[MARMAM] New publication on modelling of Cuvier's beaked whles in the whole Mediterranean sea

Alnilam.Info anacanadas at alnilam.info
Thu Nov 9 06:53:51 PST 2017

Dear Marmam community,


My co-authors and I are pleased to announce our recent publication in
Ecological Indicators:


Cañadas, A., Aguilar de Soto, N., Aissi, M, Arcangeli, A., Azzolin, M.,
B-Nagy, A., Bearzi, G., Campana, I., Chicote, C., Cotte, C., Crosti, R., Di
Natale, A., Fortuna, C., Frantzis, A., Garcia, P., Gazo, M.,
Gutierrez-Xarxa, R., Holcer, D., Laran, S., Lauriano, G., Lewis, T.,
Moulins, A., Mussi, B., Notarbartolo di Sciara, G., Panigada, S., Pastor,
X., Politi, E., Pulcini, M., Raga, J.A., Rendell, L., Rosso, M., Tepsich,
P., Tomás, J., Tringali, M. 2017. The challenge of habitat modelling for
threatened low density species using heterogeneous data: the case of
Cuvier’s beaked whales in the Mediterranean. Ecological Indicators, Volume
85, February 2018, Pages 128-136, ISSN 1470-160X,



The Mediterranean population of Cuvier´s beaked whale (Ziphius cavirostris),
a deep-diving cetacean, is genetically distinct from the Atlantic, and
subject to a number of conservation threats, in particular underwater noise.
It is also cryptic at the surface and relatively rare, so obtain robust
knowledge on distribution and abundance presents unique challenges. Here we
use multiplatform and multiyear survey data to analyse the distribution and
abundance of this species across the Mediterranean Sea. We use a novel
approach combining heterogeneous data gathered with different methods to
obtain a single density index for the region. A total of 594,996 km of
survey effort and 507 sightings of Cuvier’s beaked whales, from 1990 to
2016, were pooled together from 24 different sources. Data were divided into
twelve major groups according to platform height, speed and sea state. Both
availability bias and effective strip width were calculated from the
sightings with available perpendicular distance data. This was extrapolated
to the rest of the sightings for each of the twelve groups. Habitat
preference models were fitted into a GAM framework using counts of groups as
a response variable with the effective searched area as an offset. Depth,
coefficient of variation of depth, longitude and marine regions (as defined
by the International Hydrographic Organization) were identified as important
predictors. Predicted abundance of groups per grid cell were multiplied by
mean group size to obtain a prediction of the abundance of animals. A total
abundance of 5799 (CV=24.0%) animals was estimated for the whole
Mediterranean basin. The Alborán Sea, Ligurian Sea, Hellenic Trench,
southern Adriatic Sea and eastern Ionian Sea were identified as being the
main hot spots in the region. It is important to urge that the relevant
stakeholders incorporate this information in the planning and execution of
high risk activities in these high-risk areas.


With regards

Ana Cañadas

anacanadas at alnilam.info



Alnilam Investigacion y Conservacion

Alnilam Research and Conservation

Pradillos 29, Navacerrada

28491 Madrid, SPain




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