Knowledge on the potential suitability of tree species to the site is very important for forest management planning.Natural forest distribution provides a good reference for afforestation and forest restoration.In thi...Knowledge on the potential suitability of tree species to the site is very important for forest management planning.Natural forest distribution provides a good reference for afforestation and forest restoration.In this study,we developed species distribution model(SDM)for 16 major tree species with 2,825 permanent sample plots with natural origin from Chinese National Forest Inventory data collected in Jilin Province using the Maxent model.Three types of environmental factors including bioclimate,soil and topography with a total of 33 variables were tested as the input.The values of area under the curve(AUC,one of the receiver operating characteristics of the Maxent model)in the training and test datasets were between 0.784 and 0.968,indicating that the prediction results were quite reliable.The environmental factors affecting the distribution of species were ranked in terms of their importance to the species distribution.Generally,the climatic factors had the greatest contribution,which included mean diurnal range,annual mean temperature,temperature annual range,and iosthermality.But the main environmental factors varied with tree species.Distribution suitability maps under current(1950-2000)and future climate scenarios(CCSM4-RCP 2.6 and RCP 6.0 during 2050)were produced for 16 major tree species in Jilin Province using the model developed.The predicted current and future ranges of habitat suitability of the 16 tree species are likely to be positively and negatively affected by future climate.Seven tree species were found to benefit from future climate including B etula costata,Fraxinus mandshurica,Juglans mandshurica,Phellodendron amurense,Populus ussuriensis,Quercus mongolica and Ulmus pumila;five tree species will experience decline in their suitable habitat including B.platyphylla,Tilia mongolica,Picea asperata,Pinus sylvestris,Pinus koraiensis;and four(Salix koreensis,Abies fabri,Pinus densiflora and Larix olgensis)showed the inconsistency under RCP 2.6 and RCP 6.0 scenarios.The maps of the habitat suitability can be used as a basis for afforestation and forest restoration in northeastern China.The SDMs could be a potential tool for forest management planning.展开更多
It is increasingly relevant to study the effects of climate change on species habitats. Using a maximum entropy model, 22 environmental factors with significant effects on sorghum habitat distribution in China were se...It is increasingly relevant to study the effects of climate change on species habitats. Using a maximum entropy model, 22 environmental factors with significant effects on sorghum habitat distribution in China were selected to predict the potential habitat distribution of sorghum in China. The potential distribution of sorghum under baseline climate conditions and future climate conditions (2050s and 2070s) under two climate change scenarios, RCP4.5 and RCP8.5, were simulated, and the receiver operating curve under the accuracy of the model was evaluated using the area under the receiver operating curve (AUC). The results showed that the maximum entropy model predicted the potential sorghum habitat distribution with high accuracy, with Bio2 (monthly mean diurnal temperature difference), Bio6 (minimum temperature in the coldest month), and Bio13 (rainfall in the wettest month) as the main climatic factors affecting sorghum distribution among the 22 environmental factors. Under the baseline climate conditions, potential sorghum habitats are mainly distributed in the southwest, central, and east China. Over time, the potential sorghum habitat expanded into northern and southern China, with significant additions and negligible decreases in potential sorghum habitat in the study area, and a significant increase in total area, with the RCP8.5 scenario adding much more area than the RCP4.5 scenario.展开更多
