Beta-Diversity Modeling and Mapping with LiDAR and Multispectral Sensors in a Semi-Evergreen Tropical Forest
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.
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Format: | info:eu-repo/semantics/article biblioteca |
Language: | eng |
Subjects: | info:eu-repo/classification/Autores/FLORISTIC GRADIENT, info:eu-repo/classification/Autores/SPECIES COMPOSITION DISSIMILARITY, info:eu-repo/classification/Autores/NMDS, info:eu-repo/classification/Autores/RAPIDEYE, info:eu-repo/classification/Autores/REMOTE SENSING, info:eu-repo/classification/Autores/LIDAR, info:eu-repo/classification/Autores/LINEAR MODEL, info:eu-repo/classification/Autores/MIXED MODEL, info:eu-repo/classification/cti/2, info:eu-repo/classification/cti/24, info:eu-repo/classification/cti/2417, info:eu-repo/classification/cti/241715, |
Online Access: | http://cicy.repositorioinstitucional.mx/jspui/handle/1003/1692 |
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dig-cicy-1003-16922020-07-01T00:04:19Z 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 2019 info:eu-repo/semantics/article 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. info:eu-repo/classification/Autores/FLORISTIC GRADIENT info:eu-repo/classification/Autores/SPECIES COMPOSITION DISSIMILARITY info:eu-repo/classification/Autores/NMDS info:eu-repo/classification/Autores/RAPIDEYE info:eu-repo/classification/Autores/REMOTE SENSING info:eu-repo/classification/Autores/LIDAR info:eu-repo/classification/Autores/LINEAR MODEL info:eu-repo/classification/Autores/MIXED MODEL info:eu-repo/classification/cti/2 info:eu-repo/classification/cti/24 info:eu-repo/classification/cti/2417 info:eu-repo/classification/cti/241715 info:eu-repo/classification/cti/241715 Forests, 10(5), 419, 2019 http://cicy.repositorioinstitucional.mx/jspui/handle/1003/1692 info:eu-repo/semantics/datasetDOI/10.3390/f10050419 info:eu-repo/semantics/openAccess eng citation: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. http://creativecommons.org/licenses/by-nc-nd/4.0 info:eu-repo/semantics/publishedVersion application/pdf |
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info:eu-repo/classification/Autores/FLORISTIC GRADIENT info:eu-repo/classification/Autores/SPECIES COMPOSITION DISSIMILARITY info:eu-repo/classification/Autores/NMDS info:eu-repo/classification/Autores/RAPIDEYE info:eu-repo/classification/Autores/REMOTE SENSING info:eu-repo/classification/Autores/LIDAR info:eu-repo/classification/Autores/LINEAR MODEL info:eu-repo/classification/Autores/MIXED MODEL info:eu-repo/classification/cti/2 info:eu-repo/classification/cti/24 info:eu-repo/classification/cti/2417 info:eu-repo/classification/cti/241715 info:eu-repo/classification/cti/241715 info:eu-repo/classification/Autores/FLORISTIC GRADIENT info:eu-repo/classification/Autores/SPECIES COMPOSITION DISSIMILARITY info:eu-repo/classification/Autores/NMDS info:eu-repo/classification/Autores/RAPIDEYE info:eu-repo/classification/Autores/REMOTE SENSING info:eu-repo/classification/Autores/LIDAR info:eu-repo/classification/Autores/LINEAR MODEL info:eu-repo/classification/Autores/MIXED MODEL info:eu-repo/classification/cti/2 info:eu-repo/classification/cti/24 info:eu-repo/classification/cti/2417 info:eu-repo/classification/cti/241715 info:eu-repo/classification/cti/241715 |
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info:eu-repo/classification/Autores/FLORISTIC GRADIENT info:eu-repo/classification/Autores/SPECIES COMPOSITION DISSIMILARITY info:eu-repo/classification/Autores/NMDS info:eu-repo/classification/Autores/RAPIDEYE info:eu-repo/classification/Autores/REMOTE SENSING info:eu-repo/classification/Autores/LIDAR info:eu-repo/classification/Autores/LINEAR MODEL info:eu-repo/classification/Autores/MIXED MODEL info:eu-repo/classification/cti/2 info:eu-repo/classification/cti/24 info:eu-repo/classification/cti/2417 info:eu-repo/classification/cti/241715 info:eu-repo/classification/cti/241715 info:eu-repo/classification/Autores/FLORISTIC GRADIENT info:eu-repo/classification/Autores/SPECIES COMPOSITION DISSIMILARITY info:eu-repo/classification/Autores/NMDS info:eu-repo/classification/Autores/RAPIDEYE info:eu-repo/classification/Autores/REMOTE SENSING info:eu-repo/classification/Autores/LIDAR info:eu-repo/classification/Autores/LINEAR MODEL info:eu-repo/classification/Autores/MIXED MODEL info:eu-repo/classification/cti/2 info:eu-repo/classification/cti/24 info:eu-repo/classification/cti/2417 info:eu-repo/classification/cti/241715 info:eu-repo/classification/cti/241715 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 Beta-Diversity Modeling and Mapping with LiDAR and Multispectral Sensors in a Semi-Evergreen Tropical Forest |
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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. |
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info:eu-repo/semantics/article |
topic_facet |
info:eu-repo/classification/Autores/FLORISTIC GRADIENT info:eu-repo/classification/Autores/SPECIES COMPOSITION DISSIMILARITY info:eu-repo/classification/Autores/NMDS info:eu-repo/classification/Autores/RAPIDEYE info:eu-repo/classification/Autores/REMOTE SENSING info:eu-repo/classification/Autores/LIDAR info:eu-repo/classification/Autores/LINEAR MODEL info:eu-repo/classification/Autores/MIXED MODEL info:eu-repo/classification/cti/2 info:eu-repo/classification/cti/24 info:eu-repo/classification/cti/2417 info:eu-repo/classification/cti/241715 info:eu-repo/classification/cti/241715 |
author |
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 |
author_facet |
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 |
author_sort |
ALEJANDRA DEL PILAR OCHOA FRANCO |
title |
Beta-Diversity Modeling and Mapping with LiDAR and Multispectral Sensors in a Semi-Evergreen Tropical Forest |
title_short |
Beta-Diversity Modeling and Mapping with LiDAR and Multispectral Sensors in a Semi-Evergreen Tropical Forest |
title_full |
Beta-Diversity Modeling and Mapping with LiDAR and Multispectral Sensors in a Semi-Evergreen Tropical Forest |
title_fullStr |
Beta-Diversity Modeling and Mapping with LiDAR and Multispectral Sensors in a Semi-Evergreen Tropical Forest |
title_full_unstemmed |
Beta-Diversity Modeling and Mapping with LiDAR and Multispectral Sensors in a Semi-Evergreen Tropical Forest |
title_sort |
beta-diversity modeling and mapping with lidar and multispectral sensors in a semi-evergreen tropical forest |
url |
http://cicy.repositorioinstitucional.mx/jspui/handle/1003/1692 |
work_keys_str_mv |
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1756089283813310464 |