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1.
Comparing the Performance of Forest gap Models in North America   总被引：6，自引：0，他引：6  
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.  相似文献   

2.
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.  相似文献   

3.
A comparison of forest gap models: Model structure and behaviour   总被引：4，自引：0，他引：4  
Forest gap models share a common structure for simulating tree population dynamics, and many models contain the same or quite similar ecological factors. However, a wide variety of formulations are being used to implement this general structure. The comparison of models incorporating different formulations is important for model validation, for assessing the reliability of model projections obtained under scenarios of climatic change, and for the development of models with a wide range of applicability. This paper reviews qualitative and quantitative comparisons of the structure and behaviour of forest gap models.As examples of qualitative model comparisons, the different formulations used for the heightdiameter relationship, for the maximum growth equation, and for the effects of temperature and drought on tree growth are reviewed. The variety of formulations currently in use has the potential to influence simulation results considerably, but we conclude that little is known on the sensitivity of the models in this respect.The quantitative model comparisons performed so far allow us to draw the following conclusions: (1) Gap models are quite sensitive to the formulation of climate-dependent processes under current climate, and this sensitivity is even more pronounced under a changed climate. (2) Adaptations of forest gap models to specific regions have required detailed sub-models of species life history, thus complicating model comparison. (3) Some of the complex models developed for region-specific applications can be simplified without hampering the realism with which they simulate species composition. (4) Attempts to apply the models without modification beyond the area for which they were developed have produced controversial results.It is concluded that the sensitivity of forest gap models to the exact process formulations should be examined carefully, and that more systematic comparisons of model behaviour at a range of test sites would be desirable. Such studies could improve our understanding of forest dynamics considerably, and they would help to focus future research activities with gap models.  相似文献   

4.
Assessments of the impacts of global change on carbon stocks in mountain regions have received little attention to date, in spite of the considerable role of these areas for the global carbon cycle. We used the regional hydro-ecological simulation system RHESSys in five case study catchments from different climatic zones in the European Alps to investigate the behavior of the carbon cycle under changing climatic and land cover conditions derived from the SRES scenarios of the IPCC. The focus of this study was on analyzing the differences in carbon cycling across various climatic zones of the Alps, and to explore the differences between the impacts of various SRES scenarios (A1FI, A2, B1, B2), and between several global circulation models (GCMs, i.e., HadCM3, CGCM2, CSIRO2, PCM). The simulation results indicate that the warming trend generally enhances carbon sequestration in these catchments over the first half of the twenty-first century, particularly in forests just below treeline. Thereafter, forests at low elevations increasingly release carbon as a consequence of the changed balance between growth and respiration processes, resulting in a net carbon source at the catchment scale. Land cover changes have a strong modifying effect on these climate-induced patterns. While the simulated temporal pattern of carbon cycling is qualitatively similar across the five catchments, quantitative differences exist due to the regional differences of the climate and land cover scenarios, with land cover exerting a stronger influence. The differences in the simulations with scenarios derived from several GCMs under one SRES scenario are of the same magnitude as the differences between various SRES scenarios derived from one single GCM, suggesting that the uncertainty in climate model projections needs to be narrowed before accurate impact assessments under the various SRES scenarios can be made at the local to regional scale. We conclude that the carbon balance of the European Alps is likely to shift strongly in the future, driven mainly by land cover changes, but also by changes of the climate. We recommend that assessments of carbon cycling at regional to continental scales should make sure to adequately include sub-regional differences of changes in climate and land cover, particularly in areas with a complex topography.  相似文献   

