La importancia de usar el biovolumen en estudios de fitoplancton y monitoreo ambiental de cianobacterias

Sylvia Bonilla; Inés O'Farrell

doi:10.25260/EA.23.33.2.0.2148

Authors

Sylvia Bonilla Grupo de Ecología y Fisiología de Fitoplancton. Sección Limnología, Facultad de Ciencias, Universidad de la República. Uruguay
Inés O'Farrell Departamento de Ecología, Genética y Evolución, IEGEBA (UBA-CONICET), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires. Argentina

DOI:

https://doi.org/10.25260/EA.23.33.2.0.2148

Keywords:

Latin America, counting, biomass, ecology, limnology, qualitative methods

Abstract

Phytoplankton biomass is a variable used in ecological studies and in monitoring potentially toxic cyanobacterial blooms. Biomass indicators of this community range from general and indirect, such as chlorophyll a concentrations, to specific and quasi-direct measures such as biovolume. Based on the results of a survey addressed to Latin American scientists and technicians as well as a bibliographic search, we discuss the relevance of using biovolume as the most appropriate indicator of biomass, the effort of quantifying phytoplankton using different counting units and the implications for interpretation of the results. Individuals, cells and biovolume were the quantitative units used to report phytoplankton. The individual represents the natural biological unit of the organism (cells, coenobia, colonies or filaments) and has a wide size range. We strongly advise that the phytoplankton reported as individuals per unit volume can lead to conceptual misinterpretation, such as the underestimation of the biomass of blooms. As cells have a large variation in their sizes, it poorly correlates with biovolume or chlorophyll a concentration. Considering all these aspects is crucial when selecting quantitative bioindicators to monitor potentially toxic cyanobacteria. We strongly recommend the use of biovolume as a biomass indicator for phytoplankton in general and consider it imperative for monitoring cyanobacteria.

References

Aguilera, A., V. Almanza, S. Haakonsson, H. Palacio, G. A. Benitez Rodas, M. U. G. Barros, J. Capelo-Neto, R. Urrutia, L. Aubriot, and S. Bonilla. 2023. Cyanobacterial bloom monitoring and assessment in Latin America. Harmful Algae 125:102429. https://doi.org/10.1016/j.hal.2023.102429.

Ahn, C., S. Joung, S. Yoon, and H. Oh. 2007. Alternative alert system for cyanobacterial bloom, using phycocyanin as a level determinant. The Journal of Microbiology 45:98-104.

Almuhtaram, H., F. A. Kibuye, S. Ajjampur, C. M. Glover, R. Hofmann, V. Gaget, C. Owen, E. C. Wert, and A. Zamyadi. 2021. State of knowledge on early warning tools for cyanobacteria detection. Ecological Indicators 133:108442. https://doi.org/10.1016/j.ecolind.2021.108442.

Alveal, K., M. E. Ferrario, E. C. Oliveira, and E. Sar. 1995. Manual de métodos ficológicos. Universidad de Concepción, Concepción.

Bazán, R., A. M. Cossavella, H. Calvimonte, J. D. Lozada, C. M. G. Rodríguez, G. Carnicelli, A. Casas, J. Greta, G. Calamuchita, and E. A. Storni. 2020. El aporte de la ciencia ciudadana para generar un monitoreo visual de cianobacterias en el embalse Los Molinos, Córdoba, Argentina. Innotec 21:109-131. https://doi.org/10.26461/21.01.

Bonilla, S., A. Fabre, and L. De León. 2016. Fitoplancton. Pp. 129-168 in R. Arocena (ed.). Principios y métodos de limnología: ejemplos de Uruguay. First edition. DIRAC, Montevideo. Uruguay.

Bonilla, S., and F. R. Pick. 2017. Freshwater bloom-forming cyanobacteria and anthropogenic change. e-lecture. Limnology and Oceanography 7:1-62. https://doi.org/10.1002/loe2.10006.

