Type of resources
Contact for the resource
The QUEST-GSI WP-I5 "Aquatic Ecosystems" project provided an analysis of global fisheries vulnerability across a range of global climate models, emissions scenarios, fixed degree scenarios and alternative impact metrics. This dataset contains model output data from the emission, fixed degree, Cheung potential analysis, Allison socio-economic comparison and freshwater run-off analysis scenarios. -Emission Scenarios- These results are from the analysis using the SRES emissions scenarios from the IPCC AR4 - A1b, A2, B1 and B2. -Fixed Degree- This analysis was driven by the fixed degree rise scenarios, corresponding to a fixed increase in global temperature by 2050. These are 1 to 4 degrees C, in half degree increments, with each fishery impact equally weighted across freshwater, EEZ and High Seas (see report). They are also carried out for a variety of GCMs and socio-economic scenarios. -Cheung Potential Catch Analysis- These results were generated for marine fisheries using an alternative metric to temperature change in calculating potential impact- that of predicted change in potential catch from the study carried out by W.W.L. Cheung et al. (2009 Large-scale redistribution of maximum fisheries catch potential in the global ocean under climate change. Global Change Biology 16, 24-35). This was carried out for the A1b SRES scenario using the GFDL CM2.1 global climate model. -Allison Socio-economic comparison- A comparison study using the adaptive capacity metric developed in Allison et al. (2009 Vulnerability of national economies to the impacts of climate change on fisheries. Fish and Fisheries 10, 173–196). This was undertaken for the A1b Emission Scenario using HadCM3. -Freshwater Runoff Analysis- Using predicted changes in freshwater availability from the outputs of QUEST-GSI WP-I1 global water resources project, an alternative analysis for freshwater fisheries vulnerability was carried out. This was under the 2 degrees fixed increase scenario using HadCM3.
QUEST GSI was led by Nigel Arnell (University of Reading) with co-investigators from the Universities of Aberdeen, Leeds, UEA, Edinburgh, Southampton, UCL, London School of Hygiene and Tropical Medicine, CEH and CEFAS. This dataset collection contains model data simulations under various climate, run-off and aquatic scenarios. A central aim of this project was to assess the global-scale impacts of climate change under a range of scenarios, across a number of sectors. A methodology was developed to construct scenarios from a range of climate models, representing changes under different emissions scenarios and fixed amounts of change in global mean temperature. Impacts were estimated across a range of sectors, including water resources, fluvial and coastal flooding, crop productivity and food security, ecosystem productivity and human health, at regional and global scales. The project has provided quantitative information on these impacts and their distribution across the world. The general conclusions are that impacts may be significant at relatively low levels of climate change, that estimates of impact in some sectors are very uncertain due largely to uncertainty in projected changes in rainfall (particularly in south Asia), that there are no obvious thresholds for step changes in impact that are consistent across region and sector, and that socio-economic conditions may amplify or reduce impacts, depending on context. A second project aim was to develop the methodology in such a way that it could be readily applied to estimate impacts under other climate scenarios representing for example specific policy objectives. With additional funding from other sources, the project methodology has been applied successfully to estimate the impacts avoided by a set of feasible emissions policies.
This dataset represent hydrological statistics calculated over a 30‐year period, at a spatial resolution (over land) of 0.5x0.5o across the global domain. The simulations were made using the global hydrological model Mac‐PDM.09. The data files represent runoff simulated with the baseline (1961‐1990) climate, together with runoff simulated by climate change scenarios derived from CMIP3 global climate model output (i) based on specific IPCC SRES emissions scenarios (“SRES”) and (ii) scaled to represent prescribed changes in global mean temperature (“PRESC”), and from CMIP5 global climate model output based on RCP scenarios. The simulations were run at the University of Reading between 2009 and 2013. See Gosling & Arnell (2011)mfor a description and validation of Mac‐PDM.09, and Arnell & Gosling (2013) for details of the CMIP3 climate change scenarios and their application to the simulation of river runoff. Arnell & Lloyd‐Hughes (2013) describe the application of the model with CMIP5 scenarios.
This dataset contains concentrations of dissolved organic carbon, inorganic carbon, CO2, CH4 and N2O in the Black Burn stream which drains Auchencorth Moss peatland in South East Scotland. Concentrations and fluxes have been measured within the Black Burn on an approximately weekly to fortnightly basis from approximately 2006 to present (see https://doi.org/10.5285/3f0820a7-a8c8-4dd7-a058-8db79ba9c7fe). Concentrations in this dataset are from a series of new sites, upstream of the long-term sampling record, adjacent to an area of drains blocked by Scottish Natural Heritage. Measurements began during the drain blocking. Data was collected initially as part of a masters project for University of Edinburgh through Scotland's Rural College and continued by the Centre for Ecology & Hydrology. Full details about this dataset can be found at https://doi.org/10.5285/88ffbf44-0ec0-41d6-9814-04bc3535cd84
Dataset contains concentrations of particulate and dissolved organic carbon, inorganic carbon, CO2, CH4 and N2O in the Black Burn stream which drains Auchencorth Moss peatland in South East Scotland. Auchencorth Moss is part of the UK Centre for Ecology & Hydrology's UK Carbon Catchment project. Concentrations have been measured approximately weekly from January 2007 to December 2011 Full details about this dataset can be found at https://doi.org/10.5285/3f0820a7-a8c8-4dd7-a058-8db79ba9c7fe
Chemical composition of freshwater samples from sites in Northern England. Measurements of pH, dissolved major ions (Na, Mg, K, Ca, Cl, NO3, SO4), dissolved organic carbon (DOC), dissolved Al, Fe(II) and total Fe, and measurements of Al, Fe(II) and total Fe on samples following dialysis.