Potential contributions of statistics and modelling to sustainable forest management: review and synthesis.

Abstract

This chapter provides a review of the statistical and modelling disciplines, their techniques and potential contribution to sustainable forest management (SFM). The main topics covered are: Mensuration and models for sustainable forest management (SFM) Inventory and monitoring for forest sustainability: criteria and indicators Models of tropical forests for the conservation of biodiversity Integrating information and models across spatial and temporal scales for SFM Climate and carbon models in relation to sustainability New techniques for the statistical analysis of sustainability data Uncertainly analysis in modeling and monitoring for SFM Forest data, information and model archives There are major contributions to be made, in particular in the areas of information and model integration where a synthesis of information and models across both spatial and temporal scales is required. There is a great need for international collaboration on the development of open and shared forest data and model repositories/archives, as well as continued development of forest information systems.

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

“…Such models are generally found in Northern and Central Europe. However, calibration of this type of models often requires comprehensive spatio-temporal data on re-measured tree populations, which are expensive and usually not available (Rennolls et al 2007). Large-scale matrix models based on transition probability matrices are also being used to predict future forest state, for example in the Netherlands, Denmark, Bulgaria, France and Italy.…”

“…Over the past century, empirical growth models and yield tables have become widely used by forest managers to evaluate silvicultural options, and to estimate the present and future volume of timber of their forests. Currently, existing projection systems comprise a variety of methods that range from the original yield tables to more evolved models including stand-level models, distribution-based models, individual-tree models, and more exploratory process-based eco-physiological models (Rennolls et al 2007). More recently, the respective merits of empirical models and processbased models have been discussed from the perspective of environmental changes (Fontes et al 2010;Landsberg 2003) and new silvicultural management treatments (Amaro and Tomé 1999;Amaro et al 2003).…”

Using stand-scale forest models for estimating indicators of sustainable forest management

“…For example, bird diversity is associated with forest structure at different spatial scales (Mitchell et al 2001) and can be predicted from forest composition and structure variables (Azeveda et al 2005, GilTena et al 2007. Also here, individual-tree models may be more suitable than mean-tree or diameter-class models (Rennolls et al 2007, Pretzsch 2009). They could also potentially deal with the structural diversity of continuous-cover forests that have been associated with biological diversity and forest health (Humphrey 2005).…”

“…This calls for more variety of models for different species and models with more variable stand structures, particularly emphasizing the need to understand species and tree-to-tree interactions better. Individual-tree models may be more suitable for the simulation of complex forests and the effects of novel management interventions on them (Rennolls et al, 2007) (see Criterion 4). Note however that heterogeneity can also be achieved at the forest management unit or landscape level.…”

Incorporating management history into forest growth modelling

“…Properly calibrated and validated, such models can also be used as diagnostic tools, to separate the influence of forest growth impactors such as climate change and Nitrogen deposition (Eastaugh et al 2011). Such models have however been sometimes criticised in the past for a poor representation of forest mass growth (Rennolls et al 2007, Pretzsch et al 2008). This paper presents part of a wider study that will compare aboveground biomass estimates obtained with the BIOME-BGC model (Thornton 1998, Pietsch et al 2005 with field data from the Austrian National Forest Inventory (Gabler & Schadauer 2006).…”