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The role of physical habitat and sampling effort on estimates of benthic macroinvertebrate taxonomic richness at basin and site scales

  • Déborah R. O. Silva
  • Raphael Ligeiro
  • Robert M. Hughes
  • Marcos Callisto
Article

Abstract

Taxonomic richness is one of the most important measures of biological diversity in ecological studies, including those with stream macroinvertebrates. However, it is impractical to measure the true richness of any site directly by sampling. Our objective was to evaluate the effect of sampling effort on estimates of macroinvertebrate family and Ephemeroptera, Plecoptera, and Trichoptera (EPT) genera richness at two scales: basin and stream site. In addition, we tried to determine which environmental factors at the site scale most influenced the amount of sampling effort needed. We sampled 39 sites in the Cerrado biome (neotropical savanna). In each site, we obtained 11 equidistant samples of the benthic assemblage and multiple physical habitat measurements. The observed basin-scale richness achieved a consistent estimation from Chao 1, Jack 1, and Jack 2 richness estimators. However, at the site scale, there was a constant increase in the observed number of taxa with increased number of samples. Models that best explained the slope of site-scale sampling curves (representing the necessity of greater sampling effort) included metrics that describe habitat heterogeneity, habitat structure, anthropogenic disturbance, and water quality, for both macroinvertebrate family and EPT genera richness. Our results demonstrate the importance of considering basin- and site-scale sampling effort in ecological surveys and that taxa accumulation curves and richness estimators are good tools for assessing sampling efficiency. The physical habitat explained a significant amount of the sampling effort needed. Therefore, future studies should explore the possible implications of physical habitat characteristics when developing sampling objectives, study designs, and calculating the needed sampling effort.

Keywords

Sampling efficiency Biodiversity Richness estimators Physical habitat 

Notes

Acknowledgments

We thank Companhia Energética de Minas Gerais (CEMIG), Projeto de Pesquisa e Desenvolvimento da Agência Nacional de Energia Elétrica (P&D ANEEL) (GT-487), and Programa Peixe-Vivo for research funding. Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo a Pesquisa do estado de Minas Gerais (FAPEMIG), and Fulbright-Brasil provided financial support. MC was awarded research productivity CNPq (no. 303380/2015-2) and research project CNPq (no. 446155/2014-4), and Minas Gerais research grant FAPEMIG PPM-IX - 00525-15. Special thanks to colleagues from the Laboratório de Ecologia de Bentos-UFMG for sample collection and processing assistance.

References

  1. Allan, J. D. (2004). Landscapes and riverscapes: the influence of land use on stream ecosystems. Annual Review of Ecology, Evolution, and Systematics, 35, 257–284.CrossRefGoogle Scholar
  2. Allan, J. D., & Flecker, A. S. (1993). Biodiversity conservation in running waters. BioScience, 43(1), 32–43.CrossRefGoogle Scholar
  3. Arita, H. T., & Vázquez-Domínguez, E. (2008). The tropics: cradle, museum or casino? A dynamic null model for latitudinal gradients of diversity. Ecology Letters, 11(7), 653–663.CrossRefGoogle Scholar
