Potential global distribution of the guava root-knot nematode Meloidogyne enterolobii under different climate change scenarios using MaxEnt ecological niche modeling

In recent years,Meloidogyne enterolobii has emerged as a major parasitic nematode infesting many plants in tropical or subtropical areas.However,the regions of potential distribution and the main contributing environmental variables for this nematode are unclear.Under the current climate scenario,we predicted the potential geographic distributions of M.enterolobii worldwide and in China using a Maximum Entropy(MaxEnt)model with the occurrence data of this species.Furthermore,the potential distributions of M.enterolobii were projected under three future climate scenarios(BCC-CSM2-MR,CanESM5 and CNRM-CM6-1)for the periods 2050s and 2090s.Changes in the potential distribution were also predicted under different climate conditions.The results showed that highly suitable regions for M.enterolobii were concentrated in Africa,South America,Asia,and North America between latitudes 30°S to 30°N.Bio16(precipitation of the wettest quarter),bio10(mean temperature of the warmest quarter),and bio11(mean temperature of the coldest quarter)were the variables contributing most in predicting potential distributions of M.enterolobii.In addition,the potential suitable areas for M.enterolobii will shift toward higher latitudes under future climate scenarios.This study provides a theoretical basis for controlling and managing this nematode.

Water yield and biomass production for on a eucalypt-dominated Mediterranean catchment under different climate scenarios

Worldwide,forests are vital in the regulation of the water cycle regulation and in water balance allocation.Knowledge of ecohydrological responses of production forests is essential to support management strategies,especially where water is already scarce.Shifting climatological patterns are expected to impact thermopluviometric regimes,water cycle components,hydrological responses,and plant physiology,evapotranspiration rates,crop productivity and land management operations.This work(1)assessed the impacts of different predicted climate conditions on water yield;(2)inferred the impacts of climate change on biomass production on eucalypt-to-eucalypt succes sion.To this end,the widely accepted Soil and Water Assessment Tool(SWAT)was run with the RCA,HIRHAM5 and RACMO climate models for two emission scenarios(RCP 4.5 and8.5).Three 12-year periods were considered to simulate tree growth under coppice regime.The results revealed an overall reduction in streamflow and water yield in the catchment in line with the projected reduction in total annual precipitation.Moreover,HIRHAM5 and RACMO models forecast a slight shift in seasonal streamflow of up to 2 months(for2024-2048)in line with the projected increase in precipitation from May to September.For biomass production,the extreme climate model(RCA)and severe emis sion scenario(RCP 8.5)predicted a decrease up to 46%.However,in the less extreme and more-correlated(with actual catchment climate conditions)climate models(RACMO and HIRHAM5)and in the less extreme emission scenario(RCP 4.5),biomass production increased(up to 20%),and the growth cycle was slightly reduced.SWAT was proven to be a valuable tool to assess climate change impacts on a eucalypt-dominated catchment and is a suitable decision-support tool for forest managers.

An evaluation of central Iran’s protected areas under different climate change scenarios (A Case on Markazi and Hamedan provinces)

