Expert-led priorities for a response diversity research agenda in ecology
Bibliographic record
Abstract
Abstract Response diversity aims to capture and explain the variation in ecological responses to environmental change. Response diversity is expected to drive ecological stability since a wider variety of responses to one or more environmental factors should stabilise fluctuations of ecosystem functions. However, uptake of empirical response diversity research has been slow. Here we assess current thinking around response diversity by conducting a targeted expert survey of response diversity researchers. Our survey revealed that one barrier to a unified research agenda on response diversity is the lack of agreement among respondents on the definition of response diversity, and to which dimension(s) of ecological stability response diversity might relate. When asked to select the temporal, spatial, and biological scales at which response diversity may be most relevant for ecological stability, respondents chose a wide range of scales indicating differences in how experts view response diversity’s stabilising effect. Respondents considered studies incorporating both biotic interactions and abiotic environmental responses to be especially challenging, as were those thinking about responses to multiple environmental changes simultaneously. Moreover, respondents thought inconsistencies in the definitions of, and methods for measuring, response diversity were a major challenge facing the field. Despite these barriers, the survey revealed a desire for globally coordinated research efforts on response diversity in the form of syntheses, workshops, and distributed experiments, but that a standardised response diversity metric across diverse use-cases could be too restrictive. Our findings suggest we can shift response diversity from a loose collection of conceptual studies and inconsistent empirical applications towards a quantitative and coordinated research programme mechanistically linking biodiversity and ecological stability. As such, we are launching the Response Diversity Network—a research community interested in the science and application of response diversity— whose activities we hope will benefit both individual studies of response diversity and globally coordinated research efforts.
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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 | 0.435 | 0.340 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.012 | 0.018 |
| Scholarly communication | 0.027 | 0.033 |
| Open science | 0.008 | 0.024 |
| Research integrity | 0.032 | 0.032 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".