Borics, G., V. Lerf, E. T-Krasznai, I. Stankovi, L. Pickó, V. Béres, and G. Várbíró. 2021. Biovolume and surface area calculations for microalgae, using realistic 3D models. Science of the Total Environment 773:145538. https://doi.org/10.1016/j.scitotenv.2021.145538.

Carmichael, W. W., and G. L. Boyer. 2016. Health impacts from cyanobacteria harmful algae blooms: Implications for the North American Great Lakes. Harmful Algae 54:194-212. https://doi.org/10.1016/j.hal.2016.02.002.

Chorus, I., and J. Bartram. 1999. Toxic Cyanobacteria in Water : A guide to their public health consequences, monitoring and management. En I. Chorus and J. Bartram (eds.). 1st edition. WHO, E and FN Spon, London. https://doi.org/10.4324/9780203478073.

Chorus, I., and M. Welker. 2021. Toxic cyanobacteria in water. A guide to their public health consequences, monitoring and management. Pp. 859 en I. Chorus and M. Welker (eds.). 1st edition. CRC Press, on behalf of the World Health Organization, Geneva, CH, Boca Ratón (FL). https://doi.org/10.1201/9781003081449-1.

Ciocca, D. R., and G. Delgado. 2017. The reality of scientific research in Latin America; an insider’s perspective. Cell Stress and Chaperones 22:847-852. https://doi.org/10.1007/s12192-017-0815-8.

Cremella, B., Y. Huot, and S. Bonilla. 2018. Interpretation of total phytoplankton and cyanobacteria fluorescence from cross-calibrated fluorometers, including sensitivity to turbidity and colored dissolved organic matter. Limnology and Oceanography: Methods 16:881-894. https://doi.org/10.1002/lom3.10290.

Edler, L., and M. Elbrächter. 2010. The Utermöhl method for quantitative phytoplankton analysis. Pp. 13-20 en B. Karlson, C. Cusack and E. Bresnan (eds.). Microscopic and molecular methods for quantitative phytoplankton analysis. (IOC Manuals and Guides, no. 55), UNESCO, Paris.

Hillebrand, H., C.-D. Dürselen, D. Kirschtel, U. Pollingher, and T. Zohary. 1999. Biovolume calculation for pelagic and benthic microalgae. Journal of Phycology 35:2. https://doi.org/10.1046/j.1529-8817.1999.3520403.x.

Huisman, J., G. A. Codd, H. W. Paerl, B. W. Ibelings, J. M. H. Verspagen, and P. M. Visser. 2018. Cyanobacterial blooms. Nature Reviews Microbiology 16:471-483. https://doi.org/10.1038/s41579-018-0040-1.

Lorenzen, C. J. 1967. Determination of chlorophyll and pheo‐pigments: Spectrophotometric equations. Limnology and Oceanography 12:343-346. https://doi.org/10.4319/lo.1967.12.2.0343.

Maciel, F. P., S. Haakonsson, S. Bonilla, L. Ponce de León, and F. Pedocchi. 2022. Remote sensing of chlorophyll-a for monitoring cyanobacteria in a highly turbid estuary, an implementation with Sentinel 2. Geocarto International. https://doi.org/doi.org/10.1080/10106049.2022.2160017.

Mishra, S., and D. R. Mishra. 2014. A novel remote sensing algorithm to quantify phycocyanin in cyanobacterial algal blooms. Environmental Research Letters 9. https://doi.org/10.1088/1748-9326/9/11/114003.

Mitroi, V., K. C. Ahi, P. Y. Bulot, F. Tra, J. F. Deroubaix, M. K. Ahoutou, C. Quiblier, M. Koné, J. C. Kalpy, and J. F. Humbert. 2020. Can participatory approaches strengthen the monitoring of cyanobacterial blooms in developing countries? Results from a pilot study conducted in the Lagoon Aghien (Ivory Coast). PLoS ONE. 15:1-18 https://doi.org/10.1371/journal.pone.0238832.

Mohan, J., J. Saros, and J. R. Stone. 2021. On the matter of phytoplankton: A novel method using 3D computer models to calculate biovolume of microorganisms. Limnology and Oceanography: Methods 19:331-339. https://doi.org/10.1002/lom3.10426.

