Data are presented for Above ground Carbon Density (ACD) estimated from a series of forest census surveys which took place from 1992- 2016 in a mixture of logged and unlogged tropical lowland dipterocarp forest in the Ulu Segama Forest Reserve (USFR) and Danum Valley Conservation Area (DVCA), Sabah, Malaysia. Additional data on logging method, coupe and year of logging is also presented. The USFR comprises of forested land divided into coupes that were each logged once, between 1972 and 1993 using either "tractor" or "high-lead" methods. Between 1993 and 2004, forest restoration treatments were carried out, including climber cutting and tree planting, annually across logging coupes within the USFR. The data-set was compiled from census carried out in three independent plot networks. The first led by researchers from the Universities of Dundee, Aberdeen and Nottingham. The second led by researchers from the University of Aberdeen. The third through the INnoprise FAce PROject INFAPRO project. Between 1992 and 2016 a forest census survey was carried out on at least two occasions in 553 forest plots to determine the rate of ACD accumulation and understand the impact of forest restoration treatments on ACD accumulation. Tree stem diameter, height and identity measurements at each plot were collected by project members and research assistants employed by the SouthEast Asian Rainforest Research Partnership (SEARRP). The ACD carbon estimation and modelling was led by researchers from the Universities of Dundee, ETH Zurich and Aberdeen. The data were compiled and submitted by researchers from the University of Dundee and ETH Zurich. Funding for the establishment of the original plot networks was provided by the EU-funded INDFORSUS project (ER-BIC18T960102), from New England Electric Systems, National Geographic Society and the Garden Club of America, and from Face the Future Foundation. Funding for the repeated measurements was provided by the NERC "Spatio-TEmporal Dynamics of Forest Response to ENSO Drought (STEED)" (NERC grant reference NE/P004806/1) and the Carnegie Trust for the Universities of Scotland funded project"Changing species diversity and biomass accumulation in conserved and regenerating tropical forests: two decades on". Full details about this dataset can be found at https://doi.org/10.5285/a75e6371-a931-4676-9199-d1f5af565ab2

This dataset consists of survival and heights of trees planted for forest restoration in South and Southeast Asia and the associated analytical code. The data consists of tree censuses collated from published studies, grey literature and data provided by co-authors, up to/including May 2021. Data are collated from 176 sites in areas where disturbance or clearance of the natural forest had occurred and where trees were then planted and monitored over time. The analyses included here model height growth, extract annual size-standardised growth rates and test the effects of biophysical and climatic conditions and planting regimes on survival and growth. This dataset was created to represent the current state of knowledge on forest restoration outcomes in South and Southeast Asia. This is the full dataset for the survival and height analysis. Full details about this dataset can be found at https://doi.org/10.5285/935781e1-9119-4673-bd09-3fc76ae627d5

This dataset consists of structure, biomass (carbon density) and biodiversity (plant species richness) from forest inventory plots at forest restoration sites in South and Southeast Asia and the code for the analyses of these data as conducted in Banin, Raine et al (2023). The recorded data consists of plot level censuses carried out up to May 2021 collated from published studies, grey literature and data provided by co-authors. This represents the collation of data from 11 sites in areas where disturbance had led to the clearance or degradation of natural forest. Plots where tree seedlings were planted (active restoration) and plots where no seedling planting took place (natural regeneration) were censused for structure, biomass and/or biodiversity. Some of the sites in the dataset also recorded data at old growth forest plots for reference, and/or provided repeat measures of forest metrics over time. The dataset also includes the code used for analysis of this plot level data, used to compare the outcome of different restoration approaches. Full details about this dataset can be found at https://doi.org/10.5285/3d3b1d09-9e7a-4144-b8a1-b09a3c573466