Predicting bottlenose dolphin distribution along Liguria coast (northwestern Mediterranean Sea) through different modeling techniques and indirect predictors

Marini, Chiara; Fossa, Fulvio; Paoli, Chiara; Bellingeri, M.; Gnone, G.; Vassallo, Paolo

doi:10.1016/j.jenvman.2014.11.008

Cited by 43 publications

(34 citation statements)

References 85 publications

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“…This is consistent with the species' general distribution in the Mediterranean Sea (e.g. Gnone et al, ; Marini et al, ), where shallow water preference of the bottlenose dolphin could be related to its feeding habits of preying mostly on benthic and demersal fish (e.g. Blanco, Salomon, & Raga, ; Orsi Relini, Cappello, & Poggi, ).…”

Section: Discussionsupporting

confidence: 86%

An integrated approach for cetacean knowledge and conservation in the central Mediterranean Sea using research and social media data sources

Pace

Giacomini

Campana

et al. 2019

Aquatic Conservation

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Sources of data other than those derived from conventional research protocols may contribute valuable information to fill gaps in knowledge about cetacean occurrences and diversity in a given area and help address conservation issues. The performance of a method to examine cetacean communities based on presence records systematically derived from shared photographs and videos posted by boaters and maritime operators on social media (e.g. YouTube and Facebook) combined with patchy distributed visual/acoustic data collected by researchers has been evaluated. Records (N = 1,274) gathered over a 10‐year period (2008–2017) have been used to obtain insights into species' presence and habitat selection in a scattered study area of the central Mediterranean Sea (Italy). The effectiveness of the method, practical and theoretical advantages, limitations, and challenges of using data originated from social media for research and conservation purposes are discussed. Seven out of the eight cetacean species regularly residing in the Mediterranean have been reported in the area, with different relative densities. Maximum entropy modelling techniques have been applied to the datasets derived from (a) social media, (b) research surveys, and (c) the combination of the two, using six fixed variables as proxies for cetacean presence. Distance from the coast and depth emerged as the main variables predicting encounters, with specificities related to the ecology of the species. The approach was reliable enough to obtain broad‐scale, baseline information on cetacean communities in the region, on the basis of which initial conservation recommendations and future research programmes can be proposed. With the increasing need for studying whale and dolphin population ecology coming from national/international directives, support from citizens to aid research may act as a practical, inexpensive solution to gathering extensive spatial–temporal data for regional‐scale monitoring and for the development of management priorities.

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Section: Discussionsupporting

confidence: 86%

An integrated approach for cetacean knowledge and conservation in the central Mediterranean Sea using research and social media data sources

Pace

Giacomini

Campana

et al. 2019

Aquatic Conservation

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“…Recurrent samplings may reduce this uncertainty, but the separation of 'true' absences, where animals are actually absent, from 'false' absences, where animals are present but not detected, is difficult and leads to uncertainty when interpreting results (Hall, 2000;Martin et al, 2005). Statistical adjustments to face this intrinsic uncertainty have been developed, and to this aim, in this study, we applied a correction already proposed in recent applications (Azzellino et al, 2012;Fiori et al, 2014;Marini et al, 2015;Carlucci et al, 2016) consisting of the selection of random sets of cells where absence was recorded equal to the number of presence cells.…”

Section: Model Developmentmentioning

confidence: 99%

“…In the last few decades, the advances in regression analyses have allowed the development of more and more reliable ecological models, increasing understanding of ecological systems (Guisan et al, 2002). More recently, regression based on the random forest technique (Breiman, 2001) was applied and compared to other regression techniques and proved to be more reliable and accurate in predicting habitat distribution (Cutler et al, 2007;Virkkala et al, 2010;Marini et al, 2015;Carlucci et al, 2016). In particular, recent developments in spatial modeling have made it possible to predict the presence/absence or the abundance of a species by means of a set of predictor variables, highlighting the relative importance of habitats (Baumgartner, 1997;Phillips et al, 2006;Pitchford et al, 2015;Redfern et al, 2006;Thorne et al, 2012;Carlucci et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Seamounts as hot-spots of large pelagic aggregations

Vassallo

Paoli²,

Alessi³

et al. 2018

Medit. Mar. Sci.

