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.     

气候变化下基于GIS的农田恶性杂草旱雀麦在中国的分布与发展趋势

为确定旱雀麦在我国的空间分布及其对气候变化的响应,以期进一步开展生态防控,本研究利用旱雀麦在中国的地理分布数据,结合当前气候数据和未来气候变化情景（RCP8.5情景下2050s,2070s）,建立最大熵模型（MaxEnt模型）,确定影响旱雀麦分布的主导环境因子。应用地理信息系统（GIS）对中国地区旱雀麦的适生区进行划分,以ROC曲线作为模拟的准确性评价指标。结果表明,MaxEnt模型模拟效果极好（AUC=0.965）;当前气候条件下,旱雀麦适生面积为2.5534×10⁶ km²,主要集中分布于青海省东北部、甘肃省与青海省接壤的地区、四川省的西北部,以及新疆的西北部;其中影响旱雀麦分布的主要环境因子为海拔、bio12（年降水量）、bio9（最干季度平均温度）和bio15（降水量季变异系数）,其贡献率分别为45.0%、17.5%、9.7%、9.7%,累计贡献率达81.9%;在RCP8.5情景下,未来2个时期,旱雀麦潜在高适生区分布面积与当前相比增加了12.2%~23.3%,但RCP8.5情景下2070s较RCP8.5情景下2050s旱雀麦的潜在高度适生区分布面积减少了8.9%。综上所述,气候变化情景下旱雀麦的潜在分布面积呈现出扩大趋势,且RCP8.5情景下2070s较RCP8.5情景下2050s的适生区分布面积有缩减趋势。     

Economic 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 2030s, 2050s, 2070s, and 2090s. 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 2090s 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 435.10×10⁶ and 537.20×10⁶ CNY in the 2050s and 2090s, respectively, and the cumulative economic loss value for 2099 is approximately 2124.00×10⁶ 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.     

Scenario simulation of water retention services under land use/cover and climate changes: a case study of the Loess Plateau,China

Comprehensive assessments of ecosystem services in environments under the influences of human activities and climate change are critical for sustainable regional ecosystem management. Therefore, integrated interdisciplinary modelling has become a major focus of ecosystem service assessment. In this study, we established a model that integrates land use/cover change (LUCC), climate change, and water retention services to evaluate the spatial and temporal variations of water retention services in the Loess Plateau of China in the historical period (2000-2015) and in the future (2020-2050). An improved Markov-Cellular Automata (Markov-CA) model was used to simulate land use/land cover patterns, and ArcGIS 10.2 software was used to simulate and assess water retention services from 2000 to 2050 under six combined scenarios, including three land use/land cover scenarios (historical scenario (HS), ecological protection scenario (EPS), and urban expansion scenario (UES)) and two climate change scenarios (RCP4.5 and RCP8.5, where RCP is the representative concentration pathway). LUCCs in the historical period (2000-2015) and in the future (2020-2050) are dominated by transformations among agricultural land, urban land and grassland. Urban land under UES increased significantly by 0.63×10³ km²/a, which was higher than the increase of urban land under HS and EPS. In the Loess Plateau, water yield decreased by 17.20×10⁶ mm and water retention increased by 0.09×10⁶ mm in the historical period (2000-2015), especially in the Interior drainage zone and its surrounding areas. In the future (2020-2050), the pixel means of water yield is higher under RCP4.5 scenario (96.63 mm) than under RCP8.5 scenario (95.46 mm), and the pixel means of water retention is higher under RCP4.5 scenario (1.95 mm) than under RCP8.5 scenario (1.38 mm). RCP4.5-EPS shows the highest total water retention capacity on the plateau scale among the six combined scenarios, with the value of 1.27×10⁶ mm. Ecological restoration projects in the Loess Plateau have enhanced soil and water retention. However, more attention needs to be paid not only to the simultaneous increase in water retention services and evapotranspiration but also to the type and layout of restored vegetation. Furthermore, urbanization needs to be controlled to prevent uncontrollable LUCCs and climate change. Our findings provide reference data for the regional water and land resources management and the sustainable development of socio-ecological systems in the Loess Plateau under LUCC and climate change scenarios.     

