This dataset contains records of exotic plant occurrence within 21 oil palm-dominated sites in Sabah, Malaysian Borneo. Within each site, exotic plants were recorded along 100m transects in up to four habitats that represented a gradient of disturbance. The four habitats included oil palm, forest-oil palm edge, disturbed forest and intact forest. In addition to exotic plant data, the dataset contains measurements of forest structure for each transect, including canopy cover and number of large native trees. These data were collected in order to examine the change in exotic species composition along a disturbance gradient from oil palm areas into intact rainforest remnants. Full details about this dataset can be found at https://doi.org/10.5285/372861ee-67c5-4bb3-b765-cf8c03c06199

This code uses pathway modelling to look at correlations of exotic plant invasion in tropical rainforest remnants and continuous sites. Partial least squares path-modelling looks at correlations between latent variables that are informed by measured variables. The code examines the relative influence of landscape-level fragmentation, local forest disturbance, propagule pressure, soil characteristics and native community composition on invasion. The total native community is examined first. Then subsets of the native community are modelled separately, adult trees, tree saplings, tree seedlings and ground vegetation. The relationship between the native and exotic communities was tested in both directions. Full details about this application can be found at https://doi.org/10.5285/adbf6d29-ee7b-4dd1-9730-11d2308d526c

This dataset contains records for vegetation in 49 plots across 14 fragmented forest sites and 4 continuous forest sites in Sabah, Malaysian Borneo. Living vegetation and deadwood were surveyed in two or three 0.28-ha plots in each of the 18 sites. In addition to vegetation data, the dataset contains topsoil parameters, measurements of forest structure, and metrics of the degree of forest fragmentation in the landscape surrounding the plots. These data were collected in order to conduct studies examining (1) the factors supporting invasion of exotic plant species into fragmented forest areas; and (2) the value of conservation set-asides for carbon storage and associated plant diversity in oil palm plantations. Full details about this dataset can be found at https://doi.org/10.5285/c67b06b7-c3f6-49a3-baf2-9fc3a72cb98a

The R code "carbon_stock_calculations.R" estimates aboveground carbon stocks for 49 plots in 14 fragmented forest sites and 4 continuous forest sites in Sabah, Malaysian Borneo, using the vegetation dataset 'Vegetation and habitat data for fragmented and continuous forest sites in Sabah, Malaysian Borneo, 2017'. The 14 fragmented sites were all in Roundtable on Sustainable Palm Oil-certified oil palm plantations, and are hereafter termed 'conservation set-asides'. The code also estimates the aboveground carbon stocks of oil palm plantations for comparison. The R code "analyses_and_figures.R" runs analyses and makes figures of aboveground carbon stocks and associated plant diversity for these sites, as presented in Fleiss et al. (2020) This R code was created in order to investigate the following: (1) to establish the value of conservation set-asides for increasing oil palm plantation aboveground carbon stocks; (2) to establish whether set-asides with high aboveground carbon stocks can have co-benefits for plant diversity; (3) to compare the carbon stocks and vegetation structure of conservation set-asides with that of continuous forest, including assessing tree regeneration potential by examining variation in seedling density; (4) to examine potential drivers of variation in aboveground carbon stocks of conservation set-asides (topography, degree of fragmentation, and soil parameters); (5) to scale-up the estimates of the aboveground carbon stocks of conservation set-asides, in order to predict average carbon stocks of oil palm plantations with and without set-asides, and for varying coverage of set-asides across the plantation. Full details about this application can be found at https://doi.org/10.5285/9ff5cdca-b504-4994-8b07-5912ee6aff47