生态位模型通过拟合物种分布与环境变量之间的关系提供物种空间分布预测,在生物多样性研究中有广泛应用。激光雷达(LiDAR)是一种新兴的主动遥感技术,已被大量应用于森林三维结构信息的提取,但其在物种分布模拟的应用研究比较缺乏。本研...生态位模型通过拟合物种分布与环境变量之间的关系提供物种空间分布预测,在生物多样性研究中有广泛应用。激光雷达(LiDAR)是一种新兴的主动遥感技术,已被大量应用于森林三维结构信息的提取,但其在物种分布模拟的应用研究比较缺乏。本研究以美国加州内华达山脉南部地区的食鱼貂(Martes pennanti)的分布模拟为例,探索Li DAR技术在物种分布模拟中的有效性。生态位模型采用5种传统多类分类器,包括神经网络、广义线性模型、广义可加模型、最大熵模型和多元自适应回归样条模型,并使用正样本–背景学习(presence and background learning,PBL)算法进行模型校正;同时对这5种模型使用加权平均进行模型集成,作为第6个模型。此外,一类最大熵模型也被用于模拟该物种的空间分布。模型的连续输出和二值输出分别使用AUC(area under the receiver operating characteristic curve)以及基于正样本–背景数据的评价指标F_(pb)进行评价。结果表明,仅考虑气候因子(温度和降水)时,7个模型的AUC和F_(pb)平均值分别为0.779和1.077;当考虑Li DAR变量(冠层容重、枝下高、叶面积指数、高程、坡度等)后,AUC和F_(pb)分别为0.800和1.106。该研究表明,Li DAR数据能够提高食鱼貂空间分布的预测精度,在物种分布模拟方面存在一定的应用价值。展开更多
Bilharzia is vector-borne disease carried by a parasite that is hosted by fresh water snails. The distribution of the disease is concurrent with the existence of the freshwater snails and </span></span><...Bilharzia is vector-borne disease carried by a parasite that is hosted by fresh water snails. The distribution of the disease is concurrent with the existence of the freshwater snails and </span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">is </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">dependent on certain suitable environmental conditions. It is difficult to identify the specific habitats of the snails as they are often inaccessible on the ground, the snails also migrate by means of flowing water, making it difficult to keep a track of the freshwater snails’ habitat. This paper aimed at using GIS, Remote Sensing and Species Distribution Modelling techniques to model the suitable habitats for the freshwater snails and to prove that the snails migrate when there are sudden changes in water levels whilst showing the population at risk of bilharzia. The SDM used is the Maximum Entropy (MAXENT) for its ability to make right predictions even with small presence sites. The AUC value of the model was 0.951. The research results showed that the environmental variables;brightness Index, elevation, temperatures were negatively correlated with the snails’ presence while the wetness index, MSAVI, greenness index and soil pH were positively correlated. The snails are observed to favor clay soils of the montmorillonite type and the crop-lands land cover. Areas consistently submerged by water especially after flooding are shown to be the most suitable areas where snails migrate by means of river or canal water. The research proves that Mwea is not the source habitat of the freshwater snails. The neighboring sub-counties within Kirinyaga County should be investigated using such models as a likely source-habitat of the freshwater snails. Destroying the source habitats will lead to complete eradication of the freshwater snails within Mwea.展开更多
To provide scientific support for planning maize production and designing countermeasures against the effects of climate change on the national maize crop, we analyzed the climatic suitability for cultivating maize ac...To provide scientific support for planning maize production and designing countermeasures against the effects of climate change on the national maize crop, we analyzed the climatic suitability for cultivating maize across China. These analyses were based on annual climate indices at the Chinese national level; these indices influence the geographical distribution