Global climate change poses a new challenge for species and can even push some species toward an extinction vortex. The most affected organisms are those with narrow tolerance to the climatic factors but many large mammals such as ungulates with a wider ecological niche are also being affected indirectly. Our research mainly used wild sheep in central Iran as a model species to explore how the suitable habitats will change under different climatic scenarios and to determine if current borders of protected areas will adequately protect habitat requirements. To create habitat models we used animal-vehicle collision points as an input for species presence data. We ran habitat models using Max Ent modeling approach under different climatic scenarios of the past, present and future(under the climatic scenarios for minimum(RCP2.6) and maximum(RCP8.5) CO2 concentration trajectories). We tried to estimate the overlap and the width of the ecological niche using relevant metrics. In order to analyze the effectiveness of the protected areas, suitable maps were concerted to binary maps using True Skill Statistic(TSS) threshold and measured the similarity of the binary maps for each scenario using Kappa index. In order to assess the competence of the present protected areas boundary in covering the distribution of species, two different scenarios were employed, which are ensemble scenario 1: an ensemble of the binary maps of the species distribution in Mid-Holocene, present, and RCP2.6;and ensemble scenario 2: an ensemble of binary suitability maps in Mid-Holocene, present, and RCP8.5. Then, the borders of modeled habitats with the boundaries of 23 existing protected areas in two central provinces in Iran were compared. The predicted species distribution under scenario 1(RCP2.6) was mostly similar to its current distribution(Kappa = 0.53) while the output model under scenario 2(RCP8.5) indicated a decline in the species distribution range. Under the first ensemble scenario, current borders of the protected areas in Hamedan province showed better efficiency to cover the model species distribution range. Analyzing Max Ent spatial models under the second climatic scenario suggested that protected areas in both Markazi and Hamedan provinces will not cover "high suitability" areas in the future. Modeling the efficiency of the current protected areas under predicted future climatic scenarios can help the related authorities to plan conservation activities more efficiently.

The interaction between temperature and precipitation on the potential distribution range of Betula ermanii in the alpine treeline ecotone on the Changbai Mountain

Alpine treeline ecotones are highly sensitive to climate warming.The low temperature-determined alpine treeline is expected to shift upwards in response to global warming.However,little is known about how temperature interacts with other important factors to influence the distribution range of tree species within and beyond the alpine treeline ecotone.Hence,we used a GF-2 satellite image,along with bioclimatic and topographic variables,to develop an ensemble suitable habitat model based on the species distribution modeling algorithms in Biomod2.We investigated the distribution of suitable habitats for B.ermanii under three climate change scenarios(i.e.,low(SSP126),moderate(SSP370)and extreme(SSP585)future emission trajectories)between two consecutive time periods(i.e.,current-2055,and 2055-2085).By 2055,the potential distribution range of B.ermanii will expand under all three climate scenarios.The medium and high suitable areas will decline under SSP370 and SSP585scenarios from 2055 to 2085.Moreover,under the three climate scenarios,the uppermost altitudes of low suitable habitat will rise to 2,329 m a.s.l.,while the altitudes of medium and high suitable habitats will fall to 2,201 and2,051 m a.s.l.by 2085,respectively.Warming promotes the expansion of B.ermanii distribution range in Changbai Mountain,and this expansion will be modified by precipitation as climate warming continues.This interaction between temperature and precipitation plays a significant role in shaping the potential distribution range of B.ermanii in the alpine treeline ecotone.This study reveals the link between environmental factors,habitat distribution,and species distribution in the alpine treeline ecotone,providing valuable insights into the impacts of climate change on high-elevation vegetation,and contributing to mountain biodiversity conservation and sustainable development.

Finer topographic data improves distribution modeling of Picea crassifolia in the northern Qilian Mountains

The Qilian Mountains, a national key ecological function zone in Western China, play a pivotal role in ecosystem services. However, the distribution of its dominant tree species, Picea crassifolia (Qinghai spruce), has decreased dramatically in the past decades due to climate change and human activity, which may have influenced its ecological functions. To restore its ecological functions, reasonable reforestation is the key measure. Many previous efforts have predicted the potential distribution of Picea crassifolia, which provides guidance on regional reforestation policy. However, all of them were performed at low spatial resolution, thus ignoring the natural characteristics of the patchy distribution of Picea crassifolia. Here, we modeled the distribution of Picea crassifolia with species distribution models at high spatial resolutions. For many models, the area under the receiver operating characteristic curve (AUC) is larger than 0.9, suggesting their excellent precision. The AUC of models at 30 m is higher than that of models at 90 m, and the current potential distribution of Picea crassifolia is more closely aligned with its actual distribution at 30 m, demonstrating that finer data resolution improves model performance. Besides, for models at 90 m resolution, annual precipitation (Bio12) played the paramount influence on the distribution of Picea crassifolia, while the aspect became the most important one at 30 m, indicating the crucial role of finer topographic data in modeling species with patchy distribution. The current distribution of Picea crassifolia was concentrated in the northern and central parts of the study area, and this pattern will be maintained under future scenarios, although some habitat loss in the central parts and gain in the eastern regions is expected owing to increasing temperatures and precipitation. Our findings can guide protective and restoration strategies for the Qilian Mountains, which would benefit regional ecological balance.

