SILPHID AND CARABID BEETLES IN AN EXPERIMENTAL FOREST TRIAL: iDNA AND DIETS, AND INSECT-HUMAN RELATIONSHIPS CAN BETTER INFORM FOREST MANAGEMENT
Bibliographic record
Abstract
Insect conservation, primarily focused on pollinators, is a growing issue amid concerns of climate change and the purported sixth mass extinction of Earth’s biodiversity. However, the focus on charismatic pollinators ignores a large portion of ecologically important and beneficial species. Having broader knowledge of insect diets and the impacts of anthropogenic disturbance on diets can better inform more comprehensive management approaches while also providing valuable knowledge with regards to trophic relationships between multiple species within ecosystems. This ensures the health and stability of ecosystems beyond pollination services. This research started by establishing the utility of Silphid beetles for invertebrate DNA (iDNA) studies using both Sanger and high-throughput Illumina sequencing methods. Subsequently, iDNA techniques were applied to assess population and diet responses of live-trapped Silphid and Carabid beetles to the Northern Hardwood Silviculture Experiment to Enhance Diversity (NH-SEED) in Alberta, Michigan. Silphid trapping revealed preferences for treatments with higher canopy, while light traps and pitfall traps indicated diet data at different developmental stages. Carabid trapping showed increasing diversity in recently harvested sites and changing community structure reflective of similar studies. Genetic analysis of the primary Carabid species collected, Pterostichus melanarius, indicated diet differences based on seasonality and silvicultural treatment, aligning with expected community responses, but providing novel information about earthworms in diets in forest systems, instead of agricultural systems. The final objective explored human-insect relationships, incorporating historical perspectives, art, storytelling, and engagement with Indigenous Knowledge Holders, advocating for a more holistic approach to insect conservation that respects and is inclusive of Indigenous communities. The results of these studies contribute to a broader understanding of anthropogenic disturbance and can influence how we approach insect conservation. By shifting the focus beyond pollinators and incorporating a more comprehensive understanding of diets and trophic relationships, conservation efforts can better address the complexities of ecosystem health and stability. Additionally, the consideration of diverse perspectives, including Indigenous knowledge, advocates for a more inclusive approach to conservation practices.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".