REFERENCES
Acevedo, M. A., & Villanueva-Rivera, L. J. (2006). Using Automated Digital Recording Systems as Effective Tools for the Monitoring of Birds and Amphibians. Wildlife Society Bulletin , 34(1) , 211–214. https://doi.org/10.2193/0091-7648(2006)34[211:UADRSA]2.0.CO;2
Alquezar, R. D., & Machado, R. B. (2015). Comparisons Between Autonomous Acoustic Recordings and Avian Point Counts in Open Woodland Savanna. The Wilson Journal of Ornithology , 127(4) , 712–723. https://doi.org/10.1676/14-104.1
Audacity Team. (2020). Audacity(R): Free Audio Editor and Recorder (Version 2.4.2) [Computer software]. https://audacityteam.org/
Bart, J. (1985). Causes of recording errors in singing bird surveys.The Wilson Bulletin , 161–172.
Boyle, W. A., & Martin, K. (2015). The conservation value of high elevation habitats to North American migrant birds. Biological Conservation , 192 , 461–476. https://doi.org/10.1016/j.biocon.2015.10.008
British Columbia Ministry of Forests, Lands, Natural Resource Operations, and Rural Development. (2018). Biogeoclimatic Zones of British Columbia, 2018. Forest Analysis and Inventory Branch, Victoria, B.C. https://www.for.gov.bc.ca/hre/becweb/resources/ [Map]. https://www.for.gov.bc.ca/hre/becweb/resources/maps/index.html
Burnham, K. P., & Anderson, D. R. (2002). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach(Second Edition). Springer-Verlag.
Castro, I., Rosa, A. D., Priyadarshani, N., Bradbury, L., & Marsland, S. (2019). Experimental test of birdcall detection by autonomous recorder units and by human observers using broadcast. Ecology and Evolution , 9(5) , 2376–2397. https://doi.org/10.1002/ece3.4775
Caviedes, J., & Ibarra, J. T. (2017). Influence of Anthropogenic Disturbances on Stand Structural Complexity in Andean Temperate Forests: Implications for Managing Key Habitat for Biodiversity. PLOS ONE ,12(1) , e0169450. https://doi.org/10.1371/journal.pone.0169450
Celis‐Murillo, A., Deppe, J. L., & Allen, M. F. (2009). Using soundscape recordings to estimate bird species abundance, richness, and composition. Journal of Field Ornithology , 80(1) , 64–78. https://doi.org/10.1111/j.1557-9263.2009.00206.x
Celis‐Murillo, A., Deppe, J. L., & Ward, M. P. (2012). Effectiveness and utility of acoustic recordings for surveying tropical birds.Journal of Field Ornithology , 83(2) , 166–179. https://doi.org/10.1111/j.1557-9263.2012.00366.x
Chao, A. (1984). Nonparametric Estimation of the Number of Classes in a Population. Scandinavian Journal of Statistics , 11(4) , 265–270. JSTOR.
Darras, K., Batáry, P., Furnas, B. J., Grass, I., Mulyani, Y. A., & Tscharntke, T. (2019). Autonomous sound recording outperforms human observation for sampling birds: A systematic map and user guide.Ecological Applications , 29(6) , e01954. https://doi.org/10.1002/eap.1954
Dorji, S., Rajaratnam, R., & Vernes, K. (2019). Mammal richness and diversity in a Himalayan hotspot: The role of protected areas in conserving Bhutan’s mammals. Biodiversity and Conservation ,28(12) , 3277–3297. https://doi.org/10.1007/s10531-019-01821-9
Fisher, R. A. (1992). Statistical Methods for Research Workers. In S. Kotz & N. L. Johnson (Eds.), Breakthroughs in Statistics: Methodology and Distribution (pp. 66–70). Springer. https://doi.org/10.1007/978-1-4612-4380-9_6
Fiske, I., & Chandler, R. (2011). unmarked: An R Package for Fitting Hierarchical Models of Wildlife Occurrence and Abundance. Journal of Statistical Software , 043 (i10). https://econpapers.repec.org/article/jssjstsof/v_3a043_3ai10.htm
Friedlander, A. M., Donovan, M. K., Koike, H., Murakawa, P., & Goodell, W. (2019). Characteristics of effective marine protected areas in Hawaiʻi. Aquatic Conservation: Marine and Freshwater Ecosystems ,29(S2) , 103–117. https://doi.org/10.1002/aqc.3043
Goyette, J. L., Howe, R. W., Wolf, A. T., & Robinson, W. D. (2011). Detecting tropical nocturnal birds using automated audio recordings.Journal of Field Ornithology , 82(3) , 279–287. https://doi.org/10.1111/j.1557-9263.2011.00331.x
Hobson, K. A., Rempel, R. S., Greenwood, H., Turnbull, B., & Van Wilgenburg, S. L. (2002). Acoustic Surveys of Birds Using Electronic Recordings: New Potential from an Omnidirectional Microphone System.Wildlife Society Bulletin (1973-2006) , 30(3) , 709–720.
