Carving out turf in a biodiversity hotspot: multiple, previously unrecognized shrew species co‐occur on<scp>J</scp>ava<scp>I</scp>sland,<scp>I</scp>ndonesia
Bibliographic record
Abstract
In theory, competition among species in a shared habitat results in niche separation. In the case of small recondite mammals such as shrews, little is known about their autecologies, leaving open questions regarding the degree to which closely related species co-occur and how or whether ecological niches are partitioned. The extent to which species are able to coexist may depend on the degree to which they exploit different features of their habitat, which may in turn influence our ability to recognize them as species. We explored these issues in a biodiversity hotspot, by surveying shrew (genus Crocidura) diversity on the Indonesian island of Java. We sequenced portions of nine unlinked genes in 100-117 specimens of Javan shrews and incorporated homologous data from most known Crocidura species from other parts of island South-East Asia. Current taxonomy recognizes four Crocidura species on Java, including two endemics. However, our phylogenetic, population genetic and species delimitation analyses identify five species on the island, and all are endemic to Java. While the individual ranges of these species may not overlap in their entirety, we found up to four species living syntopically and all five species co-occurring on one mountain. Differences in species' body size, use of above ground-level habitats by one species and habitat partitioning along ecological gradients may have facilitated species diversification and coexistence.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".