Measuring ecosystem resilience is a complex task that often requires the utilization of interdisciplinary approaches. It involves multiple stages of research, including, for example, ecological field study, data collection, modeling, and analysis. Additionally, resilience assessments must take into account the unique characteristics and context of the ecosystem being studied, as different ecosystems can exhibit diverse dynamics of resilience.
One commonly used approach to quantify resilience is to measure how quickly an ecosystem recovers from small disturbances. Slower recoveries indicate a loss of resilience and an increased risk of destabilization. Another commonly used approach is to measure the maximum disturbance an ecosystem can endure without transitioning to a different state. Both approaches involve the examination of different ecological indicators and processes that reflect the ability of an ecosystem to withstand and respond to disturbances. Scheffer et al. (2015) summarized the various resilience indicators and quantitative methods utilized in previous studies.
For those who are interested in statistical methods, here is an example: Guttal and Jayaprakash (2008) suggests that changes in the skewness of time series data can serve as an early warning sign for regime shifts. This is because shifting skewness indicates a change in the asymmetry of the data’s probability distribution. As a regime shift approaches, the landscape picture of the ecosystem dynamics usually displays a noticeable asymmetry around the stable state, along with a “flattening of the potential landscape” (p. 451).
Integrating Ecosystem Resilience into Economic Valuation: Addressing the Limitations of Economic Environmental Valuation
Economic Environmental Valuation (EEV) is a framework that assigns monetary value to environmental goods or services that are not typically traded in the market. By utilizing EEV methods, we can determine the Total Economic Value (TEV) of these goods or services, which represents the economic worth individuals assign to the benefits derived from a marginal change in their accessibility or availability.
Loomis and Larson (1994) serves as an example of academic research that examines the concept of TEV. The study focuses on the measurement of the TEV associated with the expansion of gray whale populations. It utilizes a contingent valuation survey, where participants were asked about their willingness to make annual contributions to the Gray Whale Protection Fund, with the goal of achieving a specific increase (50% or 100%) in whale populations and a corresponding rise in gray whale sightings along the California coast. Through the analysis of the survey responses, the study quantifies the economic value attributed to the growth of gray whale populations.
Although widely used, the EEV approach has faced criticism for several reasons, particularly its disregard for ecosystem resilience. Typically, EEV focuses on individuals’ perceived value of incremental changes in ecosystem services, potentially overlooking the broader issue of ecosystem resilience. Fisher et al. (2008) argues that relying solely on TEV does not provide a reliable indicator of an ecosystem’s capacity to sustain future service provision, as the collapse of the ecosystem can occur with just one additional marginal change.
Admiraal et al. (2013) addresses these limitations by emphasizing the importance of integrating functional diversity and ecosystem resilience into economic valuation. It highlights the significance of maintaining a resilience stock of biodiversity. According to the authors, certain species populations, even if not deemed essential for optimizing total economic value, should still be conserved due to their contribution to the ecosystem’s adaptability to external pressures.
Academic researchers have endeavored to assess the economic value of ecosystem resilience, despite it being perceived as an extremely challenging task. One notable example is the work of Scheufele and Bennett (2012), which employed a panel mixed logit model to estimate the implicit prices of factors influencing ecosystem resilience.
The questionnaire used in the study consisted of a series of five choice scenarios, each presenting participants with three alternative options regarding the management of ecosystem resilience in the Border Ranges Rainforest. The options included:
- A ‘status quo’ option with no new management actions and zero cost.
- Two options for “new management actions to improve ecosystem resilience,” each associated with a non-zero cost.
Each option presented participants with different combinations of attributes, including likelihood, reversibility, time, area, and payment. Through the analysis of participants’ choices, researchers gained valuable insights into the preferred attributes and attribute levels. This information, such as the willingness to pay for a specific improvement in ecosystem resilience, has the potential to inform and guide decision-making regarding programs aimed at enhancing ecosystem resilience.
The example presented above showcases a practical application that exemplifies the integration of ecosystem resilience into economic environmental evaluation, offering valuable insights into resource management. Research along this line enables us to adopt a more comprehensive and sustainable perspective, considering the intricate interplay between ecological health and economic benefits. This frontier of research holds promise for unlocking new insights and approaches, paving the way for a future where the long-term well-being of both ecosystems and human communities is safeguarded.
References:
Admiraal, J. F., Wossink, A., de Groot, W. T., & de Snoo, G. R. (2013). More than total economic value: How to combine economic valuation of biodiversity with ecological resilience. Ecological Economics, 89, 115–122.
Fisher, B., Turner, K., Zylstra, M., Brouwer, R., De Groot, R., Farber, S., Ferraro, P., Green, R., Hadley, D., Harlow, J., Jefferiss, P., Kirkby, C., Morling, P., Mowatt, S., Naidoo, R., Paavola, J., Strassburg, B., Yu, D., Balmford, A. (2008). Ecosystem services and economic theory: integration for policy-relevant research. Ecological Applications 18, 2050–2067.
Guttal, V., & Jayaprakash, C. (2008). Changing skewness: an early warning signal of regime shifts in ecosystems. Ecology Letters, 11(5), 450–460.
Loomis, J. B., & Larson, D. M. (1994). Total economic values of increasing gray whale populations: results from a contingent valuation survey of visitors and households. Marine Resource Economics, 9(3), 275–286
Scheffer, M., Carpenter, S. R., Dakos, V., & van Nes, E. H. (2015). Generic indicators of ecological resilience: inferring the chance of a critical transition. Annual Review of Ecology, Evolution & Systematics, 46, 145–167.
Scheufele, G., Bennett, J. (2012) Valuing ecosystem resilience, Journal of Environmental Economics and Policy, 1:1, 18-31, DOI: 10.1080/21606544.2011.640856
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