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Species tolerance degree to soil conditions shaping plant communities

  • Vinícius Andrade MaiaEmail author
  • Cléber Rodrigo de Souza
  • Rubens Manoel dos Santos
Article

Abstract

Understanding vegetation-environment relationships enables perceiving past and present patterns and to predict responses to future scenarios, thereby being useful for conservation and understanding evolutionary processes. In this context, the objective of our study was to test the hypothesis that niche processes at local scales (< 1 km2) are significantly expressive in plant communities structuring. For this, we selected the more representative and widely distributed sampled species, and then modelled their representativeness as a function of edaphic variables. The data were obtained in four fragments of seasonal semi-deciduous forests located in a transition area between the Atlantic and Cerrado biogeographic domains, Brazil. A total of 92 plots with 63 of 400 m2 and 29 of 300 m2 were randomly distributed in the fragments. Individuals that reached the inclusion criterion (circumference at breast height ≥ 15.7 cm) in each plot were measured and identified and soil samples were also collected. Then, we calculated the relative abundance and relative basal area in each plot. All species showed significant relationships with the soil variables, as their representativeness showed to be correlated (positively and/or negatively) with at least one restrictive fertility or texture condition. Therefore, the results confirm the tested hypothesis, evidencing the niche processing role in community structuring through the species tolerance degree to soil conditions.

Keywords

Vegetation Neotropical Niche Ecotone Phosphorus Aluminium Soil organic matter 

Notes

Acknowledgements

The authors wish to thank the Federal University of Lavras (UFLA), Foundation for the Support to the Researches in Minas Gerais (FAPEMIG), the Brazilian National Council for Scientific and Technological Development (CNPq), and the Coordination for the Improvement of Higher Education Personnel (CAPES) for all the support.

Supplementary material

12224_2019_9341_MOESM1_ESM.docx (24 kb)
ESM 1 (DOCX 23 kb)

