Odonata metacommunity structure in northern ecosystems is driven by temperature and latitude
Bibliographic record
Abstract
Abstract The metacommunity concept, defined as a set of local communities connected by species dispersal, provides deep understanding of large‐scale ecological processes. The elements of the metacommunity structure (EMS) framework use occurrence data to differentiate among different patterns (i.e., checkerboard, nestedness, species turnover). Metacommunities of tropical Odonata show species turnover following latitude and temperature gradients but there are no such large‐scale studies for other regions. We performed EMS analysis with data for the Odonata of British Columbia, Canada, testing the role of five environmental variables (temperature, latitude, altitude, precipitation, landcover typology) in structuring the metacommunities and their turnover. The suborder Anisoptera drives the general pattern, with the communities showing a Clementsian‐type response (groups of species that replace each other along the environmental gradients) following temperature and latitude ordering. The Clementsian pattern determined by site temperatures reflects the turnover from a group of cold‐adapted species to one of warm‐adapted species, separated by many species with more generalised temperature requirements. Similarly, the Clementsian pattern associated with the latitude gradient indicates the substitution of a low‐latitude group in the south with a high‐latitude group in the north. The sites ordered by landcover did not show significant coherence and turnover. In a macro‐scale framework, Odonata species assemblages seem to be sensitive to the climatic and geographic variables of local sites (i.e., temperature and latitude), regardless of the surrounding habitat typology. The role of such variables in shaping the assembly of Odonata communities should be considered in large‐scale management and conservation projects.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".