Forest dynamics modelling under natural fire cycles: A tool to define natural mosaic diversity for forest management

In natural boreal forests, disturbances such as fire and variation in surficial deposits create a mosaic of forest stands with different species composition and age. At the landscape level, this variety of stands can be considered as the natural mosaic diversity. In this paper, we describe a model that can be used to estimate the natural diversity level of landscapes. We sampled 624 stands for tree species composition and surficial deposits in eight stand-age classes corresponding to eight fire episodes in the region of Lake Duparquet, Abitibi, Québec at the southern fringe of the Boreal Forest. For six surficial deposit types, stand composition data were used to define equations for vegetation changes with time for a chronosequence of 230 years for four forest types. Using Van Wagner's (1978) model of age class distribution of stands, the proportion of each forest type for several lengths of fire cycle were defined. Finally, for real landscapes (ecological districts) of the ecological region of the Basses-Terres d'Amos, the proportion of forest types were weighted by the proportion of each surficial deposit type using ecological map information. Examples of the possible uses of the model for management purposes, such as biodiversity conservation and comparisons of different landscapes in terms of diversity and sensitivity to fire regime changes, are discussed.     

Measuring forest structure along productivity gradients in the Canadian boreal with small-footprint Lidar

The structure and productivity of boreal forests are key components of the global carbon cycle and impact the resources and habitats available for species. With this research, we characterized the relationship between measurements of forest structure and satellite-derived estimates of gross primary production (GPP) over the Canadian boreal. We acquired stand level indicators of canopy cover, canopy height, and structural complexity from nearly 25,000 km of small-footprint discrete return Light Detection and Ranging (Lidar) data and compared these attributes to GPP estimates derived from the MODerate resolution Imaging Spectroradiometer (MODIS). While limited in our capacity to control for stand age, we removed recently disturbed and managed forests using information on fire history, roads, and anthropogenic change. We found that MODIS GPP was strongly linked to Lidar-derived canopy cover (r?=?0.74, p?<?0.01), however was only weakly related to Lidar-derived canopy height and structural complexity as these attributes are largely a function of stand age. A relationship was apparent between MODIS GPP and the maximum sampled heights derived from Lidar as growth rates and resource availability likely limit tree height in the prolonged absence of disturbance. The most structurally complex stands, as measured by the coefficient of variation of Lidar return heights, occurred where MODIS GPP was highest as productive boreal stands are expected to contain a wider range of tree heights and transition to uneven-aged structures faster than less productive stands. While MODIS GPP related near-linearly to Lidar-derived canopy cover, the weaker relationships to Lidar-derived canopy height and structural complexity highlight the importance of stand age in determining the structure of boreal forests. We conclude that an improved quantification of how both productivity and disturbance shape stand structure is needed to better understand the current state of boreal forests in Canada and how these forests are changing in response to changing climate and disturbance regimes.     

The long time scales of the climate–economy feedback and the climatic cost of growth

This paper is based on the perception that the inertia of climate and socio-economic systems are key parameters in the climate change issue. In a first part, it develops and implements a new approach based on a simple integrated model with a particular focus on an innovative transient impact and adaptation modeling. In a second part, a climate–economy feedback is defined and characterized. The following results were found. 1) It has a long characteristic time, which lies between 50 and 100 years depending on the hypotheses; this time scale is long when compared to the system's other time scales, and the feedback cannot act as a natural damping process of climate change. 2) Mitigation has to be anticipated since the feedback of an emission reduction on the economy can be significant only after a 20-year delay and is really efficient only after at least 50 years. 3) Even discounted, production changes due to an action on emissions are significant over more than one century. 4) The methodology of the Intergovernmental Panel on Climate Change (IPCC), which neglects the feedback from impacts to emissions, is acceptable up to 2100, whatever is the level of impacts. This analysis allows also to define a climatic cost of growth as the additional climate change damages due to the additional emissions linked to economic growth.

Adaptation to What and Why?

