Predictively modelling the distribution of the threatened brush-tailed rock-wallaby (Petrogale penicillata) in Oxley Wild Rivers National Park, north-eastern New South Wales, Australia
Lachlan Thurtell A F , Rajanathan Rajaratnam B , Piers Thomas C , Guy Ballard A D , Paul Bayne E and Karl Vernes AA Ecosystem Management, University of New England, Armidale, NSW 2351, Australia.
B Geography & Planning, University of New England, Armidale, NSW 2351, Australia.
C New South Wales National Parks and Wildlife Service, Department of Planning, Industry, and Environment, 85 Faulkner Street, Armidale, NSW 2350, Australia.
D Vertebrate Pest Research Unit, NSW Department of Primary Industries, 116 Allingham Street, Armidale, NSW 2350, Australia.
E Retired: New South Wales National Parks and Wildlife Service, Department of Planning, Industry, and Environment, 85 Faulkner Street, Armidale, NSW 2350, Australia.
F Corresponding author. Email: lachlan.thurtell@gmail.com
Wildlife Research 49(2) 169-182 https://doi.org/10.1071/WR20141
Submitted: 24 August 2020 Accepted: 6 July 2021 Published: 15 September 2021
Abstract
Context: Species Distribution Models (SDM) can be used to investigate and understand relationships between species occurrence and environmental variables, so as to predict potential distribution. These predictions can facilitate conservation actions and management decisions. Oxley Wild Rivers National Park (OWRNP) is regarded as an important stronghold for the threatened brush-tailed rock-wallaby (Petrogale penicillata), on the basis of the presence of the largest known metapopulation of the species. Adequate knowledge of the species’ ecology and distribution in OWRNP is a key objective in the national recovery plan for the species occurring in the Park.
Aims: To model distribution using key GIS-derived environmental factors for the brush-tailed rock-wallaby in OWRNP and to ground-truth its presence through field surveys in areas of high habitat suitability.
Methods: We used Maxent to model the distribution of the brush-tailed rock-wallaby within OWRNP on the basis of 282 occurrence records collected from an online database, elicitation of informal records from experts, helicopter surveys and historic records. Environmental variables used in the analysis were aspect, distance to water, elevation, geology type, slope and vegetation type.
Key results: Vegetation type (37.9%) was the highest contributing predictor of suitable habitat, whereas aspect (4.8%) contributed the least. The model produced an area under the curve (AUC) of the receiver operating characteristic (ROC) of 0.780. The model was able to discriminate between suitable and non-suitable habitat for brush-tailed rock-wallabies. Areas identified in our model as being highly suitable yielded eight new occurrence records during subsequent ground-truthing field surveys.
Conclusions: Brush-tailed rock-wallaby distribution in OWRNP is primarily associated with vegetation type, followed by distance to water, elevation, geology, slope and aspect. Field surveys indicated that the model was able to identify areas of high habitat suitability.
Implications: This model represents the first predicted distribution of brush-tailed rock-wallaby in OWRNP. By identifying areas of high habitat suitability, it can be used to survey and monitor the species in OWRNP, and, thus, contribute to its management and conservation within the Park.
Keywords: brush-tailed rock-wallaby, distribution, Maxent, Species Distribution Modelling, Oxley Wild Rivers National Park.
References
Austin, M. (2002). Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecological Modelling 157, 101–118.| Spatial prediction of species distribution: an interface between ecological theory and statistical modelling.Crossref | GoogleScholarGoogle Scholar |
Bayne, P. (1994). Behaviour of the brush-tailed rock-wallaby, Petrogale penicillata, and the recognition of individuals. (University of New England: Armidale, NSW, Australia.)
Bista, D., Shrestha, S., Sherpa, P., Thapa, G. J., Kokh, M., Lama, S. T., Khanal, K., Thapa, A., and Jnawali, S. R. (2017). Distribution and habitat use of red panda in the Chitwan–Annapurna Landscape of Nepal. PLoS One 12, e0178797.
| Distribution and habitat use of red panda in the Chitwan–Annapurna Landscape of Nepal.Crossref | GoogleScholarGoogle Scholar | 29020020PubMed |
Bista, M., Panthi, S., and Weiskopf, S. R. (2018). Habitat overlap between Asiatic black bear Ursus thibetanus and red panda Ailurus fulgens in Himalaya. PLoS One 13, e0203697.
| Habitat overlap between Asiatic black bear Ursus thibetanus and red panda Ailurus fulgens in Himalaya.Crossref | GoogleScholarGoogle Scholar | 30188937PubMed |
Boria, R. A., Olson, L. E., Goodman, S. M., and Anderson, R. P. (2014). Spatial filtering to reduce sampling bias can improve the performance of ecological niche models. Ecological Modelling 275, 73–77.
| Spatial filtering to reduce sampling bias can improve the performance of ecological niche models.Crossref | GoogleScholarGoogle Scholar |
BushBlitz (2017). Oxley Wild Rivers, New South Wales. (Bush Blitz Species Discovery Program.)