  4. Bady, P., Doledec, S., Fesl, C., Gayraud, S., Bacchi, M., & Scholl, F. (2005). Use of invertebrate traits for biomonitoring of European large rivers: the effects of sampling effort on genus richness and functional diversity. Freshwater Biology, 50(1), 159–173.CrossRefGoogle Scholar
  5. Bartsch, L. A., Richardson, W. B., & Naimo, T. J. (1998). Sampling benthic macroinvertebrates in a large flood-plain river: considerations of study design, sample size, and cost. Environmental Monitoring and Assessment, 52(3), 425–439.CrossRefGoogle Scholar
  6. Basualdo, C. V. (2011). Choosing the best non-parametric richness estimator for benthic macroinvertebrates databases. Revista de la Sociedad Entomológica Argentina, 70(1–2), 27–38.Google Scholar
  7. Bonada, N., Prat, N., Resh, V. H., & Statzner, B. (2006). Developments in aquatic insect biomonitoring: a comparative analysis of recent approaches. Annual Review of Entomology, 51, 495–523.CrossRefGoogle Scholar
  8. Brasil. (1992). Normais Climatológicas (1960–1990). Ministério da Agricultura e Reforma Agrária, Secretaria Nacional de Irrigação, Departamento Nacional de Meteorologia, Brasília, 84 pGoogle Scholar
  9. Brown, R. L., Jacobs, L. A., & Peet, R. K. (2007). Species richness: small scale. In Encyclopedia of Life Sciences (pp. 1–8). John Wiley & Sons Ltd.Google Scholar
  10. Burnham, K. P., & Overton, W. S. (1978). Estimation of the size of a closed population when capture probabilities vary among animals. Biometrika, 65(3), 625–633.CrossRefGoogle Scholar
  11. Buss, D. F., & Vitorino, A. S. (2010). Rapid bioassessment protocols using benthic macroinvertebrates in Brazil: evaluation of taxonomic sufficiency. Journal of the North American Benthological Society, 29(2), 562–571.CrossRefGoogle Scholar
  12. Buss, D. F., Carlisle, D. M., Chon, T. S., Culp, J., Harding, J. S., Keizer-Vlek, H. E., Robinson, W. A., Strachan, S., Thirion, C., & Hughes, R. M. (2015). Stream biomonitoring using macroinvertebrates around the globe: a comparison of large-scale programs. Environmental Monitoring and Assessment, 187(1), 4132.CrossRefGoogle Scholar
  13. Cao, Y., Larsen, D. P., & Hughes, R. M. (2001). Evaluating sampling sufficiency in fish assemblage surveys: a similarity-based approach. Canadian Journal of Fisheries and Aquatic Sciences, 58(9), 1782–1793.CrossRefGoogle Scholar
  14. Cao, Y., Larsen, D. P., Hughes, R. M., Angermeier, P. L., & Patton, T. M. (2002). Sampling effort affects multivariate comparisons of stream communities. Journal of the North American Benthological Society, 21(4), 701–714.CrossRefGoogle Scholar
  15. Cao, Y., Williams, D. D., & Williams, N. E. (1998). How important are rare species in aquatic community ecology bioassessment? Limnology and Oceanography, 43(7), 1403–1409.CrossRefGoogle Scholar
  16. Chao, A. (1984). Nonparametric estimation of the number of classes in a population. Scandinavian Journal of Statistics, 11(4), 265–270.Google Scholar
  17. Chao, A. (2005). Species estimation and applications. In N. Balakrishnan, C. B. Read, & B. Vidakovic (Eds.), Encyclopedia of statistical sciences (pp. 7909–7916). New York: Wiley.Google Scholar
  18. Chen, K., Hughes, R. M., Xu, S., Zhang, J., Cai, D., & Wang, B. (2014). Evaluating performance of macroinvertebrate-based adjusted and unadjusted multi-metric indices (MMI) using multi-season and multi-year samples. Ecological Indicators, 36, 142–151.CrossRefGoogle Scholar
