A simple method for estimating suitable territory for bioenergy species in Chile

In the past 20 years, different areas of research concerning native and exotic species, herbaceous crops and forest plantations have been oriented toward satisfying domestic, industrial and transportation energy requirements. Because bioenergy species constitute an important resource, it would be st...

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Autores principales: Morales-Salinas,Luis, Acevedo,Edmundo, Castellaro,Giorgio, Román-Osorio,Luis, Morales-Inostroza,Jael, Alonso,Máximo F
Lenguaje:English
Publicado: Pontificia Universidad Católica de Chile. Facultad de Agronomía e Ingeniería Forestal 2015
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Acceso en línea:http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-16202015000200009
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Sumario:In the past 20 years, different areas of research concerning native and exotic species, herbaceous crops and forest plantations have been oriented toward satisfying domestic, industrial and transportation energy requirements. Because bioenergy species constitute an important resource, it would be strategic for a country to have a method for identifying areas suitable for their cultivation to properly incorporate the establishment of energy crops into land use planning. In this study, we sought to define the suitable territories for 16 bioenergy species and their energy potential based on their soil and climate requirements in Central and Southern Chile. We used an adapted version of the FAO EcoCrop database implemented through DIVA-GIS software to predict the crop suitability of different geographical areas, and our results indicate that this method is a simple way to identify land suitable for the establishment of bioenergy species, which is information that can be used in land use planning. Furthermore, spatially explicit regression and ordinary kriging proved to be satisfactory tools for interpolating data from weather station networks through the generation of continuous climatic information grids. Land suitability is presented at a scale of 1:1,000,000 in a continuous digital format expressed in probabilistic terms.