A Review of Forest Gap Models

Forest gap models, initially conceived in 1969 as a special case of individual-tree based models, have become widely popular among forest ecologists for addressing a large number of applied research questions, including the impacts of global change on long-term dynamics of forest structure, biomass, and composition. However, they have been strongly criticized for a number of weaknesses inherent in the original model structure. In this paper, I review the fundamental assumptions underlying forest gap models, the structure of the parent model JABOWA, and examine these criticisms in the context of the many alternative formulations that have been developed over the past 30 years.Four assumptions originally underlie gap models: (1) The forest is abstracted as a composite of many small patches of land, where each can have a different age and successional stage; (2) patches are horizontally homogeneous, i.e., tree position within a patch is not considered; (3) the leaves of each tree are located in an indefinitely thin layer (disk) at the top of the stem; and (4) successional processes are described on each patch separately, i.e., there are no interactions between patches. These simplifications made it possible to consider mixed-species, mixed-age forests, which had been difficult previously mainly because of computing limitations.The structure of JABOWA is analysed in terms of the functional relationships used for formulating the processes of tree establishment, growth, and mortality. It is concluded that JABOWA contains a number of unrealistic assumptions that have not been questioned strongly to date. At the same time, some aspects of JABOWA that were criticized strongly in the past years are internally consistent given the objectives of this specific model.A wide variety of formulations for growth processes, establishment, and mortality factors have been developed in gap models over the past 30 years, and modern gap models include more robust parameterizations of environmental influences on tree growth and population dynamics as compared to JABOWA. Approaches taken in more recent models that led to the relaxation of one or several of the four basic assumptions are discussed. It is found that the original assumptions often have been replaced by alternatives; however, no systematic analysis of the behavioral effects of these conceptual changes has been attempted to date.The feasibility of including more physiological detail (instead of using relatively simple parameterizations) in forest gap models is discussed, and it is concluded that we often lack the data base to implement such approaches for more than a few commercially important tree species. Hence, it is important to find a compromise between using simplistic parameterizations and expanding gap models with physiology-based functions and parameters that are difficult to estimate. While the modeling of tree growth has received a lot of attention over the past years, much less effort has been spent on improving the formulations of tree establishment and mortality, although these processes are likely to be just as sensitive to global change as tree growth itself. Finally, model validation issues are discussed, and it is found that there is no single data source that can reliably be used for evaluating the behavior of forest gap models; instead, I propose a combination of sensitivity analyses, qualitative examinations of process formulations, and quantitative tests of gap models or selected submodels against various kinds of empirical data to evaluate the usefulness of these models for assessing their utility for predicting the impacts of global change on long-term forest dynamics.     

Comparing the Performance of Forest gap Models in North America

Forest gap models have a long history in the study of forest dynamics, including predicting long-term succession patterns and assessing the potential impacts of climate change and air pollution on forest structure and composition. In most applications, existing models are adapted for the specific question at hand and little effort is devoted to evaluating alternative formulations for key processes, although this has the potential to significantly influence model behavior. In the present study, we explore the implications of alternative formulations for selected ecological processes via the comparison of several gap models. Baseline predictions of forest biomass, composition and size structure generated by several gap models are compared to each other and to measured data at boreal and temperate sites in North America. The models ForClim and LINKAGES v2.0 were compared based on simulations of a temperate forest site in Tennessee, whereas FORSKA-2V, BOREALIS and ForClim were compared at four boreal forest sites in central and eastern Canada. Results for present-day conditions were evaluated on their success in predicting forest cover, species composition, total biomass and stand density, and allocation of biomass among species. In addition, the sensitivity of each model to climatic changes was investigated using a suite of six climate change scenarios involving temperature and precipitation. In the temperate forest simulations, both ForClim and LINKAGES v2.0 predicted mixed mesophytic forests dominated by oak species, which is expected for this region of Tennessee. The models differed in their predictions of species composition as well as with respect to the simulated rates of succession. Simulated forest dynamics under the changed climates were qualitatively similar between the two models, although aboveground biomass and species composition in ForClim was more sensitive to drought than in LINKAGES v2.0. Under a warmer climate, the modeled effects of temperature on tree growth in LINKAGES v2.0 led to the unrealistic loss of several key species. In the boreal forest simulations, ForClim predicted significant forest growth at only the most mesic site, and failed to predict a realistic species composition. In contrast, FORSKA-2V and BOREALIS were successful in simulating forest cover, general species composition, and biomass at most sites. In the climate change scenarios, ForClim was highly sensitive, whereas the other two models exhibited sensitivity only at the drier central Canadian sites. Although the studied sites differ strongly with respect to both the climatic regime and the set of dominating species, a unifying feature emerged from these simulation exercises. The major differences in model behavior were brought about by differences in the internal representations of the seasonal water balance, and they point to an important limitation in some gap model formulations for assessing climate change impacts.     

