How much survey effort is required to assess bird assemblages in fire-prone eucalypt forests using acoustic recorders?
Michael J. M. Franklin
A C , Richard E. Major B and Ross A. Bradstock A
+ Author Affiliations
- Author Affiliations
A Centre for Environmental Risk Management of Bushfires, Centre for Sustainable Ecosystem Solutions, University of Wollongong, Wollongong, NSW 2522, Australia.
B Australian Museum Research Institute, Australian Museum, 1 William Street, Sydney, NSW 2010, Australia.
C Corresponding author. Email: mjmf080@uowmail.edu.au
Wildlife Research 48(5) 414-421 https://doi.org/10.1071/WR20099
Submitted: 15 June 2020 Accepted: 13 January 2021 Published: 15 March 2021
Abstract
Context: Forest fire activity is expected to increase in many parts of the globe over the course of the 21st century, with corresponding potential for heightened levels of proximate and ultimate threats to avian diversity. Landscape-scale investigations of the responses of birds in locations where current extreme fire regimes represent those expected in the future provide opportunities to identify potentially vulnerable species in advance. Autonomous acoustic recorders are well suited to survey birds in the typically large and remote natural areas with low accessibility required for these types of studies, because they offer cost-effective and relatively safe options for obtaining reliable data.
Aims: The present study aimed to optimise survey using acoustic recorders to achieve a satisfactory assessment of montane dry sclerophyll forest bird assemblages using these devices. Survey completeness, or the number of species detected as a percentage of total species, was used as a metric to gauge survey suitability.
Methods: Acoustic recorders were deployed in 10 ridge-top forest sites in the Blue Mountains, south-eastern Australia. Extensive field recordings were processed by an analyst, with species detected by their calls recorded in a series of 20-min samples. A results-based approach, incorporating a stopping rule that established when to conclude sampling at a site, was applied to the data. The results guided the target survey completeness and sampling effort levels assigned to a set of fixed-effort survey methods, which were subsequently evaluated.
Key results: The optimal survey method involved using recordings from five 20-min sampling periods immediately following dawn for 2 days, achieving an average survey completeness level of 69%.
Conclusions: The optimal survey method can obtain results that are suitable for many types of studies involving assessments of bird assemblages, because the method can detect all common and moderately common species in assemblages, plus a fair proportion of rare species.
Implications: The present study has systematically developed an effective method of using autonomous acoustic recorders to research and monitor montane bird assemblages in fire-prone dry sclerophyll forests. This methodological approach may also be applied in systems subject to altered patterns of flood, storm or other extreme weather under climate change.
Keywords: acoustic survey, autonomous recording unit, bird survey, results-based stopping rule, sample completeness.
References
Balestrieri, R., Basile, M., Posillico, M., Altea, T., and Matteucci, G. (2017). Survey effort requirements for bird community assessment in forest habitats. Acta Ornithologica 52, 1–9.| Survey effort requirements for bird community assessment in forest habitats.Crossref | GoogleScholarGoogle Scholar |
Boer, M. M., de Dios, V. R., and Bradstock, R. A. (2020). Unprecedented burn area of Australian mega forest fires. Nature Climate Change 10, 171–172.
| Unprecedented burn area of Australian mega forest fires.Crossref | GoogleScholarGoogle Scholar |
Bradstock, R. A. (2010). A biogeographic model of fire regimes in Australia: current and future implications. Global Ecology and Biogeography 19, 145–158.
| A biogeographic model of fire regimes in Australia: current and future implications.Crossref | GoogleScholarGoogle Scholar |
Buckingham, R., and Jackson, L. (2007). ‘A Field Guide to Australian Birdsong.’ (Bird Observers Club of Australia: Melbourne, Vic., Australia.)
Bureau of Meteorology (2021). ‘Climate statistics for Australian locations, Summary statistics KATOOMBA.’ Available at http://www.bom.gov.au/climate/averages/tables/cw_063039.shtml [verified 1 February 2021].
