Abstract
Abstract Conflicts of interest between resource extraction and conservation are widespread, and negotiating such conflicts, or trade‐offs, is a key issue for ecosystem managers. One such trade‐off is resource competition between fisheries and marine top predators. Managing this trade‐off has so far been difficult due to a lack of knowledge regarding the amount and distribution of prey required by top predators. Here, we develop a framework that can be used to address this gap: a bio‐energetic model linking top predator breeding biology and foraging ecology with forage fish ecology and fisheries management. We apply the framework to a Baltic Sea colony of common guillemots Uria aalge and razorbills Alca torda, two seabird species sensitive to local prey depletion, and show that densities of forage fish (sprat Sprattus sprattus and herring Clupea harengus) corresponding to the current fisheries management target BMSY are sufficient for successful breeding. A previously proposed fisheries management target for conserving seabirds, 1/3 of historical maximum prey biomass (B1/3), was also sufficient. However, the results highlight the importance of maintaining sufficient prey densities in the vicinity of the colony, suggesting that fine‐scale spatial fisheries management is necessary to maintain high seabird breeding success. Despite foraging on the same prey, razorbills could breed successfully at lower prey densities than guillemots but needed higher densities for self‐maintenance, emphasizing the importance of considering species‐specific traits when determining sustainable forage fish densities for top predators. Synthesis and applications. Our bio‐energetic modelling framework provides spatially explicit top predator conservation targets that can be readily integrated with current fisheries management. The framework can be combined with existing management approaches such as dynamic ocean management, marine spatial planning and management strategy evaluation to inform ecosystem‐based management of marine resources.
Highlights
Conflicts between biodiversity conservation and human utilization of natural resources are widespread, with examples ranging from forestry and agriculture to fisheries (Cury et al, 2011; Henle et al, 2008; Hobday et al, 2015; Niemelä et al, 2005)
We apply the framework to a Baltic Sea colony of common guillemots Uria aalge and razorbills Alca torda, two seabird species sensitive to local prey depletion, and show that densities of forage fish corresponding to the current fisheries management target Fish biomass corresponding to Maximum Sustainable Yield (BMSY) are sufficient for successful breeding
We investigated the following three questions: (a) What is the minimum density of prey fish required for successful breeding in the two seabird species and how does this depend on their population size? (b) How do species-specific traits, in particular diving and flying capabilities, influence this density? (c) Are current fisheries management targets sufficient for maintaining favourable conservation status of the two species?
Summary
Conflicts between biodiversity conservation and human utilization of natural resources are widespread, with examples ranging from forestry and agriculture to fisheries (Cury et al, 2011; Henle et al, 2008; Hobday et al, 2015; Niemelä et al, 2005). Despite the well-known fact that forage fish fisheries can affect reproduction and survival of marine top predators (Bertrand et al, 2012; Cook et al, 2014), management measures to protect their prey are relatively rare (but see for example North Sea: Frederiksen et al, 2008; Namibia: Ludynia et al, 2012; South Africa: Sherley et al, 2015) It is unknown whether targets commonly used to ensure sustainable exploitation of fish stocks, that is, maintaining biomasses (B) corresponding to Maximum Sustainable Yield (MSY) or a precautionary approach (PA; Jennings et al, 2001; List of Abbreviations), are compatible with top predator conservation (Cury et al, 2011). The study provides a general framework for how bio-energetic modelling can be combined with commonly available data to design fishery management measures that maintain sufficient prey resources for top predators, contributing to the development of an ecosystem-based approach to fishery management
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