References

Alexander, J. D., Stephens, J. L., Geupel, G. R., & Will, T. C. (2008). Decision support tools: bridging the gap between science and management. In Proceedings of the Fourth International Partners in Flight Conference: Tundra to Tropics. (p. Pages 283–291). McAllen, Texas, USA. Retrieved from http://www.partnersinflight.org/pubs/McAllenProc/articles/PIF09_Decision Support Tools/Alexander_PIF09.pdf

Arizona Game and Fish Department. (2012). Arizona’s State Wildlife Action Plan: 2012 - 2022. Arizona Game and Fish Department, Phoenix, Arizona. Retrieved from http://www.azgfd.gov/pdfs/w_c/cwcs/downloads/CWCS_Final_May2006.pdf

Baron, J. S., Julius, S. H., West, J. M., Joyce, L. A., Blate, G., Peterson, C. H., … Griffith, B. (2008). Some guidelines for helping natural resources adapt to climate change. International Human Dimensions Programme on Global Environmental Change Update, 2, 46–52.

Blakesley, J. A., & Hanni, D. J. (2009). Monitoring Colorado’s Birds, 2008 (No. Tech. Rep. M-MCB08-01.). Technical Report M-MCB08-01. Rocky Mountain Bird Observatory, Brighton, Colorado, USA.

Brooks, T., Da Fonseca, G. A. and Rodrigues, A. S. (2004). Species, Data, and Conservation Planning. Conservation Biology, 18, 1682-1688.

Buckland, S. T., Anderson, D. R., Burnham, K. P., Laake, J. L., Borchers, D. L., & Thomas, L. (2001). Introduction to distance sampling: estimating abundance of biological populations. Oxford, UK: Oxford University Press.

Buckland, S. T., Marsden, S. J., & Green, R. E. (2008). Estimating bird abundance: making methods work. Bird Conservation International, 18, S91–S108.

Bureau of Land Management. (2010). Wyoming Sensitive Species Policy and List. Retrieved from http://www.blm.gov/pgdata/etc/medialib/blm/wy/resources/efoia/IMs/2010.Par.41285.File.dat/wy2010-027atch2.pdf

Bureau of Land Management. (2014). 2014 Montana/Dakotas BLM Special Status Species List.

Bureau of Land Management. (2015). Idaho Bureau of Land Management Special Status Species List Update. Idaho State Office Instruction Memorandum 2015-009c1, attachment 1. Chesser, R. T., Burns, K. J., Cicero, C., Dunn, J. L., Kratter, A. W., Lovette, I. J., … Winker, K. (2017). Fifty-eighth supplement to the American Ornithological Society’s Check-list of North American Birds. The Auk, 134(3), 751–773.

Chesser, R. T., S. M. Billerman, K. J. Burns, C. Cicero, J. L. Dunn, B. E. Hernández-Baños, R. A. Jiménez, A. W. Kratter, N. A. Mason, P. C. Rasmussen, J. V. Remsen, Jr., D. F. Stotz, and K. Winker. 2022. Check-list of North American Birds (online). American Ornithological Society. https://checklist.americanornithology.org/taxa/

Cody, M. L. (1985). Habitat selection in birds. New York, NY, USA. Academic Press.

Colorado Parks and Wildlife. (2015). Vertebrate and Mollusk Species of Greatest Conservation Need. Retrieved from http://cpw.state.co.us/Documents/WildlifeSpecies/SWAP/SGCN-Final-Table.pdf

Correll, M. D., Drilling, N., Dwyer, A., George, T. L., Green, A. W., Panjabi, A. O., Pavlacky Jr., D. C., Quattrini, L., Shaw, A., Sparks, R. A., Strasser, E. H., & Van Boer, A. (2016). Recommendations for grassland bird species conservation in the Northern Great Plains business plan. Final report. Bird Conservancy of the Rockies, Brighton, Colorado, USA.

Dreitz, V. J., Lukacs, P. M., & Knopf, F. L. (2006). Monitoring low density avian populations: An example using Mountain Plovers. Condor, 108(3), 700–706.

Dreitz, V. J., Stinson, L. T., Hahn, B. A., Tack, J. D., & Lukacs, P. M. (2017). A large-scale perspective for managing prairie avifauna assemblages across the western US: influences of habitat, land ownership and latitude. PeerJ, 5, e2879. https://doi.org/10.7717/peerj.2879

Dyke, S. R., Johnson, S. K., Isakson, P. T. (2015). North Dakota State Wildlife Action Plan. North Dakota Game and Fish Department, Bismarck, ND. 438 pp. Environmental Systems Research Institute. (2017). ArcGIS, version 10.X. Redlands, California, USA: Environmental Systems Research Institute, Incorporated.