Runoff of arid and semi-arid regions simulated and projected by CLM-DTVGM and its multi-scale fluctuations as revealed by EEMD analysis

Runoff is a major component of the water cycle,and its multi-scale fluctuations are important to water resources management across arid and semi-arid regions.This paper coupled the Distributed Time Variant Gain Model(DTVGM)into the Community Land Model(CLM 3.5),replacing the TOPMODEL-based method to simulate runoff in the arid and semi-arid regions of China.The coupled model was calibrated at five gauging stations for the period 1980–2005 and validated for the period 2006–2010.Then,future runoff(2010–2100)was simulated for different Representative Concentration Pathways(RCP)emission scenarios.After that,the spatial distributions of the future runoff for these scenarios were discussed,and the multi-scale fluctuation characteristics of the future annual runoff for the RCP scenarios were explored using the Ensemble Empirical Mode Decomposition(EEMD)analysis method.Finally,the decadal variabilities of the future annual runoff for the entire study area and the five catchments in it were investigated.The results showed that the future annual runoff had slowly decreasing trends for scenarios RCP 2.6 and RCP 8.5 during the period 2010–2100,whereas it had a non-monotonic trend for the RCP 4.5 scenario,with a slow increase after the 2050 s.Additionally,the future annual runoff clearly varied over a decadal time scale,indicating that it had clear divisions between dry and wet periods.The longest dry period was approximately 15 years(2040–2055)for the RCP 2.6 scenario and 25 years(2045–2070)for the RCP 4.5 scenario.However,the RCP 8.5 scenario was predicted to have a long dry period starting from 2045.Under these scenarios,the water resources situation of the study area will be extremely severe.Therefore,adaptive water management measures addressing climate change should be adopted to proactively confront the risks of water resources.     

气候变化对新疆意大利蝗潜在分布的影响

意大利蝗Calliptamus italicus(L.)是新疆草原主要优势蝗虫之一,每年给新疆畜牧业经济带来严重损失,气候变化对其潜在分布影响的预测对其科学防治有重要意义。本研究采用意大利蝗的分布数据和生物气候数据,结合MaxEnt模型和ArcGIS软件,预测了BCC_CSM1.1气候模式下政府间气候变化专门委员会第五次工作报告(IPCC AR5)采用的RCP2.6、RCP4.5和RCP8.5三种气候情景在2021-2040年(2030s)、2041-2060年(2050s)和2061-2080年(2070s)的意大利蝗新疆潜在适生区分布范围。结果表明:在BCC_CSM1.1的各情景下,意大利蝗适生区在北疆及天山一带分布格局基本保持不变,但高度适生区面积都有所增加,其中在天山和阿尔泰山地区,意大利蝗中、高度适生区范围将向更高海拔区域蔓延,在北疆阿勒泰地区高度适生区明显增加。极端水分条件和水热条件对意大利蝗在新疆潜在分布发挥主要作用,其中4月、10月、3月和11月降水量对意大利蝗在新疆潜在分布影响最大,因其直接影响土壤相对含水量和土壤温度,从而决定意大利蝗卵的存活量。     

Climate change impacts on the streamflow of Zarrineh River,Iran

Zarrineh River is located in the northwest of Iran, providing more than 40% of the total inflow into the Lake Urmia that is one of the largest saltwater lakes on the earth. Lake Urmia is a highly endangered ecosystem on the brink of desiccation. This paper studied the impacts of climate change on the streamflow of Zarrineh River. The streamflow was simulated and projected for the period 1992-2050 through seven CMIP5 (coupled model intercomparison project phase 5) data series (namely, BCC-CSM1-1, BNU-ESM, CSIRO-Mk3-6-0, GFDL-ESM2G, IPSL-CM5A-LR, MIROC-ESM and MIROC-ESM-CHEM) under RCP2.6 (RCP, representative concentration pathways) and RCP8.5. The model data series were statistically downscaled and bias corrected using an artificial neural network (ANN) technique and a Gamma based quantile mapping bias correction method. The best model (CSIRO-Mk3-6-0) was chosen by the TOPSIS (technique for order of preference by similarity to ideal solution) method from seven CMIP5 models based on statistical indices. For simulation of streamflow, a rainfall-runoff model, the hydrologiska byrans vattenavdelning (HBV-Light) model, was utilized. Results on hydro-climatological changes in Zarrineh River basin showed that the mean daily precipitation is expected to decrease from 0.94 and 0.96 mm in 2015 to 0.65 and 0.68 mm in 2050 under RCP2.6 and RCP8.5, respectively. In the case of temperature, the numbers change from 12.33°C and 12.37°C in 2015 to 14.28°C and 14.32°C in 2050. Corresponding to these climate scenarios, this study projected a decrease of the annual streamflow of Zarrineh River by half from 2015 to 2050 as the results of climatic changes will lead to a decrease in the annual streamflow of Zarrineh River from 59.49 m³/s in 2015 to 22.61 and 23.19 m³/s in 2050. The finding is of important meaning for water resources planning purposes, management programs and strategies of the Lake's endangered ecosystem.     

