IIASA researchers Michael Obersteiner, David Leclère, and Piero Visconti discuss the findings of their latest paper, which proposes pathways to reverse the current trend of biodiversity loss and shows that the next 30 years will be pivotal for the Earth’s wildlife.
Species are going extinct at an unprecedented rate. Wildlife populations have fallen by more than two-thirds over the last 50 years, according to a new report from the World Wildlife Fund. The sharpest declines have occurred throughout the world’s rivers and lakes, where freshwater wildlife has plummeted by 84% since 1970 – about 4% per year.
But why should we care? Because the health of nature is intimately linked to the health of humans. The emergence of new infectious diseases like COVID-19 tend to be related to the destruction of forests and wilderness. Healthy ecosystems are the foundation of today’s global economies and societies, and the ones we aspire to build. As more and more species are drawn towards extinction, the very life support systems on which civilization depends are eroded.
Even for hard-nosed observers like the World Economic Forum, biodiversity loss is a disturbing threat with few parallels. Of the nine greatest threats to the world ranked by the organization, six relate to the ongoing destruction of nature.
Economic systems and lifestyles which take the world’s generous stocks of natural resources for granted will need to be abandoned, but resisting the catastrophic declines of wildlife that have occurred over the last few decades might seem hopeless. For the first time, we’ve completed a science-based assessment to figure out how to slow and even reverse these trends.
Our new paper in Nature featured the work of 60 coauthors and built on efforts steered by the Intergovernmental Panel on Biodiversity and Ecosystem Services. We considered ambitious targets for rescuing global biodiversity trends and produced pathways for the international community to follow that could allow us to meet these goals.
Bending the curve
The targets of the UN Convention on Biological Diversity call for global trends of terrestrial wildlife to stop declining and start recovering by 2050 or earlier. Changes in how land is used – from pristine forest to cropland or pasture – rank among the greatest threats to biodiversity on land worldwide. So what are the necessary conditions for biodiversity to recover during the 21st century while still supporting growing and affluent human societies?
Two key areas of action stand out from the rest. First, there must be renewed ambition from the world’s governments to establish large-scale conservation areas, placed in the most valuable hotspots for biodiversity worldwide, such as small islands with species found nowhere else. These reserves, in which wildlife will live and roam freely, will need to cover at least 40% of the world’s land surface to help bend the curve from decline to recovery for species and entire ecosystems.
The location of these areas, and how well they are managed, is often more important than how big they are. Habitat restoration and conservation efforts need to be targeted where they are needed most – for species and habitats on the verge of extinction.
Second, we must transform our food systems to produce more on less land. If every farmer on Earth used the best available farming practices, only half of the total area of cropland would be needed to feed the world. There are lots of other inefficiencies that could be ironed out too, by reducing the amount of waste produced during transport and food processing, for example. Society at large can help in this effort by shifting towards healthier and more sustainable diets, and reducing food waste.
This should happen alongside efforts to restore degraded land, such as farmland that’s becoming unproductive as a result of soil erosion, and land that’s no longer needed as agriculture becomes more efficient and diets shift. This could return 8% of the world’s land to nature by 2050. It will be necessary to plan how the remaining land is used, to balance food production and other uses with the conservation of wild spaces.
Without a similar level of ambition for reducing greenhouse gas emissions, climate change will ensure the world’s wildlife fares badly this century. Only a comprehensive set of policy measures that transform our relationship with the land and rapidly scale down pollution can build the necessary momentum. Our report concludes that transformative changes in our food systems and how we plan and use land will have the biggest benefits for biodiversity.
But the benefits wouldn’t end there. While giving back to nature, these measures would simultaneously slow climate change, reduce pressure on water, limit nitrogen pollution in the world’s waterways and boost human health. When the world works together to halt and eventually reverse biodiversity loss, it’s not only wildlife that will thrive.
by Melina Filzinger, IIASA Science Communication Fellow
Strategic board games are staple entertainment for families all over the world, but what many do not know is that games can also be a valuable research tool. As her project for the Young Scientists Summer Program (YSSP), Sara Turner is piloting an experiment that uses a game called the Forest Game, developed by IIASA and the Centre for Systems Solutions, to find out how policy decisions are made and how they change over time. “Games let you abstract from the specifics of a real-world case, but are more human-centric than, for example, computer simulations,” says Turner.
