Natural regeneration of tree species 29 years after timber harvesting in the Eastern Amazon

• Grant number: 22/09047-9
• Support Opportunities: Scholarships in Brazil - Doctorate
• Effective date (Start): April 01, 2023
• Status: Discontinued
• Field of knowledge: Agronomical Sciences - Forestry Resources and Forestry Engineering - Forest Management
• Principal Investigator: Edson José Vidal da Silva
• Grantee: Rodrigo Costa Pinto
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
• Associated scholarship(s): 24/04038-7 - Natural regeneration of tree species at the end of the first timber harvesting cycle in managed tropical forest in the Eastern Amazon, BE.EP.DR

Abstract

The sustainability of forest management is correlated with the availability of residual stock of commercial species for the next harvest cycles. Even with the application of Reduced-Impact Logging (RIL) techniques, it is necessary to guarantee the regeneration of these species. For this, understanding the behavior of commercial species in logging gaps environments is essential for the viability of forest management. Thus, the objective of this work is to evaluate the effects after 29 years of the application of two methods of harvesting timber: the RIL and the Conventional Logging (CL) in the natural regeneration of tree species in logging gaps. In addition, it is expected to generate a methodology for mapping gaps. Thus, data will be collected from 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 for comparison of stocks, structure and floristic composition of different ecological groups in regeneration between the two methods of logging and with the unlogged control. Drone images will be obtained for the development of the logging gaps mapping methodology. Stocks and the horizontal and vertical structure of regeneration will be analyzed using phytosociological methods and basal area. Composition data will be analyzed with Non-Metric Multidimensional Scaling and diversity by species richness and Shannon's indices and Pielou's evenness. Finally, the images will be analyzed through the techniques of photogrammetry and orthorectified images and the validation of the methodology for mapping gaps will be carried out by visual means and field visits.