The relative role of soil type and tree cover on water storage and transmission in northern headwater catchments
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Bibliographic record
Abstract
Abstract Soil water storage and stable isotopes dynamics were investigated in dominant soil–vegetation assemblages of a wet northern headwater catchment (3.2 km 2 ) with limited seasonality in precipitation. We determined the relative influence of soil and vegetation cover on storage and transmission processes. Forested and non‐forested sites were compared, on poorly drained histosols in riparian zones and freely draining podzols on steeper hillslopes. Results showed that soil properties exert a much stronger influence than vegetation on water storage dynamics and fluxes, both at the plot and catchment scale. This is mainly linked to the overall energy‐limited climate, restricting evaporation, in conjunction with high soil water storage capacities. Threshold behaviour in runoff responses at the catchment scale was associated with differences in soil water storage and transmission dynamics of different hydropedological units. Linear input–output relationships occurred when runoff was generated predominantly from the permanently wet riparian histosols, which show only small dynamic storage changes. In contrast, nonlinear runoff generation was related to transient periods of high soil wetness on the hillslopes. During drier conditions, more marked differences in soil water dynamics related to vegetation properties emerged, in terms of evaporation and impacts on temporarily increasing dynamic storage potential. Overall, our results suggest that soil type and their influence on runoff generation are dominant over vegetation effects in wet, northern headwater catchments with low seasonality in precipitation. Potential increase of subsurface storage by tree cover (e.g. for flood management) will therefore be spatially distributed throughout the landscape and limited to rare and extreme dry conditions. Copyright © 2014 John Wiley & Sons, Ltd.
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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 | 0.000 | 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 it