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 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.
Highlights
The Amazon rainforest is disproportionately important for global carbon storage and biodiversity
The functional relationships that we found in empirical data share three main features: an initial steady increase of ET, gross primary productivity (GPP), aboveground biomass (AGB) and tree cover with increasing P, a breakpoint at ~2000 mm annual P, after which the indicators do not increase with P, and a significant deviation from the steady increase trend between 1200 and 2000 mm annual P, showing a large and abrupt change in ET, GPP, AGB and tree cover at the forest–savanna transition
The underlying ecohydrological explanation for the relationship to P that is shared between vegetation structure and water, and carbon fluxes offers insights into the future resilience of Amazonia and, more broadly, of tropical forests, and what factors may cause the moist forest to shift to a lower biomass state
Summary
The Amazon rainforest is disproportionately important for global carbon storage and biodiversity. Global ESMs designed to account for feedbacks between vegetation and the atmosphere generally perform relatively poorly in the tropics when evaluated against carbon-cycle observation[11, 12]. This uncertainty originates from several issues, mainly terrestrial ecosystem sub-models, biases in climate generated internally in the ESMs, or both. We find that most differences among models are related to their internally simulated climate, P Using this information, we designed an analysis to account for climate biases by transforming the spatial information from the ESMs to P-based relationships that represent the hydrologic and ecosystem dependency on P. The underlying ecohydrological explanation for the relationship to P that is shared between vegetation structure and water, and carbon fluxes offers insights into the future resilience of Amazonia and, more broadly, of tropical forests, and what factors may cause the moist forest to shift to a lower biomass state
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