This dataset contains high-resolution (5 km) Standardized Precipitation Evaporation Index (SPEI-HR) drought data for Central Asia. There are forty-eight different SPEI time scales and the available period is from 1981 - 2018, the data was produced using Climate Hazards group InfraRed Precipitation with Station’s (CHIRPS) precipitation dataset and Global Land Evaporation Amsterdam Model’s (GLEAM) potential evaporation dataset. The SPEI-HR dataset, over time and space, correlates fairly well with SPEI values estimated from coarse-resolution Climate Research Unit (CRU) dataset. Furthermore, the SPEI-HR dataset, for 6-month timescale, displayed a good correlation of 0.66 with GLEAM root zone soil moisture and a positive correlation of 0.26 with normalized difference vegetation index (NDVI) from Global Inventory Monitoring and Modelling System (GIMMS).

Data comprise measurements of plant biomass and community composition, soil microbial community composition, greenhouse gas emissions and soil carbon and nitrogen pools from a drought experiment superimposed on a the long-term Colt Park grassland restoration experiment in northern England. Rainfall was manipulated using rain-out shelters on experimental grassland plots where fertiliser application and seed addition have been managed to enhance plant species diversity. The scientific purpose was to test the hypothesis that management aimed at biodiversity restoration increases the resistance and recovery of carbon cycling to short-term summer drought. Full details about this dataset can be found at https://doi.org/10.5285/8a41b2a2-01d7-409e-adf5-fba3f3770f29

Standardised Precipitation Index (SPI) data for Integrated Hydrological Units (IHU) Hydrometric Areas (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 1961 to 2012. [1] Kral, F., Fry, M., Dixon, H. (2015). Integrated Hydrological Units of the United Kingdom: Hydrometric Areas without Coastline. NERC-Environmental Information Data Centre doi:10.5285/3a4e94fc-4c68-47eb-a217-adee2a6b02b3 [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. Full details about this dataset can be found at https://doi.org/10.5285/5e1792a0-ae95-4e77-bccd-2fb456112cc1

This dataset consists of high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset over the whole Africa at different time scales from 1 month to 48 months. It is calculated based on precipitation estimates from the satellite-based Climate Hazards group InfraRed Precipitation with Station data (CHIRPS) and potential evaporation estimates by the Global Land Evaporation Amsterdam Model (GLEAM). The SPEI dataset covers the whole of the African continent for a 36-year-long period (1981–2016) at a horizontal resolution of 5 km (0.05 deg) and a monthly time resolution. The dataset is provided in NetCDF format with in a Geographic Lat/Lon projection. Due to the lower reliability of SPEI over areas with low hydro-climatic variability, the areas with barren or sparsely vegetated areas in Africa were masked out based on data from the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface type product (MCD12Q1).

This dataset contains maternal reproductive output data, embryonic development data and offspring performance data for the Speckled Wood butterfly, Pararge aegeria. The data were collected from a laboratory experiment testing the hypothesis that repeat periods of intensive flight during female oviposition affects egg provisioning and reduces offspring performance when larval development occurs on drought stressed host plants. The experiment involved stimulating female butterflies to fly for 5 minutes for 3 periods during oviposition; removing eggs from 5 different days during oviposition to be monitored for hatching; and removing a larva on day of hatching to be reared on a drought stressed host plant. For each larva, development time from hatching to pupation, pupal mass and survival to eclose as an adult was recorded. On eclosion, each offspring adult was sexed and the thorax weighed. The overall aim of this experimental work was to explore one of the potential mechanisms for the impact of drought and habitat fragmentation on biodiversity. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/82233733-237a-4fea-a5c1-88c734752279

Standardised Precipitation Evapotranspiration Index (SPEI) data for Integrated Hydrological Units (IHU) Hydrometric Areas (Kral et al. [1]). SPEI is a drought index based on the probability of occurrence of the Climatic Water Balance (CWB) - which is equivalent to the amount of precipitation minus the amount of evapotranspiration - for a given accumulation period as defined by Vicente-Serrano et al. [2]. SPEI 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 1961 to 2012. [1] Kral, F., Fry, M., Dixon, H. (2015). Integrated Hydrological Units of the United Kingdom: Hydrometric Areas without Coastline. NERC-Environmental Information Data Centre https://doi.org/10.5285/3a4e94fc-4c68-47eb-a217-adee2a6b02b3 [2] Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010) A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Climate, 23, 1696-1718. https://doi.org/10.1175/2009JCLI2909.1 Full details about this dataset can be found at https://doi.org/10.5285/19c230b2-415b-456a-9e93-7b00b730a465

