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Record W4389740921 · doi:10.1186/s13750-023-00320-3

Collating existing evidence on cumulative impacts of invasive plant species in riparian ecosystems of British Columbia, Canada: a systematic map protocol

2023· article· en· W4389740921 on OpenAlexafffundabout
Fabio Mologni, Chandra E. Moffat, Jason Pither

Bibliographic record

VenueEnvironmental Evidence · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsAgriculture and Agri-Food CanadaOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersMinistry of Forests, Lands and Natural Resource Operations
KeywordsRiparian zoneEcosystemGeographyEnvironmental resource managementForestryEnvironmental scienceEcologyBiologyHabitat

Abstract

fetched live from OpenAlex

BACKGROUND: Globally, 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 impacts have long been studied within other environmental contexts, research on the cumulative impacts of invasive species is comparatively scarce. We aim to develop a protocol to systematically identify and collate evidence on the individual and cumulative impacts of a set of plant species invasive in foreshore and riparian ecosystems of British Columbia, Canada. Our primary question is: what evidence is available on the individual and cumulative impacts of invasive plants in the riparian and foreshore ecosystems of British Columbia, Canada? In addition, 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. METHODS: We 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 species that 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 its environmental impacts and (iii) investigate such impacts in riparian ecosystems (iv) within North America (i.e. Canada and U.S.A.). We will use a two-stage screening process: titles and abstracts first, then the full manuscript. From each source, we will extract 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.

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)0.054
metaresearch head score (Gemma)0.093
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.693
Threshold uncertainty score0.610

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0540.093
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0480.027
Science and technology studies0.0060.004
Scholarly communication0.0050.003
Open science0.0040.007
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0240.003

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 head0.042
GPT teacher head0.263
Teacher spread0.221 · 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 designSystematic review
Domainnot available
GenreProtocol

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

Citations4
Published2023
Admission routes3
Has abstractyes

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