Evaluating tree survival and modeling initial growth for Atlantic Forest restoration

• Autor(a) principal: Gerber, Dionatan
• Data de Publicação: 2023
• Outros Autores: Bechara, Fernando Campanhã, Topanotti, Larissa Regina, Nicoletti, Marcos Felipe, Azevedo, João
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10198/27018
• topic: Subtropical forest; Reforestation; Mathematic models; Floresta subtropical; Reflorestamento; Modelos matemáticos

Ecological restoration has become an important complementary practice to protect natural resources and preserve biodiversity. However, native species may be used in restoration programs in ways that do not optimize their performance. This research evaluated the survival and to model the initial growth of 15 native tree species planted in “filling” and “diversity” lines in the post-planting phase of a restoration experiment in the subtropics of the Brazilian Atlantic Forest. We measured survival rate (%) one year after planting and collar diameter (mm), total height (m), crown projection area (m²) and crown volume (m³) in the first 48 months after planting. Growth modeling for each variable and species was based on the non-linear mathematical Logistic, Gompertz, and Chapman-Richards models. Model selection for each variable/species was supported by the Akaike Information Criterion, standard error of the estimate, and coefficient of determination. The highest survival rates were reported for Cordia americana, Gochnatia polymorpha, Inga uruguensis, Peltophorum dubium, Prunus sellowii e Zanthoxylum rhoifolium (91.7%) and for Solanum mauritianum (90.3%). The species with faster growth were, by increasing order, Mimosa scabrella, Trema micrantha, Solanum mauritianum and Croton urucurana. With a better understanding of the initial developmental potential of tree species, it is possible to increase the species and functional diversity of the filling group. There was no single model capable of describing the variables analyzed and different models were needed to describe different characteristics and species.