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Record W7106016984 · doi:10.7939/83110

Plenty of flowers in the field: the roles of resource availability and habitat type in the conservation of flower-visiting insects

2025· dissertation· en· W7106016984 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2025
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsAbundance (ecology)HabitatTaxonPollinationResource (disambiguation)Variety (cybernetics)Metric (unit)

Abstract

fetched live from OpenAlex

The conservation of flower-visiting insects is a necessary and worthwhile endeavor given their critical role in the pollination of wildflowers and crops. A lack of flowers is often cited as one of the reasons for declines of important flower-visiting taxa such as bees, so conservation and restoration efforts often revolve around the planting of native wildflowers. Given the wide variety of native wildflowers available to choose from and the expense of sourcing local seed, selecting the most preferred (i.e., the most widely visited) flowers is of the utmost importance. Flower abundance obscures preference because neutral processes, which are thought to be an important determinant of flower-visitor interactions, suggest that an abundant flower is more likely by chance to receive a visit than a rare flower. Therefore, to control for flower abundance and remove the effect of neutral processes on the data, many researchers use preference metrics to select the most preferred flowers from flower visitation data. There are a wide variety of metrics to use, and when I compared five of them using the same flower visitation dataset, I found that they produced wildly different results. The contrasting results were likely due to the varying extent to which each metric controlled for flower abundance and how strongly each metric responded to undersampling. When I experimentally controlled for flower abundance using potted plants of the five most and five least preferred plants as calculated by each metric, I found that the metrics that least controlled for flower abundance best predicted flower visitation. Furthermore, I conducted the potted plant trials in two adjacent natural regions (Grassland and Parkland) and found that insect-flower preferences changed between them, likely due to the differences in the insect communities in each natural region. However, flower abundance in the original Grassland dataset predicted flower visitation better than any metric in both regions. Thus, abundant flowers were preferred by flower-visiting insects, but not because they were abundant, and the effect of neutral processes on flower-visitor data may be overestimated. Understanding how flower-visiting insect communities and flower-visitor interactions vary among already established flower communities and habitat types will help guide flower-visiting insect conservation efforts. In agricultural systems, mass-flowering crop bloom causes the amount of floral resources on the landscape changes dramatically throughout the flight period of many insect species, which can change how they interact with other flowers and how they move about agricultural fields. When I compared flower-visiting insect species composition and flower-visitor interactions within and in field borders adjacent to canola fields in central Alberta, I found that field border type (herbaceous or treed) ultimately drove flower-visiting insect and flower-visitor interaction diversity in agricultural systems. In fact, mass-flowering crop bloom generally had a negative effect on flower-visitor interactions as interactions decreased significantly during canola bloom compared to before or after. However, that result was not consistent in 2022 as it depended on border type. I also found that hoverflies, and particularly one species, Toxomerus marginatus, are integral insects in agricultural systems in central Alberta because they were common crop visitors, especially compared to wild bees which rarely visited canola. When I measured hoverfly movement into and out of canola crops using bi-directional Malaise traps set in the borders of canola fields, I found that field border type and not mass-flowering crop bloom affected hoverfly movement. Finally, from my Malaise trap sampling, I found new Alberta records for a hoverfly species (Platycheirus varipes), along with multiple rare species that were previously either of conservation concern, rarely found (< 15 records across their entire range), or only found via iNaturalist records. Overall, my thesis demonstrates that habitat type (through the comparison of natural regions and field border types respectively) matters more than the quantity of floral resources in shaping insect-flower visitation and insect communities. Flower-visiting insect conservation should focus on diversifying resources, even on a relatively small scale, to conserve the broadest number of species possible. Finally, I also demonstrated the prevalence and likely importance to ecosystem services of hoverflies in agricultural areas in central Alberta.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.014
GPT teacher head0.180
Teacher spread0.167 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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