Most existing sustainability indicators are entirely quantitative. They are based on quantitative measurements of variables, from which indicators and indices are derived. Some definitions of indicators identify quantification as a defining part of indicators alongside simplification and communication (Adriaanse 1993). Reliance on quantitative indicators poses a limitation with severe repercussions for sustainability assessment. Their quantitative nature means that issues measured qualitatively are less likely to be integrated into sustainable development assessments, regardless of their relevance for sustainability. As mentioned earlier, it is possible not only to communicate information in qualitative terms but also to process qualitative information by using indicators. Especially in the social sciences, indicators based on qualitatively obtained data (e.g., surveys of happiness, compliance, or agreement) are increasingly important. These data are not easily interpreted and are even more difficult to update in a robust fashion. Their integration with quantitative data remains a critical methodological challenge. The feasibility and reliability criteria for indicators, whether quantitative or qualitative, relate strictly to the scientific quality of the acquisition, reliability, and treatment of the data from which they are derived.
For a number of issues that are hard to address directly with an adequate indicator (e.g., missing data, insufficient knowledge of interactions), proxy or substitute indicators are widely used. Two broad kinds of proxy indicators can be identified: proxies as representations of complex systems (e.g., number of bird species instead of local ecosystem biodiversity) and proxies as metaphors (e.g., treaty signature instead of degree of implementation). If the first type can be very useful for communicating complex issues, the second type of proxy indicator is prone to oversimplification and value-laden assessments. For instance, bird presence has been used as proxy for certain insect populations or even for biodiversity as a whole (in the United Kingdom), suicide rates serve as proxy for a series of social issues, and GDP is used as a proxy for welfare. None of the indicators comprehensively represents the issue it is a proxy for, but each one should at least move in the same direction as that issue and thereby usefully detect and signal general changes. However, proxy indicators are much less suitable for identifying the precise dynamics of change and possible policy intervention levers. Like any indicator, proxies can be difficult to interpret and lead to wrong conclusions about the actual state of the system, as can be illustrated with the indicator "protected areas as percentage of total land area." On one hand, the higher the percentage of protected land, the stronger the policy implementation probably is. However, the higher the percentage, the more areas could have been proven to need protection, which means that the former conservation policy failed or that human activities have unacceptably high levels of impacts.
With reference to the policymaking cycle, indicators are occasionally characterized as input or output indicators. Input indicators are measurements of the procedural or substantive means engaged by policy actors to influence a condition (e.g., ratio of budgets assigned to control compliance to environmental legislation, taxes levied according to the polluter-pays principle). They are meant to provide the different types of policy actors (e.g., enterprises, consumers, politicians, lobbyists, civil servants) with an insight into the existence, potential, and performance of policy levers or societal responses. At the other end of the causal chain, output indicators measure the evolution of the identified problem itself (e.g., the state of an ecosystem). It is generally acknowledged that policy actors need such output indicators to increase their awareness of the problems but that input indicators are more appealing to them when they define policies and responses because input indicators hint more directly at the necessary implementation schemes, levers for change, or behavior adaptations.
Finally, with reference to causalities and change, two general types of indicators exist: state or stock indicators and rate or flow indicators. Especially in the environmental domain, state or stock indicators are of major importance in assessing the evolutions of systems with regard to their limits (e.g., amount of biodiversity for a given ecosystem). However, for most issues it is impossible to determine the sustainable level of the relevant stock (e.g., the necessary amount of biodiversity for the given ecosystem). In order to avoid the inherent difficulty of defining limits of acceptability (or carrying capacities), many indicator initiatives focus on the development of rate or flow indicators. Furthermore, rate or flow indicators are often more policy relevant in the short term and more attractive in a political business cycle (typically of 4—5 years). In this period, the direction and intensity of flows (e.g., CO2 emissions) can be influenced by policy and behavior in the short or medium term, whereas stocks or states are often characterized by inertia. On a sustainability time scale of decades or centuries, ignoring stock-related indicators in science and policy will hide fundamental system properties from users. Given current knowledge, improving the articulation between stock and rate indicators is a widely underestimated necessity for sus-tainability assessments.
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