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.     

Predicting suitable habitat of an invasive weed Parthenium hysterophorus under future climate scenarios in Chitwan Annapurna Landscape,Nepal

Chitwan-Annapuma Landscape(CHAL)in central Nepal is known for its rich biodiversity and the landscape is expected to provide corridors for species range shift in response to climate change.Environmental assessments have identified biological invasions and other anthropogenic activities as major threats to the biodiversity in the CHAL.One of the rapidly spreading Invasive Alien Plant species(IAPs)in the CHAL is Parthenium hysterophorus L.,a neotropical invasive weed of global significance.This study aimed to investigate the current and future projected suitable habitat of P.hysterophorus in the CHAL using MaxEnt modelling in three"Representative Concentration Pathways"(RCPs 2.6,4.5 and 8.5)corresponding to different greenhouse gases emissiontrajectories for the year 2050 and 2070.A total of 288species occurrence points,six bioclimatic variablesmean diurnal range,isothermality,annual precipitation,precipitation of driest month,precipitation seasonality,precipitation of driest quarter and two topographic variables(aspect and slope)were selected for MaxEnt modelling.Potential range shift in terms of increase or decline in the suitable habitat areas under the projected scenarios were calculated.Slope and annual precipitation were the most important variables that explained the current distribution of P.hysterophorus.Twenty percent of the total area of CHAL was predicted to be suitable habitat for the growth of P.hysterophorus in the current climatic condition.Highest gain in the suitable habitat of this noxious weed was found under RCP 4.5 scenario in 2050 and 2070.whereas there will be a loss in thesuitable habitat under RCP 8.5 scenario in 2050 and2070.Out of four physiographic regions present in CHAL,three regions-Siwalik,Middle Mountain and High Mountain have suitable habitat for P.hysterophorus under current climatic condition.The mountainous region is likely to be affected more than the Siwalik region by further spread of P.fhysteropfhorus in the future under low(RCP 2.6)to medium(RCP 4.5)emission scenarios.The suitable habitat for this weed is likely to increase in the protected areas of mountain regions(Langtang National Park,Annapurna Conservation Area and Manaslu Conservation Area)in the future.The results have revealed a risk of spreading P.hysterophorus from present localities to non-invaded areas in the current and future climatic condition.Such risk needs to be considered by decision makers and resource managers while planning for effective management of this weed to reduce its ecological and economic impacts in the CHAL.     

Relationship between niche breadth and range shifts of Rhinopoma muscatellum(Chiroptera: Rhinopomatidae) in climate change scenarios in arid and semiarid mountainous region of Iran

Rapid climate change has provided the opportunity for many species to learn to adapt fast enough to modify their range distribution. The positive and negative responses of the species in terms of distribution are related to parameters such as kind of species, degree of specialization, size and movement skills, and such factors. Moving to high elevations and transitions to higher latitudes are among the strategies proposed as a solution to the negative effects of climate change. Therefore, predicting how different species respond to climate change can help predict the conservation program for them. Species distribution models(SDMs) are widely used to predict the geographical distribution of habitat suitability and species occurrence. Rhinopoma muscatellum is one of the three mousetailed bats(Rhinopomatidae) inhabiting the southeastern, southern, and southwestern parts of Iran and its distribution range to the interior and northern parts of Iran has been limited by the Elburz and Zagros Mountain. To study the effect of climate change on this species, range shifts and coverage of protected regions, 74 presence points and environmental variables(climate, topography, anthropogenic, and vegetation) in MaxEnt software were used. Before the implementation of the model, the autocorrelation of the presence points was reduced and the selection of pseudo absent points was limited by using the bias grid. Climate variables were prepared for Mid-Holocene, Current, Climate Current, and Future scenarios in 2070(RCP2.6, RCP4.5, RCP6, and RCP8.5). In order to evaluate the overlap of ecological niche, the Schoener's D and I statistic metrics were used. Also, to measure the breadth of the niches, B1(inverse concentration) and B2(uncertainty) metrics in ENMTOOLS software were employed. TSS statistics were used as a threshold. Species distribution trend changes in climatic scenarios were performed by the Mann Kendall(MK) test. Based on the results, the AUC values for current and future climate models were calculated to be 0.89 and 0.85, respectively. The distance from settlement, soil organic carbon, and altitude variables have the greatest impact on the current distribution of the species; and among the climatic variables, Isothermality(Bio3), Temperature Seasonality(Bio4), and Max Temperature of Warmest Month(Bio5) had the greatest impact on species distribution. The results showed that in climate change scenarios by 2070, the distribution range and breadth of climatic niche of Rhinopoma muscatellum will be significantly increased(P-value 0.05), habitat fragmentation will be reduced, and in RCP8.5 scenario it will reach the maximum distribution(39.38% of total Iran). This increase will cover the Elburz and Zagros mountain ranges, and a large part of the country will be suitable for the species. In response to current climate change, migration to higher latitudes was identified in this study. Among the main different classes of protected regions in Iran(National parks, Wildlife refuges, and Protected areas), protected areas in all scenarios had the most coverage of the suitable species habitat.     

