MétaCan
Menu
Back to cohort
Record W4417186801 · doi:10.1051/kmae/2025025

Beyond pests: intermittent rivers as habitats for Thysanoptera and Scolytinae

2025· article· en· W4417186801 on OpenAlexaff
Zuzana Redžović, Lea Ružanović, Mladen Šimala, Fran Rebrina, Marina Vilenica, Boris Hrašovec, Andreja Brigić

Bibliographic record

VenueKnowledge and Management of Aquatic Ecosystems · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsCégep de Lévis
FundersHrvatska Zaklada za Znanost
KeywordsHabitatRiparian zoneBiological dispersalClimate changeEcosystemMediterranean climatePEST analysisBiodiversity

Abstract

fetched live from OpenAlex

Intermittent rivers are dynamic ecosystems increasingly affected by climate change which extends their dry phase and alters connectivity. Drying events create temporal dispersal corridors for terrestrial animals including pest taxa with potential agricultural and forestry impacts. We aimed to investigate dispersal of thrips (Thysanoptera) and bark (and ambrosia) beetles (Scolytinae) in the Mediterranean karst intermittent river Krčić, Croatia, during its dry phase by assessing spatiotemporal distribution across habitats, reaches and times of day as well as the wind effect on their activity density. Insects were sampled using cross-vane window traps in riparian and dry riverbed habitats at upper and lower reaches. Traps were emptied every 12 h over seven days in July 2021, with wind continuously monitored. Thysanoptera activity density was significantly higher in the upper reaches and during the day; light wind enhancing their dispersal, but they showed no clear habitat preference. Scolytinae preferred riparian habitat relative to the dry riverbed, likely due to differences in environmental conditions, such as temperature, light intensity and humidity. While these taxa are commonly studied in relation to their host plants, this study highlights their ecology, contributing to a better understanding of how prolonged dry periods in intermittent rivers affect biological communities.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.007
GPT teacher head0.243
Teacher spread0.236 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Explore more

Same venueKnowledge and Management of Aquatic EcosystemsSame topicForest Insect Ecology and ManagementFrench-language works237,207