Incorporating private and working lands into protected area networks could mitigate the isolation state of protected areas(PAs) and improve the efficiency of conservation.But how to select patches of land for conserva...Incorporating private and working lands into protected area networks could mitigate the isolation state of protected areas(PAs) and improve the efficiency of conservation.But how to select patches of land for conservation is still a troublesome issue.In this study, the MaxEnt model and irreplaceability index were applied to guide marsh conservation in the Nenjiang River Basin, Northeast China.According to the high accuracy of the MaxEnt model predictions(i.e., the average AUC value = 0.933), the Wuyuer River and Zhalong marshes in the downstream reaches of Wuyuer River are the optimal habitat for the Red-crowned crane and migratory waterfowls.There are 22 marsh patches selected by the patch irreplaceability index for conservation, of which 12 patches had been included in the current network of protected areas.The other 10 patches of marsh(amounting to 1096 km^2) far from human disturbances with high NDVI(up to 0.8) and close distance to water(less than 100 m), which are excluded from the existing network of PAs, should be implemented conservation easement programs to improve the protection efficiency of conservation.Specifically, the marshes at Taha, Tangchi, and Lamadian should be given priority for conservation and restoration to reintroduce migratory waterfowls, as this would lessen the current isolation state of the Zhalong National Nature Reserve.展开更多
Aims Predicting suitable habitat distribution is an effective way to protect rare or endangered medicinal plants.Cornus officinalis is a perennial tree growing in forest edge and its air-dried pericarp is one of the t...Aims Predicting suitable habitat distribution is an effective way to protect rare or endangered medicinal plants.Cornus officinalis is a perennial tree growing in forest edge and its air-dried pericarp is one of the traditional Chinese medicines(TCM)with significant medicinal values.In recent years,C.officinalis has undergone severe degeneration of its natural habitat owing to growing market demands and unprecedented damage to the forests.Moreover,the degeneration of suitable habitat has threatened the supply of medicinal materials,and even led to the extinction of some engendered medicinal plant species.In this case,there is a great risk to introduce and cultivate medicinal plants if planners determine the suitable cultivation regions based on personal subjective experience alone.Therefore,predicting suitable potential habitat distribution of medicinal plants(e.g.C.officinalis)and revealing the environmental factors determining such distribution patterns are important to habitat conservation and environmental restoration.Methods In this article,we report the results of a study on the habitat distribution of C.officinalis using maximum entropy(Maxent)modeling and fuzzy logics together with loganin content and environmental variables.The localities of 106 C.officinalis in China were collected by our group and other researchers and used as occurrence data.The loganin content of 234 C.officinalis germplasm resources were tested by high-performance liquid chromatography(HPLC)and used as content data.79 environmental variables were selected and processed with multicollinearity test by using Pearson Correlation Coefficient(r)to determine a set of independent variables.The chosen variables were then processed in the fuzzy linear model according to the cell values(maximum,minimum)of localities with estimated loganin content.The SDMtoolbox was used to spatially rarefy occurrence data and prepare bias files.Furthermore,combined Maxent modeling and fuzzy logics were used to predict the suitable habitat of C.officinalis.The modeling result was validated using null-model method.Important Findings As a result,six environmental factors including tmin3,prec3,bio4,alt,bio12 and bio3 were determined as key influential factors that mostly affected both the habitat suitability and active ingredient of C.officinalis.The highly suitable regions of C.officinalis mainly distribute in a‘core distribution zone’of the east-central China.The statistically significant AUC value indicated that combined Maxent modeling and fuzzy logics could be used to predict the suitable habitat distribution of medicinal plants.Furthermore,our results confirm that ecological factors played critical roles in assessing suitable geographical regions as well as active ingredient of plants,highlighting the need for effective habitat rehabilitation and resource conservation.展开更多
