This dataset collection is comprised of raw data from the NERC-funded, full waveform terrestrial laser scanner (TLS) deployed at sites on three continents, multiple countries and plot locations which, have been re-surveyed at different times. The terrestrial laser scanner (TLS) was able to scan 1000s of trees in tropical forests on three continents: including Amazonia, the Congo Basin and SE Asia. The laser data measured 3D tree volume and biomass non-destructively to within a few percent of the best current estimates, made by destructive harvesting and weighing. The project scanned all trees in multiple permanent sample plots (PSPs) spanning a range of soil fertility and productivity gradients (24 x 1 ha PSPs in total). The aim of the weighing trees with lasers project is to test if current allometric relationships are invariant across continents, or whether they differ significantly, and require continental level models; quantify the impact of assumptions of tree shape and wood density on tropical forest allometry; test hypotheses relating to pan-tropical differences in observed AGB from satellite and field data. It also aims to apply new knowledge to assessing retrieval accuracy of forthcoming ESA BIOMASS and NASA GEDI missions and providing calibration datasets; In addition to testing the capability of low-cost instruments to augment TLS data including: UAVs for mapping cover and canopy height; low-cost lidar instruments to assess biomass rapidly, at lower accuracy.

This data set contains nematode community data for soil samples collected from two different land uses (farmland and forest) in the Peri urban area of Ningbo China. Samples were collected seasonally between April 2017 and January 2018. Nematodes were removed from soil using density centrifugation, DNA extractions were then carried out on these extracted nematodes and directed TRFLP was used to obtain a measure of nematode community structure. Data are relative fluorescence for each TRFLP peak and have been Hellinger transformed. Full details about this dataset can be found at https://doi.org/10.5285/8ae9c761-3cf9-4709-8632-c4051a244825

The dataset delineates annual forest loss in the CAZ digitized from annual 15 metre resolution LANDSAT imagery. This dataset creates a baseline for possible long-term, near real-time monitoring of encroachment and illegal logging within the Ankeniheny-Zahamena Corridor (CAZ), Madagascar. This analysis includes a summary of suspected encroachment and illegal logging from June 2006 to December 2010 within the "protected area," which consists of zones such as priority for conservation, sustainable use, and controlled settlements. Full details about this dataset can be found at https://doi.org/10.5285/c63c543f-3e95-4c1c-8c69-12f942271813

This dataset contains calculated terrestrial fluxes of methane and nitrous oxide using static chambers from the Sodankylä region of Northern Finland across both forest and wetland ecosystems. Measurements were carried out during growing season 2012 in two measurement campaigns (Summer: 12th July - 2nd August; Autumn: 22nd September - 14th October) using 60 static chambers (21 within the forest and 39 within the wetland). Fluxes were measured on approximately 2 day intervals resulting in a total of 10 measurements for all chambers during the summer campaign, and 7 for the forest and 8 for the wetland chambers during the autumn campaign. In addition to fluxes, auxiliary measurements include soil temperature, water table depth (wetland only), soil moisture (forest only) and soil respiration. The data was collected as part of the MAMM project (Methane and other greenhouse gases in the Arctic: Measurements, process studies and Modelling, http://arp.arctic.ac.uk/projects/) funded by the UK Natural Environment Research Council (grant NE/I029293/1) involving partners from CEH and the Finnish Meteorological Institute (Climate Change Research, FI-00101 Helsinki, Finland). Full details about this dataset can be found at https://doi.org/10.5285/6b8501c8-3931-4c5e-8e1b-584a6ea0d233

The data consists of morphological properties of fine roots in old growth forests in Central Amazon. Fine roots younger than three months were sampled using the ingrowth core technique in a large-scale nutrient fertilisation experiment. Morphological properties are given as a mean of the plant community per plot, where five points inside each plot were sampled and separated in two different soil layers (0-10 and 10-30cm). Samples were collected in February 2018, eight months after the nutrient fertilisation started at the AFEX project area in Manaus, Brazil at the Biological Dynamics of Forest Fragments Project (BDFFP/ INPA). The study was funded by NERC, BDFFP (logistical support) and Brazilian government (student scholarship). Full details about this dataset can be found at https://doi.org/10.5285/4ccaab66-2818-41b8-8b31-1a710766c5d6