Adaptation in response to anthropogenic climate change seeks to maintain viability by maximising benefits and minimising losses. It is necessary because some climatic change is now inevitable, despite the international focus on mitigation measures. Indeed, the measures agreed at Kyoto would by themselves result in only a small reduction in the climate changes to be expected over the next century.Discussion of the expected changes and possible impacts leads to the following conclusions regarding climate change scenarios in relation to impacts and adaptation: Climate change in the foreseeable future will not be some new stable "equilibrium" climate, but rather an ongoing "transient" process; Climate change predictions relevant to impacts on most sectors and ecosystems are still highly uncertain; There is a need for a greater focus on developing countries and tropical regions, and on relevant key variables, including the magnitude and frequency of extreme events; The focus should shift from single predictions, or extreme ranges of uncertainty, to risk assessment; Thresholds critical to impacted sectors and ecosystems should be identified, and expressed as functions of climatic variables; Planned adaptations will be necessary to cope with multiple stresses, including those due to non-climatic changes; A major task of adaptation science is to identify the limits of adaptation, i.e., to identify "dangerous levels of greenhouse gases" beyond which adaptation becomes impractical or prohibitively expensive.     

Using Temporal Coherence to Determine the Response to Climate Change in Boreal Shield Lakes

Climate change is expected to have important impacts on aquatic ecosystems. On the Boreal Shield, mean annual air temperatures are expected to increase 2 to 4°C over the next 50 years. An important challenge is to predict how changes in climate and climate variability will impact natural systems so that sustainable management policies can be implemented. To predict responses to complex ecosystem changes associated with climate change, we used long-term biotic databases to evaluate how important elements of the biota in Boreal Shield lakes have responded to past fluctuations in climate. Our long-term records span a two decade period where there have been unusually cold years and unusually warm years. We used coherence analyses to test for regionally operating controls on climate, water temperature, pH, and plankton richness and abundance in three regions across Ontario: the Experimental Lakes Area, Sudbury, and Dorset. Inter-annual variation in air temperature was similar among regions, but there was a weak relationship among regions for precipitation. While air temperature was closely related to lake surface temperatures in each of the regions, there were weak relationships between lake surface temperature and richness or abundance of the plankton. However, inter-annual changes in lake chemistry (i.e., pH) were correlated with some biotic variables. In some lakes in Sudbury and Dorset, pH was dependent on extreme events. For example, El Nino related droughts resulted in acidification pulses in some lakes that influenced phytoplankton and zooplankton richness. These results suggest that there can be strong heterogeneity in lake ecosystem responses within and across regions.     

Modeling distribution changes of vegetation in China under future climate change

Climatic change will result in great changes in vegetation. In this paper, a biogeographical model, the BIOME1, was used to predict potential vegetation distribution in China under climate change. Firstly, the BIOME1 was validated according to the climate–vegetation relationships in China. Kappa statistics showed that the validated BIOME1 was able to capture the geographical patterns of vegetation more accurately. Then, the validated BIOME1 was used to predict the distribution of vegetation of China under two climatic scenarios produced by a Regional Circulation Model, RegCM2/CN. The simulation results showed obvious northward shifts of the boreal, temperate deciduous and evergreen and tropical forests, a large expansion of tropical dry forest/savanna and reduction of tundra on the Tibetan Plateau. Three vulnerable regions sensitive to climate changes are pointed out, i.e., Northern China, the Tibetan Plateau and Southwestern China (mainly Hengduan Mountains in Yunnan Province and west of Sichuan Province). In recent decades, China has experienced dramatic industrialization and population growth, which exert strong pressure on the environment of China. The consequences of climate changes warrant more attention for maintaining a sustainable environment for China.     

Rural poverty driven soil degradation under climate change: the sensitivity of the disposition towards the Sahel Syndrome with respect to climate

Starting from the basic assumption of the syndrome concept that essentially all of the present problematic civilization–nature interactions on the global scale can be subdivided into a limited number of typical patterns, the analysis of the response of these patterns (syndromes) to climate change can make a major contribution to climate impact research, surmounting the difficulties of more common sectoral ceteris paribus impact studies with respect to their systemic integration. In this paper we investigate in particular the influence of climate on the regional proneness or disposition towards one of the most important syndromes with respect to famines and malnutrition, the Sahel Syndrome. It describes the closely interlinked natural and socioeconomic aspects of rural poverty driven degradation of soil and vegetation on marginal sites. Two strategies of global climate impact assessment on a spatial 0.5°×0.5° grid were pursued: (a) As a measure for the climate sensitivity of the regional proneness, the absolute value of the gradient of the disposition with respect to the global field of 3} 12 monthy normals of temperature, irradiation and precipitation is calculated. (b) The disposition was evaluated for two different climate forecasts under doubled atmospheric CO₂ concentration. For both strategies two new quantitative global models were incorporated in a fuzzy-logic-based algorithm for determining the disposition towards the Sahel Syndrome: a neural-net-based model for plant productivity and a waterbalance model which calculates surface runoff considering vertical and lateral fluxes, both driven by the set of 36 monthly climatological normals and designed to allow very fast global numerical evaluation.Calculation (b) shows that the change in disposition towards the Sahel Syndrome crucially depends on the chosen climate forecast, indicating that the disagreement of climate forecasts is propagated to the impact assessment of the investigated socio-economic pattern. On the other hand the regions with a significant increase in disposition in at least one of the climate scenario-based model runs form a subset of the regions which are indicated by the local climate sensitivity study (a) as highly sensitive – illustrating that the gradient measure applied here provides a resonable way to calculate an upper limit or worst case of negative climate impact. This method is particularly valuable in the case of uncertain climate predictions as, e.g., for the change in precipitation patterns.     

