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Hydrobiologia

, Volume 830, Issue 1, pp 135–149 | Cite as

Interannual hydrological variations and ecological phytoplankton patterns in Amazonian floodplain lakes

  • Cleber Nunes KrausEmail author
  • Marie-Paule Bonnet
  • Cristina Arantes Miranda
  • Ina de Souza Nogueira
  • Jérémie Garnier
  • Ludgero Cardoso Galli Vieira
Primary Research Paper

Abstract

Amazonian aquatic environments are complex, and their interaction promotes heterogeneous environments that in turn make it difficult to describe the development of patterns. Amazonian floodplain lakes have different environmental and biological responses in similar water periods due to the interannual variation. We evaluated if the interannual variations in the physical–chemical structure and the phytoplankton community promote environmentally and biologically contrasted conditions between similar hydrological periods. Phytoplankton community structure has differences between periods, but these differences do not necessarily promote dissimilarities. Most of the phytoplankton species belong to the same functional groups. The compositions of species and functional groups between sample units inside lakes are variable and may or may not have significant differences in dissimilarity, but both periods are equally heterogeneous. Beta diversity has shown that the replacement of species and functional groups causes a high level of variation between sites, which maintain a high heterogeneity between periods. These variations have different responses for different scales turning the interpretation of patterns for these environments a problematic task. Hence, scale and interannual variability are factors that need to be carefully considered when setting standards to describe the ecological dynamics of floodplain lakes in the Amazonian system.

Keywords

Amazonian wetlands Biodiversity Plankton Freshwater Ecology Beta diversity 

Notes

Acknowledgements

The data used in this manuscript were acquired within the framework of the CARBAMA Project (funded by the white program from the French Research Agency ANR 2009–2012); and the CYMENT Project (funded by the RTRA/STAE foundation 2008–2011 supported by the International Joint Laboratory LMI OCE (IRD/University of Brasilia) funded by the IRD and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). The work also received funding from the European Union’s Horizon 2020 Research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 691053. The first author is very grateful to the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes) for providing financial assistance. This article is part of the research activities of the project INCT No 16- 2014 ODISSEIA, with funding from CNPq/Capes/FAPDF.

Supplementary material

10750_2018_3859_MOESM1_ESM.docx (65 kb)
Supplementary material 1 (DOCX 64 kb)

