Small understorey trees have greater capacity than canopy trees to adjust hydraulic traits following prolonged experimental drought in a tropical forest.

Future climate change predictions for tropical forests highlight increased frequency and intensity of extreme drought events. However, it remains unclear whether large and small trees have differential strategies to tolerate drought due to the different niches they occupy. The future of tropical forests is ultimately dependent on the capacity of small trees (<10 cm in diameter) to adjust their hydraulic system to tolerate drought. To address this question, we evaluated whether the drought tolerance of neotropical small trees can adjust to experimental water stress and was different from tall trees. We measured multiple drought resistance-related hydraulic traits across nine common neotropical genera at the world's longest-running tropical forest throughfall-exclusion experiment and compared their responses with surviving large canopy trees. Small understorey trees in both the control and the throughfall-exclusion treatment had lower minimum stomatal conductance and maximum hydraulic leaf-specific conductivity relative to large trees of the same genera, as well as a greater hydraulic safety margin (HSM), percentage loss of conductivity and embolism resistance, demonstrating that they occupy a distinct hydraulic niche. Surprisingly, in response to the drought treatment, small trees increased specific hydraulic conductivity by 56.3% and leaf:sapwood area ratio by 45.6%. The greater HSM of small understorey trees relative to large canopy trees likely enabled them to adjust other aspects of their hydraulic systems to increase hydraulic conductivity and take advantage of increases in light availability in the understorey resulting from the drought-induced mortality of canopy trees. Our results demonstrate that differences in hydraulic strategies between small understorey and large canopy trees drive hydraulic niche segregation. Small understorey trees can adjust their hydraulic systems in response to changes in water and light availability, indicating that natural regeneration of tropical forests following long-term drought may be possible.

Death from drought in tropical forests is triggered by hydraulics not carbon starvation.

Drought threatens tropical rainforests over seasonal to decadal timescales, but the drivers of tree mortality following drought remain poorly understood. It has been suggested that reduced availability of non-structural carbohydrates (NSC) critically increases mortality risk through insufficient carbon supply to metabolism ('carbon starvation'). However, little is known about how NSC stores are affected by drought, especially over the long term, and whether they are more important than hydraulic processes in determining drought-induced mortality. Using data from the world's longest-running experimental drought study in tropical rainforest (in the Brazilian Amazon), we test whether carbon starvation or deterioration of the water-conducting pathways from soil to leaf trigger tree mortality. Biomass loss from mortality in the experimentally droughted forest increased substantially after >10 years of reduced soil moisture availability. The mortality signal was dominated by the death of large trees, which were at a much greater risk of hydraulic deterioration than smaller trees. However, we find no evidence that the droughted trees suffered carbon starvation, as their NSC concentrations were similar to those of non-droughted trees, and growth rates did not decline in either living or dying trees. Our results indicate that hydraulics, rather than carbon starvation, triggers tree death from drought in tropical rainforest.

Drought impact on forest carbon dynamics and fluxes in Amazonia.

In 2005 and 2010 the Amazon basin experienced two strong droughts, driven by shifts in the tropical hydrological regime possibly associated with global climate change, as predicted by some global models. Tree mortality increased after the 2005 drought, and regional atmospheric inversion modelling showed basin-wide decreases in CO2 uptake in 2010 compared with 2011 (ref. 5). But the response of tropical forest carbon cycling to these droughts is not fully understood and there has been no detailed multi-site investigation in situ. Here we use several years of data from a network of thirteen 1-ha forest plots spread throughout South America, where each component of net primary production (NPP), autotrophic respiration and heterotrophic respiration is measured separately, to develop a better mechanistic understanding of the impact of the 2010 drought on the Amazon forest. We find that total NPP remained constant throughout the drought. However, towards the end of the drought, autotrophic respiration, especially in roots and stems, declined significantly compared with measurements in 2009 made in the absence of drought, with extended decreases in autotrophic respiration in the three driest plots. In the year after the drought, total NPP remained constant but the allocation of carbon shifted towards canopy NPP and away from fine-root NPP. Both leaf-level and plot-level measurements indicate that severe drought suppresses photosynthesis. Scaling these measurements to the entire Amazon basin with rainfall data, we estimate that drought suppressed Amazon-wide photosynthesis in 2010 by 0.38 petagrams of carbon (0.23-0.53 petagrams of carbon). Overall, we find that during this drought, instead of reducing total NPP, trees prioritized growth by reducing autotrophic respiration that was unrelated to growth. This suggests that trees decrease investment in tissue maintenance and defence, in line with eco-evolutionary theories that trees are competitively disadvantaged in the absence of growth. We propose that weakened maintenance and defence investment may, in turn, cause the increase in post-drought tree mortality observed at our plots.

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.