Green, A. W., Pavlacky, D. C., & George, T. L. (2019). A dynamic multi-scale occupancy model to estimate temporal dynamics and hierarchical habitat use for nomadic species. Ecology and Evolution, 2019(9), 793-803.

Hanni, D. J., White, C. M., Birek, J. J., Van Lanen, N. J., & McLaren, M. F. (2012). Field protocol for spatially-balanced sampling of landbird populations. Unpublished report. Brighton, Colorado, USA: Rocky Mountain Bird Observatory. Retrieved from http://rmbo.org/v3/Portals/5/Protocols/2012%20Field_protocol_for_spacially_balanced_sampling_final.pdf

Hewitt JE, Thrush SF, Dayton PK, Bonsdorff E. 2007. The effect of spatial and temporal heterogeneity on the design and analysis of empirical studies of scale-dependent systems. American Naturalist 169:398–408.

Hobbs, N. T., & Hooten, M. B. (2015). Bayesian models: a statistical primer for ecologists. Princeton University Press, Princeton, New Jersey, USA.

Johnson, D. H. (1980). The Comparison of Usage and Availability Measurements for Evaluating Resource Preference. Ecology, 61(1), 65–71. https://doi.org/10.2307/1937156

Jones, J. P. G. (2011). Monitoring species abundance and distribution at the landscape scale. Journal of Applied Ecology, 48(1), 9–13. https://doi.org/10.1111/j.1365-2664.2010.01917.x

Kellner, K. (2018). Package ‘jagsUI’. https://cran.r-project.org/web/packages/jagsUI/jagsUI.pdf. Accessed 2 Jul 2019.

Knick, S.T., and Rotenberry, J.T., 2002. Effects of habitat fragmentation on passerine birds 587 breeding in Intermountain shrubsteppe. Studies in Avian Biology 25:131–141.

Lindenmayer, D. B., & Likens, G. E. (2009). Adaptive monitoring: a new paradigm for long-term research and monitoring. Trends in Ecology and Evolution, 24(9), 482–486.

Lindenmayer, D. B., & Likens, G. E. (2010). The science and application of ecological monitoring. Biological Conservation, 143(6), 1317–1328. https://doi.org/10.1016/j.biocon.2010.02.013

Lyons, J. E., Runge, M. C., Laskowski, H. P., & Kendall, W. L. (2008). Monitoring in the context of structured decision-making and adaptive management. The Journal of Wildlife Management, 72 (8), 1683–1692.

MacKenzie, D. I., Nichols, J. D., Lachman, G. B., Droege, S., Royle, J. A., & Langtimm, C. A. (2002). Estimating site occupancy rates when detection probabilities are less than one. Ecology, 83(8), 2248–2255.

MacKenzie, D. I., Nichols, J. D., Royle, J. A., Pollock, K. H., Bailey, L. L., & Hines, J. E. (2006). Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Burlington, Massachusetts, USA: Elsevier.

Manley, P. N., Schlesinger, M. D., Roth, J. K., & Van Horne, B. (2005). A field-based evaluation of a presence-absence protocol for monitoring ecoregional-scale biodiversity. Journal of Wildlife Management, 69(3), 950–966.

Marsh, D. M., & Trenham, P. C. (2008). Current trends in plant and animal population monitoring. Conservation Biology, 22(3), 647–655.

Metzger, M. J., Brus, D. J., Bunce, R. G. H., Carey, P. D., Gonçalves, J., Honrado, J. P., … Zomer, R. (2013). Environmental stratifications as the basis for national, European and global ecological monitoring. Ecological Indicators, 33, 26–35. https://doi.org/10.1016/j.ecolind.2012.11.009

Montana Fish Wildlife and Parks. (2015). Montana State Wildlife Action Plan, 1–453. https://doi.org/10.1017/CBO9781107415324.004

Montana Natural Heritage Program. (2015). Animal Species of Concern. Retrieved April 1, 2015, from http://mtnhp.org/SpeciesOfConcern/

Mordecai, R. S., Mattsson, B. J., Tzilkowski, C. J., & Cooper, R. J. (2011). Addressing challenges when studying mobile or episodic species: Hierarchical Bayes estimation of occupancy and use. Journal of Applied Ecology 48: 56–66. https://doi.org/10.1111/j.1365-2664.2010.01921.

