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

Author:

Abreu Jadson Coelho de1ORCID,Silva José Antônio Aleixo da2ORCID,Ferreira Rinaldo Luiz Caraciolo2ORCID,Rocha Samuel José Silva Soares da3ORCID,Tavares Júnior Ivaldo da Silva4ORCID,Farias Aline Araújo4ORCID,Villanova Paulo Henrique4ORCID,Viana Aguida Beatriz Travaglia4ORCID,Schettini Bruno Leão Said4ORCID,Telles Lucas Arthur de Almeida4ORCID,Silva Arthur Araújo4ORCID

Affiliation:

1. Universidade do Estado do Amapá, Brasil

2. Universidade Federal Rural de Pernambuco, Brasil

3. Universidade Federal de Lavras, Brasil

4. Universidade Federal de Viçosa, Brasil

Abstract

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.

Publisher

FapUNIFESP (SciELO)

Subject

Forestry

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