Before she went on a science and maths camp, 19-year-old Tayla Macdonald says, she didn’t have a huge interest in science. She wanted to be a journalist.
But the camp made science significant and meaningful to her, and to her family’s Aboriginal roots. Tailored for Indigenous students, the camp blended science with Aboriginal culture, involving fieldwork and activities at culturally significant sites.
‘The camp gave me the belief that a science degree could be possible and that perhaps it wouldn’t be as difficult as I thought it was. I felt like it opened up new possibilities and choices I hadn’t considered before,’ says Tayla.
Three years later and Tayla is studying medical science, hoping to specialise in paediatrics and work either in regional communities or in humanitarian aid.
Initiatives like this are important, because Aboriginal and Torres Strait Islander students’ participation in science, technology, engineering and mathematics subjects at university and in related professions is significantly lower than the Australian average.
Alarmingly, an international survey showed that, overall, Aboriginal and Torres Strait Islander students are around two-and-a-half years behind their peers in scientific and mathematical literacy, and this gap has remained the same over ten years.
The reasons for this are complex, but our research shows that tailored learning programs can make a real difference.
That’s why we’ve partnered with BHP Billiton Foundation to deliver a new education project for Aboriginal and Torres Strait Islander students that aims to increase their participation and achievement in science, technology, engineering and mathematics (also known as STEM).
The five-year project is expected to involve Aboriginal students from all states and territories, from primary school through to tertiary education. It will cater to the diversity of learners – from those in remote communities through to high-achieving students attending mainstream schools.
Our research shows that community engagement, learning on-country and long-term investment and collaboration are vital for improving Indigenous education outcomes in science and maths subjects.
We’ve designed the project incorporating these elements, along with hands-on, inquiry-based learning approaches. There’s an awards program to recognise and reward high-achieving students.
This tailored approach will provide students with the learning setting and support they need for their best chance to achieve.
We hope students who participate in the program will consider taking up a career in science, just like Tayla.
Read more about our education program for Aboriginal and Torres Strait Islanders.
Biological illustration has come on a bit from the days of Gould’s gorgeous illustrations of birds, or Leonardo’s Vitruvian Man. Today, with the help of big data and big graphics power, we can visualise things, not just at the molecular level, but at work.
But why – apart from because it’s beautiful and fascinating – do we do it? How is it helpful? What can it show us?
Obviously, we’ve been using rudimentary data visualisation for a very long time. Charts, maps, tables, graphs. All data visualisations, but not at the level we now find ourselves working at. As Sean O’Donoghue, from our Digital Productivity and Services Flagship, puts it, ‘Data visualisation is a new visual language; we need to become fluent in it to manage the complexity of computational biology’.
Let’s think about genomic data. The more we know, the more we need new tools to deal with the knowledge we have. And we now know a lot. We’ve got the ability to generate tremendous amounts of genomic data from sequencing. Analysing that data is now the roadblock to our being able to convert what we’ve found into something useable.
Obviously, some genome analysis can be done using automated processes. But that still leaves a lot that depends on human judgement, particularly in the early stages such as hypothesis formation. Our concentration – and eyes – frankly aren’t up to spotting something different in a field of As, Cs, Gs and Ts (and nothing else), that seems to go on forever. Think of Where’s Wally?, in monochrome, with one Wally hidden on a single page hundreds of times larger than book pages. And then imagine that finding the Wally you’re looking for could make a big difference to people’s lives.
If we can combine visual and automated analysis, the pairing becomes more powerful. Users can user can seamlessly look at their data and perform computations on it, refining their analysis with each step.
Visualising also helps us reason about complex data. Sometimes, a well-chosen visualisation can make the solution to a complex problem immediately obvious. That’s because of the way that visual representations simultaneously engage the eyes and the memory. When we look at a visual, our eyes and our brain work in parallel to take in new information, and break it into small chunks. Then both the eyes and the brain process the bits in their different ways to extract meaning. It works like this.
You’ve gone to the supermarket – not your usual one – to buy bananas. When you walk in, your eyes scan the layout. At the same time, your brain is processing the various sections of the layout, and telling your eyes to home in on the fruit and veg section. It does this by sending signals from memory about how fruits look. Your eyes then break the entire scanned area into parts, then scan each part until they (all but instantly) recognise the veggie section. The same process is repeated until you spot the bananas in the fruits section. Your eyes and memory do their own things but work in parallel.
We’ve used our brains to build tools that can help us discover more and more. But making sense of what they’ve found still depends on us and our limitations. Around half of the human brain is devoted – directly or indirectly – to vision. Visualising the vast streams of data lets us work with what we’ve got to make it something more than a hunt for a tiny needle in a monstrous haystack.