Predicting the impact of climate change on the distribution of two threatened Himalayan medicinal plants of Liliaceae in Nepal

Predicting the potential distribution of medicinal plants in response to climate change is essential for their conservation and management. Contributing to the management program, this study aimed to predict the distribution of two threatened medicinal plants, Fritillaria cirrhosa and Lilium nepalense. The location of focal species gathered from herbarium specimen housed in different herbaria and online databases were geo-referenced and checked for spatial autocorrelation. The predictive environmental variables were selected, and MaxEnt software was used to model the current and future distributions of focal species. Four Representative Concentration Pathway (RCP) trajectories of the BCC-CSM1.1 model were used as the future (2050) projection layer. The MaxEnt modelling delineated the potential distribution of F. cirrhosa and L. nepalense. The current suitability is projected towards Central and Eastern Hilly/Mountainous regions. Both species gain maximum suitability in RCP 4.5 which decline towards other trajectories for L. nepalense. Overall, both the focal species shift towards the north-west, losing their potential habitat in hilly and lower mountainous regions by 2050 across all trajectories. Our results highlight the impact of future climate change on two threatened and valuable species. The results can be further useful to initiate farming of these medicinally and economically important species based on climatically suitable zone and for designing a germplasm conservation strategy.     

气候变化情景下淮河上游流域氮排放预测研究

淮河流域是水体遭受营养盐污染较严重的地区,本研究选择淮河上游的淮滨流域（淮滨站以上,流域面积1.6万km²）为研究对象,首先构建了淮滨流域SWAT水文水质模型,然后利用2011—2017年淮滨站实测的月径流和月氨氮浓度对SWAT模型进行了校正与验证,最后基于全球气候模型（GCM）气象数据,预测了未来30年（2020—2029年、2030—2039年、2040—2049年）不同气候变化情境（RCP2.6、RCP4.5、RCP6.0、RCP8.5）下的径流、氨氮浓度和非点源总氮负荷。结果发现,径流在校正期和验证期的Nash-Suttcliffe系数均为0.79,氨氮在校正期和验证期的Nash-Suttcliffe系数均高于0.5,表明模型的适用性良好。研究发现本研究区施肥量与土地利用类型是非点源氮负荷空间分异的主导因素。2020—2049年,不同气候变化情景下,本研究区的降水量和气温均为增长趋势。假如保持基准期（2011—2016年）污染排放强度,仅考虑气候变化影响,流域内非点源污染总氮负荷将比基准期最多增加31.8%,流域出水口淮滨站的年均氨氮浓度将最多减小42.6%。本研究可以为气候变化下淮滨流域的水文水质管理提供科学支撑。     

Projection of future streamflow of the Hunza River Basin,Karakoram Range (Pakistan) using HBV hydrological model

Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System(IRS). HBV model performed fairly well both during calibration(R2=0.87, Reff=0.85, PBIAS=-0.36) and validation(R2=0.86, Reff=0.83, PBIAS=-13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during bothcalibration(R2=0.94, Reff=0.88, PBIAS=0.47) and validation(R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995-2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model(GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010-2039, 2040-2069 and 2070-2099, using 1980-2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitiveparameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010-2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21 th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010-2099. However, Can ESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010-2099. The results of this study could be useful for decision making and effective future strategic plans for water management and their sustainability in the region.     