A look into the past,present and future potential distributions of Talinopsis frutescens,a North American endemic lineage closely related to Cactaceae

Talinopsis frutescens(Anacampserotaceae,a family that is close related to Cactaceae)is a succulent species endemic to North America.The aim of this study was to explore,using Ecological Niche Modeling(ENM),changes in potential distribution ranges considering different climate scenarios:past conditions during the Last Inter Glacial(LIG)and the Last Glacial Maximum(LGM),the present and projections for 2070(RCP 2.6 to 8.5).A pattern of contraction is observed during the LIG,which agrees with other studies focused in species from arid environments.This pattern was followed by a migration towards the south during the LGM and a possible recent expansion to the north as is observed in the present scenario.All future projections show the same contraction and fragmentation patterns,resulting in three discontinuous areas:the northern part of the Chihuahuan Desert,the southern-central part of the Mexican Plateau,and the smallest one in the Tehuacán-Cuicatlán Valley.Our projections for future scenarios agree with other studies and support that global climate change tends to alter the current distribution of arid environment species.     

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-HadGEM2-ES and Eta-MIROC5) from the National Institute for Space Research, and then input the data of bulk density, pH, 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-HadGEM2-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-HadGEM2-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.     

西北干旱区白刺属植物适生环境的模拟分析

白刺属(Nitraria L.)植物是古地中海第三纪孑遗植物,对我国西北干旱、半干旱地区具有极高的生态效益。本研究基于MaxEnt模型和ArcGIS软件及其SDM工具箱预测了过去到未来不同时期下白刺属6个物种在我国的潜在适生区及其迁移路线,以期为该属植物的保护及资源利用方面提供一定的理论依据。结果表明:白刺属植物当代在我国的高适生区面积占我国国土总面积的6.32%,主要集中在宁夏北部、内蒙古南部和新疆西部地区。与过去相比,白刺属植物的潜在高适生区在当代减少了1.68%。与当代相比,白刺属植物高适生区预测面积在2070年(RCP4.5)气候情景下减少了0.13%,在2070年(RCP8.5)气候情景下增加了1.61%,主要集中在甘肃东南部和宁夏地区;白刺属植物在我国潜在适生区的主导环境因子是最冷月最低温(bio6);最冷季度的平均降水量(bio19)和年均温(bio1)是影响白刺属潜在地理分布的主要环境因子;白刺属植物在末次间冰期(LIG)、末次冰盛期(LGM)、当代及2070年(RCP4.5和RCP8.5)均有向青海等高海拔地区迁移的趋势。     

Projections of temperature extremes based on preferred CMIP5 models:a case study in the Kaidu-Kongqi River basin in Northwest China

The extreme temperature has more outstanding impact on ecology and water resources in arid regions than the average temperature. Using the downscaled daily temperature data from 21 Coupled Model Inter-comparison Project(CMIP) models of NASA Earth Exchange Global Daily Downscaled Projections(NEX-GDDP) and the observation data, this paper analyzed the changes in temporal and spatiotemporal variation of temperature extremes, i.e., the maximum temperature(Tmax) and minimum temperature(Tmin), in the Kaidu-Kongqi River basin in Northwest China over the period 2020–2050 based on the evaluation of preferred Multi-Model Ensemble(MME). Results showed that the Partial Least Square ensemble mean participated by Preferred Models(PM-PLS) was better representing the temporal change and spatial distribution of temperature extremes during 1961–2005 and was chosen to project the future change. In 2020–2050, the increasing rate of Tmax(Tmin) under RCP(Representative Concentration Pathway) 8.5 will be 2.0(1.6) times that under RCP4.5, and that of Tmin will be larger than that of Tmax under each corresponding RCP. Tmin will keep contributing more to global warming than Tmax. The spatial distribution characteristics of Tmax and Tmin under the two RCPs will overall the same; but compared to the baseline period(1986–2005), the increments of Tmax and Tmin in plain area will be larger than those in mountainous area. With the emission concentration increased, however, the response of Tmax in mountainous area will be more sensitive than that in plain area, and that of Tmin will be equivalently sensitive in mountainous area and plain area. The impacts induced by Tmin will be universal and farreaching. Results of spatiotemporal variation of temperature extremes indicate that large increases in the magnitude of warming in the basin may occur in the future. The projections can provide the scientific basis for water and land plan management and disaster prevention and mitigation in the inland river basin.     