Prediction of the potential distribution and analysis of the freezing injury risk of winter wheat on the Loess Plateau under climate change

Determining the suitable areas for winter wheat under climate change and assessing the risk of freezing injury are crucial for the cultivation of winter wheat.We used an optimized Maximum Entropy(MaxEnt)Model to predict the potential distribution of winter wheat in the current period(1970-2020)and the future period(2021-2100)under four shared socioeconomic pathway scenarios(SSPs).We applied statistical downscaling methods to downscale future climate data,established a scientific and practical freezing injury index(FII)by considering the growth period of winter wheat,and analyzed the characteristics of abrupt changes in winter wheat freezing injury by using the Mann-Kendall(M-K)test.The results showed that the prediction accuracy AUC value of the MaxEnt Model reached 0.976.The minimum temperature in the coldest month,precipitation in the wettest season and annual precipitation were the main factors affecting the spatial distribution of winter wheat.The total suitable area of winter wheat was approximately 4.40×10^(7)ha in the current period.In the 2070s,the moderately suitable areas had the greatest increase by 9.02×10^(5)ha under SSP245 and the least increase by 6.53×10^(5)ha under SSP370.The centroid coordinates of the total suitable areas tended to move northward.The potential risks of freezing injury in the high-latitude and-altitude areas of the Loess Plateau,China increased significantly.The northern areas of Xinzhou in Shanxi Province,China suffered the most serious freezing injury,and the southern areas of the Loess Plateau suffered the least.Environmental factors such as temperature,precipitation and geographical location had important impacts on the suitable area distribution and freezing injury risk of winter wheat.In the future,greater attention should be paid to the northward boundaries of both the winter wheat planting areas and the areas of freezing injury risk to provide the early warning of freezing injury and implement corresponding management strategies.

Relations between Climatic Changes and High Pollution Levels in Bulgaria

One of the important consequences of the climatic changes is the potential danger of increasing the concentrations of some pollutants, which may cause damages to humans, animals and plants. Therefore, it is worthwhile to study carefully the impact of future climate changes on the high pollution levels. The major topic of the discussion in this paper is the increase of some ozone levels in Bulgaria, but several related topics are also discussed. The particular mathematical tool applied in this study is a large-scale air pollution model, the Unified Danish Eulerian Model (UNI- DEM), which was successfully used in several investigations related to potentially dangerous pollution levels in several European countries. This model is described by a non-linear system of partial differential equations, which is solved numerically by using (a) advanced numerical algorithms and (b) modern computer architectures. Moreover, (c) the code is parallelized and (d) the cache memories of the available computers are efficiently utilized. It is shown that in Bulgaria, as in the other European countries, the climatic changes will result in permanent increases of some quantities related to the ozone pollution. The important issue is that in our study the changes of the dangerous pollution levels are followed year by year. In this way, an attempt is made both to capture the effect of the interannual variations of the meteorological conditions on the levels of the ozone concentrations and to follow directly the influence of the climatic changes on the pollution levels. Moreover, the sensitivity of the pollution levels to variations of the human made (anthropogenic) and natural (biogenic) emissions is also discussed.

Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios: A Case Study of Swedish Precipitation

There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.

