Distribution and habitat modelling of common dolphins (Delphinus delphis) in the eastern North Atlantic

Abstract

The eastern North Atlantic (ENA) has many highly productive areas where several species of cetaceans have been recorded, with the common dolphin (Delphinus delphis) being one of the most frequently sighted species. However, its spatial and temporal distribution in high seas is poorly known. The study presents the results from 5 years of cetacean monitoring in the ENA (2012–2016) aboard cargo ships that follow the routes from Continental Portugal to the Macaronesian archipelagos and north-west Africa. Common dolphin was the most frequently sighted cetacean with 192 occurrences registered on effort and an overall encounter rate of 0.36 sightings/100 nmi. The species was distributed in coastal and offshore waters, but absent from the Canaries and Cape Verde islands. Statistical ‘habitat’ models were developed to describe and explain the occurrence of sightings of the species: variables affecting detection of dolphins had a small impact and there were clear spatiotemporal distribution patterns, influenced to some degree by environmental variables. Predicted probability of occurrence was highest in coastal waters of continental Portugal and around the Azores. The models, combined with maps of distribution, were useful to identify important areas for the species, which could be the focus of future conservation efforts. Common dolphin presence was related to depth, distance to coast and seamounts, seabed slope, chlorophyll concentration, sea-surface temperature and sea level anomalies; the possible ecological significance of these relationships is explored.

Distribution of cetacean species at a large scale ‐ Connecting continents with the Macaronesian archipelagos in the eastern North Atlantic

“…Previous analysis using the CETUS dataset from 2012 to 2016 showed that the species presents clear core areas of occurrence, related to specific environmental conditions (e.g. coastal colder waters related to strong coastal upwelling systems) (Correia, Gil, et al, 2019). Within its range in the ENA, the northern Continental Portugal remains a poorly studied area.…”

Predicting Cetacean Distributions in the Eastern North Atlantic to Support Marine Management

“…Previous work with CETUS dataset (Correia et al, 2019b) prove that it is important to include detectability factors (sea state, wind state and visibility) in the modelling process and the combination of detectability, spatiotemporal and environmental predictors has been previously applied (and recommended) for cetacean ecological niche models (e.g., Díaz Lopez andMethion, 2017, Díaz López andMethion, 2018;Correia et al, 2019b).…”

“…For GAMs, we chose a presence/pseudo-absence approach based on used/available habitat (Pearce and Boyce, 2006;Elith and Leathwick, 2009;Correia et al, 2015Correia et al, , 2019b, with used (cetacean occurrence) and available (survey route) habitat points combined to generate a binary (1,0) response variable. We fitted binomial GAMs (with link: logit) to these response variables, allowing a maximum of four splines (k = 4) to limit the complexity of smoothers describing the effects of explanatory variables.…”

“…We fitted binomial GAMs (with link: logit) to these response variables, allowing a maximum of four splines (k = 4) to limit the complexity of smoothers describing the effects of explanatory variables. The set of available points was generated as in Correia et al (2015Correia et al ( , 2019b, by creating equidistant points (every 5 km) along all on-effort transects. This guarantees an appropriate number of pseudo-absences representative of the environmental space (Barbet-Massin et al, 2012;Virgili et al, 2017).…”

“…Sampling protocols and techniques used in data processing and analysis have been refined. Data collected from OPOs are now frequently used to conduct ecological niche modelling in order to assess cetacean distribution and understand its relationship with habitat characteristics (e.g., Correia et al, 2015Correia et al, , 2019bBreen et al, 2017;Redfern et al, 2017;Derville et al, 2018;Fernandez et al, 2018;Fiedler et al, 2018;García et al, 2018;Passadore et al, 2018;Barragán-Barrera et al, 2019;García-Barón et al, 2019;Valente et al, 2019). Results from such models have been successfully applied in the definition of monitoring plans, management strategies and creation of Marine Protected Areas (MPAs) (Passadore et al, 2018;García-Barón et al, 2019).…”