横断山区种子植物丰富度沿海拔梯度的分布格局
文献类型：学位论文
| 作者 | 张大才 |
| 学位类别 | 博士 |
| 答辩日期 | 2008-01-23 |
| 授予单位 | 中国科学院昆明植物研究所 |
| 授予地点 | 昆明植物研究所 |
| 导师 | 孙航 |
| 关键词 | 面积 气候因子 内插值法 中间地带效应 稀疏法 特殊生境 单峰曲线格局 |
| 其他题名 | Elevational patterns of seed plant richness in the Hengduan Mountains, southwest China |
| 学位专业 | 植物学 |
| 中文摘要 | 研究目的：物种丰富度沿环境梯度的分布格局及潜在机制是生物学家的研究热点，尤其是近年来大尺度空间上γ多样性的研究文献呈几何级数增加。在较小的空间范围内环境变量沿海拔梯度发生了较大的变化，因此物种丰富度沿海拔梯度的分布格局得到更多的关注。横断山区物种丰富，是最大的海拔梯度之一，是分析物种丰富度沿海拔梯度变化的理想场所。本文的主要研究目的有：（1）探索横断山区南、北段的分界线；（2）分析横断山区种子植物丰富度沿海拔梯度的分布格局；（3）分析不同生活型物种和一些选择类群的物种丰富度沿海拔梯度的分布格局；（4）物种特有率沿海拔梯度的变化格局；（5）分析物种丰富度与面积、中间地带效应（Mid-domain effect, MDE）和气候因子之间的关系；（6）分析横断山区特殊生境中的物种丰富度及沿海拔梯度的变化。 研究方法：物种名录及海拔分布数据来源于各种出版物、85,482号标本资料和野外实地考察采集标本。在纬度梯度上将横断山区划分成9个1º纬度带，并记录物种在每个纬度带内的分布，在EstimateS 7.51软件中计算相邻两纬度带间物种组成的Jaccard相似性系数。在海拔梯度上将横断山区800-5500 m的海拔范围划分成47个100 m海拔带或16个300 m海拔带，并分别计算各海拔带内的物种丰富度、面积和气候因子数据。以内插值法（Interpolation）和稀疏法（Rarefaction）两种方法估算各海拔带内的物种丰富度。利用1﹕100万数字高程模型（DEM）在ESRT’s Arcview 3.1软件中计算各海拔带的投影面积。收集了该区域90个气象站1951-1980的气候资料，根据温度与海拔的线性回归关系估算没有气象站分布的海拔带的温度数据；在ESRT’s Arcview 3.1软件中根据克里格（Kriging）空间插值法计算降雨量沿海拔梯度的变化。在RangeModel 5.0软件中模拟计算MDE预测的各海拔带物种丰富度的平均值。最小二乘法和条件自回归模型用于分析物种丰富度与解释变量之间的关系。 研究结果：（1）横断山区种子植物区系统计：横断山区共有种子植物8590种，其中横断山区特有种2783种，特有率为32.4%。草本植物共有6070种，灌木植物1743种，乔木植物777种；草本植物特有率最高（35.5%），其次是灌木植物（29.0%），乔木植物特有率最低（15.7%）。 （2）横断山区南、北段的划分：与29ºN相邻的两纬度带的物种组成相似性明显较低，且物种丰富度在29.0-29.9ºN纬度带明显下降，因此将29ºN纬线作为横断山区南、北段的分界线。根据这一分界线，横断山区南段仅占该区域总面积的40%，但拥有该区域80%以上的物种，物种丰富度是北段的近2倍，而且横断山区50%以上的所有种和60%以上的特有种和乔木植物仅在南段有分布。 （3）物种丰富度沿海拔梯度的分布格局：内插值法和稀疏法两种方法估算的物种丰富度沿海拔梯度的分布均为单峰曲线格局，且丰富度最大值出现在相似的海拔范围内。南段所有种在2000-3200 m海拔范围内最丰富，北段所有种在2500-3800 m海拔范围内最丰富；南、北段特有种丰富度的最大值出现在相同的海拔范围内（3000-4000 m）。而且，面积校正后的物种丰富度沿海拔梯度的分布格局仍然为单峰曲线格局，但丰富度最大值出现的海拔段更低。各生活型植物丰富度沿海拔梯度的变化均为单峰曲线格局，且草本植物丰富度最大值的海拔高于灌木植物和乔木植物。 （4）特有率沿海拔梯度的变化：在4300 m以下海拔段物种特有率随海拔的增加而增加，在4300 m以上海拔段物种特有率随海拔的增加而降低。在属一级水平上，物种特有率沿海拔梯度的变化可区分出三种格局，即①物种特有率随海拔的增加而增加；②物种特有率为单峰曲线格局，即特有率在中海拔段达到最大值；③物种特有率随海拔的增加而降低。 （5）物种丰富度分布格局与解释变量之间的关系：中间地带效应（MDE）与物种丰富度之间的相关性最高，对大多数集合物种丰富度的解释率都在60%以上，且对平均海拔范围更大的物种集合丰富度的解释更高。面积与南段物种丰富度之间的相关性较高，而与北段物种丰富度之间的相关性较低；与特有种丰富度之间的相关性最高，而与非特有种丰富度之间的相关性最低；与草本植物丰富度显著相关，而与灌木植物和乔木植物丰富度之间的相关性大多不显著。所选择气候因子中，湿润指数与物种丰富度之间的相关性最高，其次是年平均降雨量，可能蒸散量与物种丰富度之间的相关性最低；气候因子对非特有种丰富的解释最高，而对特有种丰富度的解释最低；在各生活型植物中，乔木植物丰富度与气候因子之间的相关性最高，其次是灌木植物，草本植物丰富度与气候因子之间的相关性最低。解释变量的复相关关系表明所选择解释变量对物种丰富度沿海拔梯度的变化有较高的解释，其中对非特有种丰富度的解释率在96%以上，对所有种丰富度的解释率在93%以上，对特有种丰富度的解释率在73%以上。 （6）特殊生境中的物种丰富度：南段干旱河谷分布有种子植物1487种，特有种124种，特有率为8.3%；北段干旱河谷分布有种子植物2927种，特有种568种，特有率为19.4%。干旱河谷中面积、气候因子与物种丰富度均显著相关，且相关性较高。树线以上特殊生境中共有种子植物1820种，其中特有种655种，特有率为35.5%；面积、可能蒸散量和年平均降雨量与物种丰富度显著相关，对物种丰富度的解释率在97.6%以上。 主要研究结论：（1）29ºN纬线是横断山区南、北段重要的分界线，且南段是这一生物多样性热点地区的核心区域。（2）横断山区种子植物丰富度沿海拔梯度分布的单峰曲线格局得到证实，3000-4000 m海拔范围是横断山区特有种最丰富的海拔段，同是也是物种分化最强烈的海拔段，在生物多样性保护中具有重要意义。（3）在属一级水平上，物种特有率沿同一海拔梯度的多种分布格局表明物种的特有性与物种在海拔梯度上的演化和散布密切相关。（4）MDE、面积和气候是影响物种丰富度沿海拔梯度分布格局的重要因子，对物种丰富度分布格局有较高的解释能力。（5）由于数据资料的缺乏，高海拔地区的物种丰富度不能得到很好的估算，尤其是树线以上特殊生境是植物多样性考察与标本采集的薄弱区域，需要开展更多的生物多样性调查与植物标本采集工作。 |
| 英文摘要 | Aim: The pattern of species richness along an environmental gradient and its potential mechanism are the study focus of biologists, especially in the recent years, the references of gamma diversity at large-scale space have increased by geometric series. Environmental variables along an elevational gradient drastically vary within a narrow spatial range, so elevational pattern of species richness receives more attention. The elevational gradient in the Hengduan Mountains (Mount Hengduan) is one of the longest bioclimatic elevational gradients in the world, from a subtropical zone to a zone of permanent frost, and there distributes rich species, so it is ideal for the analysis of elevational pattern of species richness. This paper primarily aims to (1) explore the division of the southern and northern Mount Hengduan; (2) describe the elevational patterns of seed plant richness in the Mount Hengduan; (3) describe the elevational patterns of species richness for different life forms and some selected taxa; (4) analyze the variation of species endemism along this elevational gradient; (5) analyze the relationships between species richness and area, mid-domain effect (MDE) and