基于气象因子的森林病虫鼠害发生率预测模型研究

林业资源管理 ›› 2012›› Issue (4): 96-101.

基于气象因子的森林病虫鼠害发生率预测模型研究

张乃静, 鞠洪波, 纪平

中国林业科学研究院资源信息研究所,北京 100091

收稿日期:2012-05-03 修回日期:2012-07-15 出版日期:2012-08-28 发布日期:2020-11-27
通讯作者: 纪平(1964-),女,天津人,副研究员,主要从事数据库技术与应用研究工作。
作者简介:张乃静(1982-),女,天津人,在读博士,主要从事数据库技术与应用研究工作。Email:naijing.zhang@gmail.com
基金资助:
国家科技基础条件平台建设项目(2005DKA32200);Tropical Forest Fire Monitoring and Management System Based on Satellite Remote Sensing Data in China [ITTO PD 228/03 Rev.3(F)]

Prediction of Incidence Rate of Forest Diseases, Mice and Pests Using Meteorological Factor

ZHANG Naijing, JU Hongbo, JI Ping

Research Institute of Forestry Information Techniques,Chinese Academy of Forestry,Beijing 100091,China

Received:2012-05-03 Revised:2012-07-15 Online:2012-08-28 Published:2020-11-27

摘要/Abstract

摘要： 基于气象因子,使用一元线性回归、多元线性回归、一元非线性回归以及BP神经网络4种不同的回归模型对森林病虫鼠害发生率进行预测,结果表明:对于线性模型,多元线性回归模型的判定系数和均方根误差均优于一元线性回归模型;对于非线性模型,BP神经网络模型的判定系数和均方根误差均优于一元非线性回归模型;按优劣排序为BP神经网络模型、一元非线性回归模型、多元线性回归模型和一元线性回归模型。气象因子与森林病虫鼠害发生率的关系并非单纯的线性关系,非线性的预测模型可以更好地解释森林病虫鼠害的发生程度。

关键词: 气象因子, 森林病虫鼠害, 预测模型

Abstract: Based on some meteorological factors, prediction was made on the incidence rate of forest diseases,mice and pests by simple linear regression(SLR),multiple linear regressions(MLR),simple non-linear regression(SNLR)and BP neural network(BP).The results show that the determination coefficient(R²)and root mean square error(RMSE)of MLR are better than that of SLR,the R² and RMSE of BP are better than that of SNLR.According to the quality of models,BP model is the best of all,and SNLR is better than MLR and SLR.The conclusion is that the relations between meteorological factors and incidence rate of forest diseases,mice and pests are not linearity,non-linear model could effectively explain the incidence rate of forest diseases,mice and pests.

Key words: meteorological factor, forest diseases, mice and pests, prediction model

中图分类号:

S443
S764.5

张乃静, 鞠洪波, 纪平. 基于气象因子的森林病虫鼠害发生率预测模型研究[J]. 林业资源管理, 2012,(4): 96-101.

ZHANG Naijing, JU Hongbo, JI Ping. Prediction of Incidence Rate of Forest Diseases, Mice and Pests Using Meteorological Factor[J]. FOREST RESOURCES WANAGEMENT, 2012,(4): 96-101.

参考文献

[1] Rouault G,Candau J N,Lieutier F,et al.Effects of drought and heat on forest insect populations in relation to the 2003 drought in Western Europe[J].Annals of Forest Science,2006,63(6):613-624.
[2] Volney W J A,Fleming R A.Climate change and impacts of boreal forest insects[J].Agriculture,Ecosystems & Environment,2000,82(1-3):283-294.
[3] 唐红艳,牛宝亮.气象因子对落叶松毛虫繁殖的影响及其产卵量预测[J].东北林业大学学报,2010(1):84-87.
[4] Masters G J,Brown V K,Clarke I P,et al.Direct and indirect effects of climate change on insect herbivores:Auchenorrhyncha (Homoptera)[J].Ecological Entomology,1998,23(1):45-52.
[5] Bale J S,Masters G J,Hodkinson I D,et al.Herbivory in global climate change research:direct effects of rising temperature on insect herbivores[J].Global Change Biology,2002,8(1):1-16.
[6] 赵铁良,耿海东,张旭东,等.气温变化对我国森林病虫害的影响[J].中国森林病虫,2003,22(3):29-32.
[7] Liu K Y.Causes of Outbreak of the Larch Caterpillar (Dendrolimus Superans Butler)in Daxingan Mountain and Its Control Strategy[J].Journal of Northeast Forestry University,1994(1):34-40.
[8] 薛贤清.在马尾松毛虫测报中应用逐步回归电算方法的研究[J].林业科学,1984(1):42-49.
[9] 许彦平,姚晓红,乔艳君.甘肃小陇山林区甘肃鼢鼠危害面积的气象预测预报技术研究[J].地球科学进展,2011(8):881-886.
[10] 王纯枝,郭安红,张玉书,等.东北地区杨树烂皮病气象预报模型研究[J].中国农学通报,2012(10):47-52.
[11] 习妍,牛树奎.气候要素对松材线虫病疫情的影响研究[J].林业资源管理,2008(4):70-76.
[12] 张福丽,景天忠,王志英,等.气象因素与杨干象虫口密度的多元线性回归和判别分析[J].安徽农业科学,2011(15):9000-9001.
[13] 陈绘画,朱寿燕,崔相富.基于人工神经网络的马尾松毛虫发生量预测模型的研究[J].林业科学研究,2003(2):159-165.
[14] 林业科学数据中心.[2012-05-01] .http://www.forestdata.cn.
[15] 中国气象科学数据共享服务网.[2012-05-01] .http://cdc.cma.gov.cn.