Evaluation of habitat sustainability and vulnerability for beech (Fagus crenata) forests under 110 hypothetical climatic change scenarios in Japan

Questions: Are there any sustainable or vulnerable habitats in which beech (Fagus crenata) forests could survive in Japan under 110 hypothetical climate change scenarios? Location: Six islands of Japan on which beech grows naturally. Methods: An ecological habitat model was used to simulate the potential habitat shifts of beech forests under 110 climate change scenarios. The amount of suitable habitat loss and gain was calculated with three migration options and risk surfaces. Vulnerable and sustainable habitats were identified to evaluate the potential risks and survival of beech forests. Results: The total areas of potential suitable habitats differed considerably depending on the future temperature and precipitation changes. Some areas on the Sea of Japan (SOJ) side showed higher probability of maintaining suitable habitats, whereas there were wider areas in which suitable habitats could not persist under any of the 110 climate change scenarios. Conclusions: The risk surfaces of the suitable habitats showed that decreases in precipitation along with increases in temperature reduced the total areas of suitable habitats. Increases in precipitation with increases in temperature of more than or equal to 2°C always reduce the areas of suitable habitats. Under increased precipitation with a temperature increase of <2°C, the areas of suitable habitats showed an increase, maintenance of the status quo or a decrease, depending on the size of the increase in precipitation. Beech forests in western Japan are predicted to be vulnerable to climate change, whereas some mountains on the SOJ side are predicted to be possible future refugia.     

Influence of bioclimatic variables on tree-line conifer distribution in the Greater Yellowstone Ecosystem: implications for species of conservation concern

Aim Tree‐line conifers are believed to be limited by temperature worldwide, and thus may serve as important indicators of climate change. The purpose of this study was to examine the potential shifts in spatial distribution of three tree‐line conifer species in the Greater Yellowstone Ecosystem under three future climate‐change scenarios and to assess their potential sensitivity to changes in both temperature and precipitation. Location This study was performed using data from 275 sites within the boundaries of Yellowstone and Grand Teton national parks, primarily located in Wyoming, USA. Methods We used data on tree‐line conifer presence from the US Forest Service Forest Inventory and Analysis Program. Climatic and edaphic variables were derived from spatially interpolated maps and approximated for each of the sites. We used the random‐forest prediction method to build a model of predicted current and future distributions of each of the species under various climate‐change scenarios. Results We had good success in predicting the distribution of tree‐line conifer species currently and under future climate scenarios. Temperature and temperature‐related variables appeared to be most influential in the distribution of whitebark pine (Pinus albicaulis), whereas precipitation and soil variables dominated the models for subalpine fir (Abies lasiocarpa) and Engelmann spruce (Picea engelmannii). The model for whitebark pine substantially overpredicted absences (as compared with the other models), which is probably a result of the importance of biological factors in the distribution of this species. Main conclusions These models demonstrate the complex response of conifer distributions to changing climate scenarios. Whitebark pine is considered a ‘keystone’ species in the subalpine forests of western North America; however, it is believed to be nearly extinct throughout a substantial portion of its range owing to the combined effects of an introduced pathogen, outbreaks of the native mountain pine beetle (Dendroctonus ponderosae), and changing fire regimes. Given predicted changes in climate, it is reasonable to predict an overall decrease in pine‐dominated subalpine forests in the Greater Yellowstone Ecosystem. In order to manage these forests effectively with respect to future climate, it may be important to focus attention on monitoring dry mid‐ and high‐elevation forests as harbingers of long‐term change.     

Climate-induced changes in the vegetation pattern of China in the 21st century

Quantifying climate-induced changes in vegetation patterns is essential to understanding land–climate interactions and ecosystem changes. In the present study, we estimated various distributional changes of vegetation under different climate-change scenarios in the 21st century. Both hypothetical scenarios and Hedley RCM scenarios show that the transitional vegetation types, such as shrubland and grassland, have higher sensitivity to climatic change compared to vegetation under extreme climatic conditions, such as the evergreen broadleaf forest or desert, barren lands. Mainly, the sensitive areas in China lie in the Tibetan Plateau, Yunnan-Guizhou Plateau, northeastern plain of China and eco-zones between different vegetations. As the temperature increases, mixed forests and deciduous broadleaf forests will shift towards northern China. Grassland, shrubland and wooded grassland will extend to southeastern China. The RCM-project climate changes generally have caused positive vegetation changes; vegetation cover will probably improve 19% relative to baseline, and the forest will expand to 8% relative to baseline, while the desert and bare ground will reduce by about 13%.     

