Acta Limnologica Brasiliensia
https://actalb.org/article/doi/10.1590/S2179-975X1222
Acta Limnologica Brasiliensia
Original Article

Taxonomic and morphofunctional phytoplankton response to environmental variability in rivers from different hydrographic basins in Southern Brazil

Resposta taxonômica e morfofuncional do fitoplâncton à variabilidade ambiental em rios de diferentes bacias hidrográficas no sul do Brasil

Thaís Tagliati da Silva; Gabriela Medeiros; Mailor Wellinton Wedig Amaral; Maria Clara Pilatti; Jascieli Carla Bortolini; Norma Catarina Bueno

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Abstract

Abstract:

Aim: Urbanization, agriculture, and deforestation are the main anthropogenic factors that modify the soil, altering the quality of water, and influencing limnological aspects and the aquatic biota in rivers. We investigated the morphology-based taxonomic and functional response (MBFG) of the phytoplankton community among different public supply rivers in distinct hydrographic basins with ultraoligotrophic, oligotrophic, and mesotrophic characteristics.

Methods: We sampled the phytoplankton community and environmental variables in nine rivers along three hydrographic basins in western Paraná. In order to evaluate the taxonomic and functional relationship of the community with the environmental variables, we applied both variance and redundancy analyses.

Results: Differences in temperature, pH, turbidity, total phosphorus, chemical oxygen demand, and total dissolved solids were identified among river basins and/or trophic states. The highest taxonomic contributions to richness and biovolume were from green algae and diatoms, while the highest functional contributions were from MBFG IV (algae without specialized traits), MBFG V (unicellular flagellated algae), MBFG VI (algae with a siliceous exoskeleton) and MBFG (large colonial algae). The taxonomic approach was sensitive to environmental variability in the rivers, while for the functional approach no relationship to environmental variability was identified.

Conclusions: The taxonomic approach of the phytoplankton community was more sensitive to the environmental variability of the studied rivers than the functional approach based on morphology. Therefore, we reinforce the importance of biological indicators for understanding the dynamics in aquatic ecosystems, providing crucial information for the management of water resources used for public supply.
 

Keywords

lotic environments, bioindicators, MBFG, water quality

Resumo

Resumo:

Objetivo: A urbanização, a agricultura e o desmatamento são os principais fatores antropogênicos que modificam o solo, alterando a qualidade da água e influenciado os fatores limnológicos e a biota aquática em rios. Nós investigamos a resposta taxonômica e funcional baseada na morfologia (GFBM) da comunidade fitoplanctônica entre diferentes rios de abastecimento público em distintas bacias hidrográficas com características ultraoligotróficas, oligotróficos e mesotróficas.

Métodos: Amostramos a comunidade fitoplanctônica e as variáveis ambientais em nove rios ao longo de três bacias hidrográficas da região oeste do Paraná. Para avaliar a relação taxonômica e funcional da comunidade com as variáveis ambientais nós aplicamos análises de variância e análises de redundância.

Resultados: A maior contribuição taxonômica para a riqueza e biovolume foram de algas verdes e diatomáceas, enquanto as maiores contribuições funcionais foram dos GFBM IV (algas sem traços especializados), GFBM V (algas unicelulares flageladas), GFBM VI (algas com exoesqueleto silicoso) e GFBM (grandes algas coloniais). Apenas a abordagem taxonômica foi sensível a variabilidade ambiental dos rios, enquanto que para a abordagem funcional não foi identificada nenhuma relação com a variabilidade ambiental.

Conclusões: A abordagem taxonômica da comunidade fitoplanctônica foi mais sensível a variabilidade ambiental dos rios estudados do que a abordagem funcional baseada na morfologia. Portanto, nós reforçamos a importância dos indicadores biológicos para compreensão das dinâmicas em ecossistemas aquáticos, fornecendo informações cruciais para a gestão dos recursos hídricos utilizados para abastecimento público.
 

Palavras-chave

ambientes lóticos, bioindicadores, MBFG, qualidade da água

References

Abonyi, A., Kiss, K.T., Hidas, A., Borics, G., Várbiró, G., & Ács, E., 2020. Cell size decrease and altered size structure of phytoplankton constrain ecosystem functioning in the middle Danube river over multiple decades. Ecosystems 23(6), 1254-1264. PMid:33005096. http://dx.doi.org/10.1007/s10021-019-00467-6.

