The stable isotopes of hydrogen and oxygen (δ 2 H and δ 18 O, respectively) have been widely used to investigate tree water source partitioning. These tracers have shed new light on patterns of tree water use in time and space. However, there are several limiting factors to this methodology (e.g., the difficult assessment of isotope fractionation in trees, and the labor-intensity associated with the collection of significant sample sizes) and the use of isotopes alone has not been enough to provide a mechanistic understanding of source water partitioning. Here, we combine isotope data in xylem and soil water with measurements of tree's physiological information including tree water deficit (TWD), fine root distribution, and soil matric potential, to investigate the mechanism driving tree water source partitioning. We used a 2 m 3 lysimeter with willow trees (Salix viminalis) planted within, to conduct a high spatial-temporal resolution experiment. TWD provided an integrated response of plant water status to water supply and demand. The combined isotopic and TWD measurement showed that short-term variation (within days) in source water partitioning is determined mainly by plant hydraulic response to changes in soil matric potential. We observed

The boreal forest is a major contributor to the global climate system, therefore, reducing uncertainties in how the forest will respond to a changing climate is critical. One source of uncertainty is the timing and drivers of the spring transition. Remote sensing can provide important information on this transition, but persistent foliage greenness, seasonal snow cover, and a high prevalence of mixed forest stands (both deciduous and evergreen species) complicate interpretation of these signals. We collected tower-based remotely sensed data (reflectance-based vegetation indices and Solar-Induced Chlorophyll Fluorescence [SIF]), stem radius measurements, gross primary productivity, and environmental conditions in a boreal mixed forest stand. Evaluation of this data set shows a two-phased spring transition. The first phase is the reactivation of photosynthesis and transpiration in evergreens, marked by an increase in relative SIF, and is triggered by thawed stems, warm air temperatures, and increased available soil moisture. The second phase is a reduction in bulk photoprotective pigments in evergreens, marked by an increase in the Chlorophyll-Carotenoid Index. Deciduous leaf-out occurs during this phase, marked by an increase in all remotely sensed metrics. The second phase is controlled by soil thaw. Our results demonstrate that remote sensing metrics can be used to detect specific physiological changes in boreal tree species during the spring transition. The two-phased transition explains inconsistencies in remote sensing estimates of the timing and drivers of spring recovery. Our results imply that satellite-based observations will improve by using a combination of vegetation indices and SIF, along with species distribution information. Plain Language SummaryThe boreal forest is one of the most sensitive regions on the planet to climate change, yet its sensitivity remains poorly understood. In particular, the timing and drivers of the spring transition, as the forest changes from a winter adapted state to a summer adapted state, carry significant uncertainties. Remote sensing metrics can be used to characterize the spring transition, but their interpretation is complicated by persistent greenness, frequent snow cover, and a high prevalence of forests containing both deciduous and evergreen species. We collected tower-based remotely sensed metrics, stem radius, and carbon uptake measurements and show that the spring transition occurs in two distinct phases. The first phase is a reactivation of photosynthesis in evergreens and is triggered by thawed stems, warm air temperature, and moist soil. The second phase is a change in evergreen photoprotective pigment levels and the leaf-out of deciduous species. It is triggered by soil thaw. Both phases were detected with different remote sensing metrics that depended on species type. Our results illustrate how satellite measurements could be improved to capture the spring transition over diverse landscapes and what environmental factors control the spring transition.

Rationale:The stable isotope compositions of hydrogen and oxygen in water (δ 2 H and δ 18 O values) have been widely used to investigate plant water sources, but traditional isotopic measurements of plant waters are expensive and labor intensive.Recent work with direct vapor equilibration (DVE) on laser spectroscopy has shown potential to side step limitations imposed by traditional methods. Here, we evaluate DVE analysis of plants with a focus on spectral contamination introduced by organic compounds. We present 17 O-excess as a way of quantifying organic compound interference in DVE. Methods: We performed isotopic analysis using the δ 2 H, δ 18 O and δ 17 O values of water on an Off-Axis Integrated Cavity Output Spectroscopy (IWA-45EP OA-ICOS) instrument in vapor mode. We used a set of methanol (MeOH) and ethanol (EtOH) solutions to assess errors in isotope measurements. We evaluated how organic compounds affect the 17 O-excess. DVE was used to measure the isotopic signatures in natural plant material from Pinus banksiana, Picea mariana, and Larix laricina, and soil from boreal forest for comparison with solutions. Results: The 17 O-excess was sensitive to the presence of organic compounds in water. 17 O-excess changed proportionally to the concentration of MeOH per volume of water, resulting in positive values, while EtOH solutions resulted in smaller changes in the 17 O-excess. Soil samples did not show any spectral contamination. Plant samples were spectrally contaminated on the narrow-band and were enriched in 1 H and 16 O compared with source water. L. laricina was the only species that did not show any evidence of spectral contamination. Xylem samples that were spectrally contaminated had positive 17 O-excess values. Conclusions: 17 O-excess can be a useful tool to identify spectral contamination and improve DVE plant and soil analysis in the laboratory and in situ. The 17 O-excess flagged the presence of MeOH and EtOH. Adding measurement of δ 17 O values to traditional measurement of δ 2 H and δ 18 O values may shed new light on plant water analysis for source mixing dynamics using DVE.