Holmes, S. B., McIlwrick, K. A., & Venier, L. A. (2014). Using automated sound recording and analysis to detect bird species-at-risk in southwestern Ontario woodlands. Wildlife Society Bulletin ,38(3) , 591–598. https://doi.org/10.1002/wsb.421
Hsieh, T. C., Ma, K. H., & Chao, A. (2016). iNEXT: An R package for rarefaction and extrapolation of species diversity (Hill numbers).Methods in Ecology and Evolution , 7(12) , 1451–1456. https://doi.org/10.1111/2041-210X.12613
Hutto, R. L., & Hutto, R. R. (2020). Does the presence of an observer affect a bird’s occurrence rate or singing rate during a point count?Journal of Field Ornithology , 91(2) , 214–223. https://doi.org/10.1111/jofo.12329
Hutto, R. L., & Stutzman, R. J. (2009). Humans versus autonomous recording units: A comparison of point-count results. Journal of Field Ornithology , 80(4) , 387–398. https://doi.org/10.1111/j.1557-9263.2009.00245.x
Ibarra, J. T., & Martin, K. (2015). Biotic homogenization: Loss of avian functional richness and habitat specialists in disturbed Andean temperate forests. Biological Conservation , 192 , 418–427. https://doi.org/10.1016/j.biocon.2015.11.008
Joshi, K. A., Mulder, R. A., & Rowe, K. M. C. (2017). Comparing manual and automated species recognition in the detection of four common south-east Australian forest birds from digital field recordings.Emu - Austral Ornithology , 117(3) , 233–246. https://doi.org/10.1080/01584197.2017.1298970
Kepler, C. B., & Scott, J. M. (1981). Reducing Bird Count Variability by Training Observers. Studies in Avian Biology , 6 , 366–371.
Klingbeil, B. T., & Willig, M. R. (2015). Bird biodiversity assessments in temperate forest: The value of point count versus acoustic monitoring protocols. PeerJ , 3 , e973. https://doi.org/10.7717/peerj.973
Knight, E. C., Sòlymos, P., Scott, C., & Bayne, E. M. (2020). Validation prediction: A flexible protocol to increase efficiency of automated acoustic processing for wildlife research. Ecological Applications: A Publication of the Ecological Society of America , e02140. https://doi.org/10.1002/eap.2140
Knight, E., Hannah, K., Foley, G., Scott, C., Brigham, R., & Bayne, E. (2017). Recommendations for acoustic recognizer performance assessment with application to five common automated signal recognition programs.Avian Conservation and Ecology , 12(2) . https://doi.org/10.5751/ACE-01114-120214
Kułaga, K., & Budka, M. (2019). Bird species detection by an observer and an autonomous sound recorder in two different environments: Forest and farmland. PLOS ONE , 14(2) , e0211970. https://doi.org/10.1371/journal.pone.0211970
MacGregor-Fors, I., & Payton, M. E. (2013). Contrasting Diversity Values: Statistical Inferences Based on Overlapping Confidence Intervals. PLOS ONE , 8(2) , e56794. https://doi.org/10.1371/journal.pone.0056794
MacKenzie, D. I., Nichols, J. D., Royle, J. A., Pollock, K. H., Bailey, L., & Hines, J. E. (2017). Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence . Elsevier.