Impact of rainfed and irrigated agriculture systems on soil carbon stock under different climate scenarios in the semi-arid region of Brazil

Understanding the dynamics of soil organic carbon(SOC) is of fundamental importance in land use and management, whether in the current researches or in future scenarios of agriculture systems considering climate change. In order to evaluate SOC stock of the three districts(Delmiro Gouveia, Pariconha, and Inhapi districts) in the semi-arid region of Brazil in rainfed and irrigated agriculture systems under different climate scenarios using the Century model, we obtained RCP4.5 and RCP8.5 climate scenarios derived from the Eta Regional Climate Model(Eta-Had GEM2-ES and Eta-MIROC5) from the National Institute for Space Research, and then input the data of bulk density, p H, soil texture, maximum temperature, minimum temperature, and rainfall into the soil and climate files of the Century model. The results of this study showed that the Eta-Had GEM2-ES model was effective in estimating air temperature in the future period. In rainfed agriculture system, SOC stock under the baseline scenario was lower than that under RCP4.5 and RCP8.5 climate scenarios, while in irrigated agriculture system, SOC stock in the almost all climate scenarios(RCP4.5 and RCP8.5) and models(Eta-Had GEM2-ES and Eta-MIROC5) will increase by 2100. The results of this study will help producers in the semi-arid region of Brazil adopt specific agriculture systems aimed at mitigating greenhouse gas emissions.

Modelling the biological invasion of Prosopis juliflora using geostatistical-based bioclimatic variables under climate change in arid zones of southwestern Iran

Invasive species have been the focus of ecologists due to their undesired impacts on the environment.The extent and rapid increase in invasive plant species is recognized as a natural cause of global-biodiversity loss and degrading ecosystem services.Biological invasions can affect ecosystems across a wide spectrum of bioclimatic conditions.Understanding the impact of climate change on species invasion is crucial for sustainable biodiversity conservation.In this study,the possibility of mapping the distribution of invasive Prosopis juliflora(Swartz)DC.was shown using present background data in Khuzestan Province,Iran.After removing the spatial bias of background data by creating weighted sampling bias grids for the occurrence dataset,we applied six modelling algorithms(generalized additive model(GAM),classification tree analysis(CTA),random forest(RF),multivariate adaptive regression splines(MARS),maximum entropy(Max Ent)and ensemble model)to predict invasion distribution of the species under current and future climate conditions for both optimistic(RCP2.6)and pessimistic(RCP8.5)scenarios for the years 2050 and 2070,respectively.Predictor variables including weighted mean of CHELSA(climatologies at high resolution for the Earth’s land surface areas)-bioclimatic variables and geostatistical-based bioclimatic variables(1979–2020),physiographic variables extracted from shuttle radar topography mission(SRTM)and some human factors were used in modelling process.To avoid causing a biased selection of predictors or model coefficients,we resolved the spatial autocorrelation of presence points and multi-collinearity of the predictors.As in a conventional receiver operating characteristic(ROC),the area under curve(AUC)is calculated using presence and absence observations to measure the probability and the two error components are weighted equally.All models were evaluated using partial ROC at different thresholds and other statistical indices derived from confusion matrix.Sensitivity analysis showed that mean diurnal range(Bio2)and annual precipitation(Bio12)explained more than 50% of the changes in the invasion distribution and played a pivotal role in mapping habitat suitability of P.juliflora.At all thresholds,the ensemble model showed a significant difference in comparison with single model.However,Max Ent and RF outperformed the others models.Under climate change scenarios,it is predicted that suitable areas for this invasive species will increase in Khuzestan Province,and increasing climatically suitable areas for the species in future will facilitate its future distribution.These findings can support the conservation planning and management efforts in ecological engineering and be used in formulating preventive measures.

conomic losses from reduced freshwater under future climate scenarios: An example from the Urumqi River,Tianshan Mountains