The water balance is ecohydrology's most important equation. Rodriguez-Iturbe (2000) notes that although apparently simple, it still presents serious challenges when infiltration, evapotranspiration, and leakage are all dependent on soil moisture dynamics. While useful, the black box water accounting model is unable to mechanistically assess mixing dynamics, ages of the water fluxes, and partitioning dynamics. Because of this, there have been recent calls for a different way of addressing the water balance (McDonnell, 2017)-one that tracks both the input-storage-output relations and the age of each component. This is because closure of the water balance (annually, the tradition in catchment hydrology) is physically unrealistic when individual water balance components can greatly exceed 1 year. Indeed, traditional hydrometric approaches to water balance closure only describe how much water flows through a system and not which water.In a recent review, Sprenger et al. (2019) noted that empirical water age data in the critical zone remains scarce and "with improving technology, we are gaining insights into the diversity of water ages within pools that have been elsewhere treated as well-mixed buckets." Some examples include the fact that two third of groundwater below 250 m is more than 10,000 years old (Jasechko et al., 2017); that often summer transpiration can be older water from previous seasons (Allen et al., 2019;Brooks et al., 2010). In extreme cases transpired water can be many months or years old (Zhang et al., 2017); Generally, stored water is much older than the stream waters that drain them (Berghuijs & Kirchner, 2017)-with stream waters themselves often in the years to decades age range (McGuire & McDonnell, 2006).But while tracer data in streamflow is now relatively abundant (Penna et al., 2018;Sprenger et al., 2019) and available at high resolution (Rode et al., 2016;von Freyberg et al., 2017), a major share of the water balance still goes through an outlet that is almost unmonitored in terms of tracers: the transpiration flux.

The stable isotopes of hydrogen and oxygen in xylem water are often used to investigate tree water sources. But this traditional approach does not acknowledge the contribution of water stored in the phloem to transpiration and how this may affect xylem water and source water interpretations. Additionally, there is a prevailing assumption that there is no isotope fractionation during tree water transport. Here, we systematically sampled xylem and phloem water at daily and subdaily resolutions in a large lysimeter planted with Salix viminalis. Stem diurnal change in phloem water storage and transpiration rates were also measured. Our results show that phloem water is significantly less enriched in heavy isotopes than xylem water. At subdaily resolution, we observed a larger isotopic difference between xylem and phloem during phloem water refilling and under periods of tree water deficit. These findings contrast with the expectation of heavy‐isotope enriched water in phloem due to downward transport of enriched leaf water isotopic signatures. Because of previous evidence of aquaporin mediated phloem and xylem water transport and higher osmotic permeability of lighter hydrogen isotopologues across aquaporins, we propose that radial water transport across the xylem–phloem boundary may drive the relative depletion of heavy isotopes in phloem and their relative enrichment in xylem.

RationaleHydrogen and oxygen stable isotope ratios (δ2H, δ17O, and δ18O values) are commonly used tracers of water. These ratios can be measured by isotope ratio infrared spectroscopy (IRIS). However, IRIS approaches are prone to errors induced by organic compounds present in plant, soil, and natural water samples. A novel approach using 17O‐excess values has shown promise for flagging spectrally contaminated plant samples during IRIS analysis. A systematic assessment of this flagging system is needed to prove it useful.MethodsErrors induced by methanol and ethanol water mixtures on measured IRIS and isotope ratio mass spectrometry (IRMS) results were evaluated. For IRIS analyses both liquid‐ and vapour‐mode (via direct vapour equilibration) methods are used. The δ2H, δ17O, and δ18O values were measured and compared with known reference values to determine the errors induced by methanol and ethanol contamination. In addition, the 17O‐excess contamination detection approach was tested. This is a post‐processing detection tool for both liquid and vapour IRIS triple‐isotope analyses, utilizing calculated 17O‐excess values to flag contaminated samples.ResultsOrganic contamination induced significant errors in IRIS results, not seen in IRMS results. Methanol caused larger errors than ethanol. Results from vapour‐IRIS analyses had larger errors than those from liquid‐IRIS analyses. The 17O‐excess approach identified methanol driven error in liquid‐ and vapour‐mode IRIS samples at levels where isotope results became unacceptably erroneous. For ethanol contaminated samples, a mix of erroneous and correct flagging occurred with the 17O‐excess method. Our results indicate that methanol is the more problematic contaminant for data corruption. The 17O‐excess method was therefore useful for data quality control.ConclusionsOrganic contamination caused significant errors in IRIS stable isotope results. These errors were larger during vapour analyses than during liquid IRIS analyses, and larger for methanol than ethanol contamination. The 17O‐excess method is highly sensitive for detecting narrowband (methanol) contamination error in vapour and liquid analysis modes in IRIS.

Source water apportionment studies using the dual isotopes of oxygen and hydrogen have revolutionized our understanding of ecohydrology. But despite these developments-mostly over the past decade-many technical problems still exist in terms of linking xylem water to its soil water and groundwater sources. This is mainly

Ecohydrological investigations commonly use the stable isotopes of water (hydrogen and oxygen) as conservative ecosystem tracers. This approach requires accessing and analysing water from plant and soil matrices. Generally, there are six steps involved to retrieve hydrogen and oxygen isotope values from these matrices: (1) sampling, (2) sample storage and transport, (3) extraction, (4) pre‐analysis processing, (5) isotopic analysis, and (6) post‐processing and correction. At each step, cumulative errors can be introduced which sum to non‐trivial magnitudes. These can impact subsequent interpretations about water cycling and partitioning through the soil–plant‐atmosphere continuum. At each of these steps, there are multiple possible options to select from resulting in tens of thousands of possible combinations used by researchers to go from plant and soil samples to isotopic data. In a newly emerging field, so many options can create interpretive confusion and major issues with data comparability. This points to the need for development of shared standardized approaches. Here we critically examine the state of the process chain, reflecting on the issues associated with each step, and provide suggestions to move our community towards standardization. Assessing this shared ‘process chain’ will help us see the problem in its entirety and facilitate community action towards agreed upon standardized approaches.