Acta Limnologica Brasiliensia
https://app.periodikos.com.br/journal/alb/article/doi/10.1590/S2179-975X6223
Acta Limnologica Brasiliensia
Artigo Original

Main predictors of phytoplankton occurrence in lotic ecosystems

Principais preditores na ocorrência do fitoplâncton em sistemas lóticos

Maria Clara Pilatti; Gabriela Medeiros; Andre Andrian Padial; Mailor Wellinton Wedig Amaral; Ricardo Guicho; Norma Catarina Bueno

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Abstract

Aim: Our goal was to relate the phytoplankton metacommunity to its possible determinants in a micro watershed: (I) determinants related to landscape-scale filtering, (II) determinants referring to local microhabitat filtering, (III) determinants referring to previous colonization, and (IV) determinants representing three different dispersal routes.

Methods: Eight sampling stations were selected along the Cascavel River watershed, located in the state of Paraná, Brazil. Samples were collected quarterly for three years. All phytoplankton samples were quantitatively analyzed to determine the density of the metacommunity. In addition, it was characterized the landscape in terms of land use and occupation, and environmental characterization in terms of physical and chemical variables of the water. All data underwent relevant statistical analysis, where variance partitioning was carried out using partial RDA models, with prior selection of predictor variables, to estimate the relative role of each predictor in the community. We also compared three possible dispersal routes: “Asymmetric Eigenvector Map” (AEM), “Overland” and “Watercourse”.

Results: It was found that the metacommunity was best explained by “asymmetric eigenvector mapping” (AEM), indicating that because it is a small spatial scale the high connectivity between the sampling stations enables species to disperse overland as well. The different filters act together and depend on rainfall variation. Besides fluctuating temporally, the influence of these mechanisms is subject to which dispersal hypothesis is being considered.

Conclusions: At the watershed scale, we argue that small-scale processes should be considered, since they homogenize the landscape and consequently leave the environmental gradient similar between sampling stations. In addition, the connectivity of colonization patches is essential to understand the behavior of microalgae that have a high dispersal capacity and are not restricted only to the river course.

Keywords

dispersion, mass effect, scale, landscape

Resumo

Objetivo: O objetivo do trabalho foi relacionar a metacomunidade fitoplanctônica com seus possíveis determinantes em uma microbacia hidrográfica: (I) determinantes relacionados à filtragem em escala de paisagem, (II) determinantes referentes à filtragem local de micro-habitat, (III) determinantes referentes a colonização anterior e (IV) determinantes representando três diferentes rotas de dispersão.

Métodos: Foram selecionadas oito estações de amostragem ao longo da microbacia do Rio Cascavel, localizada no estado do Paraná, Brasil. As coletas foram realizadas trimestralmente durante três anos. Todas as amostras de fitoplâncton passaram por análise quantitativa para averiguar a densidade da metacomunidade. Além disso fizemos a caracterização da paisagem tanto o uso e ocupação do solo e caracterização ambiental quanto as variáveis físicas e químicas da água. Todos os dados passaram por análises estatísticas pertinentes, onde a partição da variância foi realizada utilizando modelos RDA parciais, com seleção prévia das variáveis preditoras, para estimar o papel relativo de cada preditor na comunidade. Ainda comparamos três possíveis rotas de dispersão: Mapa de Autovetores Assimétricos” (AEM), “Terrestre” e “Curso d´água”.

Resultados: Constatou-se que a metacomunidade foi mais bem explicada pelo “mapa de autovetores assimétricos” (AEM), indicando que por se tratar de uma pequena escala espacial a alta conectividade entre as estações de amostragem possibilita que as espécies se dispersem também por terra. Os diferentes filtros atuam em conjunto e dependem da variação de chuva. Além de flutuar temporalmente, a influência desses mecanismos está sujeita a qual hipótese de dispersão está sendo considerada.