of maize cultivation. The annual climate indices, together with geographical information on the current cultivation sites of maize, the maximum entropy (MaxEnt) model, and the ArcGIS spatial analysis technique were used to analyze and predict maize distribution. The results show that the MaxEnt model can be used to study the climatic suitability for maize cultivation. The eight key climatic factors affecting maize cultivation areas were the frost-free period, annual average temperature, ≥0°C accumulated temperature, ≥10°C accumulated temperature continuous days, ≥10°C accumulated temperature, annual precipitation, warmest month average temperature, and humidity index. We classified climatic zones in terms of their suitability for maize cultivation, based on the existence probability determined using the MaxEnt model. Furthermore, climatic thresholds for a potential maize cultivation zone were determined based on the relationship between the dominant climatic factors and the potential maize cultivation area. The results indicated that the importance and thresholds of main climate controls differ for different maize species and maturities, and their specific climatic suitability should be studied further to identify the best cultivation zones. The MaxEnt model is a useful tool to study climatic suitability for maize cultivation.展开更多
东北地区是我国沼泽湿地分布最广泛的地区。为研究沼泽湿地对气候变化的响应,选取了对沼泽湿地分布可能存在影响的26个环境因子,利用最大熵(Maximum Entropy,MaxEnt)模型模拟了沼泽湿地基准气候条件下的潜在分布,并预测了气候变化情景下...东北地区是我国沼泽湿地分布最广泛的地区。为研究沼泽湿地对气候变化的响应,选取了对沼泽湿地分布可能存在影响的26个环境因子,利用最大熵(Maximum Entropy,MaxEnt)模型模拟了沼泽湿地基准气候条件下的潜在分布,并预测了气候变化情景下2011—2040年、2041—2070年和2071—2100年3个研究阶段东北沼泽湿地潜在分布。研究结果表明:最大熵模型预测精度较高(平均AUC(Aera Under Curve)为(0.826±0.005))。基准气候条件下东北沼泽潜在分布区主要为大小兴安岭和三江平原地区。随着时间的推进,东北地区沼泽湿地原有潜在分布面积明显减少,而新增潜在分布面积较少,总面积呈现急剧减少趋势。至2071—2100年,原有沼泽湿地潜在分布面积将减少99.80%,新增潜在分布面积仅2.48%,总潜在分布面积减少97.32%。空间分布上,东北沼泽湿地潜在分布呈现由东向西迁移,南北向中心收缩的趋势。研究结果可为东北地区沼泽湿地保护政策的制定提供参考。展开更多
文摘生态位模型通过拟合物种分布与环境变量之间的关系提供物种空间分布预测,在生物多样性研究中有广泛应用。激光雷达(LiDAR)是一种新兴的主动遥感技术,已被大量应用于森林三维结构信息的提取,但其在物种分布模拟的应用研究比较缺乏。本研究以美国加州内华达山脉南部地区的食鱼貂(Martes pennanti)的分布模拟为例,探索Li DAR技术在物种分布模拟中的有效性。生态位模型采用5种传统多类分类器,包括神经网络、广义线性模型、广义可加模型、最大熵模型和多元自适应回归样条模型,并使用正样本–背景学习(presence and background learning,PBL)算法进行模型校正;同时对这5种模型使用加权平均进行模型集成,作为第6个模型。此外,一类最大熵模型也被用于模拟该物种的空间分布。模型的连续输出和二值输出分别使用AUC(area under the receiver operating characteristic curve)以及基于正样本–背景数据的评价指标F_(pb)进行评价。结果表明,仅考虑气候因子(温度和降水)时,7个模型的AUC和F_(pb)平均值分别为0.779和1.077;当考虑Li DAR变量(冠层容重、枝下高、叶面积指数、高程、坡度等)后,AUC和F_(pb)分别为0.800和1.106。该研究表明,Li DAR数据能够提高食鱼貂空间分布的预测精度,在物种分布模拟方面存在一定的应用价值。
文摘Bilharzia is vector-borne disease carried by a parasite that is hosted by fresh water snails. The distribution of the disease is concurrent with the existence of the freshwater snails and </span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">is </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">dependent on certain suitable environmental conditions. It is difficult to identify the specific habitats of the snails as they are often inaccessible on the ground, the snails also migrate by means of flowing water, making it difficult to keep a track of the freshwater snails’ habitat. This paper aimed at using GIS, Remote Sensing and Species Distribution Modelling techniques to model the suitable habitats for the freshwater snails and to prove that the snails migrate when there are sudden changes in water levels whilst showing the population