Modelling potential impacts of climate change on the spatial distribution of zonal forest communities in Switzerland

Abstract. A spatially explicit, climate-sensitive vegetation model is presented to simulate both present and future distribution of potential natural vegetation types in Switzerland at the level of zonal forest communities. The model has two versions: (1) a ‘basic’ version using geographical region, aspect, bedrock (represented by soil pH), and elevation, and (2) a ‘climate-sensitive’ version obtained by replacing elevation (complex environmental gradient) with temperature (climatic factor). Version 2 is used to predict vegetation response under different (today's and projected) climatic conditions. Two regional climate scenarios are applied: (1) assuming an annual mean temperature increase of 1.1 — 1.4 °C, and (2) assuming an increase of 2.2 — 2.75 °C. Both scenarios result in significant changes of the spatial vegetation patterns as compared with today's climatic conditions. In scenario 1, ca. 33 % of the sample points remain unchanged in terms of the simulated zonal forest community; in scenario 2, virtually all sample points change. The most noticeable changes occur on the Swiss Plateau with Carpinion forests (zonal vegetation of present colline belt) expanding to areas that are occupied today by submontane and low-montane Fagus forests. To estimate the reliability of the simulation, quantitative (comparison with field mapping) and qualitative (comparison with climate types in the Alpine region) tests are performed and the main limitations of the approach are evaluated.     

Potential Changes in Tree Species Richness and Forest Community Types following Climate Change

Potential changes in tree species richness and forest community types were evaluated for the eastern United States according to five scenarios of future climate change resulting from a doubling of atmospheric carbon dioxide (CO₂). DISTRIB, an empirical model that uses a regression tree analysis approach, was used to generate suitable habitat, or potential future distributions, of 80 common tree species for each scenario. The model assumes that the vegetation and climate are in equilibrium with no barriers to species migration. Combinations of the individual species model outcomes allowed estimates of species richness (from among the 80 species) and forest type (from simple rules) for each of 2100 counties in the eastern United States. Average species richness across all counties may increase slightly with climatic change. This increase tends to be larger as the average temperature of the climate change scenario increases. Dramatic changes in the distribution of potential forest types were modeled. All five scenarios project the extirpation of the spruce–fir forest types from New England. Outputs from only the two least severe scenarios retain aspen–birch, and they are largely reduced. Maple–beech–birch also shows a large reduction in area under all scenarios. By contrast, oak–hickory and oak–pine types were modeled to increase by 34% and 290%, respectively, averaged over the five scenarios. Although many assumptions are made, these modeled outcomes substantially agree with a limited number of predictions from researchers using paleoecological data or other models. Received 12 May 2000; accepted 20 October 2000.     

Future hydrological constraints of the Montseny brook newt (Calotriton arnoldi) under changing climate and vegetation cover

The Montseny brook newt (Calotriton arnoldi) is a critically endangered amphibian species which inhabits a small 20 km² holm oak and beech forest area in NE Spain. Calotriton arnoldi strictly lives in running waters and might be highly vulnerable to hydrological perturbations expected to occur under climate and vegetation cover changes. Knowledge about the potential response of the species habitat to environmental changes can help assessing the actions needed for its conservation. Based on knowledge of the species and supported by observations, we proposed daily low and high streamflow event thresholds for the viability of C. arnoldi. We used the rainfall–runoff model PERSiST to simulate changes in the frequency and duration of these events, which were predicted under two climate and four vegetation cover scenarios for near‐future (2031–2050) and far‐future (2081–2100) periods in a reference catchment. All future scenarios projected a significant decrease in annual streamflow (from 21% to as much as 67%) with respect to the reference period. The frequency and length of low streamflow events will dramatically increase. In contrast, the risk of catastrophic drift linked to high streamflow events was predicted to decrease. The potential change in vegetation toward an expansion of holm oak forests will be more important than climate changes in determining threshold low flow conditions. We thus demonstrated that consideration of potential changes in vegetation and not only changes in climate variables is essential in simulating future streamflows. This study shows that future low streamflow conditions will pose a severe threat for the survival of C. arnoldi and may help taking management actions, including limiting the expansion of holm oak forest, for ameliorating the species habitat and help its conservation.     