Conclusões: Na escala da microbacia hidrográfica, argumentamos que os processos de pequena escala devem ser considerados, uma vez que homogeneízam a paisagem e, consequentemente, deixam o gradiente ambiental semelhante entre as estações de amostragem. Além disso, a conectividade das manchas de colonização é essencial para entender o comportamento das microalgas que têm alta capacidade de dispersão, não se restringindo apenas ao curso do rio.
 

Palavras-chave

dispersão, efeito de massa, escala, paisagem

Referências

Aboim, I.L., Gomes, D.F., & Mafalda Junior, P.O., 2020. Phytoplankton response to water quality seasonality in a Brazilian neotropical river. Environ. Monit. Assess. 192(1), 70. PMid:31883033. http://dx.doi.org/10.1007/s10661-019-7882-5.

Akhtar, N., Syakir Ishak, M.I., Bhawani, S.A., & Umar, K., 2021. Various natural and anthropogenic factors responsible for water quality degradation: a review. Water 13(19), 2660. http://dx.doi.org/10.3390/w13192660.

Almeida, T.P., Macena, D.Â., Simões, J.S.T., Mareco, E.A., Calciolari Rossi, R., & Favareto, A.P.A., 2022. Análise de parâmetros de qualidade da água e teste de genotoxicidade em peixes da bacia hidrográfica do rio Pirapozinho - SP, Brasil. Res. Soc. Dev. 11(3), e46711319309. http://dx.doi.org/10.33448/rsd-v11i3.19309.

Alvares, C.A., Stape, J.L., Sentelhas, P.C., Moraes Gonçalves, J.L., & Sparovek, G., 2013. Köppen’s climate classification map for Brazil. Meteorol. Z. 22(6), 711-728. http://dx.doi.org/10.1127/0941-2948/2013/0507.

American Public Health Association - APHA, 2017. Standart methods for the examination of wastewater. Washington: APHA.

Bicudo, C.E.M., & Menezes, M., 2017. Gêneros de algas de águas continentais do Brasil: chave para identificação e descrições. São Carlos: RiMa.

Bivand, R., 2022. R packages for analyzing spatial data: a comparative case study with areal data. Geogr. Anal. 54(3), 488-518. http://dx.doi.org/10.1111/gean.12319.

Blanchet, F.G., Legendre, P., & Borcard, D., 2008. Modelling directional spatial processes in ecological data. Ecol. Modell. 215(4), 325-336. http://dx.doi.org/10.1016/j.ecolmodel.2008.04.001.

Borcard, D., & Legendre, P., 2002. All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecol. Modell. 153(1-2), 51-68. http://dx.doi.org/10.1016/S0304-3800(01)00501-4.

Bortolini, J.C., Silva, P.R.L., Baumgartner, G., & Bueno, N.C., 2019. Response to environmental, spatial, and temporal mechanisms of the phytoplankton metacommunity: comparing ecological approaches in subtropical reservoirs. Hydrobiologia 830(1), 45-61. http://dx.doi.org/10.1007/s10750-018-3849-8.

Bortolini, J.C., Pineda, A., Rodrigues, L.C., Jati, S., & Velho, L.F.M., 2017. Environmental and spatial processes influencing phytoplankton biomass along a reservoirs-river-floodplain lakes gradient: a metacommunity approach. Freshw. Biol. 62(10), 1756-1767. http://dx.doi.org/10.1111/fwb.12986.

Bray, J.R., & Curtis, J.T., 1957. An ordination of the upland forest communities of Southern Wisconsin. Ecol. Monogr. 27(4), 325-349. http://dx.doi.org/10.2307/1942268.

Calijuri, M.C., Dos Santos, A.C.A., & Jati, S., 2002. Temporal changes in the phytoplankton community structure in a tropical and eutrophic reservoir (Barra Bonita, S.P.: Brazil). J. Plankton Res. 24(7), 617-634. http://dx.doi.org/10.1093/plankt/24.7.617.

