4.01.05 - Process-based models for predicting forest growth and timber quality
Publication Alert: Global biodiversity and productivity
Positive biodiversity-productivity relationship predominant in global forests
This article, in which IUFRO officeholder Christian Salas is a co-author, has just been published in Science.
The relationship between biodiversity and ecosystem productivity has been explored in detail in herbaceous vegetation, but patterns in forests are far less well understood. Liang et al. have amassed a global forest data set from >770,000 sample plots in 44 countries. A positive and consistent relationship can be discerned between tree diversity and ecosystem productivity at landscape, country, and ecoregion scales. On average, a 10% loss in biodiversity leads to a 3% loss in productivity. This means that the economic value of maintaining biodiversity for the sake of global forest productivity is more than fivefold greater than global conservation costs.
Details at: http://science.sciencemag.org/content/354/6309/aaf8957
Working Party 4.01.05 deals with mathematical models of forest stand dynamics, and of the development of tree form and wood properties, that are based on ecophysiological mechanisms and principles.
State of Knowledge
Process-based growth models arose at the time when increases in computational power provided modellers with the means to calculate growth and yield as the result of fundamental physiological processes. The appeal of process based models lies in the ability to make predictions of growth and yield under a range of conditions, even outside the empirical domain, once the primary factors and variables, and the relationships and interactions between them, have been effectively expressed and calibrated in the model. Model development is a challenging undertaking, requiring considerable investment in field measurements taken under variable conditions where it is often impossible to control the factors of interest for the duration of the experiment.
As research tools, process-based models are essential for understanding the functioning of forest ecosystems. The models link and make sense of previously isolated facts, generating hypotheses to guide future studies.
Although the knowledge obtained through process-based models contributes in an important way to the improvement of forest decision support systems, their direct application in operational forest management is controversial. The practical use of process-based growth models has been constrained by the capacity of management agencies to obtain, at the scale of an entire estate, the often highly detailed site descriptors and other input variables needed to drive the models. However, there have been some significant applications of process based models, including the prediction of potential impacts on growth of climate change, the identification of sites suitable for plantation establishment, assessment of pest and disease impacts, modelling of wood property development as function of management options. Forest management planning requires that the value of the predicted yield can be estimated, so variables important for value assessment need to be included in the outputs of the model. There also have been attempts to simplify the software around process-based growth models to make them more usable in forest management applications. On the other hand, it has been suggested that timber and pulp production requires output in terms of individual stems or stem categories in different quality classes, often not included in process-based models.
Examples of process-based modelling approaches for forest management applications include the CABALA system developed by the CSIRO in Australia, the PipeQual model developed in Finland, and the ANAFORE model developed in Belgium. PipeQual describes the dimensional growth of trees as function of carbon acquisition and allocation, including a 3D description of stems, and it has been applied to the economic optimisation of thinning schedules and intensities. ANAFORE focuses on the development of fibre properties, which are also responsive to environmental change in the model.
When the value of yield is combined with the economics of carbon sequestration and ecosystem services relating to, e.g., nutrient and water balance, management-oriented process-based models could provide robust tools for multi-objective forest management.