The relative importance of space compared to topography increases from rare to common tree species across latitude

JOURNAL OF BIOGEOGRAPHY(2018)

引用 9|浏览49
暂无评分
摘要
Aim Understanding how spatial distributions of rare and common species are associated with environmental and spatial processes is essential to understanding community assembly. We addressed the following questions: (a) does the relative importance of space and topography vary from rare to common tree species? (b) Are the contributions of topography and space equal? (c) Are the variances explained by topography or space correlated with elevational ranges (ER) at the local scale? (d) Does cell-size influence those postulated associations? Location Major taxa studied China and the Americas. Tree species. Methods Results We partitioned the variation in species richness and composition of rare and common tree species by topography and space across a range of extents and grain sizes in eight communities. We calculated contribution ratio (CR) between space and topography to quantify their relative importance. We employed Kendall's rank correlation to determine the relation between CR and commonness. Mixed effect models were used to identify the influence of cell-size on the results. The majority of CR values were positively related to increasing commonness, especially for composition. The explained variances by space were always higher than that by topography regardless of commonness. At local scale, variances explained by space or topography were not correlated with ER. Main conclusions Our results indicate that the relative importance of space compared to topography increases from rare to common species across forests. We suggest that future studies of community assembly need to account for both space and topography to adequately describe differences in rare and common species assembly mechanisms at range of spatial extents and grain sizes.
更多
查看译文
关键词
alpha and beta diversity,community assembly,CTFS-ForestGEO,Niche and neutral,Scale,variation partitioning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要