Species richness and diversity in shrub savanna using ordinary kriging

Authors

  • Anderson Pedro Bernardina Batista Universidade Federal de Lavras, Departamento de Ciências Florestais, Caixa Postal 3037, CEP 37200‑000 Lavras, MG, Brazil.
  • José Márcio de Mello Universidade Federal de Lavras, Departamento de Ciências Florestais, Caixa Postal 3037, CEP 37200‑000 Lavras, MG, Brazil.
  • Marcel Régis Raimundo Universidade Federal de Lavras, Departamento de Ciências Florestais, Caixa Postal 3037, CEP 37200‑000 Lavras, MG, Brazil.
  • Henrique Ferraço Scolforo North Carolina State University, College of Natural Resources, Department of Forestry and Environmental Resources, 2820 Faucette Drive, 27695 Raleigh, North Carolina, United States.
  • Aliny Aparecida dos Reis Universidade Federal de Lavras, Departamento de Ciências Florestais, Caixa Postal 3037, CEP 37200‑000 Lavras, MG, Brazil.
  • José Roberto Soares Scolforo Universidade Federal de Lavras, Departamento de Ciências Florestais, Caixa Postal 3037, CEP 37200‑000 Lavras, MG, Brazil.

DOI:

https://doi.org/10.1590/S1678-3921.pab2016.v51.22795

Keywords:

geostatistics, Shannon index, variogram

Abstract

The objective of this work was to analyze the spatial distribution and the behavior of species richness and diversity in a shrub savanna fragment, in 2003 and 2014, using ordinary kriging, in the state of Minas Gerais, Brazil. In both evaluation years, the measurements were performed in a fragment with 236.85 hectares, in which individual trees were measured and identified across 40 plots (1,000 m2). Species richness was determined by the total number of species in each plot, and diversity by the Shannon diversity index. For the variogram study, spatial models were fitted and selected. Then, ordinary kriging was applied and the spatial distribution of the assessed variables was described. A strong spatial dependence was observed between species richness and diversity by the Shannon diversity index (<25% spatial dependence degree). Areas of low and high species diversity and richness were found in the shrub savanna fragment. Spatial distribution behavior shows relative stability regarding the number of species and the Shannon diversity index in the evaluated years.

Author Biographies

Anderson Pedro Bernardina Batista, Universidade Federal de Lavras, Departamento de Ciências Florestais, Caixa Postal 3037, CEP 37200‑000 Lavras, MG, Brazil.

Departamento de Ciências Florestais

http://lattes.cnpq.br/7496500321002933

José Márcio de Mello, Universidade Federal de Lavras, Departamento de Ciências Florestais, Caixa Postal 3037, CEP 37200‑000 Lavras, MG, Brazil.

Departamento de Ciências Florestais

http://lattes.cnpq.br/9805647108156583

Marcel Régis Raimundo, Universidade Federal de Lavras, Departamento de Ciências Florestais, Caixa Postal 3037, CEP 37200‑000 Lavras, MG, Brazil.

Departamento de Ciências Florestais

http://lattes.cnpq.br/2469638959423651

Henrique Ferraço Scolforo, North Carolina State University, College of Natural Resources, Department of Forestry and Environmental Resources, 2820 Faucette Drive, 27695 Raleigh, North Carolina, United States.

Department of Forestry and Environmental Resources

http://lattes.cnpq.br/2089292179790603

Aliny Aparecida dos Reis, Universidade Federal de Lavras, Departamento de Ciências Florestais, Caixa Postal 3037, CEP 37200‑000 Lavras, MG, Brazil.

Departamento de Ciências Florestais

http://lattes.cnpq.br/5364437916631071

José Roberto Soares Scolforo, Universidade Federal de Lavras, Departamento de Ciências Florestais, Caixa Postal 3037, CEP 37200‑000 Lavras, MG, Brazil.

Departamento de Ciências Florestais

 http://lattes.cnpq.br/8717150703694552

 

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Published

2016-10-04

How to Cite

Batista, A. P. B., de Mello, J. M., Raimundo, M. R., Scolforo, H. F., dos Reis, A. A., & Scolforo, J. R. S. (2016). Species richness and diversity in shrub savanna using ordinary kriging. Pesquisa Agropecuaria Brasileira, 51(8), 958–966. https://doi.org/10.1590/S1678-3921.pab2016.v51.22795

Issue

v.51, n.8, ago. 2016

Section

REMOTE SENSING