  19. Clarke, A., Macnally, R., Bond, N. R., & Lake, P. S. (2008). Macroinvertebrate diversity in headwater streams: a review. Freshwater Biology, 53(9), 1707–1721.CrossRefGoogle Scholar
  20. Cole, M. B. (2004). Assessment of macroinvertebrate communities in and adjacent to the city of Wilsonville, Oregon. Oregon: Unpublished report prepared for the City of Wilsonville.Google Scholar
  21. Colwell, R. K. (2006). EstimateS: statistical estimation of species richness and shared species from samples. Version 8. Persistent URL < purl.oclc.org/estimates>Google Scholar
  22. Connolly, N. M., Crossland, M. R., & Pearson, R. G. (2004). Effect of low dissolved oxygen on survival, emergence, and drift of tropical stream macroinvertebrates. Journal of the North American Benthological Society, 23(2), 251–270.CrossRefGoogle Scholar
  23. Costa, C., Ide, S., & Simonka, C. E. (2006). Insetos imaturos - metamorfose e identificação. Ribeirão Preto: Holos Editora.Google Scholar
  24. Dodds, W. K. (2002). Freshwater ecology: concepts and environmental applications. San Diego: Academic Press.Google Scholar
  25. dos Anjos, M. B., & Zuanon, J. (2007). Sampling effort and fish species richness in small terra firme forest streams of central Amazonia, Brazil. Neotropical Ichthyology, 5(1), 45–52.CrossRefGoogle Scholar
  26. Drury, D. M., & Kelso, W. E. (2000). Invertebrate colonization of woody debris in coastal plain streams. Hydrobiologia, 434(1), 63–72.CrossRefGoogle Scholar
  27. Feio, M. J., Ferreira, W. R., Macedo, D. R., Eller, A. P., Alves, C. B. M., França, J. S., & Callisto, M. (2013). Defining and testing targets for the recovery of tropical streams based on macroinvertebrates communities and abiotic conditions. River Research and Applications, 31(1), 70–85.CrossRefGoogle Scholar
  28. Fernández, H. R., & Domínguez, E. (2001). Guia para la determinación de los artrópodos bentônicos sudamericanos. Tucumán: Universidad Nacional de Tucumán.Google Scholar
  29. Ferreira, W. R., Ligeiro, R., Macedo, D. R., Hughes, R. M., Kaufmann, P. R., Oliveira, L. G., & Callisto, M. (2014). Importance of environmental factors for the richness and distribution of benthic macroinvertebrates in tropical headwater streams. Freshwater Science, 33(3), 860–871.CrossRefGoogle Scholar
  30. Ferreira, W. R., Paiva, L. T., & Callisto, M. (2011). Development of a benthic multimetric index for biomonitoring of a neotropical watershed. Brazilian Journal of Biology, 71(1), 15–25.CrossRefGoogle Scholar
  31. Freemark, K. E., Meyers, M., White, D., Warman, L. D., Kiester, A. R., & Lumban-Tobing, P. (2006). Species richness and biodiversity conservation priorities in British Columbia, Canada. Canadian Journal of Zoology, 84(1), 20–31.CrossRefGoogle Scholar
  32. Gaston, K. J. (2000). Global patterns in biodiversity. Nature, 405, 220–227.CrossRefGoogle Scholar
  33. Gerth, W. J., & Herlihy, A. T. (2006). Effect of sampling different habitat types in regional macroinvertebrate bioassessment surveys. Journal of the North American Benthological Society, 25(2), 501–512.CrossRefGoogle Scholar
  34. Gotelli, N. J., & Colwell, R. K. (2001). Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecology Letters, 4(4), 379–391.CrossRefGoogle Scholar
  35. Gotelli, N. J., & Colwell, R. K. (2010). Estimating species richness. In A. E. Magurran & B. J. McGill (Eds.), Biological diversity: frontiers in measurement and assessment (pp. 39–54). Oxford: Oxford University Press.Google Scholar
