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Optimising control of an agricultural weed in sheep-production pastures

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  • Chalak, Morteza
  • Pannell, David J.

Abstract

Optimal integrated control strategies for the weed blackberry (Rubus anglocandicans) infesting sheep pastures in Australia are analysed for a range of different circumstances. A wide range of control strategies with moderate to high costs and efficacies are analysed, including chemicals, mowing, grazing goats and biological control. The study employs a stochastic dynamic simulation model and a stochastic dynamic programming model to find the optimal control strategies under different levels of infestation. Results show that the application of a biological control agent (Phragmidium violaceum) increases expected net present value (ENPV) by so little that it is not worth introducing. Results indicate that for higher initial infestation areas, the optimal control strategies include fewer control options, resulting in lower cost but also less effective control. This is because the control costs are proportional to the infestation area, so applying expensive control strategies in high infestation area has lower net benefits. When the labour cost of spraying chemicals increases and infestation area is high, it is optimal to replace chemicals with mowing. If the efficacy of chemicals increases it is optimal to use less effective and cheaper chemicals.

Suggested Citation

  • Chalak, Morteza & Pannell, David J., 2012. "Optimising control of an agricultural weed in sheep-production pastures," Agricultural Systems, Elsevier, vol. 109(C), pages 1-8.
  • Handle: RePEc:eee:agisys:v:109:y:2012:i:c:p:1-8
    DOI: 10.1016/j.agsy.2012.01.010
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    1. C. Robert Taylor & Oscar R. Burt, 1984. "Near-Optimal Management Strategies for Controlling Wild Oats in Spring Wheat," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 66(1), pages 50-60.
    2. Abadi Ghadim, Amir K. & Pannell, David J., 1991. "Economic trade-off between pasture production and crop weed control," Agricultural Systems, Elsevier, vol. 36(1), pages 1-15.
    3. Zhang, Wei & van der Werf, Wopke & Swinton, Scott M., 2010. "Spatially optimal habitat management for enhancing natural control of an invasive agricultural pest: Soybean aphid," Resource and Energy Economics, Elsevier, vol. 32(4), pages 551-565, November.
    4. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    5. Wu, JunJie, 2001. "Optimal weed control under static and dynamic decision rules," Agricultural Economics, Blackwell, vol. 25(1), pages 119-130, June.
    6. Graeme J. Doole, 2008. "Optimal management of annual ryegrass (Lolium rigidum Gaud.) in phase rotations in the Western Australian Wheatbelt ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 52(3), pages 339-362, September.
    7. Pannell, David J., 1988. "Weed Management: A Review of Applied Economics Research in Australia," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 56(03), pages 1-15, December.
    8. Morteza Chalak & Arjan Ruijs & Ekko C. Van Ierland, 2009. "On the economics of controlling an invasive plant: a stochastic analysis of a biological control agent," International Journal of Environmental Technology and Management, Inderscience Enterprises Ltd, vol. 11(1/2/3), pages 187-206.
    9. Epanchin-Niell, Rebecca S. & Wilen, James E., 2012. "Optimal spatial control of biological invasions," Journal of Environmental Economics and Management, Elsevier, vol. 63(2), pages 260-270.
    10. James, Alex & Brown, Richard & Basse, Britta & Bourdôt, Graeme W. & Lamoureaux, Shona L. & Roberts, Mick & Saville, David J., 2011. "Application of a spatial meta-population model with stochastic parameters to the management of the invasive grass Nassella trichotoma in North Canterbury, New Zealand," Ecological Modelling, Elsevier, vol. 222(4), pages 1030-1037.
    11. Odom, Doreen I. S. & Cacho, Oscar J. & Sinden, J. A. & Griffith, Garry R., 2003. "Policies for the management of weeds in natural ecosystems: the case of scotch broom (Cytisus scoparius, L.) in an Australian national park," Ecological Economics, Elsevier, vol. 44(1), pages 119-135, February.
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    Cited by:

    1. Chalak, Morteza, 2014. "Optimal Control for a Dispersing Biological Agent," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(2), pages 1-19.

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