Natural climate variability and climate change in the North-Atlantic European region; chance for surprise?

Long-term variability in the North Atlantic Oscillation (NAO) and the Atlantic thermohaline ocean circulation (THC) are both shaping the European climate on time scales of decades and longer. Possible linear and non-linear changes in the characteristics of these natural climate modes due to global warming are an important source of uncertainty in long-term regional projections of future climate changes. This revised version was published online in July 2006 with corrections to the Cover Date.     

Air pollution and forestry in czechoslovakia

One third of the territory of Czechoslovakia is covered by forests. A substantial part of them is damaged in various degrees by air pollution. The air pollution influence on forests developed to a very serious problem during the last 40 years. The main pollutant at present is SO₂ acting directly, but the improtance of soil changes due to acid deposition increases. The consequences are increased mortality and decreased increment in the forests, further consequences are the loss of valuable ecotypes, impact on water management and decreased stability of the landscape. There are limited possibilities of the forest sector to reduce the consequences.Contribution from Fourth World Wilderness Congress—Acid Rain Symposium, Denver (Estes Park), Colorado, September 11–18, 1987.     

Monitoring the Environment: Taking a Historical Perspective

This paper introduces the five papers that follow, all of which were originally presented at a workshop titled Monitoring the Environment: Scales, Methods, and Systems in Historical Perspective. The workshop, sponsored by the Society for the History of Technology and the American Society for Environmental History, examined past efforts to develop tools, methods, and systems for measuring or monitoring some aspect of the physical environment. Four of the papers included here focus on various aspects of air quality monitoring; the fifth has to do with monitoring the earth from space. Despite differences in time period and approach, each article examines how specific tools and methods – and the motivations for developing those tools and methods – evolved. Among other things, these papers make clear that systems for monitoring various aspects of the physical environment are shaped by a variety of stakeholders and suggest that efforts to construct such systems should not be viewed as a purely technical task.     

Recent changes in the montane spruce-fir forests of the northeastern United States

Intensive study of the montane spruce-fir forests of the northeastern United States has been underway since 1980. Crown-vigor assessments, tree-ring studies, and resurveys of plots established in the 1960's have revealed a deterioration of the red spruce populations at high elevations in New England and New York. Forested sites surveyed in the 1960's and 1980's have shown decreases in density and basal area of greater than 50%. Many of these sites have not been logged or cut since settlement times and it is not expected for red spruce, a long-lived species, to undergo such a rapid, widespread decline in basal area and density. The most prominent feature of red spruce decline in the high-elevation forests of the Northeast is the loss of foliage from the tops of the crown down and from the tips of lateral branches in. Winter injury is responsible for this pattern of needle loss and, in some years, browning of needles occurs in early spring and is followed by needle loss by mid-summer. Reports from the 1800's and earlier this century describe a similar occurrence of needle browning but the previous extent and severity of this phenomenon is not known. Climate including adverse winter conditions are in part responsible for the current red spruce decline. The role of air pollution in red spruce decline has not been determined. Foliar nutrient deficiencies may exist in some high-elevation red spruce and their role in red spruce decline is not known either.Contribution from Fourth World Wilderness Congress—Acid Rain Symposium, Denver (Estes Park), Colorado, September 11–18, 1987.     