Cao, B., Bai, C., Zhang, L., Li, G., and Mao, M. (2016). Modeling habitat distribution of Cornus officinalis with Maxent modeling and fuzzy logics in China. Journal of Plant Ecology 9, 742–751.
| Modeling habitat distribution of Cornus officinalis with Maxent modeling and fuzzy logics in China.Crossref | GoogleScholarGoogle Scholar |
Capararo, S. M., and Beynon, F. M. (1996). Ground surveys of brush-tailed rock-wallaby (Petrogale penicillata) colonies in southern New South Wales. New South Wales National Parks and Wildlife Service. (Nowra.)
Caro, T., Engilis, A., Fitzherbert, E., and Gardner, T. (2004). Preliminary assessment of the flagship species concept at a small scale. Animal Conservation 7, 63–70.
| Preliminary assessment of the flagship species concept at a small scale.Crossref | GoogleScholarGoogle Scholar |
Carter, K., and Goldizen, A. W. (2003). Habitat choice and vigilance behaviour of brush-tailed rock-wallabies (Petrogale penicillata) within their nocturnal foraging ranges. Wildlife Research 30, 355–364.
| Habitat choice and vigilance behaviour of brush-tailed rock-wallabies (Petrogale penicillata) within their nocturnal foraging ranges.Crossref | GoogleScholarGoogle Scholar |
Close, R., Ingleby, S., Vanoorschot, R., Gooley, A., Briscoe, D., and Sharman, G. (1988). Identification of rock-wallabies, Petrogale penicillata (Gray, 1825), from the Grampians, Victoria, and comparison with conspecifics by examination of chromosomes, blood proteins, cell-surface antigens, parasites and morphology. Australian Journal of Zoology 36, 99–110.
| Identification of rock-wallabies, Petrogale penicillata (Gray, 1825), from the Grampians, Victoria, and comparison with conspecifics by examination of chromosomes, blood proteins, cell-surface antigens, parasites and morphology.Crossref | GoogleScholarGoogle Scholar |
Davies, M., Newsome, D., Moncrieff, D., and Smith, A. J. (2007). Conserving the Black-flanked Rock-wallaby (Petrogale lateralis lateralis) through tourism: development of a habitat ranking system for translocated animals and the need for on-going management. Conservation Science Western Australia 6, 1–12.
DECC (2008). Recovery plan for the brush-tailed rock-wallaby (Petrogale penicillata). (NSW Department of Environment and Climate Change: Sydney, NSW, Australia.)
DPIE (2020). Wildlife and Conservation Bushfire Recovery: Immediate Response January 2020. (Department of Planning, Industry and Environment: Sydney, NSW, Australia.)
DPIE (n.d.). Saving our Species – Help save the Brush-tailed Rock-wallaby. (Ed. DPIE). (Department of Planning, Industry and Environment: Sydney, NSW, Australia.)
Edwards, T. C., Cutler, D. R., Zimmermann, N. E., Geiser, L., and Moisen, G. G. (2006). Effects of sample survey design on the accuracy of classification tree models in species distribution models. Ecological Modelling 199, 132–141.
| Effects of sample survey design on the accuracy of classification tree models in species distribution models.Crossref | GoogleScholarGoogle Scholar |
Elith, J., and Leathwick, J. R. (2009). Species distribution models: ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution, and Systematics 40, 677–697.
| Species distribution models: ecological explanation and prediction across space and time.Crossref | GoogleScholarGoogle Scholar |
Elith, J. H., Graham, C. P., Anderson, R., Dudík, M., Ferrier, S., Guisan, A. J., Hijmans, R., Huettmann, F. R., Leathwick, J., and Lehmann, A. (2006). Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29, 129–151.
| Novel methods improve prediction of species’ distributions from occurrence data.Crossref | GoogleScholarGoogle Scholar |
Elith, J., Kearney, M., and Phillips, S. (2010). The art of modelling range‐shifting species. Methods in Ecology and Evolution 1, 330–342.
| The art of modelling range‐shifting species.Crossref | GoogleScholarGoogle Scholar |
ESRI (2016). ArcGIS Desktop 10.4.1. (Environmental Systems Research Institute: Redlands, CA, USA.)