Standardised Precipitation Evapotranspiration Index (SPEI) data for Integrated Hydrological Units (IHU) groups (Kral et al. [1]). SPEI is a drought index based on the probability of occurrence of the Climatic Water Balance (CWB) - which is equivalent to the amount of precipitation minus the amount of evapotranspiration - for a given accumulation period as defined by Vicente-Serrano et al. [2]. SPEI 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 general logistic distribution is 1961-2010. The dataset covers the period from 1961 to 2012. [1] Kral, F., Fry, M., Dixon, H. (2015). Integrated Hydrological Units of the United Kingdom: Groups. NERC-Environmental Information Data Centre https://doi.org/10.5285/f1cd5e33-2633-4304-bbc2-b8d34711d902 [2] Vicente-Serrano, S. M., Beguería, S., López-Moreno, J. I. (2010) A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Climate, 23, 1696 to 1718. https://doi.org/10.1175/2009JCLI2909.1 Full details about this dataset can be found at https://doi.org/10.5285/9b550cc5-4cba-45fb-ab92-8408454fa1d4

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 1961 to 2012. [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. Full details about this dataset can be found at https://doi.org/10.5285/dfd59438-2170-4472-b810-bab33a83d09f

The data comprise of four datasets for Spring wheat (Triticum aestivum L., cv. Mulika) from a season-long ozone exposure experiment in mesocosms: i) Yield and biomass data (including harvest index and individual grain weight) gathered at the end of the experiment; ii) measurements of chlorophyll content index (CCI) measured ad-hoc using a Soil-Plant Analyses Development (SPAD) chlorophyll meter throughout the experiment across all treatments; iii) measurements of leaf stomatal conductance, measured ad-hoc using a porometer throughout the experiment across all treatments; iv) results from four growth stage assessments conducted at different stages of the experiment. Yield and Biomass data are dry weights of non-edge plants, with a cutting height of 5cm above soil level. Leaf chlorophyll and stomatal conductance data were measured on the most recently fully expanded leaf (flag leaf from 28th May 2015 onwards) of randomly selected non-edge plants. The data are from an ozone and drought exposure experiment conducted during April-August 2015 at the Centre for Ecology & Hydrology Bangor solardome facility near Abergwyngregyn (Latitude 53.2387, Longitude -4.0176). The objective of the experiment was to determine how two abiotic stressors in combination - ozone and drought - would interact to influence growth and yield of wheat, and also what impact the timing of drought would have on the result. Spring wheat (Triticum aestivum L., cv. Mulika) was grown in rows within large 25-litre pots, and exposed to eight ozone treatments for 82 days. Plants experienced either (i) a well-watered regime (ii) a 10-day early-season drought event or (iii) a 10-day late-season drought event. The eight Ozone (O3) treatments ranged from a 24-hour mean of 27 parts per billion (ppb) in the lowest treatment to 57 ppb in the highest, with daily peaks ranging from 32 to 115 ppb This work was carried out as part of a Ph.D. funded by the Natural Environment Research Council (NERC) (NERC Reference NEC05014/3328/988) Full details about this dataset can be found at https://doi.org/10.5285/9678f446-0e2f-4f9c-860a-cbedfce4c7ec

This data set includes longitudinal abundance of dung beetles at dung-baited pitfall traps, recorded in 2010, 2016 and 2017 (around six years before, six months after and 18 months after the 2015-16 El Niño event, respectively) in the Brazilian Amazon region. Dung beetles were collected during the collaborative projects AFIRE (Assessing ENSO-induced Fire Impacts in tropical Rainforest Ecosystems) and ECOFOR (Biodiversity and Ecosystem Functioning in degraded and recovering Amazonian and Atlantic Forests), which are part of the NERC Human-Modified Tropical Forest (HTMF) programme. Full details about this dataset can be found at https://doi.org/10.5285/799db965-3ce7-4e9b-8590-de6a8624d652