南方小花蝽对三种蚜虫的捕食能力和喜好性

南方小花蝽Orius similis是我国南方农田生态系统中一种对小型害虫极具控害潜力的重要捕食性天敌昆虫.为了明确天敌南方小花蝽对云南小春作物上常见蚜虫的捕食能力和喜好性,本文在实验室条件下研究了南方小花蝽5龄若虫、雌雄成虫对不同组猎物的捕食喜好性.选取云南小春作物上3种主要蚜虫种类:烟蚜Myzus persicae...     

21世纪开都-孔雀河流域未来气候变化情景预估

利用Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections (DCHP)提供的31个 CMIP5降尺度数据和CRU逐月气温、降水格点数据集，通过评估PLS(偏最小二乘回归)、RR（岭回归）和EE（等权平均）3种多模式集合平均预估模型对历史气候变化的模拟能力，确定最优集合方法，进而预估开都-孔雀河流域21世纪气候变化情景。结果表明：① 所建立的PLS模型对流域的气温和降水具有较好的模拟能力，尤其对气温的模拟， r值均达到了0.64以上，明显优于降水（0.19~0.36），但存在空间异质性；② 21世纪开都-孔雀河流域各子区气温呈显著增加趋势，且RCP8.5情景下的增温速率〔0.58~0.67 ℃·（10a）-1〕是RCP4.5情景下〔0.25~0.31 ℃·（10a）-1〕的2倍以上，21世纪中叶是2种情景产生明显差异的开始。整个流域增温速率由西北山区向东南荒漠区逐渐增大；③ 未来降水在不同排放情景下变化速率的分布状况略有不同，但均呈显著增加趋势，且RCP8.5情景下的增加速率〔1.22%~1.54%·（10a）-1〕总体上高于RCP4.5〔0.80%~1.32%·（10a）-1〕。     

Prediction of meteorological drought in arid and semi-arid regions using PDSI and SDSM: a case study in Fars Province,Iran

Drought is one of the most significant environmental disasters,especially in arid and semi-arid regions.Drought indices as a tool for management practices seeking to deal with the drought phenomenon are widely used around the world.One of these indicators is the Palmer drought severity index(PDSI),which is used in many parts of the world to assess the drought situation and continuation.In this study,the drought state of Fars Province in Iran was evaluated by using the PDSI over 1995-2014 according to meteorological data from six weather stations in the province.A statistical downscaling model(SDSM)was used to apply the output results of the general circulation model in Fars Province.To implement data processing and prediction of climate data,a statistical period 1995-2014 was considered as the monitoring period,and a statistical period 2019-2048 was for the prediction period.The results revealed that there is a good agreement between the simulated precipitation(R2>0.63;R2,determination coefficient;MAE<0.52;MAE,mean absolute error;RMSE<0.56;RMSE,Root Mean Squared Error)and temperature(R2>0.95,MAE<1.74,and RMSE<1.78)with the observed data from the stations.The results of the drought monitoring model presented that dry periods would increase over the next three decades as compared to the historical data.The studies showed the highest drought in the meteorological stations Abadeh and Lar during the prediction period under two future scenarios representative concentration pathways(RCP4.5 and RCP8.5).According to the results of the validation periods and efficiency criteria,we suggest that the SDSM is a proper tool for predicting drought in arid and semi-arid regions.     

基于MaxEnt模型预测苹红缢管蚜在中国的适生区

为评估苹红缢管蚜Rhopalosiphum oxyacanthae入侵我国的潜在地理分布范围,基于其在全球的118个分布点和筛选的9个环境变量数据,利用MaxEnt模型和ArcGIS软件对苹红缢管蚜于当前和未来气候条件下在我国的潜在适生区进行预测。结果表明,基于苹红缢管蚜的全球分布数据,MaxEnt模型预测的平均AUC值为0.919,预测结果准确性较高。当前气候条件下,苹红缢管蚜在我国的总适生区面积占全国陆地面积的48.73%,其中高、中、低适生区的面积分别占全国陆地面积的5.92%、13.30%和29.51%,高适生区主要位于河南、江苏、安徽、湖北、湖南、贵州、江西、浙江、福建、广西、台湾等省区。未来RCP2.6和RCP8.5气候情景下,苹红缢管蚜在我国的总适生区面积增加并呈逐渐向东北方向迁移扩散的趋势,其中低适生区面积逐渐增加,高、中适生区面积逐渐减少,原先中南部的高适生区逐渐转变为低适生区或非适生区,但新疆维吾尔自治区北部、吉林省与辽宁省边界处的高适生区面积呈逐渐增加趋势。表明苹红缢管蚜在我国的适生范围极为广泛,具有较高的入侵风险,应加强进境口岸对该虫的检疫监管力度。     

