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Preprints
https://doi.org/10.5194/bg-2019-451
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-2019-451
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  10 Dec 2019

10 Dec 2019

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A revised version of this preprint is currently under review for the journal BG.

Landsat NIR band and ELM-FATES sensitivity to forest disturbances and regrowth in the Central Amazon

Robinson I. Negrón-Juárez1, Jennifer A. Holm1, Boris Faybishenko1, Daniel Magnabosco-Marra2,3, Rosie A. Fisher4,5, Jacquelyn K. Shuman4, Alessandro C. de Araujo6, William J. Riley1, and Jeffrey Q. Chambers1 Robinson I. Negrón-Juárez et al.
  • 1Lawrence Berkeley National Laboratory, Climate Sciences Department, 1 Cyclotron Road, Berkeley, CA 94720, USA
  • 2Max-Planck-Institute for Biogeochemistry, Hans-Knoell Str. 10, 07745 Jena, Germany
  • 3Brazil's National Institute for Research in Amazonia (INPA), Av André Araújo 2936, 690060-001, Manaus, Brazil
  • 4National Center for Atmospheric Research (NCAR), 1850 Table Mesa Dr, Boulder, CO 80305, USA
  • 5Centre Européen Research et de Formation Avencée en Calcul Scientifique, (CERFACS) Toulouse, France
  • 6Brazilian Agricultural Research Corporation – Embrapa) Eastern Amazon. Trav. Dr. Enéas Pinheiro, s/n°, Bairro Marco, CEP: 66095-903, Brazil

Abstract. Forest disturbance and regrowth are key processes in forest dynamics but detailed information of these processes is difficult to obtain in remote forests as the Amazon. We used chronosequences of Landsat satellite imagery to determine the sensitivity of surface reflectance from all spectral bands to windthrow, clearcutting, and burning and their successional pathways of forest regrowth in the Central Amazon. We also assess whether the forest demography model Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM-FATES, accurately represents the changes for windthrow and clearcut. The results show that all spectral bands from Landsat satellite were sensitive to the disturbances but after 3 to 6 years only the Near Infrared (NIR) band had significant changes associated with the successional pathways of forest regrowth for all the disturbances considered. In general, the NIR decreased immediately after disturbance, increased to maximum values with the establishment of pioneers and early-successional tree species, and then decreased slowly and almost linearly to pre-disturbance conditions with the dynamics of forest succession. Statistical methods predict that NIR will return to pre-disturbance values in about 39 years (consistent with observational data of biomass regrowth following windthrows), and 36 and 56 years for clearcut and burning. The NIR captured the observed successional pathways of forest regrowth after clearcut and burning that diverge through time. ELM-FATES predicted higher peaks of initial forest responses (e.g., biomass, stem density) after clearcuts than after windthrows, similar to the changes in NIR. However, ELM-FATES predicted a faster recovery of forest structure and canopy-coverage back to pre-disturbance conditions for windthrows compared to clearcuts. The similarity of ELM-FATES predictions of regrowth patterns after windthrow and clearcut to those of the NIR results suggest that the dynamics of forest regrowth for these disturbances are represented with appropriate fidelity within ELM-FATES and useful as a benchmarking tool.

Robinson I. Negrón-Juárez et al.

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Robinson I. Negrón-Juárez et al.

Robinson I. Negrón-Juárez et al.

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Short summary
The temporal variability of Landsat satellite NIR band captured the dynamics of forest regrowth after disturbances in Central Amazon. This variability was represented by the dynamics of forest regrowth after disturbances was properly represented by the ELM-FATES model (Functionally Assembled Terrestrial Ecosystem Simulator (FATES) in the Energy Exascale Earth System Model (E3SM) Land Model (ELM)).
The temporal variability of Landsat satellite NIR band captured the dynamics of forest regrowth...
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