at risk of bilharzia. The SDM used is the Maximum Entropy (MAXENT) for its ability to make right predictions even with small presence sites. The AUC value of the model was 0.951. The research results showed that the environmental variables;brightness Index, elevation, temperatures were negatively correlated with the snails’ presence while the wetness index, MSAVI, greenness index and soil pH were positively correlated. The snails are observed to favor clay soils of the montmorillonite type and the crop-lands land cover. Areas consistently submerged by water especially after flooding are shown to be the most suitable areas where snails migrate by means of river or canal water. The research proves that Mwea is not the source habitat of the freshwater snails. The neighboring sub-counties within Kirinyaga County should be investigated using such models as a likely source-habitat of the freshwater snails. Destroying the source habitats will lead to complete eradication of the freshwater snails within Mwea.
基金supported by the National Basic Research Program of China(2010CB951303)the Special Fund for Agro-scientific Research in the Public Interest(200903003)the Basic Operation Cost of China Meteorological Administration(CMA)
文摘To provide scientific support for planning maize production and designing countermeasures against the effects of climate change on the national maize crop, we analyzed the climatic suitability for cultivating maize across China. These analyses were based on annual climate indices at the Chinese national level; these indices influence the geographical distribution of maize cultivation. The annual climate indices, together with geographical information on the current cultivation sites of maize, the maximum entropy (MaxEnt) model, and the ArcGIS spatial analysis technique were used to analyze and predict maize distribution. The results show that the MaxEnt model can be used to study the climatic suitability for maize cultivation. The eight key climatic factors affecting maize cultivation areas were the frost-free period, annual average temperature, ≥0°C accumulated temperature, ≥10°C accumulated temperature continuous days, ≥10°C accumulated temperature, annual precipitation, warmest month average temperature, and humidity index. We classified climatic zones in terms of their suitability for maize cultivation, based on the existence probability determined using the MaxEnt model. Furthermore, climatic thresholds for a potential maize cultivation zone were determined based on the relationship between the dominant climatic factors and the potential maize cultivation area. The results indicated that the importance and thresholds of main climate controls differ for different maize species and maturities, and their specific climatic suitability should be studied further to identify the best cultivation zones. The MaxEnt model is a useful tool to study climatic suitability for maize cultivation.
文摘东北地区是我国沼泽湿地分布最广泛的地区。为研究沼泽湿地对气候变化的响应,选取了对沼泽湿地分布可能存在影响的26个环境因子,利用最大熵(Maximum Entropy,MaxEnt)模型模拟了沼泽湿地基准气候条件下的潜在分布,并预测了气候变化情景下2011—2040年、2041—2070年和2071—2100年3个研究阶段东北沼泽湿地潜在分布。研究结果表明:最大熵模型预测精度较高(平均AUC(Aera Under Curve)为(0.826±0.005))。基准气候条件下东北沼泽潜在分布区主要为大小兴安岭和三江平原地区。随着时间的推进,东北地区沼泽湿地原有潜在分布面积明显减少,而新增潜在分布面积较少,总面积呈现急剧减少趋势。至2071—2100年,原有沼泽湿地潜在分布面积将减少99.80%,新增潜在分布面积仅2.48%,总潜在分布面积减少97.32%。空间分布上,东北沼泽湿地潜在分布呈现由东向西迁移,南北向中心收缩的趋势。研究结果可为东北地区沼泽湿地保护政策的制定提供参考。