土地利用约束下中国东部南北样带生产力和植被分布对全球变化的响应

对现有的区域植被动态模拟模型进行了改进,使之包含了土地利用分布格局对植被和生态系统相关过程的影响。改进后的模型被用地研究中国东部南北样带(NSTEC)植被和净第一性生产力对未来气候变化的响应。模拟结果显示土地利用格局对未来气候条件下植被分布的变迁和生产力形成过程有非常显著的影响。与没有土地利用约束的情形相比较,土地利用作为限制条件缓减了植被类型之间的竞争,从而减少了模拟的样带区域内常绿阔叶林,但增加了模拟灌木和草地的分布。土地利用约束使得模拟得到的当前条件下的净第一性生产力更为接近实际情况,且未来气候条件下的生产力改变量更为可信。对未来CO2倍增条件下7个大气环流模型预测的气候情景的模拟结果表明：落叶阔叶林将显著增加,但针叶林、灌木和草原的分布将下降。未来气候条件下NSTEC样带的净第一性生产力总量将增加。预测样带北部的净第一性生产力的变化范围大于样带南部。温度变化比降水变化对样带的生产力具有更强的控制。     

Simulating effects of changing climate and CO2 emissions on soil carbon pools at the Hubbard Brook experimental forest

Carbon (C) sequestration in forest biomass and soils may help decrease regional C footprints and mitigate future climate change. The efficacy of these practices must be verified by monitoring and by approved calculation methods (i.e., models) to be credible in C markets. Two widely used soil organic matter models – CENTURY and RothC – were used to project changes in SOC pools after clear‐cutting disturbance, as well as under a range of future climate and atmospheric carbon dioxide (CO₂) scenarios. Data from the temperate, predominantly deciduous Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, were used to parameterize and validate the models. Clear‐cutting simulations demonstrated that both models can effectively simulate soil C dynamics in the northern hardwood forest when adequately parameterized. The minimum postharvest SOC predicted by RothC occurred in postharvest year 14 and was within 1.5% of the observed minimum, which occurred in year 8. CENTURY predicted the postharvest minimum SOC to occur in year 45, at a value 6.9% greater than the observed minimum; the slow response of both models to disturbance suggests that they may overestimate the time required to reach new steady‐state conditions. Four climate change scenarios were used to simulate future changes in SOC pools. Climate‐change simulations predicted increases in SOC by as much as 7% at the end of this century, partially offsetting future CO₂ emissions. This sequestration was the product of enhanced forest productivity, and associated litter input to the soil, due to increased temperature, precipitation and CO₂. The simulations also suggested that considerable losses of SOC (8–30%) could occur if forest vegetation at HBEF does not respond to changes in climate and CO₂ levels. Therefore, the source/sink behavior of temperate forest soils likely depends on the degree to which forest growth is stimulated by new climate and CO₂ conditions.     

土地利用约束下中国东部南北样带生产力和植被分布对全球变化的响应

对现有的区域植被动态模拟模型进行了改进,使之包含了土地利用分布格局对植被和生态系统相关过程的影响.改进后的模型被用于研究中国东部南北样带(NSTEC)植被和净第一性生产力对未来气候变化的响应.模拟结果显示土地利用格局对未来气候条件下植被分布的变迁和生产力形成过程有非常显著的影响.与没有土地利用约束的情形相比较,土地利用作为限制条件缓减了植被类型之间的竞争,从而减少了模拟的样带区域内常绿阔叶林,但增加了模拟灌木和草地的分布.土地利用约束使得模拟得到的当前条件下的净第一性生产力更为接近实际情况,且未来气候条件下的生产力改变量更为可信.对未来CO2倍增条件下7个大气环流模型预测的气候情景的模拟结果表明:落叶阔叶林将显著增加,但针叶林、灌木和草原的分布将下降.未来气候条件下NSTEC样带的净第一性生产力总量将增加.预测样带北部的净第一性生产力的变化范围大于样带南部.温度变化比降水变化对样带的生产力具有更强的控制.     

