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1 urn:ogc:def:uom:EPSG::9001

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  • The data comprise outcomes from questionnaire surveys conducted with greenspace users on their perceptions of experimentally manipulated urban meadows (varying levels of diversity and vegetation height of sown wildflower meadows), and associated socio-economic data of respondents to the questionnaire surveys. The experimental meadows were located in Bedford and Luton. Data was collected by the data authors, and participants gave informed consent before completing the questionnaires. The work was initially completed under the Fragments, functions and flows NERC BESS project in 2014. The scaling of biodiversity and ecosystem services in urban ecosystems was funded by grant NE/J015369/1 from the Biodiversity and Ecosystem Service Sustainability (BESS) programme. Subsequent analysis was carried out under the NERC grant ‘Location, Configuration, Distribution: the Role of Landscape Pattern and Diversity in Ecosystem Services’ (NE/K015508/1). Full details about this dataset can be found at https://doi.org/10.5285/29d6345f-9f53-4894-8f60-80843f49c017

  • These data consist of relative telomere length (RTL) measures from quantitative polymerase chain reaction, of Seychelles warbler birds on Cousin Island, Seychelles. The data were collected by the Seychelles Warbler Project in 1995-2014. Data include bird identity, sex, age, birth period, qPCR plate identity, RTL, technician, territory, field period, mum ID, dad ID, mum age at conception, dad age at conception, dominant female ID in the natal territory, dominant male ID in the natal territory Full details about this dataset can be found at https://doi.org/10.5285/8a8240a2-e8ed-495d-ae93-c35200956764

  • [This dataset is embargoed until September 15, 2022]. Data presented here include imagery with ground-sampling distances of 3 cm and 7 cm for March 2019, May 2019 and July 2019. Also included are the corresponding ground-truth training and verification data presented as shapefiles, as well as the classification output and other data relevant to the project such as the width of floral units. The imagery was acquired by Spectrum Aviation using A6D-100c (50mm) Hasselblad cameras with bayer filters, mounted on a Sky Arrow 650 manned aircraft. Ground-truth data for training maximum likelihood classifications and for verifying the accuracy of classifications were gathered within eight days of imagery acquisition. Ground-truth data were acquired from sown field margins and hedgerow surrounding one study field. This dataset was acquired from March to July 2019 at a farm in Northamptonshire, UK. Data were acquired as part of a NERC funded iCASE PhD studentship (NERC grant NE/N014472/1) based at the University of East Anglia and in collaboration with Hutchinsons Ltd. The aim of the research was to map the floral units of five nectar-rich flowering plant species using very high resolution multispectral imagery. Each species constitutes an important food resource for pollinators. The plant species in question were Prunus spinosa, Crataegus monogyna, Silene dioica, Centaurea nigra and Rubus fruticosus. Full details about this dataset can be found at https://doi.org/10.5285/cf68be0c-e969-4190-8ec6-abeedb51b42c

  • [This dataset is embargoed until February 22, 2022]. Half-hourly data from eight eddy covariance towers deployed in the Sevilleta Refuge (New Mexico, USA). The main sensors deployed were sonic anemometer, relative humidity sensor and carbon dioxide concentration sensor . They were deployed and maintained by Fabio Boschetti and Andrew Cunliffe (University of Exeter). The data were collected to test the new design of eddy covariance towers and investigate the spatial variability of fluxes. Data were collected from 2018-11-01 to 2019-11-01. The data contains very few small gaps due to maintenance. Half-hourly data were gap-filled using code published on GitHub. The research was funded through NERC grant reference NE/R00062X/1 - "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/e96466c3-5b67-41b0-9252-8f8f393807d7

  • This dataset contains calculated return rates for five seabird species from representative colonies on the Isle of May, off the East coast of Scotland. Annual return rates are measured as the number of individually colour marked individuals seen in any one year that were also observed in the previous year for the Atlantic puffin (Fratercula arctica), common guillemot (Uria aalge), razorbill (Alca torda), European shag (Phalacrocorax aristotelis) and black-legged kittiwake (Rissa tridactyla). Not every individual is seen in any one year and the data set does not take into account those missed in any previous years hence these data are not to be treated as survival estimates. The Isle of May long-term study (IMLOTS) aims to identify the impact of environmental change on seabirds and their associated ecosystems. Understanding the mechanisms underlying variation in seabird population size requires a thorough knowledge of demographic parameters, namely birth rates, death rates, immigration and emigration. The effects of environmental change are likely to be different according to which demographic parameter or life history stage is being considered. This complexity means that only long-term monitoring, such as that carried out on the Isle of May, will allow us to understand the functioning of bird populations and their responses to environmental change. Full details about this dataset can be found at https://doi.org/10.5285/53251b3c-6c79-4aeb-a0de-fc63b9350cc1

