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Integrating genetics, biophysical, and demographic insights identifies critical sites for seagrass conservation

Artikel i vetenskaplig tidskrift
Författare Marlene Jahnke
Per-Olav Moksnes
J. L. Olsen
N. S. Serra
M. N. Jacobi
K. Kuusemae
H. Corell
Per R. Jonsson
Publicerad i Ecological Applications
ISSN 1051-0761
Publiceringsår 2020
Publicerad vid Institutionen för marina vetenskaper
Institutionen för marina vetenskaper, Tjärnö marinlaboratoriet
Språk en
Länkar dx.doi.org/10.1002/eap.2121
Ämnesord biophysical modeling, connectivity, conservation, demographic modeling, dispersal, eelgrass, marine spatial management, restoration, seagrass, seascape ecology, seascape genetics, Zostera marina, zostera-marina, population-structure, seascape genetics, landscape, ecology, r package, connectivity, restoration, dispersal, diversity, networks, Environmental Sciences & Ecology
Ämneskategorier Marin ekologi

Sammanfattning

The eelgrass Zostera marina is an important foundation species of coastal areas in the Northern Hemisphere, but is continuing to decline, despite management actions. The development of new management tools is therefore urgent in order to prioritize limited resources for protecting meadows most vulnerable to local extinctions and identifying most valuable present and historic meadows to protect and restore, respectively. We assessed 377 eelgrass meadows along the complex coastlines of two fjord regions on the Swedish west coast-one is currently healthy and the other is substantially degraded. Shoot dispersal for all meadows was assessed with Lagrangian biophysical modeling (scale: 100-1,000 m) and used for barrier analysis and clustering; a subset (n = 22) was also assessed with population genetic methods (20 microsatellites) including diversity, structure, and network connectivity. Both approaches were in very good agreement, resulting in seven subpopulation groupings or management units (MUs). The MUs correspond to a spatial scale appropriate for coastal management of "waterbodies" used in the European Water Framework Directive. Adding demographic modeling based on the genetic and biophysical data as a third approach, we are able to assess past, present, and future metapopulation dynamics to identify especially vulnerable and valuable meadows. In a further application, we show how the biophysical approach, using eigenvalue perturbation theory (EPT) and distribution records from the 1980s, can be used to identify lost meadows where restoration would best benefit the present metapopulation. The combination of methods, presented here as a toolbox, allows the assessment of different temporal and spatial scales at the same time, as well as ranking of specific meadows according to key genetic, demographic and ecological metrics. It could be applied to any species or region, and we exemplify its versatility as a management guide for eelgrass along the Swedish west coast.

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