Climate change causes critical transitions and irreversible alterations of mountain forests

Mountain forests are at particular risk of climate change impacts due to their temperature limitation and high exposure to warming. At the same time, their complex topography may help to buffer the effects of climate change and create climate refugia. Whether climate change can lead to critical transitions of mountain forest ecosystems and whether such transitions are reversible remain incompletely understood. We investigated the resilience of forest composition and size structure to climate change, focusing on a mountain forest landscape in the Eastern Alps. Using the individual‐based forest landscape model iLand, we simulated ecosystem responses to a wide range of climatic changes (up to a 6°C increase in mean annual temperature and a 30% reduction in mean annual precipitation), testing for tipping points in vegetation size structure and composition under different topography scenarios. We found that at warming levels above +2°C a threshold was crossed, with the system tipping into an alternative state. The system shifted from a conifer‐dominated landscape characterized by large trees to a landscape dominated by smaller, predominantly broadleaved trees. Topographic complexity moderated climate change impacts, smoothing and delaying the transitions between alternative vegetation states. We subsequently reversed the simulated climate forcing to assess the ability of the landscape to recover from climate change impacts. The forest landscape showed hysteresis, particularly in scenarios with lower precipitation. At the same mean annual temperature, equilibrium vegetation size structure and species composition differed between warming and cooling trajectories. Here we show that even moderate warming corresponding to current policy targets could result in critical transitions of forest ecosystems and highlight the importance of topographic complexity as a buffering agent. Furthermore, our results show that overshooting ambitious climate mitigation targets could be dangerous, as ecological impacts can be irreversible at millennial time scales once a tipping point has been crossed.     

Future climate change effects on US forest composition may offset benefits of reduced atmospheric deposition of N and S

Climate change and atmospheric deposition of nitrogen (N) and sulfur (S) are important drivers of forest demography. Here we apply previously derived growth and survival responses for 94 tree species, representing >90% of the contiguous US forest basal area, to project how changes in mean annual temperature, precipitation, and N and S deposition from 20 different future scenarios may affect forest composition to 2100. We find that under the low climate change scenario (RCP 4.5), reductions in aboveground tree biomass from higher temperatures are roughly offset by increases in aboveground tree biomass from reductions in N and S deposition. However, under the higher climate change scenario (RCP 8.5) the decreases from climate change overwhelm increases from reductions in N and S deposition. These broad trends underlie wide variation among species. We found averaged across temperature scenarios the relative abundance of 60 species were projected to decrease more than 5% and 20 species were projected to increase more than 5%; and reductions of N and S deposition led to a decrease for 13 species and an increase for 40 species. This suggests large shifts in the composition of US forests in the future. Negative climate effects were mostly from elevated temperature and were not offset by scenarios with wetter conditions. We found that by 2100 an estimated 1 billion trees under the RCP 4.5 scenario and 20 billion trees under the RCP 8.5 scenario may be pushed outside the temperature record upon which these relationships were derived. These results may not fully capture future changes in forest composition as several other factors were not included. Overall efforts to reduce atmospheric deposition of N and S will likely be insufficient to overcome climate change impacts on forest demography across much of the United States unless we adhere to the low climate change scenario.     

Responses of vegetation structure and primary production of a forest transect in eastern China to global change

Aim A regional model of vegetation dynamics was enhanced to include biogeochemical cycling of nitrogen and was then applied to a forest transect in east China (FTEC) in order to investigate the responses of the transect to possible global change. Location Eastern China. Methods Biomass and nitrogen concentration of green and nongreen portions of vegetation, moisture contents of three soil layers, and total and available soil nitrogen are included as state variables in the enhanced model. The model was parameterized and validated against field observations of biomass, productivity, plant and soil nitrogen concentration, nitrogen uptake, a vegetation index derived from satellite remote sensing and digital maps of vegetation and soil distributions along a forest transect in eastern China (FTEC). The model was applied to FTEC in order to investigate the responsive characteristics of the ecosystems to global climatic change. Scenarios of climate change under doubled CO₂ produced by seven general circulation models (GCM) were used to drive the model. Results The simulations indicated that the model is capable of simulating accurately potential vegetation distribution and net primary productivity under contemporary climatic conditions. The simulations for GCM‐projected future climate scenarios with doubled atmospheric CO₂ concentration predicted that broadleaf forests would increase, but conifer forests, shrubs and grasses would decrease; and that deciduous forests would have the largest relative increase, but evergreen shrubs would have the largest decrease. Conclusions The overall effects of doubling CO₂ and climatic changes on FTEC were to produce an increased net primary productivity (NPP) at equilibrium for all seven GCM scenarios. The inclusion of nitrogen dynamics in the model imposes more constraint on the responses of FTEC to climatic change than the previous version of the model without nitrogen dynamics. Temperature exerts a stronger control on NPP than precipitation, as indicated by the negative correlations between NPP and temperature. The southern portion of FTEC, at latitudes less than 33 °N, show much larger increases in annual NPP than in the north. However, the predicted range of NPP increases is much larger in the north than in the south.     