Callaghan, C., Lyons, M., Martin, J., Major, R., and Kingsford, R. (2017). Assessing the reliability of avian biodiversity measures of urban greenspaces using eBird citizen science data. Avian Conservation & Ecology 12, 12.
| Assessing the reliability of avian biodiversity measures of urban greenspaces using eBird citizen science data.Crossref | GoogleScholarGoogle Scholar |
Catchpole, C. K., and Slater, P. J. B. (2008). ‘Bird Song: Biological Themes and Variations.’ 2nd edn. (Cambridge University Press: Cambridge, UK.)
Chao, A., Hwang, W.-H., Chen, Y., and Kuo, C. (2000). Estimating the number of shared species in two communities. Statistica Sinica 10, 227–246.
Chao, A., Ma, K. H., Hsieh, T. C., and Chiu, C.-H. (2016). SpadeR: Species-Richness Prediction and Diversity Estimation with R. R package version 0.1.1. Available at https://CRAN.R-project.org/package=SpadeR [verified 1 February 2021].
Chazdon, R. L., Colwell, R. K., Denslow, J. S., and Guariguata, M. R. (1998). Statistical methods for estimating species richness of woody regeneration in primary and secondary rain forests of NE Costa Rica. In ‘Forest Biodiversity Research, Monitoring and Modeling: Conceptual Background and Old World Case Studies’. (Eds F. Dallmeier, and J. A. Comiskey.) pp. 285–309. (Parthenon Publishing: Paris, France.)
Clarke, H. G., Smith, P. L., and Pitman, A. J. (2011). Regional signatures of future fire weather over eastern Australia from global climate models. International Journal of Wildland Fire 20, 550–562.
| Regional signatures of future fire weather over eastern Australia from global climate models.Crossref | GoogleScholarGoogle Scholar |
Colwell, R. K., and Coddington, J. A. (1994). Estimating terrestrial biodiversity through extrapolation. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 345, 101–118.
| Estimating terrestrial biodiversity through extrapolation.Crossref | GoogleScholarGoogle Scholar | 7972351PubMed |
Darras, K., Batáry, P., Furnas, B., Celis-Murillo, A., Van Wilgenburg, S. L., Mulyani, Y. A., and Tscharntke, T. (2018a). Comparing the sampling performance of sound recorders versus point counts in bird surveys: a meta-analysis. Journal of Applied Ecology 55, 2575–2586.
| Comparing the sampling performance of sound recorders versus point counts in bird surveys: a meta-analysis.Crossref | GoogleScholarGoogle Scholar |
Darras, K., Furnas, B., Fitriawan, I., Mulyani, Y., and Tscharntke, T. (2018b). Estimating bird detection distances in sound recordings for standardizing detection ranges and distance sampling. Methods in Ecology and Evolution 9, 1928–1938.
| Estimating bird detection distances in sound recordings for standardizing detection ranges and distance sampling.Crossref | GoogleScholarGoogle Scholar |
Darras, K., Batáry, P., Furnas, B. J., Grass, I., Mulyani, Y. A., and Tscharntke, T. (2019). Autonomous sound recording outperforms human observation for sampling birds: a systematic map and user guide. Ecological Applications 29, e01954.
| Autonomous sound recording outperforms human observation for sampling birds: a systematic map and user guide.Crossref | GoogleScholarGoogle Scholar | 31206926PubMed |
Depraetere, M., Pavoine, S., Jiguet, F., Gasc, A., Duvail, S., and Sueur, J. (2012). Monitoring animal diversity using acoustic indices: implementation in a temperate woodland. Ecological Indicators 13, 46–54.
| Monitoring animal diversity using acoustic indices: implementation in a temperate woodland.Crossref | GoogleScholarGoogle Scholar |
Driscoll, D. A., Lindenmayer, D. B., Bennett, A. F., Bode, M., Bradstock, R. A., Cary, G. J., Clarke, M. F., Dexter, N., Fensham, R., and Friend, G. (2010). Fire management for biodiversity conservation: key research questions and our capacity to answer them. Biological Conservation 143, 1928–1939.
| Fire management for biodiversity conservation: key research questions and our capacity to answer them.Crossref | GoogleScholarGoogle Scholar |
Fox, A. M. (1978). The ‘72 fire of Nadgee Nature Reserve. Parks and Wildlife 2, 5–24.
