Geostatistical modelling of spatial distribution of balaenoptera physalus in the Northwestern Mediterranean Sea from sparse count data and heterogeneous observation efforts

International audience Obtaining accurate maps of relative abundance is an objective that may be difficult to achieve on the basis of spatially heterogeneous observation efforts and infrequent and sparse animal sightings. However, characterizing spatial distribution of wild animals such as fin whale...

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Published in:Ecological Modelling
Main Authors: Monestiez, Pascal, Dubroca, Laurent, Bonnin, E., Durbec, J.P., Guinet, Christophe
Other Authors: Unité de biométrie et intelligence artificielle de Jouy (MIA-JOUY), Institut National de la Recherche Agronomique (INRA), Centre d'océanologie de Marseille (COM), Université de la Méditerranée - Aix-Marseille 2-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre d'Études Biologiques de Chizé (CEBC), Centre National de la Recherche Scientifique (CNRS)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2006
Subjects:
Online Access:https://hal.science/hal-00184618
https://doi.org/10.1016/j.ecolmodel.2005.08.042
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spelling ftunivaixmarseil:oai:HAL:hal-00184618v1 2024-02-11T10:02:21+01:00 Geostatistical modelling of spatial distribution of balaenoptera physalus in the Northwestern Mediterranean Sea from sparse count data and heterogeneous observation efforts Monestiez, Pascal Dubroca, Laurent Bonnin, E. Durbec, J.P. Guinet, Christophe Unité de biométrie et intelligence artificielle de Jouy (MIA-JOUY) Institut National de la Recherche Agronomique (INRA) Centre d'océanologie de Marseille (COM) Université de la Méditerranée - Aix-Marseille 2-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS) Centre d'Études Biologiques de Chizé (CEBC) Centre National de la Recherche Scientifique (CNRS) 2006-01 https://hal.science/hal-00184618 https://doi.org/10.1016/j.ecolmodel.2005.08.042 en eng HAL CCSD Elsevier info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecolmodel.2005.08.042 hal-00184618 https://hal.science/hal-00184618 doi:10.1016/j.ecolmodel.2005.08.042 ISSN: 0304-3800 EISSN: 1872-7026 Ecological Modelling https://hal.science/hal-00184618 Ecological Modelling, 2006, 193, pp.615-628. ⟨10.1016/j.ecolmodel.2005.08.042⟩ Relative abundance map Fin whale Sightings data Geostatistics Kriging Variogram estimation Poisson distribution Bias correction [SDE.BE]Environmental Sciences/Biodiversity and Ecology [SDE.ES]Environmental Sciences/Environment and Society info:eu-repo/semantics/article Journal articles 2006 ftunivaixmarseil https://doi.org/10.1016/j.ecolmodel.2005.08.042 2024-01-23T23:42:40Z International audience Obtaining accurate maps of relative abundance is an objective that may be difficult to achieve on the basis of spatially heterogeneous observation efforts and infrequent and sparse animal sightings. However, characterizing spatial distribution of wild animals such as fin whales is a major priority to protect these populations and to study their interactions with their environment.We have associated a geostatistical model with the Poisson distribution to model both spatial variation and discrete observation process. Assuming few weak hypotheses on the distribution of abundance, we have improved the experimental variogram estimate using weights that are derived from expected variances and proposed a bias correction that accounts for the variability added by the Poisson observation process. In the same way the kriging system was modified to interpolate directly the theoretical underlying animal abundance better than noisy observations from count data. For cumulative count data of fin whales over the summers 1993–2001, the method gave a map of the relative abundance which is informative on the spatial patterns. Kriging interpolation variances were dramatically reduced – ratio from 0.015 to 0.26 – compared to usual Ordinary Kriging on raw data. Adding the hypothesis of stationarity over time the variogram estimated on cumulative data can be then used with more sparser annual data. Article in Journal/Newspaper Balaenoptera physalus Fin whale Aix-Marseille Université: HAL Ecological Modelling 193 3-4 615 628
institution Open Polar
collection Aix-Marseille Université: HAL
op_collection_id ftunivaixmarseil
language English
topic Relative abundance map
Fin whale
Sightings data
Geostatistics
Kriging
Variogram estimation
Poisson distribution
Bias correction
[SDE.BE]Environmental Sciences/Biodiversity and Ecology
[SDE.ES]Environmental Sciences/Environment and Society
spellingShingle Relative abundance map
Fin whale
Sightings data
Geostatistics
Kriging
Variogram estimation
Poisson distribution
Bias correction
[SDE.BE]Environmental Sciences/Biodiversity and Ecology
[SDE.ES]Environmental Sciences/Environment and Society
Monestiez, Pascal
Dubroca, Laurent
Bonnin, E.