A model‐data comparison of Holocene timberline changes in the Swiss Alps reveals past and future drivers of mountain forest dynamics

Mountain vegetation is strongly affected by temperature and is expected to shift upwards with climate change. Dynamic vegetation models are often used to assess the impact of climate on vegetation and model output can be compared with paleobotanical data as a reality check. Recent paleoecological studies have revealed regional variation in the upward shift of timberlines in the Northern and Central European Alps in response to rapid warming at the Younger Dryas/Preboreal transition ca. 11 700 years ago, probably caused by a climatic gradient across the Alps. This contrasts with previous studies that successfully simulated the early Holocene afforestation in the (warmer) Central Alps with a chironomid‐inferred temperature reconstruction from the (colder) Northern Alps. We use LandClim , a dynamic landscape vegetation model to simulate mountain forests under different temperature, soil and precipitation scenarios around Iffigsee (2065 m a.s.l.) a lake in the Northwestern Swiss Alps, and compare the model output with the paleobotanical records. The model clearly overestimates the upward shift of timberline in a climate scenario that applies chironomid‐inferred July‐temperature anomalies to all months. However, forest establishment at 9800 cal. BP at Iffigsee is successfully simulated with lower moisture availability and monthly temperatures corrected for stronger seasonality during the early Holocene. The model‐data comparison reveals a contraction in the realized niche of Abies alba due to the prominent role of anthropogenic disturbance after ca. 5000 cal. BP, which has important implications for species distribution models (SDMs) that rely on equilibrium with climate and niche stability. Under future climate projections, LandClim indicates a rapid upward shift of mountain vegetation belts by ca. 500 m and treeline positions of ca. 2500 m a.s.l. by the end of this century. Resulting biodiversity losses in the alpine vegetation belt might be mitigated with low‐impact pastoralism to preserve species‐rich alpine meadows.     

Effects of climate change on net primary productivity in Larix olgensis plantations based on process modeling

Aims Climate change has significant effects on net primary productivity (NPP) in forests, but there is a large uncertainty in the direction and magnitude of the effects. Process-based models are important tools for understanding the responses of forests to climate change. The objective of the study is to simulate changes in NPP of Larix olgensis plantations under future climate scenarios using 3-PG model in order to guide the management of L. olgensis plantations in the context of global climate change.Methods Data were obtained for 30 permanent plots of L. olgensis plantations in Siping, Linjiang, Baishan, etc. of Jilin Province, and a process model, 3-PG model, was applied to simulate changes in NPP over a rotation period of 40 years under different climate scenarios. Parameter sensitivity was also determined. Important findings The locally parameterized 3-PG model well simulates the changes in NPP against the measured NPP data, with values between 272.79-844.80 g·m^-2·a^-1 and both mean relative error and relative root mean square error within 12%. The NPP in L. olgensis plantations would increase significantly with increases in atmospheric CO₂ concentration, temperature and precipitation collectively. However, an increase in temperature alone would lead to a decrease in NPP, but increases in precipitation and atmospheric CO₂ concentration would increase NPP; the positive effect of increasing precipitation appears to be weaker than the negative effect of increasing temperature. Sensitivity analysis shows that the model performance is sensitive to the optimum temperature, stand age at which specific leaf area equals to half of the sum of specific leaf area at age 0 (SLA₀) and that for mature leaves (SLA₁), and days of production loss due to frost.     