Tree Species Composition in European Pristine Forests: Comparison of Stand Data to Model Predictions

The degree of general applicability across Europe currently achieved with several forest succession models is assessed, data needs and steps for further model development are identified and the role physiology based models can play in this process is evaluated. To this end, six forest succession models (DISCFORM, ForClim, FORSKA-M, GUESS, PICUS v1.2, SIERRA) are applied to simulate stand structure and species composition at 5 European pristine forest sites in different climatic regions. The models are initialized with site-specific soil information and driven with climate data from nearby weather stations. Predicted species composition and stand structure are compared to inventory data. Similarity and dissimilarity in the model results under current climatic conditions as well as the predicted responses to six climate change scenarios are discussed. All models produce good results in the prediction of the right tree functional types. In about half the cases, the dominating species are predicted correctly under the current climate. Where deviations occur, they often represent a shift of the species spectrum towards more drought tolerant species. Results for climate change scenarios indicate temperature driven changes in the alpine elevational vegetation belts at humid sites and a high sensitivity of forest composition and biomass of boreal and temperate deciduous forests to changes in precipitation as mediated by summer drought. Restricted generality of the models is found insofar as models originally developed for alpine conditions clearly perform better at alpine sites than at boreal sites, and vice versa. We conclude that both the models and the input data need to be improved before the models can be used for a robust evaluation of forest dynamics under climate change scenarios across Europe. Recommendations for model improvements, further model testing and the use of physiology based succession models are made.     

A Comparative Analysis of the Structure and Behavior of Three Gap Models at Sites in Northeastern China

Three gap models, KOPIDE, NEWCOP, and ForClim, were compared with respect to their structure and behavior at four sites along an elevational gradient on Changbai Mt., northeastern China, under current climate and six climate change scenarios. This study intends to compare the three gap models under identical conditions, using a standardized simulation protocol. The three models were originally developed with different backgrounds and for different purposes. While they are relatively similar in the level of structural detail they include, they still differ in many respects regarding the assumptions that are made for representing specific ecological processes.The simulations showed that none of the three gap models provides satisfactory results in all situations; each gap model has strong and weak points in its behavior. While all models are fairly successful in simulating the composition of dominant species along the gradient under current climatic conditions, their projections under a set of hypothetical scenarios of climatic change diverge rather strongly. The analysis of these simulation results shows that several problem areas need to be addressed before any of the models can be used for a reliable impact assessment.Recommendations for improvements of the models are made, including the formulation of temperature and drought effects on tree establishment and tree growth, the size of the species pool, the appropriate choice of patch size and disturbance regimes, and allometric relationships. When aiming to use gap models under new environmental conditions, we propose to carefully reconsider their formulations based on our knowledge of the relevant processes in the region under concern, instead of using the models in an `as-is' mode.     

