Show simple item record

dc.contributor.author Östergren, Johan
dc.contributor.author Koljenen, Marja - Liisa
dc.contributor.author Whitlock, Rebecca
dc.contributor.author Mäntyniemi, Samu
dc.contributor.author Palm, Stefan
dc.contributor.author Dannewitz, Johan
dc.coverage.spatial Baltic Sea
dc.coverage.temporal 2014
dc.date.accessioned 2017-12-06T22:21:05Z
dc.date.available 2017-12-06T22:21:05Z
dc.date.issued 2017-12-05
dc.identifier doi:10.5061/dryad.4pg37
dc.identifier.citation Whitlock R, Mäntyniemi S, Palm S, Koljonen M, Dannewitz J, Östergren J (2017) Integrating genetic analysis of mixed populations with a spatially-explicit population dynamics model. Methods in Ecology and Evolution, online in advance of print.
dc.identifier.uri http://hdl.handle.net/10255/dryad.163222
dc.description Inferring the dynamics of populations in time and space is a central challenge in ecology. Intra-specific structure (for example genetically distinct sub-populations or meta-populations) may require methods that can jointly infer the dynamics of multiple populations. This is of particular importance for harvested species, for which management must balance utilization of productive populations with protection of weak ones. Here we present a novel method for simultaneous learning about the spatio-temporal dynamics of multiple populations that combines genetic data with prior information about abundance and movement in an integrated population modelling approach. We apply the Bayesian genetic mixed stock analysis to 17 wild and 10 hatchery-reared Baltic salmon (S. salar) stocks, quantifying uncertainty in stock composition in time and space, and in population dynamics parameters such as migration timing and speed. Our results indicate that the commonly used “equal prior probabilities” assumption may not be appropriate for all mixed stock analyses. Incorporation of prior information about stock abundance and movement resulted in more precise and plausible estimates of mixture compositions in time and space. Inclusion of a population dynamics model also allowed robust interpolation of expected catch composition at areas and times with no genetic observations. The genetic data were informative about stock-specific movement patterns, updating priors for migration path, timing and speed. The model we present here forms the basis for optimizing the spatial and temporal allocation of harvest to support the management of mixed populations of migratory species.
dc.relation.haspart doi:10.5061/dryad.4pg37/1
dc.relation.haspart doi:10.5061/dryad.4pg37/2
dc.relation.isreferencedby doi:10.1111/2041-210x.12946
dc.subject Baltic salmon
dc.subject mixed fisheries
dc.subject Bayesian
dc.subject spatial model
dc.title Data from: Integrating genetic analysis of mixed populations with a spatially-explicit population dynamics model
dc.type Article
dwc.ScientificName Salmo salar
dc.contributor.correspondingAuthor Whitlock, Rebecca
prism.publicationName Methods in Ecology and Evolution

Files in this package

Content in the Dryad Digital Repository is offered "as is." By downloading files, you agree to the Dryad Terms of Service. To the extent possible under law, the authors have waived all copyright and related or neighboring rights to this data. CC0 (opens a new window) Open Data (opens a new window)

Title Baltic_salmon_baseline_data
Downloaded 6 times
Description Baseline genotypes (17 microsatellite loci) for Baltic salmon from 27 stocks (3593 individuals of known stock of origin).
Download Baltic_salmon_baseline_data.csv (544.5 Kb)
Download README.docx (27.24 Kb)
Details View File Details
Title Baltic_salmon_mixture_data
Downloaded 3 times
Description Baltic salmon mixture data: Genotypes (17 microsatellite loci) for 2058 Baltic salmon individuals sampled from Swedish and Finnish coastal trap net fisheries in 2014.
Download Baltic_salmon_mixture_data.csv (313.0 Kb)
Download README.docx (27.90 Kb)
Details View File Details

Search for data

Be part of Dryad

We encourage organizations to: