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Modelling species richness and functional diversity in tropical dry forests using multispectral remotely sensed and topographic data
VÍCTOR ALEXIS PEÑA LARA
JUAN MANUEL DUPUY RADA
Casandra Reyes García
Lucía Sanaphre Villanueva
Carlos Portillo-Quintero
JOSE LUIS HERNANDEZ STEFANONI
Acceso Abierto
Atribución-NoComercial-SinDerivadas
https://doi.org/10.3390/rs14235919
PLANT DIVERSITY
FUNCTIONAL DIVERSITY
FUNCTIONAL TRAITS
SENTINEL-2
TEXTURE ANALYSIS
NATIONAL FOREST INVENTORY
Efforts to assess and understand changes in plant diversity and ecosystem functioning focus on the analysis of taxonomic diversity. However, the resilience of ecosystems depends not only on species richness but also on the functions (responses and effects) of species within communities and ecosystems. Therefore, a functional approach is required to estimate functional diversity through functional traits and to model its changes in space and time. This study aims to: (i) assess the accuracy of estimates of species richness and tree functional richness obtained from field data and Sentinel-2 imagery in tropical dry forests of the Yucatan Peninsula; (ii) map and analyze the relationships between these two variables. We calculated species richness and functional richness (from six functional traits) of trees from 87 plots of the National Forest Inventory in a semi-deciduous tropical forest and 107 in a semi-evergreen tropical forest. Species richness and functional richness were mapped using reflectance values, vegetation indices, and texture measurements from Sentinel-2 imagery as explanatory variables. Validation of the models to map these two variables yielded a coefficient of determination (R2) of 0.43 and 0.50, and a mean squared relative error of 25.4% and 48.8%, for tree species richness and functional richness, respectively. For both response variables, the most important explanatory variables were Sentinel-2 texture measurements and spectral bands. Tree species richness and functional richness were positively correlated in both forest types. Bivariate maps showed that 44.9% and 26.5% of the forests studied had high species richness and functional richness values. Our findings highlight the importance of integrating field data and remotely sensed variables for estimating tree species richness and functional richness. In addition, the combination of species richness and functional richness maps presented here is potentially valuable for planning, conservation, and restoration strategies by identifying areas that maximize ecosystem service provisioning, carbon storage, and biodiversity conservation. © 2022 by the authors.
2022
Artículo
Remote Sensing, 14(23), 5919, 2022.
Inglés
Peña-Lara, V.A.; Dupuy, J.M.; Reyes-Garcia, C.; Sanaphre-Villanueva, L.; Portillo-Quintero, C.A.; Hernández-Stefanoni, J.L. Modelling Species Richness and Functional Diversity in Tropical Dry Forests Using Multispectral Remotely Sensed and Topographic Data. Remote Sens. 2022, 14, 5919.https://doi.org/ 10.3390/rs14235919
ECOLOGÍA VEGETAL
Versión publicada
publishedVersion - Versión publicada
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