As important freshwater resources in alpine basins,glaciers and snow cover tend to decline due to climate warming,thus affecting the amount of water available downstream and even regional economic development.However,impact assessments of the economic losses caused by reductions in freshwater supply are quite limited.This study aims to project changes in glacier meltwater and snowmelt of the Urumqi River in the Tianshan Mountains under future climate change scenarios(RCP2.6(RCP,Representative Concentration Pathway),RCP4.5,and RCP8.5)by applying a hydrological model and estimate the economic losses from future meltwater reduction for industrial,agricultural,service,and domestic water uses combined with the present value method for the 2030 s,2050 s,2070 s,and 2090 s.The results indicate that total annual glacier meltwater and snowmelt will decrease by 65.6%and 74.5%under the RCP4.5 and RCP8.5 scenarios by the 2090 s relative to the baseline period(1980-2010),respectively.Compared to the RCP2.6 scenario,the projected economic loss values of total water use from reduced glacier meltwater and snowmelt under the RCP8.5 scenario will increase by 435.10×10^(6) and 537.20×10^(6) CNY in the 2050 s and 2090 s,respectively,and the cumulative economic loss value for 2099 is approximately 2124.00×10^(6) CNY.We also find that the industrial and agricultural sectors would likely face the largest and smallest economic losses,respectively.The economic loss value of snowmelt in different sectorial sectors is greater than that of glacier meltwater.These findings highlight the need for climate mitigation actions,industrial transformation,and rational water allocation to be considered in decision-making in the Tianshan Mountains in the future.

The Potential Scenarios of the Impacts of Climate Change on Egyptian Resources and Agricultural Plant Production

The emissions of greenhouse gasses in Egypt are about 0.58% of the total emissions of the world in the year 2015, although Egypt is one of the countries most affected by the impacts of climate change. By assessment and analysis of the expected economic impacts of climate change by the year 2030, the Egyptian cultivated area will be reduced to about 0.949 million acres, equal to about 8.22% of the Egyptian cultivated area compared with the case of no sinking part of the Delta land, thus reducing crop area in Egypt to about 1.406 million acres, approximately to about 6.25% of crop area compared with the case of no sinking part of the Delta land, in addition to surplus in the Egyptian balance water to about 2.48 billion m3. In this case value of the Egyptian agriculture production will decrease by about 6.19 billion dollars, equal to about 6.19% compared with presumably no sinking of the Delta land. In the case of sinking 15% of Delta lands, with the change of the productivity and water consumption of most crops, the result will be a reduction in the cultivated area to about 0.94 million acres. In addition to decreasing the Egyptian crop area to about 1.39 million acres, with a deficit in the Egyptian balance water to about 4.74 billion m3 compared to the case of no sinking part of the Delta land, the cultivated area will decrease to about 8.17%, and the crop area will decrease 6.18%. Also, the value of the Egyptian agriculture production will decrease by about 12.51%. While compared to sinking part of the Delta land to about 15% of the total Delta area without the other impacts of climate change, the cultivated area will increase by about 0.06%;the crop area will increase by about 0.08%;also, the value of the Egyptian agriculture production will decrease by about 5.57%.

Modelling of Sorghum (<i>Sorghum bicolor</i>) Growing Areas under Current and Future Climate in the Sudanian and Sahelian Zones of Mali

Climatic variability is one of the main constraints of agriculture in Mali, which will certainly affect long-term sorghum yields. The objective of the present study was to assess the effect of climate variability on sorghum production areas by 2050 in the Sudanian and Sahelian zones of Mali considering three climate scenarios: current scenarios (RCP 2.5), optimistic scenarios (RCP 4.5) and pessimistic scenarios (RCP 8.5). Therefore, 11,010 occurrence points of sorghum (Sorghum bicolor) were collected and associated with the environmental variables of the three climatic scenarios according to the maximum entropy approach (Maxent). Sorghum environmental data and points of occurrence were obtained from AfriClim and GBIF databases, respectively. The correlations carried out and the Jackknife test allowed us to identify variables that contributed more to the performance of the model. Overall, in the Sudanian zone, the suitable area for sorghum production which currently represents 37% of the area of the district of Koulikoro will increase up to 51% by 2050 considering the optimistic scenario (RCP 4.5). Furthermore, considering the pessimistic scenario (RCP 8.5), the suitable zones for sorghum production will experience a decrease of 10%. In the Sahelian zone, the suitable zones for sorghum production that represent 55% of San district area considering the RCP 2.5 scenario will experience a decline of 24% by 2050 considering both the optimistic (RCP 4.5) and pessimistic (RCP 8.5) scenarios. It is suggested to carry out investigations on potential sorghum yield prediction in both study areas in order to identify suitable production areas of the crop in the near future (2050) and long term (2100) as adaptation strategies and resilience of farmers to climate change.

