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LARVAHS: Predicting clam larval dispersal and recruitment using habitat suitability-based particle tracking model

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  • Bidegain, Gorka
  • Bárcena, Javier Francisco
  • García, Andrés
  • Juanes, José Antonio

Abstract

We herein explore the potential larval dispersal and recruitment patterns of Ruditapes decussatus and Ruditapes philippinarum clams, influenced by larval behavior and hydrodynamics, by means of a particle-tracking model coupled to a hydrodynamic model. The main contribution of this study is that a habitat suitability-based (ENFA, Environmental Niche Factor Analysis) settlement–recruitment submodel was incorporated into the larval dispersal model to simulate settlement behavior and post-settlement mortality. For this purpose, a specific study was carried out in the Bay of Santander (Northern Spain), a well-mixed shallow water estuary where shellfishery of both species is carried out. The model was fed with observed winds, freshwater flows and astronomical tides to obtain predictions during the clams spawning period. Dispersion of larvae from seven spawning zones was tracked, subjected to three-dimensional advection, vertical turbulent diffusion and imposed vertical migration behavior parameterized from existing literature. Three simulation periods (Spring, Summer and Autumn) and two initial releases (spring/neap tide) were combined in six different modeling scenarios. The LARVAHS model proved to be a powerful approach to estimating recruitment success, highlighting the role of habitat suitability, larval swimming behavior, planktonic duration, season (i.e. predominating winds) and spawning ground location on recruitment success together with the effect of the tidal phase at spawning. Moreover, it has proven to be a valuable tool for determining major spawning and nursery grounds and to explore the connectivity between them, having important implications for restoration strategies and shellfisheries as well as aquaculture management.

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  • Bidegain, Gorka & Bárcena, Javier Francisco & García, Andrés & Juanes, José Antonio, 2013. "LARVAHS: Predicting clam larval dispersal and recruitment using habitat suitability-based particle tracking model," Ecological Modelling, Elsevier, vol. 268(C), pages 78-92.
    • Handle: RePEc:eee:ecomod:v:268:y:2013:i:c:p:78-92
    DOI: 10.1016/j.ecolmodel.2013.07.020
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    References listed on IDEAS

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    1. Jones, Peter J.S., 2006. "Collective action problems posed by no-take zones," Marine Policy, Elsevier, vol. 30(2), pages 143-156, March.
    2. Chih-hao Hsieh & Christian S. Reiss & John R. Hunter & John R. Beddington & Robert M. May & George Sugihara, 2006. "Fishing elevates variability in the abundance of exploited species," Nature, Nature, vol. 443(7113), pages 859-862, October.
    3. García, Andrés & Sámano, María Luisa & Juanes, José A. & Medina, Raúl & Revilla, José A. & Álvarez, César, 2010. "Assessment of the effects of a port expansion on algae appearance in a costal bay through mathematical modelling. Application to San Lorenzo Bay (North Spain)," Ecological Modelling, Elsevier, vol. 221(10), pages 1413-1426.
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    1. Saraiva, S. & Fernandes, L. & van der Meer, J. & Neves, R. & Kooijman, S.A.L.M., 2017. "The role of bivalves in the Balgzand: First steps on an integrated modelling approach," Ecological Modelling, Elsevier, vol. 359(C), pages 34-48.
    2. Monal M Lal & Cyprien Bosserelle & Pranesh Kishore & Paul C Southgate, 2020. "Understanding marine larval dispersal in a broadcast-spawning invertebrate: A dispersal modelling approach for optimising spat collection of the Fijian black-lip pearl oyster Pinctada margaritifera," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-22, June.
    3. Bidegain, G. & Powell, E.N. & Klinck, J.M. & Ben-Horin, T. & Hofmann, E.E., 2016. "Microparasitic disease dynamics in benthic suspension feeders: Infective dose, non-focal hosts, and particle diffusion," Ecological Modelling, Elsevier, vol. 328(C), pages 44-61.
    4. Melo-Merino, Sara M. & Reyes-Bonilla, Héctor & Lira-Noriega, Andrés, 2020. "Ecological niche models and species distribution models in marine environments: A literature review and spatial analysis of evidence," Ecological Modelling, Elsevier, vol. 415(C).

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