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The distribution of four top predators in the Tyrrhenian Sea, a sub-basin of the Mediterranean Sea, was investigated by means of random forest regression considering depth, distance from the coast, seafloor slope, and distance from seamounts as habitat descriptors on a 2x2-nautical mile regular grid. RF results are processed to estimate variable importance and model performance. Random forest architecture reached optimal sensitivity and specificity, thus providing a consistent support tool for identifying suitable habitats. The considered species are characterized as having patched suitable habitats with a number of hot-spot areas where the different species' habitats overlap. These hot-spot areas' locations correspond to those of specific seamounts identifying the attraction effect of these topographic structures. The mean features typifying the most attractive seamounts are investigated and found to be shallow peak and base depths but wide base area and high relative elevation.

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“…These techniques represent a promising tool for predicting cetacean distributions and understanding the ecological processes that determine these distributions (Redfern et al ., ). The application of such statistical models to understand and predict relationships between species and environmental variables has become frequent for many marine species in the last two decades (Guisan and Zimmermann, ; Redfern et al ., ; Giannoulaki et al ., , 2013), while habitat modelling for marine mammals has made considerable advances in the last decade (Redfern et al ., ; De Segura et al ., ; Azzellino et al ., ; Best et al ., ; Blasi and Boitani ; Druon et al ., ; Keller et al ., ; Thorne et al ., ; Marini et al ., ).…”

Section: Introductionmentioning

confidence: 97%

“…In addition, the collection of marine mammals' occurrence data is hampered by the elusiveness and mobility of these animals (Kaschner et al ., ). As a result, dolphins' habitat modelling studies in the Mediterranean Sea have been concentrated in Italian (Northern Adriatic: Bearzi et al ., ; Simeoni, ; Tyrrhenian Sea: Blasi and Boitani ; Ligurian Sea: Azzellino et al ., ; Marini et al ., ) and Spanish (Cañadas et al ., ; Cañadas and Hammond, ; Druon et al ., ) waters using environmental related variables only. Relating cetaceans' distribution to their prey can significantly improve modelling (Hastie et al ., ; Pendleton et al ., ; Lambert et al ., ; Hazen et al , ; Scales et al , ) but it demands the availability of prey information at a suitable spatial scale which is generally scarce or not always available (Torres et al ., ).…”

Section: Introductionmentioning

confidence: 99%

Linking small pelagic fish and cetacean distribution to model suitable habitat for coastal dolphin species, Delphinus delphis and Tursiops truncatus, in the Greek Seas (Eastern Mediterranean)

Giannoulaki

Markoglou

Valavanis

et al. 2016

Aquatic Conservation

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1. A large-scale assessment of the summertime suitable habitat for Delphinus delphis (short-beaked common dolphin) and Tursiops truncatus (common bottlenose dolphin) in Greek Seas (Eastern Mediterranean) was conducted using data from dedicated and opportunistic cetacean surveys and published data records.2. Using a presence/absence approach, generalized additive models were applied to define a suite of environmental, bathymetric and biotic factors that best describe common and bottlenose dolphin spatial distribution, during early (May, June, July) and late (August, September) summer.3. A geographic information system (GIS) was used to integrate sightings data with environmental characteristics, distance from the coast and sardine probability of presence. These variables were considered as good proxies for defining species-suitable habitat within the study area's coastal environment.4. The final selected models were used to produce annual probability maps of the presence of the species in the entire Greek Seas, as a measure of habitat suitability. Based on the mean probability and standard deviation maps for the study period GIS techniques were subsequently used to determine the persistent (areas with high mean and low variation) and occasional (high mean and high variation) habitat of each species.5. Results showed that there was a high probability of common dolphin presence in areas with a high probability of sardine presence. For bottlenose dolphin, higher probability of the presence of species occurred in areas closer to the shore, with a high probability of sardine presence and with high concentrations of chlorophyll-a.6. In both seasons, the North Aegean Sea and the Inner Ionian Sea Archipelago were indicated as the most suitable areas for common dolphin distribution. Persistent habitat areas of the bottlenose dolphin included enclosed seas, continental shelf waters, and waters surrounding islands. The indicated suitable areas are discussed along with deficiencies of the models and future implications for conservation.

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Predicting bottlenose dolphin distribution along Liguria coast (northwestern Mediterranean Sea) through different modeling techniques and indirect predictors

Cited by 43 publications

References 85 publications

An integrated approach for cetacean knowledge and conservation in the central Mediterranean Sea using research and social media data sources

An integrated approach for cetacean knowledge and conservation in the central Mediterranean Sea using research and social media data sources

Seamounts as hot-spots of large pelagic aggregations

Linking small pelagic fish and cetacean distribution to model suitable habitat for coastal dolphin species, Delphinus delphis and Tursiops truncatus, in the Greek Seas (Eastern Mediterranean)

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