Influence of distance from forest on early spontaneous vegetation succession following small-scale gold-mining in the southeast Peruvian Amazon

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Jorge Garate-Quispe, Yoni Fernandez-Mamani , Sufer Baez Quispe, Margarita Soto-Benavente, Gorky Florez Castillo, Marx Herrera-Machaca, Emilia Gutierrez Merino

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The present study aimed to analyze the influence of distance from forest reference and stands age on spontaneous succession in abandoned gold-mining lands in the southeast of the Peruvian Amazon (Madre de Dios). We evaluated the species richness, floristic, forest cover, and vegetation structure of spontaneous vegetation stands with different times of abandonment (1-6 years). Twelve plots of 10 m x 25 m were used, where all individuals with DBH > 1 cm were inventoried. The DBH and height of all trees and shrubs were measured. We determined the Value of Importance (IV) and the Shannon Weaver index to evaluate the species diversity. We used the distance-based redundancy analysis (dbRDA) and regression analysis to evaluate the influence of the environmental variables on the floristic composition and floristics-structural attributes, respectively. We found 451 stems grouped into 59 species and 21 families. The three most important species were Cecropia membranacea, Chromolaena laevigata, and Ochroma pyramidale that together represented 54% of IV. The stands age, vegetation cover, and tree-shrub cover all were significantly correlated with vegetation diversity (P value<0.05), while the distance from the forest had a significant effect on abundance of natural regeneration. However, dbRDA analysis showed that only the distance from the forest had a significant effect on floristic composition of spontaneous vegetation (P-value<0.01). Our results suggest that the forest restoration of abandoned gold-mining areas in the Peruvian Amazon should take the distance from forest into account, and they should take advantage of the potential of natural regeneration to accelerate this process.

Resource Type:
Conference Presentation, SER2021

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