Establishing the Citizen Science Stream Index (CSSI) to monitor water quality in freshwaters

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dc.availability.bitstreamopenaccess
dc.contributor.advisorHarrison, Simonen
dc.contributor.advisorSullivan, Timothyen
dc.contributor.authorMcSorley, Brendan
dc.date.accessioned2023-01-17T09:48:56Z
dc.date.available2023-01-17T09:48:56Z
dc.date.issued2022-03-01
dc.date.submitted2022-03-01
dc.description.abstractStreams and rivers are amongst the most endangered ecosystems in the world. Water quality is an important measure for maintaining ecosystem function. Despite several decades of the EU Nitrates and Water Framework Directives, inputs of nutrient-rich organic matter of both agricultural and municipal origin continue to pollute many waterways in Ireland, most of which are not routinely monitored in terms of water quality. This lack of data hampers efforts to improve water quality. Citizen science projects involve non-experts contributing to scientific data voluntarily and have been identified by the EU as a growing field of practice that is likely to yield significant outcomes for water quality and data capture. In this thesis a biotic index called the Citizen Science Stream Index (CSSI) was established using a principal component analysis of an EPA data set of macroinvertebrates. A further analysis was made using the provided Q-Values in this data set to find the most indicative macroinvertebrates for a citizen science index. The CSSI uses six easily identifiable and common benthic macroinvertebrates with narrow pollution tolerances that indicate water quality, to give a rapid indication of the ecological status of a stream in a sampled area. The CSSI is an easily taught and simple to use biomonitoring index that enables non-experts to identify where pollution has affected the macroinvertebrate community. The protocol involves taking a thirty second kick sample and checking it for the presence or absence of the six taxa, giving a score from -3 to +3. This is repeated three times and the resulting three scores are summed to give a CSSI score between -9 and +9. From this score the sampler can band the water quality of the stream into three water quality bands, red (poor), orange (moderate) and green (good). This thesis validates the CSSI’s indicator taxa, protocol and scoring system by using multiple data sets with varying spatial distribution, water quality and seasonality, comparing the CSSI with contemporary metrics such as the EPA Quality-Values (Q-Values), the Biological Monitoring working Party’s (BMWP) Average Score Per Taxon (ASPT) and the Small Stream Risk Score (SSRS). A pilot study to further test the quality, accuracy and feasibility of the index in the field was carried out on the Nore River catchment with volunteers from the NoreVision project. It was found that the CSSI compared sufficiently with the contemporary metrics tested and provided accurate results in the field study. Therefore, it is fit for purpose as a rapid biomonitoring citizen science index. The CSSI is currently being rolled out in volunteer initiatives around Ireland. The CSSI has received a positive response from participants and provided consistently reliable data capture when compared to existing data points thus far.en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMcSorley, B. 2022. Establishing the Citizen Science Stream Index (CSSI) to monitor water quality in freshwaters. MSc Thesis, University College Cork.en
dc.identifier.endpage116en
dc.identifier.urihttps://hdl.handle.net/10468/14061
dc.language.isoenen
dc.publisherUniversity College Corken
dc.rights© 2022, Brendan McSorley.en
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectMacroinvertebratesen
dc.subjectWater qualityen
dc.subjectBiomonitoringen
dc.subjectCitizen scienceen
dc.titleEstablishing the Citizen Science Stream Index (CSSI) to monitor water quality in freshwatersen
dc.typeMasters thesis (Research)en
dc.type.qualificationlevelMastersen
dc.type.qualificationnameMSc - Master of Scienceen
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