Spatial relationships between two <i>Agriotes</i> click‐beetle species and wireworms in agricultural fields
Bibliographic record
Abstract
Abstract 1 The production of new insect pheromones for pest monitoring proceeds at a greater rate than their evaluation, with the consequential possibility of premature introduction. Fundamental to their successful deployment is the determination of a consistent relationship between adult male pheromone trap catches and pest damage. In the present study, adult pheromone traps and larval bait traps were used to examine spatial relationships between two species of Agriotes beetle and wireworms at the field scale. 2 The spatial distributions of adult male Agriotes lineatus and Agriotes obscurus in two fields were determined and compared with the distribution of their larvae. Data were assembled as spatially referenced trap counts, and analysed for evidence of aggregation and clustering using Spatial Analysis by Distance IndicEs (SADIE) methodology. Spatial stabilities of adult populations between sampling dates were tested using association tests. Spatial and quantitative linkages between adult and larval trap catches were also tested. Moreover, a new way of adapting SADIE methodologies is presented for situations where two datasets within an area do not share the same sampling points. 3 There was no significant difference in variance : mean relationships for the two species but there were differences in their spatial distributions, and this is a definitive example of the general argument stating that it is important to consider spatial as well as count data in ecological studies. The spatial distribution of A. lineatus varied between sampling occasions at both sites whereas A. obscurus had consistently significant SADIE indices over time at one site, and adult catches could also be linked to larval distributions and counts. It is proposed that observed differences between the two species can be explained by interference between traps and dissimilar movement rates. There was some evidence of an edge effect at the field boundaries. 4 The distance between pheromone traps is related to the time that elapses before adjacent traps interfere with trap captures and this limits the detection of statistically significant spatial patterns. It is shown that the current practice of adding trap counts for different Agriotes species and treating them as numerically equivalent is insufficiently robust to be recommended at this stage. 5 The implications for the use of sex pheromone traps in wireworm pest management are considered. It is concluded that pheromone traps, as currently used, will not reliably indicate where wireworms occur in a field, and that the complexity of interpreting adult male trap counts limits quantitative predictions of population size.
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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".