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This dataset includes key photosynthesis and respiration data collected from three common garden sites along an elevation/temperature gradient in the Colombian Andes. Raw A-Ci data, the Vcmax (carboxylation of RuBP by the enzyme Rubisco) and Jmax (the regeneration of RuBP by the electron transport chain) values estimated from this data, and Rdark (leaf dark respiration) values collected using spot measurements, are all available, along with variables such as leaf temperature (°C), relative humidity (%) and pressure values (kPa) returned by the LI-6800 portable photosynthesis system. Full details about this dataset can be found at https://doi.org/10.5285/60dd0b8f-f0c3-4e30-841b-1c2067052974
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This dataset contains a mosquito species table with counts for adults and larvae. Samples are from 12 UK wetland sites, sampled between April 2017 and September 2018. A map included in the wetlandmetadata.docx file shows site locations, which include both coastal and inland wetlands, and range from Devon to Kent and from Lincolnshire to Dorset. Samples were collected by staff from University of Greenwich and the UK Health Security Agency: collaborators in a NERC-funded project (NE/NO13379/1), part of the Valuing Nature Programme. We found a total of 19 mosquito species: • 10 Aedes • 3 Anopheles • 3 Culisseta • 2 Culex • 1 Coquillettidia. Full details about this dataset can be found at https://doi.org/10.5285/1b5a8827-4329-4c20-85f8-0979998b3c74
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[THIS DATASET HAS BEEN WITHDRAWN]. Standardised Precipitation Index (SPI) data for Integrated Hydrological Units (IHU) groups (Kral et al. [1]). SPI is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al. [2]. 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 'Standardised Precipitation Index time series for IHU Groups (1961-2012)' [SPI_IHU_groups] (Tanguy et al., 2015 [3]), apart from the temporal extent, is the underlying rainfall data from which SPI was calculated. In the previously published dataset, CEH-GEAR (Keller et al., 2015 [4], Tanguy et al., 2014 [5]) was used, whereas in this new version, Met Office 5km rainfall grids were used (see supporting information for more details). Within Historic Droughts project (grant number: NE/L01016X/1), the Met Office has digitised historic rainfall and temperature data to produce high quality historic rainfall and temperature grids, which motivated the change in the underlying data to calculate SPI. The methodology to calculate SPI is the same in the two datasets. [1] Kral, F., Fry, M., Dixon, H. (2015). Integrated Hydrological Units of the United Kingdom: Groups. NERC-Environmental Information Data Centre doi:10.5285/f1cd5e33-2633-4304-bbc2-b8d34711d902 [2] 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. [3] Tanguy, M.; Kral., F.; Fry, M.; Svensson, C.; Hannaford, J. (2015). Standardised Precipitation Index time series for Integrated Hydrological Units Groups (1961-2012). NERC Environmental Information Data Centre. https://doi.org/10.5285/dfd59438-2170-4472-b810-bab33a83d09f [4] Keller, V. D. J., Tanguy, M., Prosdocimi, I., Terry, J. A., Hitt, O., Cole, S. J., Fry, M., Morris, D. G., and Dixon, H.: 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, 2015. [5] 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/10.5285/047d914f-2a65-4e9c-b191-09abf57423db
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This dataset is part of the study of mimetic host shifts in an endangered social parasite of ants, which is a joint study of the NERC's Centre for Ecology & Hydrology(UK), the University of Oxford(UK), University of Bialystok(Poland), Polish Academy of Sciences(Poland) and UFZ Helmholtz Centre for Environmental Research(Germany). Combined with datasets collected from previous study, they compare the proportions of caterpillars of Maculinea rebeli being adopted by resident Myrmica ant species near Przemysl, Poland in autumn with proportions of successful survivors the following summer to establish host specificity of the socially parasitic butterfly species. The data comprise: the study year, the ant species, total number of ant nest, the number of caterpillar survivors found in the nest of each ant species, number of nests with caterpillar presence and total number of nests without caterpillar presence. They were obtained from one population for 4 years(Y2001, Y2003, Y2004, Y2005). Detailed research method can be found in Thomas et al. (2013) Mimetic host shifts in an endangered social parasite of ants. Proc. R. Soc. B vol. 280 no.1751. (doi: 10.1098/rspb.2012.2336) Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/b472d635-d8fa-4c39-acfe-2b285ca0b9a8
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The dataset contains information on rates of hatching failure, threat status, and management interventions for 244 species of birds extracted from 233 previously published studies. Full details about this dataset can be found at https://doi.org/10.5285/8e157aa1-a81c-436d-bb5d-e7129d91487b
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This dataset describes the composition of a co-evolving community (as colony forming units) over a 30-transfer selection experiment in soil microcosms. The community consists of Pseudomonas fluorescens SBW25 + Pseudomonas putida KT2440 + plasmid pQBR57. Full details about this dataset can be found at https://doi.org/10.5285/9da9bf05-fdbf-41f9-8591-1a4af9b84000