If you want to see more data visualisations, there are some beautiful ones at Vizbi.
We’re certainly not counting any chickens. The champagne is definitely not on the ice. But there could be a few crossed fingers here and there. You might have seen a story going the rounds that three of our scientists are contenders for a Nobel Prize.
So we thought you might like to know more about the science that won them this level of respect.
Ezio Rizzardo, Graeme Moad and San Thang developed RAFT – Reversible Addition-Fragmentation chain Transfer – polymerisation. This is a method of producing the synthetic polymers (AKA plastics) that we use every day.
What makes it outstanding is that it allows chemists to produce polymers with defined properties and a chemical structure tailored to order. Before RAFT, making polymers was an inexact science. Using RAFT means chemists can have precise control over the way in which small molecules link together to form long polymer chains. They can now design the exact polymer to fit the purpose. The result is a whole new generation of polymeric materials.
Now, a new generation of plastics doesn’t sound too exciting. But it is.
Not only does it mean existing polymer-based products and devices will perform better, it also opens up new fields. There are a large number of possible new applications in areas like engineering materials, electronics, healthcare and biotechnology. And that’s only the ones we’ve already thought of. This is the kind of technology that can create fields that haven’t been thought of yet.
One of RAFT’s big hits so far is for creating OLEDs (organic light-emitting diodes), that can produce low-cost power-efficient lighting.
RAFT polymers also form the backbone of the printable solar cells we’re so thrilled about.
See, we told you plastic could be exciting.
By Fiona Brown
Wondering who’s going to win the AFL grand final on the weekend? We were too, so we did what scientists do best and undertook some research to predict whether it will be the Swans or the Hawks taking home the cup on Saturday afternoon. This is what we found.
In favour of the swans is their size and weight. They are among the largest flying birds, with a wingspan of up to 3 metres and weighing in at up to a solid 15 kg. Compared with the hawk*, which has a wingspan of around 95 centimetres and is lucky to tip the scales at 355 grams, we’re guessing that the Swans will surely have the advantage when it comes to tackling.
However, when it comes to speed, is all that extra weight going to slow the Swans down? If you’ve ever seen a swan walk, you’ll know the answer to this one – yes. Swans are clumsy walkers, moving at slow speeds on dry land thanks to their short legs and large bodies. In contrast, hawks have relatively long legs for birds and will sometimes be seen stalking prey by running along the ground. The Swans will need to be careful that the Hawks don’t literally run away with the game.
Interestingly, in the air it’s not quite so clear cut as to who has the advantage – swans have the speed but hawks have better agility. The top speed of a Mute Swan** is claimed to be around 85 km/h, whereas when in pursuit of prey the hawk is reported to only reach speeds of up to 61 km/h. However, hawks are highly agile in flight, able to power through very small gaps in the canopy without colliding with branches. They use this ability to hunt, so are well-practised at using sudden, short bursts of speed to spring from a concealed perch, surprising unsuspecting prey. The take-home message? Watch out for some great marks!
Another key factor in predicting who will win any sporting match is the elusive team spirit. Who has the drive and aggression to get the job done? Which team will come together when it matters most? When it comes to aggression, both birds have pretty nasty reputations. Swans will aggressively protect their nests and young, using their size and powerful wings to ward off would-be predators (including humans). Hawks will also aggressively defend their territory, and they don’t get the title ‘bird of prey’ for nothing. They prey mainly upon other small to medium sized birds (including crows and magpies, which could explain Hawthorn’s defeat of Adelaide and Collingwood earlier in the season), but also eat mammals, amphibians, reptiles and occasionally insects. However, when it comes to commitment to the team, the Swans have it in the bag, with adult swans usually mating for life.
And lastly, what about the all-important weather forecast? With our friends at the Bureau of Meteorology predicting showers in Melbourne over the next couple of days and drizzle on Saturday morning, the G could be a bit damp under foot, which might be an advantage if those feet are webbed…!
Okay, so our ‘research’ might not be the most accurate method of predicting who’ll win the big game, but we definitely learnt something about our Australian feathered friends, and as Paul the Octopus clearly demonstrated, animals shouldn’t be dismissed when it comes to predicting results of football matches.
If you’d like to learn more about hawks, swans or any other Australian species for that matter, check out the Australia’s species page on the Atlas of Living Australia.
*Information about the hawks is based on our assumption that ‘hawk’ is short for ‘Brown Goshawk’, as this species of hawk has a brown head and body, yellow legs, and bright yellow eyes.
