̽��ֱ�� of Cambridge - Potsdam Institute for Climate Impact Research

Relocating farmland could turn back clock twenty years on carbon emissions

jg533 — Thu, 10 Mar 2022 10:00:00 +0000

̽��ֱ��reimagined world map of agriculture includes large new farming areas for many major crops around the cornbelt in the mid-western USA, and below the Sahara desert. Huge areas of farmland in Europe and India would be restored to natural habitat.

̽��ֱ��redesign - assuming high-input, mechanised farming - would cut the carbon impact of global croplands by 71%, by allowing land to revert to its natural, forested state. This is the equivalent of capturing 20 years’ worth of our current net CO2 emissions. Trees capture carbon as they grow, and also enable more carbon to be captured by the soil than when crops are grown in it.

In this optimised scenario, the impact of crop production on the world’s biodiversity would be reduced by 87%. This would drastically reduce the extinction risk for many species, for which agriculture is a major threat. ̽��ֱ��researchers say that croplands would quickly revert back to their natural state, often recovering their original carbon stocks and biodiversity within a few decades.

̽��ֱ��redesign would eliminate the need for irrigation altogether, by growing crops in places where rainfall provides all the water they need to grow. Agriculture is currently responsible for around 70% of global freshwater use, and this causes drinking water shortages in many drier parts of the world.

̽��ֱ��researchers used global maps of the current growing areas of 25 major crops, including wheat, barley and soybean, which together account for over three quarters of croplands worldwide. They developed a mathematical model to look at all possible ways to distribute this cropland across the globe, while maintaining overall production levels for each crop. This allowed them to identify the option with the lowest environmental impact.

̽��ֱ��study is published today in the journal Nature Communications Earth & Environment.

“In many places, cropland has replaced natural habitat that contained a lot of carbon and biodiversity – and crops don’t even grow very well there. If we let these places regenerate, and moved production to better suited areas, we would see environmental benefits very quickly,” said Dr Robert Beyer, formerly a researcher in the ̽��ֱ�� of Cambridge’s Department of Zoology, and first author of the study. Beyer is now based at the Potsdam Institute for Climate Impact Research (PIK), Germany.

Previous studies have identified priority areas for ecological restoration, but this is the first to plot the relocation of agricultural land to maximise long-term environmental benefits without compromising food security.

While a complete global relocation of cropland is clearly not a scenario that could currently be put into practice, the scientists say their models highlight places were croplands are currently very unproductive, but have potential to be hotspots for biodiversity and carbon storage.

Taking a pared-back approach and only redistributing croplands within national borders, rather than globally, would still result in significant benefits: global carbon impact would be reduced by 59% and biodiversity impact would be 77% lower than at present.

A third, even more realistic option of only relocating the worst-offending 25% of croplands nationally would result in half of the benefits of optimally moving all croplands.

“It’s currently not realistic to implement this whole redesign. But even if we only relocated a fraction of the world’s cropland, focusing on the places that are least efficient for growing crops, the environmental benefits would be tremendous,” said Beyer.

̽��ֱ��study finds that the optimal distribution of croplands will change very little until the end of the century, irrespective of the specific ways in which the climate may change.

“Optimal cropping locations are no moving target. Areas where environmental footprints would be low, and crop yields high, for the current climate will largely remain optimal in the future,” said Professor Andrea Manica in the Department of Zoology at the ̽��ֱ�� of Cambridge, senior author of the paper.

̽��ֱ��researchers acknowledge that relocating cropland must be done in a way that is acceptable to the people it affects, both economically and socially. They cite examples of set-aside schemes that give farmers financial incentives to retire part of their land for environmental benefit. Financial incentives can also encourage people to farm in better suited locations.

̽��ֱ��model generated alternative global distribution maps depending on the way the land is farmed – ranging from advanced, fully mechanised production with high-yielding crop varieties and optimum fertiliser and pesticide application, through to traditional subsistence-based organic farming. Even redistribution of less intensive farming practices to optimal locations would substantially reduce their carbon and biodiversity impacts.

While other studies show that if we moved towards more plant-based diets we could significantly reduce the environmental impacts of agriculture, the researchers say that in reality diets aren’t changing quickly. Their model assumed that diets will not change, and focused on producing the same food as today but in an optimal way.

Many of the world's croplands are located in areas where they have a huge environmental footprint, having replaced carbon-rich and biodiversity-rich ecosystems, and are a significant drain on local water resources. These locations were chosen for historical reasons, such as their proximity to human settlements, but the researchers say it is now time to grow food in a more optimal way.