  36. Haggerty, S. M., Batzer, D. P., & Jackson, C. R. (2004). Macroinvertebrate response to logging in coastal headwater streams of Washington, USA. Canadian Journal of Fisheries and Aquatic Sciences, 61(4), 529–537.CrossRefGoogle Scholar
  37. Hawkins, C. P., Norris, R. H., Hogue, J. N., & Feminella, J. W. (2000). Development and evaluation of predictive models for measuring the biological integrity of streams. Ecological Applications, 10(5), 1456–1477.CrossRefGoogle Scholar
  38. Heino, J. (2002). Concordance of species richness patterns among multiple freshwater taxa: a regional perspective. Biodiversity and Conservation, 11(1), 137–147.CrossRefGoogle Scholar
  39. Heino, J. (2011). A macroecological perspective of diversity patterns in the freshwater realm. Freshwater Biology, 56(9), 1703–1722.CrossRefGoogle Scholar
  40. Hering, D., Borja, A., Carstensen, J., Carvalho, L., Elliott, M., Feld, C. K., Heiskanen, A.-S., Johnson, R. K., Moe, J., Pont, D., Solheim, A. L., & van de Bund, W. (2010). The European Water Framework Directive at the age of 10: a critical review of the achievements with recommendations for the future. Science of the Total Environment, 408(19), 4007–4019.CrossRefGoogle Scholar
  41. Hughes, R. M., & Peck, D. V. (2008). Acquiring data for large aquatic resource surveys: the art of compromise among science, logistics, and reality. Journal of the North American Benthological Society, 27(4), 837–859.CrossRefGoogle Scholar
  42. Hughes, R. M., Herlihy, A. T., Gerth, W. J., & Pan, Y. (2012). Estimating vertebrate, benthic macroinvertebrate and diatom taxa richness in raftable Pacific Northwest rivers for bioassessment purposes. Environmental Monitoring and Assessment, 184(5), 3185–3198.CrossRefGoogle Scholar
  43. Hughes, R. M., Kaufmann, P. R., Herlihy, A. T., Intelmann, S. S., Corbett, S. C., Arbogast, M. C., & Hjort, R. C. (2002). Electrofishing distance needed to estimate fish species richness in raftable Oregon rivers. North American Journal of Fisheries Management, 22(4), 1229–1240.CrossRefGoogle Scholar
  44. Hulbert, S. H. (1971). The nonconcept of species diversity: a critique and alternative parameters. Ecology, 52(4), 577–585.CrossRefGoogle Scholar
  45. Johnson, Z. B., & Kennedy, J. H. (2003). Macroinvertebrate assemblages of submerged woody debris in the Elm Fork of the Trinity River, Texas. Journal of Freshwater Ecology, 18(2), 187–197.CrossRefGoogle Scholar
  46. Jones, F. C. (2008). Taxonomic sufficiency: the influence of taxonomic resolution on freshwater bioassessments using benthic macroinvertebrates. Environmental Reviews, 16, 45–69.CrossRefGoogle Scholar
  47. Kaller, M. D., & Kelso, W. E. (2007). Association of macroinvertebrate assemblages with dissolved oxygen concentration and wood surface area in selected subtropical streams of the southeastern USA. Aquatic Ecology, 41(1), 95–110.CrossRefGoogle Scholar
  48. Kaufmann, P. R., Levine, P., Robison, E. G., Seeliger, C., & Peck, D. V. (1999). Quantifying physical habitat in wadeable streams EPA/620/R-99/003. Washington, DC: US Environmental Protection Agency.Google Scholar
  49. Klemm, D. J., Blocksom, K. A., Fulk, F. A., Herlihy, A. T., Hughes, R. M., Kaufmann, P. R., Peck, D. V., Stoddard, J. L., Thoeny, W. T., Griffith, M. B., & Davis, W. S. (2003). Development and evaluation of a macroinvertebrate Biotic Integrity Index (MBII) for regionally assessing mid-atlantic highlands streams. Environmental Management, 31(5), 656–669.CrossRefGoogle Scholar