References

  1. Adams, D. G. & P. S. Duggan, 1999. Tansley Review No. 107. Heterocyst and akinete differentiation in cyanobacteria. New Phytologist 144: 3–33.CrossRefGoogle Scholar
  2. Affonso, A., C. Barbosa & E. Novo, 2011. Water quality changes in floodplain lakes due to the Amazon River flood pulse: Lago Grande de Curuaí (Pará). Brazilian Journal of Biology 71: 601–610.CrossRefGoogle Scholar
  3. Alcântara, E., E. M. Novo, C. F. Barbosa, M.-P. Bonnet, J. Stech & J. P. Ometto, 2011. Environmental factors associated with long-term changes in chlorophyll-a concentration in the Amazon floodplain. Biogeosciences Discussions 8: 3739–3770.CrossRefGoogle Scholar
  4. Anderson, M. J., 2001. A new method for non parametric multivariate analysis of variance. Austral Ecology 26: 32–46.Google Scholar
  5. Anderson, M. J., 2006. Distance-based tests for homogeneity of multivariate dispersions. Biometrics 62: 245–253.CrossRefGoogle Scholar
  6. Anderson, M. J., K. E. Ellingsen & B. H. McArdle, 2006. Multivariate dispersion as a measure of beta diversity. Ecology Letters 9: 683–693.CrossRefGoogle Scholar
  7. Angeler, D. G. & S. Drakare, 2013. Tracing alpha, beta, and gamma diversity responses to environmental change in boreal lakes. Oecologia 172: 1191–1202.CrossRefGoogle Scholar
  8. APHA, 1998. Standard Methods for Examination of Water and Wastewater (Standard Methods for the Examination of Water and Wastewater). Standard Methods Washington, D.C., USA. 5–16, https://www.amazon.com/standard-methods-examination-water-wastewater/dp/08.
  9. Baselga, A., 2010. Partitioning the turnover and nestedness components of beta diversity. Global Ecology and Biogeography 19: 134–143.CrossRefGoogle Scholar
  10. Baselga, A. & F. Leprieur, 2015. Comparing methods to separate components of beta diversity. Methods in Ecology and Evolution 6: 1069–1079.CrossRefGoogle Scholar
  11. Beisner, B. E., P. R. Peres-Neto, E. S. Lindström, A. Barnett & M. L. Longhi, 2006. The role of environmental and spatial processes in structuring lake communities from bacteria to fish. Ecology 87: 2985–2991.CrossRefGoogle Scholar
  12. Bonnet, M.-P., G. Barroux, J. M. Martinez, F. Seyler, P. Moreira-Turcq, G. Cochonneau, J. M. Melack, G. Boaventura, L. Maurice-Bourgoin, J. G. León, E. Roux, S. Calmant, P. Kosuth, J. L. Guyot & P. Seyler, 2008. Floodplain hydrology in an Amazon floodplain lake (Lago Grande de Curuaí). Journal of Hydrology 349: 18–30.CrossRefGoogle Scholar
  13. Bonnet, M.-P., S. Pinel, J. Garnier, J. Bois, G. Resende Boaventura, P. Seyler & D. Motta Marques, 2017. Amazonian floodplain water balance based on modelling and analyses of hydrologic and electrical conductivity data. Hydrological Processes 31: 1702–1718.CrossRefGoogle Scholar
  14. Bozelli, R. L., S. M. Thomaz, A. A. A. A. Padial, P. M. Lopes & L. M. Bini, 2015. Floods decrease zooplankton beta diversity and environmental heterogeneity in an Amazonian floodplain system. Hydrobiologia 753: 233–241.CrossRefGoogle Scholar
  15. Carvalho, J. C., P. Cardoso, P. A. V. Borges, D. Schmera & J. Podani, 2013. Measuring fractions of beta diversity and their relationships to nestedness: a theoretical and empirical comparison of novel approaches. Oikos 122: 825–834.CrossRefGoogle Scholar
  16. Chen, J. L., C. R. Wilson & B. D. Tapley, 2010. The 2009 exceptional Amazon flood and interannual terrestrial water storage change observed by GRACE. Water Resources Research 46: 1–10.Google Scholar
  17. Chrisostomou, A., M. Moustaka-Gouni, S. Sgardelis & T. Lanaras, 2009. Air-dispersed phytoplankton in a Mediterranean river-reservoir system (Aliakmon-Polyphytos, Greece). Journal of plankton research Oxford University Press 31: 877–884.CrossRefGoogle Scholar
  18. Chust, G., X. Irigoien, J. Chave & R. P. Harris, 2013. Latitudinal phytoplankton distribution and the neutral theory of biodiversity. Global Ecology and Biogeography 22: 531–543.CrossRefGoogle Scholar
