Distribution Models of Timber Species for Forest Conservation and Restoration in the Andean-Amazonian Landscape, North of Peru

• Autores: Cotrina Sánchez, Dany A., Barboza Castillo, Elgar, Rojas Briceño, Nilton B., Oliva Cruz, Manuel, Torres Guzmán, Cristóbal, Amasifuen Guerra, Carlos Alberto, Bandopadhyay, Subhajit
• Formato: artículo
• Fecha de Publicación: 2020
• Institución: Instituto Nacional de Innovación Agraria
• Repositorio: INIA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:null:20.500.12955/1139
• Enlace del recurso: https://repositorio.inia.gob.pe/handle/20.500.12955/1139; https://doi.org/10.3390/su12197945
• Nivel de acceso: acceso abierto
• Materia: Amazon; Maximum entropy; Timber; Species distribution; Forest recovery; Peru; Forestal

The Andean-Amazonian landscape has been universally recognized for its wide biodiversity, and is considered as global repository of ecosystem services. However, the severe loss of forest cover and rapid reduction of the timber species seriously threaten this ecosystem and biodiversity. In this study, we have modeled the distribution of the ten most exploited timber forest species in Amazonas (Peru) to identify priority areas for forest conservation and restoration. Statistical and cartographic protocols were applied with 4454 species records and 26 environmental variables using a Maximum Entropy model (MaxEnt). The result showed that the altitudinal variable was the main regulatory factor that significantly controls the distribution of the species. We found that nine species are distributed below 1000 m above sea level (a.s.l.), except Cedrela montana, which was distributed above 1500 m a.s.l., covering 40.68%. Eight of 10 species can coexist, and the species with the highest percentage of potential restoration area is Cedrela montana (14.57% from Amazonas). However, less than 1.33% of the Amazon has a potential distribution of some species and is protected under some category of conservation. Our study will contribute as a tool for the sustainable management of forests and will provide geographic information to complement forest restoration and conservation plans.