News on Acta Limnologica Brasiliensia to our fellow Limnologists

Fellow Limnologist! Click here to access the latest report from the editorial board of Acta Limnologica Brasiliensia.

Acta Limnologica Brasiliensia
Acta Limnologica Brasiliensia
Original Article

Trophic assessment of four tropical reservoirs using phytoplankton genera

Avaliação trófica de quatro reservatórios tropicais usando gêneros fitoplanctônicos

Carlos A. Rivera; Angela Zapata; William Villamil; Nubia León-López

Downloads: 0
Views: 66


Abstract:: Aim: Monitoring the trophic state of reservoirs requires indices that provide a quick report of the ecosystem to decision makers. This study aimed to develop a system of trophic status indicators for tropical mountain reservoirs using phytoplankton genera.

Methods: Between 2004 and 2010, four reservoirs for water supply in Bogotá (Colombia), which have different trophic statuses and hydraulic management, were monitored. Samples were collected for the analysis of physical and chemical variables and phytoplankton community. Through multivariate analysis, the significance of the relationships between environmental variables and phytoplankton species and genera was established. Subsequently, trophic indices were proposed as relevant variables. The global trophic index was calculated as the sum of the partial indices.

Results: Analysis of the main components showed that reservoirs varied chemically depending on trophic status. Phytoplankton were composed of 63 genera, 59% of which were present in the four reservoirs. Although the physical characteristics of water, such as temperature and total solids content, explained a large part of the variation in the genera, a significant relationship between the genera and variables related to trophic state was observed in each reservoir. The multivariate analyses grouping the data by genera showed a behavior similar to the analysis using information at the species level. Plankton indices of trophic state were developed for phosphorus (TP), total Kjeldahl nitrogen (TKN), total organic carbon (TOC), and Secchi disk (SD) using data grouped by genera. The indices were significantly correlated with the values of each variable in each reservoir. Linear regression models showed a significant prediction of chlorophyll-a using TP, TKN, and SD indices in the three reservoirs with the highest trophic level. In addition, the global index showed a significant relationship with variables related to the trophic state.

Conclusions: Phytoplankton data at the genus level can be used to assess trophic status. The models for SD, TP, and TKN could be used as indicators of the trophic status of the studied reservoirs.


trophic index, ecological optimum, ecological indicator, phytoplankton, eutrophication


Resumo: : Objetivo: O monitoramento do estado trófico de reservatórios requer índices que forneçam um relatório rápido do ecossistema aos tomadores de decisão. Este estudo teve como objetivo desenvolver um sistema de indicadores de estado trófico para reservatórios de montanha tropical usando gêneros de fitoplâncton.

Métodos: Entre 2004 e 2010, foram monitorados quatro reservatórios para abastecimento de água em Bogotá (Colômbia), que apresentam diferentes estados tróficos e gestão hidráulica. Amostras foram coletadas para análise de variáveis ​​físicas e químicas e comunidade fitoplanctônica. Por meio de análise multivariada, estabeleceu-se a significância das relações entre variáveis ​​ambientais e espécies e gêneros fitoplanctônicos. Posteriormente, os índices tróficos foram propostos como variáveis ​​relevantes. O índice trófico global foi calculado como a soma dos índices parciais.

Resultados: A análise dos principais componentes mostrou que os reservatórios variam quimicamente dependendo do estado trófico. O fitoplâncton foi composto por 63 gêneros, 59% dos quais estavam presentes nos quatro reservatórios. Embora as características físicas da água, como temperatura e teor de sólidos totais, explicassem grande parte da variação dos gêneros, observou-se em cada reservatório uma relação significativa entre os gêneros e as variáveis ​​relacionadas ao estado trófico. As análises multivariadas agrupando os dados por gênero mostraram um comportamento semelhante à análise utilizando informações em nível de espécie. Os índices de estado trófico do plâncton foram desenvolvidos para fósforo (TP), nitrogênio Kjeldahl total (TKN), carbono orgânico total (TOC) e disco de Secchi (SD) usando dados agrupados por gêneros. Os índices foram significativamente correlacionados com os valores de cada variável em cada reservatório. Modelos de regressão linear mostraram um poder preditivo significativa de clorofila-a usando os índices TP, TKN e SD nos três reservatórios com maior nível trófico. Além disso, o índice global apresentou relação significativa com variáveis ​​relacionadas ao estado trófico.

