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With current observations and future projections of more intense and frequent droughts in the tropics, understanding the impact that extensive dry periods may have on tree and ecosystem-level transpiration and concurrent carbon uptake has become increasingly important. Here, we investigate paired soil and tree water extraction dynamics in an old-growth upland forest in central Amazonia during the 2018 dry season. Tree water use was assessed via radial patterns of sap flow in eight dominant canopy trees, each a different species with a range in diameter, height, and wood density. Paired multi-sensor soil moisture probes used to quantify volumetric water content dynamics and soil water extraction within the upper 100 cm were installed adjacent to six of those trees. To link depth-specific water extraction patterns to root distribution, fine root biomass was assessed through the soil profile to 235 cm. To scale tree water use to the plot level (stand transpiration), basal area was measured for all trees within a 5 m radius around each soil moisture probe. The sensitivity of tree transpiration to reduced precipitation varied by tree, with some increasing and some decreasing in water use during the dry period. Tree-level water use scaled with sapwood area, from 11 to 190 L per day. Stand level water use, based on multiple plots encompassing sap flow and adjacent trees, varied from ∼1.7 to 3.3 mm per day, increasing linearly with plot basal area. Soil water extraction was dependent on root biomass, which was dense at the surface (i.e., 45% in the upper 5 cm) and declined dramatically with depth. As the dry season progressed and the upper soil dried, soil water extraction shifted to deeper levels and model projections suggest that much of the water used during the month-long dry-down could be extracted from the upper 2-3 m. Results indicate variation in rates of soil water extraction across the research area and, temporally, through the soil profile. These results provide key information on whole-tree contributions to transpiration by canopy trees as water availability changes. In addition, information on simultaneous stand level dynamics of soil water extraction that can inform mechanistic models that project tropical forest response to drought.

In forest ecosystems, transpiration (T) patterns are important for quantifying water and carbon fluxes and are major factors in predicting ecosystem change. Seasonal changes in rainfall and soil water content can alter the sensitivity of sap flux density to daily variations in vapor pressure deficit (VPD). This sensitivity is species-specific and is thought to be related to hydraulic strategies. The aim of this work is to better understand how the sap flux density of species with low versus high wood density differ in their sensitivity to VPD and soil water content and how potentially opposing water-use strategies influence T dynamics, and ultimately, correlations to evapotranspiration (ET). We use hysteresis area analysis to quantify the sensitivity of species-specific sap flux density to changes in the VPD, breakpoint-based models to determine the soil water content threshold instigating a T response and multiscalar wavelet coherency to correlate T to ET. We found that low wood density Commiphora leptophloeos (Mart.) Gillett had a more dynamic T pattern, a greater sensitivity to VPD at high soil water content, required a higher soil water content threshold for this sensitivity to be apparent, and had a significant coherency correlation with ET at daily to monthly timescales. This behavior is consistent with a drought avoidance strategy. High wood density Cenostigma pyramidale   (Tul.)   E. Gagnon & G. P. Lewis , conversely, had a more stable T pattern, responded to VPD across a range of soil water content, tolerated a lower soil water content threshold to T, and had a significant coherency correlation with ET at weekly timescales. This behavior is consistent with a drought-tolerant strategy. We build on previous research to show that these species have contrasting water-use strategies that should be considered in large-scale modeling efforts. [ABSTRACT FROM AUTHOR]