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Editor’s Choice - Linking modelling, monitoring and management

December 2010 (Issue 47:6)

Chee, Y.E. & Wintle, B. (2010) Linking modelling, monitoring and management: an integrated approach to controlling overabundant wildlife. Journal of Applied Ecology, 47, 1169-1178.

This journal’s focus is on ecological science with management relevance. This Issue’s Editor’s Choice, Chee & Wintle (2010), is a prime example of how cutting-edge science can guide a change in approach to population management, with the potential for substantial improvement in effectiveness, in order to achieve ecological and social objectives. It also exemplifies the value of crossing disciplinary boundaries when developing approaches to the management of natural resources.

Chee & Wintle’s paper is groundbreaking in demonstrating the value of linking ecological monitoring to management action for pest control; in this case the culling of an over-abundant species, the grey kangaroo Macropus fuliginosus in Australia, with the ultimate aim of promoting vegetation regeneration. It seems intuitively obvious that the outcome of ecological monitoring should inform management strategies, such as the number of animals to be culled in a given year. And indeed, this is the premise of adaptive management, which is often invoked as the way forward but less often actually implemented. This is partly because effective linkage of monitoring and management through developing rules to guide managers’ decision-making is both conceptually and operationally difficult. The status of the population being managed is only known through observations which are subject to uncertainty. In the case of the kangaroo, there is substantial inter-annual environmental variation, in other cases the observation process itself is often fraught with error and bias. Once information is obtained about population status, there is the issue of how to translate it into a robust decision rule for management action that produces the desired outcome over time, in the face of further uncertainty about both the underlying population dynamics and the implementation of the decision rule.

In fisheries, these issues have been addressed through Management Strategy Evaluation (MSE), a simulation approach that tests the performance of competing harvest rules in a virtual environment, in the presence of both monitoring and implementation uncertainty. MSE has had demonstrable successes, and is rapidly becoming the standard approach to fisheries management, with a range of secondary benefits such as improved stakeholder engagement (Smith et al. 2008). Chee & Wintle’s paper is the first that I am aware of that applies a similar approach to another area of population management, but there is potential for the MSE approach to revolutionise the conservation and harvesting of terrestrial species as well as control (Milner-Gulland et al. 2010).

Most current harvesting models aiming to inform management apply a range of potential harvesting rules to a modelled population, and then choose the best approach to recommend to managers based on the outcome of these simulations. A sophisticated and manager-friendly example of this approach is McMahon et al. (2010). Where Chee & Wintle improve on this approach is in integrating population monitoring and management decisions into a single framework. This enables the performance of harvesting rules to be assessed against explicit management targets in the light of the uncertainties surrounding both population dynamics and the observation process. This enables scientists and managers to develop and test approaches to management that are robust in the real world, rather than necessarily optimal in an ideal world.

Chee & Wintle (2010) provide an elegant framework for generating culling rules based upon information from monitoring of kangaroo populations. It tests these rules in a virtual environment under realistic levels of uncertainty, showing how the rules are likely to perform over time in meeting specific management objectives (in this case, keeping the kangaroo population within specified bounds). This provides a strong foundation for empirical application of the harvest rules, promoting learning about the dynamics of the system itself and re-evaluation of the management strategy within an adaptive management cycle. This paper deserves to be widely read and its approach swiftly applied to other areas of population management. It represents the best of applied science, and is a worthy Editor’s Choice. I very much hope to see a follow-up paper submitted to the Journal in five years time, that reports on the real-world performance of the approach and the scientific and management lessons that were learnt from its implementation.

E.J. Milner-Gulland
e.j.milner-gulland@imperial.ac.uk

References

Chee, Y.E. & Wintle, B. (2010) Linking modelling, monitoring and management: an integrated approach to controlling overabundant wildlife. Journal of Applied Ecology, 47, 1169-1178.

McMahon, C.R., Brook, B.W., Collier, N. & Bradshaw, C.J.A. (2010) Spatially explicit spreadsheet modelling for optimising the efficiency of reducing invasive animal density. Methods in Ecology and Evolution, 1, 53–68.

Milner-Gulland, E.J., Arroyo, B., Bellard, C., Blanchard, J., Bunnefeld, N., Delibes-Mateos, M., Edwards, C., Nuno, A., Palazy, L., Reljic, S., Riera, P. & Skrbinsek, T. (2010) New directions in Management Strategy Evaluation through cross-fertilisation between fisheries science and terrestrial conservation. Biology Letters online early.

Smith, A.D.M., Smith, D.C., Tuck, G.N., Klaer, N., Punt, A.E., Knuckey, I., Prince, J., Morison, A., Kloser, R., Haddon, M., Wayte, S., Day, J., Fay, G., Pribac, F., Fuller, M., Taylor, B. & Little, L.R. (2008) Experience in implementing harvest strategies in Australia's south-eastern fisheries, Fisheries Research, 94, 373-379.