The QAECO & CEBRA lab retreat 2014

QAECO has become quite a large group, and what is the best (and most fun) way for 75 people to get to know each other better?  A lab retreat of course. Earlier this month, we travelled up to Creswick with our friends at the Centre for Excellence for Biosecurity Risk Analysis (CEBRA) for a retreat generously hosted by the School of Ecosystem and Forest Science. Over the course of two days, we arranged social and work-related activities ranging from a hilarious set of speed presentations to discussions addressing equity in Science and a fiercely competitive night of pub trivia.

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A carbon code of conduct is not enough

By Hannah Pearson, Chris Baker, Natalie Briscoe, Laura Pollock and Luke Kelly.

Despite our best efforts, scientists haven’t succeeded in persuading the world’s governments that reducing carbon emissions is vital for maintaining a liveable climate on earth. This might be because we damage our credibility by creating more carbon emissions than average citizens (13). This isn’t exactly the best way to show how much we value reducing carbon emissions and minimising climate change. Favaro (2014) highlighted this issue and proposed a way of reducing scientists’ carbon emissions by going through a carbon-ethics application procedure before undertaking research-related activities. This idea is based around the principles underpinning animal research which require you to minimise and justify the suffering of animal subjects (4).

Favaro’s (2014) recommendation that scientists reduce carbon emissions in all areas of their research is admirable. However, we believe that focussing on the main source of carbon emissions would be more efficient. The majority of scientists’ carbon emissions are produced by travelling to conferences (1, 2). The average conference attendee expends 801kg of carbon in transit (2) (southern hemisphere scientists vastly exceed this average as they have to travel far greater distances to reach conferences). Therefore a conference such as the Ecological Society of America (ESA) Annual Meeting, which is attended by in excess of 7000 scientists generates the more CO2 than a Hummer driving around the world 350 times. This is compounded by many scientists traveling to several international conferences per year, drastically increasing their personal carbon emissions.

It is not surprising that scientists keep traveling to conferences despite the environmental cost. Attending conferences improves productivity (5, 6), scientific networks, and grant applications. These advantages must be maintained to avoid crippling the career advancement of researchers. But we think that there are low emission alternatives which could still provide these benefits. We advocate using advances in web technology to replace (some or all) traditional conferences with online conferences.

Some aspects of conferences could be difficult to replicate online, but online conferences have many benefits including greater scope for personalised programs and more in-depth discussions using online forums and social media (7). These tools encourage greater dialogue between researchers at all career stages.

Bearing in mind that online conferences are relatively untested and may not fully provide the benefits achieved at traditional conferences, we propose that some traditional conferences are retained, at least to begin with. However, it is important that the carbon cost of these conferences is justified by the benefits gained. Despite the potential for convenient networking at traditional (face-to-face) conferences, it is often difficult to identify, locate and approach the people who would be most beneficial. We feel that the carbon-efficiency of conferences could be improved by using social networking apps like SocialRadar and those developed for conferences such as ESA alongside ‘speed networking’ events and social media.

An increase in online conferences, paired with fewer, more effective traditional conferences, could allow the benefits of attending conferences to be maintained while reducing scientists’ carbon footprint. Maybe this will improve our credibility and make our calls for reductions in carbon emissions more compelling? Maybe it won’t? Either way, we will be doing our best to minimise our impact on the world’s climate.

Favaro’s (2014) recommendations have great potential. But their implementation is likely to be slow. As early career researchers, we believe that broader institutional change, such as the increased use of online conferences, is required to effectively reduce scientists’ carbon emissions, while minimising the impact on the career advancement of individual researchers.

If you want to get an idea of how much carbon you’re releasing by travelling to conferences you can visit this site.


1. W. M. J. Achten, J. Almeida, B. Muys, Carbon footprint of science: more than flying. Ecol. Indic. 34, 352–355 (2013).

2. D. Spinellis, P. Louridas, The Carbon Footprint of Conference Papers. PLoS One. 8 (2013).

3. L. Fahrni, Y. Rydin, S. Tunesi, M. Maslin, “Travel related carbon footprint: a case study using the UCL Environment Institute” (London, 2009).

