全球变化研究中的生物气候指标

在大气科学、地学和生态学的长期研究中，科学家们经常使用年与季节的单一和综合气候指标，来表达气候及其变异特征，并预测气候与环境的关系和未来变化。在近期的全球变化研究中，尤其是植被模型领域，科学家们较多利用生物气候指标来模拟和分析植被结构、功能与环境的定量关系，包括年均温、最冷月和最热月均温、极端低温、年降水及其季节性分配、生长度日（积温）GDD₀和GDD₅，以及各种干旱或湿润指数，比如α指数（实际蒸散与可能蒸散的比率）、Palmer干燥度指数（PDSI）和标准化降水蒸散指数（SPEI）等。然而，部分计算较复杂的指标在古生态学和古植物学领域，尤其在基于孢粉数据定量重建古气候时，使用尚不频繁。本文在简介生物气候指标及其对物种和植被分布的控制原理之后，重点介绍全球植被模型与古气候定量重建中常用的一些生物气候指标，包括其原理、计算方法、优缺点及其应用举例，并列举一些易获取的气候数据库供下载使用，如CRU和WorldClim全球气候数据库，来自中国气象数据网的各种元数据和插值数据，以及来自中国生态系统研究网络数据共享系统的中国陆地生态信息空间气象数据库等。

AN INTRODUCTION TO BIOCLIMATIC FACTORS IN GLOBAL CHANGE RESEARCH

Many simple and integrated annual or seasonal climate factors have commonly been utilized in the research of atmosphere science, geosciences and ecology to express characteristics of climate and its variations, as well as to predict climate and environment relationships and their future changes. In the international global change research, especially in vegetation modelling, however, scientists usually used bioclimatic factors to simulate and analyze quantitative relationships of vegetation structure and functions to environments. These variables include, for example, mean annual temperature, mean temperatures of the coldest and warmest months, extreme low temperature, mean annual precipitation and its seasonality, growing degree days at 0℃ and 5℃ base, some drought or moisture indexes such as the plant-available moisture index α(a ratio of actual to potential evapotranspiration), Palmer Drought Severity Index(PDSI), and Standardized Precipitation Evapotranspiration Index(SPEI). Some of these variables have not been paid more attentions, especially in domestic palaeoecological and palaeobotanical studies. These variables have not been frequently utilized by palynologists when numerically reconstructing past climates using pollen records. This paper introduces firstly some bioclimatic factors and their controls on the distribution of species and vegetation. Then, some bioclimatic factors that commonly used in global vegetation models and past climate reconstructions are emphasized, including their principles, calculation methods, advantages and disadvantages, and applications. Some easily accessible climate data and databases are finally enumerated for further downloading and using, for example, the climate databases from the Climate Research Unit(CRU)and WorldClim, climate observations and interpolated data from China's Climate Data Center, and the climate database under the Chinese terrestrial ecological information system of the Chinese Ecological Research Network.