Franklin, M. J. M., Morris, E. C., and Major, R. E. (2014). Relationships between time since fire and honeyeater abundance in montane heathland. Emu-Austral Ornithology 114, 61–68.
| Relationships between time since fire and honeyeater abundance in montane heathland.Crossref | GoogleScholarGoogle Scholar |
Franklin, M. J. M., Major, R. E., Bedward, M., and Bradstock, R. A. (2020). Establishing the adequacy of recorded acoustic surveys of forest bird assemblages. Avian Conservation & Ecology 15, 8.
| Establishing the adequacy of recorded acoustic surveys of forest bird assemblages.Crossref | GoogleScholarGoogle Scholar |
Gosper, C. R., Fox, E., Burbidge, A. H., Craig, M. D., Douglas, T. K., Fitzsimons, J. A., McNee, S., Nicholls, A., O’Connor, J., and Prober, S. M. (2019). Multi-century periods since fire in an intact woodland landscape favour bird species declining in an adjacent agricultural region. Biological Conservation 230, 82–90.
| Multi-century periods since fire in an intact woodland landscape favour bird species declining in an adjacent agricultural region.Crossref | GoogleScholarGoogle Scholar |
Hingston, A. B., Wardlaw, T. J., Baker, S. C., and Jordan, G. J. (2018). Data obtained from acoustic recording units and from field observer point counts of Tasmanian forest birds are similar but not the same. Australian Field Ornithology 35, 30–39.
| Data obtained from acoustic recording units and from field observer point counts of Tasmanian forest birds are similar but not the same.Crossref | GoogleScholarGoogle Scholar |
Holmes, S. B., McIlwrick, K. A., and Venier, L. A. (2014). Using automated sound recording and analysis to detect bird species‐at‐risk in southwestern Ontario woodlands. Wildlife Society Bulletin 38, 591–598.
| Using automated sound recording and analysis to detect bird species‐at‐risk in southwestern Ontario woodlands.Crossref | GoogleScholarGoogle Scholar |
Hughes, L. (2003). Climate change and Australia: trends, projections and impacts. Austral Ecology 28, 423–443.
| Climate change and Australia: trends, projections and impacts.Crossref | GoogleScholarGoogle Scholar |
Joshi, K. A., Mulder, R. A., and Rowe, K. M. (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, 233–246.
| Comparing manual and automated species recognition in the detection of four common south-east Australian forest birds from digital field recordings.Crossref | GoogleScholarGoogle Scholar |
Keith, D. A. (2004). ‘Ocean Shores to Desert Dunes: the Native Vegetation of New South Wales and the ACT.’ (Department of Environment and Conservation NSW: Sydney, NSW, Australia.)
Knight, E., Hannah, K., Foley, G., Scott, C., Brigham, R., and Bayne, E. (2017). Recommendations for acoustic recognizer performance assessment with application to five common automated signal recognition programs. Avian Conservation & Ecology 12, 14.
| Recommendations for acoustic recognizer performance assessment with application to five common automated signal recognition programs.Crossref | GoogleScholarGoogle Scholar |
La, V. T., and Nudds, T. D. (2016). Estimation of avian species richness: biases in morning surveys and efficient sampling from acoustic recordings. Ecosphere 7, e01294.
| Estimation of avian species richness: biases in morning surveys and efficient sampling from acoustic recordings.Crossref | GoogleScholarGoogle Scholar |
Lennon, J. J., Koleff, P., Greenwood, J. J., and Gaston, K. J. (2004). Contribution of rarity and commonness to patterns of species richness. Ecology Letters 7, 81–87.