Conclusões: Os dados do fitoplâncton em nível de gênero podem ser usados ​​para avaliar o estado trófico. Os modelos para SD, TP e TKN podem ser utilizados como indicadores do estado trófico dos reservatórios estudados.


índice trófico, ótimo ecológico, indicador ecológico, fitoplâncton, eutrofização


Almanza, V., Parra, O., Bicudo, C.E.M., González, M.A., Lopez, M., & Urrutia, R., 2016. Floraciones de fitoplancton y variación de la estructura comunitaria fitoplanctónica en tres lagos someros eutróficos de Chile Central. Gayana Bot. 73(2), 191-205. http://dx.doi.org/10.4067/S0717-66432016000200191.

American Public Health Association - APHA. American Water Works Association - AWWA. Water Environment Federation - WEF, 2005. Standard methods for the examination of water and wastewater (21th ed.). Washington: APHA, AWWA & WEF.

Arteaga, L.A., Boss, E., Behrenfeld, M.J., Westberry, T., & Sarmiento, T., 2020. Seasonal modulation of phytoplankton biomass in the Southern Ocean. Nat. Commun. 11(1), 5364. PMid:33097697. http://dx.doi.org/10.1038/s41467-020-19157-2.

Atkinson, K.M., 1972. Birds as transporters of algae. Br. Phycol. J 7(3), 319-321. http://dx.doi.org/10.1080/00071617200650331.

Becker, V., Caputo, L., Ordonez, J., Marce, R., Armengol, J., Crossetti, L.O., & Huszar, V.L.M., 2010a. Driving factors of the phytoplankton functional groups in a deep Mediterranean reservoir. Water Res. 44(11), 3345-3354. PMid:20398914. http://dx.doi.org/10.1016/j.watres.2010.03.018.

Becker, V., Ihara, P., Yunes, J.S., & Huszar, V.L.M., 2010b. Occurrence of anatoxin-a(s) during a bloom of Anabaena crassa in a water-supply reservoir in southern Brazil. J. Appl. Phycol. 22(3), 235-241. http://dx.doi.org/10.1007/s10811-009-9451-8.

Beisner, B.E., Peres-Neto, P.R., Lindström, E.S., Barnett, A., & Longhi, M.L., 2006. The role of environmental and spatial processes in structuring lake communities from bacteria to fish. Ecology 87(12), 2985-2991. http://dx.doi.org/10.1890/0012-9658(2006)87[2985:TROEAS]2.0.CO;2.

Bhateria, R., & Jain, D., 2016. Water quality assessment of lake water: a review. Sustain. Water Resour. Manag. 2(2), 161-173. http://dx.doi.org/10.1007/s40899-015-0014-7.

Bouvy, M., Falcão, D., Marinho, M., Pagano, M., & Moura, A., 2010. Occurrence of Cylindrospermopsis (Cyanobacteria) in 39 Brazilian tropical reservoirs during the 1998 drought. Aquat. Microb. Ecol. 23(1), 13-27. http://dx.doi.org/10.3354/ame023013.

Burford, M.A., Johnson, S.A., Cook, A.J., Packer, T.V., Taylor, B.M., & Townsley, E.R., 2007. Correlations between watershed and reservoir characteristics, and algal blooms in subtropical reservoirs. Water Res. 41(18), 4105-4114. http://dx.doi.org/10.1016/j.watres.2007.05.053.

Cahyonugroho, O.H., Hariyanto, S., & Supriyanto, G., 2022. Dissolved organic matter and its correlation with phytoplankton abundance for monitoring surface water quality. Glob. J. Environ. Sci. Manage. 8, 59-74.

Carlson, R.E., 1977. A trophic state index for lakes. Limnol. Oceanogr. 22(2), 361-369. http://dx.doi.org/10.4319/lo.1977.22.2.0361.

Carneiro, F.M., Bini, L.M., & Rodrigues, L.C., 2010. Influence of taxonomic and numerical resolution on the analysis of temporal changes in phytoplankton communities. Ecol. Indic. 10(2), 249-255. http://dx.doi.org/10.1016/j.ecolind.2009.05.004.

