Deprecated: mysql_connect(): The mysql extension is deprecated and will be removed in the future: use mysqli or PDO instead in /www/produccionvegetal/htdocs/inc/conexion.php on line 5
Dpto. De Produccion Vegetal
Ver historia del Ing. Agr. Jorge Gesumar韆


Deprecated: mysql_connect(): The mysql extension is deprecated and will be removed in the future: use mysqli or PDO instead in /www/produccionvegetal/htdocs/contador/count.php on line 14
Visitas Totales: 3019189 | Visitas hoy: 11 | Usuarios Online: 1

Modeling forest site productivity using climate data and topographic imagery in Pinus elliottii plantations of central Argentina

Abstract
Key message To be useful for silvicultural and forest management practices, the models of Site Index (SI) should be based on accessible predictor variables. In this study, we used spatially explicit data obtained from digital elevation models and climate data to develop SI prediction models with high local precision.
Context Predicting tree growth and yield is a key component to sustainable forest management and depends on accurate measures of site quality.
Aims The aim of this study was to develop both empirical models to predict site index (SI) from biophysical variables and a dynamic model of top height growth for plantations of Pinus elliottii Engelm. in C贸rdoba, Argentina.
Methods Site productivity described by SI was related to environmental characteristics, including topographic and climatic variables. Separate models were created from only topographic data and the combination of topographic and climate data.
Results Although SI can be adequately predicted through both types of models, the best results were obtained when combining topographic and climate variables (R2 = 0.83, RMSE% = 7.02%, for the best-fitting model). The key factors affecting site productivity were the landscape position and the mean precipitation of the last 5 years before the reference age, both related to the amount of plant-available water in the soils. Furthermore, the top height growth models developed are fairly accurate, considering the proportion of variance explained (R2 = 98%) and the precision of the estimates (RMSE% < 8%).
Conclusion The models developed here are likely to have considerable application in forestry, since they are based on accessible predictor variables, which make them useful for silvicultural and forest management practices, particularly for nonforest areas and for the young or uneven-aged stands.
Keywords Site index . Biophysical factors . Digital elevation models . Prediction models . Forest productivity . C贸rdoba

Fiandino, S., Plevich, J., Tarico, J. et al. Modeling forest site productivity using climate data and topographic imagery in Pinus elliottii plantations of central Argentina. Annals of Forest Science 77, 95 (2020). https://doi.org/10.1007/s13595-020-01006-3
Solicite una ejemplar digital a santifiandino@gmail.com

Informaci贸n de contacto


Departamento de Producción Vegetal, Facultad de Agronomía y Veterinaria - Universidad Nacional de Río Cuarto 



Ruta 36 km 601, Río Cuarto, Córdoba - Argentina   +54 (0358) 467-6159 / 504  / 509



Mail: deptoprodvegetal@ayv.unrc.edu.ar


Sitio Web: Diez a帽os en linea... El sitio web Oficial del Departamento de Producci贸n Vegetal de la Facultad de Agronom铆a y Veterina... Leer mas
Tutorial Transmisi贸n Evento Y... El Departamento de Producci贸n vegetal FAV-UNRC pone a disposici贸n de toda la comunidad un tutorial... Leer mas
INFORME: Rendimiento Potencial... El rendimiento potencial del cultivo de ma铆z es que determinado por el genotipo, la oferta de radia... Leer mas
Docencia Virtual en Produccion... Frente a la suspensi贸n de clases presenciales motivo de la Pandemia COVID-19 el Departamento de Pro... Leer mas
Libro "El Cultivo de Man铆 en ... A partir del mes de mayo de 2017 se encuentra disponible en nuestro sitio web la Segunda Edici贸n am... Leer mas

 

Producci贸n Vegetal 漏 2014 - Todos los derechos reservados - 聽

Responsables de Contenidos: PhD Guillermo Balboa - Dr.聽 Federico Morla聽

ISSN 2422-5479

Subir