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Productivity gradient affects the temporal dynamics of testate amoebae in a neotropical floodplain
Institution:1. State University of Maringa, Brazil;2. Federal University of Southern Bahia, Brazil;1. Centro de Ciências da Natureza, Universidade Federal de São Carlos, Campus Lagoa do Sino, Buri, SP, Brazil;2. Programa de Pós-Graduação em Ecologia e Recursos Naturais, Universidade Federal de São Carlos, São Carlos, SP, Brazil;3. Laboratório de Meiofauna, Universidade de São Paulo, USP, IB, Departamento de Zoologia, São Paulo, SP, Brazil;4. Universidade Estadual Paulista, UNESP, IB, Departamento de Zoologia, Distrito de Rubião Jr., Botucatu, SP, Brazil;1. Department of Botany, University of Wisconsin-Madison, 430 Lincoln Drive, Madison, WI 53706-1381, USA;2. USDA Forest Service, Portland Forestry Sciences Lab, 620 SW Main, Suite 400, Portland, OR 97205, USA;3. USDA Forest Service, Rocky Mountain Research Station, Logan Forestry Sciences Lab, 860 N 1200 E, Logan, UT 84321, USA;1. Environment, University of York, Heslington, York, YO105DD, United Kingdom;2. Department of Zoology and Ecology, Penza State University, Krasnaya str. 40, 440026, Penza, Russia;3. GEOTOP-Université du Québec à Montréal, 201 Avenue Président-Kennedy, Montréal, Québec, H2X 3Y7, Canada;4. Department of Geography, Environment and Earth Sciences, University of Hull, Cottingham Road, Hull, HU6 7RX, United Kingdom;5. Department of Earth and Environmental Sciences, Lehigh University, 1 West Packer Avenue, Bethlehem, PA, 18015-3001, USA;6. Geography, College of Life and Environmental Sciences, University of Exeter, Amory Building, Rennes Drive, Exeter, EX4 4RJ, United Kingdom;7. Natural England, Northminster House, Peterborough, PE1 1UA, United Kingdom;8. Laboratoire Chrono-Environnement, UMR 6249 Université de Franche-Comté/CNRS, UFR Sciences et Techniques, 16 route de Gray, 25030, Besançon, France;9. Geography and Environment, University of Southampton, University Road, Southampton, SO17 1BJ, United Kingdom;10. Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Site Lausanne, Station 2, 1015, Lausanne, Switzerland;11. Department of Biogeography and Palaeoecology, Faculty of Geographical and Geological Science, Adam Mickiewicz University, Poznan, ul. Dziegielowa 27, 61-680, Poznan, Poland;12. School of Geosciences, University of Aberdeen, Elphinstone Road, Aberdeen, AB24 3UF, United Kingdom;13. Department of Hydrobiology, Lomonosov Moscow State University, Leninskiye gory, 1, Moscow, 119991, Russia;14. Laboratory of Soil Biology, University of Neuchâtel, Rue Emile-Argand 11, CH-2000, Neuchâtel, Switzerland;15. Jardin Botanique de Neuchâtel, Pertuis-du-Sault 58, CH-2000, Neuchâtel, Switzerland;p. School of Geography, University of Leeds, Leeds, LS2 9JT, United Kingdom;q. EECRG, Department of Biology, University of Bergen, Allegaten 41, N-5007, Bergen, Norway;1. Brandenburg University of Technology Cottbus-Senftenberg, Dept. General Ecology, 03013 Cottbus, Germany;2. Brandenburg University of Technology Cottbus-Senftenberg, Forschungszentrum Landschaftsentwicklung und Bergbaulandschaften (FZLB), 03013 Cottbus, Germany;3. Leibniz-Centre for Agricultural Landscape Research (ZALF) e.V., Institute of Soil Landscape Research, 15374 Müncheberg, Germany;4. University of Potsdam, Institute of Earth and Environmental Sciences, 14476 Potsdam, Germany;1. Universidade de Brasília (UnB), Campus Planaltina, Área Universitária 1, Vila Nossa Senhora de Fátima, CEP 73345-010, Planaltina, Distrito Federal, Brazil;2. Departamento de Ecologia, Universidade Federal de Goiás, Av. Esperança s/n, CEP 74690-900, Goiânia, Goiás, Brazil;3. Núcleo de Pesquisas em Limnologia, Ictiologia e Aquicultura (NUPELIA), Universidade Estadual de Maringá, Av. Colombo, 5.790, CEP 87020-900, Maringá, Paraná, Brazil;4. Campus de Ciências Exatas e Tecnológica (CCET), Universidade Estadual de Goiás, BR-153, 3.105, CEP 75132-903, Anápolis, Goiás, Brazil;1. Laboratory of Wetland Ecology and Monitoring, Adam Mickiewicz University in Poznań, Krygowskiego 10, 61-680 Poznań, Poland;2. Department of Biogeography and Palaeoecology, Adam Mickiewicz University in Poznań, Krygowskiego 10, 61-680 Poznań, Poland;3. Institute of Plant Sciences and Oeschger Centre for Climate Change Research, University of Bern, Altenbergrain 21, CH-3013 Bern, Switzerland;4. Polish Geological Institute, Ko?cierska 5, 80-328 Gdańsk, Poland;5. Institute of Geological Sciences, Polish Academy of Sciences, Research Centre in Warsaw Twarda St. 51/55, PL-00818 Warsaw, Poland
Abstract:Testate amoeba communities are influenced by temporal variation in the productivity levels in the environment, and may be used as an indicator group for these changing conditions. Here, we analysed the effect of temporal variation in the levels of productivity variables on testate amoeba community of the upper Paraná River floodplain. We evaluated the hypothesis that the frequency and abundance of the testate amoeba community change along an environmental gradient, with different taxa establishing at different points along the gradient in response to changes in the levels of productivity variables. We predicted that the number of species would increase and decrease at points associated with higher and lower levels of productivity variables, respectively. Testate amoeba species were sampled quarterly between 2000 and 2012 from six lakes in the upper Paraná River floodplain, Brazil. We recorded 110 species belonging to 11 families. Threshold Indicator Taxa Analysis identified positive and negative significant shift points in response to the concentration of chlorophyll-a, total nitrogen, and total phosphorus on the frequency and abundance of the testate amoeba community. Our results indicated that change intervals in the levels of productivity variables were associated with the establishment of different taxa. The main bioindicator species of productivity were Difflugia acuminata, D. amphoralis, D. helvetica multilobata, D. kempny, D. lobostoma multilobata, D. parva, D. schurmanni, D. ventricosa, and Lesquereusia ovalis. These species were linked to the increase and decrease in the levels of productivity, confirming the ecological importance of the role of these organisms as bioindicators in aquatic ecosystems.
Keywords:Protozoan  Arcellinida  Threshold productivity  Indicator species  Temporal variation
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