[This dataset is embargoed until November 1, 2024]. These data contain bank strength measurements in a 100 km reach of the Solimões River from Sep/Oct 2022 recorded with a shear vane and a cohesion strength meter. In addition, processed satellite (Landsat) imagery from 1984-2021 was used to calculate erosional and depositional area in three 50-120 km long reaches in the Solimoes River presented here as shape-files. Processed Corona imagery 1967 for a 120 km long reach in the Solimoes River shows the banklines and bar outlines. A spreadsheet provides erosional and depositional area at 20-km sections along the 1,600km of the Solimoes River that were based on measuring floodplain width from a digital elevation model (FABDEM). We also attach a GeoTIFF file of the multibeam echo sounder (MBES) data collected during the field campaign in a 20-km long reach in the Solimoes River Full details about this dataset can be found at https://doi.org/10.5285/11786f86-a3ac-45ab-81b5-10fd157e3d7a

[This dataset is embargoed]. The following dataset contains information on saplings of woody plant species in invaded subtropical mountain forests (Yungas) over three years. The forests were located in the Horco Molle Experimental Reserve and Parque Sierra de San Javier, Tucumán, Argentina. The data was collected as part of an experiment to investigate the impact of management control on the invasion of non-native species such as Ligustrum lucidum, and other less abundant non-native species, on the dynamics of the woody community. The experiment was conducted between June 2020 and November 2023. This work was carried out as part of NERC grant NE/S011641/1 “Optimising the long-term management of invasive species affecting biodiversity and the rural economy using adaptive management”. Full details about this dataset can be found at https://doi.org/10.5285/4311fa93-fdcc-43bd-bb2e-185118c06ed7

[This dataset is embargoed until December 15, 2025]. This data set represents field-based monitoring of insect pollinator communities found within soya (Glycine max L. Merril) crops located along a latitudinal gradient ranging from -37.669486 to -24.495121 covering both Argentina and Brazil. Yield data was also collected from these same sites to elucidate the dependencies of this crop on insect pollination with a focus on managed and wild pollinators. Data was collected over multiple seasons between 2020 and 2022. Soybean is one of the most traded agricultural commodities and is of significant economic importance in South America. Full details about this dataset can be found at https://doi.org/10.5285/2bd21042-ebbc-4454-8ca3-96e18333ccd2

This dataset contains two gridded potential evapotranspiration variables for Great Britain from 1961-2019: daily total potential evapotranspiration (PET; kg m-2 d-1) and daily total potential evapotranspiration with interception correction (PETI; kg m-2 d-1). The variables were calculated from the Climate Hydrology and Ecology research Support System meteorology dataset for Great Britain (1961-2019) [CHESS-met] gridded observed meteorological data at 1 km resolution. The units kg m-2 d-1 are equivalent to mm d-1. The data are provided in gridded NetCDF files. There is one file for each variable, for each calendar month. Full details about this dataset can be found at https://doi.org/10.5285/bcec9c33-f863-464e-ac28-73b981bd40a4

[This nonGeographicDataset is embargoed until September 2, 2024]. The data consists of 3D surface scans of the beaks of 662 museum specimens of sixteen species (representing fifteen families of passerine birds: Fringillidae, Ploceidae, Passeridae, Viduidae, Thraupidae, Estrildidae, Artamidae, Cardinalidae, Sittidae, Prunellidae, Motacillidae, Emberizidae, Alaudidae, Cinclidae, Bombycillidae). Each species has scans from between 23 and 31 specimens with the exception of chaffinches (Fringilla coelebs), with scans from 230 specimens representing fourteen subspecies. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/e53b2c4f-fc2e-47a9-b5b7-cc3a59f790ac

[This dataset is embargoed until March 15, 2025]. This dataset consists of bird observation and mist netting records for both bats and birds collected from December 2020 to March 2023. The data collection employed a mixed-methods approach incorporating point counts and mist netting techniques. Surveys were carried out in multiple localities, encompassing 3 sites in Ghana and 5 in Zambia. The data were collected as part of the Social and Environmental Trade-Offs in African Agriculture (Sentinel) project, funded by UK Research and Innovation via the Global Challenges Research Fund (Grant Number: ES/P011306/1). Full details about this dataset can be found at https://doi.org/10.5285/c3b89279-ba7d-4df3-bc6c-82ffcaeaad3d

This dataset provides stream networks for three river basins in eastern Sri Lanka (Mundeni Aru, Maduru Oya and Miyangolla Ela). The stream networks were developed for use in hydrologic modelling and are provided as shapefiles. The work was supported by the Natural Environment Research Council (Grant NE/S005838/1). Full details about this dataset can be found at https://doi.org/10.5285/0537af26-5cab-4381-aca0-d997db421111

