Guy R. Larocque

Progress in integrated assessment and modelling

Environmental processes have been modelled for decades. However. the need for integrated assessment and modeling (IAM) has,town as the extent and severity of environmental problems in the 21st Century worsens. The scale of IAM is not restricted to the global level as in climate change models, but includes local and regional models of environmental problems. This paper discusses various definitions of IAM and identifies five different types of integration that Lire needed for the effective solution of environmental problems. The future is then depicted in the form of two brief scenarios: one optimistic and one pessimistic. The current state of IAM is then briefly reviewed. The issues of complexity and validation in IAM are recognised as more complex than in traditional disciplinary approaches. Communication is identified as a central issue both internally among team members and externally with decision-makers. stakeholders and other scientists. Finally it is concluded that the process of integrated assessment and modelling is considered as important as the product for any particular project. By learning to work together and recognise the contribution of all team members and participants, it is believed that we will have a strong scientific and social basis to address the environmental problems of the 21st Century.

Effect of temperature on soil organic matter decomposition in three forest biomes of eastern Canada

The sensitivity of soil organic matter decomposition to temperature change is critical tothe global carbon balance and to whether soils will respond with positive feedback to climate change. Forest cover determines litter composition, which controls to a large extent soil organic matter quality and its sensitivity to temperature. The effect of temperature on soil organic matter decomposition was studied along a latitudinal gradient encompassing sugar maple, balsam fir and black spruce forest types. Long-term laboratory soil incubations conducted at four different temperatures were used to discriminate the effect of temperature from that of organic matter quality on decomposition rates. The specific C mineralization rate of the humus layer was highest for balsam fir sites, intermediate for one sugar maple site and lowest for black spruce sites and the other sugar maple site. However, considering the total C pools of the FH layer and of the top 20 cm of mineral soil, it was estimated that coniferous sites e...

Seasonal Dynamics of Understory Vegetation in Four Eastern Canadian Forest Types

Understory vegetation dynamics was monitored throughout the 1998 growing season in four eastern Canadian forest types: sugar maple–American beech (Acer saccharum Marsh.–Fagus grandifolia Ehrh.); sugar maple–yellow birch (Betula alleghaniensis Britton); balsam fir (Abies balsamea [L.] Mill.); and black spruce–jack pine (Picea mariana [Mill.] BSP–Pinus banksiana Lamb.). Significant differences in biomass were obtained among species groups (herbaceous, woody, and mosses) within each site. However, biomass did not vary significantly throughout the growing season, except in the sugar maple–American beech site. The four sites differed in total biomass, but these differences could be explained mainly by the presence of some key species (e.g., Lycopodium lucidulum Michx.) and the light regime under the canopy. Species richness varied throughout the growing season on each site. However, peaks in richness did not occur at the same time in each site: richness peaked later with increasing latitude, from late May in the southernmost site to late September in the northernmost site. Average richness did not vary across sites. Aboveground nutrient concentrations for herbaceous species were greater than nutrient concentrations for stems of woody species. However, nutrient concentrations for woody species leaves were comparable to those of herbaceous species. Our results highlighted the importance of understory species in the cycling of nutrients and their capacity to keep nutrients within a site. Specific leaf area (SLA) for herbaceous species was greater than SLA for woody species, which indicated a greater capacity to acclimate to different light conditions than woody species. Increase in leaf area ratio with decrease in height for sugar maple and beech suggests that both species decreased their efficiency to produce biomass at the ground level as they were overtopped by higher surrounding vegetation.

Coupling a detailed photosynthetic model with foliage distribution and light attenuation functions to compute daily gross photosynthesis in sugar maple (Acer saccharum Marsh.) stands

Abstract Canopy multilayer models for forest stands to scale from leaf to canopy have generally focused on developing relatively detailed photosynthetic active radiation (PAR) characterization functions within canopies, but with much simplified photosynthetic production functions. This study aimed at developing a multilayer model based on detailed foliage distribution, PAR interception and photosynthesis components. Allometric, physiological and meteorological data collected in two sugar maple (Acer saccharum Marsh.) stands that differed in climatic conditions, stand structure and fertility were used to calibrate the model. In the leaf photosynthesis model, photosynthetic rate is limited by the ribulose-bisphosphate (RUBP) concentration or the activity of RUBP carboxylase/oxygenase. The Rubisco potential capacity for CO2 fixation, Vcmax, and the potential electron transport rate, J, were related to temperature and leaf nitrogen and soluble and insoluble protein contents. The Weibull distribution function was used to represent leaf area and biomass distribution within the canopy. PAR was computed in different layers of the canopy using a radiative transfer approach. There was fairly good agreement between measured and predicted photosynthetic rate at the individual leaf level, which indicated that the leaf photosynthesis model accounted for variation in PAR, temperature and foliage nitrogen content. The pattern of foliage nitrogen variation at different levels of the canopy was similar for both sites. However, foliage area and biomass distribution functions were characterized by different patterns between both sites. Simulations showed that differences in canopy properties represented by the site-specific functions were essential to obtain good agreement between predicted and measured PAR below the canopy, as both stands had relatively close values in leaf area index (LAI) and leaf biomass. Sensitivity analysis indicated that the coupled multilayer model derived accounted for relatively small variation in LAI and foliage nitrogen concentration.

