Tripathi Poonam, Behera Mukund Dev, Roy Partha Sarathi
Centre for Oceans, Rivers, Atmosphere and Land Sciences (CORAL), Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, INDIA.
FNASc, FNAAS, NASI Senior Scientist Platinum Jubilee Fellow, Center for Earth & Space Sciences, University of Hyderabad, Andhra Pradesh, India.
PLoS One. 2017 Mar 15;12(3):e0173774. doi: 10.1371/journal.pone.0173774. eCollection 2017.
Data on the distribution of plant species at spatial (grid) scales are required as input for integrative analysis along with related climate, environment, topography and soil data. Although the world's scientific community is increasingly generating data on plant species at various spatial grids and statistically interpolating and extrapolating the available information, data on plant diversity from the Asian continent are scant. Such data are unavailable for India, the mainland of which has part of three of the world's 36 biodiversity hotspots. Although sufficient field sampling is always impossible and impractical, it is essential to utilize fully any available database by adjudging the sampling sufficiency at a given scale. In this work, we used an exhaustive database of the plant species of the Indian mainland that was sufficient in terms of sampling vegetation types. We transformed the data, obtained the distribution at the 1° and 2° spatial grid levels and evaluated the sampling sufficiency at acceptable threshold limits (60% to 80%). The greatest species richness values recorded in the 0.04 ha quadrant, 1° grid and 2° grid were 59, 623 and 1244, respectively. Clench model was significantly (p value < 0.001) fitted using the plant species data at both the grid levels with a very high coefficient of determination (>0.95). At an acceptable threshold limit of 70%, almost all the grids at the 2° level and more than 80% of the grids at the 1° level were found to be sufficiently sampled. Sampling sufficiency was observed to be highly scale-dependent as a greater number of 2° grids attained asymptotic behaviour following the species-area curve. Grid-level sampling insufficiency was attributed to lower numbers of sampling quadrats in forests with poor approachability, which coincided with the world biodiversity hotspots', suggesting that additional sampling was required. We prescribe the use of the 1° and 2° spatial grids with sufficient sampling for any ecological analysis in conjunction with other data and thereby offer grid-level plant species richness data for the Indian mainland for the first time.
植物物种在空间(网格)尺度上的分布数据,与相关的气候、环境、地形和土壤数据一样,是综合分析所需的输入信息。尽管全球科学界越来越多地生成各种空间网格上的植物物种数据,并对现有信息进行统计插值和外推,但来自亚洲大陆的植物多样性数据却很少。印度就没有这样的数据,其大陆部分包含世界36个生物多样性热点地区中的三个。虽然充分的实地采样往往是不可能且不切实际的,但通过判断给定尺度下的采样充足性来充分利用任何可用数据库至关重要。在这项工作中,我们使用了一个关于印度大陆植物物种的详尽数据库,该数据库在植被类型采样方面是充分的。我们对数据进行了转换,获得了1°和2°空间网格水平上的分布,并在可接受的阈值范围(60%至80%)内评估了采样充足性。在0.04公顷样方、1°网格和2°网格中记录的最大物种丰富度值分别为59、623和1244。使用两个网格水平上的植物物种数据,Clench模型均得到了显著拟合(p值<0.001),决定系数非常高(>0.95)。在70%的可接受阈值下,发现2°水平上几乎所有网格以及1°水平上超过80%的网格采样充足。观察到采样充足性高度依赖尺度,因为更多的2°网格遵循物种-面积曲线呈现渐近行为。网格水平的采样不足归因于难以到达的森林中采样样方数量较少,这与世界生物多样性热点地区相吻合,表明需要额外采样。我们规定在结合其他数据进行任何生态分析时,使用采样充足的1°和2°空间网格,从而首次提供印度大陆网格水平的植物物种丰富度数据。