Global distribution of a key trophic guild contrasts with common latitudinal diversity patterns
Bibliographic record
Abstract
Most hypotheses explaining the general gradient of higher diversity toward the equator are implicit or explicit about greater species packing in the tropics. However, global patterns of diversity within guilds, including trophic guilds (i.e., groups of organisms that use similar food resources), are poorly known. We explored global diversity patterns of a key trophic guild in stream ecosystems, the detritivore shredders. This was motivated by the fundamental ecological role of shredders as decomposers of leaf litter and by some records pointing to low shredder diversity and abundance in the tropics, which contrasts with diversity patterns of most major taxa for which broad-scale latitudinal patterns haven been examined. Given this evidence, we hypothesized that shredders are more abundant and diverse in temperate than in tropical streams, and that this pattern is related to the higher temperatures and lower availability of high-quality leaf litter in the tropics. Our comprehensive global survey (129 stream sites from 14 regions on six continents) corroborated the expected latitudinal pattern and showed that shredder distribution (abundance, diversity and assemblage composition) was explained by a combination of factors, including water temperature (some taxa were restricted to cool waters) and biogeography (some taxa were more diverse in particular biogeographic realms). In contrast to our hypothesis, shredder diversity was unrelated to leaf toughness, but it was inversely related to litter diversity. Our findings markedly contrast with global trends of diversity for most taxa, and with the general rule of higher consumer diversity at higher levels of resource diversity. Moreover, they highlight the emerging role of temperature in understanding global patterns of diversity, which is of great relevance in the face of projected global warming.
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.
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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".