Mazerolle, M. J. (2017). Package “AICcmodavg”: Model selection and multimodel inference based on (Q)AIC(c) (2.2-2) [CRAN R Project].
Moussus, J.-P., Jiguet, F., Clavel, J., & Julliard, R. (2009). A method to estimate phenological variation using data from large‐scale abundance monitoring programmes. Bird Study , 56(2) , 198–212. https://doi.org/10.1080/00063650902792064
Payton, M. E., Greenstone, M. H., & Schenker, N. (2003). Overlapping confidence intervals or standard error intervals: What do they mean in terms of statistical significance? Journal of Insect Science ,3(1) . https://doi.org/10.1093/jis/3.1.34
Ralph, C. J., John R. Sauer, & Sam Droege. (1995). Monitoring Bird Populations by Point Counts (Gen. Tech. Rep. PSW-GTR-149, p. 187). Pacific Southwest Research Station, Forest Service, US. Department of Agriculture.
Roberts, N. J. (2011). Investigation into survey techniques of large mammals: Surveyor competence and camera-trapping vs. transect-sampling.Bioscience Horizons: The International Journal of Student Research , 4(1) , 40–49. https://doi.org/10.1093/biohorizons/hzr006
Rosenberg, K. V., Blancher, P. J., Stanton, J. C., & Panjabi, A. O. (2017). Use of North American Breeding Bird Survey data in avian conservation assessments. The Condor , 119(3) , 594–606. https://doi.org/10.1650/CONDOR-17-57.1
Sauer, J. R., Pardieck, K. L., Ziolkowski, D. J., Smith, A. C., Hudson, M.-A. R., Rodriguez, V., Berlanga, H., Niven, D. K., & Link, W. A. (2017). The first 50 years of the North American Breeding Bird Survey.The Condor , 119(3) , 576–593. https://doi.org/10.1650/CONDOR-17-83.1
Schramm, K. D., Harvey, E. S., Goetze, J. S., Travers, M. J., Warnock, B., & Saunders, B. J. (2020). A comparison of stereo-BRUV, diver operated and remote stereo-video transects for assessing reef fish assemblages. Journal of Experimental Marine Biology and Ecology ,524 , 151273. https://doi.org/10.1016/j.jembe.2019.151273
Shonfield, J., & Bayne, E. (2017). Autonomous recording units in avian ecological research: Current use and future applications. Avian Conservation and Ecology , 12(1) . https://doi.org/10.5751/ACE-00974-120114
Tegeler, A. K., Morrison, M. L., & Szewczak, J. M. (2012). Using extended-duration audio recordings to survey avian species.Wildlife Society Bulletin , 36(1) , 21–29. https://doi.org/10.1002/wsb.112
Van Wilgenburg, S., Sólymos, P., Kardynal, K., & Frey, M. (2017). Paired sampling standardizes point count data from humans and acoustic recorders. Avian Conservation and Ecology , 12(1) . https://doi.org/10.5751/ACE-00975-120113
Venier, L. A., Holmes, S. B., Holborn, G. W., Mcilwrick, K. A., & Brown, G. (2012). Evaluation of an automated recording device for monitoring forest birds. Wildlife Society Bulletin36(1) , 30-39. https://doi.org/10.1002/wsb.88
Vold, S. T., Handel, C. M., & McNew, L. B. (2017). Comparison of acoustic recorders and field observers for monitoring tundra bird communities. Wildlife Society Bulletin , 41(3) , 566–576. https://doi.org/10.1002/wsb.785
Wright, W. J., Irvine, K. M., & Rodhouse, T. J. (2016). A goodness-of-fit test for occupancy models with correlated within-season revisits. Ecology and Evolution , 6(15) , 5404–5415. https://doi.org/10.1002/ece3.2292
Xeno-canto foundation. (2019). Xeno-canto: Sharing bird songs from around the world [www.xeno-canto.org].
Yip, D., Leston, L., Bayne, E., Sólymos, P., & Grover, A. (2017). Experimentally derived detection distances from audio recordings and human observers enable integrated analysis of point count data.Avian Conservation and Ecology , 12(1) . https://doi.org/10.5751/ACE-00997-120111