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1.
New Phytol ; 222(3): 1284-1297, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-30720871

RESUMO

Seasonal dynamics in the vertical distribution of leaf area index (LAI) may impact the seasonality of forest productivity in Amazonian forests. However, until recently, fine-scale observations critical to revealing ecological mechanisms underlying these changes have been lacking. To investigate fine-scale variation in leaf area with seasonality and drought we conducted monthly ground-based LiDAR surveys over 4 yr at an Amazon forest site. We analysed temporal changes in vertically structured LAI along axes of both canopy height and light environments. Upper canopy LAI increased during the dry season, whereas lower canopy LAI decreased. The low canopy decrease was driven by highly illuminated leaves of smaller trees in gaps. By contrast, understory LAI increased concurrently with the upper canopy. Hence, tree phenological strategies were stratified by height and light environments. Trends were amplified during a 2015-2016 severe El Niño drought. Leaf area low in the canopy exhibited behaviour consistent with water limitation. Leaf loss from short trees in high light during drought may be associated with strategies to tolerate limited access to deep soil water and stressful leaf environments. Vertically and environmentally structured phenological processes suggest a critical role of canopy structural heterogeneity in seasonal changes in Amazon ecosystem function.


Assuntos
Secas , Florestas , Luz , Folhas de Planta/anatomia & histologia , Folhas de Planta/efeitos da radiação , Estações do Ano , Brasil , El Niño Oscilação Sul
2.
Ecol Lett ; 15(12): 1406-14, 2012 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-22994288

RESUMO

Tropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) - remotely estimated from LiDAR - control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth across tree size classes in forest near Manaus, Brazil. The same statistical model, with no parameterisation change but driven by different observed canopy structure, predicted the higher productivity of a site 500 km east. Gap fraction and a metric of vegetation vertical extent and evenness also predicted biomass gains and losses for one-hectare plots. Despite significant site differences in canopy structure and carbon dynamics, the relation between biomass growth and light fell on a unifying curve. This supported our hypothesis, suggesting that knowledge of canopy structure can explain variation in biomass growth over tropical landscapes and improve understanding of ecosystem function.


Assuntos
Carbono/metabolismo , Luz , Modelos Biológicos , Folhas de Planta/metabolismo , Árvores/metabolismo , Meio Ambiente
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