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Hydrologic resilience and Amazon productivity

Ahlström, Anders LU ; Canadell, Josep G.; Schurgers, Guy LU ; Wu, Minchao LU ; Berry, Joseph A.; Guan, Kaiyu and Jackson, Robert B. (2017) In Nature Communications 8(1).
Abstract

The Amazon rainforest is disproportionately important for global carbon storage and biodiversity. The system couples the atmosphere and land, with moist forest that depends on convection to sustain gross primary productivity and growth. Earth system models that estimate future climate and vegetation show little agreement in Amazon simulations. Here we show that biases in internally generated climate, primarily precipitation, explain most of the uncertainty in Earth system model results; models, empirical data and theory converge when precipitation biases are accounted for. Gross primary productivity, above-ground biomass and tree cover align on a hydrological relationship with a breakpoint at ~2000 mm annual precipitation, where the... (More)

The Amazon rainforest is disproportionately important for global carbon storage and biodiversity. The system couples the atmosphere and land, with moist forest that depends on convection to sustain gross primary productivity and growth. Earth system models that estimate future climate and vegetation show little agreement in Amazon simulations. Here we show that biases in internally generated climate, primarily precipitation, explain most of the uncertainty in Earth system model results; models, empirical data and theory converge when precipitation biases are accounted for. Gross primary productivity, above-ground biomass and tree cover align on a hydrological relationship with a breakpoint at ~2000 mm annual precipitation, where the system transitions between water and radiation limitation of evapotranspiration. The breakpoint appears to be fairly stable in the future, suggesting resilience of the Amazon to climate change. Changes in precipitation and land use are therefore more likely to govern biomass and vegetation structure in Amazonia.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Nature Communications
volume
8
issue
1
publisher
Nature Publishing Group
external identifiers
  • scopus:85028544041
  • wos:000408695100004
ISSN
2041-1723
DOI
10.1038/s41467-017-00306-z
language
English
LU publication?
yes
id
0116c3a6-894d-412c-916f-4bd8ce3b00bb
date added to LUP
2017-09-26 08:27:35
date last changed
2018-01-16 13:26:28
@article{0116c3a6-894d-412c-916f-4bd8ce3b00bb,
  abstract     = {<p>The Amazon rainforest is disproportionately important for global carbon storage and biodiversity. The system couples the atmosphere and land, with moist forest that depends on convection to sustain gross primary productivity and growth. Earth system models that estimate future climate and vegetation show little agreement in Amazon simulations. Here we show that biases in internally generated climate, primarily precipitation, explain most of the uncertainty in Earth system model results; models, empirical data and theory converge when precipitation biases are accounted for. Gross primary productivity, above-ground biomass and tree cover align on a hydrological relationship with a breakpoint at ~2000 mm annual precipitation, where the system transitions between water and radiation limitation of evapotranspiration. The breakpoint appears to be fairly stable in the future, suggesting resilience of the Amazon to climate change. Changes in precipitation and land use are therefore more likely to govern biomass and vegetation structure in Amazonia.</p>},
  articleno    = {387},
  author       = {Ahlström, Anders and Canadell, Josep G. and Schurgers, Guy and Wu, Minchao and Berry, Joseph A. and Guan, Kaiyu and Jackson, Robert B.},
  issn         = {2041-1723},
  language     = {eng},
  month        = {12},
  number       = {1},
  publisher    = {Nature Publishing Group},
  series       = {Nature Communications},
  title        = {Hydrologic resilience and Amazon productivity},
  url          = {http://dx.doi.org/10.1038/s41467-017-00306-z},
  volume       = {8},
  year         = {2017},
}