Princeton University Professor Simon Levin—IIASA council chair 2003-2008–has won numerous awards for his interdisciplinary research in environmental sciences, economics, and evolutionary biology. On 10 November, Levin gave a public lecture at IIASA, at which he was named an IIASA Distinguished Visiting Fellow.
Simon Levin speaks at the fifth IIASA/OeAW Public Lecture in Laxenburg on 10 November. Credit: IIASA/Matthias Silveri
IIASA: Your research explores issues such as environmental degradation, human inequality, and climate change. Why are global problems such as these so difficult to address? Simon Levin: To a large extent, many of these are problems not well addressed in market-based systems. The problem is that for public goods and common-pool resources, the incentives for individual actions are misaligned with the interests of society. Equity gaps and discounting of the future add to these problems, and make it difficult to achieve consensus, especially at global levels for which the feedback loops associated with individual and local actions are weak.
What kinds of approaches are needed to understand such complex, global environmental and social problems? Certainly we need systems approaches to deal with the linkages and scaling problems within these complex adaptive systems. We need interdisciplinarity, and we need more study of how to achieve cooperation at national and international levels. These are all problems central to the agenda of IIASA.
What new insights has your research brought to these problems? I have long been impressed with the power of using what we learn in one set of systems to address analogous problems in others, and have benefited greatly from what I have learned from colleagues in other disciplines. I feel that I have been able to get a great deal of mileage out of translating and adapting those lessons to environmental problems, and feel that my ecological and evolutionary perspective in particular, and what I have learned from how evolution has dealt with challenges, has allowed me to bring useful perspectives to the management of coupled biological and socioeconomic systems.
How can models of complex environmental systems inform our understanding of human systems such as the economy? We learn from such systems what makes them robust, and what makes them vulnerable to collapse; the importance of diversity, redundancy, and modularity to the ability of systems to adapt in variable environments; the importance of flexible and adaptive governance.
“We learn from [environmental] systems what makes them robust, and what makes them vulnerable to collapse” Credit: PhotonQ via Flickr
What can studies of cooperation in nature tell us about cooperation in human societies? Cooperation in nature is strongest in small groups; and as those groups become larger, agreements, social norms and institutions become increasingly important. Nobel Prize winner Elinor Ostrom led in adapting those principles to the management of small societies, and I agree with her on the importance of polycentricity—building up from smaller agreements—in addressing global environmental problems.
How can we apply such findings to find practical solutions for the problems we face? We need research, but we also need partners outside of science. Increasingly, business leaders have looked to biological systems for models as to how they can deal with challenges; we now similarly need to partner with government leaders if we are to address the grand challenges in achieving a sustainable future.
By Johannes Pirker and Aline Mosnier, IIASA Ecosystems Services and Management Research Program
In the late 2000s, Palm oil became a major target of environmental NGO’s working to save tropical forests. Bleak images of recently cleared forest sites left no doubt about the harmful impact of the commodity which today is omnipresent in our food—palm oil today is used in many everyday products such as chocolate bars, shampoo, and margarine. Campaigning against palm oil is a safe bet for NGO’s; it has become the North Korea among the vegetable oils.
The facts are clear: oil palm cultivation has expanded tremendously in recent years. Indonesia and Malaysia were and continue to be the epicenter of this expansion. In these two countries, new plantations have led to at least 3.7 million hectares of forest loss during the last 20 years, an area bigger than Belgium. This deforestation threatens not only animal and plant species, but expansion of palm oil plantations is increasingly occurring into carbon-rich peat soils, leading to the release of tremendous amounts of climate-warming CO2 into the atmosphere.
Palm oil mill of CDC in the South-West province in Cameroon, taken by Aline Soterroni, a 2010 IIASA YSSP participant and collaborator on the REDD-PAC project. Photo Credit: Aline Soterroni
On the other hand, even environmental NGOs cannot deny that the palm-oil boom has brought major benefits to the economies of producer countries. In Indonesia, the sector is estimated to employ on average 0.4 persons per hectare – at least 3.2 million jobs in a country where about 30 million people live in poverty. Unskilled slave labor? Well, no. Almost half of the plantations in the country are owned and managed by smallholders. In Thailand the share is as high as three quarters of the total plantation area.
Demand for palm oil remains high and there is now evidence that the palm oil boom might spill over to Central and Western Africa, where about 800,000 hectares of plantation concession have been granted to companies in recent years. Latin American countries too see the opportunity to benefit from the boom, such as Brazil, which has recently included oil palm in its reforestation plans, bolstered by a generous subsidy scheme for smallholders. So is the way inevitably paved for the palm oil industry to embark on a new round of forest-destroying plantation expansion?