Simulating the effects of climate changes on Eastern Eurasia forests

The extensive forests of Eastern Eurasia cover an area of ca. 6 million km². The FAREAST model, a forest gap model that simulates the stand composition and dynamics of Eastern Eurasian forests under the current climate, was used to simulate the responses of the Eastern Eurasia Forests to the climate change. Two different scenarios of possible future climatic change were obtained from the IPCC (2001) report (CMIP2 and IS92a-GS) and were used as input to the FAREAST model to determine the compositional and structural sensitivity to climate changes for several locations and along montane elevation gradients. The simulation results suggest that, under the influence of the conditions in the two climate-change scenarios, the underlying forest dynamics should be quite different. Further, Eastern Eurasian forests maintain currents forest structure and biomass only within a small range of climate change. Broad-leaved deciduous trees of such genera as Fraxinus, Quercus and Tilia increase their ranges over Eastern Eurasia under the climate-change scenarios. Conifers, such as Larix and Picea, decrease sharply under climate change and the area of their distributions are reduced. The overall biomass of Pinus is not decreased over the region. While the Pinus distribution range shifts, the area associated with the range of the taxa is not changed.     

Assessing potential impacts of climatic change on subalpine forests on the eastern Tibetan Plateau

Forest gap models have been used widely in the study of forest dynamics, including predicting long-term succession patterns and assessing the potential impacts of climate change on forest structure and composition. However, little effort is devoted to predict forest dynamics in the high elevation areas, although they have the sensitive response to global climate change. In the present study, based on a modified height-diameter function, we developed a new version (FAREAST-GFSM) of the forest patch model, FAREAST for simulating the changes of subalpine forests. The observed data from the Gongga Mt. Alpine Station were also used to test model precision. With the improved performance of FAREAST-GFSM, we explored the impact of three warming scenarios on subalpine forest on the eastern Tibetan plateau within a 100-year period. The study result indicates that the effects of climate change were evident on subalpine forests in the high elevation areas. The response of different species to the warming climate might eventually transform the subalpine Abies fabric forest into Betula utilis forest similar to that which is now widely distributed in the eastern Tibetan Plateau mountainous areas with the relatively lower elevation. Subalpine forests could move to higher and colder areas, which are currently tundra.     

Simulating forest dynamics in a complex topography using gridded climatic data

The forest model ForClim was used to evaluate the applicability of gap models in complex topography when the climatic input data is provided by a global database of 0.5° resolution. The analysis was based on 12 grid cells along an altitudinal gradient in the European Alps. Forest dynamics were studied both under current climate as well as under four prescribed 2 × CO₂ scenarios of climatic change obtained from General Circulation Models, which allowed to assess the sensitivity of mountainous forests to climatic change.Under current climate, ForClim produces plausible patterns of species composition in space and time, although the results for single grid cells sometimes are not representative of reality due to the limited precision of the climatic input data.Under the scenarios of climatic change, three responses of the vegetation are observed, i.e., afforestation, gradual changes of the species composition, and dieback of today's forest. In some cases widely differing species compositions are obtained depending on the climate scenario used, suggesting that mountainous forests are quite sensitive to climatic change. Some of the new forests have analogs on the modern landscape, but in other cases non-analog communities are formed, pointing at the importance of the individualistic response of species to climate.The applicability of gap models on a regular grid in a complex topography is discussed. It is concluded that for their application on a continental scale, it would be desirable to replace the species in the models by plant functional types. It is suggested that simulation studies like the present one must not be interpreted as predictions of the future fate of forests, but as means to assess their sensitivity to climatic change.     

