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Soil nutritional factors improve models of plant species distribution: an illustration with Acer campestre (L.) in France

Soil nutritional factors improve models of plant species distribution: an illustration with Acer... Aim To estimate the relative importance of climate and soil nutritional variables for predicting the distribution of Acer campestre (L.) in French forests. Location France. Methods 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. Results 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. Main conclusion Soil nutritional variables may improve the performance of fine‐scale (grain) plant species distribution models. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Biogeography Wiley

Soil nutritional factors improve models of plant species distribution: an illustration with Acer campestre (L.) in France

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References (144)

Publisher
Wiley
Copyright
Copyright © 2006 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0305-0270
eISSN
1365-2699
DOI
10.1111/j.1365-2699.2005.01443.x
Publisher site
See Article on Publisher Site

Abstract

Aim To estimate the relative importance of climate and soil nutritional variables for predicting the distribution of Acer campestre (L.) in French forests. Location France. Methods 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. Results 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. Main conclusion Soil nutritional variables may improve the performance of fine‐scale (grain) plant species distribution models.

Journal

Journal of Biogeography – Wiley

Published: Oct 1, 2006

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