Dear colleagues,

My co-authors and I are pleased to announce our recent publication in
Marine Mammal Science:

Heloise J. Pavanato, Fernando P. Mayer, Leonardo L. Wedekin, Márcia H.
Engel, Paul G. Kinas. 2018. Prediction of humpback whale group densities
along the Brazilian coast using spatial autoregressive models. DOI:

At the breeding grounds of most baleen whales the patchiness and gaps in
spatial distribution results from interactions between behavior patterns and
environmental conditions. We evaluated the influence of environmental factors
(bathymetry and distance from shore with quadratic terms, and wind speed),
effort, and spatial autocorrelation effects to predict humpback whale group
density in the Southwest Atlantic Ocean. Count data of groups by grid cells
were fitted with conditional autoregressive models (CAR). Bayesian inference
was performed via integrated nested Laplace approximation. The best-fit
model contained distance from shore and its quadratic term, bathymetry, and
the autoregressive component. Occupancy probability was high for the Abrolho
s Bank, some cells from the northeast continental shelf and southeast mar
gin, but gaps in occurrence were identified. High densities were estimated
in the east continental margin, with the highest density in the Abrolhos Ban
k, in some cells of the northeast continental margin and in the southernmost
area. We report that intermediate distances from the coast, and shallow
waters were preferred for breeding and calving activities. We suggest that
CAR models may incorporate aggregation mechanisms into habitat modeling and
may provide advances in marine mammal analyses by accounting for residual

The article is available online at
Alternatively, email me to request a pdf copy:

Kind regards,
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