Forecasting blowfly strike in Queensland sheep flocksExport / Share PlumX View Altmetrics View AltmetricsWard, M. P. (2000) Forecasting blowfly strike in Queensland sheep flocks. Veterinary Parasitology, 92 (4). pp. 309-317. ISSN 0304-4017 Full text not currently attached. Access may be available via the Publisher's website or OpenAccess link. Article Link: https://doi.org/10.1016/S0304-4017(00)00283-1 AbstractThe occurrence of blowfly strike between 1993 and 1999, derived from the reported use of pesticides for flystrike control, was investigated in 247 sheep flocks in Queensland, Australia using autoregressive techniques. Although there was a small increase (0.0016 per year) in flystrike incidence during the study period, this long-term linear trend was not significant (p=0.53). The occurrence of flystrike was best described by an autoregressive model that included flystrike in the previous 2 months: flystriket=0.0170+0.0392 flystriket−1+0.3589 flystriket−2. Flystrike was associated with the southern oscillation index (SOI). The SOI is based on barometric pressure readings and is associated with periods of below- (negative SOI) and above-average (positive SOI) rainfall in northern Australia. Flystrike incidence was significantly (p=0.03) greater in months in which the SOI was positive. The strongest correlation (r=0.33) was found between flystrike incidence and the SOI 2 months previously. Using the SOI, the best-fitting autoregressive model describing flystrike was flystriket=0.0238+0.3033 flystriket−2+0.0009 SOIt−2. The incidence of flystrike was significantly (p<0.05) correlated with average monthly radiation (r=0.26), but not with average monthly maximum and minimum temperature, total rainfall, evaporation and vapour pressure. The best-fitting autoregressive model describing flystrike occurrence based on these variables was flystriket=−0.0259+0.3610 flystriket−2+0.0022 radiationt. Results suggest that a useful early-warning system could be developed based on the correlation between flystrike incidence and the SOI up to 2 months previously. Such attempts to forecast flystrike may assist decision-making by wool producers with respect to flystrike control options, leading to more efficient control of blowfly strike in their industry.
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