Seasonal Sources of Plant Water Uptake and Soil Evaporation Dynamics Across a Boreal Forest‐Shrub Taiga Gradient
Bibliographic record
Abstract
ABSTRACT As high latitudes warm, there is limited knowledge of how rapidly changing species composition and density, combined with shifting precipitation and thawing permafrost, will affect critical zone water fluxes across the subarctic. Here, we use stable isotopes of hydrogen and oxygen to assess the role of soil moisture, precipitation dynamics and plant species on the timing, magnitude and sources of plant water uptake at three sites along an elevational gradient in a subarctic, alpine catchment in southern Yukon, Canada. The sites ranged from a low‐elevation boreal forest to higher elevation shrub taiga with variable shrub cover. We sampled soil and xylem water approximately every 3 weeks from pre‐leaf out to post‐senescence over two hydrologically distinct years. We answer the questions: (1) What are the seasonal and interannual changes in the isotopic composition of soil and xylem water across this range of subarctic vegetation covers?, (2) How does the seasonal origin of xylem water vary in wet and dry conditions? and (3) Do different shrub species at the same location rely on different sources of water? Results showed that while δ 2 H and δ 18 O of volume weighted precipitation became more negative with elevation, the opposite was true of xylem water. Despite less snowfall at lower elevations, plant water uptake was more reflective of snow water at the forest than at the high elevation shrub sites. Near‐surface bulk soil water had lower line‐conditioned excess at the forest than at the shrub sites throughout the season and with depth, highlighting increased contributions from soil evaporation at the forest. Differences in annual precipitation and climate had a strong influence on stable isotopes of hydrogen and oxygen in the soil. These results demonstrate that vegetation type and elevation strongly mediate plant water sourcing and evaporative partitioning in subarctic catchments, underscoring the need to account for species‐specific and landscape‐scale variability when predicting blue/green water fluxes in a changing climate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".