Tymen B., Vincent Grégoire, Courtois E. A., Heurtebize J., Dauzat J., Marechaux I., Chave J. (2017). Quantifying micro-environmental variation in tropical rainforest understory at landscape scale by combining airborne LiDAR scanning and a sensor network. Annals of Forest Science, 74 (2), p. art. 32 [13 p.]. ISSN 1286-4560.
Titre du document
Quantifying micro-environmental variation in tropical rainforest understory at landscape scale by combining airborne LiDAR scanning and a sensor network
Tymen B., Vincent Grégoire, Courtois E. A., Heurtebize J., Dauzat J., Marechaux I., Chave J.
Source
Annals of Forest Science, 2017,
74 (2), p. art. 32 [13 p.] ISSN 1286-4560
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 thesemetrics depend on forest type and proximity to canopy gaps. Our study has implications for the study of natural forest regeneration. Context 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. Aims 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. Methods 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 twomodels relating micro-environmental conditions to LiDAR metrics. Results 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. Conclusions 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.
Plan de classement
Sciences du monde végétal [076]
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Etudes, transformation, conservation du milieu naturel [082]
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Télédétection [126]
