Recentering evolution for sustainability science
Bibliographic record
Abstract
Abstract Non-technical summary Evolutionary biology considers how organisms and populations change over multiple generations, and so is naturally focused on issues of sustainability through time. Yet, sustainability science rarely incorporates evolutionary thinking and most scientists and policy makers do not account for how evolutionary processes contribute to sustainability. Understanding the interplay between evolutionary processes and nature's contribution to people is key to sustaining life on Earth. Technical summary Evolution, the change in gene frequencies within populations, is a process of genetically based modification by descent, providing the raw material essential for adaptation to environmental change. Therefore, it is crucial that we understand evolutionary processes if we aim for a sustainable planet. We here contribute to this development by describing examples of contemporary, rapid evolutionary changes of concern for sustainability, specifically highlighting the global spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and how the evolutionary toolbox allowed tracking the origins and evolution of SARS-CoV-2 in real time and predicting potential future outbreaks. We also consider how urban development accelerates evolutionary processes such as altered phenotypic and physiological changes and the spread of infectious and zoonotic diseases. We show the importance of evolutionary concepts and techniques for public-health decision making. Many examples of the potential of evolutionary insights contributing to crucial sustainability challenges exist, including infectious and zoonotic diseases, ecosystem and human health, and conservation of natural resources. We thus join recent calls advocating for a stronger collaboration between evolutionary biologists and the sustainability community, increasing interdisciplinarity and the awareness about the knowledge of evolutionary processes for decision making and policies. Social media summary Evolution is fundamental to sustaining life on Earth and should be incorporated in sustainability measures and policies.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.006 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| 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; 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".