A new model to assess the probability of occurrence of a species, based on presence-only data

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Authors G Beaugrand, S Lenoir, F Ibañez, C Manté
Journal/Conference Name Marine Ecology
Paper Category
Paper Abstract This study aims to describe a new nonparametric ecological niche model for the analysis of presence-only data, which we use to map the spatial distribution of Atlantic cod and to project the potential impact of climate change on this species. The new model, called the Non-Parametric Probabilistic Ecological Niche (NPPEN) model, is derived from a test recently applied to compare the ecological niche of 2 different species. The analysis is based on a simplification of the Multiple Response Permutation Procedures (MRPP) using the Generalised Mahalanobis distance. For the first time, we propose to test the generalized Mahalanobis distance by a non-parametric procedure, thus avoiding the arbitrary selection of quantile classes to allow the direct estimation of the probability of occurrence of a species. The model NPPEN was applied to model the ecological niche (sensu Hutchinson) of Atlantic cod and therefore its spatial distribution. The modelled niche exhibited high probabilities of occurrence at bathymetry ranging from 0 to 500 m (mode from 100 to 300 m), at annual sea surface temperature of from –1 to 14°C (mode from 4 to 8°C) and at annual sea surface salinity ranging from 0 to 36 (mode from 25 to 34). This made the species a good indicator of the subarctic province. Current climate change is having a strong effect on North Sea cod and may have also reinforced the negative impact of fishing on stocks located offshore of North America. The model shows a pronounced effect of present-day climate change on the spatial distribution of Atlantic cod. Projections for the coming decades suggest that cod may eventually disappear as a commercial species from regions where a sustained decrease or collapse has already been documented. In contrast, the abundance of cod is likely to increase in the Barents Sea.
Date of publication 2010
Code Programming Language R

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