Hydrological connectivity influences the aquatic metacommunity structure of an Arctic delta floodplain
Bibliographic record
Abstract
Hydrological connectivity is a fundamental determinant of aquatic metacommunity structure. However, the potential response to altered patterns of connectivity in a changing climate remain poorly understood, particularly in regard to vulnerable systems such as Arctic deltaic lakes. Here, we present the first study to examine the metacommunity structure of aquatic invertebrates in a major Arctic floodplain system (Mackenzie Delta, Northwest Territories). We sampled macroinvertebrate communities across the longitudinal span of the Delta and used three complementary analyses (variance partitioning, elements of metacommunity structure, and fourth corner analysis) to determine the relative influence of environmental versus spatial variation, metacommunity structure across dispersal modes, and the functional metacommunity structure. Environmental factors explained the most variation (23%) compared to spatial factors (2%) or environmental/spatial covariance (4%). Functional structure was primarily related to macroinvertebrate dispersal mode and lake isolation, with distributions of aerial dispersers determined mainly by environmental factors and aquatic dispersers by both dispersal limitation and environmental factors. We attribute these results to the inter-lake mixing effects of annual flooding and the lack of barriers to aerial dispersal, and discuss how a loss of aquatic invertebrate biodiversity could result from projected climate-mediated alterations to ice jam dynamics in the Delta.
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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 | 0.000 |
| 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".