Cembranel, A.S., Sampaio, S.C., Remor, M.B., Gotardo, J.T., & Rosa, P.M.D., 2017. Geochemical background in an oxisol. Eng. Agric. 37(3), 565-573. http://dx.doi.org/10.1590/1809-4430-eng.agric.v37n3p565-573/2017.

Chaparro, G., O’Farrell, I., & Hein, T., 2023. Hydrological conditions determine shifts of plankton metacommunity structure in riverine floodplains without affecting patterns of species richness along connectivity gradients. Aquat. Sci. 85(2), 41. http://dx.doi.org/10.1007/s00027-023-00937-z.

Choudhury, A.K., Das, M., Philip, P., & Bhadury, P., 2015. An assessment of the implications of seasonal precipitation and anthropogenic influences on a mangrove ecosystem using phytoplankton as proxies. Estuaries Coasts 38(3), 854-872. http://dx.doi.org/10.1007/s12237-014-9854-x.

Devercelli, M., Scarabotti, P., Mayora, G., Schneider, B., & Giri, F., 2016. Unravelling the role of determinism and stochasticity in structuring the phytoplanktonic metacommunity of the Paraná River floodplain. Hydrobiologia 764(1), 139-156. http://dx.doi.org/10.1007/s10750-015-2363-5.

Dias, J.D., Simões, N.R., Meerhoff, M., Lansac-Tôha, F.A., Velho, L.F.M., & Bonecker, C.C., 2016. Hydrological dynamics drives zooplankton metacommunity structure in a Neotropical floodplain. Hydrobiologia 781(1), 109-125. http://dx.doi.org/10.1007/s10750-016-2827-2.

Diniz, L.P., Petsch, D.K., Mantovano, T., Rodrigues, L.C., Agostinho, A.A., & Bonecker, C.C., 2023. A prolonged drought period reduced temporal β diversity of zooplankton, phytoplankton, and fish metacommunities in a Neotropical floodplain. Hydrobiologia http://dx.doi.org/10.1007/s10750-023-05140-7.

Dittrich, J., Dias, J.D., Bonecker, C.C., Lansac‐Tôha, F.A., & Padial, A.A., 2016. Importance of temporal variability at different spatial scales for diversity of floodplain aquatic communities. Freshw. Biol. 61(3), 316-327. http://dx.doi.org/10.1111/fwb.12705.

Doretto, A., Piano, E., & Larson, C.E., 2020. The River Continuum Concept: lessons from the past and perspectives for the future. Can. J. Fish. Aquat. Sci. 77(11), 1853-1864. http://dx.doi.org/10.1139/cjfas-2020-0039.

Dray, S., Pélissier, R., Couteron, P., Fortin, M.J., Legendre, P., Peres-Neto, P.R., Bellier, E., Bivand, R., Blanchet, F.G., De Cáceres, M., Dufour, A.-B., Heegaard, E., Jombart, T., Munoz, F., Oksanen, J., Thioulouse, J., & Wagner, H.H., 2012. Community ecology in the age of multivariate multiscale spatial analysis. Ecol. Monogr. 82(3), 257-275. http://dx.doi.org/10.1890/11-1183.1.

Field, C.B., Behrenfeld, M.J., Randerson, J.T., & Falkowski, P., 1998. Primary production of the biosphere: integrating terrestrial and oceanic components. Science 281(5374), 237-240. PMid:9657713. http://dx.doi.org/10.1126/science.281.5374.237.

Foets, J., Wetzel, C.E., Teuling, A.J., & Pfister, L., 2020. Temporal and spatial variability of terrestrial diatoms at the catchment scale: controls on communities. PeerJ 8, e8296. PMid:31915584. http://dx.doi.org/10.7717/peerj.8296.

Fundação para o Desenvolvimento Científico e Tecnológico - FUNDETEC, 1995. Recuperação ambiental da bacia hidrográfica do rio Cascavel. Cascavel.

