2023
DOI: 10.3389/fenvs.2023.1218055
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The potential for freshwater citizen science to engage and empower: a case study of the Rivers Trusts, United Kingdom

Rob Collins,
Anneka France,
Michelle Walker
et al.

Abstract: Rivers Trusts in the United Kingdom work to protect and restore freshwater ecosystems. This includes the provision of citizen science opportunities that encompass water quality monitoring, assessment of polluting outfalls, surveying riverine plastic pollution, mapping and control of freshwater invasive species and assessment of the biological health of rivers. In some cases, citizen science data has led directly to action being taken to address a pollution source and, in one example, indirectly influenced poli… Show more

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“…Even when appropriately funded, regulatory monitoring may not deliver effective monitoring to cover the spatial and temporal variability of nutrient concentrations present in most catchments (Varekar et al, 2021). With the advent and the expansion of alternative monitoring approaches, from remote sensing to citizen science, there are new opportunities to improve spatial and temporal monitoring of rivers or lakes to better understand and mitigate pollution sources (Collins et al, 2023). Numerous studies have shown that citizen science data can help identify pollution drivers and prioritize action (Loiselle et al, 2016;Thornhill et al, 2018).…”
Section: Introductionmentioning
confidence: 99%
“…Even when appropriately funded, regulatory monitoring may not deliver effective monitoring to cover the spatial and temporal variability of nutrient concentrations present in most catchments (Varekar et al, 2021). With the advent and the expansion of alternative monitoring approaches, from remote sensing to citizen science, there are new opportunities to improve spatial and temporal monitoring of rivers or lakes to better understand and mitigate pollution sources (Collins et al, 2023). Numerous studies have shown that citizen science data can help identify pollution drivers and prioritize action (Loiselle et al, 2016;Thornhill et al, 2018).…”
Section: Introductionmentioning
confidence: 99%