Introduction:Climate change will either improve,reduce,or shift its appropriate climatic habitat of a particular species,which could result in shifts from its geographical range.Predicting the potential distribution t...Introduction:Climate change will either improve,reduce,or shift its appropriate climatic habitat of a particular species,which could result in shifts from its geographical range.Predicting the potential distribution through MaxEnt modeling has been developed as an appropriate tool for assessing habitat distribution and resource conservation to protect bamboo species.Methods:Our objective is to model the current and future distribution of Oxytenanthera abyssinica(A.Richard)based on three representative concentration pathways(RCP)(RCP2.6,RCP4.5,and RCP8.5)for 2050s and 2070s using a maximum entropy model(MaxEnt)in Northern Ethiopia.For modeling procedure,77 occurrence records and 11 variables were retained to simulate the current and future distributions of Oxytenanthera abyssinica in Northern Ethiopia.To evaluate the performance of the model,the area under the receiver operating characteristic(ROC)curve(AUC)was used.Results:All of the AUCs(area under curves)were greater than 0.900,thereby placing these models in the“excellent”category.The jackknife test also showed that precipitation of the coldest quarter(Bio19)and precipitation of the warmest quarter(Bio18)contributed 66.8%and 54.7%to the model.From the area of current distribution,1367.51 km2(2.52%),7226.28 km2(13.29%),and 5377.26 km2(9.89%)of the study area were recognized as high,good,and moderate potential habitats of Oxytenanthera abyssinica in Northern Ethiopia,and the high potential area was mainly concentrated in Tanqua Abergele(0.70%),Kola Temben(0.65%),Tselemti(0.60%),and Tsegede(0.31%).Kafta Humera was also the largest good potential area,which accounts for 2.75%.Compared to the current distribution,the total area of the high potential regions and good potential regions for Oxytenanthera abyssinica under the three RCPs(RCP2.6,RCP4.5,and RCP8.5)would increase in the 2050s and 2070s.However,the total area of the least potential regions under the three RCPs(RCP2.6,RCP4.5,and RCP8.5)in 2050s and 2070s would decrease.Conclusion:This study can provide vital information for the protection,management,and sustainable use of Oxytenanthera abyssinica,the resource to address the global climate challenges.展开更多
Incarvillea younghusbandii is a well-known Tibetan medicinal plant with considerable development and research value distributed widely throughout the Tibetan plateau.It is important to study spatial distribution patte...Incarvillea younghusbandii is a well-known Tibetan medicinal plant with considerable development and research value distributed widely throughout the Tibetan plateau.It is important to study spatial distribution patterns of the plant in order to develop effective protection measures.Based on field survey work and environmental data, the potential geographic distribution of Incarvillea younghusbandii was delineated using a Maximum Entropy (Maxent)model with 28environmental variables that screened for climate,topography,human activity and biological factors.Our results showed that the main geographic range of Incarvillea younghusbandii included the valley between the Yarlung Zangbo river and the Duoxiong Zangbo river,the valley in the middle section of the Himalaya Mountains,and the area between the north side of the east section of the Himalayas and the south bank of the middle reach of the Yarlung Zangbo river.Distribution may spread to parts of the eastern Himalayas.The Jackknife test indicated that soil types,ratio of precipitation to air temperature,extreme atmospheric pressure differences and annual precipitation were the most important predictive factors for the model,while other variables made relatively small contributions.展开更多
瓜类细菌性果斑病(bacterial fruit blotch)是瓜类作物上重要的种传细菌性病害,病原菌为西瓜噬酸菌Acidovorax citrulli。我国是全球西甜瓜的主要生产区。近年来,瓜类细菌性果斑病的频繁发生已严重影响我国西甜瓜产业的健康发展。为明...瓜类细菌性果斑病(bacterial fruit blotch)是瓜类作物上重要的种传细菌性病害,病原菌为西瓜噬酸菌Acidovorax citrulli。我国是全球西甜瓜的主要生产区。近年来,瓜类细菌性果斑病的频繁发生已严重影响我国西甜瓜产业的健康发展。为明确瓜类细菌性果斑病在我国的适生性,根据其在全球的最新分布数据,本研究利用MaxEnt模型结合ArcGIS软件预测了瓜类细菌性果斑病在我国的潜在地理分布。结果表明,MaxEnt模型的平均AUC(area under curve,AUC)值均大于0.9,预测结果的准确性较高。在历史气候条件下,瓜类细菌性果斑病适生区分布广泛,主要包括华中、华南和华东地区,以及部分华北、东北地区,占我国面积的47.36%。影响瓜类细菌性果斑病在我国潜在分布区域的主要气候因子包括最热月份最高温度、月平均昼夜温差、最干月份降水量和最干季平均温度。未来气候情景无论是低环境强迫还是高环境强迫,适生区面积均呈现增长的趋势,预示着随着气候的变化,瓜类细菌性果斑病在我国发生的风险不断增加,因此建议应加强检疫监测和防控,严防其扩散。展开更多
基金supported by the forestry public welfare scientific research project(Grant No.201504303)。