Fourcade, Y., Engler, J. O., Besnard, A. G., Rödder, D., and Secondi, J. (2013). Confronting expert-based and modelled distributions for species with uncertain conservation status: a case study from the corncrake (Crex crex). Biological Conservation 167, 161–171.
| Confronting expert-based and modelled distributions for species with uncertain conservation status: a case study from the corncrake (Crex crex).Crossref | GoogleScholarGoogle Scholar |
Fourcade, Y., Engler, J. O., Rödder, D., and Secondi, J. (2014). Mapping species distributions with MAXENT using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias. PLoS One 9, e97122.
| Mapping species distributions with MAXENT using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias.Crossref | GoogleScholarGoogle Scholar | 24818607PubMed |
Gordon, G., McRae, P., Lim, L., Reimer, D., and Porter, G. (1993). The conservation status of the yellow-footed rock-wallaby in Queensland. Oryx 27, 159–168.
| The conservation status of the yellow-footed rock-wallaby in Queensland.Crossref | GoogleScholarGoogle Scholar |
Gottwald, J., Appelhans, T., Adorf, F., Hillen, J., and Nauss, T. (2017). High-resolution MaxEnt modelling of habitat suitability for maternity colonies of the barbastelle bat Barbastella barbastellus (Schreber, 1774) in Rhineland–Palatinate, Germany. Acta Chiropterologica 19, 389–398.
| High-resolution MaxEnt modelling of habitat suitability for maternity colonies of the barbastelle bat Barbastella barbastellus (Schreber, 1774) in Rhineland–Palatinate, Germany.Crossref | GoogleScholarGoogle Scholar |
Gowen, C. (2015). Between a rock and a hardplace: Management issues for the endangered brush-tailed rock-wallaby, ‘Petrogale penicillata’, in north-eastern New South Wales. (University of New England: Armidale, NSW, Australia.)
Gowen, C., and Vernes, K. (2014). Population estimates of an endangered rock-wallaby (Petrogale penicillata) using time-lapse photography from camera traps. In ‘Camera Trapping: Wildlife Management and Research’. (Eds P. Meek, P. Fleming, G. Ballard, P. Banks, A. Claridge, J. Sanderson, and D. Swann.) pp. 61–68. (CSIRO Publishing: Melbourne, Vic., Australia.)
Guisan, A., Broennimann, O., Engler, R., Vust, M., Yoccoz, N. G., Lehmann, A., and Zimmermann, N. E. (2006). Using niche‐based models to improve the sampling of rare species. Conservation Biology 20, 501–511.
| Using niche‐based models to improve the sampling of rare species.Crossref | GoogleScholarGoogle Scholar | 16903111PubMed |
Guisan, A., Tingley, R., Baumgartner, J. B., Naujokaitis‐Lewis, I., Sutcliffe, P. R., Tulloch, A. I., Regan, T. J., Brotons, L., McDonald‐Madden, E., and Mantyka‐Pringle, C. (2013). Predicting species distributions for conservation decisions. Ecology Letters 16, 1424–1435.
| Predicting species distributions for conservation decisions.Crossref | GoogleScholarGoogle Scholar | 24134332PubMed |
Guisan, A., Thuiller, W., and Zimmermann, N. E. (2017). ‘Habitat suitability and distribution models: with applications in R.’ (Cambridge University Press: Cambridge.)
Harrell, F. E. (2001). ‘Regression Modelling strategies with Applications ti Linear Models, Logistic Regression and Surival Analysis.’ 1st edn. (Springer-Verlag: New York, NY, USA.)
Hernandez, J. (2015). Ecological Niche Modeling of Pteronotropis Hubbsi, the Bluehead Shiner: Evaluating the Effects of Spatial Filtering and Maxent Features across Various Spacial Extents. (University of Texas: Tyler, TX, USA.)