Effects of climate change on potential habitats of the cold temperate coniferous forest in Yunnan province, southwestern China

We built a classification tree （CT） model to estimate climatic factors controlling the cold temperate coniferous forest （CTCF） distributions in Yunnan province and to predict its potential habitats under the current and future climates, using seven climate change scenarios, projected over the years of 2070-2099. The accurate CT model on CTCFs showed that minimum temperature of coldest month （TMW） was the overwhelmingly potent factor among the six climate variables. The areas of TMW〈-4.05 were suitable habitats of CTCF, and the areas of -1.35 〈 TMW were non-habitats, where temperate conifer and broad-leaved mixed forests （TCBLFs） were distribute in lower elevation, bordering on the CTCF. Dominant species of Abies, Picea, and Larix in the CTCFs, are more tolerant to winter coldness than Tsuga and broad-leaved trees including deciduous broad-leaved Acer and Betula, evergreen broad- leaved Cyclobalanopsis and Lithocarpus in TCBLFs. Winter coldness may actually limit the cool-side distributions of TCBLFs in the areas between -1.35℃ and -4.05℃, and the warm-side distributions of CTCFs may be controlled by competition to the species of TCBLFs. Under future climate scenarios, the vulnerable area, where current potential （suitable ＋ marginal） habitats （80,749 km^2） shift to non-habitats, was predicted to decrease to 55.91% （45,053 km^2） of the current area. Inferring from the current vegetation distribution pattern, TCBLFs will replace declining CTCFs. Vulnerable areas predicted by models are important in determining priority of ecosystem conservation.

Changes of Terrestrial Water Storage in River Basins of China Projected by RegCM4

In this study, a historic simulation covering the period from 1951 to 2000 and three projected scenario simulations covering 2001-2050 were conducted em- ploying the regional climate model RegCM4 to detect the changes of terrestrial water storage （TWS） in major river basins of China, using the Intergovernmental Panel on Climate Change （IPCC） Special Report on Emissions Scenarios （SRES）： A1B, A2, and B1. The historic simula- tion revealed that the variations of TWS, which are dominated by precipitation in the basins, rely highly on their climatic features. Compared with the historic simu- lation, the changes of TWS in the scenario simulations showed strong regional differences. However, for all sce- narios, TWS was found to increase most in Northeast China and surrounding mountains around the Tibetan Plateau, and decrease most in eastern regions of China. Unlike the low seasonal variations of TWS in arid areas, the TWS showed strong seasonal variations in eastern monsoon areas, with the maximum changes usually oc- curring in summer, when TWS increases most in a year. Among the three scenario simulations, TWS increased most in Songhua River Basin of B1 scenario, and de- creased most in Pearl River Basin of A2 scenario and Hal River Basin of A1B scenario, accompanied by different annual trends and seasonal variations.

