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 data set contains satellite-derived information on geomorphic river mobility for ten catchments in the Philippines. We applied the locational probability approach to map the proportion of time that a river channel occupies a particular location. We quantified satellite-derived locational probabilities for 600 km2 of riverbed. The information is useful for predicting and developing resilience to river-related hazards in dynamic landscapes. We provide example Google Earth Engine (GEE) and MATLAB codes to replicate satellite-derived locational probability analyses, and provide outputs for each catchment. Data sets include: (1) example GEE codes to run satellite imagery analyses; (2) example MATLAB codes and data to generate locational probabilities; (3) example MATLAB codes and data to produce longitudinal analyses; and, (4) processed locational probability outputs for the ten catchments. The work was supported by the Natural Environment Research Council (NERC) and Department of Science and Technology - Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD) – Newton Fund grant NE/S003312. Full details about this dataset can be found at https://doi.org/10.5285/a2bcc66e-4dcc-4ed1-897d-cdf36dde246d

The shapefiles contain the classification and locations of each river style determined by the authors. The data were used to characterise the river styles in Bislak River, Philippines. Shapefiles were clipped to the catchment boundary from different national government agencies to produce different thematic maps. Catchment properties such as land use (from the National Mapping and Resource Information Authority (NAMRIA)), geology (from the Mines and Geosciences Bureau), fault (from Philippine Institute of Volcanology and Seismology, rainfall isohyets, slope map, and the digital elevation model (also from NAMRIA) were used for regional and catchment analysis. The data only covers the whole Bislak catchment, Philippines. The CSV contains data used for the stream power analysis where stream power is a factor of slope and discharge. Full details about this dataset can be found at https://doi.org/10.5285/31ae71aa-74a9-466b-9a3a-25d2b1a9406e

The data set contains multi-temporal aerial imagery for two river segments in the Philippines. Imagery covers: (i) the downstream segment of the Bislak River and (ii) the confluence of the Abuan, Bintacan and Pinacanauan de Ilagan Rivers (referred to as ‘Ilagan’ in this data resource). Repeat aerial surveys were completed in 2019 and 2020. The data coverage includes the river channels, floodplains and surrounding areas. Raw aerial images were processed to produce spatially corrected orthoimagery (see supporting documentation). The resulting orthoimagery has a 0.2 m spatial resolution, containing information on the red, green and blue (RGB) bands. The work was supported by the Natural Environment Research Council (NERC) and Department of Science and Technology - Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD) – Newton Fund grant NE/S003312. Full details about this dataset can be found at https://doi.org/10.5285/e040ff39-2176-4ed4-9e5d-861bdae8a030

This dataset contains RGB photographs acquired from drone surveys. There are 741 harvest plots from 38 surveys at 36 sites around the world. Each site was approximately 1 ha in area. Included with the photographic images are the coordinates of ground control markers, biomass, taxonomic and location data for harvest plots and ancillary metadata. The observations can be used to obtain allometric size-biomass models. This work was supported by the Natural Environment Research Council award number NE/R00062X/1 as part of the project 'Do dryland ecosystems control variability and recent trends in the land CO2 sink?' Full details about this dataset can be found at https://doi.org/10.5285/1ec13364-cbc6-4ab5-a147-45a103853424

This dataset describes the chemical and physical properties of wildfire ash collected following wildland fires in different ecosystems and burn severity conditions across the globe. For the chemical properties, ash was collected from sampling sites across eight countries (Australia, Canada, South Africa, US, UK, The Netherlands, Spain and Austria). For the physical properties, ash was collected from four locations in Tenerife (Spain), Victoria (Australia), Manchester (UK) and Idaho (US). Full details about this dataset can be found at https://doi.org/10.5285/cd3d8b4e-0e0c-461c-8ec4-55e81d32eebb