Published February 2, 2020 | Version v1
Dataset Open

Supporting Dataset for "Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests"

Creators

  • 1. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
  • 2. International Institute of Tropical Forestry, USDA Forest Service, Rio Piedras, Puerto Rico
  • 3. Embrapa Informática Agropecuária
  • 4. NASA Goddard Space Flight Center, Greenbelt, MD, United States
  • 5. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, United States
  • 6. AMAP, Univ Montpellier, IRD, CIRAD, CNRS, INRAE, Montpellier, 34000 France
  • 7. Université de Lorraine, INRAE, AgroParisTech, UMR Silva, F-54000 Nancy, France
  • 8. Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), UMR EcoFoG (AgroParisTech, CNRS, INRAE, Université des Antilles, Université de Guyane), Campus Agronomique, Kourou 97379, France
  • 9. Department of Earth System Science, University of California, Irvine, CA, United States
  • 10. Institut National de Recherche en Agriculture, Alimentation et Environnement (INRAE), UMR 0745 EcoFoG, Campus Agronomique, Kourou 97379, France
  • 11. University of Arizona, Tucson, AZ, United States
  • 12. Max-Planck-Institut für Biochemie

Description

This data set is a supplement for:

Longo, M., S. S. Saatchi, M. Keller, K. W. Bowman, A. Ferraz, P. R. Moorcroft, D. Morton, D. Bonal, P. Brando, B. Burban, G. Derroire, M. N. dos-Santos, V. Meyer, S. R. Saleska, S. Trumbore, and G. Vin- cent, 2020: Impacts of degradation on water, energy, and carbon cycling of the Amazon tropical forests. J. Geophys. Res.-Biogeosci., 125 (8), e2020JG005 677, doi:10.1029/2020JG005677.

This data set contains the following files (which should be all downloaded and uncompressed in the same root directory):

  • 00_SiteLidar.zip – R scripts to process forest inventory plots and Airborne LiDAR point clouds.  Sub-directories contains a directory Template, which should be copied for each site for which data are to be processed.
  • 01_LidarSynthesis.zip – R scripts to fit the statistical models of aggregated properties, and to evaluate both the statistical model and the prediction of Airborne LiDAR profiles to be used to initialize ED-2.2.
  • 02_model_eval.zip – R scripts to compare the ED-2.2 model output and evaluate the model against tower observations.
  • 03_degrad_mtr – R scripts to visualize the ED-2.2 simulation results.
  • InputData – Miscellaneous data to be used by the scripts.
  • Util – Additional R scripts
    • Rsc – Mostly R functions, which may be called by other R scripts
    • OutsideLAS – List of plots that were not fully overlapped by the Airborne LiDAR surveys
    • GenMERRA2_ED2 – Utility scripts to process MERRA-2 to generate the met drivers needed by ED-2.2
    • GenMSWEP2_ED2 – Utility scripts to process MSWEP-2.2 to generate the met drivers needed by ED-2.2 
  • ED2IN_Config – list of ED2IN files used in the runs.

 

To see the input data used for this analysis, load any of the objects available in 01_LidarSynthesis/01_eval_multivar, and look for the following structures:

List of variables and units of data structure census[[1]], rlidar[[1]], and tchdat[[1]].
Variable Structure Description Units
identifier census[[1]], rlidar[[1]], tchdat[[1]] Plot identifier. This always has the site identifier (see below), the area within each site, the nominal year of the campaign, the unique sub-plot ID (Pxx_Byy for rectangular plots, and Txx_Pyy for long transects)   
iata

census[[1]], rlidar[[1]], tchdat[[1]]

Site identifier:

  • 115: Km 115 of BR-163 highway, PA, BRA
  • ana: Anambé, PA, BRA
  • and: Fazenda Andiroba, PA, BRA
  • bon: Fazenda Bonal, AC, BRA
  • cau: Fazenda Cauaxi, PA, BRA
  • duc: Reserva Ducke, AM, BRA
  • fc2: Feliz Natal (zone C, area 2), MT, BRA
  • fd1: Feliz Natal (zone D, area 1), MT, BRA
  • fd2: Feliz Natal (zone D, area 2), MT, BRA
  • fd3: Feliz Natal (zone D, area 3), MT, BRA
  • fn2: Feliz Natal (long transect 2), MT, BRA
  • fna: Feliz Natal (zone A), MT, BRA
  • fst: Saracá-Taquera National Forest, PA, BRA
  • gf1: Paracou (Guyaflux plots), GUF
  • gf2: Paracou (Logging experiment plots), GUF
  • hum: Fazenda Humaitá, AC, BRA
  • jm2: Jamari National Forest (area 2), RO, BRA
  • jm3: Jamari National Forest (area 3), RO, BRA
  • par: Fazenda Nova Neonita, PA, BRA
  • sbe: 
  
local census[[1]], rlidar[[1]], tchdat[[1]]

Region identifier (used for regional cross-validation):

