Gradients of precipitation and ant abundance may contribute to the altitudinal range limit of subsocial spiders: insights from a transplant experiment
Bibliographic record
Abstract
Species range boundaries often form along environmental gradients that dictate the success of the phenotypes present in each habitat. Sociality may allow colonization of environments where related species with a solitary lifestyle cannot persist. Social spiders in the genus Anelosimus appear restricted to low- and mid-elevation moist environments in the tropics, while subsocial spiders, common at higher elevations and latitudes, appear to be absent from the lowland tropical rainforest. Here, we seek factors that may simultaneously prevent subsocial Anelosimus species from colonizing the lowland rainforest while favouring species with large social groups in this habitat. To this end, we transplanted small groups of a subsocial species, which contain the offspring of a single female, from cloud forest habitat in the centre of its natural range to lower montane rainforest on the range margin and to lowland rainforest outside of the species range. Groups transplanted at the range margin and below their range limit were less likely to disperse and experienced increased mortality. This was correlated with greater rainfall intensity and ant abundance. We show that protection from rainfall enhances the performance of small groups of spiders in the lowland rainforest, and suggest that predation or disturbance by ants may influence the geographical range limits of this species.
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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 | 0.001 | 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 | 0.001 |
| 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".