  19. Ciarrocchi, G., A. Fortunato, F. Cobianchi & A. Falaschi, 1976. An intracellular endonuclease of Bacillus subtilis specific for single-stranded DNA. European journal of biochemistry 61: 487–492.CrossRefGoogle Scholar
  20. Davidson, E. A., A. C. de Araújo, P. Artaxo, J. K. Balch, I. F. Brown, M. M. C. Bustamante, M. T. Coe, R. S. DeFries, M. Keller, M. Longo, J. W. Munger, W. Schroeder, B. S. Soares-Filho, C. M. Souza & S. C. Wofsy, 2012. The Amazon basin in transition. Nature 481: 321–328.CrossRefGoogle Scholar
  21. De Oliveira, M. D. & D. F. Calheiros, 2000. Flood pulse influence on phytoplankton communities of the south Pantanal floodplain, Brazil. Hydrobiologia 427: 101–112.CrossRefGoogle Scholar
  22. Dray, S., G. Blanchet, D. Borcard, G. Guenard, T. Jombart, G. Larocque, P. Legendre, N. Madi, & H. Wagner, 2016. Adespatial: multivariate multiscale spatial analysis. R package version 0.0-9.Google Scholar
  23. Forsberg, B. R., J. M. Melack, T. Dunne, R. B. Barthem, M. Goulding, R. C. D. Paiva, M. V. Sorribas, U. L. Silva & S. Weisser, 2017. The potential impact of new Andean dams on Amazon fluvial ecosystems. PLoS ONE 12: e0182254.CrossRefGoogle Scholar
  24. Gianuca, A. T., S. A. J. J. Declerck, P. Lemmens & L. De Meester, 2017. Effects of dispersal and environmental heterogeneity on the replacement and nestedness components of ?-diversity. Ecology 98: 525–533.CrossRefGoogle Scholar
  25. Goes, J. I., H. D. R. Gomes, A. M. Chekalyuk, E. J. Carpenter, J. P. Montoya, V. J. Coles, P. L. Yager, W. M. Berelson, D. G. Capone, R. A. Foster, D. K. Steinberg, A. Subramaniam & M. A. Hafez, 2014. Influence of the Amazon River discharge on the biogeography of phytoplankton communities in the western tropical north Atlantic. Progress in Oceanography Elsevier Ltd 120: 29–40.CrossRefGoogle Scholar
  26. Grasshoff, P., 1983. Methods of Seawater Analysis, Vol. 419. Verlag Chemie, Weinheim: 61–72.Google Scholar
  27. Hess, L. L., J. M. Melack, A. G. Affonso, C. Barbosa, M. Gastil-Buhl & E. M. L. M. Novo, 2015. Wetlands of the lowland amazon basin: extent, vegetative cover, and dual-season inundated area as mapped with JERS-1 synthetic aperture radar. Wetlands 35: 745–756.CrossRefGoogle Scholar
  28. Hillebrand, H., C.-D. Dürselen, D. Kirschtel, U. Pollingher & T. Zohary, 1999. Biovolume calculation for pelagic and benthic microalgae. Journal of Phycology 35: 403–424.CrossRefGoogle Scholar
  29. Hoek, C., H. Van den Hoeck, D. Mann & H. M. Jahns, 1995. Algae: an introduction to phycology. Cambridge University Press, Cambridge.Google Scholar
  30. Howeth, J. G. & M. A. Leibold, 2010. Species dispersal rates alter diversity and ecosystem stability in pond metacommunities. Ecology 91: 2727–2741.CrossRefGoogle Scholar
  31. Huston, M. A., 1999. Variation in the diversity of plants and animals local processes and regional patterns: appropriate scales for understanding variation in the diversity of plants and animals. Oikos 86: 393–401.CrossRefGoogle Scholar
  32. Jespersen, A.-M. & K. Christoffersen, 1987. Measurements of chlorophyll-a from phytoplankton using ethanol as extraction solvent. Archive of Hydrobiology 109: 445–454.Google Scholar
  33. Junk, W. J., M. T. F. Piedade, F. Wittmann, J. Schöngart & P. Parolin, 2010. Amazonian Floodplain Forests: Ecophysiology, Biodiversity and Sustainable Management. Springer, New York.Google Scholar
  34. Junk, W. J., M. T. F. Piedade, J. Schöngart & F. Wittmann, 2012. A classification of major natural habitats of Amazonian white-water river floodplains (várzeas). Wetlands Ecology and Management 20: 461–475.CrossRefGoogle Scholar
  35. Kruk, C., N. Mazzeo, G. Lacerot & C. S. Reynolds, 2002. Classification schemes for phytoplankton: a local validation of a functional approach to the analysis of species temporal replacement. Journal of Plankton Research 24: 901–912.CrossRefGoogle Scholar