Climate change and modelled biome representation in Canada's national park system: implications for system planning and park mandates

Aim The study examined the potential for change in biome representation within Canada's national park system under multiple climate change scenarios and subsequent potential vulnerabilities in Parks Canada policy and planning frameworks. Location The study was conducted for Canada's 39 national parks. Methods The vegetation change scenarios were based on modelling results from the BIOME3 and MAPSS equilibrium process‐based global vegetation models (GVM), run with multiple doubled‐CO₂ climate change scenarios. The six vegetation distribution scenarios were calculated at 0.5° latitude–longitude resolution and the boundaries of 39 national parks superimposed in a geographic information system (GIS). Park management plans and other planning documents were also reviewed as part of the analysis. Results The proportional distribution of biomes in Canada's national park system was very similar (within 3% of area for each biome) using BIOME3 and MAPSS under the current climate. Regardless of the GVM and climate change scenario used, the modelling results suggest the potential for substantial change in the biome representation in Canada's national park system. In five of six vegetation scenarios, a novel biome type appeared in more than half of the national parks and greater than 50% of all vegetation grid boxes changed biome type. The proportional representation of tundra and taiga/tundra in the national park system declined in each of the vegetation scenarios, while more southerly biomes (temperate forests and savanna/woodland) increased (in some scenarios doubling to quadrupling). Results for boreal forest varied among the climate change scenarios. A range of potential vulnerabilities in existing policy and planning frameworks were identified, including the national park system plan, individual park objectives, and fire and exotic species management plans. Conclusions Climate change represents an unprecedented challenge to Parks Canada and its ability to achieve its conservation mandate as presently legislated. Research is needed not only on ecosystem responses to climate change, but also on the capacity of conservation systems and agencies to adapt to climate change.     

Probabilistic spatio‐temporal assessment of vegetation vulnerability to climate change in Swaziland

In a spatially explicit climate change impact assessment, a Bayesian network (BN) model was implemented to probabilistically simulate future response of the four major vegetation types in Swaziland. Two emission scenarios (A2 and B2) from an ensemble of three statistically downscaled coupled atmosphere‐ocean global circulation models (CSIRO‐Mk3, CCCma‐CGCM3 and UKMO‐HadCM3) were used to simulate possible changes in BN‐based environmental envelopes of major vegetation communities. Both physiographic and climatic data were used as predictors representing the 2020s, 2050s and the 2080s periods. A comparison of simulated vegetation distribution and the expert vegetation map under baseline conditions showed an overall correspondence of 97.7% and a Kappa coefficient of 0.966. Although the ensemble projections showed comparable trends during the 2020s, the results from the A2 storyline were more drastic indicating that grassland and the Lebombo bushveld will be impacted negatively as early as the 2020s with about 1 °C temperature increase. The bioclimatically suitable areas of all but one vegetation type decline drastically after about 2 °C warming, more so under the more severe A2 scenario and in particular during the 2080s. The sour bushveld is the only vegetation type that initially responds positively to warming by possibly encroaching to the highly vulnerable grassland areas. Vulnerability of vegetation is increased by the limited ability to migrate into suitable climates due to close affinity to certain geological formations and the fragmentation of the landscape by agriculture and other land uses. This is expected to have serious impacts on biodiversity in the country. Under warmer climates, the likely vegetation types to emerge are uncertain due to future novel combinations of climate and bedrock lithology. The strengths and limitations of the BN approach are also discussed.     

Potential Changes in the Distributions of Western North America Tree and Shrub Taxa under Future Climate Scenarios

Increases in atmospheric greenhouse gases are driving significant changes in global climate. To project potential vegetation response to future climate change, this study uses response surfaces to describe the relationship between bioclimatic variables and the distribution of tree and shrub taxa in western North America. The response surfaces illustrate the probability of the occurrence of a taxon at particular points in climate space. Climate space was defined using three bioclimatic variables: mean temperature of the coldest month, growing degree days, and a moisture index. Species distributions were simulated under present climate using observed data (1951–80, 30-year mean) and under future climate (2090–99, 10-year mean) using scenarios generated by three general circulation models—HADCM2, CGCM1, and CSIRO. The scenarios assume a 1% per year compound increase in greenhouse gases and changes in sulfate (SO₄) aerosols based on the Intergovernmental Panel on Climate Change (IPCC) IS92a scenario. The results indicate that under future climate conditions, potential range changes could be large for many tree and shrub taxa. Shifts in the potential ranges of species are simulated to occur not only northward but in all directions, including southward of the existing ranges of certain species. The simulated potential distributions of some species become increasingly fragmented under the future climate scenarios, while the simulated potential distributions of other species expand. The magnitudes of the simulated range changes imply significant impacts to ecosystems and shifts in patterns of species diversity in western North America. Received 12 May 2000; accepted 20 December 2000.     