| Contribution of rarity and commonness to patterns of species richness.Crossref | GoogleScholarGoogle Scholar |
Lindenmayer, D. B., Blanchard, W., McBurney, L., Blair, D., Banks, S. C., Driscoll, D. A., Smith, A. L., and Gill, A. (2014). Complex responses of birds to landscape‐level fire extent, fire severity and environmental drivers. Diversity & Distributions 20, 467–477.
| Complex responses of birds to landscape‐level fire extent, fire severity and environmental drivers.Crossref | GoogleScholarGoogle Scholar |
Loyn, R. H. (1997). Effects of an extensive wildfire on birds in far eastern Victoria. Pacific Conservation Biology 3, 221–234.
| Effects of an extensive wildfire on birds in far eastern Victoria.Crossref | GoogleScholarGoogle Scholar |
Loyn, R. H., and McNabb, E. G. (2015). Bird population responses to wildfire and planned burns in foothill forests of Victoria, Australia. Journal of Ornithology 156, 263–273.
| Bird population responses to wildfire and planned burns in foothill forests of Victoria, Australia.Crossref | GoogleScholarGoogle Scholar |
McGrann, M. C., and Furnas, B. J. (2016). Divergent species richness and vocal behavior in avian migratory guilds along an elevational gradient. Ecosphere 7, e01419.
| Divergent species richness and vocal behavior in avian migratory guilds along an elevational gradient.Crossref | GoogleScholarGoogle Scholar |
Moritz, M. A., Parisien, M. A., Batllori, E., Krawchuk, M. A., Van Dorn, J., Ganz, D. J., and Hayhoe, K. (2012). Climate change and disruptions to global fire activity. Ecosphere 3, 49.
| Climate change and disruptions to global fire activity.Crossref | GoogleScholarGoogle Scholar |
Nimmo, D. G., Avitabile, S., Banks, S. C., Bliege Bird, R., Callister, K., Clarke, M. F., Dickman, C. R., Doherty, T. S., Driscoll, D. A., and Greenville, A. C. (2019). Animal movements in fire‐prone landscapes. Biological Reviews of the Cambridge Philosophical Society 94, 981–998.
| Animal movements in fire‐prone landscapes.Crossref | GoogleScholarGoogle Scholar | 30565370PubMed |
Nolan, R. H., Boer, M. M., Collins, L., Resco de Dios, V., Clarke, H., Jenkins, M., Kenny, B., and Bradstock, R. A. (2020). Causes and consequences of eastern Australia’s 2019–20 season of mega‐fires. Global Change Biology 26, 1039–1041.
| Causes and consequences of eastern Australia’s 2019–20 season of mega‐fires.Crossref | GoogleScholarGoogle Scholar | 31916352PubMed |
Office of Environment and Heritage NSW (2016). ‘Fire History – Wildfires and Prescribed Burns. Spatial Data Set.’ (Office of Environment and Heritage: Sydney, NSW, Australia.)
Pearman, P. B., and Weber, D. (2007). Common species determine richness patterns in biodiversity indicator taxa. Biological Conservation 138, 109–119.
| Common species determine richness patterns in biodiversity indicator taxa.Crossref | GoogleScholarGoogle Scholar |
Penman, T. D., Kavanagh, R. P., Binns, D. L., and Melick, D. R. (2007). Patchiness of prescribed burns in dry sclerophyll eucalypt forests in south-eastern Australia. Forest Ecology and Management 252, 24–32.
| Patchiness of prescribed burns in dry sclerophyll eucalypt forests in south-eastern Australia.Crossref | GoogleScholarGoogle Scholar |
Priyadarshani, N., Marsland, S., and Castro, I. (2018). Automated birdsong recognition in complex acoustic environments: a review. Journal of Avian Biology 49, jav-01447.
| Automated birdsong recognition in complex acoustic environments: a review.Crossref | GoogleScholarGoogle Scholar |
Pyke, G. H. (1988). Yearly variation in seasonal patterns of honeyeater abundance, flower density and nectar production in heathland near Sydney. Australian Journal of Ecology 13, 1–10.
| Yearly variation in seasonal patterns of honeyeater abundance, flower density and nectar production in heathland near Sydney.Crossref | GoogleScholarGoogle Scholar |
R Core Team (2019). ‘R: A Language and Environment for Statistical Computing.’ (R Foundation for Statistical Computing: Vienna, Austria.) Available at https://www.r-project.org/ [Verified 1 February 2021].
