Journal of Siberian Federal University. Biology / Dead Zooplankton Content in Saline Lakes of South Siberia (Republic of Khakassia, Russia) and Prospects for Its Assessment by Underwater Video Survey Method

Full text (.pdf)
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

Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

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