Evolutionary history and the effect of biodiversity on plant productivity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Loss of biological diversity because of extinction is one of the most pronounced changes to the global environment. For several decades, researchers have tried to understand how changes in biodiversity might impact biomass production by examining how biomass correlates with a number of biodiversity metrics (especially the number of species and functional groups). This body of research has focused on species with the implicit assumption that they are independent entities. However, functional and ecological similarities are shaped by patterns of common ancestry, such that distantly related species might contribute more to production than close relatives, perhaps by increasing niche breadth. Here, we analyze 2 decades of experiments performed in grassland ecosystems throughout the world and examine whether the evolutionary relationships among the species comprising a community predict how biodiversity impacts plant biomass production. We show that the amount of phylogenetic diversity within communities explained significantly more variation in plant community biomass than other measures of diversity, such as the number of species or functional groups. Our results reveal how evolutionary history can provide critical information for understanding, predicting, and potentially ameliorating the effects of biodiversity loss and should serve as an impetus for new biodiversity experiments.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it