基于优化的MaxEnt模型评价红松适宜分布区
|
摘要
了解红松的适宜区分布,对于红松种质资源保护和阔叶红松林的植被恢复具有重要意义。本研究利用R软件的ENMeval数据包,通过调整MaxEnt模型的参数(特征组合、调控倍率)来优化模型。基于优化后的MaxEnt模型,利用168个红松分布点数据和22个环境因子图层,模拟了红松的分布区域,并分析决定红松适宜区分布的主导环境因子及其阈值。结果表明,当特征组合为线性、二次型、片段化和乘积型,调控倍率为3时,模型复杂度和过拟合程度较低,模型模拟准确性提高,被确定为最终的设置参数。红松高度适宜区主要分布于我国东北地区东部山地,占研究区总面积的19.24%;低度适宜区和不适宜区分别占研究区的28.54%和52.22%。影响红松适宜区分布的主导环境因子主要是年降雨量、降雨量季节性变异系数、海拔和年平均温度,其适宜值范围分别是630～1090 mm、86%～97%、210～1140 m和0.3～4.3℃。
Understanding the suitable habitat distribution of Korean pine( Pinus koraiensis) is significant for genetic resource conservation of Korean pine and vegetation restoration of broadleaved Korea pine mixed forest. In this study,we optimized the parameters( such as feature combination and regularization multiplier) of MaxEnt model. Using 168 geographical distribution records of Korean pine and 22 environmental factors,we simulated the habitat suitability of Korean pine and identified the major environmental factors controlling its distribution. The results showed that the complexity and degree of overfitting of the model were relatively low. The model was more accurate when the feature combination was linear,quadratic,hinge and product equation,and regularization multiplier was 3. Korean pine was mainly distributed in the eastern mountain area of Northeast China. The highly suitable area,low suitable area,and unsuitable area accounted for19.24%,28.54% and 52.22% of the total area,respectively. Annual precipitation,precipitation seasonality,elevation,and annual mean temperature played important roles in regulating the distribution of Korean pine,with the suitable threshold of each factor being 630-1090 mm,86%-97%,210-1140 m and 0.3-4.3 ℃,respectively.
Understanding the suitable habitat distribution of Korean pine( Pinus koraiensis) is significant for genetic resource conservation of Korean pine and vegetation restoration of broadleaved Korea pine mixed forest. In this study,we optimized the parameters( such as feature combination and regularization multiplier) of MaxEnt model. Using 168 geographical distribution records of Korean pine and 22 environmental factors,we simulated the habitat suitability of Korean pine and identified the major environmental factors controlling its distribution. The results showed that the complexity and degree of overfitting of the model were relatively low. The model was more accurate when the feature combination was linear,quadratic,hinge and product equation,and regularization multiplier was 3. Korean pine was mainly distributed in the eastern mountain area of Northeast China. The highly suitable area,low suitable area,and unsuitable area accounted for19.24%,28.54% and 52.22% of the total area,respectively. Annual precipitation,precipitation seasonality,elevation,and annual mean temperature played important roles in regulating the distribution of Korean pine,with the suitable threshold of each factor being 630-1090 mm,86%-97%,210-1140 m and 0.3-4.3 ℃,respectively.
引文
傅俊卿.2009.东北天然红松林资源现状与保护经营对策.东北林业大学学报,37(2):75-78.
高慧淋,董利虎,李凤日.2018.黑龙江省红松和长白落叶松人工林树冠外部轮廓模拟.南京林业大学学报:自然科学版,42(3):10-18
郭杰,刘小平,张琴,等.2017.基于Maxent模型的党参全球潜在分布区预测.应用生态学报,28(3):992-1000.
郭泉水,阎洪,徐德应,等.1998.气候变化对我国红松林地理分布影响的研究.生态学报,18(5):484-488.
国家林业局和农业部.1999.国家重点保护野生植物名录(第一批)[EB/OL].[2018-8-12].http://www.gov.cn/gongbao/content/2000/content_60072.htm.
