Cryptic matters: overlooked species generate most butterfly beta‐diversity
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
The cryptic fraction of biodiversity is composed of morphologically similar species that are or have been overlooked by scientists. Although current research is increasingly documenting new cases, cryptic species are frequently ignored in large‐scale studies and monitoring programs, either because they have not yet been discovered, or because of the practical difficulties involved in differentiating them. However, it is unknown if this could represent a bias extending beyond the number of missed species. By analyzing the butterfly fauna of the west Mediterranean (335 species), we defined cryptic species based on the current consensus of the scientific community, compared their properties to other congeneric species and investigated the consequences of their inclusion/exclusion in beta‐diversity analyses. We show that, as defined, the cryptic fraction of butterfly diversity represents about 25% of the west Mediterranean fauna and is overwhelmingly composed by groups of species that are not sympatric. Our results show that co‐occurrence among cryptic species is significantly lower than among congeneric non‐cryptic species. Accordingly, albeit the frequency of cryptic species is homogenously distributed over the study area, their distribution pattern accounts for most beta‐diversity turnover over sea (from 50 to 100%). Beta‐diversity turnover, a direct measure of the frequency of species replacement from site to site, is recognized as a fundamental parameter in ecology and is widely used to detect biogeographic patterns. These findings represent a change of paradigm in showing that cryptic diversity comprises original qualitative aspects in addition to merely quantitative ones. This highlights the importance of differentiating cryptic species for various research fields and opens the door to the study of further potential particularities of cryptic diversity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 | 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 it