4. B. Favaro, A carbon code of conduct for science. Science (80-. ). 344, 1461 (2014).

5. D. Teodorescu, Correlates of faculty publication productivity: A cross-national analysis. High. Educ. 39, 201–222 (2000).

6. K. Prpic, The publication productivity of young scientists: An empirical study. Scientometrics. 49, 453–490 (2000).

7. iCohere, “Getting it right: five steps to planning a successful 100% online conference” (2013), pp. 0–10.

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Saving the most species at #uomOpenDay

How should you invest $20 million to save the most species from extinction? That was the challenge we put to visitors to The University of Melbourne Open Day. You can take the challenge too!

It is a difficult problem; programs to conserve different species will cost different amounts of money and will have different levels of success.

A difficult choice

Choices, choices… If money is short, do we fund the parrot, the frog, or a bit of both?

We used the paper by Liana Joseph and her colleagues as a case study; we had 32 different species, and the total funding required for all of them cost over $100 million. With only $20 million to spend, we need to find more money to invest in species conservation. But while waiting for Treasury to provide more funds, how do we decide which species to save?

Before reading about the optimal solution, you can try for yourself; please download the Excel spreadsheet here. (The expected success of each program differs, as does the cost. Enter the proportion of each program that you want to fund. Unfortunately, you can’t fund them all – you will have to prioritize. Can you save the most species?)

Hard at work saving the most species. (Photo by Liz Martin:

Working hard to save the most species. (Photo by Liz Martin)

Here is how to construct this as an environmental decision problem; we then use some basic maths to maximize the number of species saved.

Let’s look at the data for the first two species on the spreadsheet we used:

Species Benefit
(Reduction in extinction risk)
Probability of success Cost
Long-tailed bat 0.95 0.21 $6,210,151
North Island brown kiwi 0.95 1.00 $7,910,292

For North Island brown kiwi, the risk of extinction will be reduced by 0.95 if its conservation program is successful. And that particular conservation program is certain to succeed – the probability of success is 1.00. So if it is funded, we’ll improve the expected number of species saved by 0.95.

For the long-tailed bat, the benefit of the conservation program is also 0.95, but the probability of success is only 0.21. So if that is funded, the expected improvement in the number of saved species is only 0.95×0.21 = 0.1995.

The expected benefit of funding the kiwi program is greater, but the long-tailed bat program is cheaper. So which would we prefer to fund?

Well, we simply ask “Which species gives us the best bang for our buck?” That is, we select the option where the expected number of species saved per dollar spent is the greatest.

By multiplying the benefit by the probability of success, and then dividing by the cost, we can rank the options by their relative efficiencies. We fund the species where the relative efficiencies are greatest until we run out of money.

In the example in the Excel spreadsheet, the optimal solution saves just under an extra 7.84 species. You can download that optimal solution here.

This approach to efficient allocation of funding is now being used in New Zealand, and is being adopted in some Australian states. You can read more about it in Liana Joseph’s paper.

Some species might be valued more than others – they might influence the ecology of an area more than others, they might be economically important (e.g., think of the tourism value of koalas), or they might be more evolutionarily distinct. These different factors can be incorporated by modifying the benefit derived from conserving each species.

The benefit of a conservation program might change non-linearly with the level of funding, while this example assumes linear changes. The maths required to solve the non-linear case is more complicated – it requires calculus, but it is not much more complicated than the calculus taught in high schools (email Mick if you want a copy of the paper – this will generate an email, and the automatic response will send you a copy of the paper).

While it is relatively straight-forward to determine the budget for a conservation program, determining the values of saving species and estimating the probability of success can be difficult. If those values are hard to calculate, you might wonder whether this approach is useful. In fact, this approach is particularly useful because it focuses one’s mind on the parameters that need to be determined so that a good decision can be made. We don’t end up worrying about factors that are irrelevant to the decision at hand.

Some might worry that this approach sanitizes the extinction of species – in fact, I think it does the opposite, by making clear that current levels of funding are insufficient. It forces us to calculate how much money is actually required to save species from extinction.