Soil conservation assessment via climate change and vegetation growth scenarios in the Nile River basin

Soil conservation by vegetation can mitigate soil erosion hazard and prevent reductions in food productivity. However, previous research applies little consideration to the interaction between vegetation and climate change in the estimation of future soil conservation change. Therefore, based on the Revised Universal Soil Loss Equation(RUSLE), Representative Concentration Pathways(RCPs, specifically RCP4.5 and RCP8.5), and the vegetation index and precipitation datasets, we built a multivariate regression equation that considers changes in vegetation growth under climate change scenarios in the context of soil conservation. Using the Nile River basin as a case study, via our established methods, we modelled and projected the impact of vegetation and climate change on future soil conservation between 2020 and 2100, where three main results were obtained:(1) under the scenarios of RCP4.5 and RCP8.5 from 2020 to 2100, soil conservation in the Nile Basin will first increase and then decrease, with its highest value in the years 2060, at 117.72(t ha-1 y-1), and 2070, at 134.39(t ha-1 y-1).(2) Soil conservation under RCP4.5 is lower than that under the RCP8.5 scenario, with a maximum difference of 27(t ha-1 y-1) in 2040 and a minimum difference of 0.2(t ha-1 y-1) in 2100.(3) The vegetation and climate change models in 2100 had soil conservation values of 110.77(t ha-1 y-1) under RCP4.5 and 38.70(t ha-1 y-1) under RCP8.5. In conclusion, although vegetation growth can increase soil conservation in the Nile River basin, the change in precipitation can offset the soil conservation enhanced by vegetation growth.     

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 m3 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.     

Effect of climate change on seasonal water use efficiency in subalpine Abies fabri

Abies fabri is a typical subalpine dark coniferous forest in southwestern China. Air temperature increases more at high elevation areas than that at low elevation areas in mountainous regions,and climate change ratio is also uneven in different seasons. Carbon gain and the response of water use efficiency(WUE) to annual and seasonal increases in temperature with or without CO_2 fertilization were simulated in Abies fabri using the atmospheric-vegetation interaction model(AVIM2). Four future climate scenarios(RCP2.6,RCP4.5,RCP6.0 and RCP8.5) from the Coupled Model Intercomparison Project Phase 5(CMIP5) were selectively investigated. The results showed that warmer temperatures have negative effects on gross primary production(GPP) and net primary production(NPP) in growing seasons and positive effects in dormant seasons due to the variation in the leaf area index. Warmer temperatures tend to generate lower canopy WUE and higher ecosystem WUE in Abies fabri. However,warmer temperature together with rising CO_2 concentrations significantlyincrease the GPP and NPP in both growing and dormant seasons and enhance WUE in annual and dormant seasons because of the higher leaf area index(LAI) and soil temperature. The comparison of the simulated results with and without CO_2 fertilization shows that CO_2 has the potential to partially alleviate the adverse effects of climate warming on carbon gain and WUE in subalpine coniferous forests.     

Species and plant community reorganization in the Trans-Mexican Volcanic Belt under climate change conditions

This study analyzes six vegetation communities in relation to current climatic parameters and eight climate change scenarios along an elevation gradient extending from 2,710 m to 4,210m in the Trans-Mexican Volcanic Belt. The projected movements of 25 plant species with the current restricted or wide altitudinal distributions were also modeled. To relate climatic parameters to the species and communities, a Precipitation/Temperature(P/T)index was used both for the current and the different climate-change scenarios. The temperatures are expected to increase by 1.1°C to 1.7°C by 2020 and by2°C to 3°C by 2050. A decrease of 4% to 13% in the annual precipitation is expected for the 2020 horizon,and a reduction between 3% and 20% is expected for2050. The reductions in water availability were projected for all altitude levels and plant communities.The most marked reduction was under the HADLEYA2 scenario, in which the lower limit of the altitudinal range increased from 2,710 to 3,310 m(2050 horizon)with reductions in the P/T index between 36% and39% compared to the current climate. Most plant species tended to shift their distribution from 200 to300 m upward in the 2020 temporal horizon scenarios. The Pinus hartwegii, Alnus jorullensis and Pinus montezumae communities would have a shorter altitudinal range as they move upward and merge with the remaining species at the higher altitudinal range. For the 2050 temporal horizon,30% of the species, primarily those from the higher altitudinal range, would disappear because their P/Tindex values would be above the limit of plant survival(4,210 m).     

