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GCRIFood NexusEstablished
Methods and uncertainty

Methods and uncertainty

The methods Food Nexus relies on, the assumptions they carry and the limits of what they can show.

Publisher
The Global Centre for Risk and Innovation
Field
Food and agriculture, Trade, resources and supply chains, Climate and hazards
Canvas · draft to published versionDesign, not a record
Methods and uncertainty: systematic evidence synthesisA question is framed with its owner and a protocol registered; records are searched, screened and checked for eligibility by two reviewers; data are extracted, synthesised and graded for certainty before a brief is written. Design of the process, not a record of a run.

Fig.How a finding is reviewed before it is published. Design, not a record.

01In brief

The short answer.

The Food Nexus methods page sets out the methods the platform relies on, among them agricultural, soil and food science, ecology and biodiversity science, and Earth observation and remote sensing, with their assumptions, validation and limits. Each analysis lists its assumptions and data, reports ranges and confidence beside central estimates, is checked against observations or other models, and states what it cannot show.

02Geography

Food systems and trade routes in Argentina.

Plains, deltas and basins, the corridors that carry food to ports, and how far each division sits from one, shown for Argentina as an example geography for this subject.

Plains, deltas and basins, the corridors that carry food to ports, and how far each division sits from one.Indicator derived from Natural Earth at map scale; a screening view, not an assessment.
GCRI · Food Nexus · fieldDESIGN FIGURE
03Methods

The methods in use.

  1. Agricultural, soil and food scienceCrop simulation for seasonal yield risk · Yield gap and nutrient limitation analysisApplied here
  2. Ecology and biodiversity sciencePollination and natural pest control · Fisheries and aquatic food websApplied here
  3. Earth observation and remote sensingCrop condition monitoring · Crop type and area mapping · Irrigation and water productivityApplied here
  4. Spatial statistics and geostatisticsSmall-area estimation of food insecurity · Digital soil mappingApplied here
  5. Forecasting and time-series analysisSeasonal production outlooks · Staple price forecasting · Anticipatory action triggersApplied here
  6. Optimization and operations researchHumanitarian supply and prepositioning · Strategic reserve designApplied here
  7. EconometricsPrice transmission and market integration · Effects of trade policyApplied here
  8. Hydrology and water scienceIrrigation supply and demand · Agricultural drought monitoring · Flood exposure of croplandApplied here
  9. Biotechnology platformsBreeding for stress tolerance · Rapid diagnostics for pests and diseaseApplied here
  10. Water and environmental engineeringIrrigation and drainage design · Safe wastewater reuse in agricultureApplied here
04Method register

Each method, its role in this field and how it is checked.

05Uncertainty

Where uncertainty in food system analysis comes from, and how it is shown.

SourceWhy it matters hereHow it is reported
Crop model structureModels diverge most under heat stress and in their response to carbon dioxideMulti-model ensembles following AgMIP protocols
Production statisticsSmallholder output and subsistence production are estimated, not measuredEvidence label on each figure; survey basis stated
StocksMany countries do not publish public or private stock levelsRanges and stated assumptions in stocks-to-use ratios
Price transmissionDepends on policy, exchange rates and market integration that change quicklyScenario sets rather than single elasticities
Household accessFood security outcomes rest on surveys with long gapsIPC consensus process and its confidence levels

An acute food insecurity figure is never shown without its classification system, the analysis period and whether it is a current estimate or a projection.

06Uncertainty

How uncertainty is reported.

  1. 01

    State assumptions

    Each analysis lists its assumptions and the data it depends on.

  2. 02

    Quantify where possible

    Ranges and confidence are reported alongside central estimates.

  3. 03

    Validate and compare

    Models are checked against observations and, where possible, against other models.

  4. 04

    Publish limits

    What an analysis cannot show is stated beside what it can.

07Key terms

Terms used on this page.

Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.

TermDefinition
Uncertainty quantificationCharacterising and propagating the uncertainties in a model to state confidence in its outputs.
Sensitivity analysisRepeating an analysis under different assumptions to show how much the result depends on them.
Model validationComparing model predictions with independent observations to judge fitness for a stated use.
Agricultural, soil and food scienceAgricultural science studies crop and livestock production, soil processes and food systems.
08Sources

Where this page's references lead.

The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.

09Questions

Questions and answers.

Are the methods open?
Method descriptions are public on the STEM Commons. Code and data follow their own licences and access terms, listed in the source register.
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