Towards a better understanding of the relationships between pollinators, human well‐being, and medicine plants in the Great Lakes Region of Eastern North America
Bibliographic record
Abstract
Societal Impact Statement A diversity of values is needed to maximize the effectiveness of conservation planning, including policies and programs. The results of the United Nations Biodiversity Conference (COP 15) in Montreal, Canada, highlight the importance of a shift towards recognizing multiple ways of knowing in ecology and conservation. This review aims to provide a baseline of what is known about culturally significant plants in the Great Lakes Region of Eastern North America. The results of this research provide insight into the ways in which ecology has been conducted in the past and the importance of changing the way ecology is conducted in the future. Summary Biocultural conservation theory allows for an examination of complex problems using systems thinking and conserving biological and cultural diversity together. In the Great Lakes Region of Eastern North America, wild medicine plants are an important part of what Anishinaabe people understand as Mini bimaadizi, or the good life, and of aki miijim, or traditional food systems. Given the various threats facing wild plant populations and continued global change, this review aims to investigate what is known about the pollination and breeding systems of culturally significant plants in the Great Lakes Region. The overall goal is to determine what proportion of these plants have had basic ecological studies done and the degree to which culturally significant plants in this region rely on insect pollination. A systematic review of the literature was conducted on breeding systems and pollination of culturally significant plants. Half of all the culturally significant plants included lacked specific information related to reproduction. Most plants that have been studied relied on outcrossing, and the most commonly reported pollinators were in the Apidae family. With the complex interactions between plants and pollinators and many insect pollinators experiencing population declines, it is important to determine the dependence of culturally significant plants on animal pollination. These findings will be relevant to conservation planning and policy in the future.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".