Gomes, A.L., Cunha, C.J., Lima, M.O., Sousa, E.B., Costa-Tavares, V.B., & Martinelli-Lemos, J.M., 2021. Biodiversity and interannual variation of cyanobacteria density in an estuary of the Brazilian Amazon. An. Acad. Bras. Cienc. 93(4), e20191452. PMid:34705935. http://dx.doi.org/10.1590/0001-3765202120191452.

Grönroos, M., Heino, J., Siqueira, T., Landeiro, V.L., Kotanen, J., & Bini, L.M., 2013. Metacommunity structuring in stream networks: roles of dispersal mode, distance type, and regional environmental context. Ecol. Evol. 3(13), 4473-4487. PMid:24340188. http://dx.doi.org/10.1002/ece3.834.

Guicho, R., Ferreira, J.H.D., Medeiros, G., Siqueira, J.A.C., Souza, S.N.M., & Prior, M., 2021. Method for estimating the wind power micro and minigeneration applied to a city with a subtropical climate in south America. Res. Soc. Dev. 10(12), e105101220009. http://dx.doi.org/10.33448/rsd-v10i12.20009.

Haque, M.A., Jewel, M.A.S., Akhi, M.M., Atique, U., Paul, A.K., Iqbal, S., Islam, M.S., Das, S.K., & Alam, M.M., 2021. Seasonal dynamics of phytoplankton community and functional groups in a tropical river. Environ. Monit. Assess. 193(11), 704. PMid:34623504. http://dx.doi.org/10.1007/s10661-021-09500-5.

Heino, J., Melo, A.S., Siqueira, T., Soininen, J., Valanko, S., & Bini, L.M., 2015. Metacommunity organisation, spatial extent and dispersal in aquatic systems: patterns, processes and prospects. Freshw. Biol. 60(5), 845-869. http://dx.doi.org/10.1111/fwb.12533.

Hitchcock, J.N., 2022. Microplastics can alter phytoplankton community composition. Sci. Total Environ. 819, 153074. PMid:35038524. http://dx.doi.org/10.1016/j.scitotenv.2022.153074.

Huang, Z., Pan, B., Soininen, J., Liu, X., Hou, Y., & Liu, X., 2023. Seasonal variation of phytoplankton community assembly processes in Tibetan Plateau floodplain. Front. Microbiol. 14, 1122838. PMid:36891389. http://dx.doi.org/10.3389/fmicb.2023.1122838.

Hubbell, S.J. 2011. The unified neutral theory of biodiversity and biogeography (MPB-32). Princeton: Princeton University Press. http://dx.doi.org/10.1515/9781400837526.

Huszar, V.L.M., Nabout, J.C., Appel, M.O., Santos, J.B.O., Abe, D.S., & Silva, L.H.S., 2015. Environmental and not spatial processes (directional and non-directional) shape the phytoplankton composition and functional groups in a large subtropical river basin. J. Plankton Res. 37(6), 1190-1200. http://dx.doi.org/10.1093/plankt/fbv084.

Incagnone, G., Marrone, F., Barone, R., Robba, L., & Naselli-Flores, L., 2015. How do freshwater organisms cross the “dry ocean”? A review on passive dispersal and colonization processes with a special focus on temporary ponds. Hydrobiologia 750(1), 103-123. http://dx.doi.org/10.1007/s10750-014-2110-3.

Instituto Brasileiro de Geografia e Estatística - IBGE, 2013. Manual técnico de uso da terra. Rio de Janeiro: IBGE.

Jeppesen, E., Brucet, S., Naselli-Flores, L., Papastergiadou, E., Stefanidis, K., Nõges, T., Nõges, P., Attayde, J.L., Zohary, T., Coppens, J., Bucak, T., Menezes, R.F., Freitas, F.R.S., Kernan, M., Søndergaard, M., & Beklioğlu, M., 2015. Ecological impacts of global warming and water abstraction on lakes and reservoirs due to changes in water level and related changes in salinity. Hydrobiologia 750(1), 201-227. http://dx.doi.org/10.1007/s10750-014-2169-x.

