Environmental Science & Technology Research Works

Permanent URI for this collectionhttp://hdl.handle.net/1903/1601

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Author: search.filters.author.Li, Andrew Y.

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    White-Tailed Deer Spatial Distribution in Relation to ‘4-Poster’ Tick Control Devices in Suburbia
    (MDPI, 2022-04-17) Roden-Reynolds, Patrick; Kent, Cody M.; Li, Andrew Y.; Mullinax, Jennifer M.
    Deer are keystone hosts for adult ticks and have enabled the spread of tick distributions. The ‘4-Poster’ deer bait station was developed by the United States Department of Agriculture to control ticks feeding on free-ranging deer. Although effective in certain scenarios, ‘4-Poster’ deer treatment stations require the use of bait to attract deer to one location, which may cause increased deer disease transmission rates and habitat damage. To better understand and manage the impact of baited ‘4-Poster’ stations on deer movements, we captured and GPS-monitored 35 deer as part of an integrated pest management project. Fifteen ‘4-Poster’ stations were deployed among three suburban county parks to control ticks. To quantify the effects of ‘4-Poster’ stations, we calculated deer movement metrics before and after feeders were filled with whole kernel corn, and we gathered information on visitation rates to feeders. Overall, 83.3% of collared deer visited a feeder and revisited approximately every 5 days. After feeders were refilled, collared deer were ~5% closer to feeders and conspecifics than before filling. Males used a higher percentage of available feeders and visited them more throughout the deployment periods. Although these nuanced alterations in behavior may not be strong enough to increase local deer abundance, in light of infectious diseases affecting deer populations and effective ‘4-Poster’ densities, the core range shifts and clustering after refilling bait may be a cause for concern. As such, trade-offs between conflicting management goals should be carefully considered when deploying ‘4-Poster’ stations.
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    Very small collars: an evaluation of telemetry location estimators for small mammals
    (Springer Nature, 2022-09-28) Hummell, Grace F.; Li, Andrew Y.; Mullinax, Jennifer M.
    Fine-scale tracking of animals such as Peromyscus spp. is still done with micro-very high frequency collars due to the animal’s small size and habitat usage. In most cases, tracking micro-very high frequency collars requires manual telemetry, yet throughout the literature, there is little reporting of individual telemetry methods or error reporting for small mammal spatial analyses. Unfortunately, there is even less documentation and consensus on the best programs used to calculate fine-scale animal locations from compass azimuths. In this study, we present a strategy for collecting fine-scale spatial data on Peromyscus spp. as a model species for micro-very high frequency collars and assess multiple programmatic options and issues when calculating telemetry locations. Mice were trapped from April to October 2018–2019 with Sherman traps in Howard County, Maryland, USA. Collars were placed on 61 mice, of which 31 were included in the analyses. We compared the two most cited location estimator programs in the literature, location of a signal software and Locate III, as well as the Sigloc package in program R. To assess the programmatic estimates of coordinates at a fine scale and examine programmatic impacts on different analyses, we created and compared minimum convex polygon and kernel density estimator home ranges from locations produced by each program. We found that 95% minimum convex polygon home range size significantly differed across all programs. However, we found more similarities in estimates across calculations of core home ranges. Kernel density estimator home ranges had similar patterns as the minimum convex polygon home ranges with significant differences in home range size for 95% and 50% contours. These differences likely resulted from different inclusion requirements of bearings for each program. This study highlights how different location estimator programs could change the results of a small mammal study and emphasizes the need to calculate telemetry error and meticulously document the specific inputs and settings of the location estimator.