The dynamics of the diversity–energy relationship during the last 21,000 years
Bibliographic record
Abstract
Abstract Aim Spatial diversity patterns are linked to energy availability, but how the diversity–energy relationship changes in space and time is unclear. There are three possible scenarios: (a) equilibrium dynamics, where diversity is always positively related to energy availability in both time and space; (b) out‐of‐equilibrium dynamics, where diversity is determined by energy availability in equilibrium, but diversity variation lags behind changes in energy availability, leading to a mismatch between temporal and spatial diversity–energy relationships; and (c) disequilibrium dynamics where the equilibrium does not exist or is irrelevant. We attempt to distinguish these scenarios using spatio‐temporal palaeoecological data. Location USA and Canada. Time period 21,000–1,000 years before present. Major taxa studied Woody plants. Methods We tested for the strength and direction of temporal and spatial relationships between pollen type diversity of woody species and energy availability (estimated from temperature and precipitation) in 1,000‐year time steps. Results Whereas the temporal diversity–energy relationship appears only when energy levels rapidly change, the spatial diversity–energy relationship is pronounced only when these levels stabilize. Main conclusions Our findings are consistent with the out‐of‐equilibrium scenario – diversity equilibria do exist and act as attractors of diversity dynamics, but diversity is often out of equilibrium. Consequently, current rapid climate changes can disrupt spatially consistent diversity–energy relationships. To understand diversity dynamics, it is crucial to simultaneously consider both the spatial and temporal dimensions of diversity variation.
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 | 0.000 | 0.002 |
| 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 | 0.001 | 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".