Large-scale dynamics of a heterogeneous forest resource are driven jointly by geographically varying growth conditions, tree species composition and stand structure

Abstract

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Overview of methods and tools for evaluating future woody biomass availability in European countries

“…The French diameter-class model was recalibrated using 2006-2008 NFI data and a sensitivity analysis was carried out by Wernsdörfer et al (2012).…”

An Area-Based Matrix Model for Uneven-Aged Forests

“…Originally, it was intended for a national level or wider geographical scope analysis. There is a French diameter class model [22] that has been applied in a large-scale analysis, but it is as the authors claim static in a sense that makes it less appropriate for long-term analyses.…”

“…They were applied on uneven-aged stands already in the 1970s [13]. Throughout the years, several studies were conducted to improve the model and estimation procedures e.g., [9,[14][15][16][17][18][19][20][21][22]. However, these models encounter problems when applied to a forest that consists of many different stands.…”

Uncertainty assessment of large-scale forest growth predictions based on a transition-matrix model in Catalonia

“…Since then, this approach has been widely used in a large array of forest conditions (e.g., Solomon et al 1986;Liang and Buongiorno 2005;Wernsdörfer et al 2012;Picard and Liang 2014). Matrix models are based on the assumption that individuals in a population (e.g., trees) can be classified into discrete classes of an individual-specific key feature, such as the aforementioned diameter classes.…”

“…The EFISCEN matrix model, which was originally developed by Sallnäs (1990), and the Global Forest Model (Kindermann et al 2006) count among the very few of their kind, although they have been used in many European countries in order to produce national or regional forecasts since the early 2000s (e.g., Nabuurs et al 2000;Thürig and Schelhaas 2006;Groen et al 2013). Other large-scale growth models are being developed to meet the demand for these types of predictive tools (e.g., Wernsdörfer et al 2012;Packalen et al 2014).…”