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Topography and Three-Dimensional Structure Can Estimate Tree Diversity along a Tropical Elevational Gradient in Costa Rica

1
Department of Geography, University of California, Los Angeles, CA 90095, USA
2
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
3
Institute of Environment and Sustainability, University of California, Los Angeles, CA 90095, USA
4
Department of Biology, University of Missouri-St. Louis, St. Louis, MO 63121, USA
5
Organization for Tropical Studies, Puerto Viejo de Sarapiquí, Heredia 41001, Costa Rica
6
Department of Statistics, University of California, Los Angeles, CA 90095, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(4), 629; https://doi.org/10.3390/rs10040629
Received: 25 February 2018 / Revised: 7 April 2018 / Accepted: 12 April 2018 / Published: 18 April 2018
(This article belongs to the Special Issue Remote Sensing of Tropical Forest Biodiversity)
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Abstract

This research seeks to understand how tree species richness and diversity relates to field data (1-ha plots) on forest structure (stems, basal area) and lidar derived data on topography and three-dimensional forest structure along an elevational gradient in Braulio Carrillo National Park, Costa Rica. In 2016 we calculated tree species richness and diversity indices for twenty 1-ha plots located along a gradient ranging from 56 to 2814 m in elevation. Field inventory data were combined with large footprint (20 m) airborne lidar data over plots in 2005, in order to quantify variations in topography and three-dimensional structure across plots and landscapes. A distinct pattern revealing an increase in species’ richness and the Shannon diversity index was observed in correlation with increasing elevation, up to about 600 m; beyond that, at higher elevations, a decrease was observed. Stem density and basal area both peaked at the 2800 m site, with a mini-peak at 600 m, and were both negatively associated with species richness and diversity. Species richness and diversity were negatively correlated with elevation, while the two tallest relative height metrics (rh100, rh75) derived from lidar were both significantly positively correlated with species richness and diversity. The best lidar-derived topographical and three-dimensional forest structural models showed a strong relationship with the Shannon diversity index (r2 = 0.941, p < 0.01), with ten predictors; conversely, the best species richness model was weaker (r2 = 0.599, p < 0.01), with two predictors. We realize that our high r² has to be interpreted with caution due to possible overfitting, since we had so few ground plots in which to develop the relationship with the numerous topographical and structural explanatory variables. However, this is still an interesting analysis, even with the issue of overfitting. To reduce issues with overfitting we used ridge regression, which acted as a regularization method, shrinking coefficients in order to decrease their variability and multicollinearity. This study is unique because it uses paired 1-ha plot and airborne lidar data over a tropical elevation gradient, and suggests potential for mapping species richness and diversity across elevational gradients in tropical montane ecosystems using topography and relative height metrics from spaceborne lidar with greater spatial coverage (e.g., GEDI). View Full-Text
Keywords: Costa Rica; lidar; montane gradient; neotropical forest; remote sensing; tree diversity Costa Rica; lidar; montane gradient; neotropical forest; remote sensing; tree diversity
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Robinson, C.; Saatchi, S.; Clark, D.; Hurtado Astaiza, J.; Hubel, A.F.; Gillespie, T.W. Topography and Three-Dimensional Structure Can Estimate Tree Diversity along a Tropical Elevational Gradient in Costa Rica. Remote Sens. 2018, 10, 629.

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