GCRI · Food Nexus

Food trade and markets

Trade moves food from surplus to deficit regions and lets countries eat beyond what they grow. It also concentrates dependence: a few exporters supply most traded grain and vegetable oil, and much of it passes through a few straits, canals and ports. Prices carry shocks from world markets into local ones, unevenly. This page sets out how import dependence, market concentration, chokepoints and price transmission are measured, and who decides on the evidence.

01Register

Food trade and markets on the record.

02The question

Food trade and markets: how the risk develops.

Import concentration, prices and trade routes. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

Mechanism

Import dependence and concentration

Countries that import much of a staple from few suppliers are exposed to those suppliers’ harvests, policies and logistics. Concentration of both suppliers and routes compounds the exposure.

Mechanism

Chokepoints channel flows

Grain, oilseeds and fertiliser move through a limited set of straits, canals, rail corridors and ports. Closure, congestion or low water reroutes cargo, lengthens voyages and raises freight and insurance costs.

Mechanism

Export restrictions multiply

When prices spike, exporters may restrict sales to protect domestic consumers. Each restriction raises world prices further and encourages others to follow, so a supply shock becomes a policy shock.

Mechanism

Transmission is uneven

World price changes reach local markets through exchange rates, transport costs, tariffs, subsidies and market structure. Currency depreciation can raise import costs even while world prices fall.

03Geography

Growing conditions in the Black Sea region.

Crop greenness, night lights and population density over the Black Sea region, from NASA GIBS. Each layer carries its own date.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

Growing conditions, for this page

About this layer
Evidence
Observed (clouds leave gaps)
Source
MODIS Terra NDVI (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite index; clouds leave gaps
Newest at build
2026-10-13
Resolution
about 250 m grid
Uncertainty
Satellite greenness index over the 8 days to the date shown; an indicator of crop and pasture condition, not a yield estimate or a food security warning.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed
Source
VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
Provider
NASA LAADS DAAC
Licence
NASA open data
Vintage
daily; Satellite radiance, corrected for moonlight and atmosphere
Newest at build
2026-10-12
Resolution
about 500 m grid
Uncertainty
Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Estimated
Source
Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
Provider
NASA SEDAC (CIESIN, Columbia University)
Licence
CC BY 4.0
Vintage
null; Census-based estimate, static (2020)
Resolution
about 1 km grid
Uncertainty
Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Modelled
Source
SMAP Level 4 (NASA NSIDC DAAC)
Provider
NASA NSIDC DAAC
Licence
NASA open data
Vintage
daily; Model with satellite data assimilated
Newest at build
2026-10-11
Resolution
about 2 km grid
Uncertainty
Model with satellite data assimilated. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed
Source
VIIRS NOAA-20 corrected reflectance (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite image
Newest at build
2026-10-14
Resolution
about 250 m grid
Uncertainty
Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Modelled (latest year GIBS publishes)
Source
MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
Provider
NASA LP DAAC
Licence
NASA open data
Vintage
yearly; Satellite classification; latest year GIBS publishes
Newest at build
2024-01-01
Resolution
about 500 m grid
Uncertainty
Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

Loading the latest NASA imagery.

Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

Growing conditions, framed on the Black Sea region.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA JPL OPERA DIST-ALERTSources and licences

  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
  • SMAP Level 4 soil moisture and snow mass, NASA Global Modeling and Assimilation Office; distributed by the NASA National Snow and Ice Data Center DAAC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
  • Live: NASA EONET Events are indicative, not authority warnings.
  • Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • River discharge forecast, 30 days with range (GloFAS via Open-Meteo): Contains modified Copernicus Emergency Management Service information 2026; not a flood warning.
  • Past year, daily temperature (ERA5 via Open-Meteo): Contains modified Copernicus Climate Change Service information 2026.
  • Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
  • Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
  • Optional layers (13 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE · 13 Oct 2026
  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Root-zone soil moisture, 0 to 100 cm: SMAP Level 4, NASA NSIDC DAAC · 11 Oct 2026
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024

04Couplings

Markets transmit shocks from every domain into prices.