  50. Leitão, R. P., Zuanon, J., Villéger, S., Williams, S. E., Baraloto, C., Fortunel, C., Mendoça, F. P., & Mouillot, D. (2016). Rare species contribute disproportionately to the functional structure of species assemblages. Proceedings of the Royal Society B. doi: 10.1098/rspb.2016.0084.Google Scholar
  51. Lenat, D. R., & Resh, V. H. (2001). Taxonomy and stream ecology—the benefits of genus- and species-level identifications. Journal of the North American Benthological Society, 20(2), 287–298.CrossRefGoogle Scholar
  52. Li, J., Herlihy, A., Gerth, W., Kaufmann, P., Gregory, S., Urquhart, S., & Larsen, D. P. (2001). Variability in stream macroinvertebrates at multiple spatial scales. Freshwater Biology, 46(1), 87–97.CrossRefGoogle Scholar
  53. Li, L., Liu, L., Hughes, R. M., Cao, Y., & Wang, X. (2014). Towards a protocol for stream macroinvertebrate sampling in China. Environmental Monitoring and Assessment, 186(1), 469–479.CrossRefGoogle Scholar
  54. Ligeiro, R., Ferreira, W., Hughes, R. M., & Callisto, M. (2013a). The problem of using fixed-area subsampling methods to estimate macroinvertebrate richness: a case study with Neotropical stream data. Environmental Monitoring and Assessment, 185(5), 4077–4085.CrossRefGoogle Scholar
  55. Ligeiro, R., Hughes, R. M., Kaufmann, P. R., Macedo, D. R., Firmiano, K. R., Ferreira, W. R., Oliveira, D., Melo, A. S., & Callisto, M. (2013b). Defining quantitative stream disturbance gradients and the additive role of habitat variation to explain macroinvertebrate taxa richness. Ecological Indicators, 25, 45–57.CrossRefGoogle Scholar
  56. Ligeiro, R., Melo, A. S., & Callisto, M. (2010). Spatial scale and the diversity of macroinvertebrates in a Neotropical catchment. Freshwater Biology, 55(2), 424–435.CrossRefGoogle Scholar
  57. Lorenz, A., Kirchner, L., & Hering, D. (2004). ‘Electronic subsampling’ of macrobenthic samples: how many individuals are needed for a valid assessment result? Hydrobiologia, 516(1), 299–312.CrossRefGoogle Scholar
  58. Macedo, D. R., Hughes, R. M., Ferreira, W. R., Firmiano, K. R., Silva, D. R., Ligeiro, R., Kaufmann, P. R., & Callisto, M. (2016). Development of a benthic macroinvertebrate multimetric index (MMI) for Neotropical Savanna headwater streams. Ecological Indicators, 64, 132–141.Google Scholar
  59. Macedo, D. R., Hughes, R. M., Ligeiro, R., Ferreira, W. R., Castro, M. A., Junqueira, N. T., Oliveira, D. R., Firmiano, K. R., Kaufmann, P. R., Pompeu, P. S., & Callisto, M. (2014). The relative influence of catchment and site variables on fish and macroinvertebrate richness in cerrado biome streams. Landscape Ecology, 29(6), 1001–1016.CrossRefGoogle Scholar
  60. Magurran, A. E. (2004). Measuring biological diversity. Oxford: Blackwell Science Ltd.Google Scholar
  61. Mao, C. X., & Colwell, R. K. (2005). Estimation of species richness: mixture models, the role of rare species, and inferential challenges. Ecology, 86(5), 1143–1153.CrossRefGoogle Scholar
  62. Martínez-Sanz, C., García-Criado, F., Fernández-Aláez, C., & Fernández-Aláez, M. (2010). Assessment of richness estimation methods on macroinvertebrate communities of mountain ponds in Castilla y León (Spain). Annales de Limnologie - International Journal of Limnology, 46(2), 101–110.CrossRefGoogle Scholar
  63. McGarvey, D. J., & Terra, B. F. (2015). Using river discharge to model and deconstruct the latitudinal diversity gradient for fishes of the Western Hemisphere. Journal of Biogeography. doi: 10.1111/jbi.12618.Google Scholar
