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Soil nutritional factors improve models of plant species distribution: an illustration with Acer campestre (L.) in France
To estimate the relative importance of climate and soil nutritional variables for predicting the distribution of Acer campestre (L.) in French forests. France. We used presence/absence information for A. campestre in 3286 forest plots scattered all over France, coupled with climatic and edaphic data...
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Published in: | Journal of biogeography 2006-10, Vol.33 (10), p.1750-1763 |
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creator | Coudun, Christophe Gégout, Jean-Claude Piedallu, Christian Rameau, Jean-Claude |
description | To estimate the relative importance of climate and soil nutritional variables for predicting the distribution of Acer campestre (L.) in French forests. France. We used presence/absence information for A. campestre in 3286 forest plots scattered all over France, coupled with climatic and edaphic data. More than 150 climatic variables (temperature, precipitation, solar radiation, evapotranspiration, water balance) were obtained using a digital elevation model (DEM) and a geographical information system (GIS). Six direct soil variables (pH, C/N ratio, base saturation rate, concentrations of calcium, magnesium and potassium) were available from EcoPlant, a phytoecological data base for French forests. Using a forward stepwise logistic regression technique, we derived two distinct predictive models for A. campestre; the first with climatic variables alone and the second with both climatic and edaphic variables. The distribution of A. campestre was poorly modelled when including only climatic variables. The inclusion of edaphic variables significantly improved the quality of predictions for this species, allowing prediction of patches of presence/absence within the study region. Soil nutritional variables may improve the performance of fine-scale (grain) plant species distribution models. |
doi_str_mv | 10.1111/j.1365-2699.2005.01443.x |
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France. We used presence/absence information for A. campestre in 3286 forest plots scattered all over France, coupled with climatic and edaphic data. More than 150 climatic variables (temperature, precipitation, solar radiation, evapotranspiration, water balance) were obtained using a digital elevation model (DEM) and a geographical information system (GIS). Six direct soil variables (pH, C/N ratio, base saturation rate, concentrations of calcium, magnesium and potassium) were available from EcoPlant, a phytoecological data base for French forests. Using a forward stepwise logistic regression technique, we derived two distinct predictive models for A. campestre; the first with climatic variables alone and the second with both climatic and edaphic variables. The distribution of A. campestre was poorly modelled when including only climatic variables. The inclusion of edaphic variables significantly improved the quality of predictions for this species, allowing prediction of patches of presence/absence within the study region. 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France. We used presence/absence information for A. campestre in 3286 forest plots scattered all over France, coupled with climatic and edaphic data. More than 150 climatic variables (temperature, precipitation, solar radiation, evapotranspiration, water balance) were obtained using a digital elevation model (DEM) and a geographical information system (GIS). Six direct soil variables (pH, C/N ratio, base saturation rate, concentrations of calcium, magnesium and potassium) were available from EcoPlant, a phytoecological data base for French forests. Using a forward stepwise logistic regression technique, we derived two distinct predictive models for A. campestre; the first with climatic variables alone and the second with both climatic and edaphic variables. The distribution of A. campestre was poorly modelled when including only climatic variables. The inclusion of edaphic variables significantly improved the quality of predictions for this species, allowing prediction of patches of presence/absence within the study region. Soil nutritional variables may improve the performance of fine-scale (grain) plant species distribution models.