Abonyi, A., Descy, J.P., Borics, G., & Smeti, E., 2021. From historical backgrounds towards the functional classification of river phytoplankton sensu Colin S. Reynolds: what future merits the approach may hold? Hydrobiologia 848(1), 131-142. http://dx.doi.org/10.1007/s10750-020-04300-3.

Agência Nacional de Águas – ANA, 2020. Conjuntura dos recursos hídricos no Brasil 2020: informe anual. Brasília: ANA, 108 p.

American Public Health Association – APHA , 2017. Standard Methods for the Examination of Wastewater, Washington. DC: APHA.

Anderson, M.J., 2001. A new method for non-parametric multivariate analysis of variance. Austral Ecol. 26, 32-46.

Associação dos Municípios do Oeste do Paraná – AMOP, 2018. Mapa Região da AMOP [online]. Retrieved in 2020, Jan 20, from http://www.amop.org.br/wp-content/uploads/2018/05/MAPA.pdf

Barnard, S., Morgenthal, T.L., Stolz, M., & Venter, A., 2021. Impact of land-use and flow conditions on the phytoplankton of the Sabie River, South Africa. Bothalia 51(1), a6. http://dx.doi.org/10.38201/btha.abc.v51.i1.6.

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

Bohnenberger, J.E., Schneck, F., Crossetti, L.O., Lima, M.S., & Motta-Marques, D.D., 2018. Taxonomic and functional nestedness patterns of phytoplankton communities among coastal shallow lakes in southern Brazil. J. Plankton Res. 40(5), 555-567. http://dx.doi.org/10.1093/plankt/fby032.

Bolgovics, A., Várbíró, G., Ács, E., Trábert, Z., Kiss, K.T., Pozderka, É.V., Görgényi, J., Boda, P., Lukács, B.A., Nagy-László, Z., Abonyi, A., & Borics, G., 2017. Phytoplankton of rhithral rivers: its origin, diversity and possible use for quality-assessment. Ecol. Indic. 81, 587-596. http://dx.doi.org/10.1016/j.ecolind.2017.04.052.

Borcard, D., Gillet, F., & Legendre, P., 2011. Numerical Ecology with R. New York: Springer. http://dx.doi.org/10.1007/978-1-4419-7976-6.

Borics, G., Abonyi, A., Salmaso, N., & Ptacnik, R., 2021. Freshwater phytoplankton diversity: models, drivers and implications for ecosystem properties. Hydrobiologia 848(1), 53-75. PMid:32836348. http://dx.doi.org/10.1007/s10750-020-04332-9.

Bortolini, J.C., Rodrigues, L.C., Jati, S., & Train, S., 2014. Phytoplankton functional and morphological groups as indicators of environmental variability in a lateral channel of the Upper Paraná River floodplain. Acta Limnol. Bras. 26(1), 98-108. http://dx.doi.org/10.1590/S2179-975X2014000100011.

Brasil, J., & Huszar, V.L.M., 2011. O papel dos traços funcionais na ecologia do fitoplâncton continental. Oecol. Aust. 15(4), 799-834. http://dx.doi.org/10.4257/oeco.2011.1504.04.

Bussi, G., Whitehead, P.G., Bowes, M.J., Read, D.S., Prudhomme, C., & Dadson, S.J., 2016. Impacts of climate change, land-use change and phosphorus reduction on phytoplankton in the River Thames (UK). Sci. Total Environ. 572, 1507-1519. PMid:26927961. http://dx.doi.org/10.1016/j.scitotenv.2016.02.109.

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.

Casé, M., Leça, E.E., Leitão, S.N., Sant′Anna, E.E., Schwamborn, R., & de Moraes Junior, A.T., 2008. Plankton community as an indicator of water quality in tropical shrimp culture ponds. Mar. Pollut. Bull. 56(7), 1343-1352. PMid:18538353. http://dx.doi.org/10.1016/j.marpolbul.2008.02.008.

Castro-Roa, D., & Pinilla-Agudelo, G., 2014. Periphytic diatom index for assessing the ecological quality of the Colombian Andean urban wetlands of Bogotá. Limnetica 33, 297-312.

Conceição, L.P., Affe, H.J.M., Silva, D.M.L., & Nunes, J.C.M., 2021. Spatio-temporal variation of the phytoplankton community in a tropical estuarine gradient, under the influence of river damming. Reg. Stud. Mar. Sci. 43, 101642. http://dx.doi.org/10.1016/j.rsma.2021.101642.