Meteorological drought features in northern and northwestern parts of Mexico under different climate change scenarios

Meteorological drought has been an inevitable natural disaster throughout Mexican history and the northern and northwestern parts of Mexico(i.e., the studied area), where the mean annual precipitation(MAP) is less than 500 mm, have suffered even more from droughts in the past. The aim of this study was to conduct a meteorological drought analysis of the available MAP data(1950–2013) from 649 meteorological stations selected from the studied area and to predict the drought features under the different IPCC-prescribed climate change scenarios. To determine the long-term drought features, we collected 1×10~4 synthetic samples using the periodic autoregressive moving average(PARMA) model for each rainfall series. The simulations first consider the present prevailing precipitation conditions(i.e., the average from 1950 to 2013) and then the precipitation anomalies under IPCC-prescribed RCP 4.5 scenario and RCP 8.5 scenario. The results indicated that the climate changes under the prescribed scenarios would significantly increase the duration and intensity of droughts. The most severe impacts may occur in the central plateau and in the Baja California Peninsula. Thus, it will be necessary to establish adequate protective measures for the sustainable management of water resources in these regions.     

南方小花蝽对为害蚕豆的三种蚜虫的捕食作用

豆蚜Aphis craccivora、豌豆蚜Acyrthosiphon pisum和豌豆修尾蚜Megoura crassicauda是为害豆科作物的主要害虫。南方小花蝽Orius strigicollis是重要捕食性食蚜天敌,广泛分布于我国南方。为明确南方小花蝽对豆科作物上3种蚜虫的捕食作用和生物防治潜能,本研究在实验室条件下,测定了南方小花蝽对3种蚜虫的捕食选择性和捕食功能反应。结果表明,南方小花蝽对3种蚜虫的捕食功能反应均符合Holling Ⅱ模型,不同龄期南方小花蝽对3种蚜虫捕食量由大到小依次为5龄若虫,雌成虫,低龄若虫。对豆蚜的捕食量均大于对豌豆修尾蚜的捕食量,对豌豆蚜的捕食量最小,雌成虫对以上3种蚜虫的日最大捕食量分别为豆蚜63.69头/d、豌豆蚜36.23头/d和豌豆修尾蚜49.26头/d。南方小花蝽对3种蚜虫的寻找效应随蚜虫密度的增加而降低,随小花蝽龄期的增加而升高,相同龄期的南方小花蝽对3种蚜虫的寻找效应由大到小依次为豌豆修尾蚜,豆蚜,豌豆蚜。南方小花蝽对猎物的捕食作用受自身密度的干扰,当猎物密度不变时,随着小花蝽自身密度的增加,单头小花蝽平均捕食量下降,其干扰反应符合HasseⅡ模型方程。南方小花蝽对豆蚜、豌豆蚜和豌豆修尾蚜的喜好性指数分别为0.186、-0.245、0.027,对豆蚜和豌豆修尾蚜表现出正喜好性,且对豆蚜的喜好性强于豌豆修尾蚜,但对豌豆蚜表现出负喜好性。综上所述,南方小花蝽对豆科作物上的3种蚜虫具有良好的防治潜能。     

Impact of climate change on the streamflow in the glacierized Chu River Basin,Central Asia

Catchments dominated by meltwater runoff are sensitive to climate change as changes in precipitation and temperature inevitably affect the characteristics of glaciermelt/snowmelt, hydrologic circle and water resources. This study simulated the impact of climate change on the runoff generation and streamflow of Chu River Basin(CRB), a glacierized basin in Central Asia using the enhanced Soil and Water Assessment Tool(SWAT). The model was calibrated and validated using the measured monthly streamflow data from three discharge gauge stations in CRB for the period 1961–1985 and was subsequently driven by downscaled future climate projections of five Global Circulation Models(GCMs) in Coupled Model Inter-comparison Project Phase 5(CMIP5) under three radiative forcing scenarios(RCP2.6, RCP4.5 and RCP8.5). In this study, the period 1966–1995 was used as the baseline period, while 2016–2045 and 2066–2095 as the near-future and far-future period, respectively. As projected, the climate would become warmer and drier under all scenarios in the future, and the future climate would be characterized by larger seasonal and annual variations under higher RCP. A general decreasing trend was identified in the average annual runoff in glacier(–26.6% to –1.0%), snow(–21.4% to +1.1%) and streamflow(–27.7% to –6.6%) for most of the future scenario periods. The projected maximum streamflow in each of the two future scenarios occurred one month earlier than that in the baseline period because of the reduced streamflow in summer months. Results of this study are expected to arouse the serious concern about water resource availability in the headwater region of CRB under the continuously warming climate. Changes in simulated hydrologic outputs underscored the significance of lowering the uncertainties in temperature and precipitation projection.     

