Morphological and structural plasticity of grassland species in response to a gradient in saline‐sodic soils
Bibliographic record
Abstract
The abundance and distribution of species can be ascribed to both environmental heterogeneity and stress tolerance, with the latter measure sometimes associated with phenotypic plasticity. Although phenotypic plasticity varies predictably in response to common forms of stress, we lack a mechanistic understanding of the response of species to high saline-sodic soils. We compared the phenotypic plasticity of three pairs of high and low saline-sodic tolerant congeners from the families Poaceae (Leymus chinensis versus L. secalinus), Fabaceae (Lespedeza davurica versus L. bicolor) and Asteraceae (Artemisia mongolica versus A. sieversiana) in a controlled pot experiment in the Songnen grassland, China. The low tolerant species, L. secalinus and A. sieversiana exhibited higher plasticity in response to soil salinity and sodicity than their paired congeners. Highly tolerant species, L. chinensis and A. mongolica, had higher values for several important morphological traits, such as shoot length and total biomass under the high saline-sodic soil treatment than their paired congeners. In contrast, congeners from the family Fabaceae, L. davurica and L. bicolor, did not exhibit significantly different plasticity in response to soil salinity and sodicity. All species held a constant reproductive effort in response to saline-sodic soil stress. The different responses between low and high tolerant species offer an explanation for the distribution patterns of these species in the Songnen grassland. Highly tolerant species showed less morphological plasticity over a range of saline-sodic conditions than their paired congeners, which may manifest as an inability to compete with co-occurring species in locations where saline-sodic soils are absent.
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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 | 0.000 | 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) | 0.001 | 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".