5.
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.  相似文献   

6.
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.  相似文献   

7.
The response of plant species to future climate conditions is probably dependent on their ecological characteristics, including climatic niche, demographic rates and functional traits. Using forest inventory data from 27 dominant woody species in Spanish forests, we explore the relationships between species characteristics and projected changes in their average climatic suitability (occurrence of suitable climatic conditions for a species in a given territory) obtained by empirical niche-based models, under a business-as-usual climate change scenario (A1, HadCM3, 2001–2100). We hypothesize that most species will suffer a decline in climatic suitability, with a less severe for species (i) currently living in more arid climates or exhibiting a broader current climatic niche; (ii) with higher current growth rates; (iii) with functional traits related to resistance to water deficits. The analysis confirm our hypothesis since apart from a few Mediterranean species, most species decrease their climatic suitability in the region under future climate, characterized by increased aridity. Also, species living in warmer locations or under a wider range of climatic conditions tend to experience less decrease in climatic suitability. As hypothesized, a positive relationship was detected between current relative growth rates and increase in future climatic suitability. Nevertheless, current tree mortality did not correlate with changes in future climatic suitability. In contrast with our hypothesis, functional traits did not show a clear relationship with changes in climate suitability; instead species often presented idiosyncratic responses that, in some cases, could reflect past management. These results suggest that the extrapolation of species performance to future climatic scenarios based on current patterns of dominance is constrained by factors other than species autoecology, particularly human activity.  相似文献   

8.
The likely effects on two tree species of a range of scenarios of climatic and atmospheric change expected by the year 2050 are investigated using a climatic mapping program, a simple simulation model and a process-based simulation model. Styrax tonkinensis is a native species for which relatively little information is available. Acacia mangium is an introduced species, which is important for pulp production in several other countries, and for which there is considerable information for growth and utilization. A climatic mapping program is used to show areas which may be suitable for these species under present and predicted conditions. Two simulation models are used to investigate likely effects on productivity of the two species for a range of climatic change scenarios for Hanoi and Ho Chi Minh City. The estimated changes in production are predicted to be relatively small, though uncertainities associated with the simulations are quite high. However, the models highlight areas where more data are needed and also suggest some key regions in Vietnam which would be worth monitoring to detect early signs of the effects of climatic and atmospheric change.  相似文献   

9.
Regional climate models are major tools for regional climate simulation and their output are mostly used for climate impact studies. Notes are reported from a series of numerical simulations of summer rainfall in China with a regional climate model. Domain sizes and running modes are major foci. The results reveal that the model in forecast mode driven by "perfect" boundaries could reasonably represent the inter-annual differences: heavy rainfall along the Yangtze River in 1998 and dry conditions in 1997. Model simulation in climate mode differs to a greater extent from observation than that in forecast mode. This may be due to the fact that in climate mode it departs further from the driving fields and relies more on internal model dynamical processes. A smaller domain in climate mode outperforms a larger one. Further development of model parameterizations including dynamic vegetation are encouraged in future studies.  相似文献   

10.
This study examines the sensitivity of maize and sorghum crops to global warming in Botswana, a country with arid climatic conditions and shortfalls in locally produced grain. The vulnerability of the maize and sorghum crops to climate change were studied using crop simulation models while climate change scenarios were generated from Global Circulation Models. Simulated yields indicated that rain-fed crop production under the observed climate was a small fraction of what could be produced under optimal conditions. The gap was attributed to both physical (especially lack of rain) and socio-economic constraints. Using the southern African core climate change scenario, simulated yields declined by 36% in the case of maize and 31% for sorghum in the sand veldt region. Yield reductions from thehard veldt region were in the order of 10% for both maize and sorghum. The growing season became shorter, the average reduction in days in the sand veldt region being 5 and 8 days for maize and sorghum respectively, and correspondingly, 3 and 4 days over the hard veldt region. The food security option currently followed in Botswana was found to be a good adaptive strategy under a changed climate.  相似文献   

11.
The article proposes the method of climatic forecast of the occurrence frequency of synoptic conditions causing severe hydrometeorological events as well as severe events that are genetically related to them, in particular, storm wind waves. The choice of sea level pressure field as an indicator of atmospheric conditions of storm waves is substantiated. The algorithm for the method implementation is developed. It includes the processing of observational/reanalysis data; wind wave simulation; the systematization of synoptic conditions that accompany storm waves under the modern climate; the assessment of the ability of climate models of atmospheric and oceanic general circulation to simulate correctly the frequency of the revealed types of synoptic conditions for the modern climate; and the forecast of the frequency of these types for the possible scenarios of the future climate.  相似文献   

