DOI: 10.5061/dryad.tqjq2bw10
title: Spatial autocorrelation shapes liana distribution better than topography and host tree properties in a subtropical evergreen broadleaved forest in SW China

description: 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 2,472 – 2,628 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.
description: From
 October 2015 to January 2016, all rooted lianas with the diameter ≥ 1 cm
 were tagged, mapped, measured, and identified to species level following
 standard methods. Briefly, we labelled and mapped the largest “principal
 stem” and additional multiple stems, and then measured the diameter 130 cm
 from the rooting point at the soil surface. When lianas branched below 130
 cm (but ≥ 40 cm from the roots), we measured the diameter 20 cm below the
 branching point. Because multiple stems seem to be functionally equivalent
 in their dynamics and effects on trees, we treated them as separate
 individuals in the subsequent statistical analyses. We classified climbing
 mechanisms into four categories: stem twiner, tendril, hook, and root
 climbers. In total, 3,725 liana stems, including multiple stems, were
 recorded in the 20-ha plot, representing 24 species and 15 families. We
 selected the 12 most abundant species for the study (abundance &gt; 1
 stem ha<sup>–1</sup>), constituting up to 96.9% (3,609 stems)
 of the total liana stems and 97.5% (8.83 m<sup>2</sup>) of the
 total basal area. We quantified the numbers of stems (including multiple
 stems) per species in each of the 500 quadrats. For each of
 the 500 20 × 20 m quadrat, we calculated elevation as the mean elevation
 of the four corners of the quadrat. We calculated slope as the average
 angular deviation of each of the four triangular planes formed by
 connecting three corners at a time with respect to the horizontal line.
 Convexity was the difference between the average elevation of the focused
 quadrat and the average elevation of the eight neighbor quadrats. For the
 edge quadrat, convexity was calculated as the difference between the
 elevation of the center of the focal quadrat and the average elevation of
 the four corners. Aspect was calculated as: , where<i> fx</i> and <i>fy</i> are the elevation difference from east to west, north to south in the 20 × 20 m quadrat, respectively.