Beetle and Plant Density As Cues Initiating Disperal In Two Species of Adult Predaceous Diving Beetles
Bibliographic record
Abstract
Dispersal can influence population dynamics, species distributions, and community assembly, but few studies have attempted to determine the factors that affect dispersal of insects in natural populations. Consequently, little is known about how proximate factors affect the dispersal behavior of individuals or populations, or how an organism’s behavior may change in light of such factors. Adult predaceous diving beetles are active dispersers and are important predators in isolated aquatic habitats. We conducted interrelated studies to determine how several factors affected dispersal in two common pond-inhabiting species in southern Alberta, Canada: Graphoderus occidentalis and Rhantus sericans. Specifically, we (1) experimentally tested the effect of plant and beetle densities on dispersal probabilities in ponds; (2) surveyed ponds and determined the relationships among beetle densities and plant densities and water depth; and (3) conducted laboratory trials to determine how beetle behavior changed in response to variation in plant densities, conspecific densities, food, and water depth. Our field experiment determined that both species exhibited density dependence, with higher beetle densities leading to higher dispersal probabilities. Low plant density also appeared to increase beetle dispersal. Consistent with our experimental results, densities of R. sericans in ponds were significantly related to plant density and varied also with water depth; G. occidentalis densities did not vary with either factor. In the laboratory, behavior varied with plant density only for R. sericans, which swam at low density but were sedentary at high density. Both species responded to depth, with high beetle densities eliciting beetles to spend more time in deeper water. The presence of food caused opposite responses for G. occidentalis between experiments. Behavioral changes in response to patch-level heterogeneity likely influence dispersal in natural populations and are expected to be important for observed patterns of individuals in nature.
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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) | 0.000 | 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".