Kruk, C., Huszar, V.L.M., Peeters, E.T.H.M., Bonilla, S., Costa, L., Lürling, M., Reynolds, C., & Scheffer, M., 2010. A morphological classification capturing functional variation in phytoplankton. Freshw. Biol. 55(3), 614-627. http://dx.doi.org/10.1111/j.1365-2427.2009.02298.x.

Lansac‐Tôha, F.M., Bini, L.M., Heino, J., Meira, B.R., Segovia, B.T., Pavanelli, C.S., Bonecker, C.C., de Deus, C.P., Benedito, E., Alves, G.M., Manetta, G.I., Dias, J.D., Vieira, L.C.G., Rodrigues, L.C., do Carmo Roberto, M., Brugler, M.R., Lemke, M.J., Tessler, M., DeSalle, R., Mormul, R.P., Amadio, S., Lolis, S.F., Jati, S., Siqueira, T., Silva, W.M., Higuti, J., Lansac-Tôha, F.A., Martens, K., & Velho, L.F.M., 2021. Scale‐dependent patterns of metacommunity structuring in aquatic organisms across floodplain systems. J. Biogeogr. 48(4), 872-885. http://dx.doi.org/10.1111/jbi.14044.

Legendre, P., & Legendre, L., 2012. Numerical ecology. Amsterdam: Elsevier.

Leibold, M.A., Holyoak, M., Mouquet, N., Amarasekare, P., Chase, J.M., Hoopes, M.F., Holt, R.D., Shurin, J.B., Law, R., Tilman, D., Loreau, M., & Gonzalez, A., 2004. The metacommunity concept: a framework for multi-scale community ecology. Ecol. Lett. 7(7), 601-613. http://dx.doi.org/10.1111/j.1461-0248.2004.00608.x.

Loaiza-Restano, A.M., Marquardt, G.C., Ferragut, C., & Bicudo, C.E.M., 2020. Spatial and temporal variation of the phytoplankton structure in cascading oligotrophic reservoirs of southeast Brazil. Acta Limnol. Bras. 32, e12. http://dx.doi.org/10.1590/s2179-975x7618.

Lund, J.W.G., Kipling, C., & Le Cren, E.D., 1958. The inverted microscope method of estimating algal numbers and the statistical basis of estimations by counting. Hydrobiologia 11(2), 143-170. http://dx.doi.org/10.1007/BF00007865.

Lürling, M., 2021. Grazing resistance in phytoplankton. Hydrobiologia 848(1), 237-249. http://dx.doi.org/10.1007/s10750-020-04370-3.

Machado, K.B., Teresa, F.B., Vieira, L.C.G., Huszar, V.L., & Nabout, J.C., 2016. Comparing the effects of landscape and local environmental variables on taxonomic and functional composition of phytoplankton communities. J. Plankton Res. 38(5), 1334-1346. http://dx.doi.org/10.1093/plankt/fbw062.

Margalef, R., 1983. Limnología. Barcelona: Ediciones Omega, S.A.

Medeiros, G., Padial, A.A., Amaral, M.W.W., Guicho, R., Pilatti, M.C., Sampaio, S.C., Ludwig, T.A.V., Bueno, N.C., & dos Reis, R.R., 2022. Exploring key determinants of the periphytic diatom community in a Southern Brazilian micro-watershed. Water 14(23), 3913. http://dx.doi.org/10.3390/w14233913.

Medeiros, G., Padial, A.A., Wedig Amaral, M.W., Ludwig, T.A.V., & Bueno, N.C., 2020. Environmental variables likely influence the periphytic diatom community in a subtropical lotic environment. Limnologica 80, 125718. http://dx.doi.org/10.1016/j.limno.2019.125718.

Mihaljevic, J.R., 2012. Linking metacommunity theory and symbiont evolutionary ecology. Trends Ecol. Evol. 27(6), 323-329. PMid:22341499. http://dx.doi.org/10.1016/j.tree.2012.01.011.