Water resources response and prediction under climate change in Tao'er River Basin,Northeast China

Climate change has significantly affected hydrological processes and increased the frequency and severity of water shortage,droughts and floods in northeast China.A study has been conducted to quantify the influence of climate change on the hydrologic process in the Tao’er River Basin(TRB),one of the most prominent regions in northeast China for water contradiction.The Soil and Water Assessment Tool(SWAT)model was calibrated and validated with observed land use and hydro-climatic data and then employed for runoff simulations at upper,middle and lower reaches of the river basin for different climate change scenarios.The results showed that a gradual increase in temperature and decrease in annual precipitation in the basin was projected for the period 2020-2050 for both representative concentration pathways(RCP)4.5 and 8.5 scenarios.The climate changes would cause a decrease in annual average runoff at basin outlet by 12 and 23 million m^(3) for RCP4.5 and 8.5,respectively.The future runoff in the upstream and midstream of the basin during 2020-2050 would be-10.8% and-12.1% lower than the observed runoff compared to the base period for RCP4.5,while those would be-5.3% and-10.7%lower for RCP8.5.The future runoff will decrease at three hydrology stations for the assumed future climate scenarios.The results can help us understand the future temperature and precipitation trends and the hydrological cycle process under different climate change scenarios,and provide the basis for the rational allocation and management of water resources under the influence of future climate change in the TRB.

Climate Suitability of Schima superba in Subtropical Zone of China under Future Climate Scenario

[ Objective] The research aimed to study climate suitability of S. superba in subtropical zone of China under future climate scenario and response of its regional distribution on climate change. [ Metbed] Based on climate- vegetation related Kira model, Holdridge model and ecological suitability theory, climate suitability model of S. superba was established by using fuzzy mathematics. Based on the daily meteorological data at 246 stations of the subtropical zone from 1960 to 2005, by using spatial interpolation method, suitability of S. superba on temperature, precipitation, po- tential evapotranspiration rate was analyzed. According to Intergovernmental Panel on Climate Change （IPCC） Special Report on Emissions Sce- nario （SRES）, future scenario simulation result was used. Under IPCC A2 scenario, climate suitability of S. superba and its change were studied in subtropical zone of China under future climate scenario. Climate suitability of S. superba in future was classified. [ Result] Under future climate scenario, climate suitability of S. superba was stronger in most of areas in Hunan, north Guangdong, northeast Guangxi and east coast of Zhe- jiang. It was suitable for growth of S. superba in central Guangxi, east Guizhou, central Jiangxi and Fuzhou. Growth suitability of S. superba was still lower in the north of Gongshan - Weixi - Lijiang - Yuanjiang - Huize - Leibo - Emei - Neijiang - Nanchong - Bazhong - Zhongxiang - zaoyang - Xinyang -Lu＇an -Chuzhou -Gaoyou -Taitong. Climate suitability in west Yunnan and Sichuan had big change. Future climate suitability change of S. superba was greatly affected by temperature and potential evapotranspiration rate. [ Conclusion] Future climate suitability decreased toward west and north from Hunan. The climate suitability had a decline trend as time went by under future climate scenario. The research provided theoretical basis for studying geographic distribution of the vegetation population.

Modelling the impact of climate change on rangeland forage production using a generalized regression neural network:a case study in Isfahan Province,Central Iran

Monitoring of rangeland forage production at specified spatial and temporal scales is necessary for grazing management and also for implementation of rehabilitation projects in rangelands. This study focused on the capability of a generalized regression neural network（GRNN） model combined with GIS techniques to explore the impact of climate change on rangeland forage production. Specifically, a dataset of 115 monitored records of forage production were collected from 16 rangeland sites during the period 1998–2007 in Isfahan Province, Central Iran. Neural network models were designed using the monitored forage production values and available environmental data（including climate and topography data）, and the performance of each network model was assessed using the mean estimation error（MEE）, model efficiency factor（MEF）, and correlation coefficient（r）. The best neural network model was then selected and further applied to predict the forage production of rangelands in the future（in 2030 and 2080） under A1 B climate change scenario using Hadley Centre coupled model. The present and future forage production maps were also produced. Rangeland forage production exhibited strong correlations with environmental factors, such as slope, elevation, aspect and annual temperature. The present forage production in the study area varied from 25.6 to 574.1 kg/hm^2. Under climate change scenario, the annual temperature was predicted to increase and the annual precipitation was predicted to decrease. The prediction maps of forage production in the future indicated that the area with low level of forage production（0–100 kg/hm^2） will increase while the areas with moderate, moderately high and high levels of forage production（≥100 kg/hm^2） will decrease both in 2030 and in 2080, which may be attributable to the increasing annual temperature and decreasing annual precipitation. It was predicted that forage production of rangelands will decrease in the next couple of decades, especially in the western and southern parts of Isfahan Province. These changes are more pronounced in elevations between 2200 and 2900 m. Therefore, rangeland managers have to cope with these changes by holistic management approaches through mitigation and human adaptations.