In the Forest Game, a group of five to ten players is asked to make decisions about the management of a forest together. Harvesting trees yields returns for the players, while harvesting too many of them might destroy the forest or increase the risk of flooding. There are some uncertainties in the game – for example, the players do not know exactly how resilient the forest is. The goal of the research project is to run multiple iterations of the game with different players and starting conditions, and trace how group discussions and the resulting decisions change over time. This helps to generate hypotheses about the ways in which individuals interact to generate policy outcomes. Each game takes about an hour to play.
Even though the Forest Game deals with forest management, this is only one example of a broader class of decision-making dilemma: when a resource is limited, and it is costly to prevent access, people will tend to over-exploit the resource. This in turn leads to a wide range of problems, from over-fishing to air pollution. Although games cannot capture the complexity of real situations, they can still help us understand the core dynamics of the problem and develop ideas and strategies that are relevant to solving it. “The game is not designed to be directly applicable to real life, but it helps to come up with hypotheses that you can then compare to real-life cases,” explains Turner.
Questions about the sustainable management of resources have been studied for decades, but not a lot is known about the role values play in shaping group decision making and the stability of the implemented policies. To investigate this, each participant is asked to fill out a short ten-minute survey assessing their core values and beliefs, after which they are put into a group with people who either have a very similar or very different worldview from them. “It is really interesting to put a person in a decision-making context with other people and get some insight into how they work through that problem,” says Turner.
For example, if you are a person that strongly values equality, in the game you might be likely to argue in favor of a policy where all participants obtain the same amount of returns, regardless of the number of trees the individual player chooses to harvest. If many players in the group share your belief, that policy might be more likely to be implemented than in a very diverse group.
Another interesting question whenever you run a game for research purposes is, “Who are the right players?” Some games are targeted at real-world policymakers, but often games can also be educational for the broader public. ‘’People learn a lot during games, because of the way that information is processed and experienced,” says Turner. That is why many participants, although they might not see a connection between the game and their life at first, find themselves relying on the insights they gained while playing when faced with similar situations in the future.
In this case, the goal is to study group decision-making processes in general, so the details of who is playing are not particularly important. However, to obtain groups of players with heterogeneous worldviews, a high degree of diversity is preferable.
While the game has previously mainly been played by YSSP participants and students of the University of Vienna, Turner is currently trying to recruit a more diverse set of players from both within and outside of IIASA. “It would be ideal to have a pool of participants who come from a wide variety of educational and cultural backgrounds,” she says.
If you are interested in participating in the Forest Game, you can write Sara Turner an e-mail to email@example.com.
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.
By Victor Maus, IIASA Ecosystems Services and Management Program
Nowadays, satellite images are an abundant supply of data which we can use to get information about our planet and its changes. Satellite images can, for example, help us detect an approaching storm, measure the expansion of a city, identify deforested areas, or estimate how crop areas change over time. Usually, we are interested in extracting information from large areas, for example, deforestation in the Amazon Rainforest (5.5 million km², around 15 times the area of Germany). It would be challenging for us to monitor and map such vast areas without combining satellite images with automated and semi-automated computer programs.
To address this problem, I developed — along with my colleagues Gilberto Camara from the Brazilian National Institute for Space Research and Marius Appel and Edzer Pebesma from the University of Münster, Germany — a new open source software to extract information about land-cover changes from satellite images. The tool maps different crop types (e.g., soybean, maize, and wheat), forests, and grassland, and can be used to support land-use monitoring and planning.
Our software, called dtwSat, is open-source and can be freely installed and used for academic and commercial purposes. It builds upon on other graphical and statistical open-source extensions of the statistical program R. Adding to that, our article in press in Journal of Statistical Software is completely reproducible and provides a step-by-step example of how to use the tool to produce land-cover maps. Given that we have public access to an extensive amount satellite images, we also get much benefit from tools that are openly available, reproducible, and comparable. These, in particular, can contribute to rapid scientific development.
