Physiological responses to extreme hydrological events in the Pantanal wetland: heterogeneity of a plant community containing super‐dominant species
Bibliographic record
Abstract
Abstract Aims We tested two mechanisms of adaptation to extreme hydrological stresses (flooding and drought) of species making up a tropical wetland plant community by measuring leaf gas exchange and water potential. We hypothesized that anoxic conditions that occur during flooding will decrease leaf gas exchange when compared to the dry season, and that ‘super‐dominant’ species will have a distinctive physiological advantage when compared to other plants within the community. Location Northern Pantanal wetland, Private Natural Heritage Reserve of the Brazilian Social Service of Commerce (RPPN‐SESC Pantanal), Mato Grosso, Brazil. Methods Two periods representing typical extreme hydrological conditions in the Pantanal wetland were selected based on historical soil and meteorological measurements: (1) a drought period when plants experience stress due to soil moisture deficits during a dry season that persists for several months (May to Sept), and (2) a flooding period when oxidation‐reduction potential is negative for 30 d or more (Mar or Apr), indicating anoxic stress. Measurements of gas exchange and leaf water potential were made on seven species in drought and flood stress conditions. The seven species represent the majority of the plant community. Results As a whole, the plant community showed significantly lower potential net photosynthesis (PN) during flooding when soil oxidation‐reduction potential reached close to −900 mV when compared to the dry season, but the magnitude of the decline in PN was species specific. Not all super‐dominant species showed higher PN compared to non‐dominant species, but they did demonstrate higher stomatal conductance and transpiration leading to lower water use efficiency. The combination of higher PN despite low soil water content suggests that the plant community had access to deep water resources. This access was also confirmed by the midday leaf water potential, which was similar for the flood and dry seasons. Conclusions Results suggest that the plant community may have high physiological performance under a wide range of soil oxidation‐reduction potentials. Higher PN rates of super‐dominant species indicate a physiological advantage of these species in the different hydrological conditions.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".