Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates

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Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates. / Dalagnol, Ricardo; Wagner, Fabien H.; Galvão, Lênio S.; Streher, Annia S.; Phillips, Oliver L.; Gloor, Emanuel; Pugh, Thomas A.M.; Ometto, Jean P.H.B.; Aragão, Luiz E.O.C.

In: Scientific Reports, Vol. 11, No. 1, 1388, 12.2021.

Research output: Contribution to journalArticlepeer-review

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APA

Dalagnol, R., Wagner, F. H., Galvão, L. S., Streher, A. S., Phillips, O. L., Gloor, E., Pugh, T. A. M., Ometto, J. P. H. B., & Aragão, L. E. O. C. (2021). Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates. Scientific Reports, 11(1), [1388]. https://doi.org/10.1038/s41598-020-80809-w

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Author

Dalagnol, Ricardo ; Wagner, Fabien H. ; Galvão, Lênio S. ; Streher, Annia S. ; Phillips, Oliver L. ; Gloor, Emanuel ; Pugh, Thomas A.M. ; Ometto, Jean P.H.B. ; Aragão, Luiz E.O.C. / Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates. In: Scientific Reports. 2021 ; Vol. 11, No. 1.

Bibtex

@article{49844d1c242b4402af365736cfcb9e01,
title = "Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates",
abstract = "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.",
author = "Ricardo Dalagnol and Wagner, {Fabien H.} and Galv{\~a}o, {L{\^e}nio S.} and Streher, {Annia S.} and Phillips, {Oliver L.} and Emanuel Gloor and Pugh, {Thomas A.M.} and Ometto, {Jean P.H.B.} and Arag{\~a}o, {Luiz E.O.C.}",
note = "Funding Information: This research was supported by the S{\~a}o Paulo Research Foundation (FAPESP) [Grant numbers 2015/22987-7, 2015/50484-0, 2016/17652-9, 2019/09248-1 and 2019/21662-8]; the Brazilian National Council for Scientific and Technological Development (CNPq) [Grant numbers 160286/2019-0, 301486/2017-4, 305054/2016-3]; the BNDES-Amazon Fund [Grant number 14.2.0929.1]; the NAS and USAID [Grant number AID-OAA-A-11-00012] for the airborne lidar data acquisition; the CSSP Brazil; the Newton Fund/UK Met Office; the FORAMA Royal Society; the NERC BIO-RED [Grant number NE/N012542/1]; the European Research Council under the European Union Horizon 2020 programme [Grant number 758873, TreeMort]. We thank the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (EMBRAPA), the US Forest Service, USAID, and the US Department of State, for providing the multi-temporal airborne lidar dataset. We also thank the team from the EBA project, especially Mauro Assis and Luciane Sato, for supporting the use of the single-date lidar datasets. We thank the three anonymous reviewers which helped to improve this manuscript. Publisher Copyright: {\textcopyright} 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",
year = "2021",
month = dec,
doi = "10.1038/s41598-020-80809-w",
language = "English",
volume = "11",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
number = "1",

}

RIS

TY - JOUR

T1 - Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates

AU - Dalagnol, Ricardo

AU - Wagner, Fabien H.

AU - Galvão, Lênio S.

AU - Streher, Annia S.

AU - Phillips, Oliver L.

AU - Gloor, Emanuel

AU - Pugh, Thomas A.M.

AU - Ometto, Jean P.H.B.

AU - Aragão, Luiz E.O.C.

N1 - Funding Information: This research was supported by the São Paulo Research Foundation (FAPESP) [Grant numbers 2015/22987-7, 2015/50484-0, 2016/17652-9, 2019/09248-1 and 2019/21662-8]; the Brazilian National Council for Scientific and Technological Development (CNPq) [Grant numbers 160286/2019-0, 301486/2017-4, 305054/2016-3]; the BNDES-Amazon Fund [Grant number 14.2.0929.1]; the NAS and USAID [Grant number AID-OAA-A-11-00012] for the airborne lidar data acquisition; the CSSP Brazil; the Newton Fund/UK Met Office; the FORAMA Royal Society; the NERC BIO-RED [Grant number NE/N012542/1]; the European Research Council under the European Union Horizon 2020 programme [Grant number 758873, TreeMort]. We thank the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (EMBRAPA), the US Forest Service, USAID, and the US Department of State, for providing the multi-temporal airborne lidar dataset. We also thank the team from the EBA project, especially Mauro Assis and Luciane Sato, for supporting the use of the single-date lidar datasets. We thank the three anonymous reviewers which helped to improve this manuscript. Publisher Copyright: © 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/12

Y1 - 2021/12

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85099458577&partnerID=8YFLogxK

U2 - 10.1038/s41598-020-80809-w

DO - 10.1038/s41598-020-80809-w

M3 - Article

C2 - 33446809

AN - SCOPUS:85099458577

VL - 11

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

IS - 1

M1 - 1388

ER -