Affiliation:
1. Department of Biosciences, Biotechnology and Environment University of Bari Aldo Moro Bari Italy
2. Archipelagos Institute of Marine Conservation Pythagorio Samos Greece
3. Department of Mechanical Engineering Brunel University London Uxbridge UK
4. Department of Estuarine and Delta Systems NIOZ Royal Netherlands Institute for Sea Research Yerseke The Netherlands
5. Department of Physical Geography Utrecht University Utrecht The Netherlands
6. Department of Geology and Geoenvironment, School of Science National and Kapodistrian University of Athens Athens Greece
Abstract
Abstract
Cetaceans are considered bioindicators of the health state of marine ecosystems owing to their wide distribution across the different aquatic ecosystems in the world and their significant top‐down control role in the food chain, despite their low biomass. At the same time, effective management of wild cetacean populations severely affected by human pressure requires extensive knowledge on species distribution, habitat use, and associated threats. In this context, defining the factors that directly influence the local occurrence and distribution of cetaceans is one of the underlying challenges and is essential for their conservation and long‐term survival.
Delphinus delphis sightings data, collected between 2017 and 2021 during 284 standardized vessel‐based surveys, were used to set up a presence–absence distribution model in the eastern Aegean Sea, eastern Mediterranean Sea. Binomial generalized additive models with logit as link function were run using the R package mgcv (restricted maximum likelihood method) and different biogeochemical explanatory variables collected from different sources.
Longitude, latitude, salinity, chlorophyll a, dissolved ammonium, and dissolved phosphate were selected as non‐collinear predictive variables. Through a model validation based on a 10‐fold cross‐validation approach and a random data splitting procedure of 70%/30% (train/test dataset), a model formula has been selected with an explained deviance of 38.10%, an Akaike information criterion value of 1,661.3, and an area under curve of 0.91.
The study confirms that long‐term time series of satellite‐derived data are useful to assess the occurrence and the spatial distribution of D. delphis, suggesting the need for a better understanding of the influence of these environmental factors especially in the framework of climate changes.
Outcomes highlight the need to test further variables and further methods in order to provide increasingly reliable results in view of the conservation measures that must be adopted to stop or reduce the degree of pressure to which these species are subjected.
Subject
Nature and Landscape Conservation,Ecology,Aquatic Science
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