  36. Lampert, W. & U. Sommer, 2007. Limnoecology: the ecology of lakes and streams. Oxford University Press, Oxford.Google Scholar
  37. Lawton, J. H., 1999. Are there general laws in ecology? Oikos 84: 177.CrossRefGoogle Scholar
  38. Legendre, P., 2014. Interpreting the replacement and richness difference components of beta diversity. Global Ecology and Biogeography 23: 1324–1334.CrossRefGoogle Scholar
  39. Legendre, P. & M. J. Anderson, 1999. Distance-based redundancy analysis: testing multispecies responses in multifactorial ecological experiments. Ecological Monographs 69: 1–24.CrossRefGoogle Scholar
  40. Legendre, P. & M. De Cáceres, 2013. Beta diversity as the variance of community data: dissimilarity coefficients and partitioning. Ecology Letters 16: 951–963.CrossRefGoogle Scholar
  41. Levin, S. A., 1992. The problem of pattern and scale in ecology: the Robert H. MacArthur award lecture. Ecology 73: 1943–1967.CrossRefGoogle Scholar
  42. Lima-Mendez, G., K. Faust, N. Henry, J. Decelle, S. Colin, F. Carcillo, S. Chaffron, J. C. Ignacio-Espinosa, S. Roux, F. Vincent, L. Bittner, Y. Darzi, J. Wang, S. Audic, L. Berline, G. Bontempi, A. M. Cabello, L. Coppola, F. M. Cornejo-Castillo, F. D’Ovidio, L. De Meester, I. Ferrera, M.-J. Garet-Delmas, L. Guidi, E. Lara, S. Pesant, M. Royo-Llonch, G. Salazar, P. Sanchez, M. Sebastian, C. Souffreau, C. Dimier, M. Picheral, S. Searson, S. Kandels-Lewis, G. Gorsky, F. Not, H. Ogata, S. Speich, L. Stemmann, J. Weissenbach, P. Wincker, S. G. Acinas, S. Sunagawa, P. Bork, M. B. Sullivan, E. Karsenti, C. Bowler, C. de Vargas & J. Raes, 2015. Determinants of community structure in the global plankton interactome. Science 348: 1262073.CrossRefGoogle Scholar
  43. Loverde-Oliveira, S. M. & V. L. M. Huszar, 2007. Phytoplankton ecological responses to the flood pulse in a Pantanal lake, Central Brazil. Acta Limnologica Brasiliensia 19: 117–130.Google Scholar
  44. Lund, J. W. G., C. Kipling & E. D. Le Cren, 1958. The inverted microscope method of estimating algal numbers and the statistical basis of estimations by counting. Hydrobiologia 11: 143–170.CrossRefGoogle Scholar
  45. Machado, K. B., P. P. Borges, F. M. Carneiro, J. F. de Santana, L. C. G. Vieira, V. L. de Moraes Huszar & J. C. Nabout, 2015. Using lower taxonomic resolution and ecological approaches as a surrogate for plankton species. Hydrobiologia 743: 255–267.CrossRefGoogle Scholar
  46. Massol, F., D. Gravel, N. Mouquet, M. W. Cadotte, T. Fukami & M. A. Leibold, 2011. Linking community and ecosystem dynamics through spatial ecology. Ecology Letters 14: 313–323.CrossRefGoogle Scholar
  47. Mcardle, B. H. & M. J. Anderson, 2013. Fitting multivariate models to community data: a comment on distance-based redundancy analysis. Ecology 82: 290–297.CrossRefGoogle Scholar
  48. McGill, B. J., B. J. Enquist, E. Weiher & M. Westoby, 2006. Rebuilding community ecology from functional traits. Trends in Ecology and Evolution 21: 178–185.CrossRefGoogle Scholar
  49. Merico, A., G. Brandt, S. L. Smith & M. Oliver, 2014. Sustaining diversity in trait-based models of phytoplankton communities. Frontiers in Ecology and Evolution 2: 1–8.CrossRefGoogle Scholar
  50. Mitsch, W. J. & J. G. Gosselink, 2007. Wetlands, 4th ed. Wiley, Hoboken.Google Scholar
  51. Oksanen, J., F. G. Blanchet, R. Kindt, P. Legendre, P. R. Minchin, R. B. O’Hara, G. L. Simpson, P. Solymos, M. H. H. Stevens, & H. Wagner, 2013. Package ‘vegan.’ Community ecology package, version 2Google Scholar
  52. Padisák, J., L. O. Crossetti & L. Naselli-Flores, 2009. Use and misuse in the application of the phytoplankton functional classification: a critical review with updates. Hydrobiologia 621: 1–19.CrossRefGoogle Scholar
  53. Paerl, H. W. & T. G. Otten, 2013. Harmful cyanobacterial blooms: causes, consequences, and controls. Microbial Ecology 65: 995–1010.CrossRefGoogle Scholar
