Upland game birds are an important resource for the Utah Division of Wildlife Resources (UDWR) and Utah hunters. Most upland game species in Utah have relatively long hunting seasons and generous bag and possession limits. While Utah's big game resources have a deservedly strong reputation with a loyal and passionate hunter base, upland game birds in the state provide daily opportunities for hunting from September to mid-February. Additionally, in Utah most upland game species inhabit areas that are accessible to the public or hunting license holders. Opportunity and access are some of the most important factors for all hunters, especially for those new to hunting. Upland game birds have traditionally been an important gateway for most hunters, and because of their accessibility and opportunity, it is likely that they will continue to be key resources for the future of hunting and its role in wildlife conservation. Harvest management is one of the key responsibilities of state wildlife agencies. The UDWR, under the authority of the state legislature, has legal jurisdiction to set hunting regulations for game species. The intent of harvest management is to provide opportunities for hunters to legally take game into possession within legal limits (e.g., individual permits, daily bag and possession limits, etc.) to ensure game populations are sustainable in the future. As such, harvest management is best implemented when it includes monitoring game populations to gain information about breeding potential and productivity (Pope and Powell 2021). For the last several decades, annual upland game harvest regulations have been set by state wildlife agencies primarily based on tradition (i.e., past regulations) and a conservative approach to changes in season lengths and limits (Dahlgren et al. 2018, Dahlgren et al. 2021). Upland game harvest management that accounts for changes in population abundance has been limited (Dahlgren et al. 2021). Greater sage-grouse (Centrocercus urophasianus) harvest has been one of the first upland game examples to incorporate population change (via lek counts) into regulating hunting opportunities and total harvest, in other words adaptive harvest management. In the late 1990s when declines in sage-grouse populations became a broad conservation concern, the UDWR was one of the first state wildlife agencies to develop and implement adaptive harvest management to continue to provide Utah's hunters with the opportunity to hunt greater sage-grouse. While information about changes in population abundance is highly desirable for effectively managing harvest, obtaining that information is often challenging and expensive. UDWR biologists are usually responsible for monitoring multiple species of wildlife and their populations. Because most wildlife in the Northern Hemisphere breed during the spring, conducting breeding surveys for game and other species taxes workloads and the available time for individual biologists. Additionally, state wildlife agencies, including the UDWR, have limited resources and are constrained to prioritize which species and populations get monitored. Given these tradeoffs and the fact that to date the traditional approach for setting upland game harvest regulations has worked (Dahlgren et al. 2018) it is understandable that upland game populations have not been regularly monitored. However, there are other issues that may need to be considered at this time. Upland game populations across North America have been steadily decreasing, along with the habitat that supports these populations (Ford et al. 2009). As human populations and development continue to expand, upland game, along with other resources, will become more and more at risk and limited. Additionally, our modern societal and cultural values continue to shift. Society's value of and tolerance for hunting (i.e., the killing of animals) will become an increasingly complex issue for wildlife agencies and hunters alike. Having a defensible scientific-based harvest management approach could provide an antidote to some of society's concerns. By understanding population change for harvested species, we can strengthen the justification of harvest management, including for upland game birds (Dahlgren et al. 2021). In recent years, Autonomous Recording Units (ARUs) are increasingly used by wildlife professionals to help assess and monitor wildlife populations (Fiss et al. 2024). ARUs are small acoustic recorders that log audio data that can be analyzed. Software is available to develop algorithms or classifiers to detect species-specific bird calls, such as those associated with breeding displays. Generally, this type of data has been used within occupancy modeling (Rempel et al. 2019). However, in more recent years some researchers have implemented different types of N-Mixture modeling, such as Royle-Nichols and Time-to-Detection models, to estimate abundance using ARU derived data (Fiss et al. 2024). In Utah, pheasants (Phasianus colchicus) remain the most popular upland hunting activity (Bernales et al. 2023). Forest grouse, ruffed (Bonasa umbellus) and dusky grouse (Dendragapus obscurus), are also popular and hunter activity has been increasing for these species over the last decade or more. Currently, novel research is underway using ARUs to understand how to monitor breeding forest grouse in the Bear River Range of northern Utah. Chukar (Alectoris chukar) and gray partridge (Perdix perdix) hunting is also very prevalent among Utah's uplanders. None of these popular upland game bird species in Utah currently have regular monitoring for breeding populations.

