Spider diversity across an elevation gradient in Área de Conservación Guanacaste (ACG), Costa Rica
Bibliographic record
Abstract
Abstract Throughout the Neotropics, temperature and precipitation change with elevation and these changes affect the assemblage of species at any particular elevation. We documented the diversity of litter‐inhabiting spiders, (Arachnida: Araneae) along a Costa Rican elevational gradient as it relates to covarying abiotic factors such as temperature and precipitation. The spiders we collected were principally unidentifiable juveniles, and so we used Barcode Index Numbers (BINs) derived from DNA barcodes as proxies for species‐level interim names. We contrasted these taxon‐based estimates with phylogenetic measures of alpha‐ and beta‐diversity derived from both the mitochondrial DNA barcode region and a multi‐gene phylogeny of spiders and found that neither the abundance nor the species richness of spiders was significantly correlated with elevation, temperature, or precipitation. However, we did find that spider assemblages in the upper elevation cloud forests were phylogenetically clustered, (and this pattern was unrelated to whether the phylogenetic patterns were derived mitochondrially or from a multi‐gene analysis). One standard explanation for such a pattern is that harsh abiotic conditions in higher elevation forests have selected for particular spider lineages; however, this remains to be tested fully. The diversity of leaf‐litter spider species we uncovered was high and further sampling of spider abundance and diversity across the ACG is likely to yield many new 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 | 0.000 | 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) | 0.000 | 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".