Annals of Forest Science

, 74:32

Quantifying micro-environmental variation in tropical rainforest understory at landscape scale by combining airborne LiDAR scanning and a sensor network

  • Blaise Tymen
  • Grégoire Vincent
  • Elodie A. Courtois
  • Julien Heurtebize
  • Jean Dauzat
  • Isabelle Marechaux
  • Jérôme Chave
Original Paper

DOI: 10.1007/s13595-017-0628-z

Cite this article as:
Tymen, B., Vincent, G., Courtois, E.A. et al. Annals of Forest Science (2017) 74: 32. doi:10.1007/s13595-017-0628-z


Key message

We combined aerial LiDAR and ground sensors to map the spatial variation in micro-environmental variables of the tropical forest understory. We show that these metrics depend on forest type and proximity to canopy gaps. Our study has implications for the study of natural forest regeneration.


Light impacts seedling dynamics and animals, either directly or through their effect on air temperature and relative humidity. However, the micro-environment of tropical forest understories is heterogeneous.


We explored whether aerial laser scanning (LiDAR) can describe short-scale micro-environmental variables. We also studied the determinants of their spatial and intra-annual variation.


We used a small-footprint LiDAR coverage combined with data obtained from 47 environmental sensors monitoring continuously understory light, moisture and temperature during 1 year over the area. We developed and tested two models relating micro-environmental conditions to LiDAR metrics.


We found that a volume-based model predicts empirical light fluxes better than a model based on the proportion of the LiDAR signal reaching the ground. Understory field sensors measured an average daily light flux between 2.9 and 4.7% of full sunlight. Relative seasonal variation was comparable in the understory and in clearings. In canopy gaps, light flux was 4.3 times higher, maximal temperature 15% higher and minimal relative humidity 25% lower than in the forest understory. We found consistent micro-environmental differences among forest types.


LiDAR coverage improves the fine-scale description of micro-environmental variables of tropical forest understories. This opens avenues for modelling the distribution and dynamics of animal and plant populations.


French Guiana Light Nouragues station Plant dynamics Temperature Relative humidity 

Supplementary material

13595_2017_628_MOESM1_ESM.docx (119 kb)
Fig. S1(DOCX 119 kb)
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Table S1(DOCX 14 kb)
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Table S2(DOCX 12 kb)
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Table S3(DOCX 16 kb)

Copyright information

© INRA and Springer-Verlag France 2017

Authors and Affiliations

  • Blaise Tymen
    • 1
  • Grégoire Vincent
    • 2
  • Elodie A. Courtois
    • 3
    • 4
  • Julien Heurtebize
    • 2
  • Jean Dauzat
    • 2
  • Isabelle Marechaux
    • 1
  • Jérôme Chave
    • 1
  1. 1.Laboratoire Evolution et Diversité Biologique UMR 5174, CNRSUniversité Paul SabatierToulouseFrance
  2. 2.IRD, UMR AMAP, TA A-51/PS1MontpellierFrance
  3. 3.Laboratoire Ecologie, évolution, interactions des systèmes amazoniens (LEEISA)Université de Guyane, CNRS, IFREMERCayenneFrance
  4. 4.Department of Biology, Centre of Excellence PLECO (Plant and Vegetation Ecology)University of AntwerpWilrijkBelgium

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