To those who used the spreadsheet at Open Day, thanks for participating. I hope you enjoyed the challenge, and learned a little about some of the things we study at The University of Melbourne. Congratulations to Tim and Sam who figured out the approach to optimizing this particular problem. And thanks to Natasha for organizing everything!

To learn more about using maths to help manage the environment, check out our research centre’s (free) monthly magazine Decision Point.

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Socially-acceptable conservation planning: how can we integrate biological and social values to improve conservation?

By Rachael Vorwerk, Amy Whitehead and Heini Kujala (This article was first published in the July 2014 issue of Decision Point, The Monthly Magazine of the Environmental Decisions Group)

Understanding how society perceives and values different areas is important for effective land-use planning. Making use of social values is arguably one of the most important challenges in modern conservation planning, yet their potential remains poorly exploited. Previous research suggests the inclusion of social values can reduce conflicts between stakeholders and provide more efficient conservation implementation. However, the potential tradeoffs related to incorporating social values into spatial conservation planning are not well understood. These gaps in knowledge led Amy Whitehead and colleagues to investigate methods for integrating social values into spatial conservation planning.

Obtaining social and biological values

The research group collected spatial data on social values by conducting a Public Participation GIS (PPGIS) survey in the Lower Hunter Valley in eastern New South Wales. Local residents were asked to map areas perceived to be important for their natural or potential development values. Randomly-selected landowners were given a map of the region and a set of sticker dots that corresponded to different social values, including biodiversity, natural significance and intrinsic value types (social values for biodiversity). Another set of stickers corresponded to areas believed to be appropriate for different types of future development (social values for development). Participants were asked to place stickers on areas of the map they associated with each of the social values for biodiversity and development. The responses were then digitised and used to create density maps for each social value in the region.

In addition to social values data, the researchers used biological data to represent areas important for conservation. Seven fauna species considered to be vulnerable to land clearance were selected to represent the biological values in the Lower Hunter Valley. These species were mapped onto the landscape using species distribution models, derived from occurrence data.

Integrating social and biological values in conservation planning

The spatial prioritisation of the Lower Hunter Valley was done using Zonation, a commonly-used tool in conservation planning. The program ranks sites in the landscape based on their importance for all features in the model, producing a spatially-explicit output that identifies areas of high value. Zonation is typically used with biological data to identify areas of high conservation value but any spatially-explicit variable of interest, such as social values, can be included.

The researchers first examined three scenarios that identified priority areas for each of the datasets. The top 30% of each individual prioritisation was overlaid on the other prioritisations to identify potential areas of synergy or conflict. Identifying these areas spatially allows decision makers to target specific actions and policies depending on biological and social values (Figure 1). For example, an area with high biodiversity values and high community awareness for its natural significance (2) may require a different strategy to one with conflicts between high biodiversity values and a perceived suitability for future development (6).

Figure 1. Overlaying the top priority areas from biological values and social values for biodiversity and development allows decision makers to identify potential areas of synergy or conflict between the different value sets.  Each combination requires a specific type of management action and may require further community engagement or specific policy implementation to ensure socially-acceptable conservation outcomes.

Figure 1. Overlaying the top priority areas from biological values and social values for biodiversity and development allows decision makers to identify potential areas of synergy or conflict between the different value sets. Each combination requires a specific type of management action and may require further community engagement or specific policy implementation to ensure socially-acceptable conservation outcomes.

The next step was to integrate the three datasets into spatial prioritisations to examine whether the inclusion of social values for biodiversity and development would come at the cost of trading off actual biological values. The researchers investigated six integrated prioritisation scenarios that explored different methods of integration. Social values for biodiversity were either included as features in the prioritisation together with the biological data, or as a cost layer where the priority areas were pushed towards those areas that the community perceived as having high biodiversity value. Social values for development were either included as a cost layer where the solution was guided away from areas considered to be important for future development, or as a mask where the top 30% of the high priority areas for development were forced out of the conservation solution.