Land use planning as a way forward In many countries land is available – mainly degraded forests and grassland – to satisfy the future demand for palm oil in a less damaging way. Earmarking the right sites for palm plantations requires a good deal of capacity and knowledge by local authorities about where natural conditions are suitable for oil palm, which environmental and social safeguards need to be considered and at which place – a land use planning process.
The map above shows where palm oil production is possible on the globe when taking into account climate, soil, and topography features.
The first step toward more sustainable oil production is a map indicating where bio-physical conditions are suitable for oil palm cultivation. To that end, we constructed a global bio-physical suitability map, building on climate, soil and topography data at the resolution of 1 km. The map reveals that in fact the Amazon basin – the better part of it is located in Brazil – harbors by far the biggest stretch of suitable land, followed by the Democratic Republic of the Congo (DRC) and Indonesia.
IIASA supports the MOABI platform, a collaborative mapping initiative that aims to increase transparency and accountability on resource issues in DRC. Our oil palm suitability map will help to inform this process by providing insight to the sustainability of the expected expansion of oil palm in DRC in the coming years.
This map shows areas that are potentially suitable for oil palm cultivation in the Democratic Republic of the Congo. The map was developed from our data, and made interactive and zoomable by our partners the Moabi Project.
Biophysical suitability is not all However, if and where plantations will start to appear will depend on many factors, most of which are economic :
Availability, productivity and costs of land and labor
The institutional set-up and support for the sector
Accessibility to refinery plants and markets is a key determinant for oil palm plantations profitability
In order to address these issues, an economic model such as IIASA’s Global Biosphere Management Model (GLOBIOM) model can be deployed to gain insights in the likely development of the sector, help land use planning and explicitly show the trade-off between economic development and biodiversity protection.
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
By Linda See and Ian McCallum, IIASA Ecosystems Services and Management Program, Earth Observation Team
Land cover is of fundamental importance for environmental research. It serves as critical baseline information for many large-scale models, for example in developing future scenarios of land use and climate change. However, current land cover products are not accurate enough for many applications and to improve them we need better and more accessible validation data. We recently argued this point in a Nature correspondence, and here we take the opportunity to expand on our brief letter.
In the last decade, multiple global land cover data products have been developed. But when these products are compared, there are significant amounts of spatial disagreement across land cover types. Where one map shows cropland, another might show forest domains. These discrepancies persist even when you take differences in the legend definitions into account. The reasons for this disagreement include the use of different satellite sensors, different classification methodologies, and the lack of sufficient data from the ground, which are needed to train, calibrate, and validate land cover maps.
An artist’s illustration of the NASA Landsat Data Continuity Mission spacecraft, one of the many satellites that collects data about Earth’s surface. Credit: NASA/GSFC/Landsat
A recent Comment in Nature (Nature, 513, 30-31; 2014) argued that freely available satellite imagery will improve science and environmental-monitoring products. Although we fully agree that greater open access and sharing of satellite imagery is urgently needed, we believe that this plea neglects a crucial component of land cover generation: the data required to calibrate and validate these products.
At present, remotely sensed global land cover is not accurate enough for monitoring biodiversity loss and ecosystem dynamics or for many of the other applications for which baseline land cover and change over time are critical inputs. When Sentinel-2–a new Earth observation satellite to be launched in 2015 by the European Space Agency–comes online, it will be possible to produce land cover maps at a resolution of 10 meters. Although this has incredible potential for society as a whole, these products will only be useful if they represent the land cover more accurately than the current products available. To improve accuracy, more calibration and validation data are required. Although more investment is clearly needed in ground-based measurements, there are other, complementary solutions to this problem.
Map showing cropland disagreement between two different land cover maps, GlobCover and GLC2000: all colors represent disagreement. Credit: Geo-Wiki.org, Google Earth
Not only should governments and research institutes be urged to share imagery, they should also share their calibration and validation data. Some efforts have been made by the Global Observation for Forest Cover and Land Dynamics (GOFC-GOLD) in this direction, but there is an incredible amount of data that remains locked within institutes and agencies. The atmospheric community shares their data much more readily than the Earth Observation (EO) community, even though we would only benefit by doing so.
Crowdsourcing of calibration and validation data also has real potential for vastly increasing the amount of data available to improve classification algorithms and the accuracy of land cover products. The IIASA Geo-Wiki project is one example of a growing community of crowdsourcing applications that aim to improve the mapping of the Earth’s surface.
New apps developed by IIASA’s Earth Observation Team aim to involve people around the world in on-the-ground data validation efforts.
