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

IF 0.6 4区农林科学 Q4 FORESTRY

Revista Arvore Pub Date : 2023-09-04 DOI:10.1590/1806-908820230000012

J. C. D. Abreu, José Antônio Aleixo da Silva, R. Ferreira, S. J. S. S. D. Rocha, Ivaldo da Silva Tavares Júnior, A. A. Farias, Paulo Henrique Villanova, Aguida Beatriz Travaglia Viana, B. Schettini, L. A. A. Telles, Arthur Araújo Silva

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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.

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巴西caatinga生物群系物种营养预测的混合模型

应用于巴西Caatinga树种的营养预测模型可以成为了解该生物群系的重要工具。该研究旨在拟合一个混合模型来预测位于巴西伯南布哥州弗洛雷斯塔市Caatinga生物群落的原生树种的氮(N)、磷(P)和钾(K)含量。以下物种被认为是该地区最重要的，并在本研究中进行了评估:Poincianella bracteosa (Tul。l.p.k eiroz，含羞草眼科中心。前底，梨叶穗轴，槲皮穗轴。参数)。Pax。& Hoffm, and Anadenanthera colubrina var. cebil (Griseb.)Altschul。取4棵树，代表每个直径级的平均周长，进行氮磷钾量化。对spr模型进行了NPK预测，所有模型中物种包含作为随机效应显著(p > 0.05)。具有固定效应和随机效应的Spurr模型在所有营养物质的所有参数上都比固定效应模型具有更好的统计性。生成的NPK预测方程可以作为一个方便的工具来了解木材开采对Caatinga生物地球化学循环的影响，并指导世界半干旱地区的森林管理策略。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Revista Arvore FORESTRY-

CiteScore

1.00

自引率

0.00%

发文量

审稿时长

4-8 weeks

期刊介绍： A Revista Árvore é um veículo de comunicação científica da Sociedade de Investigações Florestais – SIF. O jornal é de acesso gratuito, revisado por pares, que publica bimestralmente trabalhos científicos originais no campo da Ciência Florestal. As áreas temáticas para publicação são: Ambiência e Conservação da Natureza, Manejo Florestal, Silvicultura e Tecnologia da Madeira e Utilização de Produtos Florestais. A política editorial visa manter alta conduta ética em relação à publicação e aos seus funcionários, rigor na qualidade dos artigos científicos, seleção de revisores qualificados, respeito profissional aos autores e processo de tomada de decisão imparcial. A Revista Árvore publica artigos apenas em inglês. Artigos de revisão podem ser publicados se houver uma discussão relevante resumindo o estado da arte sobre o assunto. A revisão estrita da literatura não é aceita.