Response of Four Shrub Species to Different Water Source Components in an Arid Environment
Bibliographic record
Abstract
Shrubland species in the Great Basin (USA) depend on soil water recharged from precipitation and/or groundwater for survival and growth. Climate warming and possible basin water diversion could alter the amount and timing of water availability to these plants. The objective of this study was to quantify the extent to which each of four co-occurring shrub species, big sage [Artemisia tridentata], rabbitbrush [Ericameria nauseosus], greasewood [Sarcobatus vermiculatus] and shadscale [Atriplex confertifolia)) acquired water from different sources (precipitation, soil vadose zone and/or groundwater) during a growing season. Soil salinity increased linearly with depth over the upper 1.5 m of soil, with salinity ranging from 0.84 to 31.70 dSm-1 in saturation extracts (R2=0.78, p<0.001). Changes in soil water both with depth and time during the growing period indicated that all species accessed soil water from precipitation recharge. Evapotranspiration totals for the growing period exceeded total precipitation by 137 mm, indicating that plants also used water stored deeper within the vadose zone and/or from groundwater (particularly) by the phreatophyte greasewood. Delta18O in the soil solution declined linearly with depth over the upper 100 cm (R2=0.80, p<0.001). Delta18O values in greasewood corresponded closely to Delta18O values measured deeper in the vadose zone and groundwater. Output from a mixing model indicated a decrease in groundwater reliance for greasewood from 30% in July to 2% in September, with a major shift to deeper soil water in the vadose zone (180 cm depth) (38% in July to 97% in September). Our data suggested that the four shrub species at our site were able to coexist because of their different spatial, temporal, and physiological uses of available soil water, reflecting possible water resource partitioning based on differences in response to precipitation, ability to extract water at deeper depths and variable tolerance to elevated levels of soil salinity to access groundwater.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".