climatic factors; (6) estimate the species richness in special eco-environment of dry valley or elevations above timber line and its variation along this elevational gradient. Methods: Data of species richness and distribution at elevational space came from publications, 85,482 specimens and field investigation. The Mount Hengduan region was divided into 9 latitudinal belts using 1 degree of latitude to define the latitudinal belt. The distribution of species in each latitudinal belt was recorded, and Jaccard similar index of species between adjacent latitudinal belts was calculated by EstimateS 7.51 software. The elevations from 800 to 5500 m were divided into 47 100-m elevational belts, or 16 300-m elevational belts, and species richness, area and climatic data in each 100-m or 300-m elevational belt were calculated. Species richness was estimated by interpolation and rarefaction. A digital elevational model (DEM) was used to calculate the area in each 100-m elevational belt in the region using ESRI’s Arcview 3.1. Climatic factors were obtained from 90 climate stations with a record length of 30 yr (1951-1980). The linear regression between temperature and elevation was significant and strong, so it was used to calculate temperate data for these 100-m elevational belts where no distribution of climate stations. The Kriging algorithm was used to realize spatial interpolation of rainfall using ESRI’s Arcview 3.1. RangeModel software was used to generate a null distribution predicted by the mid-domain effect. The ordinary least squares (OLS) and conditional autoregressive models (CAR) were used to correlate the relationship between species richness and explainable variables. Results: (1) Flora of seed plants in the Mount Hengduan. There distributed 8590 seed plants, of which 2783 species were endemic to the region of the Mount Hengduan, holding 32.4% of total seed plants. There were 6070 herb species, 1743 shrub species and 777 tree species. The herb species had the highest endemism (35.5%), followed by shrub species (29.0%), and tree species had the lowest endemism (15.7%). (2) Division of the southern and northern Mount Hengduan. Species similarity between adjacent latitudinal belts across 29ºN latitude showed a visibly low value, and latitudinal patterns of species richness, shown by the c-value of species-area power function and species / area ratio, showed a sharp decrease at the 1 degree latitudinal belt of 29.0º-29.9ºN. So, the 29ºN latitudinal curve can be as the division of the southern and northern Mount Hengduan. According to this division, the southern subregion occupied 40% of total area, but contained more than 80% of species, almost twice as much as in the northern subregion; 50% of total species, 60% of the endemic or tree species were only distributed in the southern subregion. (3) Elevational patterns of species richness. Elevational patterns of species richness estimated by interpolation and rarefaction both presented to be unimodal, and the highest richness almost located at the same elevations. Total species had the highest richness at the elevations of 2000-3200 m in the southern subregion, and at the elevations of 2500-3800 m in the northern subregion. The elevations having the highest richness of endemic species were located at the same elevational range (3000-4000 m) between the southern and northern subregions. Furthermore, elevational patterns of species richness adjusted by area also presented to be unimodal, but the elevations with the highest richness were far lower. Among the different life forms, their elevational patterns of species richness also presented to be unimodal, and the elevations with the highest richness of herb species were higher than that of shrub and tree species. (4) Variation of endemism along the elevational gradient. Endemism increased with ascending elevation below 4300 m, and then decreased with elevation gain. There were three patterns of endemism at generic level with increasing elevation: namely it (i) increased, (ii) decreased, or (iii) peaked at middle elevations. (5) Relationships between elevational