12.
An investigation is made of the possible impacts of a climatic change (induced by a doubling of atmospheric carbon dioxide concentration) on the European agricultural sector. Two general circulation models have been used to develop climatic change scenarios for the European study area. From the scenarios, information was obtained concerning the possible behavior of temperature, precipitation, solar radiation, and relative humidity in the altered climatic state. This meteorological information was then employed in two separate crop-weather models - an empirical/statistical model (for winter wheat) and a simple simulation model (for biomass potential). This type of approach represents a considerable departure from that employed by previous large-scale climate impact studies. Both the seasonal and regional components of a possible climatic change are incorporated directly in the two crop-weather models. The results of this investigation demonstrate that a simple crop-weather simulation model may be more suitable for the purposes of agricultural impact analysis than the linear regression models frequently used in such studies. In order for such an impact analysis to be accepted as a valid scientific experiment, a full presentation of the underlying assumptions and uncertainties is essential.  相似文献   

13.
气候变化情景生成技术研究综述   总被引：8，自引：0，他引：8  
吴金栋  王馥棠 《气象》1998,24(2):3-8
简单回顾了气候变化对农业生产影响研究的进展,分析了气候变化情景生成技术研究的必要性,即影响模式与ＧＣＭｓ的嵌套困难及对气候变率和产量变率的认识。指出该技术是目前这一领域研究的关键所在。  相似文献   

14.
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15.
Scaling Issues in Forest Succession Modelling   总被引：5，自引：0，他引：5  
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.  相似文献   

16.
利用5个全球气候模式和中国东北地区162个站点地面温度实测资料,评估全球气候模式和多模式集合平均对中国东北地区地面温度的模拟能力,并对SRES B1、A1B和A2排放情景下,中国东北地区未来地面温度变化进行预估。结果表明：全球气候模式能够较好地再现了东北地区地面温度的年变化和空间分布特征,但存在系统性冷偏差,模式对夏季地面温度模拟偏低1.16 ℃,优于冬季。预估结果表明,3种排放情景下21世纪中期和末期东北地区地面温度均将升高,末期增幅高于中期,冬季增幅高于其他季节, SRES A2排放情景下增幅最大,B1排放情景下最小;增温幅度自南向北逐渐增大,增温最显著地区位于黑龙江小兴安岭;21世纪末期3种情景下中国东北地区年平均地面温度将分别升高2.39 ℃(SRES B1)、3.62 ℃(SRES A1B)和4.43 ℃(SRES A2)。  相似文献   

17.
One strand of research relates the magnitude of severe weather disasters to climatic and human development factors; another highlights dramatic growth in catastrophe losses. However, there have been few attempts to put the two strands together. Here we use an explicit modeling framework to determine the contribution of climate variability relative to human factors in reported catastrophe losses. We then examine how future climate change can be expected to affect losses from natural disasters. Simultaneous regression models are constructed from three equations in which the dependent variables are U.S. flood loss, U.S. hurricane loss and U.S. catastrophe loss. Then two kinds of simulation under two climate change scenarios explore how climate change would affect losses. The climate change scenarios respectively project 13.5% and 21.5% increases in annual precipitation. The first simulation increases only the mean value of annual precipitation; the second simulation assumes that the mean and standard deviation of annual precipitation change in the same proportion. Results show that the growth in reported losses from weather-related natural disasters is due mainly to three socioeconomic factors: inflation, population growth and growth in per capita real wealth. However, weather variables such as precipitation and the number of hurricanes per period also clearly affect losses. The three stage least squares (3SLS) simultaneous equation model shows that a 1% increase in annual precipitation would enlarge catastrophe loss by as much as 2.8%. These findings are suggestive as planning signals to decision makers.  相似文献   

