Realizing Opportunities in Forest Growth Modelling

The world is continually changing: the emergence of new technology and new demands for pertinent information pose new challenges and possibilities for forest management. Are forest growth models keeping up with client needs? To remain relevant, modelers need to anticipate client needs, gauge the data needed to satisfy these demands, develop the tools to collect and analyze these data efficiently, and resolve how best to deliver the resulting models and other findings. Researchers and managers should jointly identify and articulate anticipated needs for the future, and initiate action to satisfy them. New technology that offers potential for innovation in forest growth modelling include modelling software, automated data collection, and animation of model outputs. New sensors in the sky and on forest machines can routinely provide data previously considered unattainable (e.g., tree coordinates, crown dimensions), as census rather than sample data. What does this revolution in data availability imply for forest growth models, especially for our choice of driving variables

Can silvicultural treatments improve the water economy? -

International audienc

Les pratiques sylvicoles peuvent-elles améliorer l'économie d'eau ? -

International audienc

Deforestation: Correlations, Possible Causes and Some Implications

Changes in national forest areas during 1990-2000 are contrasted with other variables to illustrate correlations and provoke discussion about possible causes. Twenty-five statistically-significant correlations (including rural population, life expectancy, GDP, literacy, commerce, agriculture, poverty and inflation) are illustrated and a statistical model suggests that good governance, alternative employment opportunities, and payments for environmental services may be effective in combating deforestation. The data suggest that a global forest convention may need to be supported by substantial and carefully-targeted development assistance to foster good governance

Estimating Sapling Vitality for Scots Pine (Pinus sylvestris L.) in Russian Karelia

A new method is proposed for estimating vitality or growth potential for saplings of Scots pine (Pinus sylvestris L.), based on height, diameter and height increment. A two-stage process was used to establish the vitality index. The logarithms of height, diameter and height increment were regressed against age, to adjust for the wide range of ages present in our data (c. 10,000 saplings with ages spanning 4-50 years). Then principal component analysis was used to obtain coefficients, which were, in turn, standardized on each axis to provide a vitality index scaled in standard deviations. This standardized scale allows the rank of an individual in the population to be assessed, and draws attention to possible outliers. The use of age-adjusted residuals ensured that the estimator was independent of age, and stable over a wide age range. The first principal component indicates if a sapling is relatively tall (weight = 0.5), thick (w = 0.5) or fast-growing (w = 0.7) for its age. Most of the information is contained in the first principal component, but the second component, which explains about 10% of the variance, appears to offer some utility as an indicator of `acceleration' due to changing conditions. The resulting measures of vitality have been useful for research and management in the dry lichen-moss pine forest in Russian Karelia, but are specific to this species, locality and ecotype. Further research and site-specific data are necessary to adapt the system to other situations

Sustainable Harvesting of Tropical Rainforests: Reply to Keto, Scott and Olsen

This paper refutes the Keto et al. proposition that the Queensland selection logging system is neither ecologically nor economically sustainable. The key requirements of this system are: (1) that logging guidelines are sympathetic to the silvicultural characteristics of the forest, ensuring adequate regeneration of commercial species and discouraging invasion by weeds; (2) tree-marking by trained staff specifies trees to be retained, trees to be removed and the direction of felling to ensure minimal damage to the residual stand; (3) logging equipment is appropriate and driven by trained operators to ensure minimal damage and soil disturbance, compaction and erosion; (4) prescriptions ensure that adequate stream buffers and steep slopes are excluded from logging; (5) sufficient areas for scientific reference, feature protection and recreation are identified and excluded from logging; and (6) that deficiencies in an evolving system are recognized and remedied, leading to an improved system. Many studies of the effects of logging in these forests have been published and collectively provide a unique demonstration of one possible approach to sustainable timber harvesting

Assessing the Quality of Permanent Sample Plot Databases for Growth Modelling in Forest Plantations

Informed plantation management requires a good database, since the quality of information depends on the quality of data, growth models and other planning tools. There are several important questions concerning permanent plots: how many plots, where to put them, and how to manage them. Plot measurement procedures are also important. This paper illustrates graphical procedures to evaluate existing databases, to identify areas of weakness, and to plan remedial sampling. Two graphs, one of site index versus age, another with stocking versus tree size, may provide a good summary of the site and stand conditions represented in the database. However, it is important that these variables, especially site index, can be determined reliably. Where there is doubt about the efficacy of site index estimates, it is prudent to stratify the database according to geography, soil/geology or yield level (total basal area or volume production). Established permanent plot systems may sample a limited range of stand conditions, and clinal designs are an efficient way to supplement such data to provide a better basis for silvicultural inference. Procedures are illustrated with three data sets: teak plantations in Burma, Norway spruce in Denmark, and a clinal spacing experiment in India

A Growth Model for North Queensland Rainforests

A model to predict the growth of commercial timber in north Queensland's rainforests is described. More than 100 commercial species and several hundred other tree species are aggregated into about 20 species groups based on growth habit, volume relationships and commercial criteria. Trees are grouped according to species group and tree size into cohorts, which form the basis for simulation. Equations for predicting increment, mortality and recruitment are presented. The implications of the model on rainforest management for timber production are examined. The model has been used in setting the timber harvest from these rainforests, and should provide an objective basis for investigating the impact of rainforest management strategies. The approach should be applicable to other indigenous forests

Evaluating Forest Growth Models

Effective model evaluation is not a single, simple procedure, but comprises several interrelated steps that cannot be separated from each other or from the purpose and process of model construction. We draw attention to several statistical and graphical procedures that may assist in model calibration and evaluation, with special emphasis on those useful in forest growth modelling. We propose a five-step framework to examine logic and bio-logic, statistical properties, characteristics of errors, residuals, and sensitivity analyses. Empirical evaluations may be made both with data used in fitting the model, and with additional data not previously used. We emphasize that the validity of conclusions drawn from all these assessments depends on the validity of assumptions underlying both the model and the evaluation. These principles should be kept in mind throughout model construction and evaluation