Effect of landscape structure on the movement behaviour of a specialized goldenrod beetle, <i>Trirhabda borealis</i>
Bibliographic record
Abstract
We hypothesize that the ability of an organism to move through a landscape is determined by the interaction between its movement behaviour and the landscape structure. In contrast, models predicting spatial distribution, local population stability, or metapopulation stability typically assume that movement ability is independent of landscape structure. These model predictions will be invalid if the assumption of constant movement ability is incorrect. To assess the influence of landscape structure on movement behaviour (and therefore movement ability), we tracked individual goldenrod beetles (Trirhabda borealis) through microlandscapes composed of three patch types (goldenrod, cut vegetation, and cut vegetation containing camouflage netting to a height of 50 cm) that differed in terms of available food resources and structural complexity. In goldenrod patches, beetles moved infrequently in brief bursts of slow meandering movements. In cut patches, beetles moved frequently in sustained bursts of slow directed movements. In netting patches, beetles moved frequently in brief bursts of fast meandering movements. Using mark-release experiments, we determined that T. borealis did not detect goldenrod from afar or respond to edge type. Since T. borealis movement behaviour differed between patch types, its movement ability must depend on landscape structure. If this general result applies to other species, it implies that predictions of local population and metapopulation responses to landscape alteration could be erroneous. Effects of landscape alteration on movement behaviour should be incorporated into models of population response to landscape alteration.
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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) | 0.003 | 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".