</description><subject>Biogeography</subject><subject>Climate models</subject><subject>Climatic variables</subject><subject>Ecological modeling</subject><subject>EcoPlant</subject><subject>Edaphic factors</subject><subject>Forest ecology</subject><subject>Forest soils</subject><subject>Life Sciences</subject><subject>logistic regression</subject><subject>logit analysis</subject><subject>Modeling</subject><subject>Plants</subject><subject>soil nutritional variables</subject><subject>spatial autocorrelation</subject><subject>Species</subject><subject>species distribution modelling</subject><subject>Vegetation</subject><issn>0305-0270</issn><issn>1365-2699</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><recordid>eNqNkEFv0zAYhi0EEmXwD5DwkR0SPtuxnSBxKBNbxwocxrSj5ToOc3HjyE639t_jENQzvth63_fx4UEIEyhJPh-2JWGCF1Q0TUkBeAmkqlh5eIYWp-I5WgADXgCV8BK9SmkLAA1n1QIdb4PzuN-P0Y0u9NrjTpsxxITdbojh0eJdaK1POHR48LofcRqscTbh1qUMbfYT9hHrHjvv9znSU4Cf3PiAl8ZGbPRusDm3-P26PMeux5dR98a-Ri867ZN98-8-Q3eXX35erIr1j6vri-W6MBUDVnBTQdXKjdCcSMHEppU1t53pWm5oBXUtW0YszY-GCtNuNDeys9wKTblgumFn6Hz-90F7NUS30_GognZqtVyrKQMqhJSsfiR5W89bE0NK0XYngICadKutmqyqyaqadKu_utUho59m9Ml5e_xvTn39fD29Mv925rcp6z_xrGY1J1Wui7nO1u3hVOv4WwnJJFf336-UuPl2T9jqRvG8fzfvOx2U_hVdUne3FAgDqClnvGF_AO8jqHE</recordid><startdate>200610</startdate><enddate>200610</enddate><creator>Coudun, Christophe</creator><creator>Gégout, Jean-Claude</creator><creator>Piedallu, Christian</creator><creator>Rameau, Jean-Claude</creator><general>Oxford, UK : Blackwell Publishing Ltd</general><general>Blackwell Publishing Ltd</general><general>Blackwell Publishing</general><general>Wiley</general><scope>FBQ</scope><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>1XC</scope><orcidid>https://orcid.org/0000-0002-5760-9920</orcidid><orcidid>https://orcid.org/0000-0001-7316-1874</orcidid></search><sort><creationdate>200610</creationdate><title>Soil nutritional factors improve models of plant species distribution: an illustration with Acer campestre (L.) in France</title><author>Coudun, Christophe ; Gégout, Jean-Claude ; Piedallu, Christian ; Rameau, Jean-Claude</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4303-5c404d7b6a517636bd785efcfd5c240887d31e2088926cdba5c7fe5e6a2563a93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Biogeography</topic><topic>Climate models</topic><topic>Climatic variables</topic><topic>Ecological modeling</topic><topic>EcoPlant</topic><topic>Edaphic factors</topic><topic>Forest ecology</topic><topic>Forest soils</topic><topic>Life Sciences</topic><topic>logistic regression</topic><topic>logit analysis</topic><topic>Modeling</topic><topic>Plants</topic><topic>soil nutritional variables</topic><topic>spatial autocorrelation</topic><topic>Species</topic><topic>species distribution modelling</topic><topic>Vegetation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Coudun, Christophe</creatorcontrib><creatorcontrib>Gégout, Jean-Claude</creatorcontrib><creatorcontrib>Piedallu, Christian</creatorcontrib><creatorcontrib>Rameau, Jean-Claude</creatorcontrib><collection>AGRIS</collection><collection>Istex</collection><collection>CrossRef</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Journal of biogeography</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Coudun, Christophe</au><au>Gégout, Jean-Claude</au><au>Piedallu, Christian</au><au>Rameau, Jean-Claude</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Soil nutritional factors improve models of plant species distribution: an illustration with Acer campestre (L.) in France</atitle><jtitle>Journal of biogeography</jtitle><date>2006-10</date><risdate>2006</risdate><volume>33</volume><issue>10</issue><spage>1750</spage><epage>1763</epage><pages>1750-1763</pages><issn>0305-0270</issn><eissn>1365-2699</eissn><abstract>To estimate the relative importance of climate and soil nutritional variables for predicting the distribution of Acer campestre (L.) in French forests. 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The inclusion of edaphic variables significantly improved the quality of predictions for this species, allowing prediction of patches of presence/absence within the study region. Soil nutritional variables may improve the performance of fine-scale (grain) plant species distribution models.</abstract><cop>Oxford, UK</cop><pub>Oxford, UK : Blackwell Publishing Ltd</pub><doi>10.1111/j.1365-2699.2005.01443.x</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-5760-9920</orcidid><orcidid>https://orcid.org/0000-0001-7316-1874</orcidid></addata></record> |
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subjects | Biogeography Climate models Climatic variables Ecological modeling EcoPlant Edaphic factors Forest ecology Forest soils Life Sciences logistic regression logit analysis Modeling Plants soil nutritional variables spatial autocorrelation Species species distribution modelling Vegetation |
title | Soil nutritional factors improve models of plant species distribution: an illustration with Acer campestre (L.) in France |
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