Scaling Issues in Forest Succession Modelling

This paper reviews scaling issues in forest succession modelling, focusing on forest gap models. Two modes of scaling are distinguished: (1) implicit scaling, i.e. taking scale-dependent features into account while developing model equations, and (2) explicit scaling, i.e. using procedures that typically involve numerical simulation to scale up the response of a local model in space and/or time. Special attention is paid to spatial upscaling methods, and downscaling is covered with respect to deriving scenarios of climatic change to drive gap models in impact assessments. When examining the equations used to represent ecological processes in forest gap models, it becomes evident that implicit scaling is relevant, but has not always been fully taken into consideration. A categorization from the literature is used to distinguish four methods for explicit upscaling of ecological models in space: (1) Lumping, (2) Direct extrapolation, (3) Extrapolation by expected value, and (4) Explicit integration. Examples from gap model studies are used to elaborate the potential and limitations of these methods, showing that upscaling to areas as large as 3000 km² is possible, given that there are no significant disturbances such as fires or insect outbreaks at the landscape scale. Regarding temporal upscaling, we find that it is important to consider migrational lags, i.e. limited availability of propagules, if one wants to assess the transient behaviour of forests in a changing climate, specifically with respect to carbon storage and the associated feedbacks to the atmospheric CO₂ content. Regarding downscaling, the ecological effects of different climate scenarios for the year 2100 were compared at a range of sites in central Europe. The derivation of the scenarios is based on (1) imposing GCM grid-cell average changes of temperature and precipitation on the local weather records; (2) a qualitative downscaling technique applied by the IPCC for central and southern Europe; and (3) statistical downscaling relating large-scale circulation patterns to local weather records. Widely different forest compositions may be obtained depending on the local climate scenario, suggesting that the downscaling issue is quite important for assessments of the ecological impacts of climatic change on forests.     

Assessing impacts of climate change on forests: The state of biological modeling

Models that address the impacts of climate change on forests are reviewed at four levels of biological organization: global, regional or landscape, community, and tree. The models are compared for their ability to assess changes in fluxes of biogenic greenhouse gases, land use, patterns of forest type or species composition, forest resource productivity, forest health, biodiversity, and wildlife habitat. No one model can address all of these impacts, but landscape transition models and regional vegetation and land-use models have been used to consider more impacts than the other models. The development of landscape vegetation dynamics models of functional groups is suggested as a means to integrate the theory of both landscape ecology and individual tree responses to climate change. Risk assessment methodologies can be adapted to deal with the impacts of climate change at various spatial and temporal scales. Four areas of research needing additional effort are identified: (1) linking socioeconomic and ecologic models; (2) interfacing forest models at different scales; (3) obtaining data on susceptibility of trees and forest to changes in climate and disturbance regimes; and (4) relating information from different scales.The U.S. Government right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged.Managed by Martin Marietta Energy Systems, Inc., for the U.S. Department of Energy under contract DE-AC05-84OR21400.     

陆地生态系统模型及其与气候模式耦合的回顾

陆地生态系统和气候系统通过能量通量、水汽通量、物质交换相互影响、作用。作者对陆地生态系统模型及其与气候模式耦合的研究进行综述和讨论,总结了当代5类主要全球陆地生态系统模型,即生物地理模型、生物地球化学模型、森林林窗模型、陆面生物圈模型和动态全球植被模型,以及它们与气候模式耦合的研究进展。阐述了动态全球植被模型及其与气候模式耦合研究在全球变化研究的重要作用。最后,对未来模拟研究的方向进行了分析。     

Ungulate herbivory modifies the effects of climate change on mountain forests

Recent temperature observations suggest a general warming trend that may be causing the range of tree species to shift to higher latitudes and altitudes. Since biotic interactions such as herbivory can change tree species composition, it is important to understand their contribution to vegetation changes triggered by climate change. To investigate the response of forests to climate change and herbivory by wild ungulates, we used the forest gap model ForClim v2.9.6 and simulated forest development in three climatically different valleys in the Swiss Alps. We used altitudinal transects on contrasting slopes covering a wide range of forest types from the cold (upper) to the dry (lower) treeline. This allowed us to investigate (1) altitudinal range shifts in response to climate change, (2) the consequences for tree species composition, and (3) the combined effect of climate change and ungulate herbivory. We found that ungulate herbivory changed species composition and that both basal area and stem numbers decreased with increasing herbivory intensity. Tree species responded differently to the change in climate, and their ranges did not change concurrently, thus causing a succession to new stand types. While climate change partially compensated for the reductions in basal area caused by ungulate herbivory, the combined effect of these two agents on the mix of the dominant species and forest type was non-compensatory, as browsing selectively excluded species from establishing or reaching dominance and altered competition patterns, particularly for light. We conclude that there is an urgent need for adaptive forest management strategies that address the joint effects of climate change and ungulate herbivory.     

