Abstract

Effective rodent monitoring tools are needed to allow agricultural producers and pest control specialists to determine when rodent control strategies are needed, as well as to allow researchers to assess the efficacy of various management options. General indexing tools that utilize continuous response metrics, as well as traditional presence-absence indexing strategies, are commonly used for such monitoring programs, but their ability to track rodent abundance should be verified in different ecological systems. Therefore, we tested the ability of tracking tunnels (binary response only) and remote-triggered cameras (both binary and continuous response) to effectively track roof rat (Rattus rattus) abundance in three lemon (Citrus limon) and two orange (Citrus sinensis) orchards in the southern San Joaquin Valley, California. We placed remote-triggered cameras and tracking tunnels both on the ground and within trees to assess activity, and subsequently live-trapped roof rats in these same plots to determine an estimate of population size and minimum number known values. We used multiple linear regression to compare these values to allow us to determine the effectiveness of these monitoring tools at tracking roof rat abundance depending on the monitoring tool used, the vertical zone where traps were placed (i.e., within trees or on the ground), and the crop that was monitored. We determined that both tracking tunnels and remote-triggered cameras (both binary and continuous response metrics) were correlated to roof rat abundance irrespective of their location on the ground or in the trees. We also noted a difference in the relationship between index values and roof rat abundance for lemon and orange orchards, indicating the importance of considering orchard type when interpreting models. Regardless, tracking tunnels and remote-triggered cameras both effectively reflected roof rat abundance irrespective of orchard type, and as such, they both should prove useful for future monitoring projects in citrus orchards.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.