Current velocity and habitat patchiness shape stream herbivore movement
Bibliographic record
Abstract
Animal movements are influenced by the structure and arrangement of patches in a landscape. Most movement studies occur in terrestrial landscapes, though aquatic landscapes are equally heterogeneous and feature patches that differ in resistance to animal movements. Furthermore, the variable and highly directional flow of water over streambed landscapes is a unique environmental element, yet its constraint on animal movement is poorly understood. This study examines how habitat availability in a streambed landscape interacts with current velocity to affect movement patterns of two benthic grazers: glossosomatid caddisfly larvae ( Agapetus boulderensis ) and pulmonate snails ( Physa sp.). Using experimental streambed landscapes, we found that Agapetus traveled farther as availability of smooth habitat (composed of low diatom turfs) increased compared to tall, structured filamentous stands, but only did so in slow current velocities. Swifter flows caused restricted movement of Agapetus and more upstream‐oriented paths, but only in smooth landscapes where the potential for flow refugia from filamentous stands was minimal. Similarly, increasing proportions of smooth habitat facilitated greater net displacement of Physa using more upstream‐oriented paths. Higher current velocities caused Physa to move faster, a pattern demonstrated only in smooth landscapes. Our results illustrate a strong interaction between benthic habitat structure and current velocity in shaping patterns of grazer movements in a streambed landscape. Our study also suggests that the flow of water be considered not only a strong environmental gradient in streams, but also an interactive landscape feature that can combine with streambed structure to determine the permeability of patches to the movement of benthic organisms. Landscape ecology has mainly focused on terrestrial environments, and this study offers insight into some of the unique processes that may shape animal movement in aquatic environments.
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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 | 0.000 |
| 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 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".