Ecological Niche Modeling of Three Species of Stenella Dolphins in the Caribbean Basin, With Application to the Seaflower Biosphere Reserve

Abstract

Dolphins of the genus Stenella occur in pelagic waters of both tropical and warmtemperate oceans. Three species, the Atlantic spotted dolphin (Stenella frontalis), the pantropical spotted dolphin (S. attenuata), and the spinner dolphin (S. longirostris) are abundant worldwide, but in the Caribbean Basin they have been poorly studied and information on their distribution patterns is scarce. Specifically, in Colombia's remote Seaflower Biosphere Reserve (SFBR) S. attenuata has been reported occasionally, but S. frontalis and S. longirostris have never been recorded before. To address this information gap, an ecological niche modeling approach was used to determine the potential distribution patterns of these three dolphin species in the region. Records of these species for the Caribbean Basin were compiled, including both published and unpublished data. Environmental information, including bathymetry, bathymetric slope, distance to shore, sea surface temperature, sea surface salinity, and chlorophylla concentration was gathered from public databases (MARSPEC and Bio-ORACLE) in raster format. The maximum entropy algorithm (Maxent) for modeling species' geographic distributions with presence-only data was used. After filtering the data, 210 records of S. attenuata, 204 of S. frontalis, and 80 of S. longirostris were used to run models. The best configuration for each model was chosen based on the AICc criterion. For all three species, the final ecological niche models returned AUC

Genetic Diversity and Demographic Connectivity of Atlantic Green Sea Turtles at Foraging Grounds in Northeastern Colombia, Caribbean Sea

“…From July to December, there is no upwelling because the direction of the trade winds changes and the rain falls, so this period is coined the "wet season" (Invemar and Corpoguajira, 2012). Due to this coastal upwelling, variation in nutrient supply and thus in productivity may affect foraging sources and their availability for juvenile turtles (Arévalo-Martínez and Franco-Herrera, 2008;Paramo et al, 2011), as has been reported for other marine vertebrates such as dolphins (e.g., Farías-Curtidor et al, 2017;Barragán-Barrera et al, 2019). C. mydas feeds on seagrasses and marine macroalgae primarily but also on small marine invertebrates (Bjorndal, 1980;Mortimer, 1981;Seminoff et al, 2002;Makowski et al, 2006;Amorocho and Reina, 2007;Shimada et al, 2014).…”

“…The high connectivity and diversity of C. mydas found in the northern portion of Colombia points to its relevance as a transit feeding area for multiple populations (Arthur et al, 2008). Indeed, previous studies have suggested La Guajira as an important transit area for other marine vertebrates in the Caribbean Sea, like dolphins (Farías-Curtidor et al, 2017;Barragán-Barrera et al, 2019). The dispersal mechanisms by which multiple C. mydas populations can contribute to the observed mixed stock diversity in Colombia are unknown.…”

Cetaceans along the southeastern Brazilian coast: occurrence, distribution and niche inference at local scale

“…The differences in the distribution patterns among Stenella species have been related not only to oceanographic conditions ( do Amaral et al., 2015 ), but also to prey distribution and feeding preferences ( Davis et al., 2005 ). However, in the Caribbean, dolphins of the genus Stenella did not show the same levels of niche partitioning, probably due to the low productivity levels in the Caribbean Sea ( Barragán-Barrera et al, 2019 ).…”

Potential distribution model of Leontochir ovallei using remote sensing data

“…Its distribution is associated with arid environments with scarce and unpredictable precipitation throughout the year (Muñoz, 1973). However, years with higher rainfall during the winter promote the productivity and development of this and other plant species in an event known as "desert bloom" (Errázuriz and Hanisch, 1995;Chávez et al, 2019). This species is classified as endangered (MINSEGPRES, 2008), which is partially due to its narrow distribution (Cereceda, et al, 2000).…”

“…Research suggests that predictions derived from habitat suitability cartography for narrow distribution species is a useful tool for understanding the contribution of different environmental factors to the spatial distribution of species (Franklin, 2010;Urbina-Cardona and Flores-Villela, 2010;Marini et al, 2010;Morales, 2012;Hawk, 2017;Tang et al, 2018;Thapa et al, 2018;Barragán-Barrera et al, 2019;Sarma et al, 2018;Giannakopoulos et al, 2019). Consequently, Wang et al (2012) recommend using predictive models to evaluate the distribution pattern of species with scarce available data.…”