Articles | Volume 18, issue 24
https://doi.org/10.5194/bg-18-6517-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-18-6517-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Dec 2021
Research article |
| 20 Dec 2021
| 20 Dec 2021
Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5 years of monthly drone data for a 50 ha plot
Raquel Fernandes Araujo
CORRESPONDING AUTHOR
Forest Global Earth Observatory (Center for Tropical Forest Science),
Smithsonian Tropical Research Institute, P.O. Box 0843-03092, Balboa, Ancón,
Panama
Samuel Grubinger
Department of Forest Resources Management, University of British
Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada
Carlos Henrique Souza Celes
Forest Global Earth Observatory (Center for Tropical Forest Science),
Smithsonian Tropical Research Institute, P.O. Box 0843-03092, Balboa, Ancón,
Panama
Robinson I. Negrón-Juárez
Climate Sciences Department, Lawrence Berkeley National Laboratory, 1
Cyclotron Road, Berkeley, CA 94720, USA
Milton Garcia
Forest Global Earth Observatory (Center for Tropical Forest Science),
Smithsonian Tropical Research Institute, P.O. Box 0843-03092, Balboa, Ancón,
Panama
Jonathan P. Dandois
Facilities Information Technology, Johns Hopkins Facilities and Real Estate, Johns Hopkins University, 3910 Keswick Rd., Suite N3100, Baltimore, MD 21211, USA
Helene C. Muller-Landau
Forest Global Earth Observatory (Center for Tropical Forest Science),
Smithsonian Tropical Research Institute, P.O. Box 0843-03092, Balboa, Ancón,
Panama
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Cited articles
Aleixo, I., Norris, D., Hemerik, L., Barbosa, A., Prata, E., Costa, F., and
Poorter, L.: Amazonian rainforest tree mortality driven by climate and
functional traits, Nat. Clim. Change, 9, 384–388,
https://doi.org/10.1038/s41558-019-0458-0, 2019.
Araujo, R. F., Nelson, B. W., Celes, C. H. S., and Chambers, J. Q.: Regional
distribution of large blowdown patches across Amazonia in 2005 caused by a
single convective squall line: Distribution of Amazonia Blowdown Damage,
Geophys. Res. Lett., 44, 7793–7798, https://doi.org/10.1002/2017GL073564,
2017.
Araujo, R. F., Chambers, J. Q., Celes, C. H. S., Muller-Landau, H. C.,
Santos, A. P. F. dos, Emmert, F., Ribeiro, G. H. P. M., Gimenez, B. O.,
Lima, A. J. N., Campos, M. A. A., and Higuchi, N.: Integrating high
resolution drone imagery and forest inventory to distinguish canopy and
understory trees and quantify their contributions to forest structure and
dynamics, PLoS ONE, 15, e0243079,
https://doi.org/10.1371/journal.pone.0243079, 2020.
Araujo, R. F., Celes, C. H. S., Negrón-Juárez, R. I., and Muller-Landau, H. C.: Analysis codes and datasets: Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from five years of monthly drone data for a 50-ha plot, Zenodo [code], https://doi.org/10.5281/zenodo.5786740, 2021a.
Araujo, R. F., Grubinger, S., Garcia, M., Dandois, J. P., and Muller-Landau, H. C.: Collection of datasets: Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5 years of monthly drone data for a 50-ha plot, Smithsonian Tropical Research Institute, Collection, Figshare [data set], https://doi.org/10.25573/data.c.5389043.v1, 2021b.
Arellano, G., Medina, N. G., Tan, S., Mohamad, M., and Davies, S. J.: Crown
damage and the mortality of tropical trees, New Phytol., 221, 169–179,
https://doi.org/10.1111/nph.15381, 2019.
Asner, G. P., Kellner, J. R., Kennedy-Bowdoin, T., Knapp, D. E., Anderson,
C., and Martin, R. E.: Forest Canopy Gap Distributions in the Southern
Peruvian Amazon, PLoS ONE, 8, e60875,
https://doi.org/10.1371/journal.pone.0060875, 2013.
Aubry-Kientz, M., Rossi, V., Cornu, G., Wagner, F., and Hérault, B.:
Temperature rising would slow down tropical forest dynamic in the Guiana
Shield, Sci. Rep., 9, 10235, https://doi.org/10.1038/s41598-019-46597-8, 2019.
Brokaw, N. V. L.: Treefalls: frequency, timing, and consequences, in: The
ecology of a tropical forest: seasonal rhythms and long-term changes,
Smithsonian Institution, Washington, DC, 101–108, ISBN 0874746019, 1982.
