Wagner, Fabien H.
Galvao, Lenio S.
Streher, Annia S.
Phillips, Oliver L.
Pugh, Thomas A. M.
Ometto, Jean P. H. B.
Aragao, Luiz E. O. C.
Número total de Autores: 9
Afiliação do(s) autor(es):
 Natl Inst Space Res INPE, Earth Observat & Geoinformat Div, BR-12227010 Sao Jose Dos Campos, SP - Brazil
 Fdn Sci Technol & Space Applicat FUNCATE, GeoProc Div, BR-12210131 Sao Jose Dos Campos, SP - Brazil
 Univ Leeds, Sch Geog, Leeds LS2 9JT, W Yorkshire - England
 Univ Birmingham, Sch Geog Earth & Environm Sci, Birmingham B15 2TT, W Midlands - England
 Univ Birmingham, Birmingham Inst Forest Res, Birmingham B15 2TT, W Midlands - England
 Natl Inst Space Res INPE, Earth Syst Sci Ctr, BR-12227010 Sao Jose Dos Campos, SP - Brazil
 Univ Exeter, Coll Life & Environm Sci, Geog, Exeter EX4 4RJ, Devon - England
Número total de Afiliações: 7
Tipo de documento:
JAN 14 2021.
Citações Web of Science:
We report large-scale estimates of Amazonian gap dynamics using a novel approach with large datasets of airborne light detection and ranging (lidar), including five multi-temporal and 610 single-date lidar datasets. Specifically, we (1) compared the fixed height and relative height methods for gap delineation and established a relationship between static and dynamic gaps (newly created gaps); (2) explored potential environmental/climate drivers explaining gap occurrence using generalized linear models; and (3) cross-related our findings to mortality estimates from 181 field plots. Our findings suggest that static gaps are significantly correlated to dynamic gaps and can inform about structural changes in the forest canopy. Moreover, the relative height outperformed the fixed height method for gap delineation. Well-defined and consistent spatial patterns of dynamic gaps were found over the Amazon, while also revealing the dynamics of areas never sampled in the field. The predominant pattern indicates 20-35% higher gap dynamics at the west and southeast than at the central-east and north. These estimates were notably consistent with field mortality patterns, but they showed 60% lower magnitude likely due to the predominant detection of the broken/uprooted mode of death. While topographic predictors did not explain gap occurrence, the water deficit, soil fertility, forest flooding and degradation were key drivers of gap variability at the regional scale. These findings highlight the importance of lidar in providing opportunities for large-scale gap dynamics and tree mortality monitoring over the Amazon. (AU)