|Modelling harbour porpoise seasonal density as a function of the German Bight environment: implications for management|Gilles, A.; Adler, S.; Kaschner, K.; Scheidat, M.; Siebert, U. (2011). Modelling harbour porpoise seasonal density as a function of the German Bight environment: implications for management. Endang. Species Res. 14(2): 157-169. hdl.handle.net/10.3354/esr00344
In: Endangered Species Research. Inter-Research: Oldendorf/Luhe. ISSN 1613-4796, more
Conservation; Phocoena phocoena (Linnaeus, 1758) [WoRMS]; ANE, North Sea [Marine Regions]; Marine
Habitat modelling; Generalised additive model
|Authors|| || Top |
- Gilles, A.
- Adler, S.
- Kaschner, K.
- Scheidat, M., more
- Siebert, U.
A classical user–environment conflict could arise between the recent expansion plans of offshore wind power in European waters and the protection of the harbour porpoise Phocoena phocoena, an important top predator and indicator species in the North Sea. There is a growing demand for predictive models of porpoise distribution to assess the extent of potential conflicts and to support conservation and management plans. Here, we used a range of oceanographic parameters and generalised additive models to predict harbour porpoise density and to investigate seasonal shifts in porpoise distribution in relation to several static and dynamic predictors. Sightings were collected during dedicated line-transect aerial surveys conducted year-round between 2002 and 2005. Over the 4 yr, survey effort amounted to 38720 km, during which 3887 harbour porpoises were sighted. Porpoises aggregated in distinct hot spots within their seasonal range, but the importance of key habitat descriptors varied between seasons. Predictors explaining most of the variance were the hydrographical parameter ‘residual current’ and proxies for primary production and fronts (chlorophyll and nutrients) as well as the interaction ‘distance to coast/water depth’. Porpoises preferred areas with stronger currents and concentrated in areas where fronts are likely. Internal cross-validation indicated that all models were highly robust. In addition, we successfully externally validated our summer model using an independent data set, which allowed us to extrapolate our predictions to a more regional scale. Our models improve the understanding of determinants of harbour porpoise habitat in the North Sea as a whole and inform management frameworks to determine safe limits of anthropogenic impacts.