Hostname: page-component-594f858ff7-pr6g6 Total loading time: 0 Render date: 2023-06-09T08:40:45.328Z Has data issue: false Feature Flags: { "corePageComponentGetUserInfoFromSharedSession": true, "coreDisableEcommerce": false, "corePageComponentUseShareaholicInsteadOfAddThis": true, "coreDisableSocialShare": false, "useRatesEcommerce": true } hasContentIssue false

Understanding habitat use of the Endangered Alligator Rivers Yellow Chat Epthianura crocea tunneyi to inform monitoring and management

Published online by Cambridge University Press:  22 February 2022

Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, NT, 0909, Australia. Threatened Species Recovery Hub, National Environmental Science Program.
Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, NT, 0909, Australia. Threatened Species Recovery Hub, National Environmental Science Program. Kakadu National Park, Jabiru, NT, 0886, Australia.
Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, NT, 0909, Australia.
Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, NT, 0909, Australia. Threatened Species Recovery Hub, National Environmental Science Program.
Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, NT, 0909, Australia. Threatened Species Recovery Hub, National Environmental Science Program.
*Author for correspondence; email:


Knowledge of where a threatened species occurs in a landscape is crucial for determining its habitat requirements and informing its conservation planning and management. We conducted the first broad-scale survey of the Endangered Alligator Rivers Yellow Chat Epthianura crocea tunneyi across much of its known range on drying coastal floodplains in northern Australia. Presence-absence records from 257 sites surveyed in the late dry season (August–December) of 2018 and 2019 were modelled using occupancy/detectability models. Occupancy was estimated to be 0.10 ± 0.04 with a high detection probability (0.89 ± 0.07). Modelling of 13 site-level environmental covariates found that chats were more likely to be detected at sites where the native shrub Sesbania sesban was present, were close to hydrogeological features such as depressions or channels, were long unburnt (5+ years) and/or with topsoil damage caused by feral pigs. Our estimates of chat occupancy, detectability, and the covariates that influence their occupancy, have improved our understanding of the role that fire and feral animals have on chat distribution and habitat selection, and can be used as a baseline for future monitoring. We also provide recommendations on how to design and implement future monitoring of this subspecies.

Research Article
© The Author(s), 2022. Published by Cambridge University Press on behalf of BirdLife International

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)


