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张大才,孙 航.横断山区树线以上区域种子植物的标本分布与物种丰富度.生物多样性.2008, 16 (4): 381–388

【摘要】:植物标本是植物空间分布信息的重要来源,也是估算物种丰富度的主要数据资料。本文收集了有关数据库和标本馆的标本资料,以分析横断山区树线以上区域种子植物标本的采集现状和物种丰富度。将树线以上区域(4,100–5,500m)划分成14个100m海拔带,将每号标本的海拔信息记录到相应的海拔带内。共收集8,316号标本信息,记载种子植物1,820种,其中横断山区特有种655种。这些标本在物种间的分布极不均匀,仅有1–2号标本的物种最多,共974种,占53.5%。各海拔带内标本总数、种均标本数和物种丰富度随海拔的增加而下降,但物种稀疏曲线不能很好地描述物种丰富度沿海拔梯度的分布格局。因此,需要开展更多的样地调查和标本采集工作,为物种丰富度的估算积累更多的资料。

【关键词】: 海拔梯度 特有种 植物标本 物种丰富度 物种稀疏曲线

Jihong Huang, Bin Chen, Canran Liu, Jiangshan Lai, Jinlong Zhang and Keping Ma. 2012. Identifying hotspots of endemic woody seed plant diversity in China. Diversity and Distributions, 18:673-688.

ABSTRACT
Aim This study aimed to detect distribution patterns and identify diversity hotspots for Chinese endemic woody seed plant species (CEWSPS).

Location China.
Methods Presence of 6885 CEWSPS throughout China was mapped by taking the Chinese administrative county as the basic spatial analysis unit. The diversity was measured with five indices: endemic richness (ER), weighted endemism (WE), phylogenetic diversity (PD), phylogenetic endemism (PE) and biogeographically weighted evolutionary distinctiveness (BED). Three levels of area (i.e. 1, 5 and 10% of China’s total land area) were used to identify hotspots,but the 5% level was preferred when both the total area of the hotspots identified and the diversity of CEWSPS reached by the hotspots were considered.

Results Distribution patterns of CEWSPS calculated with the five indices are consistent with each other over the national extent. However, the hotspots do not show a high degree of consistency among the results derived from the five indices.
Those identified with ER and PD are very similar, and so are those with WE and BED. In total, 20 hotspots covering 7.9% of China’s total land area were identified, among which 11 were identified with all the five indices, including the Hengduan Mountains, Xishuangbanna Region, Hainan Island, and eight mountainous areas located in east Chongqing and west Hubei, in east Yunnan and west Guangxi, in north Guangxi, south-east Guizhou and south-west Hunan,in north Guangdong and south Hunan, in south-east Tibet, and in south-east Hubei and north-west Jiangxi. Taiwan Island was also identified as a major hotspot with WE, PE and BED.
Main conclusions Hotspots of CEWSPS were identified with five indices considering both distributional and phylogenetic information. They cover most of the key areas of biodiversity defined by previous researchers using other approaches. This further verifies the importance of these areas for China’s biodiversity conservation.

Keywords
Biodiversity conservation, endemism, evolutionary distinctiveness, phylogeneticdiversity, range size, weighted endemism.

Wenjing Yang, Keping Ma* and Holger Kreft*. 2013. Geographical sampling bias in a large distributional database and its effects on species richness–environment models. Journal of Biogeography,40:1415-1426

Aim
Recent advances in the availability of species distributional and high-resolution environmental data have facilitated the investigation of species richness–environment relationships. However, even exhaustive distributional databases are prone to geographical sampling bias. We aim to quantify the inventory incompleteness of vascular plant data across 2377 Chinese counties and to test whether inventory incompleteness affects the analysis of richness–environment relationships and spatial predictions of species richness.

Location
China.

Methods
We used the most comprehensive database of Chinese vascular plants, which includes county-level occurrences for 29,012 native species derived from 4,236,768 specimen and literature records. For each county, we computed smoothed species accumulation curves and used the mean slope of the last 10% of the curves as a proxy for inventory incompleteness. We created a series of data subsets with different levels of inventory incompleteness by excluding successively more under-sampled counties from the full data set. We then applied spatial and non-spatial regression models to each of these subsets to investigate relationships between the species richness of subsets and environmental factors, and to predict spatial patterns of vascular plant species richness in China.

Results
Log10-transformed numbers of records and documented species were strongly correlated (r = 0.97). In total, 91% of Chinese counties were identified as under-sampled. After controlling for inventory incompleteness, the overall explanatory power of environmental factors markedly increased, and the strongest predictor of species richness switched from elevational range to annual wet days. Environmental models calibrated with more complete inventories yielded better spatial predictions of species richness.

Main conclusions
Our results indicate that inventory incompleteness strongly affects the explanatory power of environmental factors, the main determinants of species richness obtained from regression analyses, and the reliability of environment-based spatial predictions of species richness. We conclude that even large distributional databases are prone to geographical sampling bias, with far-reaching implications for the perception of and inferences about macroecological patterns.