A new approach for modeling stand height development of German forests under climate change

Abstract

IntroductionWe developed a new approach for site index curve models that combines longitudinal height development patterns derived from state-space data with the broad environmental conditions covered by space-for-time data.MethodsFor this, we gathered dendrometry from both inventories and research plots. Concerning environmental variables, we included soil mapping data as well as atmospheric data, i.e., precipitation, temperature, and nitrogen deposition. The atmospheric data was included as a weighted mean over the stand life of the sums for the dynamically determined vegetation period or as yearly sums in the case of nitrogen deposition, respectively. As a weight, the values of a height increment function were used. Then, we derived the basic shape of a height development curve from research plot data and transferred said shape to a site index curve model.ResultsThe model represents a substantial advancement of a previous version and was fitted as a generalized additive model (GAM). All effects were of relevant size and showed biologically feasible patterns.DiscussionThough the model is biased for young ages, we could predict site index curves that, under constant environmental conditions, closely follow yield table curves and thus accurately depict stand height development. Moreover, the model does not require initial dendrometry, which broadens its applicability. Thus, the model represents a useful tool for forest management and planning under climate change.