Project highlights

  • The conceptual appeal for an early warning system to provide timely response to environmental disruption (e.g. extreme climate and weather events, radiation leaks, infectious diseases)
  • The characteristic of disruptive events, their emergence and potential consequences for food chain actors
  • A methodological toolkit for embedding early warning tools in decision processes, and the new capacity, skills, resources and behaviours needed for implementation in decision-making processes

Overview

Environmental shock events can be propagated along food supply chains by numerous social, economic, political and technological factors. Understanding the characteristics and consequences of environmental disruption is fundamental to reducing risks associated with periodic food shortages, price volatility and reductions in food quality and security (Davies et al., 2021). However, environmental shocks such as climate extremes, radiation leaks, infectious diseases and endocrine disruptive chemicals  can occur suddenly and are characterised by uncertainty in terms of the likelihood of the risk and their potential impact. These risks develop and change over time so need to be constantly monitored and assessed to interpret their impact on food supply chains.

Early warning systems (EWS) that combine forward-looking assessment tools and processes (e.g. horizon scanning, data mining, Delphi and trends and time series analysis) with traditional decision making tools (e.g. risk assessments) will deliver a more informed and integrated view of food supply chains and of systemic environmental risks and issues over the short to long-term (EFSA 2018, FSA 2017, FSS 2017). An early warning system is an integrated risk information (including perceptions of risks) and communication system that engages experts, policy makers, and increasingly citizens, in analysing and interpreting environmental change and its potential impacts on food chain actors (Pulwarty and Sivakumar, 2014).

There is general consensus that EWS are not meeting their current potential to provide decision-makers with timely information in a format that enables action (CIAT, 2014, Buchanan-Smith 2000). Historic failures to effectively repond to extreme climate events (e.g. floods, droughts) have been ascribed to failures in decision-making rather than deficiencies in EWS (Raymond et al. 2020, CIAT 2014). To support more timely action, there is a need to build early warning competencies for integrated monitoring of disruptive events, focusing on: (1) identifying the characteristics of these events, how they emerge and permeate across the food chain, and (2) what combination of methods allow for carrying out a comprehensive assessment of food chain vulnerabilities to environmental disruption. These fundamental questions will shape the research with the following specific objectives:

  1. Develop an evidence base of EWS tools and processes that have been effective in anticipating the development pathways and impacts of disruptors
  2. Identify environmental disruptors that present significant risks for food quality and safety and map the development pathways and impacts of these events
  3. Design a methodological toolkit for embedding EWS tools and processes in decision-making processes in a regulatory environment
  4. Evaluate how the toolkit supports early warning, examining what new capacity, skills, resources and behaviours are needed for implementation

 

CENTA Flagship

This is a CENTA Flagship Project

Case funding

This project is suitable for CASE funding

Host

Cranfield University

Theme

  • Climate and Environmental Sustainability
  • Organisms and Ecosystems

Supervisors

Project investigator

Dr Kenisha Garnett, Cranfield University ([email protected])

Co-investigators

How to apply

Methodology

To address the project objectives, the study methodology is developed in three phases.

Phase 1: Gathering intelligence from non-traditional sources. Build an evidence-base for early detection and monitoring capabilities by understanding the conceptual appeal for EWS and the trade-offs needed to enhance performance in a regulatory context.

Phase 2: Combine multiple tools to understand the systemic nature of emerging environmental risks and their consequences for food chain actors. Build a methodological ‘toolkit’ for integrating these tools in decision-making process, exploring the potential for near and real-time monitoring to deliver more comprehensive assessments of food chain vulnerabilities to environmental disruption across the short, medium and long-term planning horizon.

Phase 3: Embedding EWS tools in decision-making processes. Evaluate the ‘agency’ for adapting to change, focusing on how EWS competencies can be embedded into the ‘evidence-based’ culture of regulatory organisations to deliver new levels of capacity, skills, resources and behaviours that improve the evaluation and management of environmental disruption across the food chain.

Training and skills

The student will receive guidance and training to build EWs skills required for this project. This includes training through the postgraduate course curriculum at Cranfield, which will provide fundamental skills in forward-looking assessments (e.g. horizon scanning, data mining, Delphi and trends and time series analysis) and food chain surveillance (e.g. food diagnostics, food safety & quality). Cranfield’s PhD students become part of a vibrant Doctoral Network, which allows them to participate in seminars, lectures and receive core training in skills such as project management, data management and security, statistics, academic writing and communication.

Partners and collaboration

The project will be led by Cranfield. A dual internship is being discussed for the student, involving a primary placement at UK Food Standards Agency (9 mths) and a secondary one at Food Standards Scotland (3 mths), which will help the student gain familiarity with the UK regulatory environment. During placement the student will gain core skills in assessing food chain vulnerabilities, complex dependencies and cascading impacts associated with environmental disruption or sudden on-set risks that affects food supply chains. This will enable the student to gain real insights into how combined EWS and food chain surveillance work in practice, equipping them with data to evaluate what suite of EWS tools could be embedded in a regulatory organisation.

