湖北省杉木栽培区划及气候特征研究
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摘要
通过收集湖北省杉木人工林地理信息和温、湿度相关气候因子数据,利用ArcGIS软件和最大信息熵模型,对湖北省杉木栽培区域进行划分,并找出影响杉木栽培的主要气候因子以及适宜栽培的区域,为杉木人工林的科学布局提供依据。结果表明:1)湖北省杉木气候区划可以分为3个等级:最适宜区、较适宜区和不适宜区,其中最适宜区面积为1.86×10~6 hm~2,较适宜区面积为3.23×10~6 hm~2,适宜区域主要为鄂西山区和鄂东南低山丘陵区;2)模型ROC曲线检测AUC值为0.916,利用二类清查人工林信息验证准确率达到96.22%,说明模型预测效果较好;3)刀切法分析对预测贡献率较大的主要为反应水分条件及水热同步的指标,排名前4位的因子分别为最湿季平均温度、最湿季降水量、年降水量和最湿月降水量。
In order to classify cultivation regions and provide references for layout of Cunninghamia lanceolata in Hubei province,the software ArcGIS and MaxEnt were used to analyze the main climate factors affecting the ?r cultivation and the suitable cultivation region with environmental data of temperature and humidity and the known distribution of plantations. The results show that 1) The climate division of Chinese ?r in Hubei province can be divided into three grades: the most suitable area, the suitable area and the unsuitable area. The most suitable area was 1.86×10~6 hm~2, and the suitable area was 3.23×10~6 hm~2. The suitable areas were mainly located in the mountainous areas in Western Hubei and hilly areas in southeastern Hubei. 2) The AUC value of model ROC curve detection was 0.916,and the accuracy of veri?cation by using the information of second-class inventory plantation reached 96.22%, which shows that the model has a good prediction effect. 3) The results of knife-cut analysis show that the main factors contributing to the prediction were the reaction water condition and the synchronization index of water and heat, the top four factors were the average temperature in the wettest season, the rainfall in the wettest season, the annual rainfall and the monthly rainfall in the wettest season.
In order to classify cultivation regions and provide references for layout of Cunninghamia lanceolata in Hubei province,the software ArcGIS and MaxEnt were used to analyze the main climate factors affecting the ?r cultivation and the suitable cultivation region with environmental data of temperature and humidity and the known distribution of plantations. The results show that 1) The climate division of Chinese ?r in Hubei province can be divided into three grades: the most suitable area, the suitable area and the unsuitable area. The most suitable area was 1.86×10~6 hm~2, and the suitable area was 3.23×10~6 hm~2. The suitable areas were mainly located in the mountainous areas in Western Hubei and hilly areas in southeastern Hubei. 2) The AUC value of model ROC curve detection was 0.916,and the accuracy of veri?cation by using the information of second-class inventory plantation reached 96.22%, which shows that the model has a good prediction effect. 3) The results of knife-cut analysis show that the main factors contributing to the prediction were the reaction water condition and the synchronization index of water and heat, the top four factors were the average temperature in the wettest season, the rainfall in the wettest season, the annual rainfall and the monthly rainfall in the wettest season.
引文
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[3]盛炜彤,王岚,张洪英.杉木生长区气候区划的初步研究[J].林业科学,1981,17(1):50-56.
[4]高智慧.浙江省杉木栽培区气候区划的初步研究[J].浙江林学院学报,1986,3(2):9-15.
[5]陶国祥.云南省杉木气候区划[J].云南林业调查规划,1993(1):13-17.
[6]刘建锋,康峰峰.杉木潜在适生区及其对气候变化的响应[J].西南林学院学报,2010,30(5):22-24.
[7]张东方,张琴,郭杰,等.基于MaxEnt模型的当归全球生态适宜区和生态特征研究[J].生态学报,2017,37(15):5111-5120.
[8]胡忠俊.张镱锂,于海彬.基于MaxEnt模型和GIS的青藏高原紫花针茅分布格局模拟[J].应用生态学报,2015,26(2):505-511.
[9]PHILLIPS S J,ANDERSON R P,SCHAPIRE R E.Maximum entropy modeling of species geographic distributions[J].Ecological Modelling,2006,190(3/4):231?259.
[10]王运生,谢丙炎,万方浩,等.ROC曲线分析在评价入侵物种分布模型中的应用.生物多样性,2007,15(1):365-372.
[11]王雷宏,杨俊仙,徐小牛.基于MaxEnt分析金钱松适生的生物气候特征[J].林业科学,2015,51(1):127-131.
[12]雷军成,徐海根.基于MaxEnt的加拿大一枝黄花在中国的潜在分布区预测[J].生态与农村环境学报,2010,26(2):137-141.
[13]RAXWORTHY C J,MARTINEZ-MEYER E,HORNINGN,et al.Predicting distributions of known and unknown reptile species in Madagascar[J].Nature,2003(426):837-841.
[14]王伟,田荣荣,那立妍,等.基于Max Ent生态软件划分澳洲坚果的潜在地理适生区[J].林业科学研究,2017,30(3):444-449.
[15]崔相艳,王文娟,杨小强,等.基于生态位模型预测野生油茶的潜在分布[J].生物多样性,2016,24(10):1117-1128.
[16]吴中伦.杉木[M].北京:中国林业出版社,1984.
[17]CHEN P F,WILEY E O,MCNYSET K M.Ecological niche modeling as a predictive tool:silver and bighead carps in North America[J].Biological Invasions,2006,9(1):43-51.
[18]陈新美,雷渊才,张雄清,等.样本量对MaxEnt模型预测物种分布精度和稳定性的影响.林业科学,2012,48(1):53-59.