Cordoba, J., Perez, E., Van Vlierberghe, M., Bertrand, A.R., Lupo, V., Cardol, P., & Baurain, D., 2021. De novo transcriptome meta-assembly of the mixotrophic freshwater microalga Euglena gracilis. Genes (Basel) 12(6), 842. PMid:34072576. http://dx.doi.org/10.3390/genes12060842.

Cupertino, A., Gücker, B., Von Rückert, G., & Figueredo, C.C., 2019. Phytoplankton assemblage composition as an environmental indicator in routine lentic monitoring: taxonomic versus functional groups. Ecol. Indic. 101, 522-532. http://dx.doi.org/10.1016/j.ecolind.2019.01.054.

Descy, J.P., Leitao, M., Everbecq, E., Smitz, J.S., & Deliège, J.F., 2011. Phytoplankton of the River Loire, France: a biodiversity na modelling study. J. Plankton Res. 34(2), 120-135. http://dx.doi.org/10.1093/plankt/fbr085.

Domingues, C.D., & Torgan, L.C., 2012. Chlorophyta de um lago artificial hipereutrophic no sul do Brasil. Iheringia 67, 75-91.

Fietz, S., Kobanova, G., Izmest’eva, L., & Nicklisch, A., 2005. Regional, vertical and seasonal distribution of phytoplankton and photosynthetic pigments in lake Baikal. J. Plankton Res. 27(8), 793-810. http://dx.doi.org/10.1093/plankt/fbi054.

Gleick, P.H., 2018. Transitions to freshwater sustainability. Perspective PNAS, 115(36), 8863-8871. https://doi.org/10.1073/pnas.1808893115.

Graco-Roza, C., Soininen, J., Corrêa, G., Pacheco, F.S., Miranda, M., Domingos, P., & Marinho, M.M., 2021. Functional rather than taxonomic diversity reveals changes in the phytoplankton community of a large dammed river. Ecol. Indic. 121, 107048. http://dx.doi.org/10.1016/j.ecolind.2020.107048.

Instituto Brasileiro de Geografia e Estatística – IBGE, 2010. Censo demográfico [online]. Retrieved in 2021, Jul 18, from https://www.ibge.gov.br/pt/inicio.html

Jia, J., Gao, Y., Song, X., & Chen, S., 2019. Characteristics of phytoplankton community anda water net primary productivity response to the nutrient status of the poyang lake na gan river, China. Ecohydrology 12(7), 2136. http://dx.doi.org/10.1002/eco.2136.

Jia, X., Fu, B., Feng, X., Hou, G., Liu, Y., & Wang, X., 2014. The tradeoff and synergy between ecosystem services in the grain-for-green areas in Northern Shaanxi, China. Ecol. Indic. 43, 103-111. http://dx.doi.org/10.1016/j.ecolind.2014.02.028.

Kashaigili, J.J., 2008. Impacts of land-use and land-cover changes on flow regimes of the usangu wetland and the Great Ruaha River, Tanzania. Phys. Chem. Earth Parts ABC 33(8-13), 640-647. http://dx.doi.org/10.1016/j.pce.2008.06.014.

Kelly, V., Stets, E.G., & Crawford, C., 2015. Long-term changes in nitrate conditions over the 20th century in two midwestern corn belt streams. J. Hydrol. (Amst.) 525, 559-571. http://dx.doi.org/10.1016/j.jhydrol.2015.03.062.

Kim, J.S., Seo, I.W., & Baek, D., 2019. Seasonally varying effects of environmental factors on phytoplankton abundance in the regulated rivers. Sci. Rep. 9(1), 9266. PMid:31239474. http://dx.doi.org/10.1038/s41598-019-45621-1.

Kruk, C., & Segura, A.M., 2012. The habitat template of phytoplankton morphology-based functional groups. Hydrobiologia 698(1), 191-202. http://dx.doi.org/10.1007/s10750-012-1072-6.

Kruk, C., Devercelli, M., Huszar, V.L.M., Hernández, E., Beamud, G., Diaz, M., Silva, L.H.S., & Segura, A.M., 2017. Classification of Reynolds phytoplankton functional groups using individual traits and machine learning techniques. Freshw. Biol. 62(10), 1681-1692. http://dx.doi.org/10.1111/fwb.12968.

Kruk, C., Huszar, V.L.M., Peeters, E.H.M., Bonilla, S., Costa, L., Lurling, M., Reynolds, C.S., & 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.