Further details

Dr Kenisha Garnett
Lecturer in Decision Science (Strategic Foresight)
Cranfield University,

School of Water, Energy and Environment

Centre for Environmental and Agricultural Informatics
Email: [email protected]
Tel: +44 (0)1234 754 292

https://www.cranfield.ac.uk/people/dr-kenisha-garnett-845215

Professor Paul Burgess

Professor of Sustainable Agriculture and Agroforestry

Cranfield Soil and Agrifood Institute

Cranfield University

E-mail: [email protected]

https://www.cranfield.ac.uk/people/dr-paul-burgess-784015

Dr Abdou Khouakhi

Lecturer in Remote Sensing
Cranfield University,

School of Water, Energy and Environment

Centre for Environmental and Agricultural Informatics
Email: [email protected]

https://www.cranfield.ac.uk/people/dr-abdou-khouakhi-26326359

Dr Greg Wasinski

Strategic Insights Team Lead

Science Evidence and Research Division

Food Standards Agency

[email protected]

 Dr Kasia Kazimierczak

Senior Scientific Advisor

Food Protection Science and Surveillance

Food Standards Scotland

[email protected]

To apply, please visit: https://www.cranfield.ac.uk/research/phd/an-early-warning-system-for-food-supply-chain

Possible timeline

Year 1

Conduct a review of academic and grey literature of EWS research and build an evidence-base (i.e. using a multi-case study approach) of EWS tools and processes, and the conceptual appeal as well as the trade-offs needed to enhance their use in a regulatory context. The student will pull together approximately 25 case studies for shallow analysis, leading to 5-8 cases for in-depth analysis, supported by key informant interviews with developers (e.g. researchers, consultants) and users of the tools (e.g. public sector organisations). This year will result is the student building a solid understanding of the capabilities of EWS tools and processes and the successes and challenges inherent in their use in evidence-based decision processes. Training and capacity building in EWS will be provided.

Year 2

The start of the second year will involve the student liaising with the regulatory body (sponsors) to understand requirements for early warning. This learning will be delivered through a planned programme of activities via a 12-months internship, where the student will be embedded in the organisation. The student will identify 2-3 food groups and value chains, particularly vulnerability to environmental disruption (e.g. climate extremes) to be used as case studies in exploring the potential for near and real-time monitoring to deliver more comprehensive assessments of food chain vulnerabilities to environmental disruption across the short to long-term planning horizons. Towards the end of the internship, the student will start to develop a methodological toolkit for integrating EWS tools into monitoring programmes at a regulatory body, potentially looking at its applicability to other context as well (e.g. corporate environment).

Year 3

During the first half of the final year, the student will develop the toolkit, testing elements of it with other potential users (e.g. government, business, academia). The focus will be on exploring how EWS competencies can be embedded into the ‘evidence-based’ culture of regulatory organisations to deliver new levels of capacity, skills, resources and behaviours that improve the evaluation and management of environmental disruption across the food chain. Testing will involve running a series of workshops and supplementary interviews to examine cultural barriers to the implementation of EWS. This could be complemented with ‘pilot experiements’ designed to test the application of the EWS tool through ‘real-world’ applications. The latter part of the year will involve writing up the thesis, which is intended to be presented in ‘manuscript’ form.

The student will be supported in presenting outputs of their research at suitable conferences and workshops throughout the 3-year programme as a key aspect of building confidence and a professional network.

Further reading

  1. Buchanan-Smith (2000). Role of early warning systems in decision-making processes. Expert Working Group on Early Warning Systems for Drought Preparedness and Drought Management. Hmanitarian Policy Group, Overseas Development Institute (ODI). Accessed on 27 Oct 2021: https://www.alnap.org/system/files/content/resource/files/main/4943.pdf
  2. CIAT (2014). Expanding the contribution of early warning to climate-resilient agricultural development in Africa. International Center for Tropical Agriculture (CIAT). CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), FCC/SBSTA/2014/L.14. Accessed on 27 October 2021: https://assets.publishing.service.gov.uk/media/57a0896ce5274a31e0000096/Expanding_the_Contribution_of_Early_Warning_to_Climate-Resilient_Agricultural.pdf
  3. Davis, K. F., Downs, S., Gephart, J. A. (2021). Towards food chain resilience to environmental shocks. Nature Food, 2: 54-56.
  4. EFSA (European Food Safety Authority), Donohoe T, Garnett K., et al., 2018. Scientific report on the emerging risks identification on food and feed – EFSA. EFSA Journal 16(7):5359, 37 pp. https://doi.org/10.2903/j.efsa.2018.5359
  5. FSA (Food Standards Agency) 2017. Developing our approach to identifying risks and issues across the food system. FSA Board Meeting, 21 June 2017. https://www.food.gov.uk/sites/default/files/media/document/fsa170606%20%281%29.pdf
  6. FSS (Food Standards Scotland) 2017. A Food Surveillance Strategy for Scotland. A model for the collection, recording, analysis and interpretation of information and intelligence relating to the safety and authenticity of the Scottish food chain. FSS Draft Strategy Document. https://consult.foodstandards.gov.scot/2013-food-protection-science-and-surveillance/a-food-surveillance-strategy-for-scotland/
  7. Pulwarty, R.S. and Sivakumar, M.V.K. (2014). Information systems in a changing climate: Early warnings and drought risk management. Weather and Climate Extremes, 3: 14-21.
  8. Raymond, C., Horton, R.M., Zscheischler, J., et al. (2020). Understanding and managing extreme events. Nature Climate Change, 10: 611-621.

COVID-19

This research is primarily desk-based so it is not forseen that COVID-19 restrictions will place an unduly significant burden on the research planned. A 12 months internship is planned for year 2 of the research programme (see timeline below), where government protocols around Covid-19 applies. The student will receive an induction to working on government premises including health and safety guidance as it relates to Covid-19.