Application of a forest succession model to a continentality gradient through Central Europe

The forest succession model FORSKA was applied to a west-east transect across Central Europe using points from a global climate data set. Climate change experiments were undertaken for two general circulation model scenarios and two different site classes. The simulated climate changes lead to reduced forest productivity and a changed species composition on most sites. Under current climate, the broad scale pattern of the climatically driven distribution of forest communities is quite realistically reproduced. However, the resolution of climate data imposes limitations on the simulation of forest dynamics in subcontinental climate, because climate variability and extreme events are not well represented.     

Cross-scale ensemble projections of dissolved organic carbon dynamics in boreal forest streams

Climate is an important driver of dissolved organic carbon (DOC) dynamics in boreal catchments characterized by networks of streams within forest-wetland landscape mosaics. In this paper, we assess how climate change may affect stream DOC concentrations ([DOC]) and export from boreal forest streams with a multi-model ensemble approach. First, we apply an ensemble of regional climate models (RCMs) to project soil temperatures and stream-flows. These data are then used to drive two biogeochemical models of surface water DOC: (1) The Integrated Catchment model for Carbon (INCA-C), a detailed process-based model of DOC operating at the catchment scale, and (2) The Riparian Integration Model (RIM), a simple dynamic hillslope scale model of stream [DOC]. All RCMs project a consistent increase in temperature and precipitation as well as a shift in spring runoff peaks from May to April. However, they present a considerable range of possible future runoff conditions with an ensemble median increase of 31 % between current and future (2061–2090) conditions. Both biogeochemical models perform well in describing the dynamics of present-day stream [DOC] and fluxes, but disagree in their future projections. Here, we assess possible futures in three boreal catchments representative of forest, mire and mixed landscape elements. INCA-C projects a wider range of stream [DOC] due to its temperature sensitivity, whereas RIM gives consistently larger inter-annual variation and a wider range of exports due to its sensitivity to hydrological variations. The uncertainties associated with modeling complex processes that control future DOC dynamics in boreal and temperate catchments are still the main limitation to our understanding of DOC mechanisms under changing climate conditions. Novel, currently overlooked or unknown drivers may appear that will present new challenges to modelling DOC in the future.     

Regionally optimized forest management under changing climate

The purpose of this study was to optimize forest management for a forest region (the total area of forest and scrub land 1.54 mill. ha) under changing climate by using the large-scale forestry scenario model MELA and sample plot data from the geo-referenced National Forest Inventory (NFI). The MELA model is based on integrated simulation and optimisation; in the simulation it utilises empirical tree-level models into which the impacts of climate change were introduced by transfer variables derived by using the physiological model FinnFor. Six scenarios with differences in climate and forest management were defined. In simulations, the accelerating tree growth caused by climate change resulted in an increase in maximum sustainable removal of trees at regional level. Changes in regionally optimized forest management were also detected during the analysis period of 30 years; the proportion of thinnings increased because the stands fulfilled the thinning requirements earlier than in the current climate. This study was the first attempt to solve endogenously maximum sustainable timber production and corresponding forest management at the regional level under different climate scenarios. When implemented in the MELA system, which is widely used in Finnish forestry, the transfer variables offer means of disseminating the results from physiological studies to planning of adjustment and mitigation measures under changing climate.     

