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Array ( [TITRE] => <b>Type de document : </b> [TITRE_CLEAN] => Type de document [OPAC_SHOW] => 1 [TYPE] => list [AFF] => Mémoire [ID] => 4 [NAME] => cp_typdoc [DATATYPE] => integer [VALUES] => Array ( [0] => 4 ) )
![Assessing the drivers of forest structure and dynamics using airborne LiDAR and field data in an Indian monsoon forest](https://infodoc.agroparistech.fr/img_cache/pmb_agroparistech_record_187075.webp)
Titre : |
Assessing the drivers of forest structure and dynamics using airborne LiDAR and field data in an Indian monsoon forest
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Auteur(s) : | Anaïs Valance, Auteur (et co-auteur) |
Type de document : | Mémoire |
Filière : | Ing. DA : GF -- Gestion forestière |
Résumé : |
Understanding the drivers of forest structure and dynamics is very important for predicting the response of tropical forests to global change. These forests are among the most complex and rich ecosystems on the entire planet, and they play a main role in Carbon storage and dynamics. However, the scientific focus on the role of tropical forests in the global carbon budget is relatively recent, dating back to the end of the 20th century. In this study, we examined canopy height structure and dynamics in a wet evergreen tropical montane forest in order to understand the main drivers of their spatial variation. In particular, we focused on the effect of topography in this study. We used data series for trees ≥ 30 cm in girth standing at 1.3 m above the ground level and two airborne LiDAR [...]
Understanding the drivers of forest structure and dynamics is very important for predicting the response of tropical forests to global change. These forests are among the most complex and rich ecosystems on the entire planet, and they play a main role in Carbon storage and dynamics. However, the scientific focus on the role of tropical forests in the global carbon budget is relatively recent, dating back to the end of the 20th century. In this study, we examined canopy height structure and dynamics in a wet evergreen tropical montane forest in order to understand the main drivers of their spatial variation. In particular, we focused on the effect of topography in this study. We used data series for trees ≥ 30 cm in girth standing at 1.3 m above the ground level and two airborne LiDAR datasets, acquired in 2005 and 2013. We built linear models relating LiDAR canopy height, or LiDAR canopy change, with selected topographic variables considered as proxies of abiotic conditions: elevation, slope, curvature and aspect in the south-west direction. Statistical analyses revealed significant topographical effects on forest structure and dynamics. We observed a positive correlation between forest height and elevation but a negative one with curvature and slope. Forest height tends to be smaller in the south-west direction but the effect was not significant. Concerning forest dynamics, only elevation had a significant negative impact on canopy change. However, accounting for spatial autocorrelation in our data revealed that the forest structure and dynamics at the landscape scale were not significantly related with topographical gradients. It is a surprising result, especially with the complex topographical features of the Uppangala forest. Our results run against many studies and raise the importance of taking into account spatial autocorrelation when testing the relationship between two variables that are spatially structured.
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Editeur(s) : | Nancy [France] : AgroParisTech |
Date de publication : | 2016 |
Format : | 1 vol. (67 p.) / ill. en coul., couv. en coul., figures ; annexes / 30 cm |
Note(s) : |
Stage de fin de 3ème année de la formation d'Ingénieur AgroParisTech
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Langue(s) : | Anglais |
Lien vers la notice : | https://infodoc.agroparistech.fr/index.php?lvl=notice_display&id=187075 |
Exemplaires (1)
Localisation | Emplacement | Pôle | Section | Cote | Support | Disponibilité |
---|---|---|---|---|---|---|
Nancy | Bibliothèque | sans section | MEM-3A-2016-VALA-E | Numérique | Confidentiel Exclu du prêt |