**The Swan’s mascot is based on the white species of swan found in Australia, which is the Mute Swan.
It’s no secret that mining is important to Australia, but that doesn’t necessarily make it popular with society at large.
We wanted to have a better understanding of what Australians think about mining, so in 2013/14 we conducted an online survey of 5,121 Australians.
The survey results have now been published as Australian attitudes toward mining: Citizen Survey – 2014 Results
Surveying community attitudes helps us to understand the impacts and benefits of mining, and how the relationship between the mining industry, government and society affects what Australia’s citizens think about it, and how much they accept the mining industry. It gives us insight into what needs to happen before mining has a ‘social licence to operate’ in Australia.
We’ve gone beyond basic descriptions of attitudes towards the extractive industries, and looked at the relationship between mining and society in a more constructive and sophisticated way.
We wanted to know what goes into influencing trust in the mining industries, and the government, over mining developments. What, for example, is the relationship between good governance and social acceptance of the extractive industries? What are the key issues for a productive dialogue between the extractive industries and other stakeholders?
Some of the important findings from the survey are that:
- People view mining as central and significant to Australia’s economy and standard of living. They see it as a ‘necessary’ industry for Australia, which is important to Australia’s future prosperity
- Australians generally understand what it means to have a significant mining industry. Overall, they think that at present the benefits of mining outweigh its impacts.
- The more the benefits of mining outweigh the costs, the higher the level of acceptance. If this balance is perceived to move toward the negative impacts of mining, acceptance of mining will be eroded.
- Australians trust and accept the industry more when they believe the industry is listening to them and will respond to their concerns, when benefits from mining are shared equitably, and when the legislative and regulatory frameworks in place make them confident that industry will do the right thing.
- Governments and industry need to work with communities to earn and maintain the ‘social licence to operate’ and develop effective, constructive, mutually beneficial relationships.
As heads of state gather in New York for tomorrow’s United Nations climate summit, a new report on the state of the world’s carbon budget tells them that greenhouse emissions hit a new record last year, and are still growing.
It shows that global emissions from burning fossil fuels and cement production reached a new record of 36 billion tonnes of CO2 in 2013, and are predicted to grow by a further 2.5% in 2014, bringing the total CO2 emissions from all sources to more than 40 billion tonnes. This is about 65% more fossil-fuel emission than in 1990, when international negotiations to reduce emissions to address climate change began.
Meanwhile, deforestation now accounts for just 8% of total emissions, a fraction that has been declining for several decades.
The growth of global emissions since 2009 has been slower than in the prior period of 2000-08. However, projections based on forecast growth in global gross domestic product (GDP) and continuance of improving trends in carbon intensity (emissions per unit of GDP) suggest a continuation of rapid emissions growth over the coming five years.
Global emissions continue to track the most carbon-intensive range among more than a thousand scenarios developed by the Intergovernmental Panel on Climate Change (IPCC). If continued, this situation would lead to global average temperatures between 3.2C and 5.4C above pre-industrial levels by 2100.
There have been other striking changes in emissions profiles since climate negotiations began. In 1990, about two-thirds of CO2 emissions came from developed countries including the United States, Japan, Russia and the European Union (EU) nations. Today, only one-third of world emissions are from these countries; the rest come from the emerging economies and less-developed countries that account for 80% of the global population, suggesting a large potential further emissions growth.
Continuation of current trends over the next five years alone will lead to a new world order on greenhouse gas emissions, with China emitting as much as the United States, Europe and India together.
Country emission profiles
There are several ways to explore countries’ respective contributions to climate change. These include current emissions, per capita emissions, and cumulative emissions since the industrial revolution.
The largest emitters in 2013 were China, the United States, the 28 EU countries (considered as a single bloc), and India. Together, they account for 58% of global emissions and 80% of the emissions growth in 2013 (with the majority the growth coming from China, whereas the EU cut its emissions overall).
Here’s how the major emitters fared in 2013.
Emissions grew at 4.2%, the lowest level since the 2008 global financial crisis, because of weaker economic growth and improvements in the carbon intensity of the economy. Per capita emissions in China (7.2 tonnes of CO2 per person) overtook those in Europe (6.8 tonnes per person).
A large part of China’s high per capita emissions is due to industries that provide services and products to the developed world, not for China’s domestic use. China’s cumulative emissions are still only 11% of the total since pre-industrial times.
Emissions increased by 2.9% because of a rebound in coal consumption, reversing a declining trend in emissions since 2008. Emissions are projected to remain steady until 2019 in the absence of more stringent climate policies, with improvements in the energy and carbon intensity of the economy being offset by growth in GDP and population. The United States remains the biggest contributor of cumulative emissions with 26% of the total.
