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Environmental variables influencing occurrence and distribution of Delphinus delphis in the eastern Aegean Sea (eastern Mediterranean Sea)
Ingrosso, M.; Tintoré, B.; Cipriano, G.; Ricci, P.; Grandjean, T.; Tsimpidis, T.; Nomikou, P.; Carlucci, R.; Miliou, A. (2023). Environmental variables influencing occurrence and distribution of Delphinus delphis in the eastern Aegean Sea (eastern Mediterranean Sea). Aquat. Conserv. 34(1). https://dx.doi.org/10.1002/aqc.4031
In: Aquatic Conservation: Marine and Freshwater Ecosystems. Wiley: Chichester; New York . ISSN 1052-7613; e-ISSN 1099-0755, more
Peer reviewed article  

Available in  Authors 

Author keywords
    Aegean Sea; common dolphin; environmental predictors; environmental variables; GAM; spatial distribution

Authors  Top 
  • Ingrosso, M.
  • Tintoré, B.
  • Cipriano, G.
  • Ricci, P.
  • Grandjean, T., more
  • Tsimpidis, T.
  • Nomikou, P.
  • Carlucci, R.
  • Miliou, A.

Abstract
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.

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