). These feedbacks are influenced by angler preferences that depend on biotic and abiotic characteristics and trip contexts (Beardmore, Haider, Hunt, & Arlinghaus, ; Chizinski, Martin, Shizuka, & Pope, ; Hunt, ; Hunt et al, ).…”

Governing the recreational dimension of global fisheries

“…Anglers can sort in space and seek those opportunities best matching their preferences (20), promoting a self-regulating system. Although some agencies have implicitly used this lakescape/seascape approach (23), this is seldom the explicit policy. The potential for a stabilizing portfolio effect of a diversified management scheme is, however, substantial.…”

The future of recreational fisheries: Advances in science, monitoring, management, and practice

“…Therefore, legal restrictions are placed on fishing effort (both harvest and C&R activity) in the majority of current RF including limitations on the number and size of fish harvested, seasonal and spatial closures, and allowable gear types (Cox et al, 2002;Johnson and Martinez, 1995;Wilde et al, 2003). Yet, because fisheries are often managed at regional scales, effort is rarely regulated at the individual fishery level (Carruthers et al, 2018;Lester et al, 2003;Mee et al, 2016;Post, 2013;Post et al, 2003). Further, recreational anglers often maintain high levels of fishing effort when fish abundance and fishing quality decline (Johnston et al, 2010;Post, 2013).…”