Extreme Rainfall Indices in the Hydrographic Basins of Brazil

The authors analyze climate extremes indices (CEI) of rainfall over the largest basins of the Brazilian territory: Amazon (AMA), S?o Francisco (SF), Tocantins (TO) and Paraná (PAR) rivers. The CEI represent the frequency of heavy precipitation events (R30mm and R95p) and short duration extreme rainfall (RX5day and RX1day). Droughts (CDDd) are identified based on two indicators: The longest dry period (CDD) and the annual cycle. The results demonstrate that CDDd, RX1day and RX5day occurred with more frequency and intensity in SF basin during El Ni?o events. CDDd was of greater magnitude in the TO basin during La Ni?a events, while an increase of RX1day occurred in El Ni?o. The strong El Ni?o events (1983 and 1997) caused more intense and frequent RX1day and R30mm over the PAR basin. Amazon droughts occurred in two out of the six El Ni?o events. Moreover, the relationship between the positive (negative) sea superficial temperatures anomalies in North (South) Tropical Atlantic and drought in AMA basin was corroborated. A gradual warming of SST was observed at the start of 2003 until it achieved a maximum in 2005 associated with the southwestern Amazon drought. The second highest anomaly of SST was in 2010 linked with drought that was more spatially extensive than the 2005 drought. The spatial distribution of annual trends showed a significant increase of CDD in south-eastern AMA, Upper SF, northern PAR and throughout the TO basins. R20mm, RX1day and RX5day tend to increase significantly in southwestern (northeast) PAR (AMA) and northwestern TO basins. Comparisons between CEI derived from daily precipitation data from Climate Prediction Center (CPCp) and of the ETA_HadCM3 model showed that the model overestimated RX1day, RX5day and CDD, in the four basins. Future scenarios show that dry periods will occur with greatest magnitude in all the basins until 2071-2099 time slice, while RX1day will be more intense in the TO and SF basins.

Vulnerability of natural ecosystem in China under regional climate scenarios： An analysis based on eco-geographical regions

Assessment of vulnerability for natural ecosystem to climate change is a hot topic in climate change and ecology, and will support adapting and mitigating climate change. In this study, LPJ model modified according to features of China＇s natural ecosystems was em- ployed to simulate ecosystem dynamics under A2, B2 and A1B scenarios. Vulnerability of natural ecosystem to climate change was assessed according to the vulnerability assessment model. Based on eco-geographical regions, vulnerability of natural ecosystem to climate change was analyzed. Results suggest that vulnerability for China＇s natural ecosystems would strengthen in the east and weaken in the west, but the pattern of ecosystem vulner- ability would not be altered by climate change, which rises from southeast to northeast gradually. Increase in ecosystem vulnerable degree would mainly concentrate in temperate humid/sub-humid region and warm temperate humid/sub-humid region. Decrease in eco- system vulnerable degree may emerge in northwestern arid region and Qinghai-Tibet Plateau region. In the near-term scale, natural ecosystem in China would be slightly affected by cli- mate change. However, in mid-term and long-term scales, there would be severely adverse effect, particularly in the east with better water and thermal condition.