From 1 - 4 / 4
  • This dataset includes the PROTECH validation output against a yearlong monitoring study conducted during 2016 in the lake and catchment of Rostherne Mere and the PROTECH output files following changes in internal and external nutrient loads and future climate scenarios based on the UK Climate Projections (UKCP09) data. These data were collected to demonstrate the future possible trajectories of change with alterations in air temperature, internal nutrient loads and external nutrient loads. Validation data is presented as daily model outputs, while all future projection data is presented as collated annual average model output data for each future change scenario. The PROTECH model (Phytoplankton RespOnses To Environmental CHange) simulates the in situ dynamics of phytoplankton in lakes and reservoirs, specialising in predicting phytoplankton species, particularly Cyanobacteria (blue-green algae) The work was carried out as part of a Natural Environment Research Council (NERC) funded PhD [grant number NE/L002493/1]. Full details about this dataset can be found at https://doi.org/10.5285/2f0eae1c-1512-4823-9cbe-cb54f05ee996

  • This dataset includes catchment stream inflow and outflow rates, secchi depth, chlorophyll, phytoplankton counts and nutrient concentrations for the lake, inflow, outflow and groundwater spring. The measurements are from a PhD research project at Rostherne Mere in Cheshire. These data were collected to show the relationship between the catchment hydrology and in-lake nutrient loads for assessment of the current catchment nutrient budget. The monitoring study covered a period from January 2016 to January 2017. All data is presented with date, flow rate, nutrient and chlorophyll concentrations and phytoplankton species abundance. The work was carried out as part of a Natural Environment Research Council (NERC) funded PhD [grant number NE/L002493/1]. Full details about this dataset can be found at https://doi.org/10.5285/5c6b2bcb-6b10-4c57-a595-ce94a655e709

  • This dataset includes sediment trap, sediment core and loss-on-ignition to total organic carbon measurements from a PhD research project at Rostherne Mere in Cheshire. These data were collected to show the relationship between the changing nutrient loads and subsequent organic carbon burial over the last 120 years. The sediment trap data cover the period from May 2010 to August 2016, while the sediment core was taken in September 2011 and has been 210Pb dated to circa 1360AD. All data is presented for date, loss-on-ignition (LOI) and calcium carbonate (CaCO3), with sediment trap data converted into net flux measurements and sediment core data calculated for net sedimentation rate following 210Pb dating. The conversion from LOI to total organic carbon was measured using mass spectrometry and applied to the trap and core data. The work was carried out as part of a Natural Environment Research Council (NERC) funded PhD [grant number NE/L002493/1], with part of the work also funded by the NERC small grant [grant number NE/H011978/1]. Full details about this dataset can be found at https://doi.org/10.5285/8616c1a0-6c6d-441c-9b10-8464dc4ee346

  • This dataset includes sediment trap diatom captures and water column temperature profiles from a PhD research project at Rostherne Mere in Cheshire. These data were collected to show the relationship between climate, especially short-term climatic perturbations, and diatom assemblages. The sediment trap data cover the period from October 2004 to January 2017, while the thermal profiles cover October 2005 to December 2016. Diatom data is presented with date, percentage taxa abundance and diatom fluxes based on total sediment yield. Temperature profiles are presented as mean daily figures. The work was carried out as part of a Natural Environment Research Council (NERC) funded PhD [grant number NE/L002493/1], with the temperature data funded by the UKLEON (UK Lake Ecological Observatory Network) project via a NERC small grant [grant number NE/I007261/1]. Full details about this dataset can be found at https://doi.org/10.5285/16f52064-a19d-4cf5-a388-aff04a592179