贾翔,马芳芳,周旺明,等.2017.气候变化对阔叶红松林潜在地理分布区的影响.生态学报,37(2):464-473.
贾炜玮,孙守强,李凤日,等.2015.基于混合模型的红松人工林枝条动态研究.植物研究,35(3):425-430.
蒋育昊.2017.基于随机森林模型的红松潜在分布预测及适宜性评价(硕士学位论文).北京:中国林业科学研究院.
刘芳,李晟,李迪强.2013.利用分布有/无数据预测物种空间分布的研究方法综述.生态学报,33(22):7047-7057.
马建路,庄丽文,陈动,等.1992.红松的地理分布.东北林业大学学报,20(5):40-48.
毛德华,王宗明,罗玲,等.2016.1990-2013年中国东北地区湿地生态系统格局演变遥感监测分析.自然资源学报,31(8):1253-1263.
欧阳林男,陈少雄,张维耀,等.2019.柠檬桉在中国的适生地理分布及其影响因子.生态学杂志,38(2):361-367.
孙晓红.2012.中国红松地理分布与气候的关系研究(硕士学位论文).北京:中国科学院植物研究所.
王璐,许晓岗,李垚.2018.末次盛冰期以来陀螺果潜在地理分布格局变迁预测.生态学杂志,37(1):278-286.
卫林,王辉民,王其冬,等.1995.气候变化对我国红松林的影响.地理研究,14(1):17-26.
吴正方.2003.东北阔叶红松林分布区生态气候适宜性及全球气候变化影响评价.应用生态学报,14(5):771-775.
吴志军,苏东凯,牛丽君,等.2015.阔叶红松林森林资源可持续利用方案.生态学报,35(1):24-30.
杨志香,周广胜,殷晓洁,等.2014.中国兴安落叶松天然林地理分布及其气候适宜性.生态学杂志,33(6):1429-1436.
于大炮,周旺明,包也,等.2015.天保工程实施以来东北阔叶红松林的可持续经营.生态学报,35(1):10-17.
朱耿平,乔慧捷.2016.Maxent模型复杂度对物种潜在分布区预测的影响.生物多样性,24(10):1189-1196.
IPCC(Intergovernmental Panel on Climate Change).2007.Climate Change 2007:The Physical Science Basis.Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.Cambridge:Cambridge University Press.
Muscarella R,Galante PJ,Soley-Guardia M,et al.2014.ENMeval:An R package for conducting spatially independent evaluations and estimating optimal model complexity for MAXENT ecological niche models.Methods in Ecology and Evolution,5:1198-1205.
Phillips SJ,Anderson RP,Schapire RE.2006.Maximum entropy modeling of species geographic distributions.Ecological Modelling,190:231-259.
Phillips SJ,Dudík MM.2008.Modeling of species distributions with Maxent:New extensions and a comprehensive evaluation.Ecography,31:161-175.
Sillero N.2011.What does ecological modeling model?A proposed classification of ecological niche models based on their underlying methods.Ecological Modelling,222:1343-1346.
Xu DY,Yan H.2001.A study of the impacts of climate change on the geographic distribution of Pinus koraiensis in China.Environment International,27:201-205.
Yang XQ,Kushwaha SPS,Saran S,et al.2013.Maxent modeling for predicting the potential distribution of medicinal plant,Justicia adhatoda L.in Lesser Himalayan foothills.Ecological Engineering,51:83-87.
Yu DP,Zhou L,Zhou WM,et al.2011.Forest management in Northeast China:History,problems,and challenges.Environmental Management,48:1122-1135.
高慧淋,董利虎,李凤日.2018.黑龙江省红松和长白落叶松人工林树冠外部轮廓模拟.南京林业大学学报:自然科学版,42(3):10-18
郭杰,刘小平,张琴,等.2017.基于Maxent模型的党参全球潜在分布区预测.应用生态学报,28(3):992-1000.