This research was funded by the European Research Council.

Reference

Beyer, RM et al: ‘Relocating croplands could drastically reduce the environmental impacts of global food production.’ Nature Communications Earth & Environment, March 2022. DOI: 10.1038/s43247-022-00360-6

Scientists have produced a map showing where the world’s major food crops should be grown to maximise yield and minimise environmental impact. This would capture large amounts of carbon, increase biodiversity, and cut agricultural use of freshwater to zero.

If we moved production to better suited areas, we would see environmental benefits very quickly

Robert Beyer

Wheat fields

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Climate change may have driven the emergence of SARS-CoV-2

jg533 — Fri, 05 Feb 2021 12:03:26 +0000

A new study published today in the journal Science of the Total Environment provides the first evidence of a mechanism by which climate change could have played a direct role in the emergence of SARS-CoV-2, the virus that caused the COVID-19 pandemic.

̽��ֱ��study has revealed large-scale changes in the type of vegetation in the southern Chinese province of Yunnan, and adjacent regions in Myanmar and Laos, over the last century. Climatic changes including increases in temperature, sunlight, and atmospheric carbon dioxide - which affect the growth of plants and trees - have changed natural habitats from tropical shrubland to tropical savannah and deciduous woodland. This created a suitable environment for many bat species that predominantly live in forests.

̽��ֱ��number of coronaviruses in an area is closely linked to the number of different bat species present. ̽��ֱ��study found that an additional 40 bat species have moved into the southern Chinese province of Yunnan in the past century, harbouring around 100 more types of bat-borne coronavirus. This ‘global hotspot’ is the region where genetic data suggests SARS-CoV-2 may have arisen.

“Climate change over the last century has made the habitat in the southern Chinese Yunnan province suitable for more bat species,” said Dr Robert Beyer, a researcher in the ̽��ֱ�� of Cambridge’s Department of Zoology and first author of the study, who has recently taken up a European research fellowship at the Potsdam Institute for Climate Impact Research, Germany.

He added: “Understanding how the global distribution of bat species has shifted as a result of climate change may be an important step in reconstructing the origin of the COVID-19 outbreak.”

To get their results, the researchers created a map of the world’s vegetation as it was a century ago, using records of temperature, precipitation, and cloud cover. Then they used information on the vegetation requirements of the world’s bat species to work out the global distribution of each species in the early 1900s. Comparing this to current distributions allowed them to see how bat ‘species richness’, the number of different species, has changed across the globe over the last century due to climate change.

“As climate change altered habitats, species left some areas and moved into others - taking their viruses with them. This not only altered the regions where viruses are present, but most likely allowed for new interactions between animals and viruses, causing more harmful viruses to be transmitted or evolve,” said Beyer.

̽��ֱ��world’s bat population carries around 3,000 different types of coronavirus, with each bat species harbouring an average of 2.7 coronaviruses - most without showing symptoms. An increase in the number of bat species in a particular region, driven by climate change, may increase the likelihood that a coronavirus harmful to humans is present, transmitted, or evolves there.

Most coronaviruses carried by bats cannot jump into humans. But several coronaviruses known to infect humans are very likely to have originated in bats, including three that can cause human fatalities: Middle East Respiratory Syndrome (MERS) CoV, and Severe Acute Respiratory Syndrome (SARS) CoV-1 and CoV-2.

̽��ֱ��region identified by the study as a hotspot for a climate-driven increase in bat species richness is also home to pangolins, which are suggested to have acted as intermediate hosts to SARS-CoV-2. ̽��ֱ��virus is likely to have jumped from bats to these animals, which were then sold at a wildlife market in Wuhan - where the initial human outbreak occurred.

̽��ֱ��researchers echo calls from previous studies that urge policy-makers to acknowledge the role of climate change in outbreaks of viral diseases, and to address climate change as part of COVID-19 economic recovery programmes.

“ ̽��ֱ��COVID-19 pandemic has caused tremendous social and economic damage. Governments must seize the opportunity to reduce health risks from infectious diseases by taking decisive action to mitigate climate change,” said Professor Andrea Manica in the ̽��ֱ�� of Cambridge’s Department of Zoology, who was involved in the study.

