A growth-effective age-based periodic site-index for the estimation of dynamic forest site productivity under environmental changes

Abstract Key message A novel periodic site index is introduced for the quantification of dynamic forest site productivity. The measure is age-independent, sensitive to environmental changes and efficient for the estimation and prediction of stand height and stand volume increment. Context Accurate and up-to-date prediction of site productivity is crucial for the sustainable management of forest ecosystems, especially under environmental changes. Aims The aim of this study was to introduce a novel concept: a periodic site index based on growth-effective age for the quantification of dynamic forest site productivity. Methods The growth-effective age based periodic site index is estimated from repeated or multi-temporal measurements of stand dominant height. Furthermore, a recursive procedure to update the underlying site index model is presented by using repeated measurements of stand dominant height. The database used in this study comprised repeated measurements of 945 Norway spruce ( Picea abies L.) experimental plots at 508 different locations in Southwest Germany. Results The evaluation shows that periodic site index is statistically superior to the conventional site index, based on chronological stand age, for estimating stand height and stand volume increment. The analysis of temporal differences between growth-effective stand age and chronological stand age and between periodic site index and conventional site index in the period 1900 to 2020 reveals trends referring to stand age and site productivity, which corroborate earlier regional studies on forest growth trends due to environmental changes. Conclusions The periodic site index is a better indicator for site productivity than conventional site index. Under conditions of environmental changes, conventional site index is biased, whereas the growth-effective age based site index provides an unbiased estimate of stand height development. With the more widespread application of remote sensing techniques, such as airborne laser scanning, the availability of multi-temporal stand height data will increase in the near future. The novel concept provides an adaptive modeling approach perfectly suited to these data for an improved estimation and prediction of forest site productivity under environmental changes and can straightforwardly be applied also to uneven-aged and multi-species stands.