Long-term decline of the Amazon carbon sink.

Atmospheric carbon dioxide records indicate that the land surface has acted as a strong global carbon sink over recent decades, with a substantial fraction of this sink probably located in the tropics, particularly in the Amazon. Nevertheless, it is unclear how the terrestrial carbon sink will evolve as climate and atmospheric composition continue to change. Here we analyse the historical evolution of the biomass dynamics of the Amazon rainforest over three decades using a distributed network of 321 plots. While this analysis confirms that Amazon forests have acted as a long-term net biomass sink, we find a long-term decreasing trend of carbon accumulation. Rates of net increase in above-ground biomass declined by one-third during the past decade compared to the 1990s. This is a consequence of growth rate increases levelling off recently, while biomass mortality persistently increased throughout, leading to a shortening of carbon residence times. Potential drivers for the mortality increase include greater climate variability, and feedbacks of faster growth on mortality, resulting in shortened tree longevity. The observed decline of the Amazon sink diverges markedly from the recent increase in terrestrial carbon uptake at the global scale, and is contrary to expectations based on models.

Long-term (1990-2019) monitoring of forest cover changes in the humid tropics.

Accurate characterization of tropical moist forest changes is needed to support conservation policies and to quantify their contribution to global carbon fluxes more effectively. We document, at pantropical scale, the extent and changes (degradation, deforestation, and recovery) of these forests over the past three decades. We estimate that 17% of tropical moist forests have disappeared since 1990 with a remaining area of 1071 million hectares in 2019, from which 10% are degraded. Our study underlines the importance of the degradation process in these ecosystems, in particular, as a precursor of deforestation, and in the recent increase in tropical moist forest disturbances (natural and anthropogenic degradation or deforestation). Without a reduction of the present disturbance rates, undisturbed forests will disappear entirely in large tropical humid regions by 2050. Our study suggests that reinforcing actions are needed to prevent the initial degradation that leads to forest clearance in 45% of the cases.

Shifts in plant respiration and carbon use efficiency at a large-scale drought experiment in the eastern Amazon.

*The effects of drought on the Amazon rainforest are potentially large but remain poorly understood. Here, carbon (C) cycling after 5 yr of a large-scale through-fall exclusion (TFE) experiment excluding about 50% of incident rainfall from an eastern Amazon rainforest was compared with a nearby control plot. *Principal C stocks and fluxes were intensively measured in 2005. Additional minor components were either quantified in later site measurements or derived from the available literature. *Total ecosystem respiration (R(eco)) and total plant C expenditure (PCE, the sum of net primary productivity (NPP) and autotrophic respiration (R(auto))), were elevated on the TFE plot relative to the control. The increase in PCE and R(eco) was mainly caused by a rise in R(auto) from foliage and roots. Heterotrophic respiration did not differ substantially between plots. NPP was 2.4 +/- 1.4 t C ha(-1) yr(-1) lower on the TFE than the control. Ecosystem carbon use efficiency, the proportion of PCE invested in NPP, was lower in the TFE plot (0.24 +/- 0.04) than in the control (0.32 +/- 0.04). *Drought caused by the TFE treatment appeared to drive fundamental shifts in ecosystem C cycling with potentially important consequences for long-term forest C storage.

A method for extracting plant roots from soil which facilitates rapid sample processing without compromising measurement accuracy.

This study evaluates a novel method for extracting roots from soil samples and applies it to estimate standing crop root mass (+/- confidence intervals) in an eastern Amazon rainforest. Roots were manually extracted from soil cores over a period of 40 min, which was split into 10 min time intervals. The pattern of cumulative extraction over time was used to predict root extraction beyond 40 min. A maximum-likelihood approach was used to calculate confidence intervals. The temporal prediction method added 21-32% to initial estimates of standing crop root mass. According to predictions, complete manual root extraction from 18 samples would have taken c. 239 h, compared with 12 h using the prediction method. Uncertainties (percentage difference between mean, and 10th and 90th percentiles) introduced by the prediction method were small (12-15%), compared with uncertainties caused by spatial variation in root mass (72-191%, for nine samples per plot surveyed). This method provides a way of increasing the number of root samples processed per unit time, without compromising measurement accuracy.