Brokaw, N. V. L.: Gap-Phase Regeneration in a Tropical Forest, Ecology, 66, 682–687,
https://doi.org/10.2307/1940529, 1985.
Burnham, K. P. and Anderson, D. R.: Model selection and multimodel
inference: a practical information-theoretic approach, 2nd Edn.,
Springer-Verlag New York, New York, 520 pp., ISBN 0387953647, 2002.
Carvalho, L.: An Improved Evaluation of Kolmogorov's Distribution, J. Stat.
Soft., 65, 1–8, https://doi.org/10.18637/jss.v065.c03, 2015.
Cavaleri, M. A., Reed, S. C., Smith, W. K., and Wood, T. E.: Urgent need for
warming experiments in tropical forests, Glob. Change Biol., 21, 2111–2121,
https://doi.org/10.1111/gcb.12860, 2015.
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., and Aragão, L. E. O.
C.: Large-scale variations in the dynamics of Amazon forest canopy gaps from
airborne lidar data and opportunities for tree mortality estimates, Sci. Rep.,
11, 1388, https://doi.org/10.1038/s41598-020-80809-w, 2021.
Dalling, J. W., Winter, K., and Hubbell, S. P.: Variation in growth
responses of neotropical pioneers to simulated forest gaps, Funct Ecol.,
18, 725–736, https://doi.org/10.1111/j.0269-8463.2004.00868.x, 2004.
Dandois, J. P. and Ellis, E. C.: High spatial resolution three-dimensional
mapping of vegetation spectral dynamics using computer vision, Remote
Sens. Environ., 136, 259–276,
https://doi.org/10.1016/j.rse.2013.04.005, 2013.
Deb, J., Phinn, S., Butt, N., and Mcalpine, C.: Climate change impacts on
tropical forests: identifying risks for tropical Asia, J. Trop.l Forest Sci., 30, 182–194, 2018.
Denslow, J. S.: Patterns of plant species diversity during succession under
different disturbance regimes, Oecologia, 46, 18–21,
https://doi.org/10.1007/BF00346960, 1980.
Denslow, J. S.: Tropical Rainforest Gaps and Tree Species Diversity, Ann. Rev. Ecol. Syst., 1,
431–451, 1987.
Fisher, J. I., Hurtt, G. C., Thomas, R. Q., and Chambers, J. Q.: Clustered
disturbances lead to bias in large-scale estimates based on forest sample
plots: Clustered disturbance and forest plot bias, Ecol. Lett., 11, 554–563,
https://doi.org/10.1111/j.1461-0248.2008.01169.x, 2008.
Fontes, C. G., Chambers, J. Q., and Higuchi, N.: Revealing the causes and
temporal distribution of tree mortality in Central Amazonia, Forest Ecol.
Manag., 424, 177–183, https://doi.org/10.1016/j.foreco.2018.05.002,
2018.
Garstang, M., White, S., Shugart, H. H., and Halverson, J.: Convective cloud
downdrafts as the cause of large blowdowns in the Amazon rainforest,
Meteorl. Atmos. Phys., 67, 199–212, https://doi.org/10.1007/BF01277510,
1998.
Hall, J., Muscarella, R., Quebbeman, A., Arellano, G., Thompson, J.,
Zimmerman, J. K., and Uriarte, M.: Hurricane-Induced Rainfall is a Stronger
Predictor of Tropical Forest Damage in Puerto Rico Than Maximum Wind Speeds,
Sci. Rep., 10, 4318, https://doi.org/10.1038/s41598-020-61164-2, 2020.
Harms, K. E., Condit, R., Hubbell, S. P., and Foster, R. B.: Habitat
associations of trees and shrubs in a 50-ha neotropical forest plot:
Habitat associations of trees and shrubs, J. Ecol., 89, 947–959, https://doi.org/10.1111/j.1365-2745.2001.00615.x, 2001.
Holdridge, L. R.: Determination of World Plant Formations from Simple
Climatic Data, Science, 105, 367–368, 1947.
Hubbell, S. P., Foster, R. B., O'Brien, S. T., Harms, K. E., Condit, R.,
Wechsler, B., Wright, S. J., and Loo de Lao, S.: Light-Gap Disturbances,
Recruitment Limitation, and Tree Diversity in a Neotropical Forest, Science, 283,
554–557, https://doi.org/10.1126/science.283.5401.554, 1999.
IPCC: Summary for Policymakers, in: Climate Change 2014, Mitigation of
Climate Change. Contribution of Working Group III to the Fifth Assessment
Report of the Intergovernmental Panel on Climate Change, Cambridge
University Press, United Kingdom and New York, NY, USA, 32 pp., ISBN 978-92-9169-143-2, 2014.
