Research ArticleAPPLIED ECOLOGY

Persistent collapse of biomass in Amazonian forest edges following deforestation leads to unaccounted carbon losses

See allHide authors and affiliations

Science Advances  30 Sep 2020:
Vol. 6, no. 40, eaaz8360
DOI: 10.1126/sciadv.aaz8360
  • Fig. 1 LiDAR point cloud profile.

    Point cloud data collected in 2014 in the northeast of the Pará state, Brazil with 420 m of length. The points represent the vegetation height, which was normalized by the terrain altimetry. (A) Structure of a nondegraded old-growth forest, where the trees height reaches up to 40 m. (B) Forest edge (width of 120 m), where the height of the vegetation reaches up to 25 m. (C) Deforested area with vegetation regrowth (height up to 5 m).

  • Fig. 2 Forest edges creation, erosion, and age composition in Amazonia.

    (A) Temporal forest edges variation in Amazonia, where the black bars are the annual forest edges increment rate and the blue line is the total gross forest area increment from 2001. (B) Boxplots of forest edges erosion rates (as a negative percentage) for Amazonia, where the bold horizontal lines are the medians, the blue dots are the averages, the shaded area is the frequency distribution function, and n is the number of observations. (C) Spatial distribution of forest edges age in 2015 in Amazonia; ages were aggregated by the average in a 10 km by 10 km grid cell to improve visualization. (D) Dot plots of forest edge age [each dot corresponds to a single grid cell in (C)] in Amazonian countries in 2015, where the vertical bars are the SDs, the black dots are the averages, the gray dots are the data observations, and n is the number of observations. The letters in bold represent the groups defined by the post hoc test.

  • Fig. 3 Spatial variability of carbon losses in Amazonia.

    Spatial variability of carbon losses between 2001 and 2015 from (A) edge effect and (B) deforestation. Histograms of frequency distribution of carbon losses related to (C) the edge effect presented in (A) and (D) the deforestation presented in (B). (E) Percent contribution of edge effect and deforestation to the total carbon loss of each pixel in Amazonia. Carbon losses were aggregated by the sum in a 10 km by 10 km grid cell to improve visualization in (A) and (B).

  • Fig. 4 Temporal variability of carbon losses in Amazonia.

    (A) Temporal carbon loss variability by fragmentation. (B) Temporal carbon loss variability by deforestation. The bottom panels show the contribution as a percentage of each country to the annual carbon loss by edge effect (C) and deforestation (D).

  • Table 1 Average and median of the forest edges ages for the Amazonian countries.

    CountryForest edges ages (years)
    Average ± SDMedian
    Bolivia7.00 ± 2.357.01
    Brazil7.38 ± 2.847.54
    Colombia7.67 ± 2.887.96
    Ecuador6.58 ± 2.176.84
    France Guyana6.57 ± 3.116.41
    Guyana6.78 ± 2.916.57
    Peru6.48 ± 2.506.56
    Suriname5.94 ± 2.935.49
    Venezuela7.53 ± 2.947.59
  • Table 2 Temporal trend and average carbon losses induced by edge effect and deforestation for all Amazonian countries.

    Where S is the Man-Kendell statistics. The S statistic with an asterisk (*) means a significant temporal trend at 95% of significance level (P ≤ 0.05).

    CountryEdge effectDeforestation
    SSen’s slope
    (Tg C year−1)
    Average ± SD
    (Tg C year−1)
    SSen’s slope
    (Tg C year−1)
    Average ± SD
    (Tg C year−1)
    Bolivia0.370.145 ± 1.41−0.03−0.0210 ± 3.60
    Brazil−0.31−0.5842 ± 7.67−0.61*−8.41139 ± 47.68
    Colombia−0.11−0.034 ± 0.47−0.15−0.028 ± 1.97
    Ecuador0.71*0.061 ± 0.340.51*0.081 ± 0.53
    France Guiana0.350.010 ± 0.060.150.010 ± 0.20
    Guyana0.71*0.041 ± 0.230.41*0.041 ± 0.28
    Peru0.73*0.418 ± 1.970.63*0.6511 ± 4.25
    Suriname0.83*0.071 ± 0.360.75*0.071 ± 0.49
    Venezuela0.45*0.021 ± 0.170.090.012 ± 0.52

Supplementary Materials

  • Supplementary Materials

    Persistent collapse of biomass in Amazonian forest edges following deforestation leads to unaccounted carbon losses

    Celso H. L. Silva Junior, Luiz E. O. C. Aragão, Liana O. Anderson, Marisa G. Fonseca, Yosio E. Shimabukuro, Christelle Vancutsem, Frédéric Achard, René Beuchle, Izaya Numata, Carlos A. Silva, Eduardo E. Maeda, Marcos Longo, Sassan S. Saatchi

    Download Supplement

    This PDF file includes:

    • Figs. S1 to S13
    • Tables S1 to S5
    • References

    Files in this Data Supplement:

Stay Connected to Science Advances

Navigate This Article