Plant production and community structure in a mesic semi-natural grassland: Moderate soil textural variation has a much stronger influence than experimentally increased atmospheric nitrogen deposition
Bibliographic record
Abstract
Atmospheric nitrogen (N) deposition derived from agricultural intensification and fossil fuel burning can significantly impact plant growth, species diversity, and nutrient cycling. Semi-natural grasslands are of particular concern because their generally low intensity agricultural management suggests they may be very sensitive to enhanced atmospheric N deposition inputs, although previous experimental research indicates highly variable, site-specific responses. Mediating factors such as soil texture that influence actual availability of soil water and nutrients to plants have generally not been investigated. We report the impacts of 16 years of experimental N addition (simulating 2050 atmospheric N input rates) and a separate, single growing season, high-level N and phosphorus (P) factorial experiment to a hayfield of varying loam soil texture (clay-loam – sandy-loam) on plant community structure and above-and belowground biomass. The chronic low-level N addition treatment had no significant effects on either species or community aboveground growth, species richness, or diversity. These properties were best explained by variation in soil water-filled pore space, and were substantially larger on plots with relatively clay-rich soils. The general lack of responses to the low-level N additions and the lack of a growth response to the short factorial high-level N and P addition experiment, indicate that future atmospheric N deposition increases are unlikely to have major impacts on hay production or species composition in mesic semi-natural grasslands. By contrast, the strong interconnected influences of soil clay content and plant water availability in our results suggest that textural variation – even within loamy soils—will be a primary determinant of the impacts of anticipated future summer warming and reduced rainfall on hayfield vegetation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".