Jackson, T., Shenkin, A., Wellpott, A., Calders, K., Origo, N., Disney, M.,
Burt, A., Raumonen, P., Gardiner, B., Herold, M., Fourcaud, T., and Malhi,
Y.: Finite element analysis of trees in the wind based on terrestrial laser
scanning data, Agr. Forest Meteorol., 265, 137–144,
https://doi.org/10.1016/j.agrformet.2018.11.014, 2019.
Jansen, P. A., Meer, P. J. V. der, and Bongers, F.: Spatial contagiousness
of canopy disturbance in tropical rain forest: An individual-tree-based
test, Ecology, 89, 3490–3502, https://doi.org/10.1890/07-1682.1, 2008.
Jaramillo, L., Poveda, G., and Mejía, J. F.: Mesoscale convective
systems and other precipitation features over the tropical Americas and
surrounding seas as seen by TRMM, Int. J. Climatol, 37, 380–397,
https://doi.org/10.1002/joc.5009, 2017.
Johnson, M. O., Galbraith, D., Gloor, M., De Deurwaerder, H., Guimberteau,
M., Rammig, A., Thonicke, K., Verbeeck, H., Randow, C., Monteagudo, A.,
Phillips, O. L., Brienen, R. J. W., Feldpausch, T. R., Lopez Gonzalez, G.,
Fauset, S., Quesada, C. A., Christoffersen, B., Ciais, P., Sampaio, G.,
Kruijt, B., Meir, P., Moorcroft, P., Zhang, K., Alvarez-Davila, E., Alves de
Oliveira, A., Amaral, I., Andrade, A., Aragao, L. E. O. C., Araujo-Murakami,
A., Arets, E. J. M. M., Arroyo, L., Aymard, G. A., Baraloto, C., Barroso,
J., Bonal, D., Boot, R., Camargo, J., Chave, J., Cogollo, A., Cornejo
Valverde, F., Lola da Costa, A. C., Di Fiore, A., Ferreira, L., Higuchi, N.,
Honorio, E. N., Killeen, T. J., Laurance, S. G., Laurance, W. F., Licona,
J., Lovejoy, T., Malhi, Y., Marimon, B., Marimon, B. H., Matos, D. C. L.,
Mendoza, C., Neill, D. A., Pardo, G., Peña-Claros, M., Pitman, N. C. A.,
Poorter, L., Prieto, A., Ramirez-Angulo, H., Roopsind, A., Rudas, A.,
Salomao, R. P., Silveira, M., Stropp, J., Steege, H., Terborgh, J., Thomas,
R., Toledo, M., Torres-Lezama, A., Heijden, G. M. F., Vasquez, R.,
Guimarães Vieira, I. C., Vilanova, E., Vos, V. A., and Baker, T. R.:
Variation in stem mortality rates determines patterns of above-ground
biomass in Amazonian forests: implications for dynamic global vegetation
models, Glob. Change Biol., 22, 3996–4013, https://doi.org/10.1111/gcb.13315,
2016.
Kellner, J. R. and Asner, G. P.: Convergent structural responses of tropical
forests to diverse disturbance regimes, Ecol. Lett., 12, 887–897,
https://doi.org/10.1111/j.1461-0248.2009.01345.x, 2009.
Leigh, E. G. Jr.: Tropical forest ecology: a view from Barro Colorado
Island, Oxford University Press, Oxford, 264 pp., ISBN 9780195096033, 1999.
Leitold, V., Morton, D. C., Longo, M., dos-Santos, M. N., Keller, M., and
Scaranello, M.: El Niño drought increased canopy turnover in Amazon
forests, New Phytol., 219, 959–971, https://doi.org/10.1111/nph.15110, 2018.
Lobo, E. and Dalling, J. W.: Effects of topography, soil type and forest age
on the frequency and size distribution of canopy gap disturbances in a
tropical forest, Biogeosciences, 10, 6769–6781,
https://doi.org/10.5194/bg-10-6769-2013, 2013.
Lobo, E. and Dalling, J. W.: Spatial scale and sampling resolution affect
measures of gap disturbance in a lowland tropical forest: implications for
understanding forest regeneration and carbon storage, Proc. R. Soc. B., 281,
20133218, https://doi.org/10.1098/rspb.2013.3218, 2014.
Manrubia, S. C. and Solé, R. V.: On Forest Spatial Dynamics with Gap
Formation, J. Theor. Biol., 187, 159–164,
https://doi.org/10.1006/jtbi.1997.0409, 1997.
