Not logged in
Data Publisher for Earth & Environmental Science

Tobeña, Marta; Prieto, Rui; Machete, Miguel; Silva, Mónica A (2016): Mapped cetacean habitat suitability and richness in the Azores, links to ArcGIS files. PANGAEA,, Supplement to: Tobeña, M et al. (2016): Modelling the potential distribution and richness of cetaceans in the Azores from Fisheries Observer Program Data. Frontiers in Marine Science, 3, 202-?,

Always quote citation above when using data! You can download the citation in several formats below.

RIS CitationBibTeX CitationShow MapGoogle Earth

Marine spatial planning and ecological research call for high-resolution species distribution data. However, those data are still not available for most marine large vertebrates. The dynamic nature of oceanographic processes and the wide-ranging behavior of many marine vertebrates create further difficulties, as distribution data must incorporate both the spatial and temporal dimensions. Cetaceans play an essential role in structuring and maintaining marine ecosystems and face increasing threats from human activities. The Azores holds a high diversity of cetaceans but the information about spatial and temporal patterns of distribution for this marine megafauna group in the region is still very limited. To tackle this issue, we created monthly predictive cetacean distribution maps for spring and summer months, using data collected by the Azores Fisheries Observer Programme between 2004 and 2009. We then combined the individual predictive maps to obtain species richness maps for the same period. Our results reflect a great heterogeneity in distribution among species and within species among different months. This heterogeneity reflects a contrasting influence of oceanographic processes on the distribution of cetacean species. However, some persistent areas of increased species richness could also be identified from our results. We argue that policies aimed at effectively protecting cetaceans and their habitats must include the principle of dynamic ocean management coupled with other area-based management such as marine spatial planning.
Related to:
Calabrese, Justin M; Certain, Grégoire; Kraan, Casper; Dormann, Carsten F (2014): Stacking species distribution models and adjusting bias by linking them to macroecological models. Global Ecology and Biogeography, 23(1), 99-112,
Dudík, Miroslav; Phillips, Steven J; Schapire, Robert E (2007): Maximum entropy density estimation with generalized regularization and an application to species distribution modeling. Journal of Machine Learning Research, 8, 1217-1260, hdl:10013/epic.48546.d001
Phillips, Steven J; Anderson, Robert P; Schapire, Robert E (2006): Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3-4), 231-259,
Warren, Dan L; Glor, Richard E; Turelli, Michael (2010): ENMTools: a toolbox for comparative studies of environmental niche models. Ecography, 33(3), 607-611,
Median Latitude: 38.325000 * Median Longitude: -28.141500 * South-bound Latitude: 34.425000 * West-bound Longitude: -33.775000 * North-bound Latitude: 42.225000 * East-bound Longitude: -22.508000
Date/Time Start: 2004-01-01T00:00:00 * Date/Time End: 2009-12-31T00:00:00
CetaceanMaxentAzores * Latitude Start: 34.425000 * Longitude Start: -33.775000 * Latitude End: 42.225000 * Longitude End: -22.508000 * Location: Azores * Method/Device: Biological sample (BIOS)
Project(s): TRACE (PTDC/ MAR/74071/2006); MAPCET (M2.1.2/F/012/2011); Horizont 2020 (M2.1.2/I/026/2011); Azorean Fisheries Observer Program (POPA)
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
1ORDINAL NUMBEROrd NoTobeña, MartaGeocode
2TypeTypeTobeña, Marta
3DATE/TIMEDate/TimeTobeña, MartaGeocode – Start
4DATE/TIMEDate/TimeTobeña, MartaGeocode – End
5File contentContentTobeña, Marta
6Analytical methodMethodTobeña, Marta
7File nameFile nameTobeña, Marta
8File formatFile formatTobeña, Marta
9File sizeFile sizekByteTobeña, Martazipped
10Uniform resource locator/link to fileURL fileTobeña, Marta
847 data points

Download Data

Download dataset as tab-delimited text — use the following character encoding:

View dataset as HTML