The data consists of potential phosphatase activity released by fine roots in old growth forests in Central Amazon. Fine roots younger than three months were sampled using the ingrowth core technique in a large-scale nutrient fertilisation experiment. Phosphatase activity is given as a mean of the plant community per plot, where five points inside each plot were sampled and separated in two different soil layers (0-10 and 10-30cm). Samples were collected in February 2018, eight months after the nutrient fertilisation started at the AFEX project area in Manaus, Brazil at the Biological Dynamics of Forest Fragments Project (BDFFP/ INPA). The study was funded by NERC, BDFFP (logistical support) and Brazilian government (student scholarship) Full details about this dataset can be found at https://doi.org/10.5285/6529004d-b6e8-429d-ac68-0f5324d7e5d0

[This dataset is embargoed until April 1, 2026]. The dataset contains field measurements of atmospheric ammonia under forest canopies in the Himalayas in India, Pakistan, Nepal and Bhutan and in a tropical forest in Sri Lanka between 2022 and 2024. Monthly mean atmospheric ammonia concentrations are provided from 33 sites across the five countries. This dataset provides the first ever empirical measurements of ammonia from South Asian forests and can be used to estimate ecological impact, inform policy decisions, validate atmospheric chemistry transport models and satellite data and design future air quality and ecological monitoring in the region. The ammonia concentration data was collected monthly by deploying passive citric acid-coated samplers at the study locations. Full details about this dataset can be found at https://doi.org/10.5285/9c4aee69-3693-4f18-97c8-ff740045f3de

The NCEO Kenya forest aboveground biomass map shows aboveground woody biomass (AGB) in Kenyan forests. Forest areas include vegetated wetlands and wooded grassland for the year 2015. The map was generated by combining field inventory plots (KFS) with Advanced Land Observing Satellite (ALOS-2), Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) and multispectral optical data (NASA Landsat 8), by means of a Random Forests algorithm within a k-Fold calibration/validation framework. The characterization of carbon stocks and dynamics at the national level is critical for countries engaging in climate change mitigation and adaptation strategies. However, several tropical countries, including Kenya, lack the essential information typically provided by a complete national forest inventory. These data were produced by the National Centre for Earth Observation (NCEO), University of Leicester, in collaboration with the Kenya Forest Service (KFS) with funding from the NCEO ODA Programme. Known Issues: Residual scan line corrector (SLC) effects due to the use of the SLEEK land cover product as a retrieval mask (derived from Landsat imagery) are visible in some areas

The NCEO Manaus plots Above Ground Biomass (AGB) map 2014 v1.0 shows above ground woody biomass in plot sites around the city of Manaus in the state of Amazonas, Brazil. The data supports characterization of carbon stocks and dynamics at the national level, which is critical for countries engaging in climate change mitigation and adaptation strategies. The data consists of AGB for 22 plot sites in the dbf data file. The file is accompanied by shape and metadata files (sbx, shp, shx and prj files) containing plot location information enabling display in GIS applications such as QGIS.

The dataset contains top-of-canopy height before and after the 2015-15 El Niño Southern Oscillation (ENSO) event across a human-modified tropical landscape in Malaysian Borneo. The derived changes in top-of-canopy height from 36,655 repeated measurements were investigated. Data were obtained from airborne LiDAR in November 2014 and April 2016. Topographic Position Index and distance from oil palm plantations are also included to investigate the effects of topography and fragmentation on the canopy height change during the ENSO event. Each observation (pixel) contains the coordinates to assess the spatial effects on canopy changes. Full details about this dataset can be found at https://doi.org/10.5285/534838c8-0e1f-4a04-a837-2e19a4e93797