How can science guide best-practice pest management?
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Biotic invasions of plant and animal pests and pathogens pose serious threats to indigenous biodiversity, ecosystem function and services, and agricultural productivity. Pest management is complex and ideally integrates knowledge of the species’ biology, our ability to detect and control populations, and their impacts on the ecosystem. Despite the voluminous amount of ecological research focused on pest species, this research rarely helps managers identify optimal bio-economic pest-management strategies. A consequence of the disconnect between science and management is that financially-constrained managers are left with a ‘trial-and-error’ approach that may be based on extensive ecological experience but lacks a formal mechanism for assessing management impacts and guiding improvements.
Dean Anderson and colleagues from the Invasive Animals Cooperative Research Centre (IA CRC) in Australia are currently investigating how science can better guide best-practice pest management. They suggest that the disconnect between science and pest management is influenced by the fact that questions addressed by the two groups are fundamentally different. Answers to management questions result in actions on the ground, such as when, where and how to apply resources to achieve objectives (e.g. eradication, control, containment). On the other hand, ecologists address questions related to biological or detection processes (e.g. dispersal, population dynamics, detection probabilities). While research findings may contribute to management, decisions that are based on a single process (e.g. home-range size, herbivory rates, dispersal) may be ineffective or result in unexpected outcomes because system dynamics result from a complex web of interacting processes.
To help managers identify optimal bio-economic pest-management strategies, the IA CRC team has developed a research framework for use by collaborating managers and applied ecologists (Fig.). Importantly, the process requires ongoing engagement with managers. The framework has five integrated elements: (1) management questions, which will result in actions on the ground; (2) identification and investigation of biological and detection processes; (3) pathway analyses and impact assessment; (4) inferential and predictive modelling of potential management scenarios; and (5) bio-economic decision theory to incorporate economic, social and political constraints (Fig.). Research questions are built into the framework to address specific stakeholder needs. Because the framework is inherently system-specific and explores relevant management scenarios, the process increases the likelihood that evidence-based management will be applied. Ongoing collaboration between managers and researchers allows for adaptive management in which ecological models are improved by testing predictions against results from operational trials. In addition, theoretical insights are achieved through the examination of complex interactions of biological and detection processes; an outcome appealing to both managers and ecologists.
The five elements described above are not novel. However, their integration to explicitly address management questions is rarely implemented. The framework is flexible in that existing or novel approaches can be used to address any of the five elements. Also, the skills required to integrate all five elements usually requires a team with diverse skill sets. As a result of their work, Dean and the team anticipate a reduction in the gap between researchers and pest managers over time by: (1) applied ecologists beginning new research projects with stakeholder engagement and questions; and (2) managers seeking capability/collaboration to undertake the comprehensive adaptive management approach. Two recent examples of the team’s approach are described below.
Example 1: The adaptive management of stoats on Resolution Island
Stoats persist on the near-shore Resolution Island despite 6 years of trapping for biodiversity benefits (see Kararehe Kino Issue 23). The critical management question is where and when to deploy traps to optimise the probability of eradication? Dean and Andrea Byrom collaborated with the Department of Conservation (DOC) to identify major impediments to reaching management objectives: immigration from the mainland, trap shyness, and a residual population of breeding female stoats. The predicted probability of sustained eradication in the next 5 years with the current trapping programme was only 17%. Managers therefore need to intensify efforts to reduce immigration, increase capture rates of stoats on the island, and capture females disproportionately. Using this work as a guide, DOC has now updated its Operational Plan, taking into account the need for increased expenditure to address the impediments to eradication. Viewed as a broad-scale management experiment, the operational changes will be closely monitored and results will be used to update and improve the ecological-model predictions.
Example 2: Predicting the effectiveness of new strains of rabbit haemorrhagic disease (RHD-Boost)
A new strain of RHD virus is currently being investigated by IA CRC and is scheduled for field release in 2015, but its effectiveness at suppressing rabbit populations is unknown. Dave Ramsey collaborated with Tarnya Cox to model population dynamics of rabbits that are under the influence of multiple RHD strains, to determine the potential ‘on-ground’ outcomes of the release of RHD-Boost, and identify a suitable strategy to detect, with a high degree of statistical power, the level of population suppression achieved. Results suggest that the success of the released strain will depend on the strength of cross-immunity afforded to rabbits surviving wild-type viral strains. If cross-immunity could be overcome, RHD-Boost should suppress rabbit populations by an additional 10–20% above that achieved by virulent wild-type strains. On the basis of these predictions, managers have now designed a field-monitoring programme to run over 3 years (one year pre-release and two years post-release) that is capable of detecting a 20% population reduction.
This work was funded by the Australian Invasive Animals Cooperative Research Centre.
Dean Anderson & Andrea Byrom
Peter Baxter (University of Queensland),
Phillip Cassey (Invasion Ecology Group, University of Adelaide),
David Ramsey (Arthur Rylah Institute, Victoria)
Andrew Woolnough (Department of Environment and Primary Industries, Victoria)
