Towards an applied metaecology
Bibliographic record
Abstract
Abstract The complexity of ecological systems is a major challenge for practitioners and decision-makers who work to avoid, mitigate and manage environmental change. Here, we illustrate how metaecology - the study of spatial interdependencies among ecological systems through fluxes of organisms, energy, and matter - can enhance understanding and improve managing environmental change at multiple spatial scales. We present several case studies illustrating how the framework has leveraged decision-making in conservation, restoration and risk management. Nevertheless, an explicit incorporation of metaecology is still uncommon in the applied ecology literature, and in action guidelines addressing environmental change. This is unfortunate because the many facets of environmental change can be framed as modifying spatial context, connectedness and dominant regulating processes - the defining features of metaecological systems. Narrowing the gap between theory and practice will require incorporating system-specific realism in otherwise predominantly conceptual studies, as well as deliberately studying scenarios of environmental change.
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 | 0.023 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".