Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/72729
|Títulos:||Long-term seagrass degradation: Integrating landscape, demographic, and genetic responses||Autores/as:||Manent, Pablo
Curbelo Muñoz, Leticia
Espino Rodríguez, Fernando
|Clasificación UNESCO:||241705 Biología marina||Palabras clave:||Anthropogenic Disturbances
|Fecha de publicación:||2020||Publicación seriada:||Aquatic Conservation: Marine and Freshwater Ecosystems||Resumen:||Seagrass meadows are crucial habitats on nearshore areas, which are exposed to human disturbances that frequently cause seagrass loss. Although demographic and mapping data have been widely used in long-term monitoring programmes, the integration of multi-locus genotype data through time remains rare. The present work links, for the first time, landscape, demographic, and genetic data for a seagrass, so as to explore long-term responses to persistent human impacts. The temporal patterns in meadow area, shoot density, and clonal and genetic diversity of three Cymodocea nodosa meadows were compared: in one meadow directly affected by the construction of an industrial port and in two control areas. The hypothesis tested was that seagrass deterioration and subsequent habitat loss at the affected meadow would be associated with a reduction of seagrass clonal and genetic diversity. The results show significant reductions in both meadow area (from approx. 21 to 1.5 ha) and shoot density (from approx. 1,800 to 400 shoots per m2) at the impacted meadow, with concurrently reduced clonal and allelic richness (by approx. 22%), as well as heterozygosity (HLmean, approx. 21%; Hobs, approx. 12%). These descriptors, however, remained stable, or even increased, in the controls. Importantly for seagrass management, multi-disciplinary analysis made it possible to link slower, large-scale, landscape and genetic degradation processes with faster demographic deterioration on an intermediate meadow scale. Multi-locus genotype data were also crucial for revealing long-term degradation processes at the genetic level, which is undetectable by traditional monitoring techniques. In summary, this holistic approach provides a valuable framework for long-term seagrass monitoring programmes to detect cumulative signals of seagrass meadow degradation across a range of scales.||URI:||http://hdl.handle.net/10553/72729||ISSN:||1052-7613||DOI:||10.1002/aqc.3325||Fuente:||Aquatic Conservation: Marine and Freshwater Ecosystems [ISSN 1052-7613], (Enero 2020)|
actualizado el 23-may-2020
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