Evidence map›Paper›PMID 41920844›Full record

ArticlePloS one2026

Analyzing the distribution patterns of soybeans and rapeseeds in china under future climate change scenarios utilizing the maxent model.

Yi Xiang, Zhibo Han, Shan Zhang, Feili Wei

Abstract read
In one paragraph

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

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0citing papers in PubMed
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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

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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

4 authors.

Yi XiangGuangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions, Guangxi Normal University, Guilin, China.
Zhibo HanGuangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions, Guangxi Normal University, Guilin, China.ORCID https://orcid.org/0000-0001-6024-2456
Shan ZhangGuangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions, Guangxi Normal University, Guilin, China.
Feili WeiGuangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions, Guangxi Normal University, Guilin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soybeans and oilseed rape are the main oil crops in China. Assessing the potential geographical distributions of soybean and oilseed rape in China under global warming trends can provide a scientific basis for agricultural production. In this study, 19 climate factors were used as environmental settings based on the MaxEnt model, and the dominant factors were screened and analyzed to predict the potential distributions of soybean and oilseed rape under three climate scenarios of shared socio-economic pathways (SSP) in simulated historical and future periods and to analyze the change trends. The main conclusions were as follows: (1) There are three predominant climatic factors affecting soybeans, among which the mean temperature during the warmest season and the precipitation in the wettest month are the most significant. For rapeseed, five factors are dominant, with annual precipitation and the mean temperature during the coldest season being the primary ones. (2) It is projected that in the next nearly 50 years, the highly suitable cultivation areas for soybean and rapeseed in China will increase by at least 137,000 km² compared to historical periods, representing an increase ranging from 0.14% to 9.33%. A northward shift of cultivation boundaries primarily characterizes this expansion, while most northwest inland areas will become unsuitable for cultivation. (3) In the intermediate stage of the 21st century under the SSP126 scenario, the potential suitable areas for soybeans and rapeseed will have the largest increases of 4.28% and 8.28% respectively, indicating that the planting effect will be the best during this period. The results indicate that future climate conditions will be more suitable for the growth of soybean and rapeseed. Cultivation area selection for soybean and oilseed rape in suitable eastern areas, the selection and breeding of good varieties, and yield improvement to obtain the maximum benefits should be considered.

Indexed as

Brassica rapaClimate ChangeGlycine maxModels, TheoreticalAgricultureChinaCrops, AgriculturalSeasonsTemperature

Identifiers

PMID41920844
PMCPMC13042770

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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.