MétaCan
Menu
← Back to cohort
Record W2893637083 · doi:10.1139/cjfas-2018-0098

An introduced plant is associated with declines in terrestrial arthropods, but no change in stream invertebrates

2018· article· en· W2893637083 on OpenAlexvenueno aff
Hannah L. Riedl, William H. Clements, Liba Pejchar

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric Administration
KeywordsRiparian zoneTerrestrial plantEcologyTerrestrial ecosystemForbVegetation (pathology)InvertebrateSpecies richnessBiomass (ecology)Food webBiologyEcosystemArthropodEnvironmental scienceGrasslandHabitat

Abstract

fetched live from OpenAlex

Riverine systems often spread non-native species, yet the co-occurring impacts of introduced riparian vegetation on aquatic- and terrestrial-derived resources are unknown. We compared aquatic and terrestrial arthropod communities and their flux into and out of streams in riparian reaches invaded and uninvaded by Robinia neomexicana, a woody plant introduced to a western Colorado watershed. We found that invaded reaches had fewer terrestrial arthropods collected off foliage, conceivably because of the plant’s later leaf-out phenology. Overall, seasonal and annual factors best described terrestrial and aquatic arthropod communities. However, when we evaluated vegetation and stream characteristics in lieu of season and year, we found terrestrial arthropod biomass and richness were negatively related to cover of R. neomexicana and positively related to vegetative cover, forb cover, and vertical vegetation structure. Our results suggest ecosystems respond to landscape variation differently, where directly related food web components (i.e., terrestrial arthropods on introduced vegetation) respond stronger than more distally related constituents (i.e., aquatic insects).

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)0.000
metaresearch head score (Gemma)0.000
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.225
Teacher spread0.205 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicFire effects on ecosystems→French-language works237,207→