Robinson, N. M., Leonard, S. W., Bennett, A. F., and Clarke, M. F. (2014). Refuges for birds in fire-prone landscapes: the influence of fire severity and fire history on the distribution of forest birds. Forest Ecology and Management 318, 110–121.
| Refuges for birds in fire-prone landscapes: the influence of fire severity and fire history on the distribution of forest birds.Crossref | GoogleScholarGoogle Scholar |
Shonfield, J., and Bayne, E. (2017). Autonomous recording units in avian ecological research: current use and future applications. Avian Conservation & Ecology 12, 14.
| Autonomous recording units in avian ecological research: current use and future applications.Crossref | GoogleScholarGoogle Scholar |
Sitters, H., Christie, F. J., Di Stefano, J., Swan, M., Penman, T., Collins, P. C., and York, A. (2014). Avian responses to the diversity and configuration of fire age classes and vegetation types across a rainfall gradient. Forest Ecology and Management 318, 13–20.
| Avian responses to the diversity and configuration of fire age classes and vegetation types across a rainfall gradient.Crossref | GoogleScholarGoogle Scholar |
Truskinger, A., Cottman-Fields, M., Johnson, D., and Roe, P. (2013). Rapid scanning of spectrograms for efficient identification of bioacoustic events in big data. In ‘Proceedings of the 2013 IEEE 9th International Conference on e-Science (eScience), Beijing, China’. (Eds T. Tan, and T. Hey.) pp. 270–277. (Institute of Electrical and Electronic Engineers (IEEE): New York, NY, USA.)
Turgeon, P., Van Wilgenburg, S., and Drake, K. (2017). Microphone variability and degradation: implications for monitoring programs employing autonomous recording units. Avian Conservation & Ecology 12, 9.
| Microphone variability and degradation: implications for monitoring programs employing autonomous recording units.Crossref | GoogleScholarGoogle Scholar |
Van Gessel, F., and Kane, R. (2002). ‘Birds of the Greater Sydney Region: a Regional Field Guide,’ Vol. 5. (Professional Wildlife Sounds: Woy Woy, NSW, Australia.)
Watson, D. M. (2003). The ‘standardized search’: an improved way to conduct bird surveys. Austral Ecology 28, 515–525.
| The ‘standardized search’: an improved way to conduct bird surveys.Crossref | GoogleScholarGoogle Scholar |
Watson, D. M. (2004). Comparative evaluation of new approaches to survey birds. Wildlife Research 31, 1–11.
| Comparative evaluation of new approaches to survey birds.Crossref | GoogleScholarGoogle Scholar |
Watson, D. M. (2010). Optimizing inventories of diverse sites: insights from Barro Colorado Island birds. Methods in Ecology and Evolution 1, 280–291.
| Optimizing inventories of diverse sites: insights from Barro Colorado Island birds.Crossref | GoogleScholarGoogle Scholar |
Watson, D. M. (2017). Sampling effort determination in bird surveys: do current norms meet best-practice recommendations? Wildlife Research 44, 183–193.
| Sampling effort determination in bird surveys: do current norms meet best-practice recommendations?Crossref | GoogleScholarGoogle Scholar |
Wimmer, J., Towsey, M., Roe, P., and Williamson, I. (2013). Sampling environmental acoustic recordings to determine bird species richness. Ecological Applications 23, 1419–1428.
| Sampling environmental acoustic recordings to determine bird species richness.Crossref | GoogleScholarGoogle Scholar | 24147413PubMed |
