The International Satellite Land Surface Climatology Project, Initiative II (ISLSCP II) is a follow on project from The International Satellite Land Surface Climatology Project (ISLSCP). ISLSCP II had the lead role in addressing land-atmosphere interactions - process modelling, data retrieval algorithms, field experiment design and execution, and the development of global data sets. The ISLSCP II dataset contains comprehensive data over the 10 year period from 1986 to 1995, from the International Satellite Land Surface Climatology Project (ISLSCP). This dataset contains: *Albedo *Ecosystem roots *Historic crop land and land cover *Potential vegetation *Continuous vegetation The data are mapped to consistent grids (0.5 x 0.5 degrees for topography, 1 x 1 degrees for meteorological parameters). Some data have a grid size of 0.25 x 0.25 degrees. The temporal resolution for most data sets is monthly (however a few are at finer resolution - 3 hourly). This dataset is public.

The Fourier-Adjusted, Sensor and Solar zenith angle corrected, Interpolated, Reconstructed (FASIR) adjusted Normalized Difference Vegetation Index (NDVI) dataset was detected with the Advanced Very High Resolution Radiometer (AVHRR) on-board the MetOp satellites. Derived biophysical parameter fields were generated to provide a 17-year satellite record of monthly changes in the photosynthetic activity of terrestrial vegetation. The FASIR NDVI data set was produced and provided by Dr. Sietse Los from the Department of Geography, University of Wales at Swansea. The production of the dataset and its associated biophysical parameters was funded by NASA's Land Surface Hydrology program and the Higher Education Funding Council for Wales (HEFCW) as a core component of the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II Data Collection. AVHRR FASIR data is restricted to academic research use only.

This dataset contains netcdf files produced from the output of UK Met Office Unified Model atmosphere-only simulations over West Africa for current vegetation and 1950s vegetation scenarios. The region covered is 20W to 20E, 0N-25N and simulations were run for 5 days from 1st June 2014 conditions using boundary conditions and sea surface temperature from ERA-Interim reanalysis. The files contain ensemble means (from 10 member ensembles) and the results of a paired Student's T-Test between the two scenarios. There are also files for specific longitude bands and some averaged over 16W-16E, 4N-15N for all land, deforested land and unchanged land. The data is mostly hourly and allows analysis of the impact of recent deforestation in this region. The simulations were run by Julia Crook (University of Leeds) on the ARCHER supercomputer. This data was collected as part of the NERC project 'Vegetation Effects on Rainfall in West Africa (VERA)'.

This dataset is a compilation of results obtained from vegetation surveys in the Stalybride estate moorlands (commonly known as the Saddleworth moors) following a wildfire in 2018. Ten plots were established in October 2018 at the post-fire site which were 10 m x 10 m in size. Five plots were identified as suffering a less severe (shallow) burn. The other 5 plots were in areas where a more severe (deep) burn. In all plots the surface vegetation had been removed by the fire exposing the bare peat. The data file contains: (1) On-site post-fire vegetation data – species ID and coverage, and (2) species presence in the one-year post-fire seed bank. The dataset is the result of research in the light of an NERC Urgency grant entitled 'RECOUP-Moor: Restoring Ecosystem CarbOn Uptake of Post-fire Moorland' (NE/S011943/1, led by Dr. Bjorn Robroek of the University of Southampton (now Radboud University Nijmegen, the Netherlands). Full details about this dataset can be found at https://doi.org/10.5285/56561ed3-55d0-454c-a6b9-7e633ccf9647

Vegetation survey data comprise per-quadrat species level data and abundances, abundance cover classes (following Braun-Blanquet method), family, growth duration, habitat and native species. Data also contain ground cover class and Denisom reading for tree canopy cover. Data were collected from the South Fork McKenzie river, Oregon, USA in June 2021 following the Holiday Farm wildfire in Autumn 2020. Vegetation surveys were conducted in restored and unrestored reaches of the South Fork McKenzie River with a view to quantifying differences in vegetation response to wildfire in the restored vs. unrestored river reaches. The study was conducted by the University of Nottingham, with data collected by partners from The US Forest Service, Portland State University, Washington State University and Colorado State University. Funding for the work was received from the Natural Environment Research Council. Full details about this dataset can be found at https://doi.org/10.5285/251081d0-0388-44fa-b5f9-a4c784f64218

This information product contains gridded estimates of Ellenberg vegetation indicator scores for four different indicators: fertility (N); pH/reactivity (R); light availability (L) and moisture (F) at 1km2 resolution. Both cover-weighted (cwt) and non-cover weighted (site) Ellenberg indicators are estimated. Estimates are made for two different time periods, 1990 and 2015-2019 and the change between the two time periods is also presented. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/0a9900f2-8556-4487-bc13-9c2fdc05082c