Carvalho, L., Poikane, S., Lyche Solheim, A., Phillips, G., Borics, G., Catalan, J., De Hoyos, C., Drakare, S., Dudley, B.J., Järvinen, M., Laplace-Treyture, C., Maileht, K., McDonald, C., Mischke, U., Moe, J., Morabito, G., Nõges, P., Nõges, T., Ott, I., Pasztaleniec, A., Skjelbred, B., & Thackeray, S.J., 2013. Strength and uncertainty of phytoplankton metrics for assessing eutrophication impacts in lakes. Hydrobiologia 704(1), 127-140. http://dx.doi.org/10.1007/s10750-012-1344-1.

Chandler, R.L., O’shaughnessy, J.C., & Blanc, F.C., 1976. Pollution monitoring with total organic carbon analysis. J. Water Pollut. Control 48(12), 2791-2803.

Chellappa, N.T., Chellappa, T., Câmara, F.R.A., Rocha, O., & Chellappa, S., 2009. Impact of stress and disturbance factors on the phytoplankton communities in Northeastern Brazil reservoir. Limnologica 39(4), 273-282. http://dx.doi.org/10.1016/j.limno.2009.06.006.

Douma, M., Ouahid, Y., del Campo, F.F., Loudiki, M., Mouhri, K., & Oudra, B., 2010. Identification and quantification of cyanobacterial toxins (microcystins) in two Moroccan drinking-water reservoirs (Mansour Eddahbi, Almassira). Environ. Monit. Assess. 160(1-4), 439-450. PMid:19130275. http://dx.doi.org/10.1007/s10661-008-0708-5.

Dunalska, J., 2011. Total organic carbon as a new index for monitoring trophic states in lakes. Oceanol. Hydrobiol. Stud. 40(2), 112-115. http://dx.doi.org/10.2478/s13545-011-0022-7.

Elser, J.J., Andersen, T., Baron, J.S., Bergström, A.K., Jansson, M., Kyle, M., Nydick, K.R., Steger, L., & Hessen, D.O., 2009. Shifts in lake N: P stoichiometry and nutrient limitation driven by atmospheric nitrogen deposition. Science 326(5954), 835-837. PMid:19892979. http://dx.doi.org/10.1126/science.1176199.

Engel, F., Drakare, S., & Weyhenmeyer, G.A., 2019. Environmental conditions for phytoplankton influenced carbon dynamics in boreal lakes. Aquat. Sci. 81(2), 35. http://dx.doi.org/10.1007/s00027-019-0631-6.

Hakspiel-Segura, C., Barrios-Galvan, B., & Pinilla-Agudelo, G., 2021. Phytoplankton functional groups as environmental indicators at a high neotropical mountain reservoir in Colombia. Rev. Acad. Colomb. Cienc. Exactas Fis. Nat. 45(176), 817-832. http://dx.doi.org/10.18257/raccefyn.1326.

Horn, H., Paul, L., Horn, W., & Petzoldt, T., 2011. Long-term trends in the diatom composition of the spring bloom of a German reservoir: is Aulacoseira subarctica favoured by warm winters? Freshw. Biol. 56(12), 2483-2499. http://dx.doi.org/10.1111/j.1365-2427.2011.02674.x.

Huisman, J., Codd, G.A., Paerl, H.W., Ibelings, B.W., Verspagen, J.M.H., & Visser, P.M., 2018. Cyanobacterial blooms. Nat. Rev. Microbiol. 16(8), 471-483. PMid:29946124. http://dx.doi.org/10.1038/s41579-018-0040-1.

Huszar, V.L.M., Silva, L.H.S., Marinho, M., Domingos, P., & Sant’anna, C.L., 2000. Cyanoprokaryote assemblages in eight productive tropical Brazilian waters. Hydrobiologia 424(1), 67-77. http://dx.doi.org/10.1023/A:1003996710416.

Intergovernmental Oceanographic Commission of Unesco - IOC UNESCO, 2010. Microscopic and molecular methods for quantitative phytoplankton analysis. Paris: UNESCO, 110 p., IOC Manuals and Guides, no. 55.

Jongman, R.H.G., Ter Braak, C.J.F., & van Tongeren, O.F.R., eds., 1995. Data analysis in community and landscape ecology. Cambridge: Cambridge University Press. 299 p.. http://dx.doi.org/10.1017/CBO9780511525575.