Our proposed objective is to use ARUs for sampling Utah's upland game bird breeding populations to estimate annual abundance for pheasants, forest grouse, and partridge at broad landscape scales.

For pheasant breeding surveys, we will sample the Ogden Bay Wildlife Management Area (WMA), the Bear River Migratory Bird Refuge, and Cache Valley in urban, exurban, and wildland areas (Figure 1). For forest grouse breeding surveys we will use ARUs in the Bear River Range, the Wildcat and Current Creek WMAs, and the Monroe Mountain and Fishlake Area (Figure 1). Both species of partridge will be sampled with ARUs in Box Elder County where their distributions consistently overlap (Figure 1). Timing: pheasants and forest grouse surveys will be conducted April 15 to June 15; partridge surveys will be conducted February 1 through March 31.

Forest grouse habitat treatments; Conduct surveys to check for utilization in habitat project areas. May conduct scat transects, drumming surveys, etc., Work with regional staff and other partners to apply for at least 5 WRI projects per region per year, Improve current methods to monitor annual upland game productivity, Collaborate with regional wildlife managers, NGO partners, and universities to identify needs for upland game species. Priority species include forest grouse, chukar, scaled quail, ptarmigan, rabbits and grey partridge. Apply for funding through WRI and apply through Research Council to facilitate university student research. Utilize emerging technologies to conduct surveys.

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Will comply with all rules and regulations, including applying for a special use permit through the Bear River Migratory Bird Refuge, and working with state and federal biologists to ensure compliance at all study sites.