This dataset presents a palaeoecological record of stratigraphy, radiocarbon-dated chronology, spores of coprophilous fungi (SCF), pollen and charcoal from lake sediment cores collected from Laguna La Yeguada, Panama. Laguna La Yeguada is an elliptical lake situated in the Veraguas Province within the Isthmus of Panama (8°27' N, 80°51' W). The data were collected to investigate the Late Quaternary megafaunal extinction in Panama and establish the first detailed record of megafaunal presence/absence, vegetation dynamics, and fire activity, respectively, spanning the Late Pleistocene to the Holocene. The data was collected for the PhD research titled: Ecological consequences of Pleistocene megafaunal declines in the Neotropics (https://gtr.ukri.org/projects?ref=studentship-2859430), funded by https://gtr.ukri.org/projects?ref=NE/S007504/1. The data is to be published in the Quaternary Science Reviews Journal: Pym, F., Franco-Gaviria, F., Raczka, M., Adediran, G.A., Sitch, S. and Urrego, D.H. The Timing and Ecological Consequences of the Late Pleistocene Megafaunal Declines on the Isthmus of Panama: Implications for Trophic Rewilding, Quaternary Science Reviews.

We present here the land cover classification across West Antarctica and the McMurdo Dry Valley produced from Landsat-8 Operational Land Imager (OLI) images of six proglacial regions of Antarctica at 30 m resolution, with an overall accuracy of 77.0 % for proglacial land classes. We conducted this classification using an unsupervised K-means clustering approach, which circumvented the need for training data and was highly effective at picking up key land classes, such as vegetation, water, and different sedimentary surfaces. This work is supported by the Leeds-York-Hull Natural Environment Research Council (NERC) Doctoral Training Partnership (DTP) Panorama under grant NE/S007458/1. The Ministry of Education, Youth and Sports of the Czech Republic project VAN 1/2022 and the Czech Antarctic Foundation funded fieldwork that contributed to part of this work.

This dataset contains information about soil near-surface physical and hydrological properties, vegetation observations and land use & management information across the Thames catchment (UK). It was collected during the ‘Landwise' project's ‘Broad-scale field survey' which sampled 1836 location points across a total of 164 fields/land parcels. The aim of the survey was to quantify the impact of innovative land use and management on soil properties, with implications for natural flood management. The surveyed fields were selected to represent four broad land use and management classes (arable with and without grass in rotation, permanent grassland and broadleaf woodland) and five generalised soil/geology classes. Approximately eight fields were sampled for each of the twenty combinations of land use and soil/geology class. The sampled fields cover a range of traditional and innovative agricultural practices. Within each field/parcel, representative sampling locations were selected to cover the anticipated range of soil variability, including typical infield, untrafficked margins and trafficked headlands/tramlines etc. Sampling was undertaken once during the period 2018-2021. Samples were measured and analysed using a range of field and laboratory techniques (see Data Lineage). Point data include: 1. Survey point location (British National Grid coordinates) 2. Soil quantitative measurements (near-surface: 0 – 50 mm below ground level): dry bulk density, volumetric water content, organic matter, derived porosity, derived porosity accounting for variable organic matter, particle size distribution and texture classification 3. Vegetation quantitative measurements: maximum and minimum height 4. Soil qualitative measurements: hand texture classification, aggregate stability test slaking and dispersion results, hydrochloric acid test for calcareous soil, and for a subset of locations Visual Evaluation of Soil Structure (VESS) score 5. Observations (also classified into groups): soil surface condition (e.g. slaked/unslaked/capped/poached etc.), vegetation type Field contextual data include: 1. Land owner/manager responses to a land use and management questionnaire (primary data) including information on: crop types/rotation, cover crops, herbal leys, organic or conventional, organic amendments, lime additions, tillage, last ploughed, tramlines, buffer strips, field drainage, grass species, livestock, last grazed, stocking density, grazing weeks per year, stock out-wintering, mob or paddock grazing, woodland management, tree species, woodland age, path management, land use history, flooding history, waterlogging, water or sediment runoff 2. Classification of selected questionnaire free text responses into categories (derived secondary data) 3. General field observations (primary data) including: slope gradient and shape, surface form, surface water, surface condition (slaking, capped, ruts, wheelings, poaching etc.), soil erosion or deposition features As agreed with the survey participants, this dataset has been anonymised by removing location specific information, such as farm and field names, along with any other personally identifiable information. As also agreed, point data location coordinates have been degraded to the nearest 1 km grid point. The dataset was co-produced by the UK Centre for Ecology and Hydrology and Landwise Partners as part of the Landwise Natural Flood Management project, supported by the Natural Environment Research Council (Grant NE/R004668/1). The participation and assistance of the land owners and managers is gratefully acknowledged. Full details about this dataset can be found at https://doi.org/10.5285/9ab5285f-e9c4-4588-ba21-476e79e87668