Hernandez, P., Franke, I., Herzog, S., Pacheco, V., Paniagua, L., Quintana, H., Soto, A., Swenson, J., Tovar, C., and Valqui, T. (2008). Predicting species distributions in poorly-studied landscapes. Biodiversity and Conservation 17, 1353–1366.
| Predicting species distributions in poorly-studied landscapes.Crossref | GoogleScholarGoogle Scholar |
Hijmans, R. J., van Etten, J., Mattiuzzi, M., Sumner, M., Greenberg, J., Lamigueiro, O., Bevan, A., Racine, E., and Shortridge, A. (2019). Raster package in R. Available at https://cran.r-project.org/.
Hunter, J. T. (2004). Factors affecting the nestedness of rock outcrop floras of the New England Batholith of eastern Australia. Proceedings of the Royal Society of Queensland 111, 31–38.
Jarman, P. J., and Bayne, P. (1997). Behavioural ecology of P. penicillata in relation to conservation. Australian Mammalogy 19, 219–228.
Kramer‐Schadt, S., Niedballa, J., Pilgrim, J. D., Schröder, B., Lindenborn, J., Reinfelder, V., Stillfried, M., Heckmann, I., Scharf, A. K., and Augeri, D. M. (2013). The importance of correcting for sampling bias in MaxEnt species distribution models. Diversity & Distributions 19, 1366–1379.
| The importance of correcting for sampling bias in MaxEnt species distribution models.Crossref | GoogleScholarGoogle Scholar |
Law, B., Caccamo, G., Roe, P., Truskinger, A., Brassil, T., Gonsalves, L., McConville, A., and Stanton, M. (2017). Development and field validation of a regional, management‐scale habitat model: a koala Phascolarctos cinereus case study. Ecology and Evolution 7, 7475–7489.
| Development and field validation of a regional, management‐scale habitat model: a koala Phascolarctos cinereus case study.Crossref | GoogleScholarGoogle Scholar | 28944032PubMed |
Laws, R. J., and Goldizen, A. W. (2003). Nocturnal home ranges and social interactions of the brushtailed rock-wallaby Petrogale penicillata at Hurdle Creek, Queensland. Australian Mammalogy 25, 169–176.
| Nocturnal home ranges and social interactions of the brushtailed rock-wallaby Petrogale penicillata at Hurdle Creek, Queensland.Crossref | GoogleScholarGoogle Scholar |
Lobert, B. (1988). The Brush-tailed rock wallaby (Petrogale penicillata) in the Grampians National Park and the Black Range, Victoria. Part 1 – Survey, Technical Report Series No. 64. Department of Conservation, Forest, and Lands, Melbourne, Vic., Australia.
Lobo, J. M., Jiménez‐Valverde, A., and Real, R. (2008). AUC: a misleading measure of the performance of predictive distribution models. Global Ecology and Biogeography 17, 145–151.
| AUC: a misleading measure of the performance of predictive distribution models.Crossref | GoogleScholarGoogle Scholar |
Maswanganye, K. A., Cunningham, M. J., Bennett, N. C., Chimimba, C. T., and Bloomer, P. (2017). Life on the rocks: Multilocus phylogeography of rock hyrax (Procavia capensis) from southern Africa. Molecular Phylogenetics and Evolution 114, 49–62.
| Life on the rocks: Multilocus phylogeography of rock hyrax (Procavia capensis) from southern Africa.Crossref | GoogleScholarGoogle Scholar | 28411160PubMed |
Mathewson, P. D., Moyer‐Horner, L., Beever, E. A., Briscoe, N. J., Kearney, M., Yahn, J. M., and Porter, W. P. (2017). Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates. Global Change Biology 23, 1048–1064.
| Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates.Crossref | GoogleScholarGoogle Scholar | 27500587PubMed |
McCoy, R. M. (2005). Sampling in the Field. In ‘Field Methods in Remote Sensing’. (Ed. R. M. McCoy.) pp. 12–25. (Guilford Press: New York, NY, USA.)
Menkhorst, P., and Hynes, E. (2011). National Recovery Plan for the Brush-tailed Rock-wallaby Petrogale penicillata. (Department of Sustainability and Environment: Melbourne, Vic., Australia.)
Menon, S., Choudhury, B. I., Khan, M. L., and Peterson, A. T. (2010). Ecological niche modeling and local knowledge predict new populations of Gymnocladus assamicus a critically endangered tree species. Endangered Species Research 11, 175–181.
| Ecological niche modeling and local knowledge predict new populations of Gymnocladus assamicus a critically endangered tree species.Crossref | GoogleScholarGoogle Scholar |
Messner, A. (2005). Youdales Hut, Oxley Wild Rivers National Park. (National Parks and Wildlife Service: Armidale, NSW, Australia.)
