Scale‐dependent effects of species diversity on aboveground biomass and productivity in a subtropical broadleaved forest on Mt. Huangshan

Xie, Lei; Chen, Hao; Wei, Lai; Chen, Shuifei; Wang, Lu; Xu, Bao-Kun; Yi, Xian-Gui; Wang, Xianrong; Fang, Yanming

doi:10.1002/ece3.9786

Cited by 5 publications

(2 citation statements)

References 59 publications

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“…Furthermore, Zhou [72] suggested that according to the lowfrequency hypothesis [76], ecological dominance might influence the spatial distribution patterns of species because dominant individuals have more frequent interactions than others. Although it is a more frequently encountered problem in biodiversity studies [77], we acknowledge that sampling issues related to different scales can also impact the results of species association investigations. For example, Legendre and Legendre [2] suggested that it is more instructive to compare dominant or abundant species than rare taxa because the latter, having low frequencies of occurrence, are generally inadequately sampled.…”

Section: Specific Co-occurrence Patternsmentioning

confidence: 99%

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Patterns of Forest Species Association in a Broadleaf Forest in Romania

Palaghianu

Coșofreț

2023

Forests

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Ecological patterns of species distribution can reveal essential information on the spatial and functional relationship between species or species and their environment. Various approaches can be used to assess species associations, and our study aimed to compare three methods at different scales: the co-occurrence indices for binary presence–absence data, principal component analysis (PCA) on species abundance and point process analysis. Our goal was to gain a deeper understanding of the species’ co-occurrence patterns and notice if the three methods capture roughly the same spatial distribution trends. Our observational study of the analysed sapling community displayed several positive relationships between species (e.g., the association between ash and linden). However, many relationships were inconsistent across different scales. Furthermore, attraction between species was more prevalent than repulsion. Overall, there is a positive association trend, with more relationships being significantly positive across all scales. This trend is consistent with other recent studies of tree–species interaction. Nonetheless, the results suggest that the scale significantly influences spatial patterns of associations. Positive associations tend to be more prevalent on larger scales, while negative associations are more commonly found on smaller scales, regardless of the analysis method used. While the PCA results are less consistent, the point process analysis allowed us to detect more refined patterns of species associations based on the distance of their interaction. In addition, the binary presence–absence analysis provided solid results, with a coarser spatial perspective but with significantly less sampling effort.

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Section: Specific Co-occurrence Patternsmentioning

confidence: 99%

“…Investigations of the spatial distribution of individuals, processes or phenomena are undoubtedly affected by the scale of the analysis [37,77,78]. Bivariate spatial point process analysis is a native spatial analysis method and a robust tool for estimating species co-occurrence patterns [61].…”

Section: Co-occurrence Patterns At Different Scalementioning

confidence: 99%