Modified Whittaker plots as an assessment and monitoring tool for vegetation in a lowland tropical rainforest

Resource exploitation in lowland tropical forests is increasingand causing loss of biodiversity. Effective evaluation and management of the impacts of development on tropical forests requires appropriate assessment and monitoring tools. We proposethe use of 0.1-ha multi-scale, modified Whittaker plots (MWPs) to assess and monitor vegetation in lowland tropical rainforests.We established MWPs at 4 sites to: (1) describe and comparecomposition and structure of the sites using MWPs, (2) compare these results to those of 1-ha permanent vegetation plots (BDPs),and (3) evaluate the ability of MWPs to detect changes in populations (statistical power). We recorded more than 400 species at each site. Species composition among the sites was distinctive, while mean abundance and basal area was similar. Comparisons between MWPs and BDPs show that they record similarspecies composition and abundance and that both perform equallywell at detecting rare species. However, MWPs tend to record morespecies, and power analysis studies show that MWPs were more effective at detecting changes in the mean number of species of trees 10 cm in diameter at breast height (dbh) and in herbaceous plants. Ten MWPs were sufficient to detect a change of 11% in the mean number of herb species, and they were able to detect a 14% change in the mean number of species of trees 10 cm dbh. The value of MWPs for assessment and monitoringis discussed, along with recommendations for improving the sampling design to increase power.     

CO2 Capture and Storage with Leakage in an Energy-Climate Model

Geological CO₂ capture and storage (CCS) is among the main near-term contenders for addressing the problem of global climate change. Even in a baseline scenario, with no comprehensive international climate policy, a moderate level of CCS technology is expected to be deployed, given the economic benefits associated with enhanced oil and gas recovery. With stringent climate change control, CCS technologies will probably be installed on an industrial scale. Geologically stored CO₂, however, may leak back to the atmosphere, which could render CCS ineffective as climate change reduction option. This article presents a long-term energy scenario study for Europe, in which we assess the significance for climate policy making of leakage of CO₂ artificially stored in underground geological formations. A detailed sensitivity analysis is performed for the CO₂ leakage rate with the bottom-up energy systems model MARKAL, enriched for this purpose with a large set of CO₂ capture technologies (in the power sector, industry, and for the production of hydrogen) and storage options (among which enhanced oil and gas recovery, enhanced coal bed methane recovery, depleted fossil fuel fields, and aquifers). Through a series of model runs, we confirm that a leakage rate of 0.1%/year seems acceptable for CCS to constitute a meaningful climate change mitigation option, whereas one of 1%/year is not. CCS is essentially no option to achieve CO₂ emission reductions when the leakage rate is as high as 1%/year, so more reductions need to be achieved through the use of renewables or nuclear power, or in sectors like industry and transport. We calculate that under strict climate control policy, the cumulative captured and geologically stored CO₂ by 2100 in the electricity sector, when the leakage rate is 0.1%/year, amounts to about 45,000 MtCO₂. Only a little over 10,000 MtCO₂ cumulative power-generation-related emissions are captured and stored underground by the end of the century when the leakage rate is 1%/year. Overall marginal CO₂ abatement costs increase from a few €/tCO₂ today to well over 150 €/tCO₂ in 2100, under an atmospheric CO₂ concentration constraint of 550 ppmv. Carbon costs in 2100 turn out to be about 40 €/tCO₂ higher when the annual leakage rate is 1%/year in comparison to when there is no CO₂ leakage. Irrespective of whether CCS deployment is affected by gradual CO₂ seepage, the annual welfare loss in Europe induced by the implementation of policies preventing “dangerous anthropogenic interference with the climate system” (under our assumption, implying a climate stabilisation target of 550 ppmv CO₂ concentration) remains below 0.5% of GDP during the entire century.

PREDICTING CHANGE IN NON-LINEAR SYSTEMS

Complex systems are characterizedby surprising switches to new behaviours. Evaluating and predicting these changes demands anunderstanding of the behaviour of the whole system. The combined ecosystem-climate system shows chaoticor pseudorandom behaviour, stochastic or trulyrandom behaviour, as well as simple bifurcation andsemi-stability. Semistability involves the suddenchange from a destabilized attractor to a newstable attractor which may occur after an apparentlyunpredictable time delay. We present some recentresults for analyzing time series data and for usingsimulations of non-linear models to predict these changes.     