  54. Panarelli, E., A. Güntzel & C. Borges, 2013. How does the Taquari River influence in the cladoceran assemblages in three oxbow lakes? Brazilian Journal of Biology 73: 717–725.CrossRefGoogle Scholar
  55. Pimentel, J. S. M. & A. Giani, 2014. Microcystin production and regulation under nutrient stress conditions in toxic Microcystis strains. Applied and Environmental Microbiology 80: 5836–5843.CrossRefGoogle Scholar
  56. Prance, G. T., 1980. A terminologia dos tipos de florestas amazônicas sujeitas a inundação. Acta Amazonica 10: 499–504.CrossRefGoogle Scholar
  57. Ptacnik, R., T. Andersen, P. Brettum, L. Lepistö & E. Willén, 2010. Regional species pools control community saturation in lake phytoplankton. Proceedings Biological Sciences/The Royal Society 277: 3755–3764.CrossRefGoogle Scholar
  58. Rastogi, R. P., R. P. Sinha & A. Incharoensakdi, 2014. The cyanotoxin-microcystins: current overview. Reviews in Environmental Science and Biotechnology 13(2): 215–249.CrossRefGoogle Scholar
  59. Rastogi, R. P., D. Madamwar & A. Incharoensakdi, 2015. Bloom dynamics of cyanobacteria and their toxins: environmental health impacts and mitigation strategies. Frontiers in Microbiology 6: 1–22.CrossRefGoogle Scholar
  60. Reynolds, C. S., V. Huszar, C. Kruk, L. Naselli-Flores & S. S. Melo, 2002. Towards a functional classification of the freshwater phytoplankton. Journal of Plankton Research 24: 417–428.CrossRefGoogle Scholar
  61. Rudorff, C. M., J. M. Melack & P. D. Bates, 2014a. Flooding dynamics on the lower Amazon floodplain: 1. Hydraulic controls on water elevation, inundation extent, and river-floodplain discharge. Water Resources Research 50: 619–634.CrossRefGoogle Scholar
  62. Rudorff, C. M., J. M. Melack & P. D. Bates, 2014b. Flooding dynamics on the lower Amazon floodplain: 2. Seasonal and interannual hydrological variability. Water Resources Research 50: 635–649.CrossRefGoogle Scholar
  63. Salmaso, N., L. Naselli-Flores & J. Padisák, 2015. Functional classifications and their application in phytoplankton ecology. Freshwater Biology 60: 603–619.CrossRefGoogle Scholar
  64. Sampaio, F. P. R., D. G. Aguiar, N. P. Filizola Junior, & T. Schor, 2012. Níveis fluviométricos e o custo de vida em cidades ribeirinhas da Amazônia: O caso de Manacapuru e Óbidos. Symposium SELPER..Google Scholar
  65. Saraiva, D. D., K. S. de Sousa & G. E. Overbeck, 2015. Multiscale partitioning of cactus species diversity in the South Brazilian grasslands: implications for conservation. Journal for Nature Conservation Elsevier GmbH. 24: 117–122.CrossRefGoogle Scholar
  66. Schindler, D. W., 2012. The dilemma of controlling cultural eutrophication of lakes. Proceedings of the Royal Society B: Biological Sciences 279: 4322–4333.CrossRefGoogle Scholar
  67. Schindler, D. W., R. E. Hecky, D. L. Findlay, M. P. Stainton, B. R. Parker, M. J. Paterson, K. G. Beaty, M. Lyng & S. E. M. Kasian, 2008. Eutrophication of lakes cannot be controlled by reducing nitrogen input: results of a 37-year whole-ecosystem experiment. Proceedings of the National Academy of Sciences 105: 11254–11258.CrossRefGoogle Scholar
  68. Schöngart, J. & W. J. Junk, 2007. Forecasting the flood-pulse in Central Amazonia by ENSO-indices. Journal of Hydrology 335: 124–132.CrossRefGoogle Scholar
  69. Sciuto, K. & I. Moro, 2015. Cyanobacteria: the bright and dark sides of a charming group. Biodiversity and Conservation 24: 711–738.CrossRefGoogle Scholar
  70. Sharma, N. K., S. Singh & A. K. Rai, 2006. Diversity and seasonal variation of viable algal particles in the atmosphere of a subtropical city in India. Environmental Research Elsevier 102: 252–259.CrossRefGoogle Scholar
  71. Simberloff, D., 2004. Community ecology: is it time to move on? (An American Society of Naturalists presidential address). The American naturalist. 163: 787–799.CrossRefGoogle Scholar
