Effects of landscape matrix on the distribution and dispersal of insects inhabiting the purple pitcher plant (Sarracenia purpurea)
Bibliographic record
Abstract
The examination of spatial scales of movement and the distribution of organisms is an important step towards understanding how landscape structure affects population dynamics. I asked if there was an effect of landscape matrix on the dispersal and distribution of two inhabitants of the pitcher plant, Sarracenia purpurea, the larvae of Wyeomyia smithii (a mosquito), and Metriocnemus knabi (a midge) by looking at how their larvae are distributed within bogs surrounded by forest, clear-cut, or scrub. I hypothesized that the distribution of insects would vary over a range of spatial scales and that their dispersal would vary with life history attributes. Sampling was conducted in western Newfoundland in six bogs surrounded by forest, scrub, or clear-cut. Defaunation of a 30-meter circle of pitcher plant leaves removed all larvae in the area. The location of each plant and larval incidence was mapped. I assessed the aggregation of mosquito and midge larvae relative to the position of plants across a continuous range of spatial scales using the K-function. Mosquitoes and midges varied with regard to the degree of clustering relative to the amount of aggregation of the plants, and displayed significant clustering at smaller spatial scales within individual bogs. These patterns were not significant between species or surrounding bog matrix. The locations of recolonized leaves were used to assess the dispersal of midges and mosquitoes. The mean and maximum distances from the edge of the defaunated areas were inconclusive between species and bog treatments. This experiment has theoretical applications for other animal populations, and potentially could be used for multi-scaled ecological studies.
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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 | 0.000 | 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 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".