Evidence map›Paper›PMID 33670998›Full record

ArticlePlants (Basel, Switzerland)2021

Assessing the Impact of Climate Change on the Distribution of Lime (16srii-B) and Alfalfa (16srii-D) Phytoplasma Disease Using MaxEnt.

Amna M Al Ruheili, Alaba Boluwade, Ali M Al Subhi

Open access · goldAbstract read
In one paragraph

Article in Plants (Basel, Switzerland), 2021. 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
3.1field-weighted citation impact, top 9% of its field
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, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Prediction of Suitable Habitat Distribution ofJournal of fungi (Basel, Switzerland) · 2023
    Article
  5. Prediction of the Potential Distributions ofJournal of fungi (Basel, Switzerland) · 2023
    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

3 authors at 1 institution in 1 country.

Amna M Al RuheiliDepartment of Plant Science, College of Agriculture and Marine Science, Sultan Qaboos University, Muscat 123, Oman.ORCID 0000-0003-3611-0423
Alaba BoluwadeDepartment of Soil, Water and Agricultural Engineering, College of Agriculture and Marine Science, Sultan Qaboos University, Muscat 123, Oman.
Ali M Al SubhiDepartment of Plant Science, College of Agriculture and Marine Science, Sultan Qaboos University, Muscat 123, Oman.ORCID 0000-0001-6687-1069
Sultan Qaboos University · OM

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Witches' broom disease has led to major losses in lime and alfalfa production in Oman. This paper identifies bioclimatic variables that contribute to the prediction of distribution of witches' broom disease in current and future climatic scenarios. It also explores the expansion, reduction, or shift in the climatic niche of the distribution of the disease across the different geographical areas of the entire country (309,501 km²). The maximum entropy model (MaxEnt) and geographical information system were used to investigate the potential suitability of habitats for the phytoplasma disease. This study used current (1970-2000) and future projected climatic scenarios (2021-2040, 2041-2060, 2061-2080, and 2081-2100) to model the distribution of phytoplasma for lime trees and alfalfa in Oman. Bioclimatic variables were downloaded from WorldClim with ± 60 occurrence points for lime trees and alfalfa. The area under the curve (AUC) was used to evaluate the model's performance. Quantitatively, the results showed that the mean of the AUC values for lime (16SrII-B) and alfalfa (16SrII-D) future distribution for the periods of 2021-2040, 2041-2060, 2061-2080, and 2081-2100 were rated as "excellent", with the values for the specified time periods being 0.859, 0.900, 0.931, and 0.913 for 16SrII-B; and 0.826, 0.837, 08.58, and 0.894 for 16SrII-D respectively. In addition, this study identified the hotspots and proportions of the areas that are vulnerable under the projected climate-change scenarios. The area of current (2021-2040) highly suitable distribution within the entire country for 16SrII-D was 19474.2 km

Indexed as

bioclimatic variablesdistribution modelfuture projectionwitches’ broom disease

Identifiers

PMID33670998
PMCPMC7997136
OpenAlexW3134430160

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.