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Static site indices from different national forest inventories: harmonization and prediction from site conditions

Authors :
Thomas Rötzer
Susanne Brandl
Patrick Vallet
Wolfgang Falk
Tobias Mette
Hans Pretzsch
Source :
Annals of Forest Science, Annals of Forest Science, Springer Nature (since 2011)/EDP Science (until 2010), 2018, 75 (2), pp.56. ⟨10.1007/s13595-018-0737-3⟩
Publication Year :
2018
Publisher :
HAL CCSD, 2018.

Abstract

International audience; AbstractKey messageStatic site indices determined from stands’ top height are derived from different forest inventory sources with height and age information and thus enable comparisons and modeling of a species’ productivity encompassing large environmental gradients.ContextEstimating forest site productivity under changing climate requires models that cover a wide range of site conditions. To exploit different inventory sources, we need harmonized measures and procedures for the productive potential. Static site indices (SI) appear to be a good choice.AimsWe propose a method to derive static site indices for different inventory designs and apply it to six tree species of the German and French National Forest Inventory (NFI). For Norway spruce and European beech, the climate dependency of SI is modeled in order to estimate trends in productivity due to climate change.MethodsHeight and age measures are determined from the top diameters of a species at a given site. The SI is determined for a reference age of 100 years.ResultsThe top height proves as a stable height measure that can be derived harmoniously from German and French NFI. The boundaries of the age-height frame are well described by the Chapman-Richards function. For spruce and beech, generalized additive models of the SI against simple climate variables lead to stable and plausible model behavior.ConclusionThe introduced methodology permits a harmonized quantification of forest site productivity by static site indices. Predicting productivity in dependence on climate illustrates the benefits of combined datasets.

Details

Language :
English
ISSN :
12864560 and 1297966X
Database :
OpenAIRE
Journal :
Annals of Forest Science, Annals of Forest Science, Springer Nature (since 2011)/EDP Science (until 2010), 2018, 75 (2), pp.56. ⟨10.1007/s13595-018-0737-3⟩
Accession number :
edsair.doi.dedup.....77525e068b95e124aed3d391a4c74251