Mizsei, E., Üveges, B., Vági, B., Szabolcs, M., Lengyel, S., Pfliegler, W. P., Nagy, Z. T., and Tóth, J. P. (2016). Species distribution modelling leads to the discovery of new populations of one of the least known European snakes, Vipera ursinii graeca, in Albania. Amphibia-Reptilia 37, 55–68.
| Species distribution modelling leads to the discovery of new populations of one of the least known European snakes, Vipera ursinii graeca, in Albania.Crossref | GoogleScholarGoogle Scholar |
Molina, J., Zamora, R., and Silva, F. R. (2019). The role of flagship species in the economic valuation of wildfire impacts: an application to two Mediterranean protected areas. The Science of the Total Environment 675, 520–530.
| The role of flagship species in the economic valuation of wildfire impacts: an application to two Mediterranean protected areas.Crossref | GoogleScholarGoogle Scholar | 31030158PubMed |
Murray, J., Choy, S. L., McAlpine, C., Possingham, H., and Goldizen, A. (2008). The importance of ecological scale for wildlife conservation in naturally fragmented environments: a case study of the brush-tailed rock-wallaby (Petrogale penicillata). Biological Conservation 141, 7–22.
| The importance of ecological scale for wildlife conservation in naturally fragmented environments: a case study of the brush-tailed rock-wallaby (Petrogale penicillata).Crossref | GoogleScholarGoogle Scholar |
Murray, J. V., Goldizen, A. W., O’Leary, R. A., McAlpine, C. A., Possingham, H. P., and Choy, S. L. (2009). How useful is expert opinion for predicting the distribution of a species within and beyond the region of expertise? A case study using brush‐tailed rock‐wallabies Petrogale penicillata. Journal of Applied Ecology 46, 842–851.
| How useful is expert opinion for predicting the distribution of a species within and beyond the region of expertise? A case study using brush‐tailed rock‐wallabies Petrogale penicillata.Crossref | GoogleScholarGoogle Scholar |
Murray, J., Low Choy, S., McAlpine, C., Possingham, H., and Goldizen, A. (2011). Evaluating model transferability for a threatened species to adjacent areas: implications for rock‐wallaby conservation. Austral Ecology 36, 76–89.
| Evaluating model transferability for a threatened species to adjacent areas: implications for rock‐wallaby conservation.Crossref | GoogleScholarGoogle Scholar |
Muscarella, R., Galante, P. J., Soley‐Guardia, M., Boria, R. A., Kass, J. M., Uriarte, M., and Anderson, R. P. (2014). ENM eval: an R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods in Ecology and Evolution 5, 1198–1205.
| ENM eval: an R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models.Crossref | GoogleScholarGoogle Scholar |
O’Leary, R. A., Choy, S. L., Murray, J. V., Kynn, M., Denham, R., Martin, T. G., and Mengersen, K. (2009). Comparison of three expert elicitation methods for logistic regression on predicting the presence of the threatened brush‐tailed rock‐wallaby Petrogale penicillata. Environmetrics 20, 379–398.
Perera, A. H., Drew, A., and Johnson, C. J. (2012). Experts, Expert Knowledge, and Their Roles in Landscape Ecological Applications. In ‘Expert Knowledge and its Application in Landscape Ecology’. (Eds A. H. Perera, A. Drew, and C. J. Johnson.) pp. 1–10. (Springer: New York, NY, USA.)
Phillips, S. J., Dudík, M., and Schapire, R. E. (2004). A maximum entropy approach to species distribution modeling. In ‘Proceedings of the Twenty-First International Conference on Machine Learning’. pp. 655–662. (AAI Press: Banf, Alberta Canada.)
Phillips, S. J., Anderson, R. P., and Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling 190, 231–259.
| Maximum entropy modeling of species geographic distributions.Crossref | GoogleScholarGoogle Scholar |
Piggott, M., Banks, S. C., and Taylor, A. C. (2006). Population structure of brush‐tailed rock‐wallaby (Petrogale penicillata) colonies inferred from analysis of faecal DNA. Molecular Ecology 15, 93–105.
| Population structure of brush‐tailed rock‐wallaby (Petrogale penicillata) colonies inferred from analysis of faecal DNA.Crossref | GoogleScholarGoogle Scholar | 16367833PubMed |
Preau, C., Trochet, A., Bertrand, R., and Isselin-Nondereu, F. (2018). Modeling potential distributions of three European amphibian species comparing ENFA and Maxent. Herpetological Conservation and Biology 13, 91–104.
