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Natural regeneration of tree species at the end of the first timber harvesting cycle in managed tropical forest in the Eastern Amazon

Grant number: 24/04038-7
Support Opportunities:Scholarships abroad - Research Internship - Doctorate
Effective date (Start): August 01, 2024
Effective date (End): March 31, 2025
Field of knowledge:Agronomical Sciences - Forestry Resources and Forestry Engineering - Forest Management
Principal Investigator:Edson José Vidal da Silva
Grantee:Rodrigo Costa Pinto
Supervisor: Marielos Peña Claros
Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Research place: Wageningen University & Research, Netherlands  
Associated to the scholarship:22/09047-9 - Natural regeneration of tree species 29 years after timber harvesting in the Eastern Amazon, BP.DR

Abstract

The intensity of timber harvesting is one of the main factors affecting forest recovery and the natural regeneration of timber stocks for subsequent harvesting cycles after the first cut. Even with the application of reduced-impact logging (RIL), it is crucial to ensure the recovery and regeneration of these individuals. Therefore, understanding the behavior of these species in logging gaps is essential to ensure the long-term sustainability of forest management. In this context, the aim of this study is to evaluate the effects of two harvesting methods (RIL and Conventional Logging (CL) on the recovery of structure and the diversity of natural regeneration of tree species in logging gaps. Field and lidar data were collected in permanent sample plots with for over 30 years. Data were collected for all individuals of tree species in three strata: a) individuals with height e 30 cm and DBH < 5 cm, b) individuals with DBH e 5 and < 10 cm, and c) individuals with DBH e 10 cm in 15 logging gaps for each treatment. For field inventory, comparisons of stocks, structure, and floristic composition of different ecological groups in regeneration between the two forest logging methods will be analyzed. For lidar data, we will analyze the profiles of the forest structure, and I will combine three canopy structural variables from the lidar and four field inventory data to assess the lidar's potential to estimate the results found in the field. Thus, we intend to understand the effects of two selective harvestd techniques on logging gaps and whether they are already similar to the reference area.

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