植物种分布的模拟研究进展
收稿日期: 2005-11-30
录用日期: 2006-06-01
网络出版日期: 2006-11-30
基金资助
国家自然科学基金重大项目(30590383);中国气象局气候变化专项(CCSF2006-33)
REVIEW OF MODELLING THE DISTRIBUTION OF PLANT SPECIES
Received date: 2005-11-30
Accepted date: 2006-06-01
Online published: 2006-11-30
从植物种水平研究植被与气候的关系一直是生态学的热点之一。该文综述了植物种与气候关系的早期研究历史和国内外近期研究进展,尤其是20世纪80年代以来,随着全球变化研究的不断发展和深入,植物种地理分布与气候因子关系研究的最新发展,汇总了最近20年来国际上模拟预测植物种潜在地理分布的模型,比较了不同模型的优缺点。统计模型主要包括以生物气候分室模型或气候分室模型为代表的相关模型、以广义线性模型和广义加性模型为代表的回归模型、以分类和回归树分析及人工神经网络为代表的基于规则的模型、以及生态位模型、气候响应面模型等。机理模型主要介绍了基于BIOME1生物地理模型和FORSKA林窗模型的STASH模型、基于过程的物候模型PHENOFIT,以及一种基于水分平衡、温度和植物物候现象的模型。总结不同模型模拟预测的不同地区植物种未来分布的格局,并介绍中国植物种潜在分布区及未来变化的模拟预测工作,从而为更加准确地模拟预测植物种在未来全球变化情景下的变化趋势提供背景知识。
王娟, 倪健 . 植物种分布的模拟研究进展[J]. 植物生态学报, 2006 , 30(6) : 1040 -1053 . DOI: 10.17521/cjpe.2006.0133
Vegetation-climate relationship at the species level has always been a popular research topic in ecology. This review paper summarizes early research and recent research advances on plant species-climate relationship in China and in the world. Especially since the 1980s, when global change study started and rapidly developed, research has focused on relationship between plant species' geographical distribution and climate. During the past two decades, predictive models on species' potential geographical distributions have been well developed. These include statistical models (e.g., correlative models including bioclimatic envelope or climatic envelope models, regression models including generalized linear and generalized additive models, rule-based models including classification and regression tree analysis and artificial neural network, as well as ecological niche models and climatic response models) and mechanistic models (e.g., the STASH model on the basis of BIOME1 biogeographical model, FORSKA forest gap model, the process-based phenology model PHENOFIT, and a model based on water balance, temperature and plant phenology). We compare the advantages and disadvantages of different models, synthesize predictions on the future distribution of plant species in different regions and introduce China's studies about the potential and future distributions of selected plant species. This review provides background knowledge in order to more precisely model and predict the future change of plant species under global change.
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