Durbec, J.P.
Guinet, Christophe
Geostatistical modelling of spatial distribution of balaenoptera physalus in the Northwestern Mediterranean Sea from sparse count data and heterogeneous observation efforts
topic_facet Relative abundance map
Fin whale
Sightings data
Geostatistics
Kriging
Variogram estimation
Poisson distribution
Bias correction
[SDE.BE]Environmental Sciences/Biodiversity and Ecology
[SDE.ES]Environmental Sciences/Environment and Society
description International audience Obtaining accurate maps of relative abundance is an objective that may be difficult to achieve on the basis of spatially heterogeneous observation efforts and infrequent and sparse animal sightings. However, characterizing spatial distribution of wild animals such as fin whales is a major priority to protect these populations and to study their interactions with their environment.We have associated a geostatistical model with the Poisson distribution to model both spatial variation and discrete observation process. Assuming few weak hypotheses on the distribution of abundance, we have improved the experimental variogram estimate using weights that are derived from expected variances and proposed a bias correction that accounts for the variability added by the Poisson observation process. In the same way the kriging system was modified to interpolate directly the theoretical underlying animal abundance better than noisy observations from count data. For cumulative count data of fin whales over the summers 1993–2001, the method gave a map of the relative abundance which is informative on the spatial patterns. Kriging interpolation variances were dramatically reduced – ratio from 0.015 to 0.26 – compared to usual Ordinary Kriging on raw data. Adding the hypothesis of stationarity over time the variogram estimated on cumulative data can be then used with more sparser annual data.
author2 Unité de biométrie et intelligence artificielle de Jouy (MIA-JOUY)
Institut National de la Recherche Agronomique (INRA)
Centre d'océanologie de Marseille (COM)
Université de la Méditerranée - Aix-Marseille 2-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)
Centre d'Études Biologiques de Chizé (CEBC)
Centre National de la Recherche Scientifique (CNRS)
format Article in Journal/Newspaper
author Monestiez, Pascal
Dubroca, Laurent
Bonnin, E.
Durbec, J.P.
Guinet, Christophe
author_facet Monestiez, Pascal
Dubroca, Laurent
Bonnin, E.
Durbec, J.P.
Guinet, Christophe
author_sort Monestiez, Pascal
title Geostatistical modelling of spatial distribution of balaenoptera physalus in the Northwestern Mediterranean Sea from sparse count data and heterogeneous observation efforts
title_short Geostatistical modelling of spatial distribution of balaenoptera physalus in the Northwestern Mediterranean Sea from sparse count data and heterogeneous observation efforts
title_full Geostatistical modelling of spatial distribution of balaenoptera physalus in the Northwestern Mediterranean Sea from sparse count data and heterogeneous observation efforts
title_fullStr Geostatistical modelling of spatial distribution of balaenoptera physalus in the Northwestern Mediterranean Sea from sparse count data and heterogeneous observation efforts
title_full_unstemmed Geostatistical modelling of spatial distribution of balaenoptera physalus in the Northwestern Mediterranean Sea from sparse count data and heterogeneous observation efforts
title_sort geostatistical modelling of spatial distribution of balaenoptera physalus in the northwestern mediterranean sea from sparse count data and heterogeneous observation efforts
publisher HAL CCSD
publishDate 2006
url https://hal.science/hal-00184618
https://doi.org/10.1016/j.ecolmodel.2005.08.042
genre Balaenoptera physalus
Fin whale
genre_facet Balaenoptera physalus
Fin whale
op_source ISSN: 0304-3800
EISSN: 1872-7026
Ecological Modelling
https://hal.science/hal-00184618
Ecological Modelling, 2006, 193, pp.615-628. ⟨10.1016/j.ecolmodel.2005.08.042⟩
op_relation info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecolmodel.2005.08.042
hal-00184618
https://hal.science/hal-00184618
doi:10.1016/j.ecolmodel.2005.08.042
op_doi https://doi.org/10.1016/j.ecolmodel.2005.08.042
container_title Ecological Modelling
container_volume 193
container_issue 3-4
container_start_page 615
op_container_end_page 628
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