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Record W7105994858 · doi:10.7939/83118

Patterns and mechanisms of plant invasions: cross-habitat insights from central Alberta

2025· dissertation· en· W7105994858 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2025
Typedissertation
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRuderal speciesHabitatSpecies richnessContext (archaeology)BiodiversityLandscape ecologyMarshRiparian zoneDisturbance (geology)

Abstract

fetched live from OpenAlex

Biological invasions are a leading cause of biodiversity loss and ecosystem change globally, with non-native vascular plants altering nutrient cycling, disturbance regimes, and community structure. Non-native plant invasions are increasingly acknowledged as context-dependent processes. Yet relatively few studies have disentangled patterns and mechanisms of invasions across habitat types, although habitat context has been suggested to be a key factor underlying invasion dynamics. Research on habitat context has relied either on observational surveys to describe levels of invasion or manipulative experiments to test for habitat invasibility. When combined, these contrasting approaches could help us understand whether these two metrics align. This thesis examined the role of habitat type in shaping invasion processes in the Central Parkland Natural Subregion of Alberta, and its interaction with propagule pressure, disturbance, and species identity. I tested hypotheses using field surveys and field experiments in a landscape defined by natural gradients and a legacy of agricultural and industrial land use. In Chapter 2, I quantified the relative richness and cover of agronomic and noxious species across seven habitat types. My research was the first to show that agronomic species – those intentionally introduced for forage and reclamation – can be a dominant component of the non-native flora, surpassing noxious weeds in both frequency and cover. Additionally, levels of invasion varied significantly by habitat type, with ruderal habitat showing the highest levels of invasion and saline marsh the lowest. In Chapter 3, I explored how habitat type interacts with environmental and anthropogenic predictors and species identity (agronomic vs. noxious) in shaping of non-native richness and cover. Habitat type, native plant cover, and proxies for propagule pressure (e.g. road length, amount of nearby cultivated land) emerged as significant predictors, although effects depended on species identity. Agronomic species were strongly associated with anthropogenic land use, while noxious species showed weaker and more variable responses, possibly due to their smaller frequency and abundance, and thus a higher stochasticity. In Chapter 4, I experimentally manipulated propagule pressure and soil disturbance across three habitat types to disentangle intrinsic habitat invasibility from realized levels of invasion. Germination increased with propagule pressure across all study species and habitats, but responses varied by habitat and species identity. Notably, prairie grassland showed strong invasion resistance despite exhibiting high levels of invasion in field surveys. Together, these findings highlight that plant invasions are shaped by complex, context-dependent interactions among habitat characteristics, human land use, and species identity. Overall, my thesis shows that land use legacies, disturbance and propagule pressure can override intrinsic resistance in habitat types, leading to high levels of invasion. A novel finding is that agronomic species represent a uniquely challenging threat: they are widespread, unregulated, and strongly linked to economic activity, yet ecologically disruptive. I argue for a shift toward habitat-specific management strategies that integrate species identity, landscape context, and socio-economic trade-offs. These should include limiting propagule pressure from agronomic species, promoting native vegetation recovery, and re-evaluating practices to balance ecological resilience with human land use. By emphasizing the role of context in non-native plant invasion dynamics, this thesis contributes to a more nuanced and practical understanding of plant invasions.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.050
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.175
Teacher spread0.169 · 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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