Relating Tree Physiology to Past and Future Changes in Tropical Rainforest Tree Communities

Predicting future changes in tropical rainforest tree communities requires a good understanding of past changes as well as a knowledge of the physiology, ecology and population biology of extant species. Climate change during the next hundred years will be more similar to climate fluctuations that have occurred in the last few thousand years and of a much smaller magnitude than the extent of climate change experienced during last glaciation or at the Pleistocene–Holocene transition. Unfortunately, the extent to which tropical rainforest tree communities have changed during the last few thousand years has been little investigated. As a consequence we lack the detailed evidence for population and range shifts of individual tropical species resulting from climate change analogous to the evidence available for temperate zone forests. Some evidence suggests that the rate of tropical forest change in the last several thousand years may have been high. If so, then CO₂ increases and the likely alterations in temperature, forest turnover rate, rainfall, or severe droughts may drive substantial future forest change. How can we predict or model the effects of climate change on a highly diverse tree community? Explanations for the regulation of tropical tree populations often invoke tree physiology or processes that are subject to physiological regulation such as herbivory, pathology or seed production. In order to incorporate such considerations into climate change models, the physiology of a very diverse tree community must be understood. My work has focused on simplifying this diversity by categorizing the shade-tolerant species into functional physiological groups. Most species and most individual trees are shade-tolerant species, gap-requiring species being relatively uncommon. Additionally, in a regenerating gap most of the individuals are shade-tolerant species that established before gap formation. Despite the fact that the shade-tolerant species are of major ecological importance, their comparative physiology has received little attention. I have found that shade-tolerant species differ substantially in their responses to light flecks, treefall light gaps and drought. Furthermore, among phylogenetically unrelated species, these differences in physiology can be predicted from leaf lifetime. These results provide a general framework for understanding the mechanics of tropical rainforests from a physiological perspective that can be used to model their responses to climate change.     

Aboveground Growth and Competition in Forest Gap Models: An Analysis for Studies of Climatic Change

Gap models have been used extensively in ecological studies of forest structure and succession, and they should be useful tools for studying potential responses of forests to climatic change. There is a wide variety of gap models with different degrees of physiological detail, and the manner in which the effects of climatic factors are analyzed varies across that range of detail. Here we consider how well the current suite of gap models can accommodate climatic-change issues, and we suggest what physiological attributes and responses should be added to better represent responses of aboveground growth and competition. Whether a gap model is based on highly empirical, aggregated growth functions or more mechanistic expressions of carbon uptake and allocation, the greatest challenge will be to express allocation correctly. For example, incorporating effects of elevated CO₂ requires that the fixed allometry between stem volume and leaf area be made flexible. Simulation of the effects of climatic warming should incorporate the possibility of a longer growing season and acclimation of growth processes to changing temperature. To accommodate climatic-change factors, some of the simplicity of gap models must be sacrificed by increasing the amount of physiological detail, but it is important that the capability of the models to predict competition and successional dynamics not be sacrificed.     

Stability Analysis of the Climate-Vegetation System in the Northern High Latitudes

The stability of the climate-vegetation system in the northern high latitudesis analysed with three climate system models of different complexity: A comprehensive 3-dimensional model of the climate system, GENESIS-IBIS, and two Earth system models of intermediate complexity (EMICs), CLIMBER-2 andMoBidiC. The biogeophysical feedback in the latitudinal belt 60–70° N, although positive, is not strong enough to support multiple steady states: A unique equilibriumin the climate-vegetation system is simulated by all the models on a zonal scale for present-day climate and doubled CO₂ climate.EMIC simulations with decreased insolation also reveal a unique steady state. However, the climate sensitivity to tree cover, T_F, exhibits non-linear behaviour within the models. For GENESIS-IBIS and CLIMBER-2, T_F islower for doubled CO₂ climate than for present-day climate due to a shorter snow season and increased relative significance ofthe hydrological effect of forest cover. For the EMICs, T_F is higher for low tree fraction than for high treefraction, mainly due to a time shift in spring snow melt in response to changes in tree cover. The climate sensitivity to tree coveris reduced when thermohaline circulation feedbacks are accounted for in the EMIC simulations. Simpler parameterizations of oceanic processes have opposite effects on T_F: T_F is lower in simulations with fixed SSTs and higher in simulations with mixed layer oceans. Experiments with transient CO₂ forcing show climate and vegetation not in equilibrium in the northern high latitudes at the end of the 20thcentury. The delayed response of vegetation and accelerated global warming lead to rather abrupt changes in northern vegetation cover in the first halfof the 21st century, when vegetation cover changes at double the present day rate.     