Marra, D. M., Chambers, J. Q., Higuchi, N., and Trumbore, S. E.: Large-Scale
Wind Disturbances Promote Tree Diversity in a Central Amazon Forest, PLOS ONE, 9, e103711, https://doi.org/10.1371/journal.pone.0103711,
2014.
Marvin, D. C. and Asner, G. P.: Branchfall dominates annual carbon flux
across lowland Amazonian forests, Environ. Res. Lett., 11, 094027,
https://doi.org/10.1088/1748-9326/11/9/094027, 2016.
McDowell, N., Allen, C. D., Anderson-Teixeira, K., Brando, P., Brienen, R.,
Chambers, J., Christoffersen, B., Davies, S., Doughty, C., Duque, A.,
Espirito-Santo, F., Fisher, R., Fontes, C. G., Galbraith, D., Goodsman, D.,
Grossiord, C., Hartmann, H., Holm, J., Johnson, D. J., Kassim, Abd. R.,
Keller, M., Koven, C., Kueppers, L., Kumagai, T., Malhi, Y., McMahon, S. M.,
Mencuccini, M., Meir, P., Moorcroft, P., Muller-Landau, H. C., Phillips, O.
L., Powell, T., Sierra, C. A., Sperry, J., Warren, J., Xu, C., and Xu, X.:
Drivers and mechanisms of tree mortality in moist tropical forests, New
Phytol., 219, 851–869, https://doi.org/10.1111/nph.15027, 2018.
McMahon, S. M., Arellano, G., and Davies, S. J.: The importance and
challenges of detecting changes in forest mortality rates, Ecosphere, 10,
e02615, https://doi.org/10.1002/ecs2.2615, 2019.
Muller-Landau, H. C., Condit, R. S., Harms, K. E., Marks, C. O., Thomas, S.
C., Bunyavejchewin, S., Chuyong, G., Co, L., Davies, S., Foster, R.,
Gunatilleke, S., Gunatilleke, N., Hart, T., Hubbell, S. P., Itoh, A.,
Kassim, A. R., Kenfack, D., LaFrankie, J. V., Lagunzad, D., Lee, H. S.,
Losos, E., Makana, J.-R., Ohkubo, T., Samper, C., Sukumar, R., Sun, I.-F.,
Nur Supardi, M. N., Tan, S., Thomas, D., Thompson, J., Valencia, R.,
Vallejo, M. I., Munoz, G. V., Yamakura, T., Zimmerman, J. K., Dattaraja, H.
S., Esufali, S., Hall, P., He, F., Hernandez, C., Kiratiprayoon, S., Suresh,
H. S., Wills, C., and Ashton, P.: Comparing tropical forest tree size
distributions with the predictions of metabolic ecology and equilibrium
models, Ecol. Lett., 9, 589–602,
https://doi.org/10.1111/j.1461-0248.2006.00915.x, 2006a.
Muller-Landau, H. C., Condit, R. S., Chave, J., Thomas, S. C., Bohlman, S.
A., Bunyavejchewin, S., Davies, S., Foster, R., Gunatilleke, S.,
Gunatilleke, N., Harms, K. E., Hart, T., Hubbell, S. P., Itoh, A., Kassim,
A. R., LaFrankie, J. V., Lee, H. S., Losos, E., Makana, J.-R., Ohkubo, T.,
Sukumar, R., Sun, I.-F., Nur Supardi, M. N., Tan, S., Thompson, J.,
Valencia, R., Munoz, G. V., Wills, C., Yamakura, T., Chuyong, G., Dattaraja,
H. S., Esufali, S., Hall, P., Hernandez, C., Kenfack, D., Kiratiprayoon, S.,
Suresh, H. S., Thomas, D., Vallejo, M. I., and Ashton, P.: Testing metabolic
ecology theory for allometric scaling of tree size, growth and mortality in
tropical forests, Ecol. Lett., 9, 575–588,
https://doi.org/10.1111/j.1461-0248.2006.00904.x, 2006b.
Muller-Landau, H. C., Cushman, K. C., Arroyo, E. E., Martinez Cano, I.,
Anderson-Teixeira, K. J., and Backiel, B.: Patterns and mechanisms of
spatial variation in tropical forest productivity, woody residence time, and
biomass, New Phytol., 229, 3065–3087, https://doi.org/10.1111/nph.17084,
2021.
Negrón-Juárez, R. I., Chambers, J. Q., Guimaraes, G., Zeng, H.,
Raupp, C. F. M., Marra, D. M., Ribeiro, G. H. P. M., Saatchi, S. S., Nelson,
B. W., and Higuchi, N.: Widespread Amazon forest tree mortality from a
single cross-basin squall line event: wind-driven tree mortality in
amazonia, Geophys. Res. Lett., 37, 1–5,
https://doi.org/10.1029/2010GL043733, 2010.
