Small-scale distribution modeling of benthic species in a protected natural hard ground area in the German North Sea (Helgoländer Steingrund)

Natural stony and coarse-grained habitats entail important ecological features for the marine environment. Due to the complexity of their bottom characteristics, they host a high biodiversity compared to surrounding soft bottom areas. The German nature conservation area “Helgoländer Steingrund” (HSG...

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Veröffentlicht in:Geo-marine letters 2020-04, Vol.40 (2), p.167-181
Hauptverfasser: Becker, Lydia R., Bartholomä, Alexander, Singer, Anja, Bischof, Kai, Coers, Susanne, Kröncke, Ingrid
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Sprache:eng
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Zusammenfassung:Natural stony and coarse-grained habitats entail important ecological features for the marine environment. Due to the complexity of their bottom characteristics, they host a high biodiversity compared to surrounding soft bottom areas. The German nature conservation area “Helgoländer Steingrund” (HSG; 54°14.00 N and 8°03.00 W) is subject to regular monitoring but lacks information on the spatial distribution of benthic species. Within this study, a new approach using species distribution models (SDM) was tested to fill these gaps of knowledge. Newly recorded environmental data (depth, sediments, current velocities) in the HSG and information on the presence and absences of nine benthic species ( Echinus esculentus , Metridium senile , Cancer pagurus , Phymatolithon spp., Axinella polypoides , Homarus gammarus , Flustra foliacea , Alcyonidium diaphanum , Alcyonium digitatum ), collected using video analysis of drop camera records, was used to perform SDMs. The models revealed good evaluation measures (true skill statistic > 0.7; area under the receiver operation characteristic curve > 0.90), implying that the model showed good predictive performance for the potential distribution of the tested species. The outcome of this study is a clear recommendation on SDM application in further environmental monitoring programs on the HSG and other protected hard ground areas.
ISSN:0276-0460
1432-1157
DOI:10.1007/s00367-019-00598-8