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 broadleaved Cyclobalanopsis and Lithocarpus in TCBLFs. Winter coldness may actually limit the cool-side distributions of TCBLFs in the areas between -1.35°C and -4.05°C, 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 nonhabitats, 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.     

An artificial neural network-based snow cover predictive modeling in the higher Himalayas

With trends indicating increase in temperature and decrease in winter precipitation, a significant negative trend in snow-covered areas has been identified in the last decade in the Himalayas. This requires a quantitative analysis of the snow cover in the higher Himalayas. In this study, a nonlinear autoregressive exogenous model, an artificial neural network （ANN）, was deployed to predict the snow cover in the Kaligandaki river basin for the next 30 years. Observed climatic data, and snow covered area was used to train and test the model that captures the gross features of snow under the current climate scenario. The range of the likely effects of climate change on seasonal snow was assessed in the Himalayas using downscaled temperature and precipitation change projection from - HadCM3, a global circulation model to project future climate scenario, under the AIB emission scenario, which describes a future world of very rapid economic growth with balance use between fossil and non-fossil energy sources. The results show that there is a reduction of 9% to 46% of snow cover in different elevation zones during the considered time period, i.e., 2Oll to 2040. The 4700 m to 52oo m elevation zone is the most affected area and the area higher than 5200 m is the least affected. Overall, however, it is clear from the analysis that seasonal snow in the Kaligandaki basin is likely to be subject to substantialchanges due to the impact of climate change.     

Modeling habitat suitability of range plant species using random forest method in arid mountainous rangelands

Mountainous rangelands play a pivotal role in providing forage resources for livestock, particularly in summer, and maintaining ecological balance. This study aimed to identify environmental variables affecting range plant species distribution, ecological analysis of the relationship between these variables and the distribution of plants, and to model and map the plant habitats suitability by the Random Forest Method(RFM) in rangelands of the Taftan Mountain, Sistan and Baluchestan Province, southeastern Iran. In order to determine the environmental variables and estimate the potential distribution of plant species, the presence points of plants were recorded by using systematic random sampling method(90 points of presence) and soils were sampled in 5 habitats by random method in 0–30 and 30–60 cm depths. The layers of environmental variables were prepared using the Kriging interpolation method and Geographic Information System facilities. The distribution of the plant habitats was finally modelled and mapped by the RFM. Continuous maps of the habitat suitability were converted to binary maps using Youden Index(?) in order to evaluate the accuracy of the RFM in estimation of the distribution of species potentialhabitat. Based on the values of the area under curve(AUC) statistics, accuracy of predictive models of all habitats was in good level. Investigating the agreement between the predicted map, generated by each model, and actual maps, generated from fieldmeasured data, of the plant habitats, was at a high level for all habitats, except for Amygdalus scoparia habitat. This study concluded that the RFM is a robust model to analyze the relationships between the distribution of plant species and environmental variables as well as to prepare potential distribution maps of plant habitats that are of higher priority for conservation on the local scale in arid mountainous rangelands.     

未来RCP4.5情景下非洲地区主要气候要素时空演变特征

气候变化影响及其适应受到广泛关注。大量研究表明,受气候变化影响所造成的增温和降水减少已影响到非洲地区的农业生产和环境。本文利用HadGEM2区域气候模式输出的RCP4.5情景数据,基于时间序列分析及空间分析方法,对非洲大陆2010-2099年主要关键气候要素时空演变特征进行了预估,探讨了非洲大陆未来90年包括降水、辐射、平均气温、最高气温、最低气温等主要气候要素的时空变化格局。结果表明：各气候要素在不同时段的变化均表现出明显的地域分异差异： ① 相较于1970-1999年基准时段,未来3个时段(2020s、2050s、2080s)降水均增加,在2080s增至峰值,增加地区集中在20 °N附近的尼日尔、乍得、利比亚等国;最高增幅达4.5%;② 辐射增加区域分布在赤道地区和非洲大陆的南北两端,尤其是高海拔地区,如撒哈拉沙漠以北的阿特拉斯山脉附近,加丹加高原等地,最大增幅达0.04%;③ 未来90年非洲地区气温增加明显,包括平均气温、最高气温、最低气温,气温增幅由2020s、2050s、2080s依次递增,到2080s达到最大值,平均气温、最高气温、最低气温的最大增幅分别达到5、4.3和5.1 ℃。总体上,未来90年非洲大陆的气温较1970-1999年基准时段明显增多,但靠近海域的沿海地区增温较小,这是由于受到近海寒流的影响,起到了降温的作用。气温增幅过高也将不利于未来农业生产和地区安全。     