This dataset details the allometry and leaf trait measurements in three common gardens of fifteen juvenile tree species from the Colombian Andes planted along a thermosequence (14, 22 and 26 deg C) in the Antioquia region of Colombia. Allometric data includes tree diameter at the base, total tree height and height to the first branch, crown diameters, health status, survival and percentage of herbivory attacks over ten measuring campaigns from February 2019 until January 2022. Trait data includes leaf area, thickness, dry weight, leaf mass per area total number of branches and leaves per tree. Regarding the common garden plantations the trees were planted in the ground between November 2019 and January 2019 with planting height ranging between 50 and 100 cm (species dependent). Full details about this dataset can be found at https://doi.org/10.5285/c7ce1610-aba3-4a09-bf7c-1b6c774d597a

[THIS DATASET HAS BEEN WITHDRAWN]. 5km gridded Standardised Precipitation Index (SPI) data for Great Britain, which is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al. [1]. SPI is calculated for different accumulation periods: 1, 3, 6, 12, 18, 24 months. Each of these is in turn calculated for each of the twelve calendar months. Note that values in monthly (and for longer accumulation periods also annual) time series of the data therefore are likely to be autocorrelated. The standard period which was used to fit the gamma distribution is 1961-2010. The dataset covers the period from 1862 to 2015. NOTE: the difference between this dataset with the previously published dataset 'Gridded Standardized Precipitation Index (SPI) using gamma distribution with standard period 1961-2010 for Great Britain [SPIgamma61-10]" (Tanguy et al., 2015 [2]), apart from the temporal and spatial extent, is the underlying rainfall data from which SPI was calculated. In the previously published dataset, CEH-GEAR (Keller et al., 2015 [3], Tanguy et al., 2014 [4]) was used, whereas in this version, Met Office 5km rainfall grids were used (see supporting information for more details). The methodology to calculate SPI is the same in the two datasets. [1] McKee, T. B., Doesken, N. J., Kleist, J. (1993). The Relationship of Drought Frequency and Duration to Time Scales. Eighth Conference on Applied Climatology, 17-22 January 1993, Anaheim, California. [2] Tanguy, M.; Hannaford, J.; Barker, L.; Svensson, C.; Kral, F.; Fry, M. (2015). Gridded Standardized Precipitation Index (SPI) using gamma distribution with standard period 1961-2010 for Great Britain [SPIgamma61-10]. NERC Environmental Information Data Centre. https://doi.org/10.5285/94c9eaa3-a178-4de4-8905-dbfab03b69a0 [3] Keller, V. D. J., Tanguy, M., Prosdocimi, I., Terry, J. A., Hitt, O., Cole, S. J., Fry, M., Morris, D. G., and Dixon, H. (2015). CEH-GEAR: 1 km resolution daily and monthly areal rainfall estimates for the UK for hydrological use, Earth Syst. Sci. Data Discuss., 8, 83-112, doi:10.5194/essdd-8-83-2015. [4] Tanguy, M.; Dixon, H.; Prosdocimi, I.; Morris, D. G.; Keller, V. D. J. (2014). Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2012) [CEH-GEAR]. NERC Environmental Information Data Centre. https://doi.org/10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e Full details about this dataset can be found at https://doi.org/10.5285/ed7444fc-8c2a-473e-98cd-e68d3cffa2b0

These data show the presence/absence and identification of Cryptosporidium species from the results of a molecular survey of various upland river biota aquatic invertebrates, biofilms, mammal droppings and fish guts, gills and faeces. Samples were collected from various upland influenced sites from around Wales between 2012 and 2015 and were collected. Additionally, otter samples from UK-wide project were also tested. Sample collection was primarily undertaken by DURESS researchers at Cardiff University. Sample testing and analysis was performed at the Cryptosporidium Reference Unit, Public Health Wales Microbiology, Swansea. DNA was extracted using a commercially available kit (Gentra PureGene), Qiagen stool and tissue DNA kits for the fish and mammal samples. These data were collected to provide new information required for the production of a catchment pathogen model to inform ecosystems (dis)services analysis of land use change scenarios for the Diversity in Upland Rivers for Ecosystem Service Sustainability (DURESS) project, part of the NERC Biodiversity and Ecosystem Service Sustainability (BESS) BESS Programme. Full details about this dataset can be found at https://doi.org/10.5285/84242834-dc78-49a6-83cb-951edac65d18