Jørgensen, S.E., Costanza, R., & Xu, F.L., eds., 2005. Handbook of ecological indicators for assessment of ecosystem health. Boca Raton: CRC Press, 498 p. http://dx.doi.org/10.1201/9780203490181.

Kruk, C., Peeters, E.T.H.M., Van Nes, E.H., Huszar, V.L.M., Costa, L.S., & Scheffer, M., 2011. Phytoplankton community composition can be predicted best in terms of morphological groups. Limnol. Oceanogr. 56(1), 110-118. http://dx.doi.org/10.4319/lo.2011.56.1.0110.

Legendre, P., & Gallagher, E.D., 2001. Ecologically meaningful transformations for ordination of species data. Oecologia 129(2), 271-280. PMid:28547606. http://dx.doi.org/10.1007/s004420100716.

Leigh, C., Burford, M.A., Roberts, D.T., & Udy, J.W., 2010. Predicting the vulnerability of reservoirs to poor water quality and cyanobacterial blooms. Water Res. 44(15), 4487-4496. PMid:20598731. http://dx.doi.org/10.1016/j.watres.2010.06.016.

León, N., Rivera-Rondon, C., Zapata, A., Jimenez, J., Villamil, W., Arenas, G., Rincón, C., & Sánchez, T., 2012. Factors controlling phytoplankton in tropical high-mountain drinking-water reservoirs. Limnetica 31(2), 305-322. http://dx.doi.org/10.23818/limn.31.26.

Lepš, J., & Šmilauer, P., 2003. Multivariate analysis of ecological data using CANOCO. Cambridge: Cambridge University Press, 269 p. http://dx.doi.org/10.1017/CBO9780511615146.

Lewis Junior, W.M.J., 2000. Basis for the protection and management of tropical lakes. Lakes Reservoirs: Res. Manage. 5(1), 35-48. http://dx.doi.org/10.1046/j.1440-1770.2000.00091.x.

Li, L., Zheng, B., & Liu, L., 2010. Biomonitoring and bioindicators used for river ecosystems: definitions, approaches and trends. Procedia Environ. Sci. 2, 1510-1524. http://dx.doi.org/10.1016/j.proenv.2010.10.164.

Lv, J., Wu, H., & Chen, M., 2011. Effects of nitrogen and phosphorus on phytoplankton composition and biomass in 15 subtropical, urban shallow lakes in Wuhan, China. Limnologica 41(1), 48-56. http://dx.doi.org/10.1016/j.limno.2010.03.003.

Lyche-Solheim, A., Feld, C.K., Birk, S., Phillips, G., Carvalho, L., Morabito, G., Mischke, U., Willby, N., Søndergaard, M., Hellsten, S., Kolada, A., Mjelde, M., Böhmer, J., Miler, O., Pusch, M.T., Argillier, C., Jeppesen, E., Lauridsen, T.L., & Poikane, S, 2013. Ecological status assessment of European lakes: a comparison of metrics for phytoplankton, macrophytes, benthic invertebrates and fish. Hydrobiologia 704(1), 57-74. http://dx.doi.org/10.1007/s10750-012-1436-y.

Mamun, M., Atique, U., & An, K.G., 2021. Assessment of water quality based on trophic status and nutrients-chlorophyll empirical models of different elevation reservoirs. Water 13(24), 3640. http://dx.doi.org/10.3390/w13243640.

Margalef, R., 1983. Limnología. Barcelona: Ediciones Omega, 1010 p.

Mazaris, A.D., Moustaka-Gouni, M., Michaloudi, E., & Bobori, D.C., 2010. Biogeographical patterns of freshwater micro- and macroorganisms: a comparison between phytoplankton, zooplankton and fish in the eastern Mediterranean. J. Biogeogr. 37(7), 1341-1351. http://dx.doi.org/10.1111/j.1365-2699.2010.02294.x.

Ochocka, A., & Pasztaleniec, A., 2016. Sensitivity of plankton indices to lake trophic conditions. Environ. Monit. Assess. 188(11), 622. PMid:27752916. http://dx.doi.org/10.1007/s10661-016-5634-3.

Oliveira Sodré, E., Langlais-Bourassa, A., Pollard, A.I., & Beisner, B.E., 2020. Functional and taxonomic biogeography of phytoplankton and zooplankton communities in relation to environmental variation across the contiguous USA. J. Plankton Res. 42(10), 1093.

