- Issue
- Journal of Siberian Federal University. Biology. 2025 18 (1)
- Authors
- Tolomeev, Aleksandr P.; Dubovskaya, Olga P.; Drobotov, Anton V.; Lemesheva, Anastasiya A.
- Contact information
- Tolomeev, Aleksandr P.: Institute of Biophysics SB RAS Federal Research Center “Krasnoyarsk Science Center SB RAS” Krasnoyarsk, Russian Federation; Siberian Federal University Krasnoyarsk, Russian Federation; tolomeev@ibp.ru; ORCID: 0000-0002-9124-4566; Dubovskaya, Olga P.: Institute of Biophysics SB RAS Federal Research Center “Krasnoyarsk Science Center SB RAS” Krasnoyarsk, Russian Federation; Siberian Federal University Krasnoyarsk, Russian Federation; Drobotov, Anton V.: Institute of Biophysics SB RAS Federal Research Center “Krasnoyarsk Science Center SB RAS” Krasnoyarsk, Russian Federation; ORCID: 0009-0007-1722-4958; Lemesheva, Anastasiya A.: Siberian Federal University Krasnoyarsk, Russian Federation
- Keywords
- zooplankton; non-predator mortality; underwater imaging
- Abstract
We analyzed the proportions of dead individuals in the populations of crustacean zooplankton in six lakes located in the Minusinsk Basin in the Republic of Khakassia between 2021 and 2024. In three thermally stratified lakes, the proportions of dead zooplankton were estimated for the epi-, meta- and hypolimnion zones. The proportions of dead individuals determined by their abundance in the study lakes were relatively low, averaging 6.5 % for copepods, 2.6 % for cladocerans, and 5.2 % for the total crustacean zooplankton. A decrease in the number of dead individuals was observed in the hypolimnion, implying high rates of degradation of dead zooplankton organic matter in the epi- and metalimnion. For quantitative comparisons of degradation rates, a new coefficient, KD, is proposed, calculated on the basis of profiles of vertical distributions of live and dead zooplankton. The use of underwater video imaging showed that the method was suitable for estimating natural mortality of zooplankton populations, but the underwater imaging system required technical modification. The results are generally consistent with the data obtained using the method of determining dead zooplankton by plankton net sampling and aniline blue staining. The accuracy of detection of dead zooplankters using underwater video imaging can be improved by increasing the volume of water scanned and employing machine learning techniques to distinguish between live and dead individuals
- Pages
- 98–115
- EDN
- PLALUA
- Paper at repository of SibFU
- https://elib.sfu-kras.ru/handle/2311/155066
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).