Lamparelli, M.C., 2004. Grau de trofia em corpos d’água do estado de São Paulo: avaliação dos métodos de monitoramento [Tese de Doutorado em Ciências na Área de Ecossistemas Terrestres e Aquáticos]. São Paulo: Departamento de Ecologia, Universidade de São Paulo.

Litchman, E., & Klausmeier, C.A., 2008. Trait-based community ecology of phytoplankton. Annu. Rev. Ecol. Evol. Syst. 39(1), 615-639. http://dx.doi.org/10.1146/annurev.ecolsys.39.110707.173549.

Litchman, E., Pinto, T.P., Edwards, F.K., Klausmeier, A.C., Kremer, T.C., & Thomas, K.M., 2015. Global biogeochemical impacts of phytoplankton: a trait-based perspective. J. Ecol. 103(6), 1384-1396. http://dx.doi.org/10.1111/1365-2745.12438.

Lobo, E.A., Heinrich, C.G., Schuch, M., Wetzel, C.E., & Ector, L., 2016. Diatoms as bioindicators in rivers. In: Necchi Junior, O., eds. River Algae. Cham: Springer, 245-271. http://dx.doi.org/10.1007/978-3-319-31984-1_11.

Lötjönen, S., & Ollikainen, M., 2019. Multiple-pollutant cost-efficiency:Coherent water and climate policy for agriculture. Ambio 48(11), 1304-1313. PMid:31552643. http://dx.doi.org/10.1007/s13280-019-01257-z.

Lv, X., Zhang, J., Liang, P., Zhang, X., Yang, K., & Huang, X., 2020. Phytoplankton in an urban river replenished by reclaimed water: Features, influential factors and simulation. Ecol. Indic. 112, 106-090. http://dx.doi.org/10.1016/j.ecolind.2020.106090.

Margalef, R. 1983. Limnología. Barcelona: Omega.

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.

Moresco, C., & Rodrigues, L., 2014. Periphytic diatom as bioindicators in urban and rural streams. Acta Scientiarum 36(1), 67-78.

Oksanen, J., Blanchet, F.G., Friendly, M., Kindt, R., Legendre, P., Mcglinn, P.R., O’Hara, R.B., Simpson, G.L., Solymos, P., Stevens, M.H.H., Szoecs, E., & Wagner, H., 2017. Vegan: Community Ecology Package. R package version, 2, 4-0. USA: Comprehensive R Archive Network.

Pan, Y.Y., Wang, S.T., Chuang, L.T., Chang, Y.W., & Chen, C.N., 2011. Isolation of thermo-tolerant and high lipid content green microalgae: oil accumulation is predominantly controlled by photosystem efficiency during stress treatments in Desmodesmus. Bioresour. Technol. 102(22), 10510-10517. PMid:21925879. http://dx.doi.org/10.1016/j.biortech.2011.08.091.

Paraná, 2006. Institui as diretrizes para a gestão de Bacias Hidrográfica (Resolução nº 024/2006 – SEMA). Diário Oficial do Estado do Paraná, Curitiba, Retrieved in 2021, May 9, from https://celepar7.pr.gov.br/sia/atosnormativos/form_cons_ato1.asp?Codigo=1355 [[Q6: Q6]]

Passy, S.I., 2007. Diatom ecological guilds display distinct and predictable behavior along nutriente and disturbance gradientes in running Waters. Aquat. Bot. 86(2), 171-178. http://dx.doi.org/10.1016/j.aquabot.2006.09.018.

Programa das Nações Unidas para o Desenvolvimento – PNUD, 2018. Panorama ODS: Oeste do Paraná em números. Brasília: PNUD.

R Development Core Team, 2014. R: a language and environment for statistical computing [online]. Vienna, Austria: R Foundation for Statistical Computing. Retrieved in 2021, Jul 18, from http://www.R-project.org/

Rangel, A.J., Lucas, F.H.R., Cavalcante, F.C., Nascimento, K.C.C., Oliveira, E.L.C., & Lacerda, S.R., 2017. Comunidade fitoplanctônica como discriminador ambiental em um trecho do rio salgado, semiárido nordestino. Cad. Cult. Cienc. 15(2), 29-41. http://dx.doi.org/10.14295/cad.cult.cienc.v15i2.1146.

Rao, C.R., 1964. The use and interpretation of principal componente analysis in Applied research. Sankhya 26, 329-358.

Reynolds, C.S., 2006. Ecology of phytoplankton. Cambridge: Cambridge University Press.

