[MARMAM] New publication: Comparative cetacean distribution models

solene derville solene.derville at ird.fr
Wed Jun 13 16:08:51 PDT 2018

Dear MARMAM community,

We are pleased to announce the publication of the following article in 
Diversity and Distributions:

*Derville S, Torres LG, Iovan C, Garrigue C. Finding the right fit: 
Comparative cetacean distribution models using multiple data sources and 
statistical approaches. Divers Distrib. 2018;00:1–17. 

*Aim. *Accurate predictions of cetacean distributions are essential to 
their conservation but are limited by statistical challenges and a 
paucity of data. This study aimed at comparing the capacity of various 
statistical algorithms to deal with biases commonly found in 
nonsystematic cetacean surveys and to evaluate the potential for citizen 
science data to improve habitat modelling and predictions. An endangered 
population of humpback whales (Megaptera novaeangliae) in their breeding 
ground was used as a case study.
*Location.* New Caledonia, Oceania.
*Methods. *Five statistical algorithms were used to model the habitat 
preferences of humpback whales from 1,360 sightings collected over 14 
years of nonsystematic research surveys. Three different background 
sampling approaches were tested when developing models from 625 
crowdsourced sightings to assess methods accounting for citizen science 
spatial sampling bias. Model evaluation was conducted through 
cross‐validation and prediction to an independent satellite tracking 
*Results.* Algorithms differed in complexity of the environmental 
relationships modelled, ecological interpretability and transferability. 
While parameter tuning had a great effect on model performances, GLMs 
generally had low predictive performance, SVMs were particularly hard to 
interpret, and BRTs had high descriptive power but showed signs of 
overfitting. MAXENT and especially GAMs provided a valuable complexity 
trade‐off, accurate predictions and were ecologically intelligible. 
Models showed that humpback whales favoured cool (22–23°C) and shallow 
waters (0–100 m deep) in coastal as well as offshore areas. Citizen 
science models converged with research survey models, specifically when 
accounting for spatial sampling bias.
*Main conclusions.* Marine megafauna distribution models present 
specific challenges that may be addressed through integrative 
evaluation, independent testing and appropriately tuned statistical 
algorithms. Specifically, controlling overfitting is a priority when 
predicting cetacean distributions for large‐scale conservation 
perspectives. Citizen science data appear to be a powerful tool to 
describe cetacean habitat.

The paper may be downloaded on 
Feel free to contact me directly for a PDF copy: solene.derville at ird.fr 
<mailto:solene.derville at ird.fr>


Solène Derville
PhD student - Spatial Ecology
UMR Entropie - Institut de Recherche pour le Développement
Université Pierre et Marie Curie
Association Opération Cétacés
101 Promenade Roger Laroque, BPA5
98848 Noumea cedex, New Caledonia
Phone: +687 912299

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