Real-time predictions of seabird distribution offer improved basis for risk assessments in the future
Abstract: Current knowledge is inadequate to safeguard seabird populations from impacts of oil spills, overfishing, displacement and collision risk at marine renewable installations. This gap is to a large extent driven by the fact that standard statistical models applied to survey data provide limi...
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| Format: | Article in Journal/Newspaper |
| Language: | unknown |
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Underline Science Inc.
2021
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| Online Access: | https://dx.doi.org/10.48448/ztrb-aw32 https://underline.io/lecture/34765-real-time-predictions-of-seabird-distribution-offer-improved-basis-for-risk-assessments-in-the-future |
| Summary: | Abstract: Current knowledge is inadequate to safeguard seabird populations from impacts of oil spills, overfishing, displacement and collision risk at marine renewable installations. This gap is to a large extent driven by the fact that standard statistical models applied to survey data provide limited documentation of the fine-scale distributional dynamics and patchiness of seabirds. Here, a new dynamic modelling framework solution is presented for prediction of fine-scale concentrations 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 seabirds in the Barents Sea where available seabird survey data are fragmented. Long-term (10 years) dynamic patterns describing currents and winds at hourly intervals were extracted from a 3-dimensional hydrodynamic module calibrated against local measurements. Long-term patterns of habitat suitability were deduced from dynamic distribution models describing the correlation between surveyed densities and water mass and frontal characteristics extracted at hourly intervals from the hydrodynamic module. Long-term movement patterns and energetics were quantified using agent-based models which integrated the modelled timeseries of currents, winds, sea temperature and habitat suitability. The oceanographic and habitat predictions were validated against independent measurements and observations, which were not used in the parameterisation of the models. The model results underline that model complexes integrating high-resolution hydrodynamic, distribution and agent-based models constitute an improved basis for undertaking more precise assessments of the risk of seabirds from anthropogenic pressures in the future. Authors: Henrik Skov¹, Teo Theophilus², Mads Madsen¹, Thomas Uhrenholdt¹, Frank Thomsen¹, Jonas Mortensen¹, Per Fauchald³, Stefan Heinänen⁴ ¹DHI, ²DHI Water & Environment Pte. Ltd., ³Norwegian Institute for Nature Research, ⁴Novia University of Applied Sciences |
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