Biocontrol of Canada Thistle (<i>Cirsium arvense</i>) With the Rust Fungus, <i>Puccinia punctiformis</i> in the Intermountain West: Integrated Weed Management Compatibility and Characterization of Microbiome Associations
Bibliographic record
Abstract
Canada thistle (Cirsium arvense) is an invasive weed of major concern in both agricultural and native areas. It competes against native plants, reduces crop production and quality, and causes significant costs in management and damages. Canada thistle can survive and spread through seeds, but primarily does so through its extensive root system, which causes the greatest management difficulties. There are several control methods for this invasive weed, herbicides are perhaps the most common and effective, however, they have limitations and negative consequences. Herbicide use near waterways is restricted and there are growing concerns of the development of herbicide resistance. Biological control is an alternative method to herbicides, and the Canada thistle rust fungus (Puccinia punctiformis) is already naturally occurring with the plant and is highly host specific (i.e., it only infects the thistle). My dissertation aims to understand how the rust works within an integrated weed management (IWM) program, which combines multiple control methods, and to identify the microbial communities that live on and inside Canada thistle. The research explores how these microbes may affect the rust fungus’s effectiveness, and how we can use this knowledge to better control the weed. My second chapter includes two IWM experiments (Utah and Colorado) that were conducted to monitor ground coverage, Canada thistle stem density, and rust incidence during application of different control Canada thistle control methods. While I did observe that rust alone decreased thistle density, it was far less effective compared to herbicide treatments, and its impact when integrated with mowing or tillage varied. My third and fourth chapters show how the microbes associated with Canada thistle differed throughout two spore stages of the pathogen, in and on the plant, and between healthy and infected plants. I did this by characterizing the microbe communities and analyzing the microbe associations in these various states. Microbes of the leaf surface were more diverse than inside the plant. I also found that disease state (whether the plant was symptomatic or not) and time of year (early and late season) led to differences in microbe communities. Multiple microbes were identified as having significant associations with specific disease states and spore types. These associations could be exploited for control efforts, such as being selected for their relationship with the biocontrol agent and Canda thistle to increase biocontrol effectiveness. Further studies will enable us to determine how much these microbes will improve the rusts' effectiveness and what role it will continue to have in an IWM program for improved management of Canada thistle.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".