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Growth parameters for tree seedlings in a lowland tropical forest in Panama, subject to experimental soil warming. The experiment is situated at the Soil Warming Experiment in Lowland Tropical Rainforest (SWELTR) on Barro Colorado Island in Panama, where the whole soil profile is subject to warming by 4-degrees. Seedling species are Inga laurina, Ormosia macrocalyx, Tachigali versicolor, Lacmellea panamensis, Protium pittieri and Virola surinamensis. Data are seedling parameters: relative growth rates, height change over time, herbivory index, light-saturated photosynthesis (Amax), leaf chlorophyll concentration, light (photosynthetic photon flux density; PPFD). We also determined soil nutrient (N and P) mineralisation for the same period using in situ ion-exchange resins each month. Data were collected over the period 2016 to 2020, following 3 years of soil warming. Photosynthesis and leaf chlorophyll content index data were collected in field campaigns during 2019 and 2022, respectively. Full details about this dataset can be found at https://doi.org/10.5285/3a4aabba-e790-4ac3-b845-936790768330
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[This dataset is embargoed until May 1, 2025]. The dataset contains information on six functional traits of woody plants, including Leaf Area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC), Leaf Thickness (Lth), Wood Density (WD), Bark Thickness (BT). It also includes data on concentrations of C, N, P, Ca, Mg, and K in leaves; leaf fresh mass and leaf dry mass data; and fresh wood volume and dry wood mass data to calculate Wood Density. Ten leaves per individual were sampled, and three measurements were taken for leaf thickness at the base, middle, and top of the leaf. For wood density, a single branch sample was taken per individual and for bark thickness five measurements per individual were made. The data were collected between 2019 and 2022 from 27 forest monitoring plots (0.5 ha each) in five locations along an altitudinal (lowland, mid-elevation, and highland forests) and forest perturbation (low, medium, and high perturbation levels) gradient in Andean ecosystems in Colombia. The database includes information about the plot location and parameters of the locality. The purpose of this data collection was to determine whether the expression of functional traits in woody plants differs between the perturbation gradient and the relationship of the traits to ecosystem processes. This information is important for understanding the drivers of variation in forest resilience and the impacts of perturbation on ecosystem functioning. This data set was obtained within the framework of the BioResilience project, a transdisciplinary investigation that seeks to understand the resilience of forest ecosystems after the post-conflict period in Colombia. Full details about this dataset can be found at https://doi.org/10.5285/0da218a8-2882-4ee7-bb2a-50a51f7f4138
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This dataset comprises operational data for a novel decentralised drinking water treatment platform (DWTP) and water quality data for three sampling points within the treatment system. The dataset captures a period of 12 weeks between November 2019 and February 2020. The DWTP was continuously operational throughout this time period with samples from across the system being collected at nine timepoints throughout this three-month period. Operational data from the remote telemetry unit on the DWTP reports flow rate through the system, transmembrane pressure for the ultrafiltration and both the oxidation-reduction potential (ORP) and the free chlorine of the treated water. Data is also provided for a suite of biological, physicochemical, chemical, metals, hydrocarbons and disinfection byproducts. This data was produced from water samples which were sent to an accredited UK laboratory. The data reports for all samples for each of the 3 sampling locations within the treatment system are summarised into .csv files. Information about the location of each sampling point and the level of treatment received at each point can be found in the supporting documentation. Full details about this dataset can be found at https://doi.org/10.5285/98148025-e8ef-40f9-907e-dae8b28106d2
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This dataset provides linear trends, over varying time periods, for the UK Butterfly Monitoring Scheme (UKBMS) Collated Indices of individual butterfly species across the UK. The main statistical values derived from a linear regression (slope, standard error, P-value) are presented for the entire time series for each species (1976 to 2015), for the last 20 years, and for the last decade. In addition a trend class, based on slope direction and its significance, and a percentage change for that time period are provided to describe the statistical trends. These trend data are provided for 59 UK butterfly species. Trends across different time series allow us to determine the long and short-term trends for individual species. This enables us to focus conservation and research and also to assess species responses to conservation already in place. The Centre for Ecology & Hydrology (CEH) and Butterfly Conservation (BC) are responsible for the calculation and interpretation of this trend datasets. The collection of the underlying UKBMS data is reliant on a large volunteer community. The UK Butterfly Monitoring Scheme is funded by a consortium of organisations led by the Joint Nature Conservation Committee (JNCC). This version supersedes the original version due to an error in the precision of the reported figures. This dataset is updated annually and a more recent version of the UKBMS species trends (2016) is now available. Full details about this dataset can be found at https://doi.org/10.5285/0383e234-daad-4f0e-8482-c227661f4941