Prediction of Suitable Habitat for Lycophytes and Ferns in Northeast China: A Case Study on Athyrium brevifrons

Suitable habitat is vital for the survival and restoration of a species.Understanding the suitable habitat range for lycophytes and ferns is prerequisite for effective species resource conservation and recovery efforts.In this study, we took Athyrium brevifrons as an example, predicted its suitable habitat using a Maxent model with 67 occurrence data and nine environmental variables in Northeast China.The area under the curve(AUC) value of independent test data, as well as the comparison with specimen county areal distribution of A.brevifrons exhibited excellent predictive performance.The type of environmental variables showed that precipitation contributed the most to the distribution prediction, followed by temperature and topography.Percentage contribution and permutation importance both indicated that precipitation of driest quarter(Bio17) was the key factor in determining the natural distribution of A.brevifrons, the reason could be proved by the fern gametophyte biology.The analysis of high habitat suitability areas also showed the habitat preference of A.brevifrons: comparatively more precipitation and less fluctuation in the driest quarter.Changbai Mountains, covering almost all the high and medium habitat suitability areas, provide the best ecological conditions for the survival of A.brevifrons, and should be considered as priority areas for protection and restoration of the wild resource.The potential habitat suitability distribution map could provide a reference for the sustainable development and utilisation of A.brevifrons resource, and Maxent modelling could be valuable for conservation management planning for lycophytes and ferns in Northeast China.     

高精度曲面建模的中国气候降尺度模型

 与站点统计降尺度插值和动力降尺度相比,高精度曲面建模(HASM)降尺度,具有不需大尺度预报因子,直接从GCM结果构建区域上高空间分辨率的未来气候模拟曲面的优势。HASM降尺度将未来气候,分为历史观测拟合的气候基准值和GCM未来气候变化值进行模拟,精度明显高于传统方法,但常系数全局拟合的气候基准值忽略了降水分布的空间非平稳性,导致降水模拟受到较大影响。为增强降水降尺度的气候背景值的描述能力,通过分析全国尺度降水的非线性非平稳性特点,提出耦合空间变系数气候基准值的HASM空间变系数降尺度模型(HASM-SVDM)以改进HASM对非平稳要素的降尺度能力,并以1961-2010年全国气温降水观测数据结合地形特征信息,利用HASM降尺度方法对HadCM3的A1Fi、A2a和B2a 3种情景的1961-1990、2010-2039、2040-2069和2070-2099时段的全国未来气温与降水进行降尺度模拟。分析表明,耦合全局线性模型的HASM常系数降尺度模型适合全国气温的降尺度模拟,而耦合空间变系数拟合的HASM-SVDM增强了空间非平稳背景值的描述能力,模拟的空间分布更能体现降水总体的非均匀分布趋势,适合全国降水的降尺度模拟。     

气候变化情景下广东省降雨诱发型滑坡灾害潜在分布及预测

降雨诱发型滑坡灾害导致了人居环境的破坏并带来巨大的经济损失,尤其是在经济高度发达的粤港澳大湾区城市群。因此,急需有关降雨诱发型滑坡灾害分布的影响因素以及未来气候变化情景下潜在分布的研究。本文从气候变化角度出发,基于最大熵（MaxEnt）模型,结合气候、地形、地表覆盖等数据,揭示不同影响因素对当前气候环境下广东省滑坡空间分布的作用,进而阐述了未来气候情景下滑坡的潜在分布。结果表明：① 影响滑坡灾害空间分布的主要因子为最湿季度降雨量、7月降雨量、海拔和4月降雨量;② 当最湿季度降雨量处于593~742 mm、7月降雨量处于139~223 mm、海拔处于81~397 m和4月降雨量处于154~186 mm之间时,滑坡灾害较易发生;③ 受到气候变化的影响,当前密集分布于粤东地区的滑坡灾害高风险区的潜在分布范围和危害性总体呈现扩大趋势。本研究的结果可以为国土空间规划及城市群灾害预防提供科学依据。     