DomainHow it couples hereWhat to watch
EnergyOil and gas prices move freight, fertiliser and biofuel demand, and with them grain prices. See energy security.Correlation of energy and food price indices
WaterDrought in an exporting region tightens world supply.Production outlook in major exporters
HealthPrice spikes reduce dietary quality before they reduce calories.Cost of a healthy diet relative to income
BiodiversityTrade shifts land conversion to exporting regions.Land-use change embodied in imports

Puma and colleagues showed in 2015 that the global wheat and rice trade networks became more connected and more concentrated, which spreads small shocks but makes importers vulnerable to disruption in a few exporters. Export restrictions in 2022 were tracked in near real time by IFPRI’s export restrictions tracker.

05Simulator

A shock through an input-output economy.

A loss of output in one sector propagates through the technical coefficients to its suppliers and customers, and recovers at the rate you set; the coefficients are teaching values, not national accounts. Teaching model with stated illustrative values, not a prediction. The map on this page shows The Black Sea region; the model itself is not tied to a place.

Controls

Sector hit first (position in the list)
0
Size of the shock
30% of its output
Duration of the shock
30 days
Recovery rate
0.08 per day
Days simulated
180 days

Readouts

Output lost over the run
0.73% of a year’s output
Total over direct (multiplier)
1.87 times
Most affected other sector
Transport
Its peak inoperability
4.4%
Numbers, methods and sources
SectorPeak inoperability (%)Output weight (%)
Farming33.8614.4
Fertiliser and inputs0.2210.2
Food processing0.2118.5
Transport4.3622.7
Wholesale and retail2.1516.2
Energy1.0918.1

Methods

  1. Input-output analysis Leontief (1936); Miller and Blair (2009), Input-Output Analysis, Cambridge University Press
  2. Inoperability input-output model Haimes and Jiang (2001), Journal of Infrastructure Systems 7
  3. Dynamic inoperability and recovery Lian and Haimes (2006), Systems Engineering 9
  4. Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
  5. One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley

Data

The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:

  • Seaports Natural Earth
  • Maritime chokepoints Nexus (named straits and canals at their published coordinates)
  • Railways Natural Earth
  • Major roads Natural Earth
A shock through an input-output economy. Illustrative teaching model: it runs on the values set by the controls, not on measured data. Methods: Input-output analysis (Leontief (1936); Miller and Blair (2009), Input-Output Analysis, Cambridge University Press); Inoperability input-output model (Haimes and Jiang (2001), Journal of Infrastructure Systems 7); Dynamic inoperability and recovery (Lian and Haimes (2006), Systems Engineering 9).

Across the six pillars, led by Nexus Consortium

06Reports, standards and contributions

Market evidence and where it is published.

Trade and price transmission analyses are designed for the Strategic Systems series. The Global Centre for Risk and Innovation (GCRI) forecasts no prices and advises on no trades; market monitoring at global level is done by the Agricultural Market Information System. Price series would carry NS-3 identifiers under the proposed Nexus Standards. Local market price data and records of trade policy changes with dates are the contributions that help most.

07Twin and cascade simulator

Model food trade and markets as a system. Run the cascade.

Assembled from the Nexus Standards area profile Food security and nutrition risk: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.

Hazards

Controls

  • NS-0 Constitution and principles
  • NS-3 Risk record UNIs (grammar, legacy crosswalk, allocation authority)
  • NS-9 Contextual UNIs (deployments, instances, programme instances)
  • NS-10 Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NRS-H57 Hazard family: Humanitarian crises (NHS-1 soc.humanitarian)
  • NRS-H61 Hazard family: Cascading failure (NHS-1 sys.cascade)
  • NRS-H81 Hazard family: Malnutrition and micronutrient deficiency (NHS-1 health.nutrition)
  • NRS-H59 Hazard family: Economic shocks and governance failure (NHS-1 soc.economic)
  • NRS-N3 Food and agriculture risk and resilience
  • NRS-N7 Water-energy-food-health-biodiversity-infrastructure nexus coupling

Observation

  • IPC acute food insecurity analyses (listed for reference)
  • FEWS NET outlooks and data (listed for reference)
  • FAO GIEWS Food Price Monitoring and Analysis tool (listed for reference)
  • CHIRPS quasi-global gridded precipitation (listed for reference)
  • Prevalence of undernourishment
  • Prevalence of moderate or severe food insecurity
  • Prevalence of stunting among children under 5 years of age
  • Prevalence of malnutrition among children under 5 years of age

Example geography

  • The Ganges and Brahmaputra Basin: 178 hexagonal cells
  • Surface soil moisture (SMAP), NASA GIBS
  • Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
  • Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
  • Rain rate, last half hour (IMERG), NASA GIBS
08Indicators

What is measured, and how well.

Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.

IndicatorUnitCadenceSource typeLabel
Cereal import dependency ratiopercent of domestic supplyannualFood balance sheetsPublished statistics
Supplier concentration of staple importsHerfindahl-Hirschman indexannualBilateral trade statisticsESTIMATED
FAO Food Price Indexindex points against a base periodmonthlyInternational export quotationsPublished statistics
Indicator of food price anomalies (SDG 2.c.1)standardised anomaly classmonthlyDomestic market price monitoringPublished statistics
Stocks-to-use ratiopercent of annual usemonthlySupply and demand balancesESTIMATED
Export restrictions in forceshare of world calorie trade affectedweeklyPolicy trackersREPORTED
Dry bulk freight rateindex pointsdailyShipping market indicesOBSERVED
Food import bill against export earningsratioannualTrade and balance of payments statisticsPublished statistics
09Sector signature

The sector signature of food trade and markets.

The sectors food trade and markets touches and how strongly they depend on each other: what a study has to observe and model together.

Select corners · hover lines6 / 15 relations

Signature

Food and its partners

Food gives nutrition to health (0.7), land conversion to biodiversity (0.6) and withdrawals and runoff to water (0.3).

W · E · I · F · H · B

Sectors
4 of 6
Relations
6 of 15
Coupling
0.46 share of total

Strongest relations in play

  • Food → Biodiversity · land conversion0.6
  • Water → Food · irrigation0.8
  • Water → Biodiversity · environmental flows0.6
  • Food → Health · nutrition0.7
Teaching values for a typical city-region, not measurements for any place. Coupling is the summed strength of the relations in play, as a share of all fifteen.
10Sources

Where the evidence comes from.

Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.

SourceWhat it givesLicence class
UN ComtradeBilateral trade flows by commodity and partnerFree with registration, terms per UN
CEPII BACIReconciled bilateral trade flows at product levelOpen licence, attribution
AMIS Market Monitor (G20 Agricultural Market Information System)Supply, demand, stocks and policy for wheat, maize, rice and soybeansFree, attribution
FAO GIEWS Food Price Monitoring and Analysis toolDomestic retail and wholesale staple prices by marketFree and open, attribution
IFPRI Food and Fertilizer Export Restrictions TrackerExport bans and licensing requirements by country and productFree and open, attribution
FAOSTAT food balances and tradeSupply utilisation accounts and trade by commodityFree and open, attribution
IMF PortWatchPort calls and chokepoint transits from satellite vessel trackingFree, terms per IMF
11Methods and evidence

How food trade and markets is modelled, measured and tested.

The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.

System model

The couplings between the systems in food trade and markets: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.

++−++FoodTradeClimateCommunitiesEconomyR reinforcingB balancing
Causal loop diagram from the page’s systems; signs show the direction of influence. Illustrative structure for a system dynamics or network model, not estimated couplings.
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
12Decisions

Who decides, and what the evidence serves.

Food Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

Who decidesThe questionEvidence this page serves
Trade and agriculture ministriesWhether to diversify suppliers, adjust tariffs or negotiate long-term supply arrangementsSupplier concentration, route exposure and price transmission for each staple
Food reserve agencies and state importersWhen to buy forward and how large a buffer to hold against a route or exporter shockStocks-to-use, freight and lead-time scenarios including chokepoint closures
Central banks and finance ministriesHow a food price shock will pass into inflation and the balance of paymentsImport bill scenarios and pass-through estimates by commodity
WTO members and regional trade bodiesHow to discipline export restrictions and keep humanitarian food purchases exemptRestriction trackers and their estimated effect on world prices

Outputs this topic produces

  • Agrifood dependency maps by commodity, supplier and route
  • Chokepoint exposure profiles by importing country
  • Estimates of world-to-local price transmission with uncertainty
  • Trade policy shock scenarios
13Core questions

What experts ask.

