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Abstract Quantifying relative contributions of plant transpiration (T) and soil evaporation to evapotranspiration (ET) is crucial to better understand how vegetation influences and controlsET, the largest efflux of the terrestrial water balance. Here, we derive estimates of transpiration fraction (T/ET) using consistent isotope‐basedETpartitioning methods for 13 sites spanning five ecosystem types of the continental US, capturing 56 snapshots ofT/ETduring the growing season. We found transpiration dominated theETflux across all sites with a meanT/ETof 0.81 ± 0.08 (±standard error). Sites and dates with higher vegetation indices exhibited higherT/ETand transpiration rates, with the latter increasing 0.30 mm/day per unit Leaf Area Index and 2.9 mm/day per unit Normalized Difference Vegetation Index. Counter to expectations, antecedent precipitation had no effect onT/ET. Despite the breadth of ecosystems and conditions represented, evaporation exceeded transpiration only once, suggesting that evaporation rarely dominatesETin the growing season. 

Abstract Land surface models (LSMs) play a crucial role in elucidating water and carbon cycles by simulating processes such as plant transpiration and evaporation from bare soil, yet calibration often relies on comparing LSM outputs of landscape total evapotranspiration (ET) and discharge with measured bulk fluxes. Discrepancies in partitioning into component fluxes predicted by various LSMs have been noted, prompting the need for improved evaluation methods. Stable water isotopes serve as effective tracers of component hydrologic fluxes, but data and model integration challenges have hindered their widespread application. Leveraging National Ecological Observation Network measurements of water isotope ratios at 16 US sites over 3 years combined with LSM‐modeled fluxes, we employed an isotope‐enabled mass balance framework to simulateETisotope values (δET) within three operational LSMs (Mosaic, Noah, and VIC) to evaluate their partitioning. Models simulatingδETvalues consistent with observations were deemed more reflective of water cycling in these ecosystems. Mosaic exhibited the best overall performance (Kling‐Gupta Efficiency of 0.28). For both Mosaic and Noah there were robust correlations between bare soil evaporation fraction and error (negative) as well as transpiration fraction and error (positive). We found the point at which errors are smallest (x‐intercept of the multi‐site regression) is at a higher transpiration fraction than is currently specified in the models. Which means that transpiration fraction is underestimated on average. Stable isotope tracers offer an additional tool for model evaluation and identifying areas for improvement, potentially enhancing LSM simulations and our understanding of land‐surface hydrologic processes. 

Plant functional traits hold the potential to greatly improve the understanding and prediction of climate impacts on ecosystems and carbon cycle feedback to climate change. Traits are commonly used to place species along a global conservative-acquisitive trade-off, yet how and if functional traits and conservative-acquisitive trade-offs scale up to mediate community and ecosystem fluxes is largely unknown. Here, we combine functional trait datasets and multibiome datasets of forest water and carbon fluxes at the species, community, and ecosystem-levels to quantify the scaling of the tradeoff between maximum flux and sensitivity to vapor pressure deficit. We find a strong conservative-acquisitive trade-off at the species scale, which weakens modestly at the community scale and largely disappears at the ecosystem scale. Functional traits, particularly plant water transport (hydraulic) traits, are strongly associated with the key dimensions of the conservative-acquisitive trade-off at community and ecosystem scales, highlighting that trait composition appears to influence community and ecosystem flux dynamics. Our findings provide a foundation for improving carbon cycle models by revealing i) that plant hydraulic traits are most strongly associated with community- and ecosystem scale flux dynamics and ii) community assembly dynamics likely need to be considered explicitly, as they give rise to ecosystem-level flux dynamics that differ substantially from trade-offs identified at the species-level. 

Abstract The National Ecological Observatory Network (NEON) provides open-access measurements of stable isotope ratios in atmospheric water vapor (δ 2 H, δ 18 O) and carbon dioxide (δ 13 C) at different tower heights, as well as aggregated biweekly precipitation samples (δ 2 H, δ 18 O) across the United States. These measurements were used to create the NEON Daily Isotopic Composition of Environmental Exchanges (NEON-DICEE) dataset estimating precipitation (P; δ 2 H, δ 18 O), evapotranspiration (ET; δ 2 H, δ 18 O), and net ecosystem exchange (NEE; δ 13 C) isotope ratios. Statistically downscaled precipitation datasets were generated to be consistent with the estimated covariance between isotope ratios and precipitation amounts at daily time scales. Isotope ratios in ET and NEE fluxes were estimated using a mixing-model approach with calibrated NEON tower measurements. NEON-DICEE is publicly available on HydroShare and can be reproduced or modified to fit user specific applications or include additional NEON data records as they become available. The NEON-DICEE dataset can facilitate understanding of terrestrial ecosystem processes through their incorporation into environmental investigations that require daily δ 2 H, δ 18 O, and δ 13 C flux data.