The software dtwSat is based on a method widely used for speech recognition called Dynamic Time Warping (DTW). Instead of spoken words, we adapted DTW to identify ‘phenological cycles’ of the vegetation. These encompass the plants’ life cycle events, such as how deciduous trees lose their leaves in the fall. The software compares a set of phenological cycles of the vegetation measured from satellite images (just like a dictionary of spoken words) with all pixels in successive satellite images, taken at different times. After comparing the satellite time series with all phenological cycles in the dictionary, dtwSat builds a sequence of the land-cover maps according to similarity to the phenological cycles.
The series of maps produced by dtwSat allows for land-cover change monitoring and can help answer questions such as how much of the Amazon rainforest has been replaced with soy or grass for cattle grazing during the last decade? It could also help study the effects of policies and international agreements, such Brazil’s Soy Moratorium, where soybean traders agreed not to buy soy from areas deforested after 2006 in the Brazilian Amazon. If soy farming cannot expand over areas deforested after 2006, it might expand to areas formerly used for cattle grazing deforested before 2006, and force the cattle grazing farmers to open new areas that have been cleared more recently. Therefore, besides monitoring changes, the land-cover information can help better understand direct and indirect drivers of deforestation and support new land-use policy.
Maus, V, Camara, G, Cartaxo, R, Sanchez, A, Ramos, FM, & de Queiroz, GR (2016). A Time-Weighted Dynamic Time Warping Method for Land-Use and Land-Cover Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9 (8): 3729–39.
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.
How did your scientific career evolve into climate change and ecosystem ecology? I studied environmental science in Spain and then I went to Australia, where I started working on free-air CO2 enrichment, or FACE experiments. These are very fancy experiments where you fumigate a forest with CO2 to see if the trees grow faster. In 2014 I moved to London for my PhD project. There, instead of focusing on one single FACE experiment, I collected data from all of them. This allowed me to make general conclusions on a global scale rather than a single forest.
You recently published a paper in Science magazine. Could you summarize the main findings? We found that we can predict how much CO2 plants transfer into growth through the CO2 fertilization effect, based on two variables—nitrogen availability and the type of mycorrhizal, or fungal, association that the plants have. The impact of the type of mycorrhizae has never been tested on a global scale—and we found that it is huge. I think it’s fascinating that such tiny organisms play such a big role at a global scale on something as important as the terrestrial capacity of CO2 uptake.
How did you come up with the idea? One random day in the shower? Long story short, researchers used to think that plants will grow faster, and take up a lot of the CO2 we emit. They assumed this in most of their models as well. But plants need other elements to grow besides CO2. In particular, they need nitrogen. So scientists started to question whether the modeled predictions overestimated the CO2 fertilization effect, because the models did not consider nitrogen limitation. To find out, I analyzed all the FACE experiments and indeed I saw that in general plants were not able to grow faster under elevated CO2 and nitrogen limitation. However, in some cases plants were able to take advantage of elevated CO2 even under nitrogen limitation. I grouped together the experiments where plants could grow under nitrogen limitation and after a lot of reading I saw what they had in common: the type of fungi! It turned out that one type of mycorrhizae is really good at transferring large quantities of nitrogen to the plant and the other type is not.
How did that feel? Awesome! When I saw the graph, I knew: this is going to be important. Of course, after this, my coauthors helped me to polish the story. Without them, the conclusions would not be as robust and clear.
So how does this process work? Where do the fungi get the nitrogen from? Particular soils might have a lot of nitrogen, but the amount available for plants to absorb might be low. Also, plants have to compete with non-fungal microorganisms for nitrogen. So if there is not much there, the microorganisms take it all. It’s called immobilization. Instead of mineralizing nitrogen, they immobilize it so that plants cannot take it up, at least not in the short term. Some types of fungi are much more efficient in accessing nitrogen, and associated with roots they allow plants to overcome limitations.
What is the impact of your findings? Plants currently take up 25-30% of the CO2 we emit, but the question is whether they will be able to continue to do so in the long term. Our findings bring good and bad news. On the one hand, the CO2 fertilization effect will not be limited entirely by nitrogen, because some of the plants will be able to overcome nitrogen limitation through their root fungi. But on the other hand, some plant species will not be able to overcome nitrogen limitation.
There was a big debate about this. One group of scientists believed that plants will continue to take up CO2 and the other group said that plants will be limited by nitrogen availability. These were two very contrasting hypotheses. We discovered that neither of the hypotheses was completely right, but both were partly true, depending on the type of fungi. Our results could bring closure to this debate. We can now make more accurate predictions about global warming.
