DOI: 10.5061/dryad.t4b8gtj96
title: Effects of climate, soil, topography, and disturbance on liana prevalence

description: 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 averaging to quantify the relative effects of the
 environmental variables on measures of liana prevalence (liana–tree basal
 area ratio, woody vine basal area and stem density, and rattan stem
 density). Liana prevalence increased with disturbance, and also with
 increasing mean annual precipitation (MAP) and the associated increases in
 temperature and decline in elevation. Increase in the liana–tree ratio
 with MAP was more pronounced for highly disturbed sites. Like other
 tropical regions, disturbance is an important driver of liana prevalence
 in Australian rainforests and also appears to interact with climate to
 increase liana–tree ratios. The observed increase in liana–tree ratio with
 MAP contrasts findings from elsewhere but is likely an artefact of local
 topography and disturbance, which highlights the importance of regional
 studies. Our findings show that forests with high disturbance and climatic
 conditions favourable to lianas are where lianas most likely to outcompete
 trees and impede forest recovery.
description: 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) &gt; 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). 
description: # 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 &lt;25 % canopy closure and '*closed*', defined as lightly disturbed with &gt;75% canopy closure.  *'tree_BA'* is the total basal area of all trees &gt; 1 cm diameter at breast height, measured at diameter at breast height (1.3m) in cm2.  'woody_BA' is the total basal area of all true woody vines &gt; 1 cm diameter at breast height, measured at diameter at breast height (1.3m) in cm2. *'woody_n'* is the total number of all true woody vine stems &gt; 1 cm diameter at breast height, measured at diameter at breast height (1.3m), per 20 m x 20 m plot.  *'rattan_BA*' is the total basal area of all true woody vines &gt; 1 cm diameter at breast height, measured at diameter at breast height (1.3m) in cm2. '*rattan_n*' is the total number of all true woody vine stems &gt; 1 cm diameter at breast height, measured at diameter at breast height (1.3m), per 20 m x 20 m plot.  'LTR' stands for liana-tree ratio and is calculated as the total basal area of all woody vines and climbing monocots (including rattans) (&gt;1cm DBH) divided by the total basal area of all trees (&gt;1 cm DBH).  In the *'environ_variables'* dataset: As above, '*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 &lt;25 % canopy closure and '*closed*', defined as lightly disturbed with &gt;75% canopy closure.  *'elevation'*  is the elevation above sea level in metres, recorded using a Garmin GPS 64sx.  *'slope'*  (degrees) was measured using a clinometer.  *'aspect'* (degrees) was measured using a compass and clinometer.  *'Lon*' is the longitude in decimal degrees of the centre of the plot, recorded using a Garmin GPS 64sx.  *'Lat'* is the latitude in decimal degrees of the centre of the plot, recorded using a Garmin GPS 64sx.  *'pH'* refers to pH of the soil, collected using a pH meter in 1:5 soil to water ratio. *'Na'* (mg/kg) refers to exchangeable base Sodium, extracted using 1M ammonium chloride at pH 7.0 then analysed with Inductively Coupled Plasma Mass Spectrometry. *'K'* (mg/kg) refers to exchangeable base Potassium, extracted using 1M ammonium chloride at pH 7.0 then analysed with Inductively Coupled Plasma Mass Spectrometry. *'Ca'* (mg/kg) refers to exchangeable base Calcium, extracted using 1M ammonium chloride at pH 7.0 then analysed with Inductively Coupled Plasma Mass Spectrometry. *'Mg* (mg/kg) refers to exchangeable base Magnesium, extracted using 1M ammonium chloride at pH 7.0 then analysed with Inductively Coupled Plasma Mass Spectrometry. *'P (mg/kg)*' refers to total Phosphorus, digested with a mixture of 70% nitric acid and 70% perchloric acid in a temperature-controlled digestion block and then the digested samples were analysed by Inductively Coupled Plasma-Optical Emission Spectrometry. ## Code/Software The R scripts with code for all statistical analysis are attached. The file *'R_script'* script contains code for the data preparation and analysis steps as well as the code for creating Figure 3. The second script *'Fig4'* contains the code for creating Figure 4 included in this article.