Forest recovery prognostics in conservation units of the Atlantic rainforest

Abstract

Forest growth models can provide valuable support tools for forest recovery assessment and forestry management, whether in the form of diagnostic or prognostic. Furthremore, they can be applied to characterize each phytophysiognomy in terms of vegetation growth parameters that and can be applied to gauge the spatiotemporal progress of recovery processes. Up to date, such parameters remain mostly unknown. In this paper, we explore a modelling framework aimed at providing computer-aided prognostics of forest recovery based on the diffusive-logistic growth (DLG) model and present case studies for a number of four preservation areas located in the Brazilian Atlantic rainforest biome. The modelling framework involves the application of vegetation indices derived from satellite images and a computational implementation of the DLG model. The objective of the study is to illustrate how forest restoration and recovery projects could gain from the proposed methodology, due to the fact that the likely outcomes of management practices could be assessed in advance. Additionally, it aims to determine the characteristic parameters of forest growth for a portion of the Atlantic rainforest biome. The diffusion and growth rate parameters from the DLG model were calibrated and they show the evolution of forest density over the years. The results show that the forest recovery process can take several decades to stabilize in the absence of negative interventions in the forest growth. The model and the implementation presented in this work are freely available and they can be an important tool for decision and policy making in what concerns forest recovery.