Salt marsh ecohydrological zonation due to heterogeneous vegetation–groundwater–surface water interactions
Bibliographic record
Abstract
Vegetation zonation and tidal hydrology are basic attributes of intertidal salt marshes, but specific links among vegetation zonation, plant water use, and spatiotemporally dynamic hydrology have eluded thorough characterization. We developed a quantitative model of an intensively studied salt marsh field site, integrating coupled 2‐D surface water and 3‐D groundwater flow and zonal plant water use. Comparison of model scenarios with and without heterogeneity in (1) evapotranspiration rates and rooting depths, according to mapped vegetation zonation, and (2) sediment hydraulic properties from inferred geological heterogeneity revealed the coupled importance of both sources of ecohydrological variability at the site. Complex spatial variations in root zone pressure heads, saturations, and vertical groundwater velocities emerged in the model but only when both sources of ecohydrological variability were represented together and with tidal dynamics. These regions of distinctive root zone hydraulic conditions, caused by the intersection of vegetation and sediment spatial patterns, were termed “ecohydrological zones” (EHZ). Five EHZ emerged from different combinations of sediment hydraulic properties and evapotranspiration rates, and two EHZ emerged from local topography. Simulated pressure heads and groundwater dynamics among the EHZ were validated with field data. The model and data showed that hydraulic differences between EHZ were masked shortly after a flooding tide but again became prominent during prolonged marsh exposure. We suggest that ecohydrological zones, which reflect the combined influences of topographic, sediment, and vegetation heterogeneity and do not emphasize one influence over the others, are the fundamental spatial habitat units comprising the salt marsh ecosystem.
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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 | 0.001 |
| 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".