“ ̽��ֱ��fact that climate change can accelerate the transmission of wildlife pathogens to humans should be an urgent wake-up call to reduce global emissions,” added Professor Camilo Mora at the ̽��ֱ�� of Hawai‘i at Manoa, who initiated the project.

̽��ֱ��researchers emphasised the need to limit the expansion of urban areas, farmland, and hunting grounds into natural habitat to reduce contact between humans and disease-carrying animals.

̽��ֱ��study showed that over the last century, climate change has also driven increases in the number of bat species in regions around Central Africa, and scattered patches in Central and South America.

This research was supported by the European Research Council.

Reference
Beyer, R.M. et al: ‘Shifts in global bat diversity suggest a possible role of climate change in the emergence of SARS-CoV-1 and SARS-CoV-2.’ Science of the Total Environment, Feb 2021. DOI: 10.1016/j.scitotenv.2021.145413

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Hear from other ̽��ֱ�� of Cambridge researchers who are investigating how to reduce the risk of animal viruses jumping to humans.

Global greenhouse gas emissions over the last century have made southern China a hotspot for bat-borne coronaviruses, by driving growth of forest habitat favoured by bats.

Governments must seize the opportunity to reduce health risks from infectious diseases by taking decisive action to mitigate climate change.

Andrea Manica

Shi bai Xiao/ Greenpeace

Forest landscape in Yunnan Province, PRC

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Modelling impacts of a warming world

lw355 — Wed, 03 Oct 2012 13:37:36 +0000

How different will the world be if it’s 2°C, 3°C or 4°C warmer? Ask this question of the multitude of different climate change impact models – each built by researchers interested in different aspects of global warming – and the likelihood is that you will get a multitude of answers. Modelling the global impact of climate change is an extremely complex process, and yet it’s absolutely essential if policy makers are to understand the consequences tomorrow of emissions policies adopted today.

Earlier this year, an international group of researchers initiated a joint project to attempt the first systematic quantification of some of the uncertainties surrounding climate change impacts to agriculture, health, biomes and water. Uncertainties such as: to what extent will the world’s vegetation change? Which regions will succumb to drought or flood? What will be the impact on global food crops? And how will the spread of human diseases be affected?

̽��ֱ��Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), coordinated by the Potsdam Institute for Climate Impact Research in Germany and the International Institute for Applied Systems Analysis in Austria, involves two- dozen research groups from eight countries.

Dr Andrew Friend from Cambridge’s Department of Geography is coordinating the analysis of results concerning changes to the world’s biomes – the communities of plants, animals and soil organisms that are characterised by a similar structure and climatic requirement.

It’s a fast-track programme. All of the teams are working to a tight deadline and, by January 2013, they hope to be ready to publish their findings on the likely impacts of climate change predictions. ̽��ֱ��collective results will contribute towards the next report of the Intergovernmental Panel on Climate Change (IPCC), the leading international body that provides a clear scientific view on the current state of knowledge in climate change and its potential environmental and socioeconomic impacts.

Each group is using their own model, together with the very latest climate predictions produced by leading climate modelling groups around the world, to run comparable simulations for four different warming scenarios – conservative, drastic and two in between – from 1950 to 2099.

For Friend, this means Hybrid, the model he first developed 15 years ago. At its heart is a set of equations that dynamically model global vegetation: “It works by simulating the dynamics of individual trees and an underlying herbaceous layer. You assume the plants compete within patches, and then scale these up to 50-km grid boxes. We use data to work out the mathematics of how the plant grows – how it photosynthesises, takes-up carbon and nitrogen, competes with other plants, and is affected by soil nutrients and water – and we do this for different vegetation types. Effectively, the whole of the land surface is understood in 2,500 km² portions. We then input real climate data up to the present and look at what might happen every 30 minutes to 2099.”

For the most extreme scenario of climate change being modelled, Friend expects to see significant impact: “this scenario could show the whole of the Amazon rainforest disappearing this century, depending on the climate model. ̽��ֱ��circumpolar Boreal forest, which began to emerge at the end of the last ice age, could migrate into the tundra and perish at its southern limit. By contrast, Russia may benefit from an increased ability to grow crops in regions that were previously too cold, and this greater productivity would help absorb atmospheric carbon.”

Modelling impacts is complex, as Friend explained: “the increase in CO₂ in the atmosphere from the burning of fossil fuels creates global warming. CO₂ can act on vegetation, increasing their rate of photosynthesis and therefore productivity. However, in heatwaves, ecosystems can emit more CO₂ than they absorb from the atmosphere