Data from: Climate and local environment structure asynchrony and the stability of primary production in grasslands
Bibliographic record
Abstract
Aim: Climate variability threatens to destabilize production in many ecosystems. Asynchronous species dynamics may buffer against such variability when decreased performance by some species is offset by increased performance of others. However, high climatic variability can eliminate species through stochastic extinctions or cause similar stress responses among species, reducing buffering. Local conditions, such as soil nutrients, can further alter production stability directly or by influencing asynchrony. We test these hypotheses using a globally distributed sampling experiment. Location: Grasslands in North America, Europe and Australia. Time period: Annual surveys over five-year intervals occurring between 2007 and 2014. Major taxa studied: Herbaceous plants. Methods: We annually sampled per-species cover and aboveground community biomass (net primary productivity; NPP), plus soil chemical properties, in twenty-nine grasslands. We tested how soil conditions, combined with precipitation and temperature variability, affect species richness, asynchrony and temporal stability of primary productivity. We used bivariate relationships and structural equation modeling to examine proximate and ultimate relationships. Results: Climate variability strongly predicted asynchrony, whereas NPP stability was more related to soil conditions. Species richness was structured by both climate variability and soils, and in turn increased asynchrony. Temperature and precipitation variability caused a unimodal asynchrony response, with asynchrony lowest at low and high climate variability. Climate impacted stability indirectly through its effect on asynchrony, with stability increasing at higher asynchrony due to lower inter-annual NPP variability. Soil conditions had no detectable effect on asynchrony but increased stability by increasing mean NPP, especially when soil organic matter was high. Main Conclusions: We found globally consistent evidence that climate modulates species asynchrony, but that the direct effect on stability is low relative to local soil conditions. Nonetheless, our observed unimodal responses to temperature and precipitation variability suggest asynchrony thresholds, beyond which there are detectable destabilizing impacts of climate on primary productivity.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 0.001 |
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".