Spatio-temporal differences in pollinator species richness, abundance and conservation status in a Mediterranean island
Bibliographic record
Abstract
Although the Mediterranean basin is a hotspot of pollinator diversity, little is still known about how such diversity is distributed in the region and about its conservation status. This study contributes to filling this information gap by studying pollinator diversity parameters in one of the main Mediterranean islands, Mallorca, and further evaluating their conservation category according to the IUCN criteria. We focus on three communities, two coastal and one mountain shrubland, which we have studied for several years. For each community, we obtained the following variables: (1) Shannon diversity (H'), (2) Pielou's index (J'), (3) Number of pollinators per plant (Lp), (4) Flower visitation rate (FVR), (5) Specialisation index (d') and (6) Normalised degree of pollinators, i.e. the number of plants visited per pollinator species relative to the total number of plant species in the community (ND). All pollinators were categorised into functional groups to test for differences in such variables among them. Differences across communities, years and functional groups were tested through GLMMs. The three communities showed differences in pollinator species composition, species richness and diversity. Pollinator diversity also varied with time, especially in the coastal community, which suffered a major disturbance during one of the study years. Regardless of the functional group, the pollinator specialisation degree seems context-dependent. Native and endemic species might disappear in the short term if appropriate management measures are not taken to narrow down the threats to pollinator populations. Further research is urgently needed to assess most insect pollinators' conservation status in the Mediterranean before such rich diversity is lost forever.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".