  • This dataset is a model output from the JULES land surface model driven with the Watch Forcing Data methodology applied to Era-Interim (WFDEI) data. It provides monthly global methane emissions from natural wetlands on 0.5 x 0.5 degree grid between 1980-2014. It includes the following variables: - fch4_wetl: modelled methane flux from natural wetland, in mg CH4 m-2 day-1 - fwetl: fraction of wetland - cs: soil carbon in each of these four soil carbon pools: decomposable plant material, resistant plant material, microbial biomass and humus), in kg m-2 - t_soil: sub-surface temperature of the four modelled soil layers (0-0.1 m, 0.1-0.35 m, 0.35-1.0 m and 1.0-2.0 m), in K Full details about this dataset can be found at https://doi.org/10.5285/6ce61e91-6912-4fe2-a095-12136af86347

  • The semiochemical experiment data were collected from novel laboratory, semi-field- and field-scale bioassay experiments taking behavioural observations and counts of pest insects and their natural enemies in the field. Crop yields were taken. Chemical analyses were also done using air entrainment. The study is part of the NERC Rural Economy and Land Use (RELU) programme. Despite the widespread concerns regarding the use of pesticides in food production and the availability of potentially viable biological pest control strategies in Integrated Pest Management (IPM) systems, the UK cereal crop production remains a bastion of pesticide use. This project aimed to understand further the reasons for this lack of adoption, using the control of summer cereal aphids as a case study. Reasons for this lack of adoption of biocontrol remain a complex interplay of both technical and economic problems. Economists highlight the potential path dependency of an industry to continue to employ a suboptimal technology, caused by past dynamics of adoption resulting in differential private cost structures of each technique. Further, risk aversion on the part of farmers regarding the perceived efficacy of a new technology may also limit up-take. This may be particularly important when IPM rests on portfolios of technologies and when little scientific understanding exists on the effect of portfolio and scale of adoption on overall efficacy. Faced with this, farmers will not adopt a socially superior IPM technology and there exists a clear need for public policy action. This action may take the form of minimising uncertainty through carefully designed research programs, government funding and dissemination of the results of large-scale research studies or direct public support for farm landscape and farm system changes that can promote biocontrol. This research looked at alternatives to the use of insecticides in arable agriculture and the difficulties facing producers in switching over to them. Two approaches were explored: habitat manipulations, to encourage predators and parasites, and using naturally occurring odours to manipulate predator distribution as model technologies. Scale and portfolio effects on biocontrol efficacy have been investigated in controlled and field scale experiments. Aim is to improve the way research and development of new products and techniques are carried out to help break the dependence on chemical pesticides. Conservation biological control experiments data investigating the effect of wild field margins on pests and predators, from this same research project, are also available. In addition, socio-economic research has been used to help direct natural science research into the development and evaluation of a combination of habitat management and semiochemical push-pull strategies of appropriate scale and complementarity to yield viable, commercially attractive and sustainable alternatives to the use of insecticides in cereal crop agriculture. These socio-economic data are available through the UK Data Archive under study number 6960 (see online resources). Further information and documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).

  • This dataset contains pollinator abundance data from 13 calcareous grassland, 13 heathland and 12 woodland sites within Dorset, UK. The sites were selected to represent a range of habitat types across a condition gradient as measured by levels of degradation from the original habitat. The original habitats were identified as being calcareous grassland, heathland or woodland from a survey conducted in the 1930s. Butterflies, bees, hoverflies, flies and beetles were recorded to species level and the plant species insects were foraging on was also recorded. Data were collected on three different dates in 2017 and 2018: calcareous grassland in June, July and August; heathland transects in May, August and September; and woodland transects in May, June and July. Full details about this dataset can be found at https://doi.org/10.5285/190b7ef8-1997-4424-a087-882cd7673e23

  • This dataset contains calculated breeding success rates for six seabird species from representative colonies on the Isle of May, off the East coast of Scotland. Annual breeding success has been measured as the number of chicks fledged per active nest for the Atlantic puffin (Fratercula arctica, since 1982), common guillemot (Uria aalge, since 1982), razorbill (Alca torda, since 1982), European shag (Phalacrocorax aristotelis, since 1987), black-legged kittiwake (Rissa tridactyla, since 1987) and northern fulmar (Fulmarus glacialis, since 1987). The number of active nests recorded are also provided. Data were collected as part of the Isle of May long-term study (IMLOTS), which aims to identify the impact of environmental change on seabirds and their associated ecosystems. This monitoring has been ongoing since 1974, by essentially the same team of scientists, using the same well-documented methods throughout this time. Full details about this dataset can be found at https://doi.org/10.5285/02c98a4f-8e20-4c48-8167-1cd5044c4afe

  • Land use/land cover (LULC) map of a 20km2 agricultural landscape centred on the Hillesden Estate, Buckinghamshire, UK. The map is based on remote sensed data (LiDAR and hyperspectral sensors) with manual updates and the addition of spring and summer floral cover data from comprehensive field surveys. The remote sensed data was generated in August 2007. The manual updates and summer floral data were from field visits in July and August 2011, and the spring floral data were from field visits in April 2011 and 2012. The map was created as part of a project led by the Centre for Ecology & Hydrology, funded under the Insect Pollinators Initiative. Full details about this dataset can be found at https://doi.org/10.5285/0667cf06-f2c3-45c1-a80a-e48539b52427