Spatial autocorrelation shapes liana distribution better than topography and host tree properties in a subtropical evergreen broadleaved forest in SW China

Lianas are an important component of subtropical forests, but the mechanisms underlying their spatial distribution patterns have received relatively little attention. Here, we selected 12 most abundant liana species, constituting up to 96.9% of the total liana stems, in a 20‐ha plot in a subtropical...

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Bibliographic Details
Published in:Biotropica 2022-03, Vol.54 (2), p.301-308
Main Authors: Bai, Xiao‐Long, Liu, Qi, Mohandass, Dharmalingam, Cao, Min, Wen, Han‐Dong, Chen, Ya‐Jun, Gupta, Sunil Kumar, Lin, Lu‐Xiang, Zhang, Jiao‐Lin
Format: Article
Language:English
Subjects:
Autocorrelation
climbing mechanism
Coniferous forests
Convexity
dispersal limitation
Distribution
Distribution patterns
Elevation
Forests
habitat preference
Lianas
Properties
Spatial analysis
Spatial distribution
spatial process
Topography
Trees
Tropical forests
variation partitioning
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Summary:Lianas are an important component of subtropical forests, but the mechanisms underlying their spatial distribution patterns have received relatively little attention. Here, we selected 12 most abundant liana species, constituting up to 96.9% of the total liana stems, in a 20‐ha plot in a subtropical evergreen broadleaved forest at 2472–2628 m elevation in SW China. Combining data on topography (convexity, slope, aspect, and elevation) and host trees (density and size) of the plot, we addressed how liana distribution is shaped by host tree properties, topography and spatial autocorrelation by using principal coordinates of neighbor matrices (PCNM) analysis. We found that lianas had an aggregated distribution based on the Ripley's K function. At the community level, PCNM analysis showed that spatial autocorrelation explained 43% variance in liana spatial distribution. Host trees and topography explained 4% and 18% of the variance, but less than 1% variance after taking spatial autocorrelation into consideration. A similar trend was found at the species level. These results indicate that spatial autocorrelation might be the most important factor shaping liana spatial distribution in subtropical forest at high elevation. We found that lianas had an aggregated distribution based on the Ripley's K function. Spatial autocorrelation shapes liana distribution better than topography and host tree properties in a subtropical evergreen broadleaved forest in SW China.
ISSN:0006-3606
1744-7429
DOI:10.1111/btp.13043