References

  1. Allen K, Dupuy JM, Gei MG, Hulshof C, Medvigy D, Pizano C, Salgado-Negret B, Smith CM, Trierweiler A, Van Bloem SJ, Waring BG, Xu X, Powers JS (2017) Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes? Environm Res Letters 12:023001CrossRefGoogle Scholar
  2. APG III – The Angiosperm Phylogeny Group (2009) An update of the angiosperm phylogeny group classification for the orders and families of flowering plants: APG III. Bot J Linn Soc 161:105–121Google Scholar
  3. Arruda DM, Fernandes-Filho EI, Solar RR, Schaefer CE (2017) Combining climatic and soil properties better predicts covers of Brazilian biomes. Sci Naturwissenschaften 104:32Google Scholar
  4. Barton K (2009) Package ‘MuMIn’. Available at https://cran.r-project.org/web/packages/mumin/index.html (Accessed 17 February 2018)
  5. Bellard C, Bertelsmeier C, Leadley P, Thuiller W, Courchamp F (2012) Impacts of climate change on the future of biodiversity. Ecol Letters 15: 365–377Google Scholar
  6. Bjørnstad ON (2016) Package ‘ncf’. Available at https://cran.r-project.org/package=ncf (Accessed 17 February 2018)
  7. Burnham KP, Anderson DR, Huyvaert KP (2011) AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons. Behav Ecol Sociobiol 65:23–35CrossRefGoogle Scholar
  8. Cadotte MW and Tucker CM (2017) Should environmental filtering be abandoned? Trends Ecol Evol 32:429–437CrossRefGoogle Scholar
  9. Chase JM (2014) Spatial scale resolves the niche versus neutral theory debate. J Veg Sci 25:319–322CrossRefGoogle Scholar
  10. Clinebell RR, Phillips OL, Gentry AH, Stark N, Zuuring H (1995). Prediction of Neotropical tree and liana species richness from soil and climatic data. Biodivers Conservation 4:56–90CrossRefGoogle Scholar
  11. Condit R, Engelbrecht BMJ, Pino D, Perez R, Turner BL (2013) Species distributions in response to individual soil nutrients and seasonal drought across a community of tropical trees. Proc Natl Acad Sci 110:5064–5068CrossRefGoogle Scholar
  12. Conradi T, Temperton VM, Kollmann J (2017) Resource availability determines the importance of niche-based versus stochastic community assembly in grasslands. Oikos 126:1134–1141CrossRefGoogle Scholar
  13. Dalanesi PE, Oliveira-Filho AT, Fontes MAL (2004). Flora e estrutura do componente arbóreo da floresta do parque ecológico quedas do Rio Bonito, Lavras, MG, e correlações entre a distribuição das espécies e variáveis ambientais. Acta Bot Brasil 18:737–757CrossRefGoogle Scholar
  14. Dormann CF, Elith J, Jacher S et al (2012) Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 35:001–020CrossRefGoogle Scholar
  15. Embrapa (1997) Manual de métodos de análise de solo. Empresa Brasileira de Pesquisa Agropecuária, Centro Nacional de Pesquisa de Solos, Rio de Janeiro.Google Scholar
  16. Embrapa (1999) Sistema brasileiro de classificação de solos. Empresa Brasileira de Pesquisa Agropecuária, Centro Nacional de Pesquisa de Solos, Rio de Janeiro.Google Scholar
  17. Engelbrecht BMJ, Comita LS, Condit R, Kursar TA, Tyree MT, Turner BL, Hubbell SP (2007) Drought sensitivity shapes species distribution patterns in tropical forests. Nature 447:80–82CrossRefGoogle Scholar
  18. Espírito-Santo FDB, Oliveira-Filho AT, Machado ELM, Souza JS, Fontes MAL, Melo Marques JJGS (2002) Variáveis ambientais e a distribuição de espécies arbóreas em um remanescente de floresta estacional semidecídua montana no campus da universidade federal de Lavras, MG. Acta Bot Brasil 16:331–356CrossRefGoogle Scholar
  19. Garzon-Lopez CX, Jansen PA, Bohlman SA, Ordonez A, Olff H (2014) Effects of sampling scale on patterns of habitat association in tropical trees. J Veg Sci 25:349–362CrossRefGoogle Scholar
  20. Harrison XA (2014) Using observation-level random effects to model overdispersion in count data in ecology and evolution. PeerJ 2:616Google Scholar
  21. Hubbell SP (2001) The unified neutral theory of biodiversity and biogeography. Princeton University Press, Princeton, NJ, USGoogle Scholar
  22. Hutchinson GE (1959) Homage to Santa Rosalia or why are there so many kinds of animals? Amer Naturalist 93: 145CrossRefGoogle Scholar
  23. John R, Dalling JH, Harms KE, Yavitt JB, Stallard RF, Mirabello M, Hubbell SP, Valencia R, Navarrete H, Vallejo M, Foster RB (2007) Soil nutrients influence spatial distributions of tropical tree species. Proc Natl Acad Sci 104:864–869CrossRefGoogle Scholar
  24. Jones MM, Tuomisto H, Clark DB, Olivas P (2006) Effects of mesoscale environmental heterogeneity and dispersal limitation on floristic variation in rain forest ferns. J Ecol 94:181–195CrossRefGoogle Scholar
  25. Kraft NJB, Adler PB, Godoy O, James EC, Fuller S, Levine JM (2014) Community assembly, coexistence and the environmental filtering metaphor. Functional Ecology 29(5):592–599.  https://doi.org/10.1111/1365-2435.12345
  26. Köppen W (1948) Climatologia fondo de cultura econômica. Mexico CityGoogle Scholar
  27. Neves DM, Dexter KG, Pennington RT, Valente ASM, Bueno ML, Eisenlohr PV, Fontes MAL, Miranda PLS, Moreira SN, Rezende VL, Saiter FZ, Oliveira-Filho AT (2017) Dissecting a biodiversity hotspot: the importance of environmentally marginal habitats in the Atlantic forest domain of south America. Diversity & Distrib 23:898–909CrossRefGoogle Scholar