Nabout, J. C., A. C. M. David, J. F. Felipe, K. B. Machado, L. Carvalho, and H. F. da Cunha. 2022. Can people detect the loss of water quality? A field experiment to evaluate the correlation between visual perception and water eutrophication degree. Acta Limnologica Brasiliensia 34. https://doi.org/10.1590/S2179-975X2921.

Nusch, E. A. 1980. Comparison of different methods for chlorophyll and phaeopigment determination. Arch Hydrobiol Beih Ergebn Limnol 14:14-36.

O´Farrell, I. 2022. Floraciones de cianobacterias. Pp. 163-170 en A. Giorgi, E. Domínguez and N. Gómez (eds.). Técnicas de monitoreo para ecosistemas fluviales de la Argentina. REM_AQUA- CONICET, Buenos Aires.

Pamula, A. S. P., H. Gholizadeh, M. J. Krzmarzick, W. E. Mausbach, and D. J. Lampert. 2023. A remote sensing tool for near real‐time monitoring of harmful algal blooms and turbidity in reservoirs. JAWRA Journal of the American Water Resources Association. https://doi.org/10.1111/1752-1688.13121.

Ramírez, A., and P. E. Gutiérrez-Fonseca. 2020. Freshwater research in Latin America: current research topics, challenges, and opportunities. Revista de Biología Tropical 68:1-10. https://doi.org/10.15517/rbt.v68iS2.44328.

Reynolds, C. S. 1994. The long, the short and the stalled: on the attributes of phytoplankton selected by physical mixing in lakes and rivers. Hydrobiologia 289:9-21. https://doi.org/10.1007/BF00007405.

Ritchie, R. J. 2006. Consistent sets of spectrophotometric chlorophyll equations for acetone, methanol and ethanol solvents. Photosynthesis Research 89:27-41. https://doi.org/10.1007/s11120-006-9065-9.

Saccà, A. 2017. Methods for the estimation of the biovolume of microorganisms: A critical review. Limnology and Oceanography: Methods 15:337-348. https://doi.org/10.1002/lom3.10162.

Sitoki, L., R. Kurmayer, and E. Rott. 2012. Spatial variation of phytoplankton composition, biovolume, and resulting microcystin concentrations in the Nyanza Gulf (Lake Victoria, Kenya). Hydrobiologia 691:109-122. https://doi.org/10.1007/s10750-012-1062-8.

Sournia, A. 1978. Phytoplancton Manual. Page Monographs on oceanographic methodology. UNESCO, Paris.

Sun, J., and D. Liu. 2003. Geometric models for calculating cell biovolume and surface area for phytoplankton. Journal of Plankton Research 25:1331-1346. https://doi.org/10.1093/plankt/fbg096.

Svirčev, Z., D. Lalić, G. Bojadžija Savić, N. Tokodi, D. Drobac Backović, L. Chen, J. Meriluoto, and G. A. Codd. 2019. Global geographical and historical overview of cyanotoxin distribution and cyanobacterial poisonings. Page Archives of Toxicology. Springer Berlin Heidelberg. https://doi.org/10.1007/s00204-019-02524-4.

Zabaleta, B., S. Haakonsson, M. Achkar, and L. Aubriot. 2023. High-frequency zones of phytoplankton blooms in the Río de la Plata Estuary associated with El Niño-Southern Oscillation. Estuarine, Coastal and Shelf Science 286:108342. https://doi.org/10.1016/j.ecss.2023.108342.

Zamyadi, A., F. Choo, G. Gayle Newcombe, S. Richard, and R. K. Henderson. 2016. A review of monitoring technologies for real-time management of cyanobacteria: recent advances and future direction. Trends in Analytical Chemistry 85(4):83-96. http://dx.doi.org/10.1016/j.trac.2016.06.023.

Zohary, T., M. Shneor, and K. D. Hambright. 2016. PlanktoMetrix - a computerized system to support microscope counts and measurements of plankton. Inland Waters 6:131-135. https://doi.org/10.5268/IW-6.2.965.