Negrón-Juárez, R. I., Jenkins, H. S., Raupp, C. F. M., Riley, W. J.,
Kueppers, L. M., and Marra, D. M.: Windthrow Variability in Central
Amazonia, Atmosphere, 17, 1–17, 2017.
Negrón-Juárez, R. I., Holm, J. A., Marra, D. M., Rifai, S. W.,
Riley, W. J., Chambers, J. Q., Koven, C. D., Knox, R. G., McGroddy, M. E.,
Di Vittorio, A. V., Urquiza-Muñoz, J., Tello-Espinoza, R., Muñoz, W.
A., Ribeiro, G. H. P. M., and Higuchi, N.: Vulnerability of Amazon forests
to storm-driven tree mortality, Environ. Res. Lett., 13, 054021,
https://doi.org/10.1088/1748-9326/aabe9f, 2018.
Phillips, O. L., Lloyd, J., Malhi, Y., Monteagudo, A., Almeida, S., Davila,
E. A., Amaral, I., Andelman, S., Andrade, A., Arroyo, L., Aymard, G., Baker,
T. R., and Bonal, D.: Drought–mortality relationships for tropical forests, New Phytol.,
16, 631–646, 2010.
Silva, C. A., Valbuena, R., Pinagé, E. R., Mohan, M., Almeida, D. R. A.,
North Broadbent, E., Jaafar, W. S. W. M., Papa, D., Cardil, A., and
Klauberg, C.: ForestGapR: An R Package for forest gap analysis from canopy
height models, Method. Ecol. Evol., 10, 1347–1356,
https://doi.org/10.1111/2041-210X.13211, 2019.
Silva, C. V. J., Aragão, L. E. O. C., Barlow, J., Espirito-Santo, F.,
Young, P. J., Anderson, L. O., Berenguer, E., Brasil, I., Foster Brown, I.,
Castro, B., Farias, R., Ferreira, J., França, F., Graça, P. M. L.
A., Kirsten, L., Lopes, A. P., Salimon, C., Scaranello, M. A., Seixas, M.,
Souza, F. C., and Xaud, H. A. M.: Drought-induced Amazonian wildfires
instigate a decadal-scale disruption of forest carbon dynamics, Philos. T.
R. Soc. B, 373, 20180043, https://doi.org/10.1098/rstb.2018.0043, 2018.
Solé, R. V. and Manrubia, S. C.: Are rainforests self-organized in a
critical state?, J. Theor. Biol., 173, 31–40,
https://doi.org/10.1006/jtbi.1995.0040, 1995.
Windsor, D. M.: Climate and moisture variability in a tropical forest: long-term records from Barro Colorado Island, Panamá, Smithsonian
Contributions to the Earth Sciences, 29, 1–45,
https://doi.org/10.5479/si.00810274.29.1, 1990.
Xu, L., Saatchi, S. S., Yang, Y., Yu, Y., Pongratz, J., Bloom, A. A.,
Bowman, K., Worden, J., Liu, J., Yin, Y., Domke, G., McRoberts, R. E.,
Woodall, C., Nabuurs, G.-J., de-Miguel, S., Keller, M., Harris, N., Maxwell,
S., and Schimel, D.: Changes in global terrestrial live biomass over the
21st century, Sci. Adv., 7, eabe9829,
https://doi.org/10.1126/sciadv.abe9829, 2021.
Yanoviak, S. P., Gora, E. M., Burchfield, J. M., Bitzer, P. M., and Detto,
M.: Quantification and identification of lightning damage in tropical
forests, Ecol. Evol., 7, 5111–5122, https://doi.org/10.1002/ece3.3095, 2017.
Zahawi, R. A., Dandois, J. P., Holl, K. D., Nadwodny, D., Reid, J. L., and
Ellis, E. C.: Using lightweight unmanned aerial vehicles to monitor tropical
forest recovery, Biol. Conserv., 186, 287–295,
https://doi.org/10.1016/j.biocon.2015.03.031, 2015.
Short summary
Our study contributed to improving the understanding of temporal variation and climate correlates of canopy disturbances mainly caused by treefalls and branchfalls. We used a unique dataset of 5 years of approximately monthly drone-acquired RGB (red–green–blue) imagery for 50 ha of mature tropical forest on Barro Colorado Island, Panama. We found that canopy disturbance rates were highly temporally variable, were higher in the wet season, and were related to extreme rainfall events.
Our study contributed to improving the understanding of temporal variation and climate...
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