Avian-locust interactions in eastern Australia and the exposure of birds to locust control pesticides
There is growing worldwide pressure to develop new and effective chemicals against agricultural pests. Unfortunately, many pesticides have unanticipated and undesired effects on the environment. In eastern Australia, the Australian Plague Locust Commission (APLC) has responsibility for locust control, currently using three pesticides (fenitrothion, fipronil and the fungal agent, Metarhizium) to limit locust populations during outbreaks.
In an effort to evaluate the potential impact of these practices on Australian native fauna, this dissertation aims to assess the probability of pesticide exposure in 285 avian species, due primarily to their co-occurrence with locusts in areas where pesticide treatments are most likely to occur. Due to the unpredictable nature of rainfall, locust outbreaks and control events, I have taken a landscape approach to this question, with the area of interest coincident with the area of responsibility of the APLC. Rainfall, vegetation and soil characteristics strongly influence locust and avian distributions. I have examined spatial and temporal patterns in these factors, as well as the relationships between them with a final aim of evaluating their impact on the spatio-temporal distribution of three locust species, locust control events and avian distributions. Avian species distributions were obtained by applying generalized linear models to presence/absence data for the areas of interest for the years 1998–2002. Probabilities of a bird species present at times and locations of locust control applications were calculated. Field observations of avian species’ occurrence and behavior during locust outbreaks were used to evaluate the model. In the last step, the risk of exposure to fipronil was evaluated considering fipronil levels in three avian food items, seed, vegetation and locust samples. Small granivorous birds consuming high amounts of food daily relative to their body weight are predicted to be at greatest risk from exposure.