How does drought tolerance compare between two improved hybrids of balsam poplar and an unimproved native species

Poplars are one of the woody plants that are very sensitive to water stress, which may reduce the productivity of fast-growing plantations. Poplars can exhibit several drought tolerance strategies that may impact productivity differently. Trees from two improved hybrids, Populus balsamifera × Populus trichocarpa Torr. & Gray (clone B × T) and P. balsamifera × Populus maximowiczii A. Henry (clone B × M), having P. balsamifera L. as a parent and trees from native and unimproved P. balsamifera were subjected to a 1-month drying cycle in a growth chamber and then rewatered. The unimproved and native B clone maintained higher stomatal conductance (g(s)) than the hybrids, and high photosynthetic activity and transpiration, even when soil water content was nearly zero. As a result, both instantaneous water use efficiency (WUE(i)) and leaf carbon isotope composition (δ(13)C) indicated that this clone was less affected by drought than both hybrids at maximal drought stress. However, this clone shed its leaves when the drought threshold was exceeded, which implied a greater loss of productivity. The B × M hybrid showed a relatively conservative response to water stress, with the greatest decrease in transpiring versus absorbing surface (total leaf area to root biomass ratio). This clone was also the only one to develop new leaves after rewatering, and its total biomass production was not significantly decreased by drought. Among the two hybrids, clone B × T was the most vigorous, with the greatest transpiration (E(i)) and net CO(2) assimilation (A) rates, allowing for high biomass production. However, it had a more risky strategy under drought conditions by keeping its stomata open and high E(i) rates under moderate drought, resulting in a lower recovery rate after rewatering. The opposite drought response strategies of the two hybrids were reflected by clone B × T having lower WUE(i) values than clone B × M at maximal drought, with a very low Ψ(min) value of -3.2 MPa, despite closed stomata and stopped photosynthetic activity. Positive linear relationships between A and g(s) for the three hybrids indicated strong stomatal control of photosynthesis. Moreover, the three poplar clones showed anisohydric behaviour for stomatal control and their use under long-term drought should be of interest, especially the B × M clone.

Evaluating the impact of competition using relative growth rate in red pine (Pinus resinosa Ait.) stands

Abstract The development of red pine ( Pinus resinosa Ait.) stands originating in different spacings was analyzed using absolute growth rate (AGR) and relative growth rate (RGR) in diameter at breast height for several ages. The objectives were to determine whether RGR better reflected the effect of competition than AGR, and to interpret the relationship between RGR and tree size. While AGR was always positively related to tree size, RGR decreased with an increase in tree size before the onset of competition and when competition was not severe, and increased with tree size under severe competitive stress. This implied that small trees were more efficient than large trees at producing new biomass before the onset of competition. The effect of competition was to reduce the efficiency of small trees relative to large trees. It was concluded that RGR expressed the competitive status of stands better than AGR.

Challenges in the Application of Existing Process-Based Models to Predict the Effect of Climate Change on C Pools in Forest Ecosystems

Process-based models used to investigate forest ecosystem response to climate change were not necessarily developed to include the effect of carbon dioxide (CO2) and temperature increases on physiological processes. Simulation of the impacts of climate change with such models may lead to questionable predictions. It is generally believed that significant shifts in the performance of black spruce (Picea mariana [Mill] B.S.P.) will occur under climate change. This species, which accounts for 64% of Ontarios coniferous growing stock and 80% of the annual allowable cut, represents important economic activity throughout the boreal forest region. Forest management planning requires relatively accurate productivity estimates. Thus, it is imperative to ensure that process-based models realistically predict the effect of climate change. In this study, CENTURY and FOREST-BGC models were calibrated for a productive, upland black spruce stand in northwestern Ontario. Even though both models predicted similar relative outcomes after 100 years of climate change, they disagreed on the impacts of temperature in combination with an increase in CO2. Also, absolute amounts of carbon sequestered varied with climate change scenarios. Comparison of both models indicated that the representation of critical processes in these two forest ecosystem models is incomplete. For instance, the interactive effects of CO2 and temperature increases on physiological processes at stand and soil levels are not well documented nor are they easily identifiable in the models. Their incorporation into models is therefore problematic. Practitioners must consequently be wary of assumptions about the inclusion of critical processes in models.

