Real-time predictions of seabird distribution improve oil spill risk assessments
| Autor: | Stefan Heinänen, Henrik Skov, Per Fauchald, Mads Madsen, Thomas Uhrenholdt, Teo Zhi En Theophilus, Jonas Brandi Mortensen, Frank Thomsen |
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| Rok vydání: | 2020 |
| Předmět: |
0106 biological sciences
Distribution (economics) 010501 environmental sciences Aquatic Science Oceanography 01 natural sciences Risk Assessment Charadriiformes biology.animal Animals Petroleum Pollution Ecosystem 0105 earth and related environmental sciences biology business.industry Arctic Regions 010604 marine biology & hydrobiology Statistical model biology.organism_classification Pollution Arctic Uria lomvia Oil spill Survey data collection Environmental science Seabird Risk assessment business |
| Zdroj: | Marine pollution bulletin. 170 |
| ISSN: | 1879-3363 |
| Popis: | Current knowledge of the distribution of sensitive seabirds is inadequate to safeguard seabird populations from impacts of oil spills in the Arctic. This gap is mainly driven by the fact that statistical models applied to survey data are coarse-scale and static with limited documentation of the distributional dynamics and patchiness of seabirds relevant to risk assessments related to oil spills. This paper describes a dynamic modelling framework solution for prediction of fine-scale densities and movements of seabirds in close-to-real time using fully integrated 3-D hydrodynamic models, dynamic habitat suitability models and agent-based models. The modelling framework has been developed and validated for the swimming migration of Brunnich's Guillemot Uria lomvia in the Barents Sea. The results document that the distributional dynamics of Brunnich's Guillemot and other seabird species to a large degree can be simulated with in-situ state variables and patterns reflecting the physical meteorology and oceanography and habitat suitability. |
| Databáze: | OpenAIRE |
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