These data are derived from a dust leaching experiment, an in-lake mesocosm experiment and from sediment cores obtained from lakes in the Kangerlussuaq area of West Greenland. The dust leaching experiment was set up in 2017 and the data show which elements and ions were leached from dust into different types of waters. The in-lake mesocosm experiment applied dust over a two week period in July 2018 resulting in chemical and algal pigment data. Data on chlorophyll and carotenoid pigments are presented from sediment cores sampled from six lakes 2017 and sectioned into 0.5-1cm intervals. Full details about this dataset can be found at https://doi.org/10.5285/9115bc7a-adb6-4a3c-8506-32d0b39bcf6f

This dataset contains the Lakes Essential Climate Variable, which is comprised of processed satellite observations at the global scale, over the period 1992-2020, for over 2000 inland water bodies. This dataset was produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project. For more information about the Lakes_cci please visit the project website. This is version 2.0 of the dataset. The five thematic climate variables included in this dataset are: • Lake Water Level (LWL), derived from satellite altimetry, is fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate change. • Lake Water Extent (LWE), modelled from the relation between LWL and high-resolution spatial extent observed at set time-points, describes the areal extent of the water body. This allows the observation of drought in arid environments, expansion in high Asia, or impact of large-scale atmospheric oscillations on lakes in tropical regions for example. . • Lake Surface Water temperature (LSWT), derived from optical and thermal satellite observations, is correlated with regional air temperatures and is informative about vertical mixing regimes, driving biogeochemical cycling and seasonality. • Lake Ice Cover (LIC), determined from optical observations, describes the freeze-up in autumn and break-up of ice in spring, which are proxies for gradually changing climate patterns and seasonality. • Lake Water-Leaving Reflectance (LWLR), derived from optical satellite observations, is a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions). Data generated in the Lakes_cci are derived from multiple satellite sensors including: TOPEX/Poseidon, Jason, ENVISAT, SARAL, Sentinel 2-3, Landsat OLI, ERS, MODIS Terra/Aqua and Metop. Detailed information about the generation and validation of this dataset is available from the Lakes_cci documentation available on the project website.

A geographic database of lakes on the Antarctic Peninsula compiled over the past five years from a number of information sources: satellite images, aerial photography, old maps and reports. The database fields include: Lake unique id; Name; location; imager reference/how identified; locality; size (longest axis); area; type (as per Hutchinson''s lake classification); reference - any existing scientific work on the lake; salinity; depth; x co-ordinate; y co-ordinate. Many of the lakes are previously unknown, and very few have been studied before. The list represents the first attempt to collate all the lakes in the area into one usable dataset. The data is available as a down-loadable text file with point co-ordinates, or as a polygon coverage downloadable from the Antarctic Digital database.

This dataset consists of phyto- and zooplankton counts, chlorophyll concentration and fish catch data from the Cumbrian Lakes (Blelham Tarn, Esthwaite Water, Windermere north and south basins). The data span the years 1940 to 2013 but time series vary in length among different species and sites, and fish data are only available from Windermere. The original data were initially collected by the Freshwater Biological Association (FBA) but have been collected by CEH and its predecessor Institute of Freshwater Ecology (IFE) since 1989. Full details about this dataset can be found at https://doi.org/10.5285/1de49dab-c36e-4700-8b15-93a639ae4d55

Datasets from the Resolving subglacial properties, hydrological networks and dynamic evolution of ice flow on the Greenland Ice Sheet (RESPONDER) project as published in the paper by Chudley et al. entitled "Supraglacial lake drainage at a fast-flowing Greenlandic outlet glacier". Please cite this paper if using this data. This dataset consists of observations of the rapid drainage of a supraglacial lake on Store Glacier, a marine-terminating outlet glacier of the west Greenland Ice Sheet. ''Lake 028'', located 70.57degN, 50.08degW, drained on 2018-07-07 and was recorded using a variety of geophysical instrumentation. The dataset presented here includes all data necessary to replicate the findings presented in the main paper, including UAV photogrammetry-derived raster data (producing a series of orthophotos, digital elevation models, and velocity fields) and time-series records from in-situ geophysical instrumentation (GPS receiver, geophone, and water pressure sensor). Funding was provided by NERC DTP grant NE/L002507/1 and ERC Horizon 2020 grant 683043.

