Alongshore advection and marine reserves: consequences for modeling and management

Kaplan, David M.

doi:10.3354/meps309011

Cited by 41 publications

(54 citation statements)

References 30 publications

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“…The symmetry of the optimal configurations, due to the simplified characterization of the coast and symmetrical dispersal kernel, should not be interpreted as literal guidance for fisheries management. In practice, evenness in reserve spacing is likely not optimal in a spatially heterogeneous system (Sanchirico 2004;Kaplan 2006).…”

Section: Discussionmentioning

confidence: 99%

Density dependence and the economic efficacy of marine reserves

White

2009

Theor Ecol

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Predictions on the efficacy of marine reserves for benefiting fisheries differ in large part due to considerations of models of either intra-or inter-cohort population density regulating fish recruitment. Here, I consider both processes acting on recruitment and show using a bioeconomic model how for many fisheries density dependent recruitment dynamics interact with harvest costs to influence fishery profit with reserves. Reserves consolidate fishing effort, favoring fisheries that can profitably harvest low-density stocks of species where adult density mediates recruitment. Conversely, proportion coastline in reserves that maximizes profit, and relative improvement in profit from reserves over conventional management, decline with increasing harvest costs and the relative importance of intra-cohort density dependence. Reserves never increase profit when harvest cost is high, regardless of density dependent recruitment dynamics. I quantitatively synthesize diverse results in the literature, show disproportionate effects on the economic performance of reserves from considering only inter-or intra-cohort density dependence, and highlight fish population and fishery dynamics predicted to be complementary to reserve management.

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Section: Discussionmentioning

confidence: 99%

Density dependence and the economic efficacy of marine reserves

White

2009

Theor Ecol

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“…For models that also include directional larval advection, ensuring persistence typically requires more, larger reserves. In so-called infinite coastline models in which there are no upstream or downstream 'edges', reserve performance is optimized when reserve width or spacing is matched to the length scale of advection, so that larvae spawned in a reserve tend to settle in a reserve (Crowder et al 2000, Kaplan 2006). Given the uncertainties involved, such a design would not be recommended.…”

Section: Introductionmentioning

confidence: 99%

Population persistence in marine reserve networks: incorporating spatial heterogeneities in larval dispersal

White

Botsford²,

Hastings³

et al. 2010

Mar. Ecol. Prog. Ser.

120

150

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ABSTRACT:The relationship between marine reserve design and metapopulation persistence has been analyzed only for cases of spatially homogenous advective-diffusive larval dispersal. However, many coastlines exhibit more complex circulation, such as retention zones in which slower-moving currents shorten dispersal distances and larvae can accumulate. We constructed metapopulation models that incorporated 3 types of spatial variability in dispersal associated with retention zones: (A) reduction of both advective (L A ) and stochastic (L S ) length scales of dispersal within the retention zone, (B) reduction of L A only, and (C) accumulation of larvae in the retention zone, followed by redistribution along the coastline. For each scenario, we examined reserve networks with a range of size and spacing configurations. The scenarios differed in the relative number of self-persistent reserves, i.e. those which can survive in isolation, and network-persistent reserves, i.e. those which rely on connectivity through space and across generations to offset shortfalls in direct self-replenishment. When dispersal was dominated by stochastic movements (L S > L A in scenarios A and B), metapopulations typically consisted of self-persistent reserves. As dispersal became increasingly advective (L A > L S ), retention aided persistence, and network persistence became more prevalent. Persistence in scenario C decreased with the amount of redistribution. The specific patterns of persistence depended on the size and number of reserves and demographic parameters, but self-persistence was always more likely for reserves in the retention zone. Thus, placing a reserve in a retention zone to promote population persistence is advisable for all 3 dispersal scenarios.KEY WORDS: Larval dispersal · Dispersal kernel · Headland · Metapopulation · Marine reserve · Persistence · Self-recruitment Resale or republication not permitted without written consent of the publisherMar Ecol Prog Ser 398: [49][50][51][52][53][54][55][56][57][58][59][60][61][62][63][64][65][66][67] 2010 ment influences metapopulation dynamics. Adequate reserve size and placement depends critically on larval dispersal patterns: reserves must be large enough or close enough together to ensure metapopulation persistence (e.g. Botsford et al. 2001, Walters et al. 2007. In this paper, we consider metapopulations made up of many discrete local populations, and define persistence in a deterministic way: when the metapopulation is near extinction, population density will tend to increase rather than decrease. Our interest is in both overall persistence (Does the metapopulation persist in at least one location?) and the spatial pattern of persistence (Where are the persistent local populations?).Recent empirical and theoretical results suggest that persistence of a metapopulation in a system of marine reserves depends on 2 mechanisms: (1) selfpersistence of local populations and (2) persistence that depends on connectivity among all or many locations in the network , Lipcius et al....

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“…Modelling metapopulations in such a complex environment remains a challenge, notwithstanding advances in the fields of hydrodynamics and metapopulation theory (Crowder et al 2000, Bode et al 2008). However, metapopulation models are necessary for evaluating and guiding conservation planning, especially in reserve system design and spatial prioritisation of complex seascapes (Gerber et al 2003, Kritzer & Sale 2004, Crowder & Figueira 2006, Kaplan 2006, Nicholson & Possingham 2007, Moilanen et al 2009). …”

Section: Introductionmentioning

confidence: 99%

Metapopulation mean life time within complex networks

Kininmonth¹,

Drechsler²,

Johst³

et al. 2010

Mar. Ecol. Prog. Ser.

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Metapopulation dynamics depend on the exchange of individuals between populations across the landscape. The environment that the migrants must traverse is influenced by many forces, so the connections are often complicated pathways, which can be represented as a network. The structure of these networks will determine which populations will receive more migrants than other populations, and this in turn affects the lifetime of the metapopulation. We present a modification of the Drechsler (2009) formulae for the mean lifetime of a metapopulation based on network properties where the arrangement of the population connections is not limited to simple dispersal kernels. We provide a graph-theoretical framework for analysing the dispersal network and apply this model to the small-world network of the Great Barrier Reef as well as to conservation planning in general. Our results highlight that the topology of the dispersal network strongly influences the metapopulation mean lifetime. Metapopulation models and conservation planning need to include the capacity for basing interactions on complex topological structures. KEY WORDS: Metapopulation · Dispersal · Networks · Graph theoryResale or republication not permitted without written consent of the publisher

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Alongshore advection and marine reserves: consequences for modeling and management

Cited by 41 publications

References 30 publications

Density dependence and the economic efficacy of marine reserves

Density dependence and the economic efficacy of marine reserves

Population persistence in marine reserve networks: incorporating spatial heterogeneities in larval dispersal

Metapopulation mean life time within complex networks

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