New Mexico Department of Game and Fish. (2016). State Wildlife Action Plan for New Mexico. New Mexico Department of Game and Fish. Santa Fe, New Mexico. Retrieved from http://www.wildlife.state.nm.us/download/conservation/swap/New-Mexico-State-Wildlife-Action-Plan-SWAP-Final-2017.pdf

Nichols, J. D., Bailey, L. L., O’Connell, A. F., Talancy, N. W., Grant, E. H. C., Gilbert, A. T., … Hines, J. E. (2008). Multi-scale occupancy estimation and modelling using multiple detection methods. Journal of Applied Ecology, 45(5), 1321–1329.

Nichols, J. D., & Williams, B. K. (2006). Monitoring for conservation. Trends in Ecology and Evolution, 21(12), 668–673.

Noon, B. R., Bailey, L. L., Sisk, T. D., & McKelvey, K. S. (2012). Efficient Species-Level Monitoring at the Landscape Scale. Conservation Biology, 26(3), 432–441.

North American Bird Conservation Initiative. (2016). The State of North America’s Birds 2016. Environment and Climate Change Canada: Ottawa, Ontario. 8 pages. www.stateofthebirds.org

North American Bird Conservation Initiative. 2022. The State of the Birds, United States of America, 2022. StateoftheBirds.org

Oklahoma Department of Wildlife Conservation. (2015). Oklahoma Comprehensive Wildlife Conservation Strategy: A Strategic Conservation Plan for Oklahoma’s Rare and Declining Wildlife Retrieved from https://www.wildlifedepartment.com/wildlifemgmt/cwcs.pdf

Opdam, P., & Wascher, D. (2004). Climate change meets habitat fragmentation: linking landscape and biogeographical scale levels in research and conservation. Biological Conservation, 117(3), 285–297.

Partners in Flight. (2017). Avian Conservation Assessment Database, version 2017. Retrieved March 7, 2018, from http://pif.birdconservancy.org/ACAD

Pavlacky, D. C., Lukacs, P. M., Blakesley, J. A., Skorkowsky, R. C., Klute, D. S., Hahn, B. A., … Hanni, D. J. (2017). A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions. PLoS ONE, 12(10). https://doi.org/10.1371/journal.pone.0185924

Pavlacky Jr., D. C., Blakesley, J. A., White, G. C., Hanni, D. J., & Lukacs, P. M. (2012). Hierarchical multi-scale occupancy estimation for monitoring wildlife populations. Journal of Wildlife Management, 76, 154–162.

Plummer, M. (2003). JAGS: a program for analysis of Bayesian graphical models using Gibbs sampling. Proceedings of the 3rd International Workshop on Distributed Statistical Computing DSC 2003, 20–22 March 2003, Vienna, Austria.

Plummer, M. (2017). JAGS version 4.3.0 user manual. https://sourceforge.net/projects/mcmc-jags/files/Manuals/4.x/jags_user_manual.pdf/download. Accessed 2 Jul 2019.

Pollock, K. H. (1982). A capture-recapture design robust to unequal probability of capture. Journal of Wildlife Management, 46(3), 752–757.

Pollock, K. H., Nichols, J. D., Simons, T. R., Farnsworth, G. L., Bailey, L. L., & Sauer, J. R. (2002). Large scale wildlife monitoring studies: statistical methods for design and analysis. Environmetrics, 13(2), 105–119. https://doi.org/10.1002/env.514

R Core Team. (2019). R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from www.R-project.org/

Rich, T. D., Beardmore, C. J., Berlanga, H., Blancher, P. J., Bradstreet, M. S. W., Butcher, G. S., … Will, T. C. (2004). Partners in Flight North American landbird conservation plan. Ithaca, New York, USA: Cornell Lab of Ornithology.

Rosenstock, S. S., Anderson, D. R., Giesen, K. M., Leukering, T., & Carter, M. F. (2002). Landbird counting techniques: current practices and an alternative. Auk, 119(1), 46–53.

Royle, J. A., Dawson, D. K., & Bates, S. (2004). Modeling abundance effects in distance sampling. Ecology, 85(6), 1591-1597.

Ruggiero, L. F., Hayward, G. D., & Squires, J. R. (1994). Viability analysis in biological evaluations: Concepts of population vability analysis, biological population, and ecological scale. Conservation Biology, 8(2), 364–372.

Ruth, J. M., Petit, D. R., Sauer, J. R., Samuel, M. D., Johnson, F. A., Fornwall, M. D., Bennett, J. P. (2003). Science for avian conservation: Priorities for the new millennium. Auk, 120(1), 204–211.

