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dc.contributor.authorSwearer, Stephen E.
dc.contributor.authorTreml, Eric A.
dc.contributor.authorShima, Jeffrey S.
dc.date.accessioned2021-02-10T12:58:18Z
dc.date.issued2019
dc.date.submitted2019-10-21 11:50:32
dc.date.submitted2020-04-01T10:07:34Z
dc.identifier1005391
dc.identifierOCN: 1135848726
dc.identifierhttp://library.oapen.org/handle/20.500.12657/24720
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/32642
dc.description.abstractLarval dispersal is arguably the most important but least understood demographic process in the sea. The likelihood of a larva dispersing from its birthplace to successfully recruit in another location is the culmination of many intrinsic and extrinsic factors that operate in early life. Empirically estimating the resulting population connectivity has been immensely difficult because of the challenges of studying and quantifying dispersal in the sea. Consequently, most estimates are based on predictions from biophysical models. Although there is a long history of dispersal modelling, there has been no comprehensive review of this literature. We conducted a systematic quantitative review to address the following questions: (1) Is there any bias in the distribution of research effort based on geographical or taxonomic coverage? (2) Are hydrodynamic models resolving ocean circulation at spatial scales (resolution and extent) relevant to the dispersal process under study? (3) Where, when and how many particles are being tracked, and is this effort sufficient to capture the spatiotemporal variability in dispersal? (4) How is biological and/or behavioural complexity incorporated into Lagrangian particle tracking models. (i.e. are key attributes of the dispersal process well captured.)? Our review confirms strong taxonomic and geographic biases in published work to date. We found that computational ‘effort’ (i.e. model resolution and particle number) has not kept pace with dramatic increases in computer processor speed. We also identified a number of shortcomings in the incorporation of biology, and behaviour specifically into models. Collectively, these findings highlight some important gaps and key areas for improvement of biophysical models that aspire to inform larval dispersal processes. In particular, we suggest the need for greater emphasis on validation of model assumptions, as well as testing of dispersal predictions with empirically derived data.
dc.languageEnglish
dc.relation.ispartofseriesOceanography and Marine Biology : An Annual Review
dc.rightsopen access
dc.subject.classificationbic Book Industry Communication::P Mathematics & science::PS Biology, life sciences
dc.subject.otherbiophysical models
dc.subject.othermarine larval dispersal
dc.subject.otherdemographic process
dc.subject.othersea
dc.titleChapter 7 A Review of Biophysical Models of Marine Larval Dispersal
dc.typechapter
oapen.relation.isPublishedByfa69b019-f4ee-4979-8d42-c6b6c476b5f0
oapen.relation.isPartOfBook29a8cb48-f444-4dd1-800c-bad320692b7c
oapen.relation.isPartOfBook60c15fb0-a7a8-4a16-aa06-d47245bd60dc
oapen.relation.isbn9780429026379
oapen.imprintCRC Press
oapen.pages34


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