Low genotypic diversity and long-term ecological decline in a spatially structured seagrass population

• Published in: Scientific reports Vol. 9; no. 1; pp. 18387 - 11
• Main Authors: Alotaibi, Nahaa M., Kenyon, Emma J., Cook, Kevan J., Börger, Luca, Bull, James C.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 05-12-2019; Nature Publishing Group
• Subjects: 631/158/2464; 631/158/670; 631/449/2491; 631/449/2668; Abundance; Alleles; Aquatic Organisms; Biological Evolution; Conservation; Conservation areas; Ecological monitoring; Ecosystem; Environmental monitoring; Evolution; Genetic diversity; Genetic structure; Genetic Variation; Genetics, Population; Genotype; Humanities and Social Sciences; Islands; Microsatellite Repeats; Microsatellites; multidisciplinary; Population decline; Population genetics; Sample size; Science; Science (multidisciplinary); United Kingdom; Zosteraceae - classification; Zosteraceae - genetics; United Kingdom
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-019-54828-1

In isolated or declining populations, viability may be compromised further by loss of genetic diversity. Therefore, it is important to understand the relationship between long-term ecological trajectories and population genetic structure. However, opportunities to combine these types of data are rare, especially in natural systems. Using an existing panel of 15 microsatellites, we estimated allelic diversity in seagrass,
Zostera marina
, at five sites around the Isles of Scilly Special Area of Conservation, UK, in 2010 and compared this to 23 years of annual ecological monitoring (1996–2018). We found low diversity and long-term declines in abundance in this relatively pristine but isolated location. Inclusion of the snapshot of genotypic, but less-so genetic, diversity improved prediction of abundance trajectories; however, this was spatial scale-dependent. Selection of the appropriate level of genetic organization and spatial scale for monitoring is, therefore, important to identify drivers of eco-evolutionary dynamics. This has implications for the use of population genetic information in conservation, management, and spatial planning.