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Static site indices from different national forest inventories: harmonization and prediction from site conditions
Authors:Susanne Brandl  Tobias Mette  Wolfgang Falk  Patrick Vallet  Thomas Rötzer  Hans Pretzsch
Institution:1.Bavarian State Institute of Forestry,Freising,Germany;2.Univ. Grenoble Alpes, Irstea, UR EMGR,St-Martin-d’Hères,France;3.Irstea, UR EFNO,Nogent-sur-Vernisson,France;4.Forest Growth and Yield Science,Technische Universit?t München,Freising,Germany
Abstract:

Key message

Static 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.

Context

Estimating 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.

Aims

We 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.

Methods

Height 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.

Results

The 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.

Conclusion

The 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.
Keywords:
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