Mohan, B., & Piryadarshinee, S., 2023. Phytoplankton as bio indicators of water quality in two perennial lakes of Coimbatore district, Tamil Nadu, India. Int. J. Entomol. Res. 8, 10-17.

Mohd-Din, M., Hii, K.S., Abdul-Wahab, M.F., Mohamad, S.E., Gu, H., Leaw, C.P., & Lim, P.T., 2022. Spatial-temporal variability of microphytoplankton assemblages including harmful microalgae in a tropical semi-enclosed strait (Johor Strait, Malaysia). Mar. Environ. Res. 175, 105589. PMid:35228143. http://dx.doi.org/10.1016/j.marenvres.2022.105589.

Moresco, G.A., Bortolini, J.C., Dias, J.D., Pineda, A., Jati, S., & Rodrigues, L.C., 2017. Drivers of phytoplankton richness and diversity components in Neotropical floodplain lakes, from small to large spatial scales. Hydrobiologia 799(1), 203-215. http://dx.doi.org/10.1007/s10750-017-3214-3.

Moresco, G.A., Bortolini, J.C., Rodrigues, L.C., Jati, S., & Machado Velho, L.F., 2020. A functional deconstructive approach to mixotrophic phytoplankton responds better to local, regional and biogeographic predictors than species. Austral Ecol. 45(2), 249-263. http://dx.doi.org/10.1111/aec.12852.

Naselli-Flores, L., & Padisák, J., 2016. Blowing in the wind: how many roads can a phytoplanktont walk down? A synthesis on phytoplankton biogeography and spatial processes. Hydrobiologia 764(1), 303-313. http://dx.doi.org/10.1007/s10750-015-2519-3.

Nobre, R.L.G., Caliman, A., Cabral, C.R., de Carvalho Araújo, F., Guerin, J., Dantas, F.D.C.C., & Carneiro, L.S., 2020. Precipitation, landscape properties and land use interactively affect water quality of tropical freshwaters. Sci. Total Environ. 716, 137044. PMid:32059302. http://dx.doi.org/10.1016/j.scitotenv.2020.137044.

Oksanen, J., Blanchet, F.G., Kindt, R., Legendre, P., Minchin, P.R., O’Hara, R.B., & Oksanen, M. J., 2020. Package ‘vegan’. Community ecology package, version 2.5-7. Vienna: R Foundation for Statistical Computing.

Ormerod, S.J., Durance, I., Hatton-Ellis, T.W., Cable, J., Chadwick, E.A., Griffiths, S., Jones, T.H., Larsen, S., Merrix, F.L., Symondson, W.O.C., Thomas, R.J., & Vaughan, I.P., 2011. Landscape connectivity of freshwater ecosystems: strategic review and recommendations. Bangor: CCW, 117 p., CCW ContractScience Report, no. 932.

Padial, A.A., Ceschin, F., Declerck, S.A.J., De Meester, L., Bonecker, C.C., Lansac-Tôha, F.A., Rodrigues, L., Rodrigues, L.C., Train, S., Velho, L.F.M., & 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.

Pellowe-Wagstaff, K.E., & Simonis, J.L., 2014. The ecology and mechanisms of overflow-mediated dispersal in a rock-pool metacommunity. Freshw. Biol. 59(6), 1161-1172. http://dx.doi.org/10.1111/fwb.12337.

Peng, C., Zou, W., Li, D., Li, G., & Bi, Y., 2022. Distinct effects of sediment regulation on phytoplankton community assembly in the tributaries and mainstream of the Three Gorges Reservoir. J. Clean. Prod. 368, 133082. http://dx.doi.org/10.1016/j.jclepro.2022.133082.

Peres, K.K., Guicho, R., Medeiros, G., Amaral, M.W.W., da Silva, T.T., Pilatti, M.C., Prior, M., & Bueno, N.C., 2022. Environmental fragility as an indicator of the risk of contamination by human action in watersheds used for public supply in western Paraná, Brazil. Environ. Earth Sci. 81(20), 486. http://dx.doi.org/10.1007/s12665-022-10619-y.

