ALBERT

Notes: Southeast Asia

Notes: Abstract Examples of nutritional stress in conifer seedlings caused by competing ericaceous species (e.g. Calluna and Kalmia), have been reported in several parts of the world. Nutritional stress (primarily N deficiency) has been reported in Sitka spruce (Picea sitchensis) plantations growing in association with an ericaceous species, salal (Gaultheria shallon), in coastal British Columbia. Nutritional interference by salal was investigated on a chronosequence of sites up to 10 yr after clearcutting and slashburning. No direct evidence for an allelopathic contribution to the N stress was obtained. However, the rapid accumulation of salal fine roots and rhizomes, and the nutrients contained therein, provides a partial explanation for the observed stress symptoms. Soil analyses and seedling bioassays demonstrated a reduction in fertility in the period 8 to 10 yr after clearcutting and slashburning in comparison to the period 2 to 4 yr, which is believed to impose further nutritional stress on Sitka spruce. It is concluded that the nutritional stress in these Sitka spruce plantations is caused by a combination of (1) salal competition for nutrients and their subsequent immobilization in salal biomass, and (2) declining site fertility caused by the termination of the flush of nutrients (the “assert period”) that occurs in the immediate post-clearcutting and slashburning period. Sustaining good growth of plantations under such circumstances will require site nutrient management as well as vegetation management.

Notes: Abstract Forest ecosystems are being subjected to an increasing variety of stresses for which we do not yet have rotation-length experience. Where we lack such experience, we cannot make experience-based predictions of the long-term effects of these stresses. While we are accumulating such experience, computer models can be used to make interim knowledge-based predictions. Most scientific knowledge has been produced by reductionist; disciplinary, process-based research. Such knowledge is a vital component of any explanation of natural or human-induced landscape phenomena, but cannot, in its reductionist, disciplinary form, provide an adequate basis on its own for long-term predictions about these phenomena. Such predictions require the development of computer models of ecosystem form and function based on the integration of knowledge from eco-physiology, autecology, community ecology, soil science, and climatology into ecosystem-level models that accurately describe the function and temporal dynamics of forest ecosystems.The ability of the ecosystem-level forest management simulation model FORCYTE-11 (FORest nutrient Cycling and Yield Trend Evaluator) to simulate forest stresses is described briefly. The question of how to model other stresses, such as air pollution, acid rain, climate change, soil compaction and erosion, and moisture competition is discussed, and the outline of a new model (FORECAST: FORestry and Environmental Change ASsessmenT) is presented.

Notes: Abstract FORECAST, an ecosystem simulation model, was calibrated for aspen (Populus tremuloides Michx) and white spruce (Picea glauca (Moench) Voss) stands using data collected in the Boreal White and Black Spruce biogeoclimatic zone in northeastern British Columbia and published data. Simulations were undertaken to examine the effects of initial density of aspen on yield of white spruce in an aspen and spruce mixedwood stand, and to compare the predicted stemwood biomass yields of aspen, white spruce and mixedwood stands. Results of the simulations suggest that mixedwood management regimes on the same medium quality site should have higher stemwood yield compared to pure white spruce stand. Simulated stemwood biomass yield of pure aspen stands over 240 years on medium site varied from 682.5 Mg ha−1 to 239.1 Mg ha−1 for different rotation lengths (30 to 120 years). Repeated rotations of monoculture white spruce produced much less stemwood biomass, simulated yields over 240 years ranging from 877.3 Mg ha−1to 248.4 Mg ha−1 for rotation lengths of 60 to 240 years. Simulated aspen and white spruce mixedwood stands produced higher stemwood biomass yields than the pure white spruce stands, but less than the pure aspen stands; from 217.4 Mg ha−1 to 292.8 Mg ha−1 over 240 years. Variations in initial densities of aspen did not affect spruce stemwood biomass yield over the simulation period. This model shows potential for comparing the relative effects of different management strategies on harvestable volume and variety of other ecosystem variables. A calibrated version of the model should be useful as both a management simulator and a research tool. However, shortcomings in the representation of the canopy architecture of mixed species stands suggested the need to develop an individual tree version of this ecosystem management model for application to mixed species stands.

