Food System Resilience Under Compound Shocks (2025)

Metric	Description	Example Indicator
Diversity	Variety of food system elements serving similar purpose	# of crop types, supply chain actors[3][4]
Redundancy	Multiple elements serving the same function	# of alternative suppliers/routes[3][4][5]
Connectivity	Degree of system interlinkage and communication	Network centrality, info sharing[3][4][5]
Capital Reserves	Backup resources for shock absorption	Stockpiles, reserve funds[3][4][5]
Flexibility	Ability to modify operations during disruption	Policy waivers, alternative sourcing[3][4][5]
Recovery Elasticity	Speed and completeness of post-shock recovery	% recovery per time unit[5][7]
Equity (Procedural, Distributional, Structural, Intergenerational)	Fairness and inclusion in resilience planning and outcomes	Resource allocation to vulnerable groups[4]

Component	Ex Ante Status	Shock/Stress	Resilience Capacity	Ex Post Status
Agro-ecological	Soil health, rainfall	Drought, flood	Diversity, capital reserves	Yield, land use[5]
Producers	Farm size, input access	Conflict, labor shortage	Flexibility, equity	Production, income[5]
Processors/Supply Chains	Capacity, tech adoption	Disruption, disease	Redundancy, connectivity	Throughput, loss rates[5]
Markets	Access, diversity	Trade ban, price shock	Flexibility, reserves	Price stability, access[5]
Infrastructure	Storage, transport	Destruction, breakdown	Redundancy, capital	Disruption duration[5]

Metric	Definition	2025 Example Value
Vulnerability Concentration	% of output in top 3 nodes	60% (global wheat exports)[5][7]
Redundancy Index	# of alternative trade routes/suppliers	2-4 (major grains)[5][7]
Recovery Elasticity	% recovery per month post-shock	10-25% (empirical range)[5][7]
Absorptive Capacity	% output maintained during shock	70-90% (high redundancy systems)[5]
Compound Risk Score	Prob.-weighted loss over scenarios	Varies by system, scenario[5][7]

Indicator	Score (0-5)	Best Practice
Diversity of food sources	3	5 = high crop/livestock diversity[3]
Redundancy in supply chains	2	5 = multiple backup suppliers/routes[3]
Connectivity/coordination	2	5 = real-time info sharing[3]
Capital reserves	2	5 = strong stocks/funds[3]
Preparedness plans	3	5 = integrated, tested[3]
Equity in resilience	2	5 = inclusive, just[4]

Few standardized, system-wide resilience metrics; most focus on farm/local scale[5][8]
Limited integration of compound risk (climate, conflict, disease) in most models[5][7][8]
Need for network-based, simulation-driven dashboards for policy and investment[3][4][5][12]
Participatory metric development with policymakers, industry, and communities[4][5][12]

Data: FAO, UNDRR, Food Systems Dashboard, GAIN, FABLE, Rockefeller Foundation, peer-reviewed literature[1][2][3][4][5][6][7][8][12].

Resilience Metrics for Food Systems Under Compound Shocks Dashboard

Core Metrics and Structure

Diversity: Measures the range of crops, suppliers, or actors in the system. More diversity means less risk if a single crop or supplier fails.
Redundancy: Tracks the number of alternative pathways (e.g., backup suppliers, routes) available. High redundancy allows the system to reroute or substitute if one part is disrupted.
Connectivity: Assesses how well different parts of the food system are linked and able to communicate. Strong connectivity supports rapid adaptation and coordination.
Capital reserves: Refers to backup resources (stockpiles, funds) that can be used during crises.
Flexibility: The system’s ability to change operations, such as switching suppliers or crops, when faced with disruption.
Recovery elasticity: How quickly and fully the system can recover after a shock.
Equity: Ensures that resilience strategies are fair and inclusive, considering vulnerable groups.

Frameworks and Indices

The Food System Resilience Index (FSRI) breaks down resilience across the food chain: agro-ecological base, producers, processors/supply chains, markets, and infrastructure. Each component is assessed for its pre-shock status, the types of shocks it faces, its resilience capacity, and post-shock outcomes.
Compound Shock Simulation uses network models and Monte Carlo methods to estimate how the system performs under multiple simultaneous shocks. Metrics like vulnerability concentration (how much is at risk if a few nodes fail), redundancy index, recovery elasticity, and absorptive capacity are visualized.
The Scorecard rates key attributes (diversity, redundancy, connectivity, capital, preparedness, equity) on a 0-5 scale, highlighting strengths and gaps.