Incorporating asymmetric movement costs into measures of habitat connectivity to assess impacts of hydrologic alteration to stream fishes
Bibliographic record
Abstract
Abstract Aim Hydrologic alterations are widespread in freshwater ecosystems worldwide and often detrimentally impact fish populations. Habitat suitability models are commonly used to assess these impacts, but these models frequently rely upon observed fish–habitat relationships rather than more mechanistic underpinnings. The aim of this study was to demonstrate how to incorporate swim performance into a measure of habitat connectivity at a fine scale, providing a method for assessing the availability of suitable habitat for stream fishes. Location We applied this technique to an endangered species, the Western Silvery Minnow Hybognathus argyritis, in the Milk River of southern Alberta, Canada. The Milk River is an augmented system, where a diversion in nearby St. Mary River augments flow by a factor >3 × (from 1–5 m3/s to 15–20 m3/s). Methods We used laboratory measured swim performance of Western Silvery Minnow to develop a movement cost function that was used in conjunction with a habitat suitability model to assess habitat availability via a recently developed graph‐theoretic metric, equivalent connected area (ECA). Results Stream augmentation altered not only habitat suitability but also habitat connectivity for this species. During augmentation, suitable habitat area declined by 81.3%. Changes in habitat connectivity were site dependent. Movement costs between habitat patches were lower during augmentation due to current‐assisted dispersal and increased distance to patches during natural flows from dried streambeds. When movement costs were incorporated into ECA, ECA decreased by 78.0% during augmentation. Main conclusions With changing climate and increasing anthropogenic impacts on aquatic ecosystems, understanding how freshwater fishes relate to their habitat is critical for appropriate management. In many cases, such as the Western Silvery Minnow, mitigating habitat suitability may not be sufficient, as species are unable to reach suitable habitat. The incorporation of swim performance into habitat connectivity assessments, as carried out here, can be easily adapted to other species and situations and can improve the understanding of impacts to stream fishes and increase the effectiveness of mitigation efforts.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".