Data_Sheet_1_Use of an INLA Latent Gaussian Modeling Approach to Assess Bird Population Changes Due to the Development of Offshore Wind Farms.pdf
The utilization of marine renewable energies such as offshore wind farming leads to globally expanding human activities in marine habitats. While knowledge on the responses to offshore wind farms and associated shipping traffic is accumulating now at a fast pace, it becomes important to assess the p...
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ftfrontimediafig:oai:figshare.com:article/14931423 2023-05-15T16:19:34+02:00 Data_Sheet_1_Use of an INLA Latent Gaussian Modeling Approach to Assess Bird Population Changes Due to the Development of Offshore Wind Farms.pdf Raul Vilela Claudia Burger Ansgar Diederichs Fabian E. Bachl Lesley Szostek Anika Freund Alexander Braasch Jochen Bellebaum Brian Beckers Werner Piper Georg Nehls 2021-07-08T06:06:02Z https://doi.org/10.3389/fmars.2021.701332.s001 https://figshare.com/articles/dataset/Data_Sheet_1_Use_of_an_INLA_Latent_Gaussian_Modeling_Approach_to_Assess_Bird_Population_Changes_Due_to_the_Development_of_Offshore_Wind_Farms_pdf/14931423 unknown doi:10.3389/fmars.2021.701332.s001 https://figshare.com/articles/dataset/Data_Sheet_1_Use_of_an_INLA_Latent_Gaussian_Modeling_Approach_to_Assess_Bird_Population_Changes_Due_to_the_Development_of_Offshore_Wind_Farms_pdf/14931423 CC BY 4.0 CC-BY Oceanography Marine Biology Marine Geoscience Biological Oceanography Chemical Oceanography Physical Oceanography Marine Engineering Red-throated loons Gavia sp population trend German North Sea Bayesian model INLA SPDE latent Gaussian model Dataset 2021 ftfrontimediafig https://doi.org/10.3389/fmars.2021.701332.s001 2021-07-14T23:00:45Z The utilization of marine renewable energies such as offshore wind farming leads to globally expanding human activities in marine habitats. While knowledge on the responses to offshore wind farms and associated shipping traffic is accumulating now at a fast pace, it becomes important to assess the population impacts on species affected by those activities. In the North Sea, the protected diver species Red-throated Diver (Gavia stellata) and Black-throated Diver (Gavia arctica) widely avoid offshore wind farms. We used an explicit spatio-temporal Bayesian model to get a robust estimate of the diver population during the spring season between 2001 and 2018, based on a set of aerial surveys from long-term monitoring programs within the German North Sea. Despite the erection of 20 offshore wind farms in the study area and marked responses of divers to wind farms, model results indicated that there was no population decline, and overall numbers fluctuated around 16,600 individuals, with average annual 95% CI ranging between 13,400 and 21,360 individuals. Although, avoidance behavior due to wind farm development led to a more narrowly focused spatial distribution of the birds centered in the persistent high concentration zone in the Eastern German Bight Special Protection Area, the results provide no indication of negative fitness consequences on these long-lived species. However, more research is needed on habitat use and food availability in this regard. Dataset Gavia arctica Frontiers: Figshare |
institution |
Open Polar |
collection |
Frontiers: Figshare |
op_collection_id |
ftfrontimediafig |
language |
unknown |
topic |
Oceanography Marine Biology Marine Geoscience Biological Oceanography Chemical Oceanography Physical Oceanography Marine Engineering Red-throated loons Gavia sp population trend German North Sea Bayesian model INLA SPDE latent Gaussian model |
spellingShingle |
Oceanography Marine Biology Marine Geoscience Biological Oceanography Chemical Oceanography Physical Oceanography Marine Engineering Red-throated loons Gavia sp population trend German North Sea Bayesian model INLA SPDE latent Gaussian model Raul Vilela Claudia Burger Ansgar Diederichs Fabian E. Bachl Lesley Szostek Anika Freund Alexander Braasch Jochen Bellebaum Brian Beckers Werner Piper Georg Nehls Data_Sheet_1_Use of an INLA Latent Gaussian Modeling Approach to Assess Bird Population Changes Due to the Development of Offshore Wind Farms.pdf |