Armstrong, M. (2004) The Yellow Chat Epthianura crocea tunneyi in Kakadu National Park. Report to Parks Australia North (NT DIPE, Darwin).Google Scholar
Batzer, D. P. and Resh, V. H. (1992) Macroinvertebrates of a California seasonal wetland and responses to experimental habitat manipulation. Wetlands 12: 17.CrossRefGoogle Scholar
Bayliss, P., Saunders, K., Dutra, L. X., Melo, L. F., Hilton, J., Prakash, M. and & Woolard, F. (2018) Assessing sea level-rise risks to coastal floodplains in the Kakadu Region, northern Australia, using a tidally driven hydrodynamic model. Mar. Freshw. Res., 69: 10641078.CrossRefGoogle Scholar
Beeton, B., Burbidge, A., Grigg, G., Harrison, P., How, R., Humphreys, B., … Woinarski, J. (2010) Final Report Christmas Island Expert Working Group to Minister for the Environment. Heritage and the Arts.Google Scholar
Burnham, K. P. and Anderson, D. R. (1998) Practical use of the information-theoretic approach. Pp. 75117 in Model selection and inference: A practical information-theoretic approach. New York, NY: Springer New York.CrossRefGoogle Scholar
Cowie, I. D., Short, P. S. and Osterkamp Madsen, M. (2000) Floodplain flora: A flora of the coastal floodplains of the Northern Territory, Australia. Darwin, Australia: Australian Biological Resources Study.Google Scholar
Crates, R., Terauds, A., Rayner, L., Stojanovic, D., Heinsohn, R., Ingwersen, D. and Webb, M. (2017) An occupancy approach to monitoring regent honeyeaters. J. Wildl. Manage. 81: 669677.CrossRefGoogle Scholar
Crawley, M. J. (2005) Statistics: an introduction using R. Chichester: Wiley.CrossRefGoogle Scholar
Department of the Environment and Energy (2015) Threatened Species Strategy Action Plan 2015-16 - 20 birds by 2020. Canberra: Australian GovernmentGoogle Scholar
Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., … Leitao, P. J. (2013) Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36: 2746.CrossRefGoogle Scholar
Fraser, B. F., Lawson, V., Morrison, S., Christophersen, P., McGreggor, S. and Rawlinson, M. (2003) Fire management experiment for the declining partridge pigeon, Kakadu National Park. Ecol. Manag. Restor. 4: 94102.CrossRefGoogle Scholar
García, M. L. and Caselles, V. (1991) Mapping burns and natural reforestation using Thematic Mapper data. Geocarto International 6: 3137.CrossRefGoogle Scholar
Garnett, S., Szabo, J. and Dutson, G. (2011) Action plan for Australian Birds 2010. Collingwood, Australia: CSIRO.CrossRefGoogle Scholar
Geyle, H. M., Woinarski, J. C., Baker, G. B., Dickman, C. R., Dutson, G., Fisher, D. O., … Kutt, A. (2018) Quantifying extinction risk and forecasting the number of impending Australian bird and mammal extinctions. Pac. Conserv. 24: 157167.CrossRefGoogle Scholar
Glisson, W. J., Conway, C. J., Nadeau, C. P. and Borgmann, K. L. (2017) Habitat models to predict wetland bird occupancy influenced by scale, anthropogenic disturbance, and imperfect detection. Ecosphere. 8: e01837.CrossRefGoogle Scholar
Hancock, G., Lowry, J. and Dever, C. (2017) Surface disturbance and erosion by pigs: a medium term assessment for the monsoonal tropics. Land Degrad. Dev. 28: 255264.CrossRefGoogle Scholar
Hayes, D. B. and Monfils, M. J. (2015) Occupancy modeling of bird point counts: implications of mobile animals. J. Wildl. Manag. 79: 13611368.CrossRefGoogle Scholar
Hayward, M. W., Paul, J., Dillon, M. J. and Fox, B. J. (2003) Local population structure of a naturally occurring metapopulation of the quokka (Setonix brachyurus Macropodidae: Marsupialia). Biol. Conserv. 110: 343355.CrossRefGoogle Scholar
Higgins, P., Peter, J. and Steele, W. E. (2001) Handbook of Australian, New Zealand and Antarctic birds . Volume 5 . Tyrant-flycatchers to chats: Melbourne: Oxford University Press.Google Scholar
KNP (2016) Kakadu National Park Management Plan 2016 - 2026. Canberra, ACT: Director of National ParksGoogle Scholar
Kyne, P. M. and Jackson, M. V. (2016) Status of the Endangered Yellow Chat Epthianura crocea tunneyi on the western South Alligator River floodplain, Kakadu National Park. Aust. Field Ornithol. 33: 169177.CrossRefGoogle Scholar
Lindenmayer, D. B., Piggott, M. P. and Wintle, B. A. (2013) Counting the books while the library burns: why conservation monitoring programs need a plan for action. Front. Ecol. Environ. 11: 549555.CrossRefGoogle Scholar
Lovett, G. M., Burns, D. A., Driscoll, C. T., Jenkins, J. C., Mitchell, M. J., Rustad, L., … Haeuber, R. (2007) Who needs environmental monitoring? Front. Ecol. Environ. 5: 253260.CrossRefGoogle Scholar
MacKenzie, D., Nichols, J., Royle, J., Pollock, K., Bailey, L. and Hines, J. (2006) Occupancy estimation and modelling: Inferring patterns and dynamics of species occurrence. London: Academic Press.Google Scholar
MacKenzie, D. I., Nichols, J. D., Lachman, G. B., Droege, S., Andrew Royle, J. and Langtimm, C. A. (2002) Estimating site occupancy rates when detection probabilities are less than one. Ecology 83: 22482255.CrossRefGoogle Scholar
MacKenzie, D. I., Nichols, J. D., Sutton, N., Kawanishi, K. and Bailey, L. L. (2005) Improving inferences in population studies of rare species that are detected imperfectly. Ecology 86: 11011113.CrossRefGoogle Scholar