We will use Wildlife Acoustics Song Meter Micro 2 ARUs for this project (https://www.wildlifeacoustics.com/products/song-meter-micro-2; regular price $249.00/unit, but currently [September 2024] on sale for $149.00/unit). Wildlife Acoustics ARUs have been very reliable for our current research with forest grouse and in other studies (Rhinehart et al. 2020). Wildlife Acoustics has free software for building classifiers to use with their data, which we have successfully used for forest grouse. Wildlife Acoustics units are also being used by other members of the National Wild Pheasant Technical Committee for sampling pheasant breeding populations and we desire to stay consistent with information among participating state agencies. We are also currently using Audiomoth (https://www.labmaker.org/collections/earth-and-ecology/products/audiomoth-v1-2-0?variant=32901956239465; $139.99/unit) ARUs in our forest grouse research, however, we have not worked through the classifier development process with the collected data yet and we believe the Wildlife Acoustic Song Meter Micro 2 unit is a more reliable option at this time with a negligible difference in cost/unit. For each species and their habitat type it is important that we gain an understanding of how far the ARUs can detect and record a species' breeding call. To accomplish this, while recording the time of each playback we will play pre-recorded e-calls for each species at increasing distance intervals and hone in to determine the distance the e-call is no longer detected by the ARU for that species and habitat type. Additionally, while conducting in-field point counts (see Methods below) we will have an observer listen from a subset of ARU locations across specific habitat types, record the time of a live bird call to match with the ARU recording and track down the detected bird to note its location and distance from the ARU. Care will be taken not to disturb and push the bird farther from its calling location. For pheasant breeding crow surveys, we will place ARUs at strategic locations within the Ogden Bay WMA (n = 50), the BRMBR (n = 50), and Cache Valley (n = 90). ARUs will be placed away from each other at least the maximum distance (see methods above) the ARU can record a pheasant crow call to avoid double sampling individual calling males. Potential locations will be determined based on available pheasant habitat and a random subset of locations will be selected for ARU placement within each area. We will obtain a permit from the U.S. Fish and Wildlife Service at the BRMBR to use ARUs within the refuge boundaries. In Cache Valley wild pheasants occur within urban, exurban, and wildland areas. To better understand breeding populations across these areas, potential locations will be delineated in each and a stratified random subset (n = 30 for each area) will be selected for ARU placement. For wildlands in Cache Valley, we will have most ARUs in lowlands with more traditional pheasant habitat, but also a few ARUs in the mountain foothills where biologists have noticed pheasants crowing in the spring in recent years. ARUs will be placed prior to and begin monitoring on April 15 until June 15 each year. For forest grouse breeding surveys, we will determine potential ARU locations within high quality breeding habitat in the Bear River Range on the Cache National Forest, the Wildcat and Current Creek WMAs, and the Monroe Mountain and Fishlake areas on the Fishlake National Forest. ARUs will be placed at a distance from each other at least the maximum distance (see methods above) the ARU can record a ruffed or dusky grouse call to avoid double sampling individual calling males. A subset of locations will be randomly selected for ARU placement. We will coordinate with the U.S. Forest Service and WMA managers for any needed permits and access to deploy ARUs before the survey period. Breeding surveys will begin April 15 until June 15 each year (based on USU's current research project). Past studies have found that breeding calls for both partridge species peak between early February and late March (Rotella and Ratti 1988, Ratti and Giudice 2001). Potential ARU locations will be delineated in Box Elder County at strategic locations where there is a high likelihood of availability for both species to be detected by each ARU. A subset of locations (n = 75) will be randomly selected for ARU placement. ARU locations will be at least 1.6 km apart because 0.8 km is the maximum distance partridge calls can be heard (Rotella and Ratti 1988). Partridge monitoring will begin February 1 and end March 31 each year. Because Partridge breeding calls peak during a period earlier than pheasants and forest grouse, individual ARUs used for partridge surveys can also be used for pheasants and forest grouse surveys. Point-Count Sampling Aural point counts by human observers will be completed at a random subset of ARU locations for each species stratified by each study area and sub-area during the same sampling periods stated above. We will conduct point-counts during annual survey periods at a minimum of 30% of the ARU locations for each species, study areas, and sub-areas. An effort will be made to conduct additional point-count surveys beyond the above 30% of ARU locations based on available time and labor. For all species, at each location observers will listen for two consecutive 4-minute intervals. During each 4-minute interval, the number of birds and calls per individual will be recorded, along with an estimated bird location (i.e., recorded on digital mapping) for each detection. The date and time of each call will be recorded so that observer data can be compared with ARU recorded data. Data Management and Analysis ARUs produce large amounts of data, which will be stored on hard drives and backed up to cloud-based data storage (e.g., USU Box Services). Classifiers for each species will be developed so that machine-learning can be used to classify passive acoustic recordings (Fiss et al. 2024). We will use N-mixture models, both Royle-Nichols and time-to-detection models, to estimate the abundance of each species using the ARU data (Fiss et al. 2024). We will also analyze point-count data using Distance modeling to estimate abundance for each species. The estimated abundances and their precision from each model will be compared.

We expect to show that passive acoustic recorded data from ARUs will have similar, but more precise, estimates of abundance when compared with point-count data. By using ARUs, we anticipate being able to demonstrate the utility and efficacy, at a fraction of the cost of using human observers, of passively monitoring and indexing breeding population abundance and yearly trends for multiple species of upland game in Utah.

Utah State University, Bear River Migratory Bird Refuge

Although there may be notable upfront investment in the ARU instruments, the equipment and methods resulting from this project are expected to be useful for many years into the future and produce reliable population-based information for defensible harvest management strategies and managing upland game into the future. Additional benefits would also include more accurate and spatially representative upland game forecasting in preparation for annual hunting seasons. Because ARUs record all sounds produced during the daily survey period, the acoustic data could be analyzed with classifiers for non-target species, such as passerines or any wildlife that regularly produce calls or other sounds.

Obtaining more information about upland game species will better inform management to ensure species sustainability.