The long term monitoring of water chemistry in Signy Island lakes is unique in polar limnology, in its duration (30+ years), detail, and range of sites. It details seasonal patterns of snow and ice cover, inorganic nutrient status and chlorophyll-a and includes vertical profiles of various physical chemical parameters. There are detailed data for several study lakes and twice/thrice yearly analyses for all the Signy Island lakes. Temperature and light climate has been studied in certain lakes using automatic data loggers. Micrometeorological monitoring with additional data loggers provided data on solar radiation (PAR, UVR), air temperature, humidity and wind conditions. Data are collected by chemical analysis, use of temperature, pH light probes and observation. The ''grand prix'' was the sampling of 16 lakes in a short period (approx. one week), this was carried out perhaps two or three times a year. Approximately three to five lakes were sampled monthly or fortnightly in more detail, these were representative of the 16 lakes. Comparative studies were also undertaken in the Arctic. The long-term programme was established in 1971, although some observations were made in 1963/1964 and 1969/1970. The programme finished in 2004. As the exact months of the data collection were not provided, and the metadata standard requires a YYYY-MM-DD format, this dataset has been dated as 1st January for start date, and 31st December for stop date.

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 contains various global lake products (1992-2019) produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project. Lakes are of significant interest to the scientific community, local to national governments, industries and the wider public. A range of scientific disciplines including hydrology, limnology, climatology, biogeochemistry and geodesy are interested in distribution and functioning of the millions of lakes (from small ponds to inland seas), from the local to the global scale. Remote sensing provides an opportunity to extend the spatio-temporal scale of lake observation. The five thematic climate variables included in this dataset are: • Lake Water Level (LWL): a proxy fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate changes. • Lake Water Extent (LWE): a proxy for change in glacial regions (lake expansion) and drought in many arid environments, water extent relates to local climate for the cooling effect that water bodies provide. • Lake Surface Water temperature (LSWT): correlated with regional air temperatures and a proxy for mixing regimes, driving biogeochemical cycling and seasonality. • Lake Ice Cover (LIC): freeze-up in autumn and advancing break-up in spring are proxies for gradually changing climate patterns and seasonality. • Lake Water-Leaving Reflectance (LWLR): a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions). Data generated in the Lakes_cci project are derived from data from multiple instruments and multiple satellites including; TOPEX/Poseidon, Jason, ENVISAT, SARAL, Sentinel, Landsat, ERS, Terra/Aqua, Suomi NPP, Metop and Orbview. For more information please see the product user guide in the documents.

This dataset contains various global lake products (1992-2019) produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project. This is version 1.1 of the dataset. Lakes are of significant interest to the scientific community, local to national governments, industries and the wider public. A range of scientific disciplines including hydrology, limnology, climatology, biogeochemistry and geodesy are interested in distribution and functioning of the millions of lakes (from small ponds to inland seas), from the local to the global scale. Remote sensing provides an opportunity to extend the spatio-temporal scale of lake observation. The five thematic climate variables included in this dataset are: • Lake Water Level (LWL): a proxy fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate changes. • Lake Water Extent (LWE): a proxy for change in glacial regions (lake expansion) and drought in many arid environments, water extent relates to local climate for the cooling effect that water bodies provide. • Lake Surface Water temperature (LSWT): correlated with regional air temperatures and a proxy for mixing regimes, driving biogeochemical cycling and seasonality. • Lake Ice Cover (LIC): freeze-up in autumn and advancing break-up in spring are proxies for gradually changing climate patterns and seasonality. • Lake Water-Leaving Reflectance (LWLR): a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions). Data generated in the Lakes_cci project are derived from data from multiple instruments and multiple satellites including; TOPEX/Poseidon, Jason, ENVISAT, SARAL, Sentinel, Landsat, ERS, Terra/Aqua, Suomi NPP, Metop and Orbview. For more information please see the product user guide in the documents.