Evidence map›Paper›PMID 36528656›Full record

ArticleScientific reports2022

Predicting potential global distribution and risk regions for potato cyst nematodes (Globodera rostochiensis and Globodera pallida).

Yitong He, Rui Wang, Honghai Zhao, Yonglin Ren, Manjree Agarwal, Dan Zheng, Shan Gao, Simon J McKirdy, Dong Chu

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. The role ofFrontiers in microbiology · 2024
    Review
  4. 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

9 authors.

Yitong HeShandong Engineering Research Centre for Environment-Friendly Agricultural Pest Management, College of Plant Health and Medicine, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China. hoyt.he@murdoch.edu.au.
Rui WangState Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China.
Honghai ZhaoShandong Engineering Research Centre for Environment-Friendly Agricultural Pest Management, College of Plant Health and Medicine, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China.
Yonglin RenHarry Butler Institute, Murdoch University, Perth, WA, 6150, Australia.
Manjree AgarwalHarry Butler Institute, Murdoch University, Perth, WA, 6150, Australia.
Dan ZhengCollege of Economics, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China.
Shan GaoHebei Dahaituo National Nature Reserve Management Centre, Chicheng, 075500, People's Republic of China.
Simon J McKirdyHarry Butler Institute, Murdoch University, Perth, WA, 6150, Australia. s.mckirdy@murdoch.edu.au.
Dong ChuShandong Engineering Research Centre for Environment-Friendly Agricultural Pest Management, College of Plant Health and Medicine, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China. chinachudong@qau.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Potato cyst nematodes (PCNs), golden (yellow) cyst nematode (Globodera rostochiensis, gPCN) and pale (white) cyst nematode (G. pallida, pPCN), are important invasive pests in many countries and regions where they can cause significant yield and economic loss for agriculture. Prediction and identification of habitats suitable for PCNs are critical for developing biosecurity strategies, both pre and post border, to maximise the potential for early elimination should an incursion occur. To date, the potential global distribution of PCNs has not been thoroughly studied. Therefore, this study conducted a species distribution model to illustrate the potential global distribution of PCNs and risk regions. In this study, the Maximum Entropy Model (Maxent) associated with the Geographic Information System (GIS) was employed to reveal the potential distribution of the gPCN and pPCN. In addition to bioclimate, soil quality was also included in the model. The global cultivated lands, whether the susceptible hosts were present or not, were used to assess the maximum potential risk regions. The limitation factors for PCNs distribution were also assessed. Results showed that 66% of the global land surface was suitable for gPCN or pPCN or both, and both species can colonise more than 75% of the global cultivated lands. The coldest quarter's mean temperature and precipitation were critical limitations in unsuitable regions. In summary, the global risk maps of PCNs contribute valuable additional information that complements previous national/regional distribution predictions. The results of this distribution research will contribute practical support for decision-makers and practitioners to implement biosecurity strategies from a global perspective, that incorporate prevention or promptly enforce control practices to limit the damage caused by future incursions.

Indexed as

Solanum tuberosumTylenchoideaAgricultureAnimalsSoilSoil

Identifiers

PMID36528656
PMCPMC9759053

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Registered trials

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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.