  64. Meir, E., Andelman, S., & Possingham, H. P. (2004). Does conservation-planning matter in a dynamic and uncertain world? Ecology Letters, 7(8), 615–622.CrossRefGoogle Scholar
  65. Melo, A. S. (2004). A critique of the use of jackknife and related non-parametric techniques to estimate species richness. Community Ecology, 5(2), 149–157.CrossRefGoogle Scholar
  66. Melo, A. S., & Froehlich, C. G. (2001). Evaluation of methods for estimating macroinvertebrate species richness using individual stones in tropical streams. Freshwater Biology, 46(6), 711–721.CrossRefGoogle Scholar
  67. Mereta, S. T., Boets, P., Bayih, A. A., Malu, A., Ephrem, Z., Sisay, A., Endale, H., Yitbarek, M., Jemal, A., De Meester, L., & Goethals, P. L. M. (2012). Analysis of environmental factors determining the abundance and diversity of macroinvertebrate taxa in natural wetlands of Southwest Ethiopia. Ecological Informatics, 7(1), 52–61.CrossRefGoogle Scholar
  68. Merritt, R. W., & Cummins, K. W. (1996). An introduction to the aquatic insects of North America. Dubuque: Kendall/Hunt.Google Scholar
  69. Monk, W. A., Wood, P. J., Hannah, D. M., Extence, C. A., Chadd, R. P., & Dunbar, M. J. (2012). How does macroinvertebrate taxonomic resolution influence ecohydrological relationships in riverine ecosystems. Ecohydrology, 5(1), 36–45.CrossRefGoogle Scholar
  70. Moreno, P., França, J. S., Ferreira, W. R., Paz, A. D., Monteiro, I. M., & Callisto, M. (2010). Factors determining the structure and distribution of benthic invertebrate assemblages in a tropical basin. Neotropical Biology and Conservation, 5(3), 135–145.CrossRefGoogle Scholar
  71. Moya, N., Hughes, R. M., Domínguez, E., Gibon, F. M., Goitia, E., & Oberdorff, T. (2011). Macroinvertebrate-based multimetric predictive models for measuring the biotic condition of Bolivian streams. Ecological Indicators, 11(3), 840–847.CrossRefGoogle Scholar
  72. Mugnai, R., Nessimian, J. L., & Baptista, D. F. (2010). Manual de identificação de macroinvertebrados aquáticos do Estado do Rio de Janeiro. Rio de Janeiro: Technical Books.Google Scholar
  73. Myers, N., Mittermeier, R. A., Mittermeier, C. G., Da Fonseca, G. A. B., & Kent, J. (2000). Biodiversity hotspots for conservation priorities. Nature, 403, 853–858.CrossRefGoogle Scholar
  74. Oberdorff, T., Guegan, J. F., & Hugueny, B. (1995). Global scale patterns of fish species richness in rivers. Ecography, 18(4), 345–352.CrossRefGoogle Scholar
  75. Oliveira, R. B. S., Baptista, D. F., Mugnai, R., Castro, C. M., & Hughes, R. M. (2011). Towards rapid bioassessment of wadeable streams in Brazil: development of the Guapiaçu-Macau Multimetric Index (GMMI) based on benthic macroinvertebrates. Ecological Indicators, 11(6), 1584–1593.CrossRefGoogle Scholar
  76. Oliveira, R. B. S., Mugnai, R., Castro, C. M., & Baptista, D. F. (2010). Determining subsampling effort for the development of a rapid bioassessment using benthic macroinvertebrates in streams of Southeastern Brazil. Environmental Monitoring and Assessment, 175(1), 75–85.Google Scholar
  77. Olsen, A. R., & Peck, D. V. (2008). Survey design and extent estimates for the Wadeable Streams Assessment. Journal of the North American Benthological Society, 27(4), 822–836.CrossRefGoogle Scholar