What will you do at IIASA and how will you link it to your PhD? I want to upscale and quantify how much carbon plants will take up in the future. If we are to predict the capacity of plants to absorb CO2, we need to quantify mycorrhizal distribution and nitrogen availability on a global scale. We are updating mycorrhizal distribution maps according to distribution of plant species. We know for instance that pines are associated with ectomycorrhizal fungi and always will be. To quantify nitrogen availability we use maps of different soil parameters that are available on a rough global scale.
By Dilek Fraisl, IIASA Ecosystems Services and Management Program
In October 2015, we launched our latest game, Picture Pile. The idea is simple: look at a pair of satellite images from different years and tell us if you can see any evidence of deforestation. Thanks to the participation of many volunteers, 2.69 million pictures have already been sorted in our pile of 5 million pairs. But we still have a long way to go, and we need your help to get us there!
Screenshot from the game: click for more information (Image credit Tobias Sturn)
Deforestation is one of the most serious environmental problems in the world today. Forests cover a third of the land area on Earth, producing vital oxygen, habitats for a diversity of wildlife, and important ecosystem services. According to the World Wildlife Fund (WWF), some 46,000 to 58,000 square miles of forest are lost each year, which is equivalent to 48 football fields every minute. But this is a rough estimate since deforestation is very difficult to track. Reasons why are that satellite imagery can be of insufficient spatial resolution to map deforestation accurately, deforestation mostly occurs in small chunks that may not be visible from medium-resolution imagery, and very high-resolution data sets are expensive and can require big data processing capabilities, so can only be used for limited areas.
To help contribute to better mapping of deforestation, researchers in IIASA’s Earth Observation Systems (EOS) group, led by Steffen Fritz, have been working on novel projects to engage citizens in scientific data collection that can complement satellite-based traditional deforestation monitoring. One of the latest applications is Picture Pile, a game that makes use of very high-resolution satellite images spanning the last decade. Designed by Tobias Sturn, the aim is to provide data that can help researchers build a better map of deforestation. Players are provided with a pair of images that span two time periods and are then asked to answer a simple question: “Do you see tree loss over time?” After examining the image, the player drags the images to the right for “yes,” left for “no,” or down to indicate “maybe” when the deforestation is not clearly visible.
Every image is sorted multiple times by numerous independent players, in order to build confidence in the results, and also to gain an understanding of how good the players are at recognizing visible patterns of deforestation. Once enough data are collected at a single location, the images are taken out of the game and new ones are added, thereby increasing the spatial coverage of our mapped area over time. Right now we are focusing on Tanzania and Indonesia, two regions where we know there are problems with existing maps of deforestation.
Picture Pile is focusing first on Indonesia (pictured) and Tanzania – two regions where there are problems with existing maps of deforestation. Photo (cc) Aulia Erlangga for Center for International Forestry Research (CIFOR).
Once the pile is fully sorted, the 5 million photos in the data set will be used to develop better maps of forest cover and forest loss using hybrid techniques developed by the group as well as inputs to classification algorithms. We will also use the data to validate the accuracy of existing global land cover maps. Finally, we will mine the data set to look for patterns regarding quality (for example, how many samples do we need to provide to the “crowd” before we can be confident enough to use their data in further research). In short, by integrating citizens in scientific research, Picture Pile will also help us improve the science of land cover monitoring through crowdsourcing mechanisms.
So please join in and help us get to the finish line. You can play Picture Pile in your browser or you can download the free iOS/Android app from the Apple and Google Play stores and play on your smartphone or tablet. Your contributions will help scientists like those at IIASA to tackle global problems such as deforestation and environmental degradation. At the same time you may win some great prizes: a brand new smartphone, a tablet, or a mini tablet.
Reference Schepaschenko D, See L, Lesiv M, McCallum I, Fritz S, Salk C, Perger C, Schepaschenko M, Shvidenko A, Kovalevskyi S, Albrecht F, Kraxner F, Bun A, Maksyutov S, Sokolov A, Dürauer M, Obersteiner M. (2015) Global hybrid forest mask: synergy of remote sensing, crowd sourcing and statistics. Remote Sensing of the Environment, 162, 208-220. doi:10.1016/j.rse.2015.02.011
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.