Non-linear growth models for tree species used for forest restoration in Brazilian Amazon Arc of Deforestation

Abstract

The large amount of degraded areas and productive potential of the legal reserves in Brazil make restoration an environmental demand and a commercial opportunity. We modelled the diameter growth as a function of age of eight tree species in restoration plantations in the Brazilian Amazon. From 14 years of annual forest inventory data, for each species, we tested variations of logistic function: simple logistic, logistic with covariant (plant area at the time of planting), logistic with random effect, logistic with random effect and covariant. Amongst the studied species, Schizolobium parahyba var. amazonicum, Tectona grandis and Simarouba amara showed the highest growth rates while Cordia alliodora, Cedrela odorata and three species of the genus Handroanthus showed slower growth. The gains from using the covariant in modeling were small for both fixed and mixed-effect models. Gains from the inclusion of the random effect were substantial. Mixed-effect models had the best performance in modeling the growth of the species. Our results provide basis for a critical view of the criteria and possibilities for degraded areas restoration and management practices in legal reserves of the Amazon. An economic analysis is required to ensure the viability of these areas’ sustainable exploitation.