  78. Peck, D. V., Herlihy, A. T., Hill, B. H., Hughes, R. M., Kaufmann, P. R., Klemm, D. J., Lazorchak, J. M., McCormick, F. H., Peterson, S. A., Ringold, P. L., Magee, T., & Cappaert, M. R. (2006). Environmental Monitoring and Assessment Program-Surface Waters: Western Pilot Study field operations manual for wadeable streams (EPA/620/R-06/003). DC: USEPA.Washington.Google Scholar
  79. Pérez, G. R. (1988). Guía para el estudio de los macroinvertebrados acuáticos del Departamento de Antioquia. Bogotá: Editorial Presencia Ltda.Google Scholar
  80. Petersen, F. T., & Meier, R. (2003). Testing species-richness estimation methods on single-sample collection data using the Danish Diptera. Biodiversity and Conservation, 12(4), 667–686.CrossRefGoogle Scholar
  81. Schneck, F., & Melo, A. S. (2010). Reliable sample sizes for estimating similarity among macroinvertebrate assemblages in tropical streams. Annales de Limnologie - International Journal of Limnology, 46(2), 93–100.CrossRefGoogle Scholar
  82. Silva, D. R., Ligeiro, R., Hughes, R. M., & Callisto, M. (2014). Visually determined stream mesohabitats influence benthic macroinvertebrate assessments in headwater streams. Environmental Monitoring and Assessment, 186(9), 5479–5488.CrossRefGoogle Scholar
  83. Stoddard, J. L., Herlihy, A. T., Peck, D. V., Hughes, R. M., Whittier, T. R., & Tarquinio, E. (2008). A process for creating multi-metric indices for large-scale aquatic surveys. Journal of the North American Benthological Society, 27(4), 878–891.CrossRefGoogle Scholar
  84. Stout, J., & Vandermeer, J. (1975). Comparison of species richness for stream-inhabiting insects in tropical and midlatitude streams. The American Naturalist, 109(967), 263–280.CrossRefGoogle Scholar
  85. Systat Software Inc. (2009). SYSTAT statistical package, version 13.0. San Jose, CA: Systat Software, Inc.Google Scholar
  86. Vlek, H. E., Sporka, F., & Krno, I. (2006). Influence of macroinvertebrate sample size on bioassessment of streams. Hydrobiologia, 566(1), 523–542.CrossRefGoogle Scholar
  87. Walther, B. A., & Morand, S. (1998). Comparative performance of species richness estimation methods. Parasitology, 116(4), 395–405.CrossRefGoogle Scholar
  88. Wang, L., Lyons, J., Kanehl, P., & Gatti, R. (1997). Influences of watershed land use on habitat quality and biotic integrity in Wisconsin streams. Fisheries, 22(6), 6–12.CrossRefGoogle Scholar
  89. Wantzen, K. M. (2003). Cerrado streams - characteristics of a threatened freshwater ecosystem type on the tertiary shields of South America. Amazoniana, 17(3–4), 485–502.Google Scholar
  90. Wantzen, K. M., Siqueira, A., Nunes Da Cunha, C., & Sá, M. F. P. (2006). Stream-valley systems of the Brazilian cerrado: impact assessment and conservation scheme. Aquatic Conservation: Marine and Freshwater Ecosystems, 16(7), 713–732.CrossRefGoogle Scholar
  91. Whittier, T. R., & Van Sickle, J. (2010). Macroinvertebrate tolerance values and an assemblage tolerance index (ATI) for western USA streams and rivers. Journal of the North American Benthological Society, 29(3), 852–866.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Déborah R. O. Silva
    • 1
  • Raphael Ligeiro
    • 2
  • Robert M. Hughes
    • 3
  • Marcos Callisto
    • 1
  1. 1.Universidade Federal de Minas Gerais, Departamento de Biologia GeralInstituto de Ciências BiológicasBelo HorizonteBrazil
  2. 2.Universidade Federal do Pará, Departamento de Biologia GeralInstituto de Ciências BiológicasBelémBrazil
  3. 3.Amnis Opes Institute and Department of Fisheries and WildlifeOregon State UniversityCorvallisUSA

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