Invasive alien ants(IAAs)are among the most aggressive,competitive,and widespread invasive alien species(IAS)worldwide.Wasmannia auropunctata,the greatest IAAs threat in the Pacific region and listed in“100 of the wo...Invasive alien ants(IAAs)are among the most aggressive,competitive,and widespread invasive alien species(IAS)worldwide.Wasmannia auropunctata,the greatest IAAs threat in the Pacific region and listed in“100 of the world’s worst IAS”,has established itself in many countries and on islands worldwide.Wild populations of W.auropunctata were recently reported in southeastern China,representing a tremendous potential threat to China’s agricultural,economic,environmental,public health,and social well-being.Estimating the potential geographical distribution(PGD)of W.auropunctata in China can illustrate areas that may potentially face invasion risk.Therefore,based on the global distribution records of W.auropunctata and bioclimatic variables,we predicted the geographical distribution pattern of W.auropunctata in China under the effects of climate change using an ensemble model(EM).Our findings showed that artificial neural network(ANN),flexible discriminant analysis(FDA),gradient boosting model(GBM),Random Forest(RF)were more accurate than categorical regression tree analysis(CTA),generalized linear model(GLM),maximum entropy model(MaxEnt)and surface distance envelope(SRE).The mean TSS values of ANN,FDA,GBM,and RF were 0.820,0.810,0.843,and 0.857,respectively,and the mean AUC values were 0.946,0.954,0.968,and 0.979,respectively.The mean TSS and AUC values of EM were 0.882 and 0.972,respectively,indicating that the prediction results with EM were more reliable than those with the single model.The PGD of W.auropunctata in China is mainly located in southern China under current and future climate change.Under climate change,the PGD of W.auropunctata in China will expand to higher-latitude areas.The annual temperature range(bio7)and mean temperature of the warmest quarter(bio10)were the most significant variables affecting the PGD of W.auropunctata in China.The PGD of W.auropunctata in China was mainly attributed to temperature variables,such as the annual temperature range(bio7)and the mean temperature of the warmest quarter(bio10).The populations of W.auropunctata in southern China have broad potential invasion areas.Developing strategies for the early warning,monitoring,prevention,and control of W.auropunctata in southern China requires more attention.展开更多
采集全国22种典型土壤,通过室内土柱试验,探讨雨水(p H 5.6)作用下污染土壤Hg(外源添加2mg/kg)的淋溶和释放特征,并对影响土壤Hg淋溶特性的因子进行分析.结果表明,22种土壤Hg的释放过程大致分为3类,第1类包括黑土?黑钙土?草毡土?水稻土...采集全国22种典型土壤,通过室内土柱试验,探讨雨水(p H 5.6)作用下污染土壤Hg(外源添加2mg/kg)的淋溶和释放特征,并对影响土壤Hg淋溶特性的因子进行分析.结果表明,22种土壤Hg的释放过程大致分为3类,第1类包括黑土?黑钙土?草毡土?水稻土?暗棕壤?福州黄壤?黄泥土?栗钙土,这8种土壤在整个淋溶过程中淋出液Hg浓度极低,未超过地下水III级标准(1μg/L).第2类包括广西红壤?贵州黄壤?棕壤?灰钙土?黄绵土等5种土壤,淋溶前期(2~3L)Hg含量较低,到淋溶中期含量显著上升,随后出现下降,到淋溶末期(5~6L)淋溶液Hg含量降低到III级标准以下.第3类土壤包括砖红壤?黄棕壤?紫色土?褐土?赤红壤?潮土?盐碱土?江西红壤?棕漠土等9种土壤,淋溶过程呈现2个阶段,当淋溶体积在4L之内,淋出液中Hg浓度较高,且变化比较剧烈,对环境及地下水威胁较大,超出4L后,Hg释放速率明显变缓,浓度降低到III级标准以下.模拟降雨条件下22种土壤Hg的释放率为0.33%~5.95%,最高的是贵州黄壤,最低是吉林黑土,平均为1.55%.逐步回归分析的结果表明,土壤有机质(OM)?p H及土壤汞含量(THg)对降雨作用下土壤Hg累计释放量(q)有重要作用,三者累计的决定系数为0.5865,回归方程为lnq=1.8+0.62ln THg-0.109p H-0.918ln展开更多
基金supported by the National Key R&D Program of China(2021YFC2600400)the Technology Innovation Program of the Chinese Academy of Agricultural Sciences(caascx-2017-2022-IAS)the Key R&D Program of Yunnan Province,China(202103AF140007)。
文摘Invasive alien ants(IAAs)are among the most aggressive,competitive,and widespread invasive alien species(IAS)worldwide.Wasmannia auropunctata,the greatest IAAs threat in the Pacific region and listed in“100 of the world’s worst IAS”,has established itself in many countries and on islands worldwide.Wild populations of W.auropunctata were recently reported in southeastern China,representing a tremendous potential threat to China’s agricultural,economic,environmental,public health,and social well-being.Estimating the potential geographical distribution(PGD)of W.auropunctata in China can illustrate areas that may potentially face invasion risk.Therefore,based on the global distribution records of W.auropunctata and bioclimatic variables,we predicted the geographical distribution pattern of W.auropunctata in China under the effects of climate change using an ensemble model(EM).Our findings showed that artificial neural network(ANN),flexible discriminant analysis(FDA),gradient boosting model(GBM),Random Forest(RF)were more accurate than categorical regression tree analysis(CTA),generalized linear model(GLM),maximum entropy model(MaxEnt)and surface distance envelope(SRE).The mean TSS values of ANN,FDA,GBM,and RF were 0.820,0.810,0.843,and 0.857,respectively,and the mean AUC values were 0.946,0.954,0.968,and 0.979,respectively.The mean TSS and AUC values of EM were 0.882 and 0.972,respectively,indicating that the prediction results with EM were more reliable than those with the single model.The PGD of W.auropunctata in China is mainly located in southern China under current and future climate change.Under climate change,the PGD of W.auropunctata in China will expand to higher-latitude areas.The annual temperature range(bio7)and mean temperature of the warmest quarter(bio10)were the most significant variables affecting the PGD of W.auropunctata in China.The PGD of W.auropunctata in China was mainly attributed to temperature variables,such as the annual temperature range(bio7)and the mean temperature of the warmest quarter(bio10).The populations of W.auropunctata in southern China have broad potential invasion areas.Developing strategies for the early warning,monitoring,prevention,and control of W.auropunctata in southern China requires more attention.
