Data from: Spatiotemporal variability in the structure of seagrass meadows and associated macrofaunal assemblages in southwest England (UK): using citizen science to benchmark ecological pattern
Smale, Dan A.; Epstein, Graham; Parry, Mark; Attrill, Martin J. (2019), Data from: Spatiotemporal variability in the structure of seagrass meadows and associated macrofaunal assemblages in southwest England (UK): using citizen science to benchmark ecological pattern, Dryad, Dataset, https://doi.org/10.5061/dryad.r06g604
Seagrass meadows underpin a variety of ecosystem services and are recognised as globally important habitats and a conservation priority. However, seagrass populations are currently impacted by a range of biotic and abiotic stressors, and many are in decline globally. As such, improved understanding of seagrass populations and their associated faunal assemblages is needed to better detect and predict changes in the structure and functioning of these key habitats. Here, we analysed a large dataset -collected by recreational scuba divers volunteering on a citizen science project - to examine spatiotemporal patterns in ecological structure and to provide a robust and reliable baseline against which to detect future change. Seagrass (Zostera marina) shoot density and the abundance of associated faunal groups was quantified across 2 years at 19 sites nested within 3 locations in southwest UK, by collecting in situ quadrat samples (2518 in total) during 328 dives. Seagrass shoot density and meadow fragmentation was comparable across locations but was highly variable amongst sites. Faunal abundance and assemblage structure varied between areas with or without seagrass shoots; this pattern was largely consistent between locations and years. Overall, increased seagrass density was related to increased faunal abundance and explained shifts in faunal assemblage structure, although individual faunal groups were affected differently. More broadly, our study shows that well-funded and orchestrated citizen science projects can, to some extent, gather fundamental information needed to benchmark ecological structure in poorly-studied nearshore marine habitats.