New Technology II

Contributed Paper
ROOM: Rooms 27 – Picuris, 29 – Sandia and 31 – Santa Ana Combined

10:30AM Beyond Capture: Development of a Visual Body Condition Index for Mule Deer Using Camera Traps
Rachel A. Smiley; Tony W. Mong; Kevin L. Monteith; Matthew J. Kauffman; Chadwick D. Rittenhouse
Advances in technology and availability associated with camera traps have resulted in a rapid rise in their use to monitor wildlife distribution, abundance, and behavior. We focus on assessing body condition, a new application of camera traps. Body condition indices must relate to the percent body fat if they are to be useful. Yet, most body condition indices require capture or mortality of animals to estimate, which has limitations when applied to free-ranging animals. We developed a non-invasive, visual body condition index (VBCI) to assess body condition of mule deer (Odocoileus hemionus) that can be applied to camera trap images or videos. The VBCI was based on the visibility of five bone regions, the scapula, spinal ridge, ribs, tuber ischium, and tuber ilium, which are covered in varying amounts of subcutaneous fat. We compared the VBCI to known values of ingesta-free body fat, obtained from ultrasonography and physical palpation of captured mule deer. Our VBCI was related positively to percent ingesta-free body fat (R2=0.22, p<.001). Additionally, all five bone regions evaluated were correlated with the percent ingesta-free body fat (p<.001). Based on the relationships between VBCI and ingesta-free body fat, we developed two visual body condition indices, one that requires a broadside orientation to the camera (VBCI-1) and one that is applicable when a deer is quartered towards the camera (VBCI-2). Potential applications of the VBCI include evaluating relationships between body condition and habitat enhancements, habitat disturbances, population performances, and weather.
10:50AM Picture This: Monitoring Migratory Elk Using Remote Photography
Travis Zaffarano; Doug McWhirter; Aly Courtemanch; Greg Anderson; Matthew Kauffman
Population estimates of big games species are essential for biologists to manage productive herds while still maintaining annual hunter harvests. Many state agencies conduct herd composition surveys via helicopter or fixed wing aircraft, which are both costly and potentially dangerous. Further complicating the estimation of herd productivity is the aggregation of migratory and resident herds on seasonal habitats. Several migratory elk (Cervus elaphus) herds in northwestern Wyoming share winter habitat with resident herds, making it difficult to attain herd-specific composition data. To gather composition data pertaining to each of these herds separately, and to understand patterns of migration timing, we deployed remote trail cameras at geographic ‘bottlenecks’ to monitor migrating elk herds. A total of 29, 32, and 34 trail cameras were deployed at potential monitoring sites in the fall of 2014, 2015, and 2016 respectively. Cameras were left in place throughout the winter and spring months to capture both seasonal migrations. Although our results are preliminary, the camera data allow for several useful comparisons, namely i) variation in peak migration timing between herds, ii) the timing of fall migration for bulls versus cows, and iii) indices of calf survival. The duration of the peak fall migration varied with geographic region, ranging from two to five weeks. The duration of peak spring migration ranged from two to four weeks across regions. The majority of adult bulls migrated with the earliest groups in spring and up to two weeks later than cow and calf groups in the fall. Long-term data on composition trends and timing of spring and fall migrations, will aid in management objectives and reduce annual survey costs.
11:10AM Developing and Testing a Software Defined Radio and UAV System for Wildlife Tracking
Kellan M. Rothfus; Matthew Robinson; Gabriel Vega; Michael Shafer; Paul Flikkema
Tracking wildlife using radio telemetry methods is laborious, time consuming, and in some cases dangerous. The ability to elevate radio receivers above local topography can greatly increase received signal strength and help to reduce ambiguity related to tag location. Our group has worked to integrate standard radio telemetry (RT) equipment with a multirotor unmanned aerial vehicle (UAV) to leverage the vehicle’s improved vantage and mobility.The UAV-RT system includes a standard handheld VHF receiver and the associated electronics to transmit the received signals to the user on the ground. The audio from this receiver is transmitted over a minimal latency wireless network link so the user can complete telemetry assessments in flight. Recordings are made on the vehicle and the ground station for post flight assessments. The vehicle developed for the UAV-RT system is a Pixhawk Mini controlled hexacopter with autonomous flight features that can be leveraged for radio tag localization efforts. When the flight controller is paired with a ground control computer software, such as Mission Planner, the UAV can be programmed to autonomously fly specific routes using onboard sensors for navigation. A goal of this effort is to utilize standard hardware and open source software to allow for customization and modifications by other radio telemetry users. This presentation will include an overview of the vehicle mechanical and avionics design, and will review two UAV-RT search methods currently used to locate VHF tags. The “tower search method” rotates the vehicle in place at a prescribed altitude and using a directional antenna to achieve estimates bearing. The “grid search method” employs an omnidirectional antenna pointed toward the ground and searches for signal nulls over a uniform or variable grid. These methods and the vehicle design have been developed to increase data collection capacity, while minimizing barriers to entry for users.
11:30AM Excel, Geodatabase, and Spatial Tool Workflows to Promote Rapid Organization and Analysis of Data Collected from Platform Transmitter Terminals
Krista Mougey; Cathy Nowak; Dan Collins; Blake Grisham
Modern advancements in wildlife tracking technologies have led to a substantial increase in both the volume and complexity of spatial ecology datasets. There are significant advantages to using relational databases to store and manage these types of data. However, because of the learning curve, time investment, and, in some cases, programming knowledge needed to operate or develop database platforms, many wildlife professionals continue to use spreadsheet programs like Microsoft Excel for spatial data management. Manipulating and formatting these data within Excel and then exporting them to other software packages for analysis is often a very time consuming and error-ridden process. We developed a series of shareable and customizable tools to: 1) help wildlife researchers more effectively use Excel spreadsheets for spatial data management, 2) automate data management processes that must be repeated each time new ARGOS PTT data are downloaded, and 3) mechanize certain Excel-to-R and Excel-to-ArcMap interface procedures for rapid data analysis. Herein, we present a summary of these toolsets using an example sandhill crane spatial dataset. We discuss the development of our file structures, describe the design of our ArcGIS geodatabase, and present custom ArcGIS geoprocessing sequences developed to reduce the workload of updating map layers in the absence of dynamic Excel-to-ArcGIS links. Our customized macros, tools, and workflows can save wildlife professionals significant amounts of time by improving the efficacy of data management techniques. Moreover, these tools can easily be adapted for other wildlife species and customized for additional research objectives.


Contributed Paper
Location: Albuquerque Convention Center Date: September 26, 2017 Time: 10:30 am - 12:10 pm