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

Jahnke, Marlene (författare)
Gothenburg University,Göteborgs universitet,Institutionen för marina vetenskaper, Tjärnö marinlaboratoriet,Department of marine sciences, Tjärnö Marine Laboratory,University of Gothenburg
Moksnes, Per-Olav, 1965 (författare)
Gothenburg University,Göteborgs universitet,Institutionen för marina vetenskaper,Department of marine sciences,University of Gothenburg
Olsen, J. L. (författare)
Rijksuniversiteit Groningen,University of Groningen
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Serra, N. S. (författare)
Rijksuniversiteit Groningen,University of Groningen
Nilsson Jacobi, Martin, 1972 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
Kuusemae, K. (författare)
DHI
Corell, H. (författare)
Jonsson, Per R., 1957 (författare)
Gothenburg University,Göteborgs universitet,Institutionen för marina vetenskaper, Tjärnö marinlaboratoriet,Department of marine sciences, Tjärnö Marine Laboratory,University of Gothenburg
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 (creator_code:org_t)
2020-04-15
2020
Engelska.
Ingår i: Ecological Applications. - : Wiley. - 1051-0761 .- 1939-5582. ; 30:6
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • 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.

Ämnesord

NATURVETENSKAP  -- Biologi -- Ekologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Ecology (hsv//eng)
NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Annan geovetenskap och miljövetenskap (hsv//swe)
NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Other Earth and Related Environmental Sciences (hsv//eng)
LANTBRUKSVETENSKAPER  -- Lantbruksvetenskap, skogsbruk och fiske -- Landskapsarkitektur (hsv//swe)
AGRICULTURAL SCIENCES  -- Agriculture, Forestry and Fisheries -- Landscape Architecture (hsv//eng)

Nyckelord

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
biophysical modeling

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