Beta-Diversity Modeling and Mapping with LiDAR and Multispectral Sensors in a Semi-Evergreen Tropical Forest

Paulino Pérez-Rodríguez,Hector De Los Santos-Posadas,Alejandra Ochoa-Franco,Juan Valdez-Hernández,Gregorio Ángeles-Pérez,José Valdez-Lazalde,José Hernández-Stefanoni

doi:10.3390/f10050419

Paulino Pérez-Rodríguez, Hector De Los Santos-Posadas + Show 5 more

Open Access

https://doi.org/10.3390/f10050419

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Abstract

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.

Highlights

Mexico is the fourth country with the greatest biological wealth, in which approximately between9% and 12% of the world’s discovered species live, despite representing approximately only 1.4% of the global territory [1]
We considered the metrics extracted from the smothered Canopy Height Model (CHM), the Digital Terrain Model (DTM)
There were significant differences in the non-metric multidimensional scaling (nMDS) axis-1 scores among patches of vegetation with different disturbance antecedents (Kruskal-Wallis test, p > 0.0001, Wilcoxon test, p < 0.0001), but the axis-2 showed no evidence for significant differences among patches (Wilcoxon test, p > 0.05), so there is not a clear ecological effect to report, and we considered the nMDS axis-1 alone as the representation of the floristic gradient, and we will be referring to it when writing β-diversity

Summary

Introduction

9% and 12% of the world’s discovered species live, despite representing approximately only 1.4% of the global territory [1] Much of this biological wealth is found in its 65 million ha of temperate and tropical forests [2], and approximately 6.2 million ha are formally managed for timber production [3]. The stand-level approach provides parameters such as the position of a specific plot on a floristic gradient of tree species dissimilarities (β-diversity) It denotes the variation in species composition among sites, giving the possibility of identifying areas with high species turnover, and planing areas of conservation not exclusively based on α-diversity, but considering simultaneously the minimum overlap in species composition, and maximizing the number of species preserved in the whole region [17,18,19]). While α-diversity is helpful for identifying areas with high local species richness and is amply documented (even for the study area [20]), β-diversity has seldom been studied and it is as important as α-diversity

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