Niche complementarity stabilizes grassland biomass during drought and eutrophication
Bibliographic record
Abstract
Anthropogenic impacts increasingly involve multi‐factor changes to resource pools and flows, whose outcomes on ecosystem function are difficult to predict. Here, we factorially manipulated drought with eutrophication (nitrogen fertilization) in C3 and C4 grassland, testing for impacts on aboveground community‐ and species‐level plant biomass. Drought and eutrophication may be especially detrimental to plant production, with elevated water demand by drought‐stressed and fertilized plants hypothesized to limit growth while potentially triggering insect outbreaks given changes to foliar‐nitrogen (N). Despite eliminating precipitation for two months, biomass was stabilized by treatment‐induced biomass increases in some species offsetting declines by others (i.e. ‘niche complementarity'), even in drought‐sensitive C3 grassland: community‐level plant biomass remained stable via significant species‐level biomass shifts among the 61 taxa in both communities. These compensatory responses occurred despite increased water demands by fertilized plants, greater drought‐tolerance by C4 grasses compared to C3 taxa, elevated plant mortality, and the reduction of soil moisture below the field‐calculated plant wilting point by mid‐summer. A key mechanism for resilience appeared to be variation in rooting depth, given that soil moisture reductions were greatest within the top 30 cm. There was no detectable change in foliar‐N with drought nor any increase in insect abundance or herbivore damage. We imposed one of the lowest rainfall totals of the past three decades in our study region yet observed resilience via species‐specific compensatory responses. Our results confirm short‐term drought‐tolerance in grasslands, with co‐occurring rainfall reductions and eutrophication unable to alter community‐level production of standing biomass.
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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) | 0.001 | 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".