Mature Andean forests as globally important carbon sinks and future carbon refuges.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
09 04 2021
09 04 2021
Historique:
received:
04
09
2020
accepted:
17
03
2021
entrez:
10
4
2021
pubmed:
11
4
2021
medline:
4
5
2021
Statut:
epublish
Résumé
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
Identifiants
pubmed: 33837222
doi: 10.1038/s41467-021-22459-8
pii: 10.1038/s41467-021-22459-8
pmc: PMC8035207
doi:
Substances chimiques
Carbon
7440-44-0
Banques de données
Dryad
['10.5061/dryad.59zw3r26f']
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
2138Commentaires et corrections
Type : ErratumIn
Références
Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).
pubmed: 21764754
doi: 10.1126/science.1201609
Requena Suarez, D. et al. Estimating aboveground net biomass change for tropical and subtropical forests: Refinement of IPCC default rates using forest plot data. Glob. Chang. Biol. 25, 3609–3624 (2019).
pubmed: 31310673
pmcid: 6852081
doi: 10.1111/gcb.14767
Brienen, R. J. W. et al. Long-term decline of the Amazon carbon sink. Nature 519, 344–348 (2015).
pubmed: 25788097
doi: 10.1038/nature14283
Hubau, W. et al. Asynchronous carbon sink saturation in African and Amazonian tropical forests. Nature 579, 80–87 (2020).
pubmed: 32132693
doi: 10.1038/s41586-020-2035-0
Immerzeel, W. W. et al. Importance and vulnerability of the world’s wáter towers. Nature 577, 364–369 (2020).
pubmed: 31816624
doi: 10.1038/s41586-019-1822-y
Myers, N., Mittermeier, R. A., Mittermeier, C. G., Fonseca, G. A. B. & Kent, J. Biodiversity hotspots for conservation priorities. Nature 403, 853–859 (2000).
pubmed: 10706275
doi: 10.1038/35002501
Orme, C. D. L. et al. Global hotspots of species richness are not congruent with endemism or threat. Nature 436, 1016–1019 (2005).
pubmed: 16107848
doi: 10.1038/nature03850
Girardin, C. A. J. et al. Net primary productivity allocation and cycling of carbon along a tropical forest elevational transect in the Peruvian Andes. Glob. Chang. Biol. 16, 3176–3192 (2010).
doi: 10.1111/j.1365-2486.2010.02235.x
Malhi, Y. et al. The variation of productivity and its allocation along a tropical elevation gradient: a whole carbon budget perspective. N. Phytol. 214, 1019–1032 (2017).
doi: 10.1111/nph.14189
Peña, M. A., Feeley, K. J. & Duque, A. Effects of endogenous and exogenous processes on aboveground biomass stocks and dynamics in Andean forests. Plant Ecol. 219, 1481–1492 (2018).
doi: 10.1007/s11258-018-0895-2
Aide, T. M. et al. Woody vegetation dynamics in the tropical and subtropical Andes from 2001 to 2014: Satellite image interpretation and expert validation. Glob. Chang. Biol. 25, 2112–2126 (2019).
pubmed: 30854741
pmcid: 6849738
doi: 10.1111/gcb.14618
Asner, G. P. et al. Landscape-scale changes in forest structure and functional traits along an Andes-to-Amazon elevation gradient. Biogeosci. Discuss. 10, 15415–15454 (2013).
Fadrique, B. et al. Widespread but heterogeneous responses of Andean forests to climate change. Nature 564, 207–212 (2018).
pubmed: 30429613
doi: 10.1038/s41586-018-0715-9
Duque, A., Stevenson, P. R. & Feeley, K. J. Thermophilization of adult and juvenile tree communities in the northern tropical Andes. Proc. Natl Acad. Sci. USA 112, 10744–10749 (2015).
pubmed: 26261350
pmcid: 4553780
doi: 10.1073/pnas.1506570112
Mcdowell, N. G. et al. Pervasive shifts in forest dynamics in a changing world. Science 368, 964 (2020).
doi: 10.1126/science.aaz9463
Jo, I., Fei, S., Oswalt, C. M., Domke, G. M. & Phillips, R. P. Shifts in dominant tree mycorrhizal associations in response to anthropogenic impacts. Sci. Adv. 5, aav6358 (2019).
doi: 10.1126/sciadv.aav6358
Van Der Heijden, M. G. A. & Bardgett, R. D. & Van Straalen, N. M. The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecol. Lett. 11, 296–310 (2008).
pubmed: 18047587
doi: 10.1111/j.1461-0248.2007.01139.x
Steidinger, B. S. et al. Climatic controls of decomposition drive the global biogeography of forest-tree symbioses. Nature 569, 404–408 (2019).
pubmed: 31092941
doi: 10.1038/s41586-019-1128-0
Soudzilovskaia, N. A. et al. Global mycorrhizal plant distribution linked to terrestrial carbon stocks. Nat. Commun. 10, 1–10 (2019).
