A system’s approach to assess the exposure of agricultural production to climate change and variability

Aavudai Anandhi,Nathaniel Bailey,Jean L Steiner

doi:10.1007/s10584-016-1636-y

Abstract

Estimating the exposure of agriculture to climate variability and change can help us understand key vulnerabilities and improve adaptive capacity, which is vital to secure and increase world food production to feed its growing population. A number of indices to estimate exposure are available in literature. However, testing or validating them is difficult and reveals a considerable variability, and no systematic methodology has been developed to guide users in selecting indices for particular applications. This need is addressed in this paper by developing a flowchart from a conceptual model that uses a system’s approach. Also, we compare five approaches to estimate exposure indices (EIs) to study the exposure of agriculture to climate variability and change: single stressor-mean climate, single stressor-extreme climate, multiple stressor-mean climate, multiple stressor-extreme climate; and combinations of the above approaches. The developed flowchart requires gathering information on the region of study, including its agriculture, stressor(s), climate factor(s) (CF), period of interest and the method of aggregation. The flowchart was applied to a case study in Kansas to better understand the five approaches to estimate EIs and the implications of the choices made in each step on the estimated the exposure. The flowchart provides options that guide EI estimation by selecting the most appropriate stressor(s), associated CF(s), and aggregation methods when a detailed methodological analysis is possible, or proposes a default method when data or resources do not allow a detailed analysis. Climate adaptation involves integration of a multitude of factors across complex systems. A more standardized approach to assessing exposure can promote information sharing across different locations and systems as this rapidly evolving area of study moves forward.

Highlights

The emerging consensus is that the world likely will exceed 9 billion people by 2050 and is unlikely to stabilize in the 21st century (Gerland et al 2014), requiring 70–100 % more food production (Tscharntke et al 2012)
The objectives of this study are to (1) compare five conventional approaches used to study the exposure of agriculture to climate change, (2) develop a systems approach to summarize in a flowchart the steps and the most relevant processes and information that should be taken into account to estimate the exposure of agriculture to climate change, and (3) present a case study to illustrate the implications of the choices made in the steps of the flowchart and the different approaches to estimate exposure indices (EIs)
The characteristics of the complex system are represented using indicator-based approaches calculated from climate stressors and climate factor(s) (CF)

Summary

Introduction

The emerging consensus is that the world likely will exceed 9 billion people by 2050 and is unlikely to stabilize in the 21st century (Gerland et al 2014), requiring 70–100 % more food production (Tscharntke et al 2012). Threats posed by climate variability and extremes to land and water resources are heightening the challenge of increasing food production (Horlings and Marsden 2011). In a recent Intergovernmental Panel for Climate Change report (IPCC-AR5), exposure is determined to be an important precondition for considering a specific vulnerability as key. This is because if a system is not at present nor in the future exposed to hazardous climatic trends or events, its vulnerability to such hazards is not relevant (Oppenheimer et al 2014). Estimating the exposure of agriculture to climate change will help us understand a region’s key vulnerabilities and improve its adaptive capacity, which is important for increasing food production to meet growing world demand

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