Modeling Diachronic Cork Oak Dieback–Comparison of Two Case Studies

• Autor(a) principal: Camilo-Alves, Constanca
• Data de Publicação: 2020
• Outros Autores: Saraiva-Dias, Susana, Dinis, Cati, Felix, Maria do Rosário, Varandas, Carla, Almeida Ribeiro, Nuno
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10174/28189; https://doi.org/10.15684/formath.19.001
• topic: Cork oak; diachronic analysis; image processing; tree mortality; Phytophthora cinnamomi; Quercus suber

Widespread events of cork oak mortality are disturbing the system and jeopardizing cork production. This research combined techniques to analyze in detail these events on a small scale. To understand the dynamics of cork oak mortality and the factors associated with it, a diachronic study was performed in two farms located in Évora, Portugal. The case studies were two nearby farms suffering from tree dieback since 2000. Aerial images of the area, taken in 2004 and 2012, were processed with GIS in order to detect dead trees and to calculate tree crown cover. Slope and aspect were obtained through cartographic and topographic maps. The intersection of those maps resulted in polygons with unique values for those characteristics. Mortality index and tree crown cover were calculated for each one of them. Maps of the kernel density of tree mortality were generated to select key spots for pests and diseases field survey. Detection of soil pathogens was performed using baiting method and molecular analyses. The analysis showed that both farms had the same predisposing and inciting factors associated with tree decline, such as the soilborne Phytophthora cinnamomi, sunlight exposure or soil disking. However, the relative importance of each factor varied among farms. As a result, the dieback processes also differed, despite their similarity regarding mortality intensity. The diachronic approach associated with field survey resulted in a better comprehension of the tree dieback on a small scale and proved its usefulness in future decision-making regarding tree mortality mitigation.