Understanding and managing river ecosystems through optimisation

Increased awareness of the ecological value of rivers has created a number of challenges to the development of robust, adaptable and socially acceptable river management strategies. New Oxford-led research explores the use of optimisation methods to assist in the management of riverine ecosystems.

Widespread degradation of the world’s river systems due to over-extraction, infrastructure development and pollution has resulted in significant economic and social cost 1,2,3,4. However, balancing the trade-offs between the vital services water provides for communities and the maintenance of ecosystem integrity, continues to present a complex management challenge involving multiple stakeholders and often conflicting objectives.

New research, led by Emily Barbour of Oxford University and the Australian National University (ANU), explores the use of optimisation methods to assist in the management of riverine ecosystems, synthesising literature from ecology, optimisation and decision science. Optimisation is a method which is being increasingly used in different areas of water management to assist in identifying effective management strategies. Through efficient exploration of different management decisions, optimisation can provide a powerful means to better understand system behaviour as well as to identify future research needs. It also allows trade-offs between multiple objectives to be examined, enabling more transparent communication between decision makers and stakeholders. 5,6,

However, representing ecosystems in an optimisation framework poses a number of challenges given ecological objectives can be difficult to define and model, and the concept of optimality is highly subjective. Identifying ecological objectives not only requires an understanding of ecosystem structure and function, it also involves identifying social perceptions of what constitutes a ‘preferred’ environmental outcome in systems that are highly modified7.

spokane

Photo: Spokane Falls by Orin Blomberg. Flickr CC BY-NC 2.0

 

Whilst there have been substantial advances in understanding flow-ecology dynamics, significant uncertainties remain given ecosystems include multiple species which respond to external drivers and complex internal interactions over different spatial and temporal scales8. These complexities limit our capacity to represent riverine ecosystems in mathematical models for evaluating management alternatives 9, as well as to develop effective monitoring systems to evaluate outcomes.

A review of existing research has identified that previous applications of optimisation for the ecological management of river systems generally have limited consideration of the impact of problem definition on modelling results, and more importantly on actual management outcomes. This can result in unintended consequences where the resulting interventions are in reality ineffective or deleterious.

The research advocates for increased evaluation of optimisation outcomes in terms of the assumptions made to identify likely actual outcomes. In particular, greater consideration is needed in the definition of ecological objectives and management alternatives, and the conceptualisation of the system in a modelling framework. In doing so, the application of optimisation can provide greater insight into system behaviour, gaps in current knowledge and data, and facilitate communication between the science community, decision makers and stakeholders5. This can lead to more transparent and informed management of our critical water resources and ecosystems.

References

  1. Poff, N. L., Allan, J. D., Bain, M. B., Karr, J. R., Prestegaard, K. L., Richter, B. D., Sparks, R. E. & Stromberg, J. C. 1997. The natural flow regime. Bioscience, 47, 769-784.
  2. Bunn, S. & Arthington, A. 2002. Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environmental Management, 30, 492 – 507.
  3. Bernhardt, E. S., Palmer, M. A., Allan, J. D., Alexander, G., Barnas, K., Brooks, S., Carr, J., Clayton, S., Dahm, C., Follstad-Shah, J., Galat, D., Gloss, S., Goodwin, P., Hart, D., Hassett, B., Jenkinson, R., Katz, S., Kondolf, G. M., Lake, P. S., Lave, R., Meyer, J. L., O’donnell, T. K., Pagano, L., Powell, B. & Sudduth, E. 2005. Synthesizing U.S. River Restoration Efforts. Science, 308, 636-637.
  4. Poff, N. L. & Matthews, J. H. 2013. Environmental flows in the Anthropocence: past progress and future prospects. Current Opinion in Environmental Sustainability, 5, 667-675.
  5. Liebman, J. C. 1976. Some simple-minded observations on role of optimization in public systems decision-making. Interfaces, 6, 102-108.
  6. Brill Jr, E. D. 1979. The use of optimization models in public-sector planning. Management Science, 25, 413-422.
  7. Steedman, R. J. 1994. Ecosystem health as a management goal. Journal of the North American Benthological Society, 13, 605-610.
  8. Holling, C. S. 1973. Resilience and stability of ecological systems. Annual Review of Ecology and Systematics, 4, 1-23.
  9. Metrick, A. & Weitzman, M. L. 1998. Conflicts and Choices in Biodiversity Preservation. Journal of Economic Perspectives, 12, 21-34.
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