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
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
We used GIS and maximum entropy to predict the potential distribution of six snake species belong to three families in Kroumiria（Northwestern Tunisia）： Natricidae（Natrix maura and Natrix astreptophora）, Colubrida...We used GIS and maximum entropy to predict the potential distribution of six snake species belong to three families in Kroumiria（Northwestern Tunisia）： Natricidae（Natrix maura and Natrix astreptophora）, Colubridae（Hemorrhois hippocrepis, Coronella girondica and Macroprotodon mauritanicus）, and Lamprophiidae（Malpolon insignitus）. The suitable habitat for each species was modelled using the maximum entropy algorithm, combining presence field data（collected during 16 years：2000–2015） with a set of seven environmental variables（mean annual precipitation, elevation, slope gradient,aspect, distance to watercourses, land surface temperature and normalized Differential Vegetation Index. The relative importance of these environmental variables was evaluated by jackknife tests and the predictive power of our models was assessed using the area under the receiver operating characteristic. The main explicative variables of the species distribution were distance from streams and elevation, with contributions ranging from 60 to 77 and from 10 to 25%,respectively. Our study provided the first habitat suitability models for snakes in Kroumiria and this information can be used by conservation biologists and land managers concerned with preserving snakes in Kroumiria.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。
基金Funding support for this work was provided by the Silvo-Pastoral Institute of Tabarka
文摘We used GIS and maximum entropy to predict the potential distribution of six snake species belong to three families in Kroumiria（Northwestern Tunisia）： Natricidae（Natrix maura and Natrix astreptophora）, Colubridae（Hemorrhois hippocrepis, Coronella girondica and Macroprotodon mauritanicus）, and Lamprophiidae（Malpolon insignitus）. The suitable habitat for each species was modelled using the maximum entropy algorithm, combining presence field data（collected during 16 years：2000–2015） with a set of seven environmental variables（mean annual precipitation, elevation, slope gradient,aspect, distance to watercourses, land surface temperature and normalized Differential Vegetation Index. The relative importance of these environmental variables was evaluated by jackknife tests and the predictive power of our models was assessed using the area under the receiver operating characteristic. The main explicative variables of the species distribution were distance from streams and elevation, with contributions ranging from 60 to 77 and from 10 to 25%,respectively. Our study provided the first habitat suitability models for snakes in Kroumiria and this information can be used by conservation biologists and land managers concerned with preserving snakes in Kroumiria.