Sauer, J. R., & Knutson, M. G. (2008). Objectives and metrics for wildlife monitoring. Journal of Wildlife Management, 72(8), 1663–1664.

Schneider, R., Fritz, M., Jorgensen, J., Schainost, S., Simpson, R., Steinauer, G., & Rothe-Groleau, C.. (2018). Revision of the Tier 1 and 2 Lists of Species of Greatest Conservation Need: A Supplement to the Nebraska Natural Legacy Project State Wildlife Action Plan. The Nebraska Game and Parks Commission, Lincoln, NE.

Sillett, T. S., Chandler, R. B., Royle, J. A., Kéry, M., & Morrison, S.A. (2012). HIerarchical distance-sampling models to estimate population size and habitat-specific abundance of an island endemic. Ecological Applications, 22(7), 1997-2006.

Sparks, R. A., & Hanni, D. J. (2013). Monitoring Birds on Little Missouri, Sheyenne and Grand River National Grasslands. Tech. Report # M-DAKPG-12. Rocky Mountain Bird Observatory, Brighton, Colorado, USA.

Sparks R. A., Van Lanen, N. J., Van Boer, A. & Pavlacky Jr., D. C. (2016). Monitoring Avian Populations on Colorado and Wyoming Military Installations. Bird Conservancy of the Rockies. Brighton, Colorado, USA.

Stevens Jr., D. L., & Olsen, A. R. (2004). Spatially balanced sampling of natural resources. Journal of the American Statistical Association, 99(465), 262–278.

Texas Parks and Wildlife Department. (2012). Texas Conservation Action Plan 2012 - 2016. Austin, TX.

Thomas, L., Buckland, S. T., Rexstad, E. A., Laake, J. L., Strindberg, S., Hedley, S. L., … Burnham, K. P. (2010). Distance software: design and analysis of distance sampling surveys for estimating population size. Journal of Applied Ecology, 47, 5–14.

Thompson, W. L. (2002). Towards reliable bird surveys: accounting for individuals present but not detected. Auk, 119(1), 18–25.

Thompson, W. L., White, G. C., & Gowan, C. (1998). Monitoring vertebrate populations. San Diego, California, USA: Academic Press.

US Forest Service. (2008). Region 2 Regional Forester’s Sensitive Species. Retrieved from http://www.fs.fed.us/r2/projects/scp/sensitivespecies/index.shtml.

US North American Bird Conservation Initiative. (2000). Bird Conservation Regions descriptions: a supplement to the North American Bird Conservation Initiative: Bird Conservation Regions map.

US North American Bird Conservation Initiative. (2009). The State of the Birds, United States of America, 2009. Washington, D.C., USA: U.S. Department of Interior. Retrieved from http://www.stateofthebirds.org/pdf_files/State of the Birds_FINAL.pdf

US North American Bird Conservation Initiative Monitoring Subcommittee. (2007). Opportunities for improving avian monitoring. Arlington, Virginia, USA: Division of Migratory Bird Management, U.S. Fish and Wildlife Service. Retrieved from http://www.nabci-us.org/aboutnabci/monitoringreportfinal0307.pdf

Utah Wildlife Action Plan Joint Team. (2015). Utah Wildlife Action Plan: A plan for managing native wildlife species and their habitats to help prevent listing under the Endangered Species Act. Salt Lake City, Utah, USA: Utah Division of Wildlife Resources.

Watanabe, S. (2010). Asymptotic equivalence of Bayes cross validation and widely applicable information criterion in singular learning theory. Journal of Machine Learning Research, 2010(11), 3571-3594.

Wiens, J. A., Rotenberry, J. T., & Van Horne, B. (1987). Habitat Occupancy Patterns of North American Shrubsteppe Birds: The Effects of Spatial Scale. Oikos, 48(2), 132. https://doi.org/10.2307/3565849

Wilson, K. A., Underwood, E. C., Morrison, S. A., Klausmeyer, K. R., Murdoch, W. W., Reyers, B., … Possingham, H. P. (2007). Conserving biodiversity efficiently: What to do, where, and when. PLoS Biology, 5(9), 1850–1861. https://doi.org/10.1371/journal.pbio.0050223

Witmer, G. W. (2005). Wildlife population monitoring: some practical considerations. Wildlife Research, 32, 259–263.

Wyoming Game and Fish Department. (2016). 2017 Species of Greatest Conservation Need. Retrieved from https://wgfd.wyo.gov/WGFD/media/content/PDF/Habitat/SWAP/Wyoming-SGCN.pdf