Multiscale spatial distribution of a littoral fish community in relation to environmental variables
Bibliographic record
Abstract
Using a new statistical tool, Principal Coordinates of Neighbor Matrices, we decomposed the signals representing the variation of fish community composition, fish density, and biomass in the littoral zone of a lake to assess the relative contributions of a series of spatial scales to the overall signal. We also quantified the relationship between variations of fish community descriptors and environmental conditions at different spatial scales. The fish community exhibited scale-dependent variability that we grouped into four categories at spatial scales ranging from 2 km (very broad scale) to <100 m (fine scale). These scales were associated with specific environmental variables, suggesting the presence of scale-dependent ecological processes within the lake. Following the hierarchy theory, we propose that Lake Drouin was primarily structured by the fetch, a very broad scale physical process. Through energy inputs, fetch might have influenced the appearance of various physical structures (i.e., rocky substrates, woody debris, and macrophyte beds) at finer spatial scales (i.e., broad and meso). Functional groups of species were observed and classified according to the range of spatial scales to which they were associated. Cyprinids and small-sized species displayed a multiscale spatial distribution, whereas the distribution patterns of zoobenthivores were restricted to a single spatial scale. This study provides quantitative support to the idea that the littoral zone of lakes can be perceived as a hierarchical arrangement of habitats that differ not only by the environmental conditions among them but also by the spatial scales at which environmental conditions vary within them.
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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) | 0.001 | 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".