[OANNES Foro] Predicting cetacean distributions in data-poor marine ecosystems

[Mario Cabrejos]

Diversity and Distributions

.         First published: 3 February 2017 

.         DOI: 10.1111/ddi.12537 


 


Predicting cetacean distributions in data-poor marine ecosystems


.         Jessica V. Redfern, Thomas J. Moore, Paul C. Fiedler, Asha de Vos,
Robert L. Brownell Jr, Karin A. Forney, Elizabeth A. Becker, Lisa T.
Ballance


.          


Abstract


Aim


Human activities are creating conservation challenges for cetaceans.
Spatially explicit risk assessments can be used to address these challenges,
but require species distribution data, which are limited for many cetacean
species. This study explores methods to overcome this limitation. Blue
whales (Balaenoptera musculus) are used as a case study because they are an
example of a species that have well-defined habitat and are subject to
anthropogenic threats.

 


Location


Eastern Pacific Ocean, including the California Current (CC) and eastern
tropical Pacific (ETP), and northern Indian Ocean (NIO).

 


Methods


We used 12 years of survey data (377 blue whale sightings and c. 225,400 km
of effort) collected in the CC and ETP to assess the transferability of blue
whale habitat models. We used the models built with CC and ETP data to
create predictions of blue whale distributions in the data-poor NIO because
key aspects of blue whale ecology are expected to be similar in these
ecosystems.

 


Results


We found that the ecosystem-specific blue whale models performed well in
their respective ecosystems, but were not transferable. For example, models
built with CC data could accurately predict distributions in the CC, but
could not accurately predict distributions in the ETP. However, the accuracy
of models built with combined CC and ETP data was similar to the accuracy of
the ecosystem-specific models in both ecosystems. Our predictions of blue
whale habitat in the NIO from the models built with combined CC and ETP data
compare favourably to hypotheses about NIO blue whale distributions, provide
new insights into blue whale habitat, and can be used to prioritize research
and monitoring efforts.

 


Main conclusions


Predicting cetacean distributions in data-poor ecosystems using habitat
models built with data from multiple ecosystems is potentially a powerful
marine conservation tool and should be examined for other species and
regions.

 



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