Ecological trends in moth communities (Geometridae, Lepidoptera) along a complete rainforest elevation gradient in Papua New Guinea
Bibliographic record
Abstract
Abstract The tropical rainforest elevation gradients, extending from lowlands to treeline, often represent global maxima of biodiversity and are models for community studies. We surveyed geometrid moths along a complete rainforest gradient from 200 to 3700 m asl. in Papua New Guinea. The 16,424 moths collected with light traps represented 1102 species, a high diversity for such system. We demonstrated the importance of molecular data for taxonomy as COI sequences (DNA barcodes) changed the definition of 19% of morphological species. The abundance of geometrids did not change with elevation while their species richness peaked at 1200 m asl. The mid‐elevation diversity peak is a common, but poorly understood, pattern for geometrids. It was best explained by the species richness of the vegetation. At the same time, the community was exposed to opposing trends in abiotic favourability (decreasing temperature) and biotic favourability (decreasing predation by ants, birds and bats) with elevation, potentially contributing to such unimodal trends in species richness. Beta diversity of communities separated by 500 m elevation increased with increasing elevation, reflecting decreasing mean elevational range of species—a pattern opposite to that expected under the Rapoport's rule. The total number of species along the elevation gradient corresponded to 280% of the highest local community diversity. This enrichment of species underscores the key role of long elevational gradients in maintaining high regional diversity and makes them a conservation priority, especially as they also allow for redistribution of species in response to climate change.
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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 | 0.000 |
| 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".