How beta diversity and the underlying causes vary with sampling scales in the Changbai mountain forests

Tan, Lingzhao ; Fan, Chunyu ; Zhang, Chunyu ; Von Gadow, Klaus ; Fan, Xiuhua (2017-10)

CITATION: Tan, L. et al. 2017. How beta diversity and the underlying causes vary with sampling scales in the Changbai mountain forests. Ecology & Evolution, 7(23):10116-10123. doi:/10.1002/ece3.3493.

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ENGLISH ABSTRACT: This study aims to establish a relationship between the sampling scale and tree species beta diversity temperate forests and to identify the underlying causes of beta diversity at different sampling scales. The data were obtained from three large observational study areas in the Changbai mountain region in northeastern China. All trees with a dbh ≥1 cm were stem-mapped and measured. The beta diversity was calculated for four different grain sizes, and the associated variances were partitioned into components explained by environmental and spatial variables to determine the contributions of environmental filtering and dispersal limitation to beta diversity. The results showed that both beta diversity and the causes of beta diversity were dependent on the sampling scale. Beta diversity decreased with increasing scales. The best-explained beta diversity variation was up to about 60% which was discovered in the secondary conifer and broad-leaved mixed forest (CBF) study area at the 40 × 40 m scale. The variation partitioning result indicated that environmental filtering showed greater effects at bigger grain sizes, while dispersal limitation was found to be more important at smaller grain sizes. What is more, the result showed an increasing explanatory ability of environmental effects with increasing sampling grains but no clearly trend of spatial effects. The study emphasized that the underlying causes of beta diversity variation may be quite different within the same region depending on varying sampling scales. Therefore, scale effects should be taken into account in future studies on beta diversity, which is critical in identifying different relative importance of spatial and environmental drivers on species composition variation.

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