Modeling the Effects of Global Climatic Change at the Ecotone of Boreal Larch Forest and Temperate Forest in Northeast China

The dynamics of the forest at the ecotone of the boreal forest and temperate forest in Northeast China were simulated using the adapted gap model BKPF under global climatic change (GFDL scenario) and doubled CO₂ concentrations at 50 years in the future. The response of tree species and species with similar biological characteristics under global climate change and double CO₂ concentrations were based on biophysical limits of the tree species in the area and their biological competition. The results showed that after 50 years the stand density and LAI (leaf area index) of the forest growing from a clear-cut would not be significantly different from those under current conditions. Stand productivity would increase about 7%, and stand aboveground biomass would increase 15%. However, the stand density of the current mature forest would be reduced by more than 20%. The stand would be dominated by Quercus mongolica Fisch., Populus davidiana Dode., Betula spp. and other broadleaved tree species, and Quercus mongolica would account for about 50% of the total density. The stand biomass would be reduced by more than 90%. Quercus mongolica would comprise about 57% of the total stand biomass. The stand productivity would not change significantly, but it would be comprised mainly of Quercus mongolica, Populus davidiana, Betula spp. The current stand height would decrease slightly. The stand LAI would decline dramatically, moreover, Quercus mongolica would comprise about 50% of the stand LAI.     

Evaluating the Tree Population Density and Its Impacts in CLM-DGVM

Vegetation population dynamics play an essential role in shaping the structure and function of terrestrial ecosystems.However,large uncertainties remain in the parameterizations of population dynamics in current Dynamic Global Vegetation Models(DGVMs).In this study,the global distribution and probability density functions of tree population densities in the revised Community Land Model-Dynamic Global Vegetation Model(CLM-DGVM) were evaluated,and the impacts of population densities on ecosystem characteristics were investigated.The results showed that the model predicted unrealistically high population density with small individual size of tree PFTs(Plant Functional Types) in boreal forests,as well as peripheral areas of tropical and temperate forests.Such biases then led to the underestimation of forest carbon storage and incorrect carbon allocation among plant leaves,stems and root pools,and hence predicted shorter time scales for the building/recovering of mature forests.These results imply that further improvements in the parameterizations of population dynamics in the model are needed in order for the model to correctly represent the response of ecosystems to climate change.     

Sea‐ice dynamics and CO2 sensitivity in a global climate model

Abstract

Present‐day results and CO₂ sensitivity are described for two versions of a global climate model (genesis) with and without sea‐ice dynamics. Sea‐ice dynamics is modelled using the cavitating‐fluid method of Flato and Hibler (1990, 1992). The atmospheric general circulation model originated from the NCAR Community Climate Model version 1, but is heavily modified to include new treatments of clouds, penetrative convection, planetary boundary‐layer mixing, solar radiation, the diurnal cycle and the semi‐Lagrangian transport of water vapour. The surface models include an explicit model of vegetation (similar to BATS and SiB), multilayer models of soil, snow and sea ice, and a slab ocean mixed layer.

When sea‐ice dynamics is turned off, the CO₂‐induced warming increases drastically around ～60–80°S in winter and spring. This is due to the much greater (and unrealistic) compactness of the Antarctic ice cover without dynamics, which is reduced considerably when CO₂ is doubled and exposes more open ocean to the atmosphere. With dynamics, the winter ice is already quite dispersed for 1 × CO₂ so that its compactness does not decrease as much when CO₂ is doubled.