topic_facet |
Oceanography Marine Biology Marine Geoscience Biological Oceanography Chemical Oceanography Physical Oceanography Marine Engineering Red-throated loons Gavia sp population trend German North Sea Bayesian model INLA SPDE latent Gaussian model |
description |
The utilization of marine renewable energies such as offshore wind farming leads to globally expanding human activities in marine habitats. While knowledge on the responses to offshore wind farms and associated shipping traffic is accumulating now at a fast pace, it becomes important to assess the population impacts on species affected by those activities. In the North Sea, the protected diver species Red-throated Diver (Gavia stellata) and Black-throated Diver (Gavia arctica) widely avoid offshore wind farms. We used an explicit spatio-temporal Bayesian model to get a robust estimate of the diver population during the spring season between 2001 and 2018, based on a set of aerial surveys from long-term monitoring programs within the German North Sea. Despite the erection of 20 offshore wind farms in the study area and marked responses of divers to wind farms, model results indicated that there was no population decline, and overall numbers fluctuated around 16,600 individuals, with average annual 95% CI ranging between 13,400 and 21,360 individuals. Although, avoidance behavior due to wind farm development led to a more narrowly focused spatial distribution of the birds centered in the persistent high concentration zone in the Eastern German Bight Special Protection Area, the results provide no indication of negative fitness consequences on these long-lived species. However, more research is needed on habitat use and food availability in this regard. |
format |
Dataset |
author |
Raul Vilela Claudia Burger Ansgar Diederichs Fabian E. Bachl Lesley Szostek Anika Freund Alexander Braasch Jochen Bellebaum Brian Beckers Werner Piper Georg Nehls |
author_facet |
Raul Vilela Claudia Burger Ansgar Diederichs Fabian E. Bachl Lesley Szostek Anika Freund Alexander Braasch Jochen Bellebaum Brian Beckers Werner Piper Georg Nehls |
author_sort |
Raul Vilela |
title |
Data_Sheet_1_Use of an INLA Latent Gaussian Modeling Approach to Assess Bird Population Changes Due to the Development of Offshore Wind Farms.pdf |
title_short |
Data_Sheet_1_Use of an INLA Latent Gaussian Modeling Approach to Assess Bird Population Changes Due to the Development of Offshore Wind Farms.pdf |
title_full |
Data_Sheet_1_Use of an INLA Latent Gaussian Modeling Approach to Assess Bird Population Changes Due to the Development of Offshore Wind Farms.pdf |
title_fullStr |
Data_Sheet_1_Use of an INLA Latent Gaussian Modeling Approach to Assess Bird Population Changes Due to the Development of Offshore Wind Farms.pdf |
title_full_unstemmed |
Data_Sheet_1_Use of an INLA Latent Gaussian Modeling Approach to Assess Bird Population Changes Due to the Development of Offshore Wind Farms.pdf |
title_sort |
data_sheet_1_use of an inla latent gaussian modeling approach to assess bird population changes due to the development of offshore wind farms.pdf |
publishDate |
2021 |
url |
https://doi.org/10.3389/fmars.2021.701332.s001 https://figshare.com/articles/dataset/Data_Sheet_1_Use_of_an_INLA_Latent_Gaussian_Modeling_Approach_to_Assess_Bird_Population_Changes_Due_to_the_Development_of_Offshore_Wind_Farms_pdf/14931423 |
genre |
Gavia arctica |
genre_facet |
Gavia arctica |
op_relation |
doi:10.3389/fmars.2021.701332.s001 https://figshare.com/articles/dataset/Data_Sheet_1_Use_of_an_INLA_Latent_Gaussian_Modeling_Approach_to_Assess_Bird_Population_Changes_Due_to_the_Development_of_Offshore_Wind_Farms_pdf/14931423 |
op_rights |
CC BY 4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.3389/fmars.2021.701332.s001 |
_version_ |
1766005960294268928 |