[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 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 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

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

The data set contains vertical profiles of diffuse light transmittance measured within six forest plots in montane Atlantic forest, São Paulo state, Brazil. The plots measured include intact, previously logged and secondary forest in a large continuous forest block of the Serra do Mar State Park (Parque Estadual de Serra do Mar), and two forest fragments outside the park. In each plot 10 - 12 individual light profiles were recorded; the data set contains these individual profiles and averages profiles for each plot based on both height above the ground and depth below the canopy. Each profile was measured only once. Data was collected March - November 2015 as part of the NERC Human modified Tropical Forest Programme. Full details about this dataset can be found at https://doi.org/10.5285/4f3cf9f6-d7e5-4ae0-87c9-064b4e66a92a

The dataset contains the chemical composition of anaerobic digestates derived from source-segregated food waste & agro-waste, with and without biomass ash, after the addition commercial polymer to enhance dewaterability. A preliminary experiment was carried to determine the type of polymer and its optimum dose (WP1A1). Then, polymer was added to digestate and digestate/ash blends, let react for short-time and physically separated into their fiber and liquid fractions (WP1A2). These experiments were carried out in the laboratory during 2016, being measured via a combination of internal and external laboratories. Preliminary experiment (WP1A1) contains data on polymer type, dose and mass added as well as supernatant and solids separated. Main experiment contain data on masses (dry & total solids), supernatant volume, pH and plant macro-nutrients profile (total concentration of Ca, Mg, P, K, TKN and S). Full details about this dataset can be found at https://doi.org/10.5285/2977fc7b-f83e-4696-b06b-2f589ffa6965

[THIS DATASET HAS BEEN WITHDRAWN]. This dataset contains daily automated weather station (AWS) data from the Climoor field site in Clocaenog forest, NE Wales. It runs from 12/6/1999 until 31/12/2013, and contains air temperature (mean, minimum and maximum), rainfall, net radiation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction. The dataset has been quality checked, and incorrect or missing values removed, data has not been infilled. Full details about this dataset can be found at https://doi.org/10.5285/01592784-807b-453a-ac52-0478ad616484

The dataset contains the radiocarbon age of soil organic matter fractions collected along grassland-to-forest conversion chronosequences across Scotland. Soil samples were collected in summer 2018. In summer 2019, soil samples were fractionated and the radiocarbon age of bulk soil and soil fraction samples determined by accelerator mass spectrometry. Full details about this dataset can be found at https://doi.org/10.5285/0dd45f6f-0536-4ee3-9932-58bac019d2c6

This dataset contains concentrations of Persistent Organic Pollutants (POPs) and mercury (Hg) in merlin and golden eagle egg contents collected as part of the Predatory Bird Monitoring Scheme (PBMS). In addition to residue data, for each record the year and region in which the egg was collected, and the egg shell index are recorded. The PBMS is a long-term, national monitoring scheme that quantifies the concentrations of contaminants in the livers and eggs of selected species of predatory and fish-eating birds in Britain. Levels of contaminants are monitored to determine variations between species and regions, changes over time and effects on individual birds and their populations. The Scheme is currently funded by CEH, Natural England, the Environment Agency (EA) and the Campaign for Responsible Rodenticide Use (CRRU). Full details about this dataset can be found at https://doi.org/10.5285/ad38a087-01a3-4865-b07c-a088ffb65916