基于生物气候因子聚类的植物群组划分及其中国生物群区模拟

BIOCLIMATE-BASED PLANT AFFINITY GROUPS AND REGIONAL BIOME SIMULATION OF CHINA

本研究基于10′×10′空间分辨率运用GIS软件对中国植被分布地理配准数字化,提取获得196个优势植物的地理分布数据以及内插相关的气候因子,运用分位数函数计算获得各个植物地理分布的气候阈值;在此基础上采用生物气候群组(BAGs)的分类方法,对196个优势植物气候因子数据进行聚类分析,同时结合中国植被的地理分布特征,最后划分出29个BAG组,包括13个乔木组(6个常绿阔叶和2个落叶阔叶群组,4个常绿针叶和1个落叶针叶群组)、10个灌木组(5个常绿灌木和5个落叶灌木群组)和6个草本组。本研究的BAGs划分是建立在较高空间分辨率和定量气候因子阈值的基础上,因此,通过计算获得BAGs气候阈值(包括每日温度变化幅度、地表霜冻频率、月均温度、月降雨量、相对湿度、日照时数和>5℃年积温等),运用生物圈碳循环CARAIB模型,模拟出中国19个生物群区的现代潜在分布。模拟结果较好地表达了中国植被类型的地理分布,尤其较详细地展示了热带、亚热带、温带和高原地区的不同植被类型地理分布格局,但由于东北地区、西部草原以及热带原生植被受人类活动严重干扰,使得模拟结果比该地区的原生植被地理分布的实际面积偏大。总体而言,本研究获得的29个生物气候群组对模拟现代生物群区分布提供了理想的分类依据,其气候阈值也是进行过去和未来生物群区模拟的重要参照数据。

Geographical patterns of Chinese vegetation are georeferenced with GRASS GIS （Geographic Resources Analysis Support System）software. 196 plant data are obtained on 10′× 10′ resolution with the climatic thresholds of plants calculated with the quantile function. Based on the geographical distribution of 196 dominant species and their related climatic data, twenty-nine Bioclimatic Affinity Groups （BAGs） including 13 tree groups （ Tropical rain green trees, Tropical seasonal rain green trees, South subtropical broad-leaved evergreen trees, Mid-subtropical broad-leaved evergreen trees, Subtropical mountain broad-leaved evergreen trees, North subtropical evergreen broad- leaved trees, Temperate broad-leaved deciduous trees, Warm temperate broad-leaved deciduous trees, Subtropical needle-leaved evergreen trees, Subtropical alpine needle-leaved evergreen trees, Warm temperate needle-leaved evergreen trees, Cool temperate/Alpine needle-leaved evergreen trees, Cool temperate needle-leaved deciduous trees）, 10 shrub groups （Tropical mangrove shrubs, Tropical and south subtropical evergreen shrubs, Subtropical mountain evergreen shrubs, Subtropical deciduous shrubs, Subtropical alpine evergreen shrubs, Savanna shrubs, Warm temperate deciduous shrubs, Temperate alpine deciduous shrubs, Temperate desert shrubs, Alpine desert shrubs） ,and 6 herb groups（ Savanna steppe, Temperate meadow steppe, Temperate steppe, Temperate semi-desert steppe, Alpine meadow steppe, Alpine desert steppe）were obtained in China by means of cluster analysis using the BAGs method. These BAGs are characterized by different geographical patterns and climatic tolerances and requirements as well. The BAGs are of enough details to describe the tropical and subtropical ecosystems（8 tree BAGs,5 shrub BAGs and 1 herb BAG）and high altitude （Tibet Plateau）ecosystems （2 tree BAGs,3 shrub BAGs and 3 herb BAGs）. We inferred their climatic envelopes for diurnal temperature ranges, ground frost frequencies, precipitation,relative humidity,amount of sunshine hours and temperature and growing degree days above 5~C for each BAGs. The thresholds of the 29 BAGs are used to test and validate a vegetation model CARAIB to simulate the potential distribution of 19 biomes（ Boreal/mountain conifer forest, Cool temperate mixed forest, Cool temperate conifer forest, Temperate broad-leaved deciduous forest, Warm temperate mixed forest, Warm temperate conifer forest, Warm temperate broad-leaved evergreen forest, Sub-tropical evergreen forest, Tropical seasonal forest, Tropical rainforest, Cold temperate/boreal open woodland, Warm temperate open woodland, Tropical savanna, Grassland/Steppe,Shrubland,Tundra, Semi-desert, Desert, Ice or polar desert） in China. The simulations are good in agreement with the major vegetation types in China, especially in Tibet Plateau and subtropical ecosystems. In temperate zone,the simulations are larger than the actual distribution due to human activities. Similar results occur in some areas of northwest and tropical zone. These results show that the threshold of 29 BAGs can be used to reconstruct the vegetation pattern in the past and simulate vegetation distribution in the future. 29 BAGs and related climatic threshold also can be applied to the analysis of vegetation schemes of China.