Cumulative impacts of invasive plant species in British Columbia’s riparian ecosystems: a systematic map protocol
Bibliographic record
Abstract
BackgroundGlobally, the structure and functioning of foreshore and riparian ecosystems are being dramatically impacted by non-native invasive plant species. Invasive species can outcompete and replace native species, modify geochemical and hydraulic cycles, alter trophic processes and change the composition and structure of communities above and below ground. However, these impacts are often investigated in isolation, even though one invasive species might increase or mitigate the impacts of others (i.e. cumulative impacts), potentially with cascading effects. Although cumulative impactshave long been studied within other environmental contexts, research on the cumulative impacts of invasive species is comparatively scarce. We aim to (1) develop a protocol for systematically assessing the cumulative impacts of invasive species and(2) conduct a test of this protocol using a suite of non-native plants that are invasive in foreshore and riparian ecosystems of British Columbia, Canada. The protocol itself aims to standardize future evaluations of the cumulative impacts of invasive species. Inaddition, our systematic map will identify the strengths and gaps in knowledge pertaining to invasive plant species impacts in foreshore and riparian ecosystems, with the ultimate goal of facilitating the development of evidence-based management strategies.MethodsWe identified the research topic and the primary and secondary questions with the support of stakeholders. We then devised a flexible string that allows for searching target invasive species. Using this string, we searched the literature for pilot speciesthat aided the iterative development of the protocol. Once all target species are identified, we will carry out a systematic literature search on their impacts. We will search Web of Science and the CABI compendium for invasive species. We will include studies if they (i) refer to the target invasive species, (ii) focus on itsenvironmental impacts and (iii) investigate such impacts in riparian ecosystems (iv) within North America (i.e. Canada & U.S.A.). We will use a two-stage screening process: titles and abstracts first, then the full manuscript. From each source, we willextract impact description, ecosystem component impacted, and magnitude and directionality of impacts. We will include a publicly available database of studies, descriptive statistics and a narrative summary within our synthesis outcomes.
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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 | 0.043 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.023 | 0.014 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.004 |
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".