Assessing patterns of nestedness in stream insect assemblages along environmental gradients
Bibliographic record
Abstract
Nestedness is a widely studied pattern in ecology and biogeography. Nestedness has been termed perfect when sites harbouring low-diversity assemblages contain subsets of species in progressively more diverse assemblages. Nestedness has been studied in various regional and environmental contexts, but few studies have rigorously examined environmental factors underlying this pattern. We studied the degree and determinants of nestedness in insect assemblages of headwater streams. We hypothesized that nested habitat characteristics and nested niche structure generate nestedness in these organisms and tested this hypothesis in 8 boreal drainage basins (63–70° N, 23–29° E). Stream insect assemblages were significantly nested in all 8 regions based on the nestedness temperature calculator and in 5 regions based on discrepancy analysis. Nestedness was weak, however, as suggested by high matrix temperature values. Site ranks in the maximally packed nestedness matrix were significantly correlated to stream size in 2 of the regions and to environmental gradients in 5 of the regions. Nestedness was primarily governed by stream size and local environmental gradients. The relationships of nestedness to environmental gradients suggest that, at least in some regions, stream insects show nested niche structure with regard to their responses to environmental gradients. These environmental relationships are highly region-specific, however, suggesting strong context- dependency in nested subset patterns.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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 teacher head, 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".