  28. Newbery DM, Alexander IJ, Thomas DW, Gartlan JS (1988) Ectomycorrhizal rain-forest legumes and soil phosphorus in Korup national park, Cameroon. New Phytol 109:433–450CrossRefGoogle Scholar
  29. Nunes YRF, Mendonça AVR, Botezelli L, Machado ELM, Oliveira-Filho AT (2003) Variações da fisionomia, diversidade e composição de guildas da comunidade arbórea em um fragmento de floresta semidecidual em Lavras, MG. Acta Bot Brasil 17:213–229CrossRefGoogle Scholar
  30. Oliveira-Filho AT and Fluminhan-Filho M (1999) Ecologia da vegetação do parque florestal quedas do rio bonito. Cerne 5:051–064Google Scholar
  31. Oliveira-Filho AT and Fontes MAL (2000) Patterns of floristic differentiation among Atlantic forests in southeastern Brazil and the influence of climate. Biotropica 32:793–810CrossRefGoogle Scholar
  32. Oliveira-Filho AT, Ratter JA (1995) A study of the origin of central brazilian forests by the analysis of plant species distribution patterns. Edinburgh J Bot 52:141–194CrossRefGoogle Scholar
  33. Paoli GD, Curran LM, Zak DR (2006) Soil nutrients and beta diversity in the Bornean Dipterocarpaceae: evidence for niche partitioning by tropical rain forest trees. J Ecol 94:157–170CrossRefGoogle Scholar
  34. Paul EA (2016) The nature and dynamics of soil organic matter: plant inputs, microbial transformations, and organic matter stabilization. Soil Biol Biochem 98:109–126CrossRefGoogle Scholar
  35. Peña-Claros M, Poorter L, Alarcón A, Blate G, Choque U, Fredericksen TS, Justiniano MJ, Leaño C, Licona JC, Pariona W, Putz FE, Quevedo L, Toledo M (2012) Soil effects on forest structure and diversity in a moist and a dry tropical forest. Biotropica 44:276–283CrossRefGoogle Scholar
  36. Phillips OL, Nuñez Vargas P, Lorenzo AM, Peña Cruz A, Zans MEC, Galiano Sanchez W, Yli-Halla M, Rose S (2003) Habitat association among amazonian tree species: a landscape-scale approach. J Ecol 91:757–775CrossRefGoogle Scholar
  37. Poulsen AD, Tuomisto H, Balslev H (2006) Edaphic and floristic variation within a 1-ha plot of lowland amazonian rain forest. Biotropica 38:468–478CrossRefGoogle Scholar
  38. R Core Team (2018) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/ (Accessed 17 February 2018)
  39. Rocha MJR, Cupertino-Eisenlohr MA, Leoni LS, Silva AG, Nappo ME (2017) Floristic and ecological attributes of a seasonal semideciduous Atlantic forest in a key area for conservation of the Zona da Mata region of Minas Gerais State, Brazil. Hoehnea 44:29–43CrossRefGoogle Scholar
  40. Siefert A, Ravenscroft C, Althoff D, Alvarez-Yépiz JC, Carter BE, Glennon KL, Heberling JM, Jo IS, Pontes A, Sauer A, Willis A, Fridley JD (2012) Scale dependence of vegetation–environment relationships: a meta-analysis of multivariate data. J Veg Sci 23:942–951CrossRefGoogle Scholar
  41. Swaine MD (1996) Rainfall and soil fertility as factors limiting forest species distributions in Ghana. J Ecol 84:419–428CrossRefGoogle Scholar
  42. Tabarelli M, Da Silva MJC, Gascon C (2004) Forest fragmentation, synergisms and the impoverishment of neotropical forests. Biodivers & Conservation 13:1419–1425CrossRefGoogle Scholar
  43. Terra MN, Santos RM, Fontes MAL, Mello JM, Scolforo JRS, Gomide LR, Prado Júnior JA, Schiavini I, Ter Steege H (2017) Tree dominance and diversity in Minas Gerais, Brazil. Biodivers & Conservation 26:2133CrossRefGoogle Scholar
  44. Tilman D (2004) Niche tradeoffs, neutrality, and community structure: a stochastic theory of resource competition, invasion, and community assembly. Proc Natl Acad Sci USA 101:10854–10861CrossRefGoogle Scholar
  45. Toledo M, Peña-Claros M, Bongers F, Alarcón A, Balcázar J, Chuviña J, Leaño C, Licona JC, Poorter L (2012) Distribution patterns of tropical woody species in response to climatic and edaphic gradients. J Ecol 100:253–263CrossRefGoogle Scholar
  46. Turner BL, Brenes-Arguedas T, Condit R (2018) Pervasive phosphorus limitation of tree species but not communities in tropical forests. Nature 555:367–370CrossRefGoogle Scholar
  47. Vellend M (2010) Conceptual synthesis in community ecology. Quart Rev Biol 85:183–206CrossRefGoogle Scholar
  48. Veloso HP, Rangel Filho ALR, Lima JCA (1991) Classificação da vegetação brasileira adaptada a um sistema universal. Instituto Brasileiro de Geografia e Estatística, Rio de JaneiroGoogle Scholar
  49. Vleminckx J, Drouet T, Amani C, Lisingo J, Lejoly J, Hardy OJ (2014) Impact of fine-scale edaphic heterogeneity on tree species assembly in a central African rainforest. J Veg Sci 26:134–144CrossRefGoogle Scholar
  50. Wang M, Zheng Q, Shen Q, Guo S (2013) The Critical role of potassium in plant stress response. Int J Molec Sci 14:7370–7390CrossRefGoogle Scholar
  51. Wickham H (2016) ggplot2: elegant graphics for data analysis. Springer. Accessed 17 February 2018Google Scholar
  52. World Reference Base for Soil Resources (2014) International soil classification system for naming soils and creating legends for soil maps. IUSS working group – FAO, RomeGoogle Scholar

Copyright information

© Institute of Botany, Academy of Sciences of the Czech Republic 2019

Authors and Affiliations

  1. 1.Forest Sciences DepartmentFederal University of LavrasLavrasBrazil

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