  72. Sioli, H., 1984. The Amazon and its main affluents: hydrography, morphology of the river courses, and river types. In Sioli, H. (ed.), The Amazon: Limnology and landscape ecology of a mighty tropical river and its basin. Springer, Dordrecht: 127–165.CrossRefGoogle Scholar
  73. Sippel, S. J., S. K. Hamilton & J. M. Melack, 1992. Inundation area and morphometry of lakes on the Amazon River floodplain, Brazil. Archiv Fur Hydrobiologie 123: 385–400.Google Scholar
  74. Stendera, S., R. Adrian, N. Bonada, M. Cañedo-Argüelles, B. Hugueny, K. Januschke, F. Pletterbauer & D. Hering, 2012. Drivers and stressors of freshwater biodiversity patterns across different ecosystems and scales: a review. Hydrobiologia 696: 1–28.CrossRefGoogle Scholar
  75. Sukenik, A., A. Quesada & N. Salmaso, 2015. Global expansion of toxic and non-toxic cyanobacteria: effect on ecosystem functioning. Biodiversity and Conservation 24: 889–908.CrossRefGoogle Scholar
  76. Team, R. C., 2018. R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Austria, 2015. ISBN 3-900051-07-0. http://www.R-project.org.
  77. Thad Scott, J. & M. J. McCarthys, 2010. Nitrogen fixation may not balance the nitrogen pool in lakes over timescales relevant to eutrophication management. Limnology and Oceanography 55: 1265–1270.CrossRefGoogle Scholar
  78. Thomaz, S. M., L. M. Bini & R. L. Bozelli, 2007. Floods increase similarity among aquatic habitats in river-floodplain systems. Hydrobiologia 579: 1–13.CrossRefGoogle Scholar
  79. Tockner, K., F. Malard & J. V. Ward, 2000. An extension of the flood pulse concept. Hydrological Processes 14: 2861–2883.CrossRefGoogle Scholar
  80. Utermöhl, H., 1958. Zur vervollkommnung der quantitativen phytoplankton-methodik. Mitt. int. Ver. theor. angew. Limnol. 9: 1–38.Google Scholar
  81. Wacklin, P., L. Hoffmann & J. Komarek, 2009. Nomenclatural validation of the genetically revised cyanobacterial genus Dolichospermum (Ralfs ex Bornet et Flahault) comb. nova. Fottea 9: 59–64.CrossRefGoogle Scholar
  82. Webb, C. T., J. A. Hoeting, G. M. Ames, M. I. Pyne & N. LeRoy Poff, 2010. A structured and dynamic framework to advance traits-based theory and prediction in ecology. Ecology Letters 13: 267–283.CrossRefGoogle Scholar
  83. Westoby, M. & I. J. Wright, 2006. Land-plant ecology on the basis of functional traits. Trends in Ecology and Evolution 21: 261–268.CrossRefGoogle Scholar
  84. Whittaker, R. H., 1960. Vegetation of the Siskiyou Mountains, Oregon and California Author (s): R. H. Whittaker Published by: Ecological Society of America Stable. http://www.jstor.org/stable/1943563 Your use of the JSTOR archive indicates your acceptance of JSTOR’ s. America 30: 279–338, http://www.jstor.org/stable/1943563.
  85. Wojciechowski, J., J. Heino, L. M. Bini & A. A. Padial, 2017. Temporal variation in phytoplankton beta diversity patterns and metacommunity structures across subtropical reservoirs. Freshwater Biology 62: 751–766.CrossRefGoogle Scholar
  86. Zagmajster, M., D. Eme, C. Fišer, D. Galassi, P. Marmonier, F. Stoch, J. F. Cornu & F. Malard, 2014. Geographic variation in range size and beta diversity of groundwater crustaceans: insights from habitats with low thermal seasonality. Global Ecology and Biogeography 23: 1135–1145.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Cleber Nunes Kraus
    • 1
    • 3
    Email author
  • Marie-Paule Bonnet
    • 2
    • 3
  • Cristina Arantes Miranda
    • 3
  • Ina de Souza Nogueira
    • 4
  • Jérémie Garnier
    • 3
  • Ludgero Cardoso Galli Vieira
    • 1
  1. 1.Environmental Science Post Graduate Program- Universidade de Brasília (UnB)BrasíliaBrazil
  2. 2.UMR 228 Espace-DEV, Institut de Recherche pour le Développement (IRD)MarseilleFrance
  3. 3.Joint International Laboratory LMI OCE “Observatory of Environmental Change’, UnB/IRDBrasíliaBrazil
  4. 4.Environmental Science and Vegetal Biodiversity Post Graduate Programs- Universidade Federal de Goiás (UFG)GoiâniaBrazil

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