Your search found 5 records
1 Dickens, Chris; Cox, A.; Johnston, Robyn; Henderson, D.; Henderson, PJ; Shinde, V. 2018. Monitoring the health of the Greater Mekong’s Rivers. Vientiane, Laos: CGIAR Research Program on Water, Land and Ecosystems (WLE). 12p.
Sustainable Development Goals ; Environmental monitoring ; Environmental health ; Ecological factors ; River basins ; Ecosystems ; Aquatic animals ; Biomonitoring / Southeast Asia / China / Myanmar / Lao People's Democratic Republic / Thailand / Cambodia / Vietnam
(Location: IWMI HQ Call no: e-copy only Record No: H048845)
2 Saad, D.; Chauke, P.; Cukrowska, E.; Richards, H.; Nikiema, Josiane; Chimuka, L.; Tutu, H. 2022. First biomonitoring of microplastic pollution in the Vaal River using Carp fish (Cyprinus carpio) “as a bio-indicator”. Science of the Total Environment, 836:155623. [doi: https://doi.org/10.1016/j.scitotenv.2022.155623]
Microplastic pollution ; Biomonitoring ; Common carp ; Cyprinus carpio ; Bioindicators ; Aquatic organisms ; Freshwater ; Biota ; Polymers ; Chemicophysical properties ; Wastewater ; Rivers ; Health hazards / South Africa / Vaal River
(Location: IWMI HQ Call no: e-copy only Record No: H051095)
(1.92 MB)
Fish inhabiting freshwater environments are susceptible to the ingestion of microplastics (MPs). Knowledge regarding MPs in freshwater fish in South Africa is very limited. In this study, the uptake of MPs by common carp (Cyprinus carpio) in the Vaal River in South Africa was assessed. MPs were detected in all of the twenty-six fish examined, 682 particles of MPs were recovered from the gastrointestinal tracts of the fish with an average of 26.23 ± 12.57 particles/fish, and an average abundance of 41.18 ± 52.81 particles/kg. The examination of the physical properties of MPs revealed a predominance on fibers (69%), small-sized particles of less than 0.5 mm (48%), as well as prevelance of coloured MPs (94%), mostly green, blue, and black. Using Raman Spectroscopy, the following plastic polymers were identified: high density polyethylene (HDPE), low density polyethylene (LDPE), polypropylene (PP), polyethylene terephthalate (PET), and polytetrafluoroethylene (PTFE).
To the best of our knowledge, this study, is the first to report MPs uptake by freshwater biota in the Vaal River using common carp as a target organism. It provided evidence of MP contamination in the Vaal.
To the best of our knowledge, this study, is the first to report MPs uptake by freshwater biota in the Vaal River using common carp as a target organism. It provided evidence of MP contamination in the Vaal.
3 Pattinson, N. B.; Kuen, R.; Kuen, R. 2022. Artificial intelligence-based biomonitoring of water quality. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation. 32p.
Water quality ; Biomonitoring ; Artificial intelligence ; Rivers ; Citizen science ; Macroinvertebrates ; Machine learning / South Africa
(Location: IWMI HQ Call no: e-copy only Record No: H051644)
(2.97 MB)
The miniSASS was developed as a citizen science tool for monitoring the health of river systems and reflecting the water quality through assessing macroinvertebrates communities. The miniSASS samples the macroinvertebrate community in a river reach and compares the community present to the expected community under ideal natural conditions. The information garnered during a survey relies heavily on the accurate identification of macroinvertebrates by lows killed citizen scientists. This leaves a potential for errors in identification which may impact the accuracy of results and, ultimately, of the river health assessment. In response, we initiated the development of a smartphone application with built-in machine-learning algorithms for the automatic, real-time identification of macroinvertebrates. This report presents our data, methodology, and preliminary results from the automated identification algorithms.
4 Pattinson, N. B.; Russell, C.; Taylor, J.; Dickens, Chris W. S.; Koen, R. C. J.; Koen, F. J.; Graham, P. M. 2023. Digital innovation with miniSASS, a citizen science biomonitoring tool. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation. 11p.
Digital technology ; Citizen science ; Biomonitoring ; Rivers ; Water quality ; Macroinvertebrates ; Mobile applications ; Machine learning ; Algorithms ; Databases ; Training ; Sustainable Development Goals / South Africa / Mooi River / uMgeni River / Karkloof River
(Location: IWMI HQ Call no: e-copy only Record No: H052345)
(1.32 MB)
The mini stream assessment scoring system (miniSASS) was developed as a citizen science biomonitoring tool for assessing the water quality and health of stream and river systems. A miniSASS survey involves sampling the aquatic macroinvertebrate community in a stream or river reach and using the known sensitivities and tolerances of the taxa present to infer information about the water quality and health of the stream or river. The quality of the outcomes of a miniSASS survey is dependent on good sampling technique and accurate identification of aquatic macroinvertebrates by low-skilled citizen scientists. As such, there is potential for errors in sampling and identification which may impact the accuracy of results. In response, we aimed to 1) develop a smartphone application (miniSASS mobile app with built-in machine learning (ML) algorithm for the automatic, real-time identification of aquatic macroinvertebrates) to assist in miniSASS surveys, 2) modernise and upgrade the miniSASS website to handle new data submissions (including photographs) and improve the user interface (UI), and 3) develop an online miniSASS training course. This report presents the methodology and preliminary results pertaining to these objectives.
5 Koen, R. C. J.; Koen, F. J.; Pattinson, N. B.; Dickens, Chris W. S.; Graham, P. M. 2023. Digitally improving the identification of aquatic macroinvertebrates for indices used in biomonitoring. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation. 10p.
Citizen science ; Data collection ; Community involvement ; Biomonitoring ; Macroinvertebrates ; Sustainable development ; Digital innovation ; Machine learning
(Location: IWMI HQ Call no: e-copy only Record No: H052512)
(602 KB)
This report provides an overview of the mini Stream Assessment Scoring System (miniSASS) and South African Scoring System Version 5 (SASS5) as biomonitoring techniques for assessing the ecological condition of streams and rivers based on the identification of aquatic macroinvertebrates. While miniSASS relies on minimally trained citizen scientists to identify macroinvertebrates at the Order-level, SASS5 utilizes expertly accredited practitioners for finer resolution, even up to the family-level. However, the reliance on citizen scientists for miniSASS identification introduces limitations in terms of precision, accuracy, and reliability. To address these limitations, ongoing developments within the CGIAR Initiative on Digital Innovation include the creation of a miniSASS smartphone application, an upgraded website, an interactive online course, and a machine-learning identification algorithm to assist with photo identification. Additionally, a revised dichotomous key has been developed to improve operator identification during miniSASS surveys. Furthermore, the potential for upscaling the machine-learning identification algorithm to assist in identifying the 91 family-level taxa used in SASS5 assessments has been explored. The outcomes of these developments and explorations presented in this paper aim to enhance the overall effectiveness and reliability of both the miniSASS and SASS5 techniques. By leveraging digital innovation and incorporating machine-learning technology, we anticipate the efficiency, accuracy, and accessibility of biomonitoring assessments will significantly improve, ultimately contributing to a better understanding and management of our aquatic ecosystems.
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