Population‐ and community‐level rarity have opposing effects on pollinator visitation and seed set
Bibliographic record
Abstract
Abstract When can small, isolated populations overcome the negative consequences of rarity? Despite considerable effort to understand threats to rare species, few studies consider how community context alters these threats. Plant–pollinator interactions offer the opportunity to test the effect of community context on rare species success, as plant–pollinator dynamics are thought to be influenced by neighbouring plants, both through competition for pollinators (reducing success in small populations) and attraction of potential pollinators (increasing success in small populations). Here, we test these predictions by experimentally decoupling community‐level rarity (relative abundance) from population‐level rarity (population size) in experimental two‐species fragments. We created experimental plant communities varying independently in population rarity (population size) and community rarity (relative abundance) of two annual plant species. We isolated plant roots to eliminate resource competition. We then compared the effects of population size versus relative abundance on pollinator visitation rates and an estimate of seed production. Both species had greatest pollinator visitation in large populations, but the negative effects of population rarity on visitation were partially offset when the neighbouring species was more abundant—community rarity offset the impacts of population rarity for the most common group of pollinators, solitary bees. These visitation trends impacted seed production for one species. When at low relative abundance,Polanisia dodecandrahad higher seed set, matching increased visitation by solitary bees.Chamaecrista fasciculatashowed no change in seed production with population‐ or community‐level rarity. Synthesis.Our results suggest that the surrounding community can offset the negative effects of low absolute abundance on fitness when neighbouring species are more abundant, and may ultimately maintain diversity even in fragmented ecological communities.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".