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. 2021 Apr 9;12(1):2138.
doi: 10.1038/s41467-021-22459-8.

Mature Andean forests as globally important carbon sinks and future carbon refuges

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Mature Andean forests as globally important carbon sinks and future carbon refuges

Alvaro Duque et al. Nat Commun. .

Erratum in

  • Author Correction: Mature Andean forests as globally important carbon sinks and future carbon refuges.
    Duque A, Peña MA, Cuesta F, González-Caro S, Kennedy P, Phillips OL, Calderón-Loor M, Blundo C, Carilla J, Cayola L, Farfán-Ríos W, Fuentes A, Grau R, Homeier J, Loza-Rivera MI, Malhi Y, Malizia A, Malizia L, Martínez-Villa JA, Myers JA, Osinaga-Acosta O, Peralvo M, Pinto E, Saatchi S, Silman M, Tello JS, Terán-Valdez A, Feeley KJ. Duque A, et al. Nat Commun. 2021 Jun 8;12(1):3617. doi: 10.1038/s41467-021-23955-7. Nat Commun. 2021. PMID: 34108485 Free PMC article. No abstract available.

Abstract

It is largely unknown how South America's Andean forests affect the global carbon cycle, and thus regulate climate change. Here, we measure aboveground carbon dynamics over the past two decades in 119 monitoring plots spanning a range of >3000 m elevation across the subtropical and tropical Andes. Our results show that Andean forests act as strong sinks for aboveground carbon (0.67 ± 0.08 Mg C ha-1 y-1) and have a high potential to serve as future carbon refuges. Aboveground carbon dynamics of Andean forests are driven by abiotic and biotic factors, such as climate and size-dependent mortality of trees. The increasing aboveground carbon stocks offset the estimated C emissions due to deforestation between 2003 and 2014, resulting in a net total uptake of 0.027 Pg C y-1. Reducing deforestation will increase Andean aboveground carbon stocks, facilitate upward species migrations, and allow for recovery of biomass losses due to climate change.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Forest plots distribution in the Andean region.
Distribution of the 119 forest-monitoring plots along latitudinal and elevational gradients in the subtropical and tropical Andes. The black points represent plots in which the aboveground carbon net change (AGC net change) was negative (<0 Mg ha−1 y−1). Blue points: 0 ≤ AGC net change ≤3 Mg ha−1 y−1. Red points: AGC net change >3 Mg ha−1 y−1.
Fig. 2
Fig. 2. Aboveground carbon dynamics along elevational and latitudinal gradients.
Generalized additive models (GAMs) assessing the changes of the aboveground carbon (AGC) dynamics in relation to latitude (°) (a, c, e) and elevation (m asl) (b, d, f), across 119 forest-monitoring plots in the subtropical and tropical Andes. Negative latitudinal values represent plots in the Southern hemisphere and positive latitudinal values represent plots in the Northern hemisphere. Solid lines represent the models that were statistically significant and da shed lines represent 95% confidence intervals. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001. AGC net change = aboveground carbon net change (Mg C ha−1 y−1). AGC productivity = aboveground carbon productivity (Mg C ha−1 y−1). AGC mortality = aboveground carbon mortality (Mg C ha−1 y−1). R2 = Coefficient of determination of the model.
Fig. 3
Fig. 3. Drivers of aboveground carbon dynamics in the Andes.
Structural equation models (SEMs) used to evaluate the effects of climate (PCAtemp1 and PCAtemp2), initial aboveground carbon stock in each plot (AGC1; Mg C ha−1), thermophilization rate (TR; °C y−1), symbiotic root associations (SRA = ln(AM/EcM)), the standardized effect size of the phylogenetic diversity (PDz), and the size-dependent probability of mortality (β) on aboveground carbon dynamics. AGCchange = aboveground carbon net change (Mg C ha−1 y−1) (a). AGCproductivity = aboveground carbon productivity (Mg C ha−1 y−1) (b). AGCmortality = aboveground carbon mortality (Mg C ha−1 y−1) (c). Red arrows indicate negative relationships and black arrows indicate positive relationships. Grey arrows represent significant (P ≤ 0.05) relationships in the IT models (Supplementary Table 7), but not in the SEM models. The values over the arrows are the associated linear coefficients of the explanatory variables found to be significant. R2 = Coefficient of determination of the overall model.

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