Ecological determinants and risk areas of Striga hermonthica infestation in western Kenya under changing climate

Striga hermonthica (Del.) Benth is a parasitic weed that is damaging major cereal crops in sub-Saharan Africa (SSA). Although Striga is recognised as an agricultural scourge, there is limited information available indicating the extent of its growth and spread as impacted by the changing climate in Kenya. This study investigated the impact of current climate conditions and projected future (2050) climate change on the infestation of Striga hermonthica in the western Kenya region. Specifically, the study aimed to predict Striga hermonthica habitat suitability in five counties in the western Kenya region through using the maximum entropy (MaxEnt) model and bioclimatic, soil, topographic and land use, and land cover (LULC) variables. Striga hermonthica geolocations were collected and collated and ecological niche models were developed to determine the habitat suitability. The results showed that approximately 1767 km² (10% of the total study area) is currently highly suitable for Striga hermonthica occurrence. The future projections showed a range between 2106 km² (19% of the total study area) and 2712 km² (53% of the total study area) at the minimum carbon (RCP 2.6) and the maximum carbon emission scenarios (RCP 8.5) respectively. Elevation, annual precipitation, LULC, temperature seasonality and soil type were determined to be the most influential ecological predictor variables for Striga hermonthica establishment. The study revealed the importance of using climate, soil, topographic and LULC variables when evaluating agricultural production constraints such as Striga's prevalence. The methodology used in this study should be tested in other Striga affected areas.     

Assessing the collapse risk of Stipa bungeana grassland in China based on its distribution changes

The criteria used by International Union for Conservation of Nature(IUCN) for its Red List of Ecosystems(RLE) are the global standards for ecosystem-level risk assessment, and they have been increasingly used for biodiversity conservation. The changed distribution area of an ecosystem is one of the key criteria in such assessments. The Stipa bungeana grassland is one of the most widely distributed grasslands in the warm-temperate semi-arid regions of China. However, the total distribution area of this grassland was noted to have shrunk and become fragmented because of its conversion to cropland and grazing-induced degradation. Following the IUCN-RLE standards, here we analyzed changes in the geographical distribution of this degraded grassland, to evaluate its degradation and risk of collapse. Past(1950-1980) distribution areas were extracted from the Vegetation Map of China(1:1,000,000). Present realizable distribution areas were equated to these past areas minus any habitat area losses. We then predicted the grassland’s present and future(under the Representative Concentration Pathway 8.5 scenario) potential distribution areas using maximum entropy algorithm(MaxEnt), based on field survey data and nine environmental layers. Our results showed that the S. bungeana grassland was mainly distributed in the Loess Plateau, Hexi Corridor, and low altitudes of the Qilian Mountains and Longshou Mountain. This ecosystem occurred mainly on loess soils, kastanozems, steppe aeolian soils and sierozems. Thermal and edaphic factors were the most important factors limiting the distribution of S. bungeana grassland across China. Since 56.1% of its past distribution area(4.9×10~4 km^2) disappeared in the last 50 a, the present realizable distribution area only amounts to 2.2×10~4 km^2. But only 15.7% of its present potential distribution area(14.0×10~4 km^2) is actually occupied by the S. bungeana grassland. The future potential distribution of S. bungeana grassland was predicted to shift towards northwest, and the total area of this ecosystem will shrink by 12.4% over the next 50 a under the most pessimistic climate change scenario. Accordingly, following the IUCN-RLE criteria, we deemed the S. bungeana grassland ecosystem in China to be endangered(EN). Revegetation projects and the establishment of protected areas are recommended as effective ways to avert this looming crisis. This empirical modeling study provides an example of how IUCN-RLE categories and criteria may be valuably used for ecosystem assessments in China and abroad.