An analytical framework to assist decision makers in the use of forest ecosystem model predictions

The predictions from most forest ecosystem models originate from deterministic simulations. However, few evaluation exercises for model outputs are performed by either model developers or users. This issue has important consequences for decision makers using these models to develop natural resource management policies, as they cannot evaluate the extent to which predictions stemming from the simulation of alternative management scenarios may result in significant environmental or economic differences. Various numerical methods, such as sensitivity/uncertainty analyses, or bootstrap methods, may be used to evaluate models and the errors associated with their outputs. However, the application of each of these methods carries unique challenges which decision makers do not necessarily understand; guidance is required when interpreting the output generated from each model. This paper proposes a decision flow chart in the form of an analytical framework to help decision makers apply, in an orderly fashion, different steps involved in examining the model outputs. The analytical framework is discussed with regard to the definition of problems and objectives and includes the following topics: model selection, identification of alternatives, modelling tasks and selecting alternatives for developing policy or implementing management scenarios. Its application is illustrated using an on-going exercise in developing silvicultural guidelines for a forest management enterprise in Ontario, Canada.

Chapter Eighteen Uncertainty and Sensitivity Issues in Process-based Models of Carbon and Nitrogen Cycles in Terrestrial Ecosystems

Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for northern forest ecosystems. These models are widely used to evaluate the long-term decisions in forest management dealing with effects like particulate pollution, productivity and climate change. Regarding climate change, one of the key questions that have sensitive political implications is whether northern forests will sequester atmospheric C or not. Whilst many process-based models have been tested for accuracy by evaluating or validating against observed data, few have dealt with the complexity of the incorporated procedures to estimate uncertainties associated with model predictions or the sensitivity of these predictions to input factors in a systematic, inter-model comparison fashion. In general, models differ in their underlying attempts to match natural complexities with assumed or imposed model structure and process formulations to estimate model parameters, to gather data and to address issues on scope, scale and natural variations. Uncertainties may originate from model structure, estimation of model parameters, data input, representation of natural variation and scaling exercises. Model structure relates to the mathematical representation of the processes modelled and the type of state variables that a model contains. The modelling of partitioning among above- and below-ground C and N pools and the interdependence among these pools remain a major source of uncertainty in model structure and error propagation. For example, most soil C models use at least three state variables to represent the different types of soil organic matter (SOM). This approach results in creating three artificial SOM pools, assuming that each one contains C compounds with the same turnover rate. In reality, SOM consists of many different types of C compounds with widely different turnover rates. Uncertainty in data and parameter estimates are closely linked. Data uncertainties are associated with high variations in estimating forest biomass, productivity and soil organic matter and their estimates may be incomplete for model initialisation, calibration, validation and sensitivity analysis of generalised predictor models. The scale at which a model is being used also affects the level of uncertainty, as the errors in the prediction of the C and N dynamics differ from site to landscape levels and across climatic regions. If the spatial or temporal scale of a model application is changed, additional uncertainty arises from neglecting natural variability in system variables in time and space. Uncertainty issues are also intimately related to model validation and sensitivity analysis. The estimation of uncertainties is needed to inform decision processes in order to detect the possible corridor of development. Uncertainty in this context is an essential measure of quality for stakeholder and decision makers.

Effects of silviculture intensity on plant diversity response patterns in young managed northern temperate and boreal forests.

Abstract : Throughout much of the northern temperate and boreal forests of Canada, intensifying silviculture to enhance fibre production is of increasing interest. However, some oppose the application of intensive silviculture, citing possible negative effects on biodiversity. Using fifth-year post-harvest data from the NEBIE Plot Network in Ontario, Canada, we studied the relationship between plant diversity, silviculture intensity, and contemporary climate. Neutral, linear (positive and negative), exponential (positive and negative), quadratic (concave up and concave down), cubic, and higher-order models were fit to the data. Here we discuss the potential influence of climate and silviculture on observed biodiversity patterns. As well, we address their effects on regional species pools, succession, hierarchical structure, invasibility by exotic species, and species resilience.