Recruitment models after reduced impact logging in the Amazon rainforest

Abstract

Recruitment models in rainforests are important for studies on forest management sustainability and can guide the assessment of remaining stocks and timber harvesting. Therefore, the objective of this study was to estimate recruitment after Reduced Impact Logging (RIL) by using two categories of models: a distance-independent individual-tree model (ITM) and a matrix model of forest dynamics or transition matrix (TMM). Data from continuous inventories conducted in a Dense Ombrophilous Forest in Paragominas, Pará state, Brazil, were utilized. Two transects of 9 ha each were installed at an area with Reduced Impact Logging, the data was collected in 2005 (nine months after logging), then in 2006, 2008, 2010 and 2012. Considering a period of 8 years after RIL, the individual tree-based model and transition matrix give consistent predictions of the recruitment in the study area. However, we observed slight superiority by the ITM, which presented values closer to the real ones for the total number of trees per hectare.