文摘Knowledge on the potential suitability of tree species to the site is very important for forest management planning.Natural forest distribution provides a good reference for afforestation and forest restoration.In this study,we developed species distribution model(SDM)for 16 major tree species with 2,825 permanent sample plots with natural origin from Chinese National Forest Inventory data collected in Jilin Province using the Maxent model.Three types of environmental factors including bioclimate,soil and topography with a total of 33 variables were tested as the input.The values of area under the curve(AUC,one of the receiver operating characteristics of the Maxent model)in the training and test datasets were between 0.784 and 0.968,indicating that the prediction results were quite reliable.The environmental factors affecting the distribution of species were ranked in terms of their importance to the species distribution.Generally,the climatic factors had the greatest contribution,which included mean diurnal range,annual mean temperature,temperature annual range,and iosthermality.But the main environmental factors varied with tree species.Distribution suitability maps under current(1950-2000)and future climate scenarios(CCSM4-RCP 2.6 and RCP 6.0 during 2050)were produced for 16 major tree species in Jilin Province using the model developed.The predicted current and future ranges of habitat suitability of the 16 tree species are likely to be positively and negatively affected by future climate.Seven tree species were found to benefit from future climate including B etula costata,Fraxinus mandshurica,Juglans mandshurica,Phellodendron amurense,Populus ussuriensis,Quercus mongolica and Ulmus pumila;five tree species will experience decline in their suitable habitat including B.platyphylla,Tilia mongolica,Picea asperata,Pinus sylvestris,Pinus koraiensis;and four(Salix koreensis,Abies fabri,Pinus densiflora and Larix olgensis)showed the inconsistency under RCP 2.6 and RCP 6.0 scenarios.The maps of the habitat suitability can be used as a basis for afforestation and forest restoration in northeastern China.The SDMs could be a potential tool for forest management planning.
文摘It is increasingly relevant to study the effects of climate change on species habitats. Using a maximum entropy model, 22 environmental factors with significant effects on sorghum habitat distribution in China were selected to predict the potential habitat distribution of sorghum in China. The potential distribution of sorghum under baseline climate conditions and future climate conditions (2050s and 2070s) under two climate change scenarios, RCP4.5 and RCP8.5, were simulated, and the receiver operating curve under the accuracy of the model was evaluated using the area under the receiver operating curve (AUC). The results showed that the maximum entropy model predicted the potential sorghum habitat distribution with high accuracy, with Bio2 (monthly mean diurnal temperature difference), Bio6 (minimum temperature in the coldest month), and Bio13 (rainfall in the wettest month) as the main climatic factors affecting sorghum distribution among the 22 environmental factors. Under the baseline climate conditions, potential sorghum habitats are mainly distributed in the southwest, central, and east China. Over time, the potential sorghum habitat expanded into northern and southern China, with significant additions and negligible decreases in potential sorghum habitat in the study area, and a significant increase in total area, with the RCP8.5 scenario adding much more area than the RCP4.5 scenario.
基金Under the auspices of National Key Research and Development Program of China(No.2016YFA0600401)the Key Research Program of Frontier Sciences from Chinese Academy of Sciences+1 种基金Fundamental Research Funds in Heilongjiang Provincial Universities(No.135209252,135309359)the Philosophy and Social Sciences Research Plan of Heilongjiang Province(No.16JLC01)
文摘Incorporating private and working lands into protected area networks could mitigate the isolation state of protected areas(PAs) and improve the efficiency of conservation.But how to select patches of land for conservation is still a troublesome issue.In this study, the MaxEnt model and irreplaceability index were applied to guide marsh conservation in the Nenjiang River Basin, Northeast China.According to the high accuracy of the MaxEnt model predictions(i.e., the average AUC value = 0.933), the Wuyuer River and Zhalong marshes in the downstream reaches of Wuyuer River are the optimal habitat for the Red-crowned crane and migratory waterfowls.There are 22 marsh patches selected by the patch irreplaceability index for conservation, of which 12 patches had been included in the current network of protected areas.The other 10 patches of marsh(amounting to 1096 km^2) far from human disturbances with high NDVI(up to 0.8) and close distance to water(less than 100 m), which are excluded from the existing network of PAs, should be implemented conservation easement programs to improve the protection efficiency of conservation.Specifically, the marshes at Taha, Tangchi, and Lamadian should be given priority for conservation and restoration to reintroduce migratory waterfowls, as this would lessen the current isolation state of the Zhalong National Nature Reserve.
