Can terrestrial laser scanners (TLSs) and hemispherical photographs predict tropical dry forest succession with liana abundance?

Gerardo Arturo Sánchez-Azofeifa,Sandra Milena Durán,Mauricio Vega-Araya,Nikhil D'Souza,Carlos Portillo-Quintero,Carlos Campos-Vargas,Thomas Gianoli,Iain Sharp,J Antonio Guzmán-Quesada

doi:10.5194/bg-14-977-2017

Gerardo Arturo Sánchez-Azofeifa, Sandra Milena Durán + Show 7 more

Open Access

https://doi.org/10.5194/bg-14-977-2017

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Abstract

Abstract. Tropical dry forests (TDFs) are ecosystems with long drought periods, a mean temperature of 25 °C, a mean annual precipitation that ranges from 900 to 2000 mm, and that possess a high abundance of deciduous species (trees and lianas). What remains of the original extent of TDFs in the Americas remains highly fragmented and at different levels of ecological succession. It is estimated that one of the main fingerprints left by global environmental and climate change in tropical environments is an increase in liana coverage. Lianas are non-structural elements of the forest canopy that eventually kill their host trees. In this paper we evaluate the use of a terrestrial laser scanner (TLS) in combination with hemispherical photographs (HPs) to characterize changes in forest structure as a function of ecological succession and liana abundance. We deployed a TLS and HP system in 28 plots throughout secondary forests of different ages and with different levels of liana abundance. Using a canonical correlation analysis (CCA), we addressed how the VEGNET, a terrestrial laser scanner, and HPs could predict TDF structure. Likewise, using univariate analyses of correlations, we show how the liana abundance could affect the prediction of the forest structure. Our results suggest that TLSs and HPs can predict the differences in the forest structure at different successional stages but that these differences disappear as liana abundance increases. Therefore, in well known ecosystems such as the tropical dry forest of Costa Rica, these biases of prediction could be considered as structural effects of liana presence. This research contributes to the understanding of the potential effects of lianas in secondary dry forests and highlights the role of TLSs combined with HPs in monitoring structural changes in secondary TDFs.

Highlights

Lianas are a key structural component of tropical forests; they account for 25–40 % of the woody stems and more than 25 % of the woody species (Schnitzer and Bongers, 2011)
This analysis suggests that the DBHmean and TBA were the only parameters affected by the interaction between successional stages and liana abundance, where E successional plots with low liana abundance (LL) and I plots with high liana abundance (HL) showed lower values of DBHmean and TBA than E and I plots with HL and LL, respectively (Table 1)
This study evaluated the potential for terrestrial laser scanner (TLS) and hemispherical photographs to observe the differences between the successional stages of a tropical dry forest chronosequence and liana abundance

Summary

Introduction

Lianas (woody vines) are a key structural component of tropical forests; they account for 25–40 % of the woody stems and more than 25 % of the woody species (Schnitzer and Bongers, 2011). Lianas are structural parasites that use trees to ascend to the forest canopies and move from tree to tree. In the last two decades lianas have increased in density and biomass in old-growth forests (Phillips et al, 2002; Schnitzer and Bongers, 2011). This increment is considered to be one of the major structural changes in tropical forests (Phillips and Lewis, 2014). These structural changes may have potentially negative effects on carbon stocks since they tend to re-

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