Most countries rely on trade for at least part of their food, feed or fertiliser. For import-dependent countries, the resilience of their food system is decided partly abroad: in the harvests of exporting regions, the policies of their governments and the security of shipping routes. Understanding that exposure is a precondition for sensible reserve, sourcing and trade policy.

  • How concentrated are a country’s imports of staples, fertiliser and feed, by supplier and by route?
  • How do export restrictions, freight costs and exchange rates move domestic prices?
  • What role do public and private stocks play in damping price spikes, and what are their costs?
  • How do speculation, information gaps and policy announcements affect price volatility?
14Mechanisms

Drivers and processes.

Markets transmit shocks across borders, and policy responses can amplify them.

Concentration

Few suppliers and routes

Dependence on one exporter or one corridor raises exposure to weather, conflict or policy in that place.

Policy

Export restrictions

When several exporters restrict sales at once, world prices can rise sharply even if global supply is adequate.

Macroeconomy

Currency and finance

Depreciation raises import costs; limited foreign exchange can delay purchases and payment.

15Methods and data

How the evidence is built, and its limits.

  1. 01

    Trade statistics

    Customs and trade databases show flows and partners. They can be delayed, revised or inconsistent between reporters.

  2. 02

    Price data

    World and national price series show transmission; local market coverage is uneven.

  3. 03

    Network analysis

    Trade network models reveal concentration and potential cascades, but depend on assumptions about substitution.

  4. 04

    Econometric models

    Built with econometrics, they estimate price transmission and the effects of policy, with results that vary by period and market.

16Methods

How it is studied, and what the methods cannot say.

  1. EconometricsPrice transmission and market integration · Effects of trade policyApplied here
  2. Optimisation and operations researchHumanitarian supply and prepositioning · Strategic reserve designApplied here
  3. Forecasting and time-series analysisSeasonal production outlooks · Staple price forecasting · Anticipatory action triggersApplied here
  4. Spatial statistics and geostatisticsSmall-area estimation of food insecurity · Digital soil mappingApplied here
  5. Agricultural, soil and food scienceCrop simulation for seasonal yield risk · Yield gap and nutrient limitation analysisApplied here
18Questions

Questions and answers.

Does trade make countries more or less food secure?
Both. Trade gives deficit countries access to food and spreads weather risk across regions, but concentrated dependence exposes importers to supplier and route shocks. The balance depends on diversification, reserves and policy.
Why do export bans raise world prices?
They remove supply from world markets when it is already short, prompt importers to buy in haste and lead other exporters to restrict too. Studies of past price spikes find the cumulative effect substantial.
What is a stocks-to-use ratio?
Stocks held at the end of a marketing year relative to annual use. A lower ratio means a thinner buffer, and prices tend to react more sharply to new supply shocks.
Which chokepoints matter most for food?
Those carrying a large share of grain, oilseed and fertiliser trade, such as the Turkish Straits, the Suez Canal and Bab el-Mandeb, the Strait of Hormuz for fertiliser, the Panama Canal and major inland waterways. Their weight differs by commodity and importer.
Does Food Nexus give trading or investment advice?
No. It publishes research on market structure and exposure. It does not advise on commodity trading or investment.
Is trade a source of risk or of resilience?
Both. Trade diversifies supply against local harvest failure, but concentration in suppliers and routes creates exposure of its own.
Which commodities are covered?
Staple cereals, oilseeds, fertiliser and feed are the focus, with other commodities where they matter for food access.
Do food reserves prevent price spikes?
Reserves can dampen local price spikes and support emergency distribution, but they are costly to hold and manage. Their value depends on size, rules for release and coordination with trade policy.
ReportsContribute

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Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

GCRIFood NexusGlobal Sector Risk and ResilienceCountry Systems Risk and ResilienceEvidence Brief
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