Congratulations to Jane Elith, who tonight will be awarded the Frank Fenner Prize for Life Scientist of the Year, an early career award within the Prime Minister’s Prizes for Science. Jane is recognised as one of the world’s leading ecologists for her work on species distribution modelling.
Understanding factors that influence the distribution of species is fundamental to ecology, and species distribution models provide important tools for that purpose. In addition to informing basic ecology, these models are used increasingly to support environmental management actions that rely on predicting the distribution of species (e.g., management of threatened and invasive species). Jane’s research has produced guides to methods [1:4], developed and extended methods appropriate for typical data types [5:10], and tested methods and explored their uncertainties [11:19].
Jane Elith’s research career is remarkable in part because she has achieved her success in a relatively short time – only about 10 years full-time equivalent since completing her PhD. She had no research experience prior to her PhD, following two previous careers – one in agricultural science and one as a full-time mother.
Since completing her PhD, Jane has become Australia’s most cited ecologist/environmental scientist in the last 10 years (as reported by Thomson-Reuters). This is particularly impressive given that in terms of citations, the field of Environment/Ecology is Australia’s strongest discipline – of the world’s most highly-cited scientists in Environment/Ecology, more than 8% are Australian. This proportion is the most of all Thomson-Reuters’ 21 research categories.
And perhaps it is worth noting that while heading the list of Australia’s most cited scientists in Environment/Ecology, Jane is the most junior scientist and the only woman of the 11 people in that list.
Australia is a world leader in Environment/Ecology, and Jane Elith contributes substantially to our reputation in this area. Congratulations to Jane – the prize is well deserved and we are very proud of her achievements.
1. Elith, J., Phillips, S.J., Hastie, T., Dudík, M., Chee, Y.E. & Yates, C.J. (2011) A statistical explanation of MaxEnt for ecologists. Diversity and Distributions, 17, 43-57.
2. Elith, J., Leathwick, J.R. & Hastie, T. (2008) A working guide to boosted regression trees. Journal of Animal Ecology, 77, 802-813.
3. Elith, J. & Leathwick, J.R. (2007) Predicting species distributions from museum and herbarium records using multiresponse models fitted with multivariate adaptive regression splines. Diversity and Distributions, 13, 165-175.
4. Wintle, B.A., Elith, J. & Potts, J. (2005) Fauna habitat modelling and mapping in an urbanising environment; A case study in the Lower Hunter Central Coast region of NSW. Austral Ecology, 30, 719-738.
5. Fithian, W., Elith, J., Hastie, T. & Keith, D. (2015, in press) Bias correction in species distribution models: pooling survey and collection data for multiple species. Methods in Ecology and Evolution.
6. Renner, I.W., Elith, J., Baddeley, A., Fithian, W., Hastie, T., Phillips, S., Popovic, G. & Warton, D. (2015, in press) Point process models for presence-only analysis: a review. Methods in Ecology and Evolution.
7. Guillera-Arroita, G., Lahoz-Monfort, J.J. & Elith, J. (2014) Maxent is not a presence-absence method: a comment on Thibaud et al. Methods in Ecology and Evolution, 5, 1192-1197.
8. Phillips, S.J. & Elith, J. (2013) On estimating probability of presence from use-availability or presence-background data. Ecology, 94, 1409-1419.
9. Ward, G., Hastie, T., Barry, S.C., Elith, J. & Leathwick, J.R. (2009) Presence-only data and the EM algorithm. Biometrics, 65, 554-563.
10. Phillips, S.J., Dudík, M., Elith, J., Graham, C.H., Lehmann, A., Leathwick, J. & Ferrier, S. (2009) Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecological Applications, 19, 181-197.
11. Elith, J., Kearney, M. & Phillips, S.J. (2010) The art of modelling range-shifting species. Methods in Ecology and Evolution, 1, 330-342.
12. Elith, J. & Graham, C. (2009) Do they? How do they? WHY do they differ? — on finding reasons for differing performances of species distribution models. Ecography, 32, 66-77.
13. Potts, J. & Elith, J. (2006) Comparing species abundance models. Ecological Modelling, 199, 153-163.
14. Elith, J. et al. (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography, 29, 129-151.
15. Elith, J., Ferrier, S., Huettmann, F. & Leathwick, J.R. (2005) The evaluation strip: a new and robust method for plotting predicted responses from species distribution models. Ecological Modelling, 186, 280-289.
16. Moilanen, A., Wintle, B., Elith, J. & Burgman, M. (2006) Uncertainty analysis for regional-scale reserve selection. Conservation Biology, 20, 1688-1697.
17. Moilanen, A., Runge, M.C., Elith, J., Tyre, D., Carmel, Y., Fegraus, E., Wintle, B., Burgman, M. & Ben-Haim, Y. (2006) Planning for robust reserve networks using uncertainty analysis. Ecological Modelling, 199, 115-124.
18. Barry, S.C. & Elith, J. (2006) Error and uncertainty in habitat models. Journal of Applied Ecology, 43, 413-423.
19. Elith, J., Burgman, M.A. & Regan, H.M. (2002) Mapping epistemic uncertainties and vague concepts in predictions of species distribution. Ecological Modelling, 157, 313-329.