Emissions fell by 1.8% on the back of a weak economy, although reductions in some countries were offset by a return to coal led by Poland, Germany and Finland. However, the long-term decrease in EU emissions does not factor in the emissions linked to imported goods and services. When accounting for these “consumption” emissions, EU emissions have merely stabilised, rather than decreased.
Emissions grew by 5.1%, driven by robust economic growth and an increase in the carbon intensity of the economy. Per capita emissions were still well below the global average, at 1.9 tonnes of CO2 per person, although India’s total emissions are projected to overtake those in the EU by 2019 (albeit for a population nearly three times as large). Cumulative emissions account for only 3% of the total.
Emissions from fossil fuels declined in 2013, largely driven by a 5% decline of emissions in the electricity sector over the previous year (as shown by the Australian National Greenhouse Gas Accounts). Fossil fuel emissions per person remain high at 14.6 tonnes of CO2.
Is it too late to tame the climate?
Despite this apparently imminent event, economic models can still come up with scenarios in which global warming is kept within 2C by 2100, while both population and per capita wealth continue to grow. Are these models playing tricks on us?
Most models invoke two things that will be crucial to stabilising the climate at safer levels. The first is immediate global action to develop carbon markets, with prices rapidly growing to over US$100 per tonne of CO2.
The second is the deployment of “negative emissions” technologies during the second half of this century, which will be needed to mop up the overshoot of emissions between now and mid-century. This will involve removing CO2 from the atmosphere and storing it in safe places such as saline aquifers.
These technologies are largely unavailable at present. The most likely candidate is the production of bioenergy with carbon capture and storage, a combination of existing technologies with high costs and with environmental and socio-economic implications that are untested at the required scales.
There are no easy pathways to climate stabilization, and certainly no magic bullets. It is still open to us to choose whether we halt our CO2 emissions completely this century – as required for a safe, stable climate – or try instead to adapt to significantly greater impacts of climate change.
What we have no choice about is the fact that the longer emissions continue to grow at rates of 2% per year or more, the harder it will be to tame our climate.
Pep Canadell received support from the Australian Climate Change Science Program.
Michael Raupach has previously received funding from the Australian Climate Change Science Program, but does not do so now.
The winners of the 2014 IgNobel prizes have just been announced, and there’s an Australian among them. Peter K. Jonason from the University of Western Sydney shared the IgNobel for Psychology with Amy Jones and Minna Lyons, for providing evidence that people who habitually stay up late are, on average, more self-admiring, more manipulative, and more psychopathic than people who habitually arise early in the morning.
We are filled with admiration.
CSIRO wasn’t among the winners this year, but we’re going to take the opportunity to boast about our earlier winners.
In 2011, David Rentz (formerly of CSIRO) and Darryl Gwynne shared the IgNobel Prize for biology, for their groundbreaking discovery that a certain kind of Australian beetle attempts to mate with stubby bottles. Specifically, that male Buprestid beetles (jewel beetles or metallic wood-boring beetles) had a particular attraction to brown stubbies – none of this fancy craft beer in clear glass for them. In true scientific spirit, having noticed this occurring, they took steps to confirm the mating hypothesis. They ruled out the beetles being attracted by beer residue – the stubby bottles were completely dry. Nor were the beetles interested in a discarded wine bottle nearby – suggesting the colour of the bottle was the source of the attraction.
They then placed several more stubby bottles within range of the male beetles, and found that these too were extremely appealing to the beetles. So appealing, in fact, that they didn’t give up of their own accord, but had to be physically dislodged from making their amorous advances.
This, of course, provides a valuable lesson about the unintended consequences of littering. Throwing away a stubby can cause grave disappointment for beetles.
But these are not our only IgNobelists.
In 2006, Nic Svenson and Piers Barnes took out the IgNobel in mathematics for working out the solution to a problem that has confounded photographers for many years: how many photos do you need to take to be sure no-one is blinking.
They managed to reduce it to a (fairly) simple rule of thumb. For groups of less than 20 people, take the number of people in the group and divide that number by three. If you take that number of photos you can be virtually certain one of them will be blink-free. If the light is bad, divide the number of people in the group by two, because there’s a greater chance people will be blinking whilst the shutter is open.
This doesn’t work as well when the groups get larger: the number of photos grows so large that the group is likely to lose patience. But as they point out, the more people in a photo, the less it matters if one of them is blinking. And you’ll be pleased to know this was all experimentally tested in the canteen at lunchtime.
So congratulations to this year’s winners, commiserations to the losers, and onwards and upwards for the spirit of inquiry that drives improbable research.
Next year, next year …