Scholarlink

<p><i>Varroa destructor</i>&#xa0;is a major global threat to apiculture. Its recent detection in New South Wales (NSW), Australia, triggered an eradicative response followed by a transition to ongoing management. To identify factors influencing the probability of <i>Varroa</i> presence across apiaries in NSW, we developed a Bayesian hierarchical logistic regression model, incorporating surveillance data alongside climatic and environmental covariates. Our analysis revealed that detection probability was higher in the eradication emergency zone compared to the general emergency zone and more likely during the summer than winter. Maximum summer temperature was positively associated with <i>Varroa</i> presence, while minimum winter humidity was negatively associated with <i>Varroa</i> presence. Surveillance methods also influenced detection probabilities, with sticky traps showing higher probabilities than sugar shake methods. Public reports were associated with higher detection probabilities compared to inspections by authorised officers. The probability of detection was lower in areas with registered beekeepers within a 50-km radius compared to areas without registered beekeepers. We observed residual spatial cluster in <i>Varroa</i> distribution across the Sydney Basin and extending into the Central Tablelands, suggesting the influence of unmeasured risk factors. These findings highlight the need for targeted surveillance during high-risk seasons and in identified hotspot regions, supported by the wider use of sensitive detection methods and stronger community engagement, to improve early detection and sustainable management of <i>Varroa</i> in Australia.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Spatial and environmental drivers of Varroa destructor detection in New South Wales, Australia

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月4日

查看全文
  • Philip P. Mshelbwala,
  • Shannon Mulholland,
  • Tiffany Doyle,
  • Chris Anderson,
  • Shane Hetherington

摘要

Varroa destructor is a major global threat to apiculture. Its recent detection in New South Wales (NSW), Australia, triggered an eradicative response followed by a transition to ongoing management. To identify factors influencing the probability of Varroa presence across apiaries in NSW, we developed a Bayesian hierarchical logistic regression model, incorporating surveillance data alongside climatic and environmental covariates. Our analysis revealed that detection probability was higher in the eradication emergency zone compared to the general emergency zone and more likely during the summer than winter. Maximum summer temperature was positively associated with Varroa presence, while minimum winter humidity was negatively associated with Varroa presence. Surveillance methods also influenced detection probabilities, with sticky traps showing higher probabilities than sugar shake methods. Public reports were associated with higher detection probabilities compared to inspections by authorised officers. The probability of detection was lower in areas with registered beekeepers within a 50-km radius compared to areas without registered beekeepers. We observed residual spatial cluster in Varroa distribution across the Sydney Basin and extending into the Central Tablelands, suggesting the influence of unmeasured risk factors. These findings highlight the need for targeted surveillance during high-risk seasons and in identified hotspot regions, supported by the wider use of sensitive detection methods and stronger community engagement, to improve early detection and sustainable management of Varroa in Australia.