Geo-Wiki is a platform which provides citizens with the means to engage in environmental monitoring of the earth by providing feedback on existing spatial information overlaid on satellite imagery or by contributing entirely new data. Data can be input via the traditional desktop platform or mobile devices, with campaigns and games used to incentivize input. Resulting data are available without restriction.
Another major research projects we are using to address many of these issues identified above is the ERC Project Crowdland .
Note: This article gives the views of the authors, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
Steffen Fritz has just been awarded an ERC Consolidator Grant to fund a research project on crowdsourcing and ground data collection on land-use and land cover. In this interview he talks about his plans for the new project, CrowdLand.
Farmers in Kenya are one group which the Crowdland Project aims to involve in their data gathering. Photo credit: Neil Palmer, CIAT
What’s the problem with current land cover data? There are discrepancies between current land cover products, especially in cropland data. It’s all based on satellite data, and in these data, it is extremely difficult to distinguish between cropland and natural vegetation in certain parts of the world if you do not use so-called very high resolution imagery, similar to a picture you take from space. With this high-resolution data you can see structures like fields and so on, which you can then use to distinguish between natural vegetation and cropland. But this is a task where currently people are still better at than computers–and there is a huge amount of data to look at.
In our Geo-Wiki project and related efforts such as the Cropland Capture game, we have asked volunteers to look at these high-resolution images and classify the ground cover as cropland or not cropland. The efforts have been quite successful, but our new project will take this even further.
How will the new project expand on what you’ve already done in Geo-Wiki? The big addition is to go on the ground. Most of the exercises we currently do are based on the desktop or the phones, or tablets, asking volunteers to classify imagery that they see on a screen.
What this project aims to do is to improve data you collect on the ground, known as in-situ data. You can use photography, GPS sensors, but also your knowledge you have about what you see. We will use volunteers to collect basic land cover data such as tree cover, cropland, and wetlands, but also much more detailed land-use information. With this type of data we can document what crops are grown where, whether they are irrigated, if the fields are fertilized, what exact type of crops are growing, and other crop management information which you cannot see in satellite imagery. And there are some things you can’t even see when you’re on the ground, thus you need to ask the farmer or recruit the farmer as a data provider. That’s an additional element this project will bring, that we will work closely with farmers and people on the ground.
For the study, you have chosen Austria and Kenya. Why these two countries? In Austria we have much better in situ data. For example, the Land Use Change Analysis System (LUCAS) in Europe collects in situ data according to a consistent protocol. But this program is very expensive, and the agency that runs it, Eurostat, is discussing how to reduce costs. Additionally the survey is only repeated every three years so fast changes are not immediately recorded. Some countries are not in favor of LUCAS and they prefer to undertake their own surveys. Then however you lose the overall consistency and there is no Europe-wide harmonized database which allows for comparison between countries. Our plan is to use gaming, social incentives, and also small financial incentives to conduct a crowdsourced LUCAS survey. Then we will examine what results you get when you pay volunteers or trained volunteers compared to the data collected by experts.
In Kenya, the idea is similar, but in general in the developing world we have very limited information, and the resources are not there for major surveys like in Europe. In order to remedy that the idea is again to use crowdsourcing and use a “bounded crowd” which means people who have a certain level of expertise, and know about land cover and land use, for example people with a surveyor background, university students, or interested citizens who can be trained. But in developing countries in particular it’s important to use financial incentives. Financial incentives, even small ones, could probably help to collect much larger amounts of data. Kenya is a good choice also because it has quite a good internet connection, a 3G network, and a lot of new technologies evolving around mobile phones and smartphone technology.
What will happen with the data you collect during this project? First, we will analyze the data in terms of quality. One of our research questions is how good are the data collected by volunteers compared to data collected by experts. Another research question is how can imperfect but large data collected by volunteers be filtered and combined so that it becomes useful and fulfills the scientific accuracy requirements.
Then we will use these data and integrate them into currently existing land use and land cover data, and find ways to make better use of it. For example, in order to make projections about future land-use and to better quantify current yield gaps it is crucial to get accurate current information on land-use, including spatially explicit information on crop types, crop management information and other data.
Once we have done some quality checks we will also make these data available for other researchers or interested groups of people.
Crowdsourcing for land cover is in its infancy. There have been lots of crowdsourcing projects in astronomy, archaeology, and biology, for example, but there hasn’t been much on land use, and there is huge potential there. ”We need to not only better understand the quality of the data we collect, but also expand the network of institutions who are working on this topic.”
Note: This article gives the views of the interviewee, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
By Erich Striessnig, Research Assistant, IIASA World Population Program
We have all heard about the terrible air pollution in India’s cities. Average concentrations of particulate pollution exceed World Health Organization guidelines through most of India, most of the time. So why hasn’t anything been done? Is it really too expensive?