doi: 10.1038/s41467-019-13019-2
Coelho de Souza, F. et al. Evolutionary diversity is associated with Wood productivity in Amazonian forests. Nat. Ecol. Evol. 3, 1754–1761 (2019).
pubmed: 31712699
doi: 10.1038/s41559-019-1007-y
González−Caro, S. et al. The legacy of biogeographic history on the composition and ecosystem function of Andean mountain forests. Ecology 101, e03131 (2020).
pubmed: 32629538
Tilman, D., Lehman, C. L. & Thomson, K. T. Plant diversity and ecosystem productivity: theoretical considerations. Proc. Natl Acad. Sci. USA 94, 1857–1861 (1997).
pubmed: 11038606
pmcid: 20007
doi: 10.1073/pnas.94.5.1857
Loreau, M. Biodiversity and ecosystem functioning: recent theoretical advances. Oikos 91, 3–17 (2000).
doi: 10.1034/j.1600-0706.2000.910101.x
Wiens, J. J. & Donoghue, M. J. Historical biogeography, ecology and species richness. Trends Ecol. Evol. 19, 639–644 (2004).
pubmed: 16701326
doi: 10.1016/j.tree.2004.09.011
Malizia, A. et al. Elevation and latitude drives structure and tree species composition in Andean forests: results from a large-scale plot network. PLoS ONE 15, e0231553 (2020).
pubmed: 32311701
pmcid: 7170706
doi: 10.1371/journal.pone.0231553
Grace, J. B. Structural Equation Modeling and Natural Systems (Cambridge University Press, 2006).
Burnham, K. P., Anderson, D. R. & Huyvaert, K. P. AIC model selection and multimodel inference in behavioral ecology: Some background, observations, and comparisons. Behav. Ecol. Sociobiol. 65, 23–35 (2011).
doi: 10.1007/s00265-010-1029-6
Karger, D. N. et al. Climatologies at high resolution for the earth’s land surface areas. Sci. Data https://doi.org/10.1038/sdata.2017.122 (2017).
Coomes, D. A. & Allen, R. B. Mortality and tree-size distributions in natural mixed-age forests. J. Ecol. 95, 27–40 (2007).
doi: 10.1111/j.1365-2745.2006.01179.x
Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).
pubmed: 24233722
doi: 10.1126/science.1244693
Gorelick, N. et al. Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27 (2017).
doi: 10.1016/j.rse.2017.06.031
Qie, L. et al. Long-term carbon sink in Borneo’s forests halted by drought and vulnerable to edge effects. Nat. Commun. 8, 1966 (2017).
pubmed: 29259276
pmcid: 5736600
doi: 10.1038/s41467-017-01997-0
Pillet, M. et al. Disentangling competitive vs. climatic drivers of tropical forest mortality. J. Ecol. 106, 1165–1179 (2018).
doi: 10.1111/1365-2745.12876
Walker, A. P. et al. Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO2. N. Phytol. 229, 2413–2445 (2021).
doi: 10.1111/nph.16866
McMahon, S. M., Arellano, G. & Davies, S. J. The importance and challenges of detecting changes in forest mortality rates. Ecosphere 10, e02615 (2019).
doi: 10.1002/ecs2.2615
Feeley, K. et al. The thermal tolerances, distributions, and performances of tropical Montane Tree species. Front. Forest Glob. Chang. 3, 1–11 (2020).
Dueñas, J. F. et al. Moderate phosphorus additions consistently affect community composition of arbuscular mycorrhizal fungi in tropical montane forests in southern Ecuador. N. Phytol. 227, 1505–1518 (2020).
doi: 10.1111/nph.16641
Terrer, C., Vicca, S., Hungate, B. A., Phillips, R. P. & Prentice, I. C. Mycorrhizal association as a primary control of the CO2 fertilization effect. Science 353, 72–74 (2016).
pubmed: 27365447
doi: 10.1126/science.aaf4610
Peña, M. A. & Duque, A. Patterns of stocks of aboveground tree biomass, dynamics,and their determinants in secondary Andean forests. Forest Ecol. Manag. 302, 54–61 (2013).
doi: 10.1016/j.foreco.2013.03.025
Strassburg, B. B. N. et al. Global priority areas for ecosystem restoration. Nature 586, 724–729 (2020).
pubmed: 33057198
doi: 10.1038/s41586-020-2784-9
Tyukavina, A., Hansen, M. C., Potapov, P. V., Krylov, A. M. & Goetz, S. J. Pan-tropical hinterland forests: mapping minimally disturbed forests. Glob. Ecol. Biogeogr. 25, 1–13 (2015).