Notes: Abstract The Canadian forest environment is characterized by high spatial and temporal variability, especially in the west. Our forests vary according to climate, landform, and surficial geology, and according to the type, intensity, extent of, and the time since the last disturbance. Most Canadian forests have had a history of repeated acute, episodic disturbance from fire, insects, wind, diseases and/or logging, with a frequency of disturbance varying from a few decades to many centuries. These sources of variability have resulted in a complex and continually changing mosaic of forest conditions and stages of successional development. Monitoring the ‘quality’ of this dynamic forested landscape mosaic is extremely difficult, and in most cases the concept of a relatively simple index of forest ecosystem quality or condition (i.e. an ‘ecological indicator‘) is probably inappropriate. Such ecological indicators are better suited for monitoring chronic anthropogenically induced disturbances that are continuous in their effect (e.g. ‘acid rain’, heavy metal pollution, air pollution, and the ‘greenhouse effect’) in ecosystems that, in the absence of such chronic disturbance, exhibit very slow directional change (e.g. lakes, higher order streams and rivers). Monitoring the effects of a chronic anthropogenic disturbance to forest ecosystems to determine if it is resulting in a sustained, directional alteration of environmental ‘quality’ will require a definition of the expected pattern of episodic disturbance and recovery therefrom (i.e. patterns of secondary succession in the absence of the chronic disturbance). Only when we have such a ‘temporal fingerprint’ of forest ecosystem condition for ‘normal’ patterns of disturbance and recovery can we determine if the ecosystem condition is being degraded by chronic human-induced alteration of the environment. Thus, degradation is assessed in terms of deviations from the expected temporal pattern of conditions rather than in terms of an instantaneous assessment of any particular condition. The concept of ‘ecological rotation’ (the time for a given ecosystem to recover from a given disturbance back to some defined successional condition) is useful in the definition of these ‘temporal fingerprints’. This requires information on the intensity of disturbance, the frequency of disturbance, and the rate of successional recovery. Only when all three of these are known or estimated can statements be made as to whether the ecosystem is in a longterm sustainable condition or not. The somewhat overwhelming complexity of this task has led forest ecologists to use ecosystem-level computer simulation models. Appropriately structured and calibrated models of this type can provide predictions of the overall temporal patterns of ecosystem structure and functions that can be expected to accompany a given frequency and character of episodic disturbance. Such models can also be used to examine the long-term consequences of chronic disturbances such as acid rain and climatic change. Predictive ecosystem-level models should be used in conjunction with some method of stratifying the inherent spatial biophysical variability of the forest environment, such as the biogeoclimatic classification system of British Columbia.

Notes: Abstract Examples of nutritional stress in conifer seedlings caused by competing ericaceous species (e. g. Calluna andKalmia), have been reported in several parts of the world. Nutritional stress (primarily N deficiency) has been reported in Sitka spruce (Picea sitchensis) plantations growing in association with an ericaceous species, salal (Gaultheria shallon), in coastal British Columbia. Nutritional interference by salal was investigated on a chronosequence of sites up to 10 yr after clearcutting and slashburning. No direct evidence for an allelopathic contribution to the N stress was obtained. However, the rapid accumulation of salal fine roots and rhizomes, and the nutrients contained therein, provides a partial explanation for the observed stress symptoms. Soil analyses and seedling bioassays demonstrated a reduction in fertility in the period 8 to 10 yr after clearcutting and slashburning in comparison to the period 2 to 4 yr, which is believed to impose further nutritional stress on Sitka spruce. It is concluded that the nutritional stress in these Sitka spruce plantations is caused by a combination of (1) salal competition for nutrients and their subsequent immobilization in salal biomass, and (2) declining site fertility caused by the termination of the flush of nutrients (the “assart period”) that occurs in the immediate post-clearcutting and slashburning period. Sustaining good growth of plantations under such circumstances will require site nutrient management as well as vegetation management.

Notes: Abstract Forest ecosystems are being subjected to an increasing variety of stresses for which we do not yet have rotation-length experience. Where we lack such experience, we cannot make experience-based predictions of the long-term effects of these stresses. While we are accumulating such experience, computer models can be used to make interim knowledge-based predictions. Most scientific knowledge has been produced by reductionist, disciplinary, process-based research. Such knowledge is a vital component of any explanation of natural or human-induced landscape phenomena, but cannot, in its reductionist, disciplinary form, provide an adequate basis on its own for long-term predictions about these phenomena. Such predictions require the development of computer models of ecosystem form and function based on the integration of knowledge from eco-physiology, autecology, community ecology, soil science, and climatology into ecosystem-level models that accurately describe the function and temporal dynamics of forest ecosystems. The ability of the ecosystem-level forest management simulation model FORCYTE-11 (FORest nutrientCycling andYieldTrendEvaluator) to simulate forest stresses is described briefly. The question of how to model other stresses, such as air pollution, acid rain, climate change, soil compaction and erosion, and moisture competition is discussed, and the outline of a new model (FORECAST:FORestry andEnvironmentalChangeASsessmenT) is presented.