基金National Natural Science Foundation of China(31100241 to C.K.B.)the Fundamental Research Funds for the Central Universities(GK201402025 to C.K.B.)+3 种基金Shaanxi Science and Technology Plan Project(2011K16-02-05 to C.K.B.)Xi’an Technology Plan Project(NC1116(1)to C.K.B.)Project of Co-Innovation Center for Qinba regions’sustainable development(CIC-QBRSD to C.K.B.)Innovation Funds of Graduate Programs of Shaanxi Normal University(2013CXS017 to B.C.).
文摘Aims Predicting suitable habitat distribution is an effective way to protect rare or endangered medicinal plants.Cornus officinalis is a perennial tree growing in forest edge and its air-dried pericarp is one of the traditional Chinese medicines(TCM)with significant medicinal values.In recent years,C.officinalis has undergone severe degeneration of its natural habitat owing to growing market demands and unprecedented damage to the forests.Moreover,the degeneration of suitable habitat has threatened the supply of medicinal materials,and even led to the extinction of some engendered medicinal plant species.In this case,there is a great risk to introduce and cultivate medicinal plants if planners determine the suitable cultivation regions based on personal subjective experience alone.Therefore,predicting suitable potential habitat distribution of medicinal plants(e.g.C.officinalis)and revealing the environmental factors determining such distribution patterns are important to habitat conservation and environmental restoration.Methods In this article,we report the results of a study on the habitat distribution of C.officinalis using maximum entropy(Maxent)modeling and fuzzy logics together with loganin content and environmental variables.The localities of 106 C.officinalis in China were collected by our group and other researchers and used as occurrence data.The loganin content of 234 C.officinalis germplasm resources were tested by high-performance liquid chromatography(HPLC)and used as content data.79 environmental variables were selected and processed with multicollinearity test by using Pearson Correlation Coefficient(r)to determine a set of independent variables.The chosen variables were then processed in the fuzzy linear model according to the cell values(maximum,minimum)of localities with estimated loganin content.The SDMtoolbox was used to spatially rarefy occurrence data and prepare bias files.Furthermore,combined Maxent modeling and fuzzy logics were used to predict the suitable habitat of C.officinalis.The modeling result was validated using null-model method.Important Findings As a result,six environmental factors including tmin3,prec3,bio4,alt,bio12 and bio3 were determined as key influential factors that mostly affected both the habitat suitability and active ingredient of C.officinalis.The highly suitable regions of C.officinalis mainly distribute in a‘core distribution zone’of the east-central China.The statistically significant AUC value indicated that combined Maxent modeling and fuzzy logics could be used to predict the suitable habitat distribution of medicinal plants.Furthermore,our results confirm that ecological factors played critical roles in assessing suitable geographical regions as well as active ingredient of plants,highlighting the need for effective habitat rehabilitation and resource conservation.
基金The authors acknowledge the financial support from Tigray Agricultural Research Institute(Mekelle Agricultural Research Center).
文摘Introduction:Climate change will either improve,reduce,or shift its appropriate climatic habitat of a particular species,which could result in shifts from its geographical range.Predicting the potential distribution through MaxEnt modeling has been developed as an appropriate tool for assessing habitat distribution and resource conservation to protect bamboo species.Methods:Our objective is to model the current and future distribution of Oxytenanthera abyssinica(A.Richard)based on three representative concentration pathways(RCP)(RCP2.6,RCP4.5,and RCP8.5)for 2050s and 2070s using a maximum entropy model(MaxEnt)in Northern Ethiopia.For modeling procedure,77 occurrence records and 11 variables were retained to simulate the current and future distributions of Oxytenanthera abyssinica in Northern Ethiopia.To evaluate the performance of the model,the area under the receiver operating characteristic(ROC)curve(AUC)was used.Results:All of the AUCs(area under curves)were greater than 0.900,thereby placing these models in the“excellent”category.The jackknife test also showed that precipitation of the coldest quarter(Bio19)and precipitation of the warmest quarter(Bio18)contributed 66.8%and 54.7%to the model.From the area of current distribution,1367.51 km2(2.52%),7226.28 km2(13.29%),and 5377.26 km2(9.89%)of the study area were recognized as high,good,and moderate potential habitats of Oxytenanthera abyssinica in Northern Ethiopia,and the high potential area was mainly concentrated in Tanqua Abergele(0.70%),Kola Temben(0.65%),Tselemti(0.60%),and Tsegede(0.31%).Kafta Humera was also the largest good potential area,which accounts for 2.75%.Compared to the current distribution,the total area of the high potential regions and good potential regions for Oxytenanthera abyssinica under the three RCPs(RCP2.6,RCP4.5,and RCP8.5)would increase in the 2050s and 2070s.However,the total area of the least potential regions under the three RCPs(RCP2.6,RCP4.5,and RCP8.5)in 2050s and 2070s would decrease.Conclusion:This study can provide vital information for the protection,management,and sustainable use of Oxytenanthera abyssinica,the resource to address the global climate challenges.