Condit, R. et al. Tropical forest dynamics across a rainfall gradient and the impact of an El Niño dry season. J. Trop. Ecol. 20, 51–72 (2004).
doi: 10.1017/S0266467403001081
Chave, J. et al. Improved allometric models to estimate the aboveground biomass of tropical trees. Glob. Chang. Biol. 20, 3177–3190 (2014).
pubmed: 24817483
doi: 10.1111/gcb.12629
Chave, J. et al. Towards a worldwide wood economics spectrum. Ecol. Lett. 12, 351–366 (2009).
pubmed: 19243406
doi: 10.1111/j.1461-0248.2009.01285.x
Martin, A. R., Doraisami, M. & Thomas, S. C. Global patterns in wood carbón concentration across the world’s trees and forests. Nat. Geosci. 11, 915–920 (2018).
doi: 10.1038/s41561-018-0246-x
Feldpausch, T. R. et al. Tree height integrated into pantropical forest biomass estimates. Biogeosciences 9, 3381–3403 (2012).
doi: 10.5194/bg-9-3381-2012
Réjou-Méchain, M., Tanguy, A., Piponiot, C., Chave, J. & Hérault, B. biomass: an r package for estimating above-ground biomass and its uncertainty in tropical forests. Methods Ecol. Evol. 8, 1163–1167 (2017).
doi: 10.1111/2041-210X.12753
Phillips, J., Ramirez, S., Wayson, C. & Duque, A. Differences in carbon stocks along an elevational gradient in tropical mountain forests of Colombia. Biotropica 51, 490–499 (2019).
doi: 10.1111/btp.12675
Talbot, J. et al. Methods to estimate aboveground wood productivity from long-term forest inventory plots. Forest Ecol. Manag. 320, 30–38 (2014).
doi: 10.1016/j.foreco.2014.02.021
Feeley, K. J. et al. Upslope migration of Andean trees. J. Biogeogr. 38, 783–791 (2011).
doi: 10.1111/j.1365-2699.2010.02444.x
Boyle, B. et al. The taxonomic name resolution service: an online tool for automated standardization of plant names. BMC Bioinformatics 14, 16 (2013).
pubmed: 23324024
pmcid: 3554605
doi: 10.1186/1471-2105-14-16
Gotelli, N. J. & Colwell, R. K. Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecol. Lett. 4, 379–391 (2001).
doi: 10.1046/j.1461-0248.2001.00230.x
Faith, D. P. Conservation evaluation and phylogenetic diversity. Biol. Conserv. 61, 1–10 (1992).
doi: 10.1016/0006-3207(92)91201-3
Webb, C. O. & Donoghue, M. J. Phylomatic: Tree assembly for applied phylogenetics. Mol. Ecol. Notes 5, 181–183 (2005).
doi: 10.1111/j.1471-8286.2004.00829.x
Gotelli, N. J. & McCabe, D. J. Species co-occurrence: a meta-analysis of J. M. Diamond’s assembly rules model. Ecology 83, 2091–2096 (2002).
doi: 10.1890/0012-9658(2002)083[2091:SCOAMA]2.0.CO;2
Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).
pubmed: 20395285
doi: 10.1093/bioinformatics/btq166
Ramírez, S. et al. The influence of historical dispersal on the phylogenetic structure of tree communities in the tropical Andes. Biotropica 51, 500–508 (2019).
doi: 10.1111/btp.12661
Segovia, R. A. et al. Freezing and water availability structure the evolutionary diversity of trees across the Americas. Sci. Adv. 6, eaaz5373 (2020).
Maherali, H. & Klironomos, J. N. Influence of phylogeny on fungal community assembly and ecosystem functioning. Science 316, 1746–1748 (2007).
pubmed: 17588930
doi: 10.1126/science.1143082
Phillips, R. P., Brzostek, E. & Midgley, M. G. The mycorrhizal-associated nutrient economy: a new framework for predicting carbon-nutrient couplings in temperate forests. N. Phytol. 199, 41–51 (2013).
doi: 10.1111/nph.12221
Averill, C., Turner, B. L. & Finzi, A. C. Mycorrhiza-mediated competition between plants and decomposers drives soil carbon storage. Nature 25, 327–343 (2014).
Jarvis, A. & Mulligan, M. The climate of cloud forests. Hydrol. Process. 25, 327–343 (2011).
doi: 10.1002/hyp.7847
Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).
doi: 10.1002/joc.5086
Olson, D. M. et al. Terrestrial Ecoregions of the World: A New Map of Life on Earth: A new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. Bioscience 51, 933–938 (2001).
doi: 10.1641/0006-3568(2001)051[0933:TEOTWA]2.0.CO;2
Burnham, K. P. & Anderson, D. R. Model selection and multimodel inference: a practical Information-Theoretic approach (Springer, 2002).
Galipaud, M., Gillingham, M. A. F. & Dechaume-Moncharmont, F. X. A farewell to the sum of Akaike weights: the benefits of alternative metrics for variable importance estimations in model selection. Methods Ecol. Evol. 8, 1668–1678 (2017).
doi: 10.1111/2041-210X.12835
Symonds, M. R. E. & Moussalli, A. A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike’s information criterion. Behav. Ecol. Sociobiol. 65, 13–21 (2011).
doi: 10.1007/s00265-010-1037-6
Cade, B. S. Model averaging and muddled multimodel inferences. Ecology 96, 2370–2382 (2015).
pubmed: 26594695
doi: 10.1890/14-1639.1