Peter, A.P., Khoo, K.S., Chew, K.W., Ling, T.C., Ho, S.H., Chang, J.S., & Show, P.L., 2021. Microalgae for biofuels, wastewater treatment and environmental monitoring. Environ. Chem. Lett. 19(4), 2891-2904. http://dx.doi.org/10.1007/s10311-021-01219-6.

Pourfallah Koushali, H., Mastouri, R., & Khaledian, M.R., 2021. Impact of precipitation and flow rate changes on the water quality of a Coastal River. Shock Vib. 2021, 1-13. http://dx.doi.org/10.1155/2021/6557689.

R Core Team, 2022. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Retrieved in 2023, June 30, from https://www.R-project.org/

Radbruch, L., De Lima, L., Knaul, F., Wenk, R., Ali, Z., Bhatnaghar, S., Blanchard, C., Bruera, E., Buitrago, R., Burla, C., Callaway, M., Munyoro, E.C., Centeno, C., Cleary, J., Connor, S., Davaasuren, O., Downing, J., Foley, K., Goh, C., Gomez-Garcia, W., Harding, R., Khan, Q.T., Larkin, P., Leng, M., Luyirika, E., Marston, J., Moine, S., Osman, H., Pettus, K., Puchalski, C., Rajagopal, M.R., Spence, D., Spruijt, O., Venkateswaran, C., Wee, B., Woodruff, R., Yong, J., & Pastrana, T., 2020. Redefining palliative care: a new consensus-based definition. J. Pain Symptom Manage. 60(4), 754-764. PMid:32387576. http://dx.doi.org/10.1016/j.jpainsymman.2020.04.027.

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

Rocha, B.S., Souza, C.A., Machado, K.B., Vieira, L.C.G., & Nabout, J.C., 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, L.C., Pivato, B.M., Vieira, L.C.G., Bovo-Scomparin, V.M., Bortolini, J.C., Pineda, A., & Train, S., 2018. Use of phytoplankton functional groups as a model of spatial and temporal patterns in reservoirs: a case study in a reservoir of central Brazil. Hydrobiologia 805(1), 147-161. http://dx.doi.org/10.1007/s10750-017-3289-x.

Salton, F.G., Morais, H., & Lohmann, M., 2021. Períodos secos no estado do Paraná. Rev. Bras. Meteorol. 36(2), 295-303. http://dx.doi.org/10.1590/0102-77863620163.

Silva, M.J.L., Pilatti, M.C., Bortolini, J.C., Baumgartner, G., & Bueno, N.C., 2023a. Chlorophyceae and Trebouxiophyceae (Chlorophyta) in lotic environments in the area of influence of the Baixo Iguaçu Hydroelectric Plant, Paraná State, Brazil. SciELO Preprints. In press.

Silva, L.B., Souza, C.A., Vieira, L.C.G., Antonio, E.V.R., & Couto Junior, A.F., 2023b. Local and regional determinants of phytoplankton communities in water reservoirs from the Cerrado biome. Acta Limnol. Bras. 35, e1. http://dx.doi.org/10.1590/s2179-975x5021.

Sistema de Tecnologia e Monitoramento Ambiental do Paraná - SIMEPAR, 2023 [online]. Retrieved in 2023, June 30, from http://www.simepar.org/

Sun, J., 2003. Geometric models for calculating cell biovolume and surface area for phytoplankton. J. Plankton Res. 25(11), 1331-1346. http://dx.doi.org/10.1093/plankt/fbg096.

Tabrez, S., Zughaibi, T.A., & Javed, M., 2022. Water quality index, Labeo rohita, and Eichhornia crassipes: suitable bio-indicators of river water pollution. Saudi J. Biol. Sci. 29(1), 75-82. PMid:35002395. http://dx.doi.org/10.1016/j.sjbs.2021.10.052.