  • bte: Belterra, PA, BRA
  • duc: Manaus (Reserva Ducke), AM, BRA
  • fst: Saracá-Taquera National Forest, PA, BRA
  • fzn: Feliz Natal, MT, BRA
  • gyf: Paracou, GUF
  • jam: Jamari National Forest, RO, BRA
  • prg: Paragominas, PA, BRA
  • rib: Rio Branco, AC, BRA
  • sfx: São Félix do Xingu, PA, BRA
  • tan: Tanguro, MT, BRA
  • sbe: Southeastern Belterra, PA, BRA
  • sx1: São Félix do Xingu (area 1), PA, BRA
  • sx2: São Félix do Xingu (area 2), PA, BRA
  • tac: Tomé-Açu, PA, BRA
  • tal: Fazenda Talismã, AC, BRA
  • tn1: Fazenda Tanguro (Sustainable Landscapes transects), MT, BRA
  • tn2: Fazenda Tanguro (fire experiment transects), MT, BRA
  • tp1: Tapajós National Forest, PA, BRA
  • tp2: São Jorge (area 2), PA, BRA
  • tp3: São Jorge (area 3), PA, BRA
  
poi census[[1]], rlidar[[1]], tchdat[[1]] Nominal size of each plot  
when census[[1]], rlidar[[1]], tchdat[[1]] Date of measurement  
col census[[1]], rlidar[[1]], tchdat[[1]] Colour associated with plot (for plotting only)  
pch census[[1]], rlidar[[1]], tchdat[[1]] Symbol associated with plot (for plotting only)  
dist.key census[[1]], rlidar[[1]], tchdat[[1]]

Disturbance flag:

  • bnm: Burnt multiple times
  • bno: Burnt once
  • cvl: Conventional logging
  • int: Intact (minimally disturbed) forest
  • lbn: Logged and burnt once
  • lth: Logged and thinned
  • ril: Reduced-impact logging
  • sbn: Secondary growth then burnt
  • sec: Secondary growth
  • ukn: Unknown/Unclassified
  
dist.age census[[1]], rlidar[[1]], tchdat[[1]] Age since last disturbance yr
dist.col census[[1]], rlidar[[1]], tchdat[[1]] Colour associated with disturbance (for plotting only)  
dist.pch census[[1]], rlidar[[1]], tchdat[[1]] Symbol associated with disturbance (for plotting only)  
agb.std census[[1]] Above-ground biomass of individuals with DBH ≥ 10 cm kgC m−2
ba.std census[[1]] Basal area of individuals with DBH ≥ 10 cm cm2 m−2
lai.std census[[1]] Potential (allometry-based) leaf area index of individuals with DBH ≥ 10 cm m2 m−2
nplant.std census[[1]] Stem number density of individuals with DBH ≥ 10 cm m−2
elev.mean rlidar[[1]] Mean elevation of point cloud return distribution (all returns) m
elev.sdev rlidar[[1]] Standard deviation of point cloud return distribution (all returns) m
elev.skew rlidar[[1]] Skewness of point cloud return distribution (all returns) m
elev.kurt rlidar[[1]] Kurtosis of point cloud return distribution (all returns) m
elev.p01 rlidar[[1]] 1st percentile of the point cloud return distribution (all returns) m
elev.p05 rlidar[[1]] 5th percentile of the point cloud return distribution (all returns) m
elev.p10 rlidar[[1]] 10th percentile of the point cloud return distribution (all returns) m
elev.p25 rlidar[[1]] 25th percentile of the point cloud return distribution (all returns) m
elev.p50 rlidar[[1]] 50th percentile (median) of the point cloud return distribution (all returns) m
elev.p75 rlidar[[1]] 75th percentile of the point cloud return distribution (all returns) m
elev.p90 rlidar[[1]] 90th percentile of the point cloud return distribution (all returns) m
elev.p95 rlidar[[1]] 95th percentile of the point cloud return distribution (all returns) m
elev.p99 rlidar[[1]] 99th percentile of the point cloud return distribution (all returns) m
elev.iqr rlidar[[1]] Interquartile range of the point cloud return distribution (all returns) m
elev.max rlidar[[1]] Maximum of the point cloud return distribution (all returns) m
fcan.elev.1.0.to.2.5.m rlidar[[1]] Fraction of returns between 1.0 and 2.5 m fraction [0-1]
fcan.elev.2.5.to.5.0.m rlidar[[1]] Fraction of returns between 2.5 and 5.0 m fraction [0-1]
fcan.elev.5.0.to.7.5.m rlidar[[1]] Fraction of returns between 5.0 and 7.5 m fraction [0-1]
fcan.elev.7.5.to.10.0.m rlidar[[1]] Fraction of returns between 7.5 and 10.0 m fraction [0-1]
fcan.elev.10.0.to.15.0.m rlidar[[1]] Fraction of returns between 10.0 and 15.0 m  fraction [0-1]
fcan.elev.15.0.to.20.0.m rlidar[[1]] Fraction of returns between 15.0 and 20.0 m fraction [0-1]
fcan.elev.20.0.to.25.0.m rlidar[[1]] Fraction of returns between 20.0 and 25.0 m fraction [0-1]
fcan.elev.25.0.to.30.0.m rlidar[[1]] Fraction of returns between 25.0 and 30.0 m fraction [0-1]
fcan.elev.above.1.0.m rlidar[[1]] Fraction of returns above 1.0 m fraction [0-1]
fcan.elev.above.2.5.m rlidar[[1]] Fraction of returns above 2.5 m fraction [0-1]
fcan.elev.above.5.0.m rlidar[[1]] Fraction of returns above 5.0 m fraction [0-1]
fcan.elev.above.7.5.m rlidar[[1]] Fraction of returns above 7.5 m fraction [0-1]
fcan.elev.above.10.0.m rlidar[[1]] Fraction of returns above 10.0 m fraction [0-1]
fcan.elev.above.15.0.m rlidar[[1]] Fraction of returns above 15.0 m fraction [0-1]
fcan.elev.above.20.0.m rlidar[[1]] Fraction of returns above 20.0 m fraction [0-1]
fcan.elev.above.25.0.m rlidar[[1]] Fraction of returns above 25.0 m fraction [0-1]
fcan.elev.above.30.0.m rlidar[[1]] Fraction of returns above 30.0 m fraction [0-1]
ztch tchdat[[1]] Mean top canopy height (0.25ha average from 1-m pixels) m

 

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00_SiteLidar.zip

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