Please use this identifier to cite or link to this item: http://cicy.repositorioinstitucional.mx/jspui/handle/1003/1692
Beta-Diversity Modeling and Mapping with LiDAR and Multispectral Sensors in a Semi-Evergreen Tropical Forest
ALEJANDRA DEL PILAR OCHOA FRANCO
JOSE RENE VALDEZ LAZALDE
GREGORIO ANGELES PEREZ
HECTOR MANUEL DE LOS SANTOS POSADAS
JOSE LUIS HERNANDEZ STEFANONI
JUAN IGNACIO VALDEZ HERNANDEZ
PAULINO PEREZ RODRIGUEZ
Acceso Abierto
Atribución-NoComercial-SinDerivadas
10.3390/f10050419
FLORISTIC GRADIENT
SPECIES COMPOSITION DISSIMILARITY
NMDS
RAPIDEYE
REMOTE SENSING
LIDAR
LINEAR MODEL
MIXED MODEL
Tree beta-diversity denotes the variation in species composition at stand level, it is a key indicator of forest degradation, and is conjointly required with alpha-diversity for management decision making but has seldom been considered. Our aim was to map it in a continuous way with remote sensing technologies over a tropical landscape with different disturbance histories. We extracted a floristic gradient of dissimilarity through a non-metric multidimensional scaling ordination based on the ecological importance value of each species, which showed sensitivity to different land use history through significant differences in the gradient scores between the disturbances. After finding strong correlations between the floristic gradient and the rapidEye multispectral textures and LiDAR-derived variables, it was linearly regressed against them; variable selection was performed by fitting mixed-effect models. The redEdge band mean, the Canopy Height Model, and the infrared band variance explained 68% of its spatial variability, each coefficient with a relative importance of 49%, 32.5%, and 18.5% respectively. Our results confirmed the synergic use of LiDAR and multispectral sensors to map tree beta-diversity at stand level. This approach can be used, combined with ground data, to detect effects (either negative or positive) of management practices or natural disturbances on tree species composition. 
2019
Artículo
Forests, 10(5), 419, 2019
Inglés
Ochoa-Franco, A. D. P., Valdez-Lazalde, J. R., Ángeles-Pérez, G., De Los Santos-Posadas, H. M., Hernández-Stefanoni, J. L., Valdez-Hernández, J. I., & Pérez-Rodríguez, P. (2019). Beta-Diversity Modeling and Mapping with LiDAR and Multispectral Sensors in a Semi-Evergreen Tropical Forest. Forests, 10(5), 419.
DESARROLLO VEGETAL
Versión publicada
publishedVersion - Versión publicada
Appears in Collections:Artículos de Investigación Arbitrados

Upload archives


File SizeFormat 
2019_A_Ochoa.pdf1.7 MBAdobe PDFView/Open