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This dataset is derived from modelled changes to the distributions of >12,700 terrestrial mammal and bird species under four different climate scenarios, projected to 2070. It contains national-level projections of species richness change under each climate scenario, based on species' modelled climatic niches, as well as projected range shifts in relation to political borders globally. Full details about this dataset can be found at https://doi.org/10.5285/5bf972a8-c9a3-4721-8089-552dfe3ff124
[This dataset is embargoed until June 1, 2023]. This dataset consists of a single orthophoto mosaic image of Irontongue Hill on Swineshaw Moor. The area of interest includes seven erosion plots (approximately 5 x 5 m) which were set up on 26/07/2018 to capture the state of the burnt moorland surface and monitor subsequent erosion and vegetation recovery. The area of interest is approximately 0.45 km2. Full details about this dataset can be found at https://doi.org/10.5285/aff5210d-27e9-4655-badb-4d16c3adeb17
Dataset contains Terrestrial laser scanner (TLS) and CT scan data collected during fieldwork on a small gravel-bed river. TLS data show the river bed surface topography collected at five intervals between September 2014 and October 2018. CT scan data show the 3D structure of sections of the river bed. CT data has been processed to segment the images into gravel grains and fine-grained matrix. Full details about this dataset can be found at https://doi.org/10.5285/b30b4d56-f0a9-43e8-aacc-09d9b5b1f9fc
The dataset contains parameter values that maximize revised Kling Gupta Efficiency (KGE’) between modelled and observed daily mean river flows when running one of 24 different hydrological models with one of 21 different climatic input datasets in one of 33 different catchments across the Citarum basin or 5 catchments across the Ciliwung basin, both in Java island, Indonesia. This dataset was created as part of a study on the advantages and disadvantages of using existing hydrological models, primarily developed for temperate and cold climates, in a tropical volcanic region. The hydrological models were based on those created for MARRMoT v1.2 (10.5194/gmd-12-2463-2019), recoded as sequential models in the R programming language. This work was supported by the Natural Environment Research Council (Grants NE/S00310X/1 and NE/S002790/1). Full details about this dataset can be found at https://doi.org/10.5285/f6cec7d4-edee-44b8-8f44-86d4f12ac72d
Terrestrial laser scanner (TLS) and CT scan data collected during flume experiments on a gravel bed. TLS data show the bed surface topography before and after waterworking of the bed. CT scan data show the 3D structure of sections of the river bed after waterworking. Some CT data has been processed to segment the images into the individual gravel grains, and for some of these data a database of grain properties is also available. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/6749d033-cdf4-479b-ba85-015c3dbb476a
The spectacular botanical preservation and long occupation of Qasr Ibrim, Egypt make this site archaeobotanically matchless. 600 samples have been collected over 20 years covering a timespan of c. 1000 BC - AD 1800. The project has particularly focussed on the period AD 100-400 during which several new summer crops including sorghum, cotton, lablab and sesame first appear. These new crops are thought to be associated with the introduction of new irrigation technology, specifically a device known as the saqia, an ox-driven water wheel from which descends a conveyor belt to which pots are attached. It has never before been possible to examine this crucial change archaeologically and this project has allowed the investigation of when and how this great change happened. This has major implications for the history of agriculture in Africa and the Indian Ocean.
The dataset consists of the world's longest fluvial dissolved organic carbon (DOC) record (1883-2014). The data have been measured at the outlet of the Thames basin, upstream of London (UK) and are reported monthly. The River Thames basin is a temperate, lowland, mineral soil-dominated catchment of 9,948 km2. Water colour data have been measured between 1883 and 1990, and DOC between 1990 and 2014. DOC until 1990 has been estimated through calibration between water colour and DOC for the period 1899-1905 when OC measurements were available. The fluvial DOC concentration shows an upward trend throughout the period. The data are presented as one table and one supporting file containing metadata and are summarised and presented in the Journal of Geophysical Research - Biogeosciences doi: 10.1002/2016JG003614. Full details about this dataset can be found at https://doi.org/10.5285/57943561-4587-4eb6-b14c-7adb90dc1dc8
This dataset consists of an ecology-focused survey of stillwaters along the rivers Yure and Swale and sediment flux measurements recorded at sites along the river Esk. The dataset results from a study which was part of the Rural Economy and Land Use (RELU) programme. The project analysed the complex network of natural and socio-economic relationships around angling in the river environment, including institutions of governance and land use practices at a range of interconnected scales. The sustainability, integrity and ecological value of river catchments are currently major issues for science. The management of freshwaters and their ecologies requires addressing processes that work across the boundaries between the natural environment, economy and society. This research focused upon these cross-cutting processes in an interdisciplinary, holistic assessment of river environments through the case of angling. Angling benefits from and influences river quality, design and management. It also links urban and rural environments and is an economic driver for the rural economy, involving about 4 million people in England and Wales and contributing 6 billion pounds to the economy through freshwater angling alone. This research aimed to provide insights into how environmental and socio-economic drivers for rural change work. This project therefore aimed to identify and analyse the complex network of influences and feedbacks around angling in the rural environment. These include natural and socio-economic influences, interdisciplinary research from both natural and social science disciplines (aquatic ecology, geomorphology, anthropology, sociology, human geography), as well as stakeholders from government, NGOs and the local community. This project focused upon three rivers in northern England - the Esk, Ure and Swale - in the course of an integrated and fine-grained study. The postal survey and business interviews from this study are available at the UK Data Archive under study number 6580 (see online resources). Further 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 consists of computer code transcripts for two proprietary flood risk models from a study as part of the NERC Rural Economy and Land Use (RELU) programme. This project was conceived in order to address the public controversies generated by the risk management strategies and forecasting technologies associated with diffuse environmental problems such as flooding and pollution. Environmental issues play an ever-increasing role in all of our daily lives. However, controversies surrounding many of these issues, and confusion surrounding the way in which they are reported, mean that sectors of the public risk becoming increasingly disengaged. To try to reverse this trend and regain public trust and engagement, this project aimed to develop a new approach to interdisciplinary environmental science, involving non-scientists throughout the process. Examining the relationship between science and policy, and in particular how to engage the public with scientific research findings, a major diffuse environmental management issue was chosen as a focus - flooding. As part of this approach, non-scientists were recruited alongside the investigators in forming Competency Groups - an experiment in democratising science. The Competency Groups were composed of researchers and laypeople for whom flooding is a matter of particular concern. The groups worked together to share different perspectives - on why flooding is a problem, on the role of science in addressing the problem, and on new ways of doing science together. We aimed to achieve four substantive contributions to knowledge: 1. To analyse how the knowledge claims and modelling technologies of hydrological science are developed and put into practice by policy makers and commercial organisations (such as insurance companies) in flood risk management. 2. To develop an integrated model for forecasting the in-river and floodplain effects of rural land management practices. 3. To experiment with a new approach to public engagement in the production of interdisciplinary environmental science, involving the use of Competency Groups. 4. To evaluate this new approach to doing public science differently and to identify lessons learnt that can be exported beyond this particular project to other fields of knowledge controversy. This dataset consists of computer code transcripts for two proprietary flood risk models. Flood risk and modelling interview transcripts from this study are available at the UK Data Archive under study number 6620 (see online resources). Further 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 is a spatial dataset containing polygons representing different geology types in the Moor House National Nature Reserve, northern Pennines, England. The survey was undertaken by G.A.L. Johnson under a grant by The Nature Conservancy in the 1950s and 1960s. Full details about this dataset can be found at https://doi.org/10.5285/0e3aefb2-ce86-4d09-8ff0-6d165dfd48db