基金National Key Technologies Research and Development Program of China(2014BAL07B02)Tibet Autonomous Region Science-technology Support Projects(201DKJGX01-38)
文摘Incarvillea younghusbandii is a well-known Tibetan medicinal plant with considerable development and research value distributed widely throughout the Tibetan plateau.It is important to study spatial distribution patterns of the plant in order to develop effective protection measures.Based on field survey work and environmental data, the potential geographic distribution of Incarvillea younghusbandii was delineated using a Maximum Entropy (Maxent)model with 28environmental variables that screened for climate,topography,human activity and biological factors.Our results showed that the main geographic range of Incarvillea younghusbandii included the valley between the Yarlung Zangbo river and the Duoxiong Zangbo river,the valley in the middle section of the Himalaya Mountains,and the area between the north side of the east section of the Himalayas and the south bank of the middle reach of the Yarlung Zangbo river.Distribution may spread to parts of the eastern Himalayas.The Jackknife test indicated that soil types,ratio of precipitation to air temperature,extreme atmospheric pressure differences and annual precipitation were the most important predictive factors for the model,while other variables made relatively small contributions.
文摘构建准确的滑坡预测模型和确定环境因子的贡献程度,对滑坡易发性评价具有重要意义。在以往研究中,最大熵物种分布(maximum entropy model,MaxEnt)模型因其对样本量要求低、预测精度高和可避免模型过度拟合等优点,被广泛运用在生态学领域。以沅陵县为研究区,基于342处滑坡灾害点数据和9个环境变量,分别采用确定性系数(certainty factor,CF)模型、逻辑回归(Logistic)模型和MaxEnt模型对沅陵县进行滑坡易发性分区预测。同时采用刀切法(Jackknife)检验环境因子对预测结果的贡献程度,确定滑坡地质灾害的主要影响因素。结果表明:确定性系数模型、逻辑回归模型和MaxEnt模型的受试者特征曲线(receiver operating characteristic,ROC)下面积(area under the curve,AUC)值分别为0.827、0.803、0.911,3种模型的预测精度均较高,且MaxEnt模型精度最高,表现较好;河流是影响研究区滑坡灾害发生贡献程度最高的环境因子;滑坡灾害主要发育在以河流为中心向外延伸100 m范围内,集中分布在沅江、深溪和兰溪附近。研究能为沅陵县地质灾害易发性评价提供一种新的方法。
文摘瓜类细菌性果斑病(bacterial fruit blotch)是瓜类作物上重要的种传细菌性病害,病原菌为西瓜噬酸菌Acidovorax citrulli。我国是全球西甜瓜的主要生产区。近年来,瓜类细菌性果斑病的频繁发生已严重影响我国西甜瓜产业的健康发展。为明确瓜类细菌性果斑病在我国的适生性,根据其在全球的最新分布数据,本研究利用MaxEnt模型结合ArcGIS软件预测了瓜类细菌性果斑病在我国的潜在地理分布。结果表明,MaxEnt模型的平均AUC(area under curve,AUC)值均大于0.9,预测结果的准确性较高。在历史气候条件下,瓜类细菌性果斑病适生区分布广泛,主要包括华中、华南和华东地区,以及部分华北、东北地区,占我国面积的47.36%。影响瓜类细菌性果斑病在我国潜在分布区域的主要气候因子包括最热月份最高温度、月平均昼夜温差、最干月份降水量和最干季平均温度。未来气候情景无论是低环境强迫还是高环境强迫,适生区面积均呈现增长的趋势,预示着随着气候的变化,瓜类细菌性果斑病在我国发生的风险不断增加,因此建议应加强检疫监测和防控,严防其扩散。