Long-term monitoring for environmental change in U.S. National Parks a watershed approach

The U.S. National Park Service (NPS) is faced with direct questions about the condition of Park natural resources. The watershed approach to long-term monitoring of natural, and remote areas within the National Parks has provided important data for detecting both spacial and temporal changes in environmental conditions. These data collections allow the partitioning of cause and effect relationships of ecological change within a given watershed. They also serve to meet both reference and early warning objectives. Success in advancing a number of acid precipitation goals has demonstrated the usefulness of these integrated watershed data for inter-ecosystem comparison and for analogy between watersheds. The watershed program owing to the NPS experience is proposed as a model for focusing the National Park Service's inventory and monitoring program inititiative. This approach provides to park researchers and resources managers the needed tools for dealing with today's complex local, regional and global natural resources issues.     

Identification and observation of desertification processes with the aid of measurements from space: Results from the European Field Experiment in Desertification-threatened Areas (EFEDA)

The ECHIVAL Field Experiment in Desertification-threatened Areas (EFEDA) addresses the question of desertification from the viewpoint of changing interactions between the land surface and the atmosphere under varying climatic conditions. The basic tool to improve our understandin of these processes are Soil-Vegetation-Atmosphere-Transfer (SVAT) and climate models. In testing techniques for deriving the needed input data from observations from space, EFEDA requires high-precision data sets that can be used to aggregate desertification-related land-surface characteristics into the scale up to the grid width of global climate models (10⁴–10⁵ km²). In this context schemes have been developed to infer from satellite measurements fluxes at the surface. To validate the information inferred from observations in space, ground measurements have been performed on 2500 km² of Castilla-La Mancha, Spain, during the drying periods of the summers of 1991 and 1994. Ultimately EFEDA aims to determine cumulative fluxes over longer periods to allow discrimination between natural variability and trends over large areas, such as the land around the Mediterranean. To recalibrate and adjust the algorithms used to infer information about the land surfaces from satellite measurements, anchor stations are proposed for critical areas to provide collateral information and continuous quality control of inferred information.     

The effects of climate change on landscape diversity: an example in Ontario forests

The predicted increase in climate warming will have profound impacts on forest ecosystems and landscapes in Canada because of increased temperature, and altered disturbance regimes. Climate change is predicted to be variable within Canada, and to cause considerable weather variability among years. Under a 2 × CO₂ scenario, fire weather index (FWI) is predicted to rise over much of Ontario by 1.5 to 2 times. FWI may actually fall slightly, compared to current values, in central eastern Ontario (Abitibi), but for central-south Ontario it is expected to rise sharply by as much as 5 times current values. We predict that the combination of temperature rise and greater than average fire occurrence will result in a shrinkage of area covered by boreal forest towards the north and east; that some form of Great Lakes forest type will occupy most of central Ontario following the 5 C isotherm north; that pyrophilic species will become most common, especially jack pine and aspen; that patch sizes will initially decrease then expand resulting in considerable homogenization of forest landscapes; that there will be little 'old-growth' forest; and that landscape disequilibrium will be enhanced. If climate change occurs as rapidly as is predicted, then some species particularly those with heavy seeds may not be able to respond to the rapid changes and local extinctions are expected. Anthropogenically-altered species compositions in current forests, coupled with fire suppression over the past 50 years, may lead to forest landscapes that are different then were seen in the Holocene period, as described by paleoecological reconstructions. In particular, forests dominated by white pine in the south and black spruce in the middle north may not be common. Wildlife species that respond at the landscape level, i.e., those with body sizes >1 kg, will be most affected by changes in landscape structure. In particular we expect moose and caribou populations to decline significantly, while white-tailed deer will likely become abundant across Ontario and Quebec.     

Climate impact on social systems: the risk assessment approach

A novel approach to the problem of estimating climate impact on social systems is suggested. This approach is based on a risk concept, where the notion of critical events is introduced and the probability of such events is estimated. The estimation considers both the inherent stochasticity of climatic processes and the artificial stochasticity of climate predictions due to scientific uncertainties. The method is worked out in some detail for the regional problem of crop production and the risks associated with global climate change, and illustrated by a case study (Kursk region of the FSU). In order to get local climatic characteristics (weather), a so-called statistical weather generator is used. One interesting finding is that the 3% risk level remains constant up to 1.0–1.1°C rise of mean seasonal temperature, if the variance does not change. On the other hand, the risk grows rapidly with increasing variance (even if the mean temperature rises very slowly). The risk approach is able to separate two problems: (i) assessment of global change impact, and (ii) decision making. The main task for the scientific community is to provide the politicians with different options; the choice of admissible (from the social point of view) critical events and the corresponding risk levels is the business of decision makers.