Radosavljevic, A., and Anderson, R. P. (2014). Making better Maxent models of species distributions: complexity, overfitting and evaluation. Journal of Biogeography 41, 629–643.
| Making better Maxent models of species distributions: complexity, overfitting and evaluation.Crossref | GoogleScholarGoogle Scholar |
Rhoden, C. M., Peterman, W. E., and Taylor, C. A. (2017). Maxent-directed field surveys identify new populations of narrowly endemic habitat specialists. PeerJ 5, e3632.
| Maxent-directed field surveys identify new populations of narrowly endemic habitat specialists.Crossref | GoogleScholarGoogle Scholar | 28785520PubMed |
Sangay, T., Rajanathan, R., Vernes, K., and Tighe, M. (2020). Local knowledge and attitude towards the Vulnerable Bhutan takin Budorcas whitei among residents living within its seasonal range. Oryx 54, 359–365.
| Local knowledge and attitude towards the Vulnerable Bhutan takin Budorcas whitei among residents living within its seasonal range.Crossref | GoogleScholarGoogle Scholar |
Short, J. (1982). Habitat requirements of the brush-tailed rock-wallaby, Petrogale penicillata, in New South Wales. Wildlife Research 9, 239–246.
| Habitat requirements of the brush-tailed rock-wallaby, Petrogale penicillata, in New South Wales.Crossref | GoogleScholarGoogle Scholar |
Skroblin A.Carboon T.Bidu G.Chapman N.Miller M.Taylor K.Taylor W.Game E. T.Wintle B. A. (2019 ).
Soberon, J., and Townsend-Peterson, A. (2005). Interpretation of models of fundamental ecological niches and species’ distributional areas. Biodiversity Informatics 2, 1–10.
| Interpretation of models of fundamental ecological niches and species’ distributional areas.Crossref | GoogleScholarGoogle Scholar |
Soderquist, T. (2011). What we don’t know and haven’t learned about cost–benefit prioritisation of rock-wallaby management. Australian Mammalogy 33, 202–213.
| What we don’t know and haven’t learned about cost–benefit prioritisation of rock-wallaby management.Crossref | GoogleScholarGoogle Scholar |
Sutton, L. J., and Puschendorf, R. (2020). Climatic niche of the Saker Falcon Falco cherrug: predicted new areas to direct population surveys in Central Asia. The Ibis 162, 27–41.
| Climatic niche of the Saker Falcon Falco cherrug: predicted new areas to direct population surveys in Central Asia.Crossref | GoogleScholarGoogle Scholar |
Swets, J. A. (1988). Measuring the accuracy of diagnostic systems. Science 240, 1285–1293.
| Measuring the accuracy of diagnostic systems.Crossref | GoogleScholarGoogle Scholar | 3287615PubMed |
Taggart, D., Schultz, D., Corrigan, T., Schultz, T., Stevens, M., Panther, D., and White, C. (2015). Reintroduction methods and a review of mortality in the brush-tailed rock-wallaby, Grampians National Park, Australia. Australian Journal of Zoology 63, 383–397.
| Reintroduction methods and a review of mortality in the brush-tailed rock-wallaby, Grampians National Park, Australia.Crossref | GoogleScholarGoogle Scholar |
Thapa, A., Wu, R., Hu, Y., Nie, Y., Singh, P. B., Khatiwada, J. R., Yan, L., Gu, X., and Wei, F. (2018). Predicting the potential distribution of the endangered red panda across its entire range using MaxEnt modeling. Ecology and Evolution 8, 10542–10554.
| Predicting the potential distribution of the endangered red panda across its entire range using MaxEnt modeling.Crossref | GoogleScholarGoogle Scholar | 30464826PubMed |
Thapa, A., Hu, Y., Aryal, P. C., Singh, P. B., Shah, K. B., and Wei, F. (2020). The endangered red panda in Himalayas: potential distribution and ecological habitat associates. Global Ecology and Conservation 21, e00890.
| The endangered red panda in Himalayas: potential distribution and ecological habitat associates.Crossref | GoogleScholarGoogle Scholar |
Thinley, P., Norbu, T., Rajaratnam, R., Vernes, K., Wangchuk, K., Choki, K., Tenzin, J., Tenzin, S., Dorji, S., and Wangchuk, T. (2019). Population abundance and distribution of the endangered golden langur (Trachypithecus geei, Khajuria 1956) in Bhutan. Primates 60, 437–448.
| Population abundance and distribution of the endangered golden langur (Trachypithecus geei, Khajuria 1956) in Bhutan.Crossref | GoogleScholarGoogle Scholar | 31376052PubMed |
Thinley, P., Rajaratnam, R., Kamler, J. F., and Wangmo, C. (2021a). Conserving an endangered canid: assessing distribution, habitat protection, and connectivity for the dhole (Cuon alpinus) in Bhutan. Frontiers in Conservation Science 2, 654976.
| Conserving an endangered canid: assessing distribution, habitat protection, and connectivity for the dhole (Cuon alpinus) in Bhutan.Crossref | GoogleScholarGoogle Scholar |
Thinley, P., Rajaratnam, R., Morreale, S. J., and Lassoie, J. P. (2021b). Assessing the adequacy of a protected area network in conserving a wide‐ranging apex predator: the case for tiger (Panthera tigris) conservation in Bhutan. Conservation Science and Practice 3, e318.
| Assessing the adequacy of a protected area network in conserving a wide‐ranging apex predator: the case for tiger (Panthera tigris) conservation in Bhutan.Crossref | GoogleScholarGoogle Scholar |
Triggs, B. (2004). ‘Tracks, scats, and other traces: a field guide to Australian mammals.’ (Oxford University Press: USA.)
van Schingen, M., Ha, Q. Q., Le, T. Q., Nguyen, T. Q., Bonkowski, M., and Ziegler, T. (2020). Discovery of a new crocodile lizard population in Vietnam: population trends, future prognoses and identification of key habitats for conservation. Revue Suisse de Zoologie 123, 241–251.
Veloz, S. D. (2009). Spatially autocorrelated sampling falsely inflates measures of accuracy for presence‐only niche models. Journal of Biogeography 36, 2290–2299.
| Spatially autocorrelated sampling falsely inflates measures of accuracy for presence‐only niche models.Crossref | GoogleScholarGoogle Scholar |
Venables, W., and Ripley, B. (2002). ‘Modern Applied Statistics with S.’ 4th edn. (Springer: New York, NY, USA.)
Volkova, L., Meyer, C. M., Haverd, V., and Weston, C. J. (2018). A data-model fusion methodology for mapping bushfire fuels for smoke emissions forecasting in forested landscapes of south-eastern Australia. Journal of Environmental Management 222, 21–29.
| A data-model fusion methodology for mapping bushfire fuels for smoke emissions forecasting in forested landscapes of south-eastern Australia.Crossref | GoogleScholarGoogle Scholar | 29800860PubMed |
Widodo, F. A., Hartoyo, D., Fadhli, N., Sukmantoro, W., Septayuda, E., and Adzan, G. (2020). Preliminary assessment of abundance and distribution of Dholes Cuon alpinus in Rimbang Baling and Tesso Nilo landscapes, Sumatra. The Raffles Bulletin of Zoology 68, 387–395.
Williams, F. H., Williams, H. F., and Knight, A. (2021). Barriers and benefits to tree kangaroo conservation in Papua New Guinea. Journal for Nature Conservation 60, 125972.
| Barriers and benefits to tree kangaroo conservation in Papua New Guinea.Crossref | GoogleScholarGoogle Scholar |
Woinarski, J., and Burbidge, A. A. (2016). Petrogale penicillata. (The IUCN Red List of Threatened Species.)
Yackulic, C. B., Chandler, R., Zipkin, E. F., Royle, J. A., Nichols, J. D., Campbell Grant, E. H., and Veran, S. (2013). Presence‐only modelling using MAXENT: when can we trust the inferences? Methods in Ecology and Evolution 4, 236–243.
| Presence‐only modelling using MAXENT: when can we trust the inferences?Crossref | GoogleScholarGoogle Scholar |
Young, N., Carter, L., and Evangelista, P. (2011). ‘A MaxEnt model v3. 3.3 e tutorial (ArcGIS v10).’ (Natural Resource Ecology Laboratory and the National Institute of Invasive Species Science: Fort Collins, CO, USA.)