Evidence map›Paper›PMID 38786880›Full record

ArticleInsects2024

Which SDM Model, CLIMEX vs. MaxEnt, Best Forecasts

Umer Hayat, Juan Shi, Zhuojin Wu, Muhammad Rizwan, Muhammad Sajjad Haider

Abstract read
In one paragraph

Article in Insects, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. PredictingInsects · 2026
    Article
  3. Article
  4. Article
  5. Assessing the Potential Distribution ofEcology and evolution · 2025
    Article
  6. Article
  7. Article
  8. Article
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

5 authors.

Umer HayatSino-France Joint Laboratory for Invasive Forest Pests in Eurasia, Beijing Forestry University, Beijing 100083, China.ORCID 0000-0001-7830-8361
Juan ShiSino-France Joint Laboratory for Invasive Forest Pests in Eurasia, Beijing Forestry University, Beijing 100083, China.
Zhuojin WuSino-France Joint Laboratory for Invasive Forest Pests in Eurasia, Beijing Forestry University, Beijing 100083, China.
Muhammad RizwanDepartment of Plant Medicine (Entomology), College of Agriculture and Life Science, Kyungpook National University, Daegu 41566, Republic of Korea.
Muhammad Sajjad HaiderDepartment of Forestry, College of Agriculture, University of Sargodha, Sargodha 40100, Pakistan.ORCID 0000-0002-6060-0628

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A precise evaluation of the risk of establishing insect pests is essential for national plant protection organizations. This accuracy is crucial in negotiating international trade agreements for forestry-related commodities, which have the potential to carry pests and lead to unintended introductions in the importing countries. In our study, we employed both mechanistic and correlative niche models to assess and map the global patterns of potential establishment for

Indexed as

Aeolesthes sartaclimate changeCLIMEXinsect pestMaxEntpest risk analysisquarantine pestspecies distribution modeling

Identifiers

PMID38786880
PMCPMC11121915

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.