Reynolds, C.S., Elliot, J.A., & Frassl, M.A., 2014. Predictive utility of trait-separated phytoplankton groups: a robust approach to modeling population dynamics. J. Great Lakes Res. 40(3), 143-150. http://dx.doi.org/10.1016/j.jglr.2014.02.005.

Rodrigues, S.C., Torgan, L., & Schwarzbold, A., 2007. Composição e variação sazonal da riqueza do fitoplâncton na foz de rios do delta do Jacuí, RS, Brasil. Acta Bot. Bras. 21(3), 707-721. http://dx.doi.org/10.1590/S0102-33062007000300017.

Round, F.E., 1965. The biology of the algae. London: Edward Arnold.

Round, F.E., 1971. The taxonomy of the Chlorophyta, 2. Brit. J. Phycol. 6, 235-26.

Salmaso, N., & Tolotti, M., 2021. Phytoplankton and anthropogenic changes in pelagic environments. Hydrobiologia 848(1), 251-284. http://dx.doi.org/10.1007/s10750-020-04323-w.

Salmaso, N., Naselli-Flores, L., & Padisák, J., 2015. Functional classifications and their application in phytoplankton ecology. Freshw. Biol. 60(4), 603-619. http://dx.doi.org/10.1111/fwb.12520.

Santana, L.M., Moraes, M.E.B., Silva, D.M.L., & Ferragut, C., 2016. Spatial and temporal variation of phytoplankton in a tropical eutrophic river. Braz. J. Biol. 76(3), 600-610. PMid:27097084. http://dx.doi.org/10.1590/1519-6984.18914.

Santos, L.C.R., Lima, S.A., Cavalcanti, B.E., Melo, M.C., & Marques, N.M., 2018. Aplicação de índices para avaliação da qualidade da água da bacia costeira da sapucaia em Sergipe. Eng. Sanit. Ambient. 23(1), 33-46. http://dx.doi.org/10.1590/s1413-41522017159832.

Schulz, U.H., & Martins-Junior, H., 2001. Astyanax fasciatus as bioindicator of water pollution of Rio dos Sinos, RS. Braz. J. Biol. 61(4), 615-622. PMid:12071317. http://dx.doi.org/10.1590/S1519-69842001000400010.

Shi, Y., Eissenstat, D.M., He, Y., & Davis, K.J., 2017. Using a spatially-distributed hydrologic biogeochemistry model with nitrogen transport to study the spatial variation of carbon stocks and fluxes in a Critical Zone Observatory. In: American Geophysical Union Fall Meeting. New Orleans, LA,: Critical Zone Observatories, Dec. 11-15.

Silva, S.C.A., Farias, N.S.N., & Pereira-Junior, A., 2020. Diatomáceas como indicadoras da qualidade da água em rios urbanos. Braz. J. Dev. 6(6), 34616-34643. http://dx.doi.org/10.34117/bjdv6n6-125.

Simić, S.B., Karadžić, V.R., Cavijan, M.V., Vasiljević, B.M., Milačič, R., Ščančar, J., & Paunović, M., 2015. Comunidades de Algal ao longo do rio Sava, The Sava River. Berlin Heidelberg: Springer, 229-248.

Soofiani, N.M., Hatami, R., Hemami, M.R., & Ebrahimi, E., 2012. Effects of trout farm effluent on water quality and the macrobenthic invertebrate community of the Zayandeh-Roud River, Iran. N. Am. J. Aquaculture 74(2), 132-141. http://dx.doi.org/10.1080/15222055.2012.672367.

Species Link, 2021 [online]. Retrieved in 2021, Jul 18, from www.splink.cria.org.br

Sun, J., & Liu, D., 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.

Toledo, A.P., Talarico, M., Chinez, S.J., & Agudo, D., 1983. Aplicação de modelos simplificados para a avaliação de processos de eutrofização em lagos e reservatórios tropicais. In: Anais do Congresso Brasileiro de Engenharia Sanitária, Rio de Janeiro: ABES, 1-34.

Triest, L., Lung’ayia, H., Ndiritu, G., & Beyene, A., 2012. Epilithic diatoms as indicators in tropical African rivers (Lake Victoria catchment). Hydrobiologia 695(1), 343-360. http://dx.doi.org/10.1007/s10750-012-1201-2.