Padial, A.A., Ceschin, F., Declerck, S.A., De Meester, L., Bonecker, C.C., Lansac-Tôha, F.A., Rodrigues, L., Rodrigues, L.C., Train, S., Velho, L.F., & Bini, L.M., 2014. Dispersal ability determines the role of environmental, spatial and temporal drivers of metacommunity structure. PLoS One 9(10), e111227. PMid:25340577. http://dx.doi.org/10.1371/journal.pone.0111227.

Pasztaleniec, A., 2016. An advanced phytoplankton trophic index: test and validation with a nationwide lake survey in Poland. Int. Rev. Hydrobiol. 101(1-2), 20-35. http://dx.doi.org/10.1002/iroh.201501799.

Peng, X., Zhang, L., Li, Y., Lin, Q., He, C., Huang, S., Li, H., Zhang, X., Liu, B., Ge, F., Zhou, Q., Zhang, Y., & Wu, Z., 2021. The changing characteristics of phytoplankton community and biomass in subtropical shallow lakes: coupling effects of land use patterns and lake morphology. Water Res. 200, 117235. PMid:34034101. http://dx.doi.org/10.1016/j.watres.2021.117235.

Phillips, G., Lyche-Solheim, A., Skjelbred, B., Mischke, U., Drakare, S., Free, G., Järvinen, M., Hoyos, C., Morabito, G., Poikane, S., & Carvalho, L., 2013. A phytoplankton trophic index to assess the status of lakes for the Water Framework Directive. Hydrobiologia 704(1), 75-95. http://dx.doi.org/10.1007/s10750-012-1390-8.

Qu, Y., Wu, N., Guse, B., & Fohrer, N., 2018. Riverine phytoplankton shifting along a lentic-lotic continuum under hydrological, physiochemical conditions and species dispersal. Sci. Total Environ. 619-620, 1628-1636. PMid:29066197. http://dx.doi.org/10.1016/j.scitotenv.2017.10.139.

R Development Core Team, 2018. R: a language and environment for statistical computing [online]. Vienna: R Foundation for Statistical Computing. Retrieved in 2020, December 20, from http://www.R-project.org

Rakocevic-Nedovic, J., & Hollert, H., 2005. Phytoplankton community and chlorophyll a as trophic state indices of lake Skadar (Montenegro, Balkan). Environ. Sci. Pollut. Res. Int. 12(3), 146-152. PMid:15986998. http://dx.doi.org/10.1065/espr2005.04.241.

Reynolds, C.S. 2006. The ecology of phytoplankton: ecology, biodiversity and conservation. Cambridge: Cambridge University Press, 535 p. http://dx.doi.org/10.1017/CBO9780511542145.

Reynolds, C.S., 1997. Vegetation processes in the pelagic: a model for ecosystem theory. Luhe: Ecology Institute, 371 p.

Reynolds, C.S., Huszar, V., Kruk, C., Naselli-Flores, L., & Melo, S., 2002. Towards a functional classification of the freshwater phytoplankton. J. Plankton Res. 24(5), 417-428. http://dx.doi.org/10.1093/plankt/24.5.417.

Rigosi, A., Carey, C.C., Ibelings, B.W., & Brookes, J.D., 2014. The interaction between climate warming and eutrophication to promote cyanobacteria is dependent on trophic state and varies among taxa. Limnol. Oceanogr. 59(1), 99-114. http://dx.doi.org/10.4319/lo.2014.59.1.0099.

Rimet, F., & Bouchez, A., 2012. Biomonitoring river diatoms: implications of taxonomic resolution. Ecol. Indic. 15(1), 92-99. http://dx.doi.org/10.1016/j.ecolind.2011.09.014.

Rivera-Rondón, C., & Zapata, A., 2009. Criterios generales para la recolección, preservación, manejo de muestras y monitoreo de ecosistemas acuáticos epicontinentales. In: Acosta, A., Zapata, A., & G. Fagua, eds. Técnicas de campo en ambientes tropicales: manual para el monitoreo en ecosistemas acuáticos y artrópodos terrestres. Bogotá: Editorial Pontificia Universidad Javeriana, 191-215, Colección de Libros de Investigación.

