Effects of climate, soil, topography, and disturbance on liana prevalence

Lianas (woody vines and climbing palms) are increasing in abundance in many tropical forests with uncertain consequences for forest functioning and their recovery following disturbance. At a global scale, these increases are likely driven by disturbances and climate change.  Yet, our understanding of the environmental variables that drive liana prevalence at regional scales is incomplete and geographically biased towards Latin America. To address this gap, we present a comprehensive study evaluating the combined effects of climate, soil, disturbance, and topography on liana prevalence in the Australian Wet Tropics. We established thirty-one 20 m x 20 m vegetation plots along an elevation gradient in low disturbance (canopy closure ≥ 75%) and high disturbance (canopy closure ≤25%) forest stands. In these plots, all tree and liana stems ≥ 1 cm DBH were measured and environmental data were collected on climate, soil, and topography. Generalised Linear Models were used with multi-model aver..., This data was collected from a vegetation plot network in the Australian Wet Tropics, northeast Queensland. In each plot (20 m x 20 m), all trees and lianas (woody vines and climbing monocots) > 1cm DBH were recorded and measured. This was used to calculate measures of 'liana prevalence' at the plot-level: woody vine basal area, woody vine stem density, rattan stem density and liana-tree ratio (basal area of all woody vine and climbing monocots divided by tree basal area). Slope, aspect (using a compass and clinometer) and elevation (using a Garmin GPS 64sx) were also recorded in each plot. A soil sample was collected from 0 - 30 cm depth from the centre of each plot using a hand auger. this was sent for subsequent analysis in the lab for pH (using pH meter), total Phosphorous (using acid digestion follwed by ICP-OES) and exchangeable bases Na, Mg, Ca and K (suing acid digestion followed by ICP-MS). All subsequent statistical analysis was conducted using R (R Core Team, 2022). , , # Effects of climate, soil, topography, and disturbance on liana prevalence

[https://doi.org/10.5061/dryad.t4b8gtj96](https://doi.org/10.5061/dryad.t4b8gtj96)

This dataset contains measures of liana prevalence and environmental variables collected from a network of vegetation plots (20 m x 20 m) located within the Wet Tropics, northeast Queensland, Australia. 

## Description of the data and file structure

This dataset consists of two files, one containing the measures of liana prevalence: *'liana_measures*' and the other containing the environmental variables *'environ_variables*'. 

In the *'liana_measures'* dataset:

'*plot_num' is the assigned number of each plot,* 'plot_*name*' is the assigned name of each plot. *'*

*'canopy'*  is categorised as either '*open*', this is the heavily disturbed plots, defined as <25 % canopy closure and '*closed*', defined as lightly disturbed with >75% canopy closure. 

*'tree_BA'* is the total basal area of all trees > 1 cm diameter at ...