Revista Árvore (Sep 2023)

MIXED MODELS FOR NUTRIENTS PREDICTION IN SPECIES OF THE BRAZILIAN CAATINGA BIOME

  • Jadson Coelho de Abreu,
  • José Antônio Aleixo da Silva,
  • Rinaldo Luiz Caraciolo Ferreira,
  • Samuel José Silva Soares da Rocha,
  • Ivaldo da Silva Tavares Júnior,
  • Aline Araújo Farias,
  • Paulo Henrique Villanova,
  • Aguida Beatriz Travaglia Viana,
  • Bruno Leão Said Schettini,
  • Lucas Arthur de Almeida Telles,
  • Arthur Araújo Silva

DOI
https://doi.org/10.1590/1806-908820230000012
Journal volume & issue
Vol. 47

Abstract

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ABSTRACT Nutrient prediction models applied to tree species from Brazilian Caatinga can be a crucial tool in understanding this biome. The study aimed to fit a mixed model to predict nitrogen (N), phosphorus (P), and potassium (K) content in tree species native to the Caatinga biome located in Floresta municipality, Pernambuco State – PE, Brazil. The following species were considered the area’s most important and evaluated in the present study: Poincianella bracteosa (Tul.) L.P.Queiroz, Mimosa ophtalmocentra Mart. ex Benth, Aspidosperma pyrifolium Mart, Cnidoscolus quercifolius (Mull. Arg.) Pax. & Hoffm, and Anadenanthera colubrina var. cebil (Griseb.) Altschul. Four trees, representing the average circumference in each diameter class, were harvested for NPK quantification. The Spurr model was evaluated for NPK prediction, and species inclusion as a random effect was significant (p > 0.05) in all models. The Spurr model with fixed and random effects presented better statistics than fixed-effect models in all parameters for all nutrients. Generated NPK predicting equations can be a handy tool to understand the impact of wood extraction over Caatinga’s biogeochemical cycles and guide forest management strategies in semi-arid regions of the world.

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