patterns of species richness and explainable variables. The mid-domain effect (MDE) had the strongest relationship with elevational patterns of species richness, and it can explain more than 60% of variation of species richness for most species groups, and MDE had a stronger relationship with broad-ranged species than narrow-ranged species. Area had the highest explainable ability for species richness in the southern subregion, followed by the entire region, and it had the lowest ability to explain the variation of species richness in the northern subregion. Area had a stronger relationship with endemic richness than that of non-endemic richness. Among the different life forms, the relationship between area and herb richness was significant, but it was not significant between area and shrub and tree richness of most groups. In the selected climatic factors, moisture index showed a significant and strong relationship with species richness, but mean annual rainfall or potential evaporation showed a weak relationship with species richness. The relationship between climatic factors and species richness was the highest for tree richness or non-endemic richness, followed by shrub richness or total richness, and it was the lowest for herb richness or endemic richness. The multi-relationship between explainable variables and species richness showed that all explainable variables had a powerful ability to explain the elevational patterns of species richness, and explained more than 96% of variation of non-endemic richness, and 93% of variation of total richness, and 73% of variation of endemic richness. (6) Species richness in the special eco-environments. There distributed 1487 seed plants in the dry valley of the southern subregion, of which 124 species were endemic to the Mount Hengduan region, holding 8.3% to total species. There were 2927 seed plants in the dry valley of northern subregion, of which 568 species were endemic to the Mount Hengduan region, holding 19.4% to total species. Area and climatic factors showed a significant and strong relationship with species richness in dry valley. There distributed 1820 species in the elevations above timber line, of which 655 species were endemic to the Mount Hengduan region, holding 35.5% to total species. Area, potential evaporation and mean annual rainfall all showed a significant and strong relationship with species richness above timber line, and they together explained more than 97.6% of variation of species richness. Main conclusions: (1) The 29ºN latitudinal curve is an important division of the southern and northern Mount Hengduan, and the southern Mount Hengduan is the core of this biodiversity hotspot. (2) The unimodal patterns of seed plant richness along the Mount Hengduan elevational gradient have been approved, and the elevational range of 3000-4000 m. has the highest richness of endemic species, and species in this elevational range have experienced the most drastic differentiation and evolution, so this elevational range is important for the biodiversity conservation. (3) At generic level, multi-patterns of endemism along the same elevational gradient show that endemism is strongly related with evolution and dispersal of species in the elevational space. (4) MDE, area and climate are the important factors to influence the elevational pattern of species richness, and they together have a strong power to explain the variation of species richness along the elevational gradient. (5) Elevational pattern of species richness in higher elevations can not be well described for the insufficiency of data, especially the intensity of plant diversity investigation and plant specimen collection are low in the elevations above timber line in the Mount Hengduan, and more investigations and collections are urgently needed. |
| 语种 | 中文 |
| 公开日期 | 2011-10-25 |
| 页码 | 110 |
| 源URL | [http://ir.kib.ac.cn/handle/151853/190]  |
| 专题 | 昆明植物研究所_昆明植物所硕博研究生毕业学位论文 |
| 推荐引用方式 GB/T 7714 | 张大才. 横断山区种子植物丰富度沿海拔梯度的分布格局[D]. 昆明植物研究所. 中国科学院昆明植物研究所. 2008. |
入库方式： OAI收割
来源：昆明植物研究所
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