Literature DB >> 30720871

Seasonal and drought-related changes in leaf area profiles depend on height and light environment in an Amazon forest.

Marielle N Smith1,2, Scott C Stark1, Tyeen C Taylor2, Mauricio L Ferreira3, Eronaldo de Oliveira4, Natalia Restrepo-Coupe2,5, Shuli Chen2, Tara Woodcock2, Darlisson Bentes Dos Santos6, Luciana F Alves7, Michela Figueira4, Plinio B de Camargo3, Raimundo C de Oliveira8, Luiz E O C Aragão9,10, Donald A Falk11,12, Sean M McMahon13, Travis E Huxman14, Scott R Saleska2.   

Abstract

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.
© 2019 The Authors. New Phytologist © 2019 New Phytologist Trust.

Entities:  

Keywords:  Amazon forest; El Niño drought; LiDAR remote sensing; climate change; forest canopy structure; leaf area; phenology

Mesh:

Year:  2019        PMID: 30720871     DOI: 10.1111/nph.15726

Source DB:  PubMed          Journal:  New Phytol        ISSN: 0028-646X            Impact factor:   10.151


  7 in total

1.  Physical structure and biological composition of canopies in tropical secondary and old-growth forests.

Authors:  David B Clark; Steven F Oberbauer; Deborah A Clark; Michael G Ryan; Ralph O Dubayah
Journal:  PLoS One       Date:  2021-08-20       Impact factor: 3.240

Review 2.  Regional and local determinants of drought resilience in tropical forests.

Authors:  Renan Köpp Hollunder; Mário Luís Garbin; Fabio Rubio Scarano; Pierre Mariotte
Journal:  Ecol Evol       Date:  2022-05-24       Impact factor: 3.167

3.  Automatic Image Processing Algorithm for Light Environment Optimization Based on Multimodal Neural Network Model.

Authors:  Mujun Chen
Journal:  Comput Intell Neurosci       Date:  2022-06-03

4.  Drought-driven wildfire impacts on structure and dynamics in a wet Central Amazonian forest.

Authors:  Aline Pontes-Lopes; Camila V J Silva; Jos Barlow; Lorena M Rincón; Wesley A Campanharo; Cássio A Nunes; Catherine T de Almeida; Celso H L Silva Júnior; Henrique L G Cassol; Ricardo Dalagnol; Scott C Stark; Paulo M L A Graça; Luiz E O C Aragão
Journal:  Proc Biol Sci       Date:  2021-05-19       Impact factor: 5.349

5.  Plant sizes and shapes above and belowground and their interactions with climate.

Authors:  Shersingh Joseph Tumber-Dávila; H Jochen Schenk; Enzai Du; Robert B Jackson
Journal:  New Phytol       Date:  2022-03-08       Impact factor: 10.323

6.  Uncrewed aircraft system spherical photography for the vertical characterization of canopy structural traits.

Authors:  Vicent Agustí Ribas Costa; Maxime Durand; T Matthew Robson; Albert Porcar-Castell; Ilkka Korpela; Jon Atherton
Journal:  New Phytol       Date:  2022-02-22       Impact factor: 10.323

7.  Understanding spatiotemporal patterns of global forest NPP using a data-driven method based on GEE.

Authors:  Siyang Yin; Wenjin Wu; Xuejing Zhao; Chen Gong; Xinwu Li; Lu Zhang
Journal:  PLoS One       Date:  2020-03-10       Impact factor: 3.240

  7 in total

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