Aerial biomass allometric models for Prosopis affinis Spreng. in native Espinal forests of Argentina

ABSTRACT Estimation of carbon stored in forest ecosystems requires accurate biomass prediction tools. The objective of this study was to determine the individual aerial biomass of Prosopis affinis and its distribution by component, to develop allometric models for the estimation of biomass and to es...

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Main Authors: Silvana M. J. Sione, Hernán J. Andrade-Castañeda, Silvia G. Ledesma, Leandro J. Rosenberger, José D. Oszust, Marcelo G. Wilson
Format: Article
Language:English
Published: Universidade Federal de Campina Grande
Series:Revista Brasileira de Engenharia Agrícola e Ambiental
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Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019000600467&lng=en&tlng=en
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author Silvana M. J. Sione
Hernán J. Andrade-Castañeda
Silvia G. Ledesma
Leandro J. Rosenberger
José D. Oszust
Marcelo G. Wilson
author_facet Silvana M. J. Sione
Hernán J. Andrade-Castañeda
Silvia G. Ledesma
Leandro J. Rosenberger
José D. Oszust
Marcelo G. Wilson
author_sort Silvana M. J. Sione
collection DOAJ
description ABSTRACT Estimation of carbon stored in forest ecosystems requires accurate biomass prediction tools. The objective of this study was to determine the individual aerial biomass of Prosopis affinis and its distribution by component, to develop allometric models for the estimation of biomass and to estimate biomass expansion factors (BEF) in native forests of Entre Ríos (Argentina). Dendrometric variables on 30 individuals of different diameter classes were measured. Values of total aerial biomass and component biomass (trunk, branches larger than 5 cm in diameter and branches smaller than 5 cm + leaves, flowers and fruits) were determined using the destructive method. Different models were developed, and the best models were selected according to the adjusted coefficient of determination (R2adj), mean squared prediction error, the Akaike information and Bayesian information criteria and the Furnival index. The variables crown area, diameter at breast height and total height were the best estimators of total aerial biomass and component biomass of P. affinis. The single-variable model based on the basal diameter has a very good predictive capacity for total aerial biomass, resulting in a simple model of great practicality. The BEF was significantly different among diameter classes, with mean values between 2.28 and 4.90. The highest values corresponded to individuals with trunk diameters larger than 25 cm. The models developed in this work present high precision (R2adj. ≥ 0.94) for the prediction of total aerial biomass of P. affinis and can be applied in the native forest area of the province of Entre Ríos (Argentina).
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spelling doaj-art-c49637c0780a47ff92bdd7dec40f2e512025-08-20T02:02:36ZengUniversidade Federal de Campina GrandeRevista Brasileira de Engenharia Agrícola e Ambiental1807-192923646747310.1590/1807-1929/agriambi.v23n6p467-473S1415-43662019000600467Aerial biomass allometric models for Prosopis affinis Spreng. in native Espinal forests of ArgentinaSilvana M. J. SioneHernán J. Andrade-CastañedaSilvia G. LedesmaLeandro J. RosenbergerJosé D. OszustMarcelo G. WilsonABSTRACT Estimation of carbon stored in forest ecosystems requires accurate biomass prediction tools. The objective of this study was to determine the individual aerial biomass of Prosopis affinis and its distribution by component, to develop allometric models for the estimation of biomass and to estimate biomass expansion factors (BEF) in native forests of Entre Ríos (Argentina). Dendrometric variables on 30 individuals of different diameter classes were measured. Values of total aerial biomass and component biomass (trunk, branches larger than 5 cm in diameter and branches smaller than 5 cm + leaves, flowers and fruits) were determined using the destructive method. Different models were developed, and the best models were selected according to the adjusted coefficient of determination (R2adj), mean squared prediction error, the Akaike information and Bayesian information criteria and the Furnival index. The variables crown area, diameter at breast height and total height were the best estimators of total aerial biomass and component biomass of P. affinis. The single-variable model based on the basal diameter has a very good predictive capacity for total aerial biomass, resulting in a simple model of great practicality. The BEF was significantly different among diameter classes, with mean values between 2.28 and 4.90. The highest values corresponded to individuals with trunk diameters larger than 25 cm. The models developed in this work present high precision (R2adj. ≥ 0.94) for the prediction of total aerial biomass of P. affinis and can be applied in the native forest area of the province of Entre Ríos (Argentina).http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019000600467&lng=en&tlng=enreservatório de carbonoecosistemasFabaceae
spellingShingle Silvana M. J. Sione
Hernán J. Andrade-Castañeda
Silvia G. Ledesma
Leandro J. Rosenberger
José D. Oszust
Marcelo G. Wilson
Aerial biomass allometric models for Prosopis affinis Spreng. in native Espinal forests of Argentina
Revista Brasileira de Engenharia Agrícola e Ambiental
reservatório de carbono
ecosistemas
Fabaceae
title Aerial biomass allometric models for Prosopis affinis Spreng. in native Espinal forests of Argentina
title_full Aerial biomass allometric models for Prosopis affinis Spreng. in native Espinal forests of Argentina
title_fullStr Aerial biomass allometric models for Prosopis affinis Spreng. in native Espinal forests of Argentina
title_full_unstemmed Aerial biomass allometric models for Prosopis affinis Spreng. in native Espinal forests of Argentina
title_short Aerial biomass allometric models for Prosopis affinis Spreng. in native Espinal forests of Argentina
title_sort aerial biomass allometric models for prosopis affinis spreng in native espinal forests of argentina
topic reservatório de carbono
ecosistemas
Fabaceae
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019000600467&lng=en&tlng=en
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