18.
During this century global warming will lead to changes in global weather and climate, affecting many aspects of our environment. Agriculture is the sector of the United States economy most likely to be directly impacted by climatic changes. We have examined potential changes in dryland agriculture (Part 3) and in water resources necessary for crop production (Part 4) in response to a set of climate change scenarios. In this paper we assess to what extent, under these same scenarios, water supplies will be sufficient to meet the irrigation requirement of major grain crops in the US. In addition, we assess the overall impacts of changes in water supply on national grain production. We apply the 12 climate change scenarios described in Part 1 to the water resources and crop growth simulation models described in Part 2 for the conterminous United States. Drawing on data from Parts 3 and 4 we calculate what the aggregate national production would be in those regions in which grain crops are currently produced by applying irrigation where needed and water supplies allow. The total amount of irrigation water applied to crops declines under all climate change scenarios employed in this study. Under certain of the scenarios and in particular regions, precipitation decreases so much that water supplies are too limited; in other regions precipitation becomes so plentiful that little value is derived from irrigation. Nationwide grain crop production is greater when irrigation is applied as needed. Under irrigation, less corn and soybeans are produced under most of the climate change scenarios than is produced under baseline climate conditions. Winter wheat production under irrigation responds significantly to elevated atmospheric carbon dioxide concentrations [CO2] and appears likely to increase under climate change.  相似文献   

19.
This special issue of Climatic Change describes an effort to improve methodology for integrated assessment of impacts and consequences of climatic change. Highlights of the seven foregoing Parts (papers) that constitute this special issue are summarized here. The methodology developed involves construction of scenarios of climate change that are used to drive individual sectoral models for simulating impacts on crop production, irrigation demand, water supply and change in productivity and geography of unmanaged ecosystems. Economic impacts of the changes predicted by integrating the results of the several sectoral simulation models are calculated through an agricultural land-use model. While these analyses were conducted for the conterminous United States alone, their global implications are also considered in this summary as is the need for further improvements in integrated assessment methodology.  相似文献   

20.
Evaluating the response of climate to greenhouse gas forcing is a major objective of the climate community, and the use of large ensemble of simulations is considered as a significant step toward that goal. The present paper thus discusses a new methodology based on neural network to mix ensemble of climate model simulations. Our analysis consists of one simulation of seven Atmosphere–Ocean Global Climate Models, which participated in the IPCC Project and provided at least one simulation for the twentieth century (20c3m) and one simulation for each of three SRES scenarios: A2, A1B and B1. Our statistical method based on neural networks and Bayesian statistics computes a transfer function between models and observations. Such a transfer function was then used to project future conditions and to derive what we would call the optimal ensemble combination for twenty-first century climate change projections. Our approach is therefore based on one statement and one hypothesis. The statement is that an optimal ensemble projection should be built by giving larger weights to models, which have more skill in representing present climate conditions. The hypothesis is that our method based on neural network is actually weighting the models that way. While the statement is actually an open question, which answer may vary according to the region or climate signal under study, our results demonstrate that the neural network approach indeed allows to weighting models according to their skills. As such, our method is an improvement of existing Bayesian methods developed to mix ensembles of simulations. However, the general low skill of climate models in simulating precipitation mean climatology implies that the final projection maps (whatever the method used to compute them) may significantly change in the future as models improve. Therefore, the projection results for late twenty-first century conditions are presented as possible projections based on the “state-of-the-art” of present climate modeling. First, various criteria were computed making it possible to evaluate the models’ skills in simulating late twentieth century precipitation over continental areas as well as their divergence in projecting climate change conditions. Despite the relatively poor skill of most of the climate models in simulating present-day large scale precipitation patterns, we identified two types of models: the climate models with moderate-to-normal (i.e., close to observations) precipitation amplitudes over the Amazonian basin; and the climate models with a low precipitation in that region and too high a precipitation on the equatorial Pacific coast. Under SRES A2 greenhouse gas forcing, the neural network simulates an increase in precipitation over the La Plata basin coherent with the mean model ensemble projection. Over the Amazonian basin, a decrease in precipitation is projected. However, the models strongly diverge, and the neural network was found to give more weight to models, which better simulate present-day climate conditions. In the southern tip of the continent, the models poorly simulate present-day climate. However, they display a fairly good convergence when simulating climate change response with a weak increase south of 45°S and a decrease in Chile between 30 and 45°S. Other scenarios (A1B and B1) strongly resemble the SRES A2 trends but with weaker amplitudes.  相似文献   

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