Marinho, P. H., Bezerra, D., Antongiovanni, M., Fonseca, C. R. and Venticinque, E. M. (2018) Estimating occupancy of the Vulnerable northern tiger cat Leopardus tigrinus in Caatinga drylands. Mammal Res. 63: 3342.CrossRefGoogle Scholar
Martin, J., Kitchens, W. M. and Hines, J. E. (2007) Importance of well‐designed monitoring programs for the conservation of endangered species: case study of the snail kite. Conserv. Biol. 21: 472481.CrossRefGoogle ScholarPubMed
McDonald, K. (1990) Rheobatrachus Liem and Taudactylus Straughan and Lee (Anura: Leptodactylidae) in Eungella National Park, Queensland: distribution and decline. Trans. R. Soc. S. Aust. 114: 187194.Google Scholar
McGregor, S., Lawson, V., Christophersen, P., Kennett, R., Boyden, J., Bayliss, P., … Andersen, A. N. (2010) Indigenous wetland burning: conserving natural and cultural resources in Australia’s World Heritage-listed Kakadu National Park. Hum. Ecol. 38: 721729.CrossRefGoogle Scholar
Mitchell, J., Dorney, W., Mayer, R. and McIlroy, J. J. W. R. (2008) Ecological impacts of feral pig diggings in north Queensland rainforests. Wildl. Res. 34: 603608.CrossRefGoogle Scholar
Noske, R. A. (1992) The status and ecology of the white-throated grasswren Amytornis woodwardi. Emu 92: 3951.CrossRefGoogle Scholar
Pereira, J. M. C., A. C. L.Sousa, A. M. O.Silva, J. M. N., Santos, T. N. and Carreira, J. M. B. (1999) Spectral characterisation and discrimination of burnt areas. Pp. 123138 in Chuvieco, E., eds. Remote sensing of large wildfires. Berlin, Heidelberg: Springer.CrossRefGoogle Scholar
Pleniou, M. and Koutsias, N. (2013) Sensitivity of spectral reflectance values to different burn and vegetation ratios: A multi-scale approach applied in a fire affected area. ISPRS J. Photogrammetry and Remote Sensing 79: 199210.CrossRefGoogle Scholar
R Core Team (2017) R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Retrieved from Scholar
Raven, P. H. (2002) Predicting species occurrences: issues of accuracy and scale. Washington DC: Island Press.Google Scholar
Runge, C. A., Martin, T. G., Possingham, H. P., Willis, S. G. and Fuller, R. A. (2014) Conserving mobile species. Front. Ecol. Environ. 12: 395402.CrossRefGoogle Scholar
Russell‐Smith, J., Evans, J., Edwards, A. C. and Simms, A. (2017) Assessing ecological performance thresholds in fire‐prone Kakadu National Park, northern Australia. Ecosphere 8: e01856.CrossRefGoogle Scholar
Siemann, E. (1998) Experimental tests of effects of plant productivity and diversity on grassland arthropod diversity. Ecology 79: 20572070.CrossRefGoogle Scholar
Skeat, A. J., East, T. J. and Corbett, L. K. (1996) Impact of feral water buffalo. Pp. 155177 in Landscape and vegetation ecology of the Kakadu Region, Northern Australia. Dordecht, The Netherlands: Kluwer Academic Publishers.CrossRefGoogle Scholar
Skroblin, A. and Legge, S. (2012) Influence of fine‐scale habitat requirements and riparian degradation on the distribution of the purple‐crowned fairy‐wren (Malurus coronatus coronatus) in northern Australia. Austral Ecol. 37: 874884.CrossRefGoogle Scholar
Threatened Species Scientific Committee (2006) Commonwealth Listing Advice on Epthianura crocea tunneyi. Retrieved from Scholar
Verner, J., Morrison, M. L. and Ralph, C. J. (1986) Wildlife 2000: modeling habitat relationships of terrestrial vertebrates: based on an international symposium held at Stanford Sierra Camp, Fallen Leaf Lake, California, 711 October 1984. Madison: University of Wisconsin Press.Google Scholar
Wang, L. and Qu, J. J. (2007) NMDI: A normalized multi‐band drought index for monitoring soil and vegetation moisture with satellite remote sensing. Geophys. Res. Lett. 34.CrossRefGoogle Scholar
Wang, L. and Qu, J. J. (2009) Satellite remote sensing applications for surface soil moisture monitoring: A review. Front. Earth Sci. China 3: 237247.CrossRefGoogle Scholar
West, A. S., Keyser, P. D., Lituma, C. M., Buehler, D. A., Applegate, R. D. and Morgan, J. (2016) Grasslands bird occupancy of native warm‐season grass. J. Wildl. Manag. 80: 10811090.CrossRefGoogle Scholar
Woinarski, J. (1999) Fire and Australian birds. An annotated bibliography. Pp. 113131 in Gill, A., ed. Australia’s biodiversity–responses to fire: plants, birds and invertebrates. Canberra, ACT: Dept. of Environment and Heritage.Google Scholar
Woinarski, J. C. and Legge, S. (2013) The impacts of fire on birds in Australia’s tropical savannas. Emu 113: 319352.CrossRefGoogle Scholar
Woinarski, J. C. Z. (2004) Threatened plants and animals in Kakadu National Park: a review and recommendations for management: Canberra: Department of Infrastructure, Planning and Environment.Google Scholar
Woinarski, J. C. Z. and Winderlich, S. (2014) A strategy for the conservation of threatened species and threatened ecological communities in Kakadu National Park 2014-2024. Darwin, Australia: National Environmental Research Program: Northern Australia Hub.Google Scholar
Xu, H. (2006) Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. Internatn. J. Remote Sensing 27: 30253033.CrossRefGoogle Scholar
Zuur, A. F., Ieno, E. N. and Elphick, C. S. (2010) A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1: 314.CrossRefGoogle Scholar
Supplementary material: File

Leppitt et al. supplementary material

Table S1

Download Leppitt et al. supplementary material(File)
File 22 KB