ArticleNature food2020
Sources of uncertainty for wheat yield projections under future climate are site-specific.
Article in Nature food, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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.
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.
Who cites it
13 citing papers in PubMed.
- Spatially explicit temperature optima improve climate impact assessment of global crop productivity.Nature communications · 2026Article
- A conceptual framework for simultaneous optimization of integrated climate scenario data and phenology models.Agronomy for sustainable development · 2026Article
- Dynamical-generative downscaling of climate model ensembles.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Cost-effective adaptations increase rice production while reducing pollution under climate change.Nature food · 2025Article
- Pathways to identify and reduce uncertainties in agricultural climate impact assessments.Nature food · 2024Review
- Diversifying crop rotation increases food production, reduces net greenhouse gas emissions and improves soil health.Nature communications · 2024Article
- Microbial inoculants with higher capacity to colonize soils improved wheat drought tolerance.Microbial biotechnology · 2023Article
- Response of Wheat, Maize, and Rice to Changes in Temperature, Precipitation, COPlants (Basel, Switzerland) · 2023Review
- Mathematical optimization of frost resistant crop production to ensure food supply during a nuclear winter catastrophe.Scientific reports · 2023Article
- Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates.Nature communications · 2023Article
- Changes in per capita wheat production in China in the context of climate change and population growth.Food security · 2023Article
- Methodological evolution of potato yield prediction: a comprehensive review.Frontiers in plant science · 2023Review
- Multi-Model Ensemble Projections of Winter Extreme Temperature Events on the Chinese Mainland.International journal of environmental research and public health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
Understanding sources of uncertainty in climate-crop modelling is critical for informing adaptation strategies for cropping systems. An understanding of the major sources of uncertainty in yield change is needed to develop strategies to reduce the total uncertainty. Here, we simulated rain-fed wheat cropping at four representative locations in China and Australia using eight crop models, 32 global climate models (GCMs) and two climate downscaling methods, to investigate sources of uncertainty in yield response to climate change. We partitioned the total uncertainty into sources caused by GCMs, crop models, climate scenarios and the interactions between these three. Generally, the contributions to uncertainty were broadly similar in the two downscaling methods. The dominant source of uncertainty is GCMs in Australia, whereas in China it is crop models. This difference is largely due to uncertainty in GCM-projected future rainfall change across locations. Our findings highlight the site-specific sources of uncertainty, which should be one step towards understanding uncertainties for more robust climate-crop modelling.
Identifiers
37128032What OpenQuestion holds
Registered trials
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.