five

Energy efficient homes for rodent control across cityscapes

收藏
DataONE2024-07-01 更新2024-07-06 收录
下载链接:
https://search.dataone.org/view/sha256:e34c7c3b84c335b61c62010c6fcc216cd32b933fc8c8242252867dda5b14ab39
下载链接
链接失效反馈
官方服务:
资源简介:
Cities spend millions of dollars on rodent mitigation to reduce public health risks. Despite these efforts, infestations often remain high. Rodents thrive in the built environment in part due to reduced natural predators and the exploitation of garbage. Though sanitation and greenspace are important factors in rodent mitigation, more complex governance and action are needed. Urban rodents are dynamic and commensal in nature, so understanding the influence of prolific urban features, like building attributes, warrants scrutiny and additionally intersects mitigation strategies with stakeholders at a localized level. Here, we model how residential structures’ efficiency influences urban rodent populations. To do so, we created an agent-based model using characteristics of urban brown rats and their natural predator, red foxes, based on three distinct neighborhoods in Philadelphia, Pennsylvania. We varied whether retrofitting occurred and its duration as well as the percent of initial energ..., , , # Energy Efficient Homes For Rodent Control Across Cityscapes [https://doi.org/10.5061/dryad.n2z34tn5b](https://doi.org/10.5061/dryad.n2z34tn5b) We have submitted our raw data as CSV files with the naming convention **Philadelphia Main Model Final (Neighborhood) Year (1,5, or 10)**. We have also submitted the NetLogo code which is how our raw data was created. There are 5 NetLogo files. **PhiladelphiaMainModel_Final_V5_NoRodentControl.nlogo**, is the model which our analysis is derived. **PhiladelphiaMainModel_Final_Rodent_Control.nlogo**, is a complementary code with an extra function for those looking to use the code for exploration. The other NetLogo codes are bare editions for sensitivity analysis; the naming convention follows **PhiladelphiaENV(Neighborhood)SensitivityAnalysisV3.nlogo**. Finally we included 4 R scripts. The main analysis is **FinalABMAnalysis4_24.R**. The other complementary R codes are neighborhood specific sensitivity analysis codes with the naming convention, ...
创建时间:
2024-07-02
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作