Sustainability And Resilience Demystified

Published on 4 March 2010 in Sustainability and Communities

Introduction

The terms sustainability and resilience occur frequently in science and policy documents and most people have an intuitive sense of what these terms mean in general when applied to agriculture, ecosystems, or rural livelihoods. In common with other terms that originate in science, and are subsequently used in wider spheres, such as in policy discussions or everyday life, the scientific meanings of sustainability and resilience have become augmented by a large, and often less well-defined, set of additional meanings and connotations. This accumulation of extra meanings and nuances is not necessarily a bad thing, but one of the results is that the everyday meanings of the terms contain ambiguities that lead to a reduction in their explanatory value. That is, the terms encompass so many possible interpretations that each use has to be qualified in order for it to be unambiguously understood. This makes their continued use as well-defined policy objectives ever more difficult. 

Key Points

Figure 1. Hypothetical example of dependence of sustainability on probability of system failure.

Sustainability:   The sustainability of a system is a measure of its lifespan. Sustainability can only be meaningfully defined relative to a known time interval (a fixed number of years, for example). In its simplest form sustainability is a binary property of a system: e.g. survives, does not survive. So, for example, suppose a given arable farm remains in business over a selected 10 year study period, the simplest measure of sustainability for that farm in that interval is “yes” or “survives” or “1” (if we want to use a number) if it does remain farming, and “no”, or “fails” or “0”, if it stops. Of course, measuring sustainability in this way can only be done after the fact and often what will be of most interest is to predict sustainability in advance. For example, we might want to predict farm sustainability under a proposed change to agricultural policy. Under such circumstance the appropriate measure of sustainability is the probability that a farm will survive (for a given period of time) and under these circumstances sustainability switches from being a simple binary quantity to a continuous one, with a lower limit of zero and an upper limit of one.

 

 

 

Figure 2. A representation of different interpretations of resilience. System 1 is more resilient than System 2 irrespective of whether resilience is measured as the size of shock which can be withstood, or the time taken to return to the initial state.

Resilience:   Resilience is one measure of the potential sustainability of a system; so, resilience is to sustainability what, say, blood pressure is to health.   The primary literature on resilience can be confusing because at least two different definitions are widely used and, while they are fundamentally connected, they do not measure resilience in the same way. In the socio-ecological interpretation of resilience it is defined as the amount of disturbance required to knock a system out of its current state into another state. In dynamic systems theory, in contrast, resilience is defined  as the time taken for a system to return to its initial state after it is subjected to a disturbance. On the face of it these two definitions do not have much in common: one measures an amount of disturbance, the other a length of time.   However, despite the superficial differences, and the sometimes polarised discussions about the topic in the literature, the two definitions are both indicators of essentially the same thing; i.e. dynamic stability.

Research Undertaken

Research on sustainability and resilience is central to a number of the work packages currently funded by Scottish Government. One key interest is in bringing together research at different scales to understand how sustainability and resilience are determined. The major focus of our research is on the analysis of existing data sets which are already gathered by Scottish Government for a variety of purposes. We use statistical modelling techniques to explore the dynamics of the data and compare the observations against theoretical expectations from different possible mechanisms for generating resilient and non-resilient systems.

Policy Implications

 While sustainability and resilience are useful as abstract concepts, loosely associated with favourable development objectives, their real usefulness lies in the fact that they have precise meanings and that those meanings can be used to guide policy development. 

Policies which aim at increasing sustainability should be constructed on the assumption that they will result in something (whatever it is that needs to be sustained) existing for longer than it would in a benchmark, counterfactual  circumstance in which the policy is withheld. The precise meaning of sustainability gives a framework for designing the experiments or surveys necessary to test whether the policy objective is being met. 

Similarly, if policy is developed with the intention of increasing resilience, the precise meaning can be used to design the protocol for testing whether the policy is achieving its intended objective. Since resilience is a component of sustainability, the opportunity should exist to do both things simultaneously.

Author

Dr Neil McRoberts neil.mcroberts@sac.ac.uk

Topics

Sustainability and Communities

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