The first offshore wind farm 'alpha ventus' in the German North Sea was constructed north east of Borkum Reef Ground approximately 45 km north off the German coast in 2008 and 2009 using percussive piling for the foundations of 12 wind turbines. Visual monitoring of harbour porpoises was conducted prior to as well as during construction and operation by means of 15 aerial line transect distance sampling surveys, from 2008 to 2010. Static acoustic monitoring (SAM) with echolocation click loggers at 12 positions was performed additionally from 2008 to 2011. SAM devices were deployed between 1 and 50 km from the centre of the wind farm. During aerial surveys, 18 600 km of transect lines were covered in two survey areas (10 934 and 11 824 km 2 ) and 1392 harbour porpoise sightings were recorded. Lowest densities were documented during the construction period in 2009. The spatial distribution pattern recorded on two aerial surveys three weeks before and exactly during pile-driving points towards a strong avoidance response within 20 km distance of the noise source. Generalized additive modelling of SAM data showed a negative impact of pile-driving on relative porpoise detection rates at eight positions at distances less than 10.8 km. Increased detection rates were found at two positions at 25 and 50 km distance suggesting that porpoises were displaced towards these positions. A pile-driving related behavioural reaction could thus be detected using SAM at a much larger distance than a pure avoidance radius would suggest. The first waiting time (interval between porpoise detections of at least 10 min), after piling started, increased with longer piling durations. A gradient in avoidance, a gradual fading of the avoidance reaction with increasing distance from the piling site, is hence most probably a product of an incomplete displacement during shorter piling events.
The seasonal distribution of harbour porpoises in the German North Sea was investigated, hot spot areas were identified and the proportion of porpoises potentially affected by the imminent construction of offshore wind farms was estimated. Data were collected during dedicated aerial surveys conducted year-round between 2002 and 2006 following line transect methodology. Survey effort amounted to 44 739 km during which a total of 5121 harbour porpoises was detected, including 258 calves. Our data suggest that porpoises move to distinct areas on a seasonal basis as their biological requirements change. They move into German waters in early spring, reach high numbers in early summer and move out of the area in autumn. The abundance estimates for the German exclusive economic zone and 12 n mile zone were highest in spring (55 048 animals; 95% CI: 32 395 to 101 671) and summer (49 687 animals; 95% CI: 29 009 to 96 385) and lowest in autumn with 15 394 animals (95% CI: 8906 to 29 470). Important aggregation zones were detected in offshore waters: in spring, 2 hot spots, Borkum Reef Ground and Sylt Outer Reef (SOR), were identified as key foraging areas. In summer, only the large hot spot SOR persisted, causing a strong north-south density gradient. In autumn, porpoises were more evenly distributed. Most mother-calf pairs were observed during spring and summer in the SOR, underlining its importance as a foraging area when reproductive costs are high. Spatial overlap exists between important areas for porpoises and areas where offshore wind farms are currently licensed or planned. The proportion of the national stock possibly exposed to the construction noise of 18 licensed wind farms was estimated applying different scenarios. Within a 20 km zone of responsiveness -as worst case scenario -39% of the harbour porpoise stock in the German EEZ could be affected during construction.KEY WORDS: Phocoena phocoena · Harbour porpoise · North Sea · Aerial survey · Distribution · Foraging · Reproduction area · Offshore wind farm · Generalised additive model Resale or republication not permitted without written consent of the publisherMar Ecol Prog Ser 383: [295][296][297][298][299][300][301][302][303][304][305][306][307] 2009 Union ( Fig. 1), and it is therefore imperative to obtain baseline data on marine mammal distributions in order to assess the risk of, and mitigate for, the impact of construction.The southeastern North Sea is an area with a wide range of human activities (Ducrotoy et al. 2000, OSPAR Commission 2000, Halpern et al. 2008. The harbour porpoise Phocoena phocoena (Linnaeus, 1758) is the most common cetacean in the North Sea (Hammond et al. 2002) and the only cetacean species found regularly in German waters (Scheidat et al. 2004, Siebert et al. 2006. There is evidence that harbour porpoise abundance in the southeastern North Sea has declined since the 1940s (Smeenk 1987, Reijnders 1992, Camphuysen & Leopold 1993. Various pressures have been identified, such as bycatch (Kock & Benke 1996, Vinther & L...
. 2016. Seasonal habitat-based density models for a marine top predator, the harbor porpoise, in a dynamic environment. Ecosphere 7(6):e01367. 10. 1002/ecs2.1367 Abstract. Effective species conservation and management requires information on species distribution patterns, which is challenging for highly mobile and cryptic species that may be subject to multiple anthropogenic stressors across international boundaries. Understanding species-habitat relationships can improve the assessment of trends and distribution by explicitly allowing high-resolution data on habitats to inform abundance estimation and the identification of protected areas. In this study, we aggregated an unprecedented set of survey data of a marine top predator, the harbor porpoise (Phocoena phocoena), collected in the UK (SCANS II, Dogger Bank), Belgium, the Netherlands, Germany, and Denmark, to develop seasonal habitat-based density models for the central and southern North Sea. Visual survey data were collected over 9 yr (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013) by means of dedicated line-transect surveys, taking into account the proportion of missed sightings. Generalized additive models of porpoise density were fitted to 156,630 km of on-effort survey data with 14,356 sightings of porpoise groups. Selected predictors included static and dynamic variables, such as depth, distance to shore and to sandeel (Ammodytes spp.) grounds, sea surface temperature (SST), proxies for fronts, and day length. Day length and the spatial distribution of daily SST proved to be good proxies for "season," allowing predictions in both space and time. The density models captured seasonal distribution shifts of porpoises across international boundaries. By combining the large-scale international SCANS II survey with the more frequent, small-scale national surveys, it has been possible to provide seasonal maps that will be used to assist the EU Habitats and Marine Strategy Framework Directives in effectively assessing the conservation status of harbor porpoises. Moreover, our results can facilitate the identification of regions where human activities and disturbances are likely to impact the population and are especially relevant for marine spatial planning, which requires accurate fine-scale maps of species distribution to assess risks of increasing human activities at sea.
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