Current and Future Fire Regimes and Their Influence on Natural Vegetation in Ethiopia

Fire is a major factor shaping the distribution of vegetation types. In this study, we used a recent high resolution map of potential natural vegetation (PNV) types and MODIS fire products to model and investigate the importance of fire as driver of vegetation distribution patterns in Ethiopia. We employed statistical modeling techniques to estimate the distribution of fire and the PNVs under current climatic conditions, and used the calibrated models to project distributions for different climate change scenarios. Results show a clear congruence between distribution patterns of fire and major vegetation types. The effect of climate change varies considerably between climate change models and scenarios, but as general trend expansions of moist Afromontane forest and Combretum–Terminalia woodlands were predicted. Fire-prone areas were also predicted to increase, and including this factor in vegetation distribution models resulted in stronger expansion of Combretum–Terminalia woodlands and a more limited increase of moist Afromontane forests. These results underline the importance of fire as a regulating factor of vegetation distribution patterns, and how fire needs to be factored into predict the possible effects of climate change. For conservation strategies to effectively address conservation challenges caused by rapid climate shifts, it is imperative that they not only consider the direct influence of climate changes on the vegetation, species species, or biodiversity patterns, but also the influence of future fire regimes.     

Analysis of vegetation distribution in Interior Alaska and sensitivity to climate change using a logistic regression approach

Aim To understand drivers of vegetation type distribution and sensitivity to climate change. Location Interior Alaska. Methods A logistic regression model was developed that predicts the potential equilibrium distribution of four major vegetation types: tundra, deciduous forest, black spruce forest and white spruce forest based on elevation, aspect, slope, drainage type, fire interval, average growing season temperature and total growing season precipitation. The model was run in three consecutive steps. The hierarchical logistic regression model was used to evaluate how scenarios of changes in temperature, precipitation and fire interval may influence the distribution of the four major vegetation types found in this region. Results At the first step, tundra was distinguished from forest, which was mostly driven by elevation, precipitation and south to north aspect. At the second step, forest was separated into deciduous and spruce forest, a distinction that was primarily driven by fire interval and elevation. At the third step, the identification of black vs. white spruce was driven mainly by fire interval and elevation. The model was verified for Interior Alaska, the region used to develop the model, where it predicted vegetation distribution among the steps with an accuracy of 60–83%. When the model was independently validated for north‐west Canada, it predicted vegetation distribution among the steps with an accuracy of 53–85%. Black spruce remains the dominant vegetation type under all scenarios, potentially expanding most under warming coupled with increasing fire interval. White spruce is clearly limited by moisture once average growing season temperatures exceeded a critical limit (+2 °C). Deciduous forests expand their range the most when any two of the following scenarios are combined: decreasing fire interval, warming and increasing precipitation. Tundra can be replaced by forest under warming but expands under precipitation increase. Main conclusion The model analyses agree with current knowledge of the responses of vegetation types to climate change and provide further insight into drivers of vegetation change.     

Tropical forests and the global carbon cycle: impacts of atmospheric carbon dioxide, climate change and rate of deforestation

The remaining carbon stocks in wet tropical forests are currently at risk because of anthropogenic deforestation, but also because of the possibility of release driven by climate change. To identify the relative roles of CO2 increase, changing temperature and rainfall, and deforestation in the future, and the magnitude of their impact on atmospheric CO2 concentrations, we have applied a dynamic global vegetation model, using multiple scenarios of tropical deforestation (extrapolated from two estimates of current rates) and multiple scenarios of changing climate (derived from four independent offline general circulation model simulations). Results show that deforestation will probably produce large losses of carbon, despite the uncertainty about the deforestation rates. Some climate models produce additional large fluxes due to increased drought stress caused by rising temperature and decreasing rainfall. One climate model, however, produces an additional carbon sink. Taken together, our estimates of additional carbon emissions during the twenty-first century, for all climate and deforestation scenarios, range from 101 to 367 Gt C, resulting in CO2 concentration increases above background values between 29 and 129 p.p.m. An evaluation of the method indicates that better estimates of tropical carbon sources and sinks require improved assessments of current and future deforestation, and more consistent precipitation scenarios from climate models. Notwithstanding the uncertainties, continued tropical deforestation will most certainly play a very large role in the build-up of future greenhouse gas concentrations.