郭泉水,阎洪,徐德应,等.1998.气候变化对我国红松林地理分布影响的研究.生态学报,18(5):484-488.
国家林业局和农业部.1999.国家重点保护野生植物名录(第一批)[EB/OL].[2018-8-12].http://www.gov.cn/gongbao/content/2000/content_60072.htm.
贾翔,马芳芳,周旺明,等.2017.气候变化对阔叶红松林潜在地理分布区的影响.生态学报,37(2):464-473.
贾炜玮,孙守强,李凤日,等.2015.基于混合模型的红松人工林枝条动态研究.植物研究,35(3):425-430.
蒋育昊.2017.基于随机森林模型的红松潜在分布预测及适宜性评价(硕士学位论文).北京:中国林业科学研究院.
刘芳,李晟,李迪强.2013.利用分布有/无数据预测物种空间分布的研究方法综述.生态学报,33(22):7047-7057.
马建路,庄丽文,陈动,等.1992.红松的地理分布.东北林业大学学报,20(5):40-48.
毛德华,王宗明,罗玲,等.2016.1990-2013年中国东北地区湿地生态系统格局演变遥感监测分析.自然资源学报,31(8):1253-1263.
欧阳林男,陈少雄,张维耀,等.2019.柠檬桉在中国的适生地理分布及其影响因子.生态学杂志,38(2):361-367.
孙晓红.2012.中国红松地理分布与气候的关系研究(硕士学位论文).北京:中国科学院植物研究所.
王璐,许晓岗,李垚.2018.末次盛冰期以来陀螺果潜在地理分布格局变迁预测.生态学杂志,37(1):278-286.
卫林,王辉民,王其冬,等.1995.气候变化对我国红松林的影响.地理研究,14(1):17-26.
吴正方.2003.东北阔叶红松林分布区生态气候适宜性及全球气候变化影响评价.应用生态学报,14(5):771-775.
吴志军,苏东凯,牛丽君,等.2015.阔叶红松林森林资源可持续利用方案.生态学报,35(1):24-30.
杨志香,周广胜,殷晓洁,等.2014.中国兴安落叶松天然林地理分布及其气候适宜性.生态学杂志,33(6):1429-1436.
于大炮,周旺明,包也,等.2015.天保工程实施以来东北阔叶红松林的可持续经营.生态学报,35(1):10-17.
朱耿平,乔慧捷.2016.Maxent模型复杂度对物种潜在分布区预测的影响.生物多样性,24(10):1189-1196.
IPCC(Intergovernmental Panel on Climate Change).2007.Climate Change 2007:The Physical Science Basis.Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.Cambridge:Cambridge University Press.
Muscarella R,Galante PJ,Soley-Guardia M,et al.2014.ENMeval:An R package for conducting spatially independent evaluations and estimating optimal model complexity for MAXENT ecological niche models.Methods in Ecology and Evolution,5:1198-1205.
Phillips SJ,Anderson RP,Schapire RE.2006.Maximum entropy modeling of species geographic distributions.Ecological Modelling,190:231-259.
Phillips SJ,Dudík MM.2008.Modeling of species distributions with Maxent:New extensions and a comprehensive evaluation.Ecography,31:161-175.
Sillero N.2011.What does ecological modeling model?A proposed classification of ecological niche models based on their underlying methods.Ecological Modelling,222:1343-1346.
Xu DY,Yan H.2001.A study of the impacts of climate change on the geographic distribution of Pinus koraiensis in China.Environment International,27:201-205.
Yang XQ,Kushwaha SPS,Saran S,et al.2013.Maxent modeling for predicting the potential distribution of medicinal plant,Justicia adhatoda L.in Lesser Himalayan foothills.Ecological Engineering,51:83-87.
Yu DP,Zhou L,Zhou WM,et al.2011.Forest management in Northeast China:History,problems,and challenges.Environmental Management,48:1122-1135.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |