Spatial prediction of brushtail possum (Trichosurus vulpecula) distribution using a combination of remotely sensed and field-observed environmental data
Thibaud Porphyre A D , Joanna McKenzie A , Andrea E. Byrom B , Graham Nugent B E , James Shepherd C and Ivor Yockney BA EpiCentre, Massey University, Private Bag 11222, Palmerston North 4442, New Zealand.
B Landcare Research, PO Box 69, Lincoln 8152, New Zealand.
C Landcare Research, Private Bag 11052, Palmerston North 4442, New Zealand.
D Present address: Epidemiology Group, Centre for Immunity, Infection and Evolution, University of Edinburgh, Ashworth Laboratories, Edinburgh, United Kingdom.
E Corresponding author. Email: nugentg@landcareresearch.co.nz
Wildlife Research 40(7) 578-587 https://doi.org/10.1071/WR13028
Submitted: 12 February 2013 Accepted: 25 November 2013 Published: 23 December 2013
Abstract
Context: In New Zealand, the introduced brushtail possum, Trichosurus vulpecula, is a reservoir of bovine tuberculosis and as such poses a major threat to the livestock industry. Aerial 1080 poisoning is an important tool for possum control but is expensive, creating an ongoing need for ever more cost-effective ways of using this technique.
Aims: To develop geographic information system (GIS) models to better predict spatial variation in the distribution of unmanaged possum populations, to facilitate better targeting of control activities.
Methods: Relative abundance of possums and their distribution among habitat types were surveyed in a dry high-country area of the northern South Island. Two GIS-based models were developed to predict the relative abundance of possums on trap lines. The first model used remotely sensed (digital) environmental data; the second complemented the remotely sensed data with fine-scale habitat and topographic data collected on the ground.
Key results: Digital environmental factors and habitat features proved to be key predictors of relative possum abundance. In both GIS models, height above valley floor, presence of forest cover and mean annual temperature were the strongest predictors.
Conclusions: Predictive maps (projections) of relative possum abundance produced from these models can provide useful decision-support tools for pest-control managers, by enabling possum control to be targeted spatially.
Implications: Spatially targeted pest control could allow effective control activities for invasive species or disease vectors to be applied at a lower cost for the same benefit.
Additional keywords: disease management, invasive species, predictive map, relative abundance, spatial modeling, spatially targeted control, species distribution, vertebrate pest.
References
Anonymous, (1986). Cattle tuberculosis – history of TB control scheme. Surveillance 13, 4–8.Boone, R. B., and Krohn, W. B. (2002). Modeling tools and accuracy assessment. In ‘Predicting Species Occurrences: Issues of Accuracy and Scale’. (Eds J. M. Scott, P. J. Heglund, M. L. Morrison, J. B. Haufler, M. G. Raphael, W. A. Wall and F. B. Samson.) pp. 265–270. (Island Press: Washington, DC.)
Bouyer, J., Guerrini, L., Desquesnes, M., de la Rocque, S., and Cuisance, D. (2006). Mapping African animal trypanosomosis risk from the sky. Veterinary Research 37, 633–645.
| Mapping African animal trypanosomosis risk from the sky.Crossref | GoogleScholarGoogle Scholar | 16777035PubMed |
Byrom, A. E., Nugent, G., Porphyre, T., Poutu, N., Shepherd, J., Whitford, J., and Yockney, I. (2008). Cost effective control of Tb in the northern South Island high country: identifying the habitats and vector species requiring control. Landcare Research contract report LC0708/110, Lincoln, New Zealand.
Clements, A. C. A., Pfeiffer, D. U., and Martin, V. (2006). Application of knowledge-driven spatial modelling approaches and uncertainty management to a study of Rift Valley fever in Africa. International Journal of Health Geographics 5, 57.
| Application of knowledge-driven spatial modelling approaches and uncertainty management to a study of Rift Valley fever in Africa.Crossref | GoogleScholarGoogle Scholar |
Dymond, J., and Shepherd, J. (2004). The spatial distribution of indigenous forest and its composition in the Wellington region, New Zealand, from ETM+ satellite imagery. Remote Sensing of Environment 90, 116–125.
| The spatial distribution of indigenous forest and its composition in the Wellington region, New Zealand, from ETM+ satellite imagery.Crossref | GoogleScholarGoogle Scholar |
Efford, M. (2000). Possum density, population structure, and dynamics. In ‘The Brushtail Possum: Biology, Impact and Management of an Introduced Marsupial’. (Ed. T. Montague.) pp. 47–61. (Manaaki Whenua Press: Lincoln, New Zealand.)
Fielding, A. H. (2002). What are the appropriate characteristics of an accuracy measure? In ‘Predicting Species Occurrences: Issues of Accuracy and Scale’. (Eds J. M. Scott, P. J. Heglund, M. L. Morrison, J. B. Haufler, M. G. Raphael, W. A. Wall and F. B. Samson.) pp. 271–281. (Island Press: Washington, DC.)
Fraser, K. W., Overton, J. M., Warburton, B., and Rutledge, D. T. (2004). ‘Predicting Spatial Patterns of Animal Pest Abundance: a Case Study of the Brushtail Possum (Trichosurus vulpecula). Science for Conservation Publication Series 236.’ (Department of Conservation: Wellington, New Zealand.)
Gauch, H. G., Hwang, J. T. G., and Fick, G. W. (2003). Model evaluation by comparison of model-based predictions and measured values. Agronomy Journal 95, 1442–1446.
| Model evaluation by comparison of model-based predictions and measured values.Crossref | GoogleScholarGoogle Scholar |
Glen, A. S., Byrom, A. E., Pech, R. P., Cruz, J., Schwab, A., Sweetapple, P. J., Yockney, I., Nugent, G., Coleman, M., and Whitford, J. (2012). Ecology of brushtail possums in a New Zealand dryland ecosystem. New Zealand Journal of Ecology 36, 29–36.
Gormley, A. M., Holland, E. P., Pech, R. P., Thomson, C., and Reddiex, B. (2012). Impacts of an invasive herbivore on indigenous forests. Journal of Applied Ecology 49, 1296–1305.
| Impacts of an invasive herbivore on indigenous forests.Crossref | GoogleScholarGoogle Scholar |
Hall, L. S., and Mannan, R. W. (1999). Multiscaled habitat selection by elegant trogons in southeastern Arizona. The Journal of Wildlife Management 63, 451–461.
| Multiscaled habitat selection by elegant trogons in southeastern Arizona.Crossref | GoogleScholarGoogle Scholar |
Hastie, T., and Tibshirani, R. (1995). Generalized additive models for medical research. Statistical Methods in Medical Research 4, 187–196.
| Generalized additive models for medical research.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaK287hvVSrsg%3D%3D&md5=fea04257ca9c08ef3e66fb74be983220CAS | 8548102PubMed |
Heglund, P. J. (2002). Foundations of species-environment relations. In ‘Predicting Species Occurrences’. (Eds J. M. Scott, P. J. Heglund, M. L. Morrison, J. B. Haufler, M. G. Raphael, W. A. Wall and F. B. Simon.) pp. 35–41. (Island Press: Washington, DC.)
Hutchings, S., Hancox, N., and Livingstone, P. (2011). Approaches to eradication of tuberculosis from wildlife in New Zealand: a revised pest management strategy. Vetscript 24, 8–12.
Isaacs, E., and Srivistava, R. (1989). ‘Introduction to Applied Geostatistics.’ (Oxford University Press: London.)
Lamb, D. S., Saalfeld, W. K., McGregor, M. J., Edwards, G. P., Zeng, B., and Vaarzon-Morel, P. (2010). GIS-based decision-making structure for managing the impacts of feral camels in Australia. The Rangeland Journal 32, 129–143.
| GIS-based decision-making structure for managing the impacts of feral camels in Australia.Crossref | GoogleScholarGoogle Scholar |
Leathwick, J., Wilson, G., Rutledge, D., Wardle, P., Morgan, F., Johnston, K., McLeod, M., and Kirkpatrick, R. (2003). ‘Land Environments of New Zealand.’ (David Bateman: Auckland.)
Luck, G. W. (2002a). The habitat requirements of the rufous treecreeper (Climacteris rufa). 1. Preferential habitat use demonstrated at multiple spatial scales. Biological Conservation 105, 383–394.
| The habitat requirements of the rufous treecreeper (Climacteris rufa). 1. Preferential habitat use demonstrated at multiple spatial scales.Crossref | GoogleScholarGoogle Scholar |
Luck, G. W. (2002b). The habitat requirements of the rufous treecreeper (Climacteris rufa). 2. Validating predictive habitat models. Biological Conservation 105, 395–403.
| The habitat requirements of the rufous treecreeper (Climacteris rufa). 2. Validating predictive habitat models.Crossref | GoogleScholarGoogle Scholar |
McKenzie, J. S. (2004). The use of GIS in the management of wildlife diseases. In ‘GIS and Spatial Analysis in Veterinary Science’. (Eds P. A. Durr and A. C. Gatrell.) pp. 249–283. (CABI Publishing: Wallingford, UK.)
McKenzie, J., and Meenken, D. (2001). Spatial clustering of low-density possum populations and association with habitat. Animal Health Board Contractual report prepared by the EpiCentre, Massey University, in collaboration with Wellington Regional Council, Wellington, New Zealand. Availabe at www.ahb.org.nz [verified June 2013].
Monks, A., and Tompkins, D. M. (2012). Optimising bait-station delivery of population-control agents to brushtail possums: field test of spatial model predictions. Wildlife Research 39, 62–69.
| Optimising bait-station delivery of population-control agents to brushtail possums: field test of spatial model predictions.Crossref | GoogleScholarGoogle Scholar |
Montague, T., and Warburton, B. (2000). Non-toxic techniques for possum control. In ‘The Brushtail Possum: Biology, Impact and Management of an Introduced Marsupial’. (Ed. T Montague.) pp. 164–174. (Manaaki Whenua Press: Lincoln, New Zealand.)
Morris, R. S., Pfeiffer, D. U., and Jackson, R. (1994). The epidemiology of Mycobacterium bovis infections. Veterinary Microbiology 40, 153–177.
| 1:STN:280:DyaK2czltlKhtA%3D%3D&md5=cd6c53a04be7be11dcfa70c59322ab78CAS | 8073623PubMed |
Nugent, G., Whitford, J., and Young, N. (2002). Use of released pigs as sentinels for Mycobacterium bovis. Journal of Wildlife Diseases 38, 665–677.
| Use of released pigs as sentinels for Mycobacterium bovis.Crossref | GoogleScholarGoogle Scholar | 12528431PubMed |
Nugent, G, Buddle, BM, and Knowles, GK (2013). The pathogenesis, epidemiology, and response to host control of Mycobacterium bovis infection in the primary wildlife reservoir of bovine tuberculosis in New Zealand, the brushtail possum (Trichosurus vulpecula). New Zealand Veterinary Journal , .
R Development Core Team (2012). ‘R: a Language Environment for Statistical Computing. Version 2.13.0.’ (R Foundation for Statistical Computing: Vienna.)
Ramsey, D., and Ball, S. (2004). ‘Statistical Limits of RTCI Monitoring.’ (Animal Health Board Ltd: Wellington, New Zealand.)
Rouco, C., Norbury, G. L., Smith, J., Byrom, A. E., and Pech, R. P. (2013). Population density estimates of brushtail possums (Trichosurus vulpecula) on open dry grassland in New Zealand. New Zealand Journal of Ecology 37, 12–17.
Sadleir, R. (2000). Evidence of possums as predators of native animals. In ‘The Brushtail Possum: Biology, Impact and Management of an Introduced Marsupial’. (Ed. T. Montague.) pp. 126–131. (Manaaki Whenua Press: Lincoln, New Zealand.)
Yockney, I., Nugent, G., Arienti, C., Perry, M., Cross, M. L., and Byrom, A. E. (2013). Comparison of ranging behaviour in a multi-species complex of free-ranging hosts of bovine tuberculosis in relation to their use as disease sentinels. Epidemiology and Infection 141, 1407–1416.
| Comparison of ranging behaviour in a multi-species complex of free-ranging hosts of bovine tuberculosis in relation to their use as disease sentinels.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC3svgsFyltQ%3D%3D&md5=7970d15fee84d6bcf5291d15cdaab80fCAS | 23433406PubMed |