Future variation in mountainous discharge in arid northwestern China: A basin case study

To better understand the variation in mountainous discharge(MD) in the future, a basin case study was conducted in the upstream Taolai River Basin(UTRB) in arid northwestern China. The Blaney-Criddle(B-C) equation, Budyko framework, and water balance method were coupled for MD calculations. The outputs of 10 global climate models(GCMs) are synthesized to confirm the future changes in air temperature and precipitation under 3 selected Representative Concentration Pathway(RCP) scenarios. The climate elasticity(CE) method was used to determine the variation in MD, and the influence of climate factors on that was quantitatively analyzed. The results reveal that the coupling framework of the three methods is suitable for MD determination in the UTRB. The weight-based synthesis of the 10 GCM outputs shows overall increases in temperature(T) and precipitation(P) under the 3 scenarios during most of the time until 2099. The above climate change leads to an increase in MD. According to CE analysis, the positive effectiveness of precipitation is greater than the negative effectiveness of temperature on MD variation, and the increase in precipitation would induce more MD in the UTRB. Uncertainty analysis reveals that GCM outputs dominate in predicting precipitation, while the RCP scenarios influence temperature more. Overall, under the background of climate change, the risk of extreme floods during wet years might increase, and a water deficit will still occur during normal and dry years. The study provides a case example for better understanding MD responses to climate change in the upper reaches of inland river basins. Findings are helpful for reasonable water resource development and utilization in the middle and lower reaches of these basins in the future. As in the Taolai River Basin, considering the future water demand across the whole basin, the development of watersaving technologies and reasonable industrial structures is crucial for a sustainable future.     

Impacts of future climate change (2030-2059) on debris flow hazard: A case study in the Upper Minjiang River basin,China

An increase in extreme precipitation events due to future climate change will have a decisive influence on the formation of debris flows in earthquake-stricken areas. This paper aimed to describe the possible impacts of future climate change on debris flow hazards in the Upper Minjiang River basin in Northwest Sichuan of China, which was severely affected by the 2008 Wenchuan earthquake. The study area was divided into 1285 catchments, which were used as the basic assessment units for debris flow hazards. Based on the current understanding of the causes of debris flows, a binary logistic regression model was used to screen key factors based on local geologic, geomorphologic, soil, vegetation, and meteorological and climatic conditions. We used the weighted summation method to obtain a composite index for debris flow hazards, based on two weight allocation methods: Relative Degree Analysis and rough set theory. Our results showed that the assessment model using the rough set theory resulted in better accuracy. According to the bias corrected and downscaled daily climate model data, future annual precipitation (2030-2059) in the study area are expected to decrease, with an increasing number of heavy rainfall events. Under future climate change, areas with a high-level of debris flow hazard will be even more dangerous, and 5.9% more of the study area was categorized as having a high-level hazard. Future climate change will cause an increase in debris flow hazard levels for 128 catchments, accounting for 10.5% of the total area. In the coming few decades, attention should be paid not only to traditional areas with high-level of debris flow hazards, but also to those areas with an increased hazard level to improve their resilience to debris flow disasters.     

Potential distribution of a montane rodent(Cricetidae,Handleyomys chapmani) through time in Mexico: the importance of occurrence data

Ecological Niche Modeling uses the geographic coordinates of species presence records as the primary input to estimate potential geographic distributions. It is little known whether carrying out rigorous data pre-processing is necessary before building niche models to be transferred to different time period. Here we compared the current, past, and future potential distributions projected by niche models built from two different databases, an openaccess database and a database compiled ad hoc, for Handleyomys chapmani, a rodent closely associated with montane cloud forests in Mexico. The models predicted different spatial patterns of climatic suitability for the three periods examined. Based on our current knowledge of cloud forest species in Mexico, the distributions predicted by the model built from the ad hoc database are more ecologically realistic than those obtained from the open-access database. The models built using the open-access database were particularly inaccurate at the limits of the geographic range, predicting larger, more diffuse distributions for the three periods. We conclude that pre-processing occurrence data is crucial for mountain species, as the number of localities and even minor inaccuracies in the geographic coordinates can translate into very different climatic conditions due to abrupt altitudinal changes. Finally, the predicted shifts in the potential distribution of H. chapmani over time indicate that this species is highly susceptible to climate change.