Identifying socially-acceptable conservation areas

Not surprisingly, the best option for conserving of the seven threatened species included in the model was obtained when the prioritisation only considered biological data (Figure 2). Interestingly however, a similar proportion of each species’ current distribution was captured when biological and social values for biodiversity were integrated and prioritised together, although the spatial location of some conservation areas changed. Even when the areas perceived to be most important for development were forced out and the remaining sites were prioritised for both biological and social values for biodiversity, Zonation still managed to find a solution that gave reasonable protection to the seven fauna species. This is good news for planners as it demonstrates spatial flexibility in the way conservation targets may be met in the Lower Hunter Valley. However, it is important to note that some of this flexibility might stem from the type and number of species used in the study; all seven species are forest dwellers and people often perceive forests as more valuable natural areas than, for example, grasslands. The integration of biological and social values may result in greater tradeoffs if a more diverse set of habitats or species were included.

This is one of the first studies to fully integrate spatially-explicit biological and social values into a quantitative spatial prioritisation analysis, providing a simple method to achieve both socially-acceptable and scientifically-defensible conservation outcomes. Such an approach can help decision makers target communication strategies and management actions to specific areas of the landscape, while integrated prioritisations can identify balanced conservation solutions that protect biodiversity and incorporate societal values. Although this approach may create an extra level of complexity for conservation planners, it offers the potential to improve conservation outcomes in contested landscapes.

Figure 2. Researchers evaluated the effectiveness of different spatial prioritisation scenarios by isolating the top 30% of each value (biological or social). Six of the seven species’ distributions in the Lower Hunter Valley, NSW, were best represented when the prioritisation only included biological values, while all species were less protected when prioritising social values for biodiversity alone. In contrast, the prioritisation of both biological and social values identified areas for conservation that were socially acceptable and did not lead to significant tradeoffs in conservation value.

Figure 2. Researchers evaluated the effectiveness of different spatial prioritisation scenarios by isolating the top 30% of each value (biological or social). Six of the seven species’ distributions in the Lower Hunter Valley, NSW, were best represented when the prioritisation only included biological values, while all species were less protected when prioritising social values for biodiversity alone. In contrast, the prioritisation of both biological and social values identified areas for conservation that were socially acceptable and did not lead to significant tradeoffs in conservation value.


Whitehead, A.L., Kujala, H., Ives, C., Gordon, A., Lentini, P.E., Wintle, B.A., Nicholson, E., Raymond, C.M., 2014. Integrating biological and social values when prioritizing for biodiversity conservation. Conservation Biology 28: 992-1003. doi: 10.1111/cobi.12257

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Qaecologists presenting at the International Statistical Ecology Conference, Montpellier 2014

So it is going to be another quiet winter in the QAECO lab. A whole bunch of us will be migrating north to Europe and other warmer climes. For many the first staging post will be the south of France [sigh], for the International Statistical Ecology Conference in Montpellier to be held next week (1-4 of July). Here is a list of the keen qaecologists presenting their work during the conference.

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Halting the spread of cane toads

By Reid TingleyDarren Southwell

Cane toads are one of the worst invasive species in Australia. Introduced to Queensland in 1935 as a biological control agent, the toads have spread at a formidable pace across northern Australia, and have had major impacts on native predators such as goannas, quolls, and freshwater crocodiles. The toads have now reached the Kimberley and there is no sign that their conquest is nearing completion. Toads seem invincible. But are there any chinks in their armour that might help us control their spread? Researchers from QAECO are currently attempting to answer precisely this question.

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Choose your cake and eat it too: A very QAECO morning tea

By Natasha Cadenhead

How do academics forage at morning tea? Do sweets go extinct faster than savouries? Which cake should you eat? How much should you eat? How close should you be to the coffee? The exit?

Yesterday we hosted a structured decision making themed morning tea for staff and students in the School of Botany at The University of Melbourne. Each month one of the research groups in the school provides tea, coffee and delicious baked goods for everyone else. It’s a great chance to get to know people you pass in the hallways every day and learn about research going on in other groups. Continue reading

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