Developing a risk prediction model for the seasonality of Lucilia spp. in New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Veterinary Science at Massey University, Manawatū, New Zealand
| dc.confidential | Embargo : Yes | en_US |
| dc.contributor.advisor | Pomroy, William | |
| dc.contributor.author | Brett, Paul Thomas James | |
| dc.date.accessioned | 2023-05-04T03:01:56Z | |
| dc.date.accessioned | 2023-05-28T23:28:07Z | |
| dc.date.available | 2023-05-04T03:01:56Z | |
| dc.date.available | 2023-05-28T23:28:07Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Flystrike of sheep in New Zealand is principally caused by Lucilia cuprina and Lucilia sericata. A series of studies were conducted to develop models to describe and predict the seasonal occurrence of these Lucilia spp. in New Zealand. Dipterans were collected on a weekly basis on eight farms across New Zealand over three fly seasons (2018/2019, 2019/2020, 2020/2021) using the LuciTrap® with a Stickytrap attachment (Lucilia spp. n = 10,559). Covid 19 travel restrictions restricted the collection of samples during the 2019/2020 and 2020/2021 seasons. Dipterans were initially identified using morphological characteristics, with further validation using the nuclear 28s rRNA and the mitochondrial ND4 gene. The morphological identification had an accuracy of 71 % for L. cuprina and 55 % for L. sericata, compared to the molecular method (p < 0.05). Consequently, the counts of both species were combined for modelling purposes. The seasonality of Lucilia spp. adult flies span from early October until late May with variability of weeks duration between farms and three weeks between seasons for individual farms. A hurdle model was used to describe the occurrence of Lucilia spp. from the 2018/2019 season (p < 0.05). Significant variables include soil temperature, rainfall, maximum temperature and photoperiod with lag times of one to seven weeks. A second model used the 2018/2019 seasonal data to predict the start of the 2019/2020 season using a mixed-effects logistic regression model using weather data from the closest Virtual Climate Station. 10 cm soil temperature and Soil Moisture Deficit Index predicted the start of the season within two weeks of the observed season (p < 0.05). Four trap and bait combinations were compared to help choose a supplementary on-farm technique to confirm model predictions. A negative binomial model fitted for Lucilia spp. catch data found no difference between LuciTrap® combined with LuciLures and the Western Australian Trap combined with sheep liver preserved in 30 % sodium sulphide (p > 0.05). While the other two trap and bait combinations were significantly worse for catching Lucilia spp. (p < 0.05). These models should provide information to allow farmers to make more informed decisions for flystrike control. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10179/18262 | |
| dc.publisher | Massey University | en_US |
| dc.rights | The Author | en_US |
| dc.subject | Lucilia | en |
| dc.subject | Seasonal distribution | en |
| dc.subject | Mathematical models | en |
| dc.subject | Sheep | en |
| dc.subject | Parasites | en |
| dc.subject | Control | en |
| dc.subject | Myiasis | en |
| dc.subject | Prevention | en |
| dc.subject | New Zealand | en |
| dc.subject.anzsrc | 300909 Veterinary parasitology | en |
| dc.title | Developing a risk prediction model for the seasonality of Lucilia spp. in New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Veterinary Science at Massey University, Manawatū, New Zealand | en_US |
| dc.type | Thesis | en_US |
| massey.contributor.author | Brett, Paul Thomas James | en_US |
| thesis.degree.discipline | Veterinary Science | en_US |
| thesis.degree.grantor | Massey University | en_US |
| thesis.degree.level | Doctoral | en_US |
| thesis.degree.name | Doctor of Philosophy (PhD) | en_US |