The relative importance of soil properties and regional climate as drivers of productivity in southern Patagonia’s Nothofagus antarctica forests

International audience AbstractKey messageSoil texture and temperature-related variables were the variables that most contributed toNothofagus antarcticaforest height in southern Patagonia. This information may be useful for improving forest management, for instance related to the establishment of s...

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Bibliographic Details
Published in:Annals of Forest Science
Main Authors: Bahamonde, Héctor A., Pastur, Guillermo Martínez, Lencinas, María V., Soler, Rosina, Rosas, yamina M., Ladd, Brenton, Guardia, Sandra Duarte, Peri, Pablo L.
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2018
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Online Access:https://hal.archives-ouvertes.fr/hal-02976519
https://hal.archives-ouvertes.fr/hal-02976519/document
https://hal.archives-ouvertes.fr/hal-02976519/file/springer.pdf
https://doi.org/10.1007/s13595-018-0725-7
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Summary:International audience AbstractKey messageSoil texture and temperature-related variables were the variables that most contributed toNothofagus antarcticaforest height in southern Patagonia. This information may be useful for improving forest management, for instance related to the establishment of silvopastoral systems or selection of suitable sites for forest reforestation in southern Patagonia.ContextChanges in forest productivity result from a combination of climate, topography, and soil properties.AimsThe relative importance of edaphic and climatic variables as drivers of productivity in Nothofagus antarctica forests of southern Patagonia, Argentina, was evaluated.MethodsA total of 48 mature stands of N. antarctica were selected. For each study site, we measured the height of three mature dominant trees, as an indicator of productivity. Seven soil, five spatial, and 19 climatic features were determined and related to forest productivity. Through partial least squares regression analyses, we obtained a model that was an effective predictor of height of mature dominant trees in the regional data set presented here.ResultsThe four variables that most contributed to the predictive power of the model were altitude, temperature annual range, soil texture, and temperature seasonality.ConclusionThe information gathered in this study suggested that the incidence of the soil and temperature-related variables on the height of dominant trees, at the regionally evaluated scale, was higher than the effect of water-related variables.