Fuzzy logic in the determination of potential forest fragments for seed harvesting

• Main Author: Peluzio, Telma Machado de Oliveira
• Publication Date: 2023
• Other Authors: Peluzio, João Batista Esteves, Abreu, Karla Maria Pedra de, Ferrari, Jeferson Luís, Kunz, Sustanis Horn, Fiedler, Nilton César, Gandine, Quênia Glória Ferreira, Paschoa, Luciana de Souza Lorenzoni, Moura, Marks Melo, Moreira, Giselle Lemos, Carvalho, Rita de Cássia Freire, Pimentel, Stefania Marques, Branco, Elvis Ricardo Figueira, Peluzio, Lucas Machado, Santos, Alexandre Rosa dos
• Format: Article
• Language: por
• Source: Ciência Florestal (Online)
• Download full: https://periodicos.ufsm.br/cienciaflorestal/article/view/70016
• topic: Mata atlântica; Conservação da natureza; Geotecnologia; Sistema de informações geográficas; Atlantic Forest; Conservation of nature; Geotechnology; Geographic information systems

The tropical forest is extremely exploited and fragmented, making it essential to collect native seeds to meet the growing demand for its restoration and maintenance of biodiversity. Thus, the objective is to select potential forest fragments with a higher degree of conservation for seed harvesting, through the use and association of landscape ecology with fuzzy logic. The study was carried out in the watershed of the Itapemirim river. The stages of selection and photointerpretation of the images were carried out; error determination; application of landscape ecology metric indices; application of fuzzy logic in a computational application and validation of the methodology in loco. 7,515 forest fragments were determined, corresponding to 19.21% of the study area, with 89.53% of hits. Fragments smaller than 5 ha are the most fragile and are at risk of extinction, while those larger than 300 ha have a lower risk of extinction, even with the increase in the edge. With the application of fuzzy logic, the mean was between 0.15, standard deviation of 0.24 and the coefficient of variation at 161.73%. Scenario 1 (FLONA of Pacotuba), has 10.25% of families, 25.92% of genera and 33.62% of species more than Scenario 2 (PEAMA Ifes Campus of Alegre), among the identified individuals. The association of landscape ecology techniques and fuzzy logic made it possible to identify fragments with a higher degree of conservation, with potential for harvesting forest seeds.