Rivera-Rondón, C.A., & Catalan, J., 2020. Diatoms as indicators of the multivariate environment of mountain lakes. Sci. Total Environ. 703, 135517. PMid:31767302. http://dx.doi.org/10.1016/j.scitotenv.2019.135517.

Rocha, B., Souza, C., Machado, K., Vieira, L., & Nabout, J., 2020. The relative influence of the environment, land use, and space on the functional and taxonomic structures of phytoplankton and zooplankton metacommunities in tropical reservoirs. Freshw. Sci. 39(2), 321-333. http://dx.doi.org/10.1086/708949.

Rodrigues, E.H.C., Vicentin, A.M., Machado, L.D.S., Pompêo, M.L.M., & Carlos, V.M., 2019. Phytoplankton, Trophic State and Ecological Potential in reservoirs in the State of São Paulo, Brazil. Rev. Ambient. Água 14(5), e2428. http://dx.doi.org/10.4136/ambi-agua.2428.

Salas, J., & Martino, P., 1990. Metodologías simplificadas para la evaluación de eutroficación en lagos cálidos tropicales. Lima: CEPIS - OMS. Retrieved in 2020, December 20, from https://iris.paho.org/handle/10665.2/55333

Seeligmann, C., & Tracanna, B.C., 2009. Phytoplankton dynamics in a high elevation reservoir of Northwestern Argentina (Tucuman). Limnetica 28(1), 105-124. http://dx.doi.org/10.23818/limn.28.08.

Silva, E., 2007. Ecology of phytoplankton in tropical waters: introduction to the topic and ecosystem. Asian J. Water Environ. Pollut. 4, 25-35.

Sotero-Santos, R.B., Carvalho, E.G., Dellamano-Oliveira, M.J., & Rocha, O., 2008. Occurrence and toxicity of an Anabaena bloom in a tropical reservoir (Southeast Brazil). Harmful Algae 7(5), 590-598. http://dx.doi.org/10.1016/j.hal.2007.12.017.

Souza, C., Machado, K., Nabout, J., Muniz, D., Oliveira-Filho, E., Kraus, C., Ribeiro, R., & Vieira, L., 2019. Monitoring simplification in plankton communities using different ecological approaches. Acta Limnol. Bras. 31, e20. http://dx.doi.org/10.1590/s2179-975x3617.

Steffensen, D.A., 2008. Economic cost of cyanobacterial blooms. In: Hudnell, H.K., ed. Cyanobacterial Harmful Algal Blooms. New York: Springer Science, 2008, 855-866. http://dx.doi.org/10.1007/978-0-387-75865-7_37.

Straskraba, M., & Tundisi, J.G., 1999. Reservoir water quality management. Kusatsu: International Lake Environment Committee Foundation, 237 p. Guidelines of Lake Management, no. 9. Retrieved in 2020, December 20, from https://wedocs.unep.org/20.500.11822/29399

Tundisi, J.G., Matsumura-Tundisi, T., & Abe, D.S., 2008. The ecological dynamics of Barra Bonita (Tietê River, SP, Brazil) reservoir: implications for its biodiversity. Braz. J. Biol. 68(4, Suppl.), 1079-1098. PMid:19197478. http://dx.doi.org/10.1590/S1519-69842008000500015.

Utermöhl, H., 1958. Zur vervollkommung der quantitativen phytoplankton-Methodik. Verh. Int. Ver. Theor. Angew. 9, 1-38.

Weithoff, G., & Gaedke, U., 2017. Mean functional traits of lake phytoplankton reflect seasonal and inter-annual changes in nutrients, climate and herbivory. J. Plankton Res. 39(3), 509-517. http://dx.doi.org/10.1093/plankt/fbw072.

Wetzel, R.G., & Likens, G.E., 2000. Limnological analyses. New York: Springer-Verlag, 429 p. http://dx.doi.org/10.1007/978-1-4757-3250-4.

Yang, Y., Colom, W., Pierson, D., & Pettersson, K., 2016. Water column stability and summer phytoplankton dynamics in a temperate lake (Lake Erken, Sweden). Inland Waters 6(4), 499-508. http://dx.doi.org/10.1080/IW-6.4.874.

Submitted date:

Accepted date:

Publication date:

63640b7aa953954e30749203 alb Articles
Links & Downloads

Acta Limnol. Bras. (Online)

Share this page
Page Sections