Timing matters: Responses of a mesic old-field meadow to global change manipulations differed after five versus 13 years
Bibliographic record
Abstract
Soil water and nutrient availability shape community structure and ecosystem productivity in temperate mesic grasslands, while herbivory is a key top-down driver. As precipitation regimes shift, nutrient loading rises, and herbivore populations change, none of these drivers will act alone. Yet, no study has examined the interacting, decadal effects of these drivers on the structure and function of old-field meadows, which are common across eastern Canada. My study addresses the following questions: What is the relative importance of the separate and combined effects of altered soil water and nutrient availability in determining: 1) ecosystem functioning (production) and 2) community structure (diversity) over 13 years? 3) Does deer herbivory significantly affect plant production and community structure over 13 years, and does it modify the impacts of altered water and nutrients? 4) Are the community and ecosystem-level responses to altered water, nutrient, and herbivore availability after 13 years different from those after the initial five years, and if so, are these changes conferring ecosystem stability? My study site is a temperate mesic old-field meadow grassland near Kingston, ON, in which factorial manipulations of water (rainout shelters and water additions), nutrient availability (NPK fertilizer additions), and herbivory (herbivore exclosures) were initiated in 2010 on 240 1 m2 plots (n = 20). Species biomass was harvested from 120 plots in 2023 and compared with corresponding data from the other 120 plots that had been harvested in 2015 (Serafini et al., 2019) to assess stability. My results suggest that production was primarily dependent on nutrient availability, except under simulated drought, whereas community structure was more sensitive to watering treatments, with added water increasing diversity and rainouts decreasing it. Simulated drought reduced production in 2015, but had no effect in 2023, suggesting the onset of functional stability. Although temperate grasslands appeared functionally resilient to drought after 13 years, this stability came at the cost of major biodiversity loss driven by community shifts. By contrasting early (five-year) and later (13-year) responses, my study shows how long-term experiments can reveal otherwise hidden trajectories of community change that have important implications for anticipating future ecosystem vulnerabilities under climate change.
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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 | 0.001 |
| 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 | 0.001 | 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".