School of Earth, Atmosphere and Environment, Monash University
This case study describes a practical exercise developed for students in the School of Geography and Environmental Science at Monash University. The exercise is based around simple bioclimatic modelling techniques and designed for first-year university students of biogeography, ecology and climatology. It incorporates aspects of past, present and future climates and their impact on species distributions, particularly in Victoria, but could be easily modified to suit any part of Australia.
Climate change is one of the biggest issues facing Australia’s biodiversity. Some of the country’s ecosystems are considered to be particularly vulnerable to increased temperatures and changing rainfall patterns (Laurance et al., 2011) and our species may have to migrate long distances across fragmented landscapes in order to survive (Hughes, 2014). Knowing what will happen to various species and ecosystems is vital to ensuring that conservation and management efforts are applied where they are most needed.
It is also important to increase public awareness of current threats to Australia’s unique biodiversity. A public understanding of the methods scientists use to predict biodiversity changes into the future is a responsibility of scientists. Too often scientific research remains hidden in journals accessible only to academics. Universities have enormous opportunities to influence public engagement in science through their education programmes. This exercise aimed at helping students to create their own bioclimatic models may also give the public insights into how scientists are grappling with the future of Australia’s biodiversity.
The practical exercise has three main parts: the first is on animal distributions under current and future climates; the second concerns plant distributions in the past and present; and the third part looks at how rare and endangered species may respond to future climate change in alpine environments.
The first part focuses on the brushtail possum (Trichosurus vulpecula) and the ringtail possum (Pseudocheirus peregrinus), which are common marsupials in Melbourne backyards and familiar to most students. We use the Atlas of Living Australia (ALA) to examine the possums’ distributions in Australia and compare them to maps of annual mean temperature and annual rainfall (two basic climatic variables, though not necessarily the most important for possum distributions!) Possum distributions are then projected into climate space using the Scatterplot function in the ALA and the students identify the core range of each species. They then modify the temperature and rainfall of Melbourne, Adelaide and Sydney according to climate predictions for 2070 to see whether any of these cities will fall outside the core range of the two possum species by 2070. The students are then asked to use their predictions to decide where to prioritise possum conservation efforts among the three cities.
The second part concerns the Southern Beech (Nothofagus cunninhamii), a long-lived, late-successional tree found in cool-temperate rainforests in southern Australia. We give the students some basic ecological information about this species, along with distribution maps and a table with selected bioclimatic variables for its current range. Students compare the current bioclimate of Nothofagus cunninghamii with that of Buxton, an area where the species apparently went extinct around 6,000 years ago (McKenzie & Busby, 1992). They also compare the current bioclimate to that of Falls Creek, a well-known ski village on the Bogong High Plains. Based on their observations, the students come up with an explanation for the local extinction of beech at Buxton and the reasons why it does not currently live at Falls Creek. This part of the exercise emphasises the potentially important role of palaeoecological data in reconstructing the climates of the past, and also highlights the importance of ecological factors such as dispersal rates and fire sensitivity. The lecture that accompanies the practical exercise also raises the possibility that the intensification of the El Niño Southern Oscillation (ENSO) during the mid-Holocene may have impacted the species.
The final part of the practical exercise relates to two rare or endangered species on the Bogong High Plains: a plant, the Bogong Eyebright (Euphrasia eichleri), and a mammal, the Mountain Pygmy Possum (Burramys parvus). The Bogong High Plains are part of the Australian Alps and include Victoria’s highest peak, Mt Bogong (1986 m). The ALA’s Predict function is employed to create niche models for the two species based on the “best 5 independent terrestrial layers”. Although these layers may not necessarily be the most appropriate for the two species in question, it is an easy introduction for students before experimenting with the 400+ layers available through the ALA (see discussion in Williams et al., 2012). Environmental lapse rates are then introduced and used to predict how a 3 °C temperature rise might impact on species distributions. The students map the current and future ranges of the two species to translate their altitude-based predictions back into geographical space. Finally, the exercise congratulates the next generation of bioclimatic modellers for their efforts and encourages them to think more broadly about non-climatic factors that could be critical to the management of rare and endangered species.
This exercise was introduced to first-year physical geography classes at Monash in 2013 and was well received by students and their demonstrators. Although the practical class could not be held in a dedicated computer lab, students appreciated the option to use their own computer and experiment with the ALA during class time. A handful of students completed the exercise in less than an hour; the remainder completed it within the two hours allocated. There was also a strong link between the lecture material and the practical class, so the relevance of the exercise to the lectures was clear. Most students clearly understood the importance of what they were doing and gained an appreciation of the potentials and pitfalls of bioclimatic modelling. This was reflected in high levels of engagement and high marks for the exercise. On completing the map on the final page of the exercise, one student declared, “Well, I guess that plant is stuffed!” Using the publicly available ALA data and tools empowers students to make their own scientifically informed decisions about biodiversity issues in Australia and encourages independent exploration and experimentation. Despite the simplicity of the practical exercise’s approach to bioclimatic modelling, it lays the groundwork for more sophisticated modelling if students decide to pursue this in later years.
The ALA proved to be an excellent educational tool in this context. Its unique combination of user-friendly interface and powerful modelling capabilities makes it far more amenable to student work than any available alternative. It is difficult to imagine any other application that allows students to create professional-standard distribution maps, bioclimatic scatterplots and niche models so simply, quickly and intuitively. The inclusion of species photo galleries and the possibility of contributing to citizen science data were also attractive to students. Minor drawbacks include the presence of fossil data in the ALA. Such records may be difficult to detect without examining records individually. There are also some noticeable data gaps where agencies have not provided information to the ALA (e.g. brushtail possum records from the Department of Environment and Primary Industry, Victoria – but these records along with many others are in the process of being added).
It is hoped that others will adapt this practical exercise and report back to the ALA with new exercises, improvements, suggestions and tips. The ALA is a tremendous educational resource, so let’s all start talking about how best to use it. The possibilities are only limited by our imagination!
Hughes, L. (2014) Changes to Australian terrestrial biodiversity. In: Christoff, P. (ed.) Four Degrees of Global Warming: Australia in a Hot World. Routledge, Oxon (UK), pp. 63-83.
Laurance, W.F., Dell, B., Turton, S.M., Lawes, M.J., Hutley, L.B., McCallum, H., Dale, P., Bird, M., Hardy, G., Prideaux, G., Gawne, B., McMahon, C.R., Yu, R., Hero, J.-M., Schwarzkopf, L., Krockenberger, A., Douglas, M., Silvester, E., Mahony, M., Vella, K., Saikia, U., Wahren, C.-H., Xu, Z., Smith, B. and Cocklin, C. (2011) The 10 Australian ecosystems most vulnerable to tipping points. Biological Conservation 144: 1472–1480.
McKenzie, G.M. and Busby, J.R. (1992). A quantitative estimate of Holocene climate using a bioclimatic profile of Nothofagus cunninghamii (Hook) Oerst. Journal of Biogeography, 19: 531-540.
Williams K.J., Belbin L., Austin, M.P., Stein, J. and Ferrier, S. (2012). Which environmental variables should I use in my biodiversity model? International Journal of Geographic Information Sciences 26: 2009-2047. http://www.tandfonline.com/doi/pdf/10.1080/13658816.2012.698015