Biotic interactions mediate patterns of herbivore diversity in the Arctic
Bibliographic record
Abstract
Abstract Aim Understanding the forces shaping biodiversity patterns, particularly for groups of organisms with key functional roles, will help predict the responses of ecosystems to environmental changes. Our aim was to evaluate the relative role of different drivers in shaping the diversity patterns of vertebrate herbivores, a group of organisms exerting a strong trophic influence in terrestrial Arctic ecosystems. This biome, traditionally perceived as homogeneous and low in biodiversity, includes wide variation in biotic and physical conditions and is currently undergoing major environmental change. Location The Arctic (including the High Arctic, Low Arctic and Subarctic) Methods We compiled available data on vertebrate (birds and mammals) herbivore distribution at a pan‐Arctic scale, and used eight variables that represent the most relevant hypotheses for explaining patterns of species richness. We used range maps rasterized on a 100 km × 100 km equal‐area grid to analyse richness patterns of all vertebrate herbivore species combined, and birds and mammalian herbivores separately. Results Overall, patterns of herbivore species richness in the Arctic were positively related to plant productivity (measured using the normalized difference vegetation index) and to the species richness of predators. Greater species richness of herbivores was also linked to areas with a higher mean annual temperature. Species richness of avian and mammalian herbivores were related to the distance from the coast, with the highest avian richness in coastal areas and mammalian richness peaking further inland. Main conclusions Herbivore richness in the Arctic is most strongly linked to primary productivity and the species richness of predators. Our results suggest that biotic interactions, with either higher or lower trophic levels or both, can drive patterns of species richness at a biome‐wide scale. Rapid ongoing environmental changes in the Arctic are likely to affect herbivore diversity through impacts on both primary productivity and changes in predator communities via range expansion of predators from lower latitudes.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".