Evidence map›Paper›PMID 42188192›Full record

ArticleInsects2026

Comparative Operational Performance of Baited Logs, Lure Traps, and Flight-Intercept Traps in a Province-Scale Surveillance Program for Pine Wood-Boring Beetles in Yunnan, Southwestern China.

Jidong Liu, Qi Jiang, Shaoshun He, Zhengqing Wu, Jianrong Wu, Taoyou Ping, Yujie Liu

Abstract read
In one paragraph

Article in Insects, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jidong LiuPest Research Center, Yinglin Branch, Yunnan Institute of Forest Inventory and Planning, Kunming 650032, China.
Qi JiangPest Research Center, Yinglin Branch, Yunnan Institute of Forest Inventory and Planning, Kunming 650032, China.ORCID 0000-0003-3907-0885
Shaoshun HePest Research Center, Yinglin Branch, Yunnan Institute of Forest Inventory and Planning, Kunming 650032, China.
Zhengqing WuLinxiang District Forestry and Grassland Pest Control and Quarantine Station, Lincang 677000, China.
Jianrong WuPest Research Center, Yinglin Branch, Yunnan Institute of Forest Inventory and Planning, Kunming 650032, China.
Taoyou PingPest Research Center, Yinglin Branch, Yunnan Institute of Forest Inventory and Planning, Kunming 650032, China.
Yujie LiuPest Research Center, Yinglin Branch, Yunnan Institute of Forest Inventory and Planning, Kunming 650032, China.

Funding

Yunnan Institute of Forest Inventory and Planning Key Technologies for Early Detection of Major Forest Pest Outbreaks in Yunnan ProvinceYunnan Province Science and Technology Department Key Technologies for Early Monitoring and Early-Warning of Major Forest Insect Disasters
6 · The paper itself

Abstract

National and provincial surveillance of pine wood-boring pests in China is designed to detect damaging taxa, map occurrence, assess risk and loss, and support early warning, zoning and control decisions. Province-scale comparisons of alternative monitoring devices remain rare, especially under the operational conditions required by such programs in climatically and topographically heterogeneous forests. Using data from the 2025-2026 systematic survey of pine wood-boring pests in Yunnan Province, China, we integrated several monitoring datasets to compare baited logs, lure traps, and flight-intercept traps. The harmonized database comprised 2603 standard monitoring subcompartments and 3519 installed sites, including 4080 baited-log piles, 4807 lure-trap units, and 373 flight-intercept traps. Main performance analyses focused on active sites with at least one collection event (570 baited-log sites, 63 flight-intercept sites, and 496 lure-trap sites), whereas installed site summaries were retained to characterize operational coverage. Because the study was observational and the three devices have different sampling mechanisms, we interpreted detection probability as the primary early warning metric, and catch, operational taxon richness, standardized yield, and cost metrics as supporting indicators of diagnostic and operational return. Site-level comparisons were complemented with paired analyses of 21 co-located subcompartments, a more comparable subset defined within county × elevation band × host group strata represented by all three methods, county-clustered regression, and a taxonomic-resolution sensitivity analysis. Lure traps consistently had the highest detection probability (0.73), the greatest cumulative catch (8617 individuals), and the broadest operational taxonomic coverage (45 operational taxa). In county-clustered models, lure traps had higher odds of detection (odds ratio = 11.25, 95% CI: 5.64-22.43) and higher catch rates (incidence rate ratio = 5.97, 95% CI: 2.26-15.76) than baited logs after adjustment for elevation band, host group, and collection effort. The same ranking persisted in the more comparable subset and after exclusion of unresolved family-, subfamily-, genus-, and unknown-level records. Standardized yield peaked at 1500-2200 m. Scenario-based costing showed that lure traps had the lowest cost per captured and resolved captured individual, whereas detection cost estimates were interpreted together with absolute detections and operational taxonomic output. Overall, the results support a tiered surveillance architecture in which lure traps serve as the primary routine early warning tool, baited logs provide targeted complementary information, and flight-intercept traps are reserved mainly for exploratory or faunistic surveys.

Indexed as

baited logsbroad-spectrum surveillanceflight-intercept trapslure trapspine wood-boring beetles

Identifiers

PMID42188192
PMCPMC13207129

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.