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

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 Ec...

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Main Authors: Beaugrand, Gregory, Lenoir, S., Ibañez, F.
Other Authors: Citadel Hill, the Hoe, Alister Hardy Foundation for Ocean Science, Laboratoire d'océanographie de Villefranche (LOV), Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)
Format: Report
Language:English
Published: HAL CCSD 2011
Subjects:
Online Access:https://hal.science/hal-00757629
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spelling ftinsu:oai:HAL:hal-00757629v1 2024-02-11T10:01:57+01:00 A new model to assess the probability of occurrence of a species based on presence-only data Beaugrand, Gregory Lenoir, S. Ibañez, F. Citadel Hill, the Hoe Alister Hardy Foundation for Ocean Science Laboratoire d'océanographie de Villefranche (LOV) Observatoire océanologique de Villefranche-sur-mer (OOVM) Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS) 2011-03-01 https://hal.science/hal-00757629 en eng HAL CCSD hal-00757629 https://hal.science/hal-00757629 https://hal.science/hal-00757629 2011 info:eu-repo/semantics/preprint Preprints, Working Papers, . 2011 ftinsu 2024-01-24T17:23:22Z 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. Report atlantic cod Barents Sea Subarctic Institut national des sciences de l'Univers: HAL-INSU Barents Sea
institution Open Polar
collection Institut national des sciences de l'Univers: HAL-INSU
op_collection_id ftinsu
language English
description 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.
author2 Citadel Hill, the Hoe
Alister Hardy Foundation for Ocean Science
Laboratoire d'océanographie de Villefranche (LOV)
Observatoire océanologique de Villefranche-sur-mer (OOVM)
Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)
format Report
author Beaugrand, Gregory
Lenoir, S.
Ibañez, F.
spellingShingle Beaugrand, Gregory
Lenoir, S.
Ibañez, F.
A new model to assess the probability of occurrence of a species based on presence-only data
author_facet Beaugrand, Gregory
Lenoir, S.
Ibañez, F.
author_sort Beaugrand, Gregory
title A new model to assess the probability of occurrence of a species based on presence-only data
title_short A new model to assess the probability of occurrence of a species based on presence-only data
title_full A new model to assess the probability of occurrence of a species based on presence-only data
title_fullStr A new model to assess the probability of occurrence of a species based on presence-only data
title_full_unstemmed A new model to assess the probability of occurrence of a species based on presence-only data
title_sort new model to assess the probability of occurrence of a species based on presence-only data
publisher HAL CCSD
publishDate 2011
url https://hal.science/hal-00757629
geographic Barents Sea
geographic_facet Barents Sea
genre atlantic cod
Barents Sea
Subarctic
genre_facet atlantic cod
Barents Sea
Subarctic
op_source https://hal.science/hal-00757629
2011
op_relation hal-00757629
https://hal.science/hal-00757629
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