Tang, W., Pei, Y., Zheng, H., Zhao, Y., Shu, L., & Zhang, H., 2022. Twenty years of China’s water pollution control: experiences and challenges. Chemosphere 295, 133875. PMid:35131279. http://dx.doi.org/10.1016/j.chemosphere.2022.133875.

Thompson, P.A., O’Brien, T.D., Paerl, H.W., Peierls, B.L., Harrison, P.J., & Robb, M., 2015. Precipitation as a driver of phytoplankton ecology in coastal waters: a climatic perspective. Estuar. Coast. Shelf Sci. 162, 119-129. http://dx.doi.org/10.1016/j.ecss.2015.04.004.

Utermohl, H., 1958. Zur Ver vollkommung der quantitativen phytoplankton-methodik. Mitt Int Verein Theor Angew Limnol. 9, 39.

Vannote, R.L., Minshall, G.W., Cummins, K.W., Sedell, J.R., & Cushing, C.E., 1980. The river continuum concept. Can. J. Fish. Aquat. Sci. 37(1), 130-137. http://dx.doi.org/10.1139/f80-017.

Viana, D.S., & Chase, J.M., 2019. Spatial scale modulates the inference of metacommunity assembly processes. Ecology 100(2), e02576. PMid:30516271. http://dx.doi.org/10.1002/ecy.2576.

Vörösmarty, C.J., McIntyre, P.B., Gessner, M.O., Dudgeon, D., Prusevich, A., Green, P., Glidden, S., Bunn, S.E., Sullivan, C.A., Liermann, C.R., & Davies, P.M., 2010. Global threats to human water security and river biodiversity. Nature 467(7315), 555-561. PMid:20882010. http://dx.doi.org/10.1038/nature09440.

Wojciechowski, J., Heino, J., Bini, L.M., & Padial, A.A., 2017. The strength of species sorting of phytoplankton communities is temporally variable in subtropical reservoirs. Hydrobiologia 800(1), 31-43. http://dx.doi.org/10.1007/s10750-017-3245-9.

Xu, S., Li, S.-L., Zhong, J., & Li, C., 2020. Spatial scale effects of the variable relationships between landscape pattern and water quality: example from an agricultural karst river basin. Agric. Ecosyst. Environ. 300, 106999. http://dx.doi.org/10.1016/j.agee.2020.106999.

Yang, Y., Chen, H., Abdullah Al, M., Ndayishimiye, J.C., Yang, J.R., Isabwe, A., Luo, A., & Yang, J., 2022. Urbanization reduces resource use efficiency of phytoplankton community by altering the environment and decreasing biodiversity. J. Environ. Sci. 112, 140-151. PMid:34955197. http://dx.doi.org/10.1016/j.jes.2021.05.001.

Yaqoob, M.M., Somlyai, I., Berta, C., Bácsi, I., Al-Tayawi, A.N., Al-Ahmady, K.K., Mohammed, R.H., Alalami, O., & Grigorszky, I., 2023. The impacts of land use and seasonal effects on phytoplankton taxa and physical-chemical variables in the Tigris River within the city of Mosul. Water 15(6), 1062. http://dx.doi.org/10.3390/w15061062.

Zhang, Y., Ma, R., Chu, H., Zhou, X., Yao, T., & Zhang, Y., 2022. Evaluation of the performance of different membrane materials for microalgae cultivation on attached biofilm reactors. RSC Advances 12(3), 1451-1459. PMid:35425202. http://dx.doi.org/10.1039/D1RA07335D.

Zhao, Z., Liu, G., Liu, Q., Huang, C., & Li, H., 2018. Studies on the spatiotemporal variability of river water quality and its relationships with soil and precipitation: a case study of the mun river basin in Thailand. Int. J. Environ. Res. Public Health 15(11), 2466. PMid:30400628. http://dx.doi.org/10.3390/ijerph15112466.
 


Submetido em:
30/06/2023

Aceito em:
20/02/2024

Publicado em:
08/03/2024

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