Trindade, R.M.L., Santos, S.M., Souza, C.A., Santos, C.R.A., & Bortolini, J.C., 2021. Using morphofunctional characteristics as a model of phytoplankton dynamics in a tropical reservoir. Braz. J. Bot. 44(2), 467-477. http://dx.doi.org/10.1007/s40415-021-00705-z.

Uhelinger, V., 1964. Étude statistique des methods de dénobrement planctonique. Arch. Sci. 17, 121-223.

Utermöhl, H., 1958. Zur Vervollkommung der quantitativen Phytoplankton-Methodic. Int. Vereinigung Theoretische Angew. Limnol. Mitt. 9, 1-38.

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.

Wan, R., Cai, S., Li, H., Yang, G., Li, Z., & Nie, X., 2014. Inferring land use and land cover impact on stream water quality using a Bayesian hierarchical modeling approach in the Xitiaoxi River Watershed, China. J. Environ. Manage. 133, 1-11. PMid:24342905. http://dx.doi.org/10.1016/j.jenvman.2013.11.035.

Wang, C., Jia, H., Wei, J., Yang, W., Gao, Y., Liu, Q., Ge, D., & Wu, N., 2021. Phytoplankton functional groups as ecological indicators in a subtropical estaurine river delta system. Ecol. Indic. 126, 107-165. http://dx.doi.org/10.1016/j.ecolind.2021.107651.

Xiao, J., Wang, L., Deng, L., & Jin, Z., 2019. Characteristics, sources, water quality and health risk assessment of trace elements in river water and well water in the Chinese Loess Plateau. Sci. Total Environ. 650(Pt 2), 2004-2012. PMid:30290343. http://dx.doi.org/10.1016/j.scitotenv.2018.09.322.

Yang, J., Wang, F., Lv, J., Liu, Q., Nan, F., Liu, X., Xu, L., Xie, S., & Feng, J., 2019. Interactive effects of temperature and nutrients on the phytoplankton community in an urban river in China. Environ. Monit. Assess. 191(11), 688. PMid:31664528. http://dx.doi.org/10.1007/s10661-019-7847-8.

Yang, J.R., Yu, X.Q., Chen, H.H., Kuo, Y.M.M., & Yang, J., 2021. Structural and functional variations of phytoplankton communities in the face of multiple disturbances. J. Environ. Sci. (China) 100, 287-297. PMid:33279042. http://dx.doi.org/10.1016/j.jes.2020.07.026.

Yang, M., Xia, J., Cai, W., Zhou, Z., Yang, L., Zhu, X., & Li, C., 2020. Seasonal and spatial distributions of morpho-functional phytoplankton groups and the role of environmental factors in a subtropical river-type reservoir. Water Sci. Technol. 82(11), 2316-2330. PMid:33339787. http://dx.doi.org/10.2166/wst.2020.489.

Yu, D., Shi, P., Liu, Y., & Xun, B., 2013. Detecting land use-water quality relationships from the viewpoint of ecological restoration in an urban area. Ecol. Eng. 53, 205-216. http://dx.doi.org/10.1016/j.ecoleng.2012.12.045.

Zhang, Y., Peng, C., Huang, S., Wang, J., Xiong, X., & Li, D., 2019. The relative role of spatial and environmental processes on seasonal variations of phytoplankton beta diversity along different anthropogenic disturbances of subtropical rivers in China. Environ. Sci. Pollut. Res. Int. 26(2), 1422-1434. PMid:30426374. http://dx.doi.org/10.1007/s11356-018-3632-4.

Zhang, Z., Gao, J., & Cai, Y., 2020. The direct and indirect effects of land use and water quality on phytoplankton communities in an agriculture-dominated basin. Environ. Monit. Assess. 192(12), 760. PMid:33184779. http://dx.doi.org/10.1007/s10661-020-08728-x.

Zhao, C., Liu, C., Xia, J., Zhang, Y., Yu, Q. & Eamus, D., 2012. Recognition of key regions for restoration of phytoplankton communities in the Huai River basin, China. J. Hydrol. 420-421, 292-300. https://doi.org/10.1016/j.jhydrol.2011.12.016.

Zohary, T., Flaim, G., & Sommer, U., 2021. Temperature and the size of freshwater phytoplankton. Hydrobiologia 848(1), 143-155. http://dx.doi.org/10.1007/s10750-020-04246-6.
 


Submitted date:
02/11/2022

Accepted date:
09/12/2022

Publication date:
09/28/2022

63348da2a953956f72101563 alb Articles
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