In a recent publication with fellow IIASA Population Program researcher Warren Sanderson and IIASA Mitigation of Air Pollution and Greenhouse Gases Program researchers Wolfgang Schöpp and Markus Amann, we set to find out. In the study, published in the journal Environmental Science and Technology, we showed that in fact, policy reforms in India targeted at reducing emissions of dangerous fine particulate matter could save thousands of lives, and at the same time save money.
Air pollution in India exceeds World Health Organization limits much of the time, which contributes to health problems and premature deaths. Photo Credit: Mark Danielson via Flickr (Creative Commons License)
Due to their very small size, small particles released by cars, factories, and other combustion can travel very deep down into people’s lungs and cause or worsen all sorts of health issues. In Indian cities, where concentrations of these pollutants are already quite high, the expected increase in economic output over the next two decades will be accompanied by an enormous increase in air pollution, leading to a higher number of sick days or even deaths.
Both of these effects could be prevented or at least reduced if stricter regulations on emission limits – already in place in other countries – were imposed. The new study shows that if India enacted pollution controls as stringent as according to European legislation, by the year 2030, the end of the study period, up to 2.5 million premature deaths would be prevented.
So how do pollution controls save money? Healthier people are more productive because they are sick less often. People who can expect to live longer in a cleaner environment are more likely to make investments which would again create jobs and boost the economy. Our study shows that by 2030 such investments would in fact more than pay for themselves, when the economic benefits of a healthier population are considered.
So why haven’t politicians started doing something already much earlier? One answer might be that such reforms initially only produce costs, whereas the benefits typically don’t crystallize before the next elections. Hopefully, this latest scientific evidence from a collaboration of IIASA population and air pollution researchers can offer these politicians an impetus to act. Read more on the IIASA Web site.
Reference Warren Sanderson, Erich Striessnig, Wolfgang Schoepp, and Markus Amann. 2013. Effects on Well-Being of Investing in Cleaner Air in India. Environmental Science and Technology. 47 (23), pp 13222–13229 DOI: 10.1021/es402867r
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
By Linda See,Research Scholar, IIASA Ecosystems Services and Management Program
Researchers estimate we spend 3 billion hours a week on game playing. CC Image courtesy TheErin on Flickr
On a recent rush hour train ride in London I looked around to see just about everybody absorbed in their mobile phone or tablet. This in itself is not that unusual. But when I snooped over a few shoulders, what really surprised me was that most of those people were playing games. I hope this bodes well for our new game, Cropland Capture, introduced last week.
Cropland Capture is a game version of our citizen science project Geo-Wiki, which has a growing network of interested experts and volunteers who regularly help us in validating land cover through our competitions. By turning the idea into a game, we hope to reach a much wider audience.
Playing Cropland Capture is simple: look at a satellite image and tell us if you see any evidence of cropland. This will help us build a better map of where cropland is globally, something that is surprisingly uncertain at the moment. This sort of data is crucial for global food security, identifying where the big gaps in crop yields are, and monitoring crops affected by droughts, amongst many other applications.
Gamification and citizen science The idea of Cropland Capture is not entirely unique. There are an astonishingly large number of games available for high tech gaming consoles, PCs and increasingly, mobile devices. While the majority of these games are pure entertainment, some are part of an emerging genre known as ”serious games” or ”games with a purpose.” These are games that either have an educational element or through the process of playing them, you can help scientists in doing their research. One of the most successful examples is the game FoldIt, where teams of players work together to decode protein structures. This is not an easy task for a computer to do, but some people are exceptionally talented at seeing these patterns. The result has even led to new scientific discoveries that have been published in high level journals such as Nature.
Jane McGonigal, in her book Reality is Broken (Why Games Make us Better and How They Can Change the World), estimates that we spend 3 billion hours a week alone on game playing, and that the average young person spends more time gaming by the end of their school career than they have actually spent in school. Although these figures may seem alarming, McGonigal argues that there are many positive benefits associated with gaming, including the development of problem-solving skills, the ability to cope better with problems such as depression or chronic pain, and even the possibility that we might live ten years longer if we played games. If people spent just a fraction of this time on “serious games” like FoldIt and Cropland Capture, imagine how much could be achieved.
Since the game started last Friday, 185 players have validated 119,777 square kilometers of land (more than twice the land area of Denmark).
Cropland Capture is easy to play – simply swipe the picture left or right to say whether there is cropland or not.
The game is being played for six months, where the top scorer each week will be crowned the weekly winner. The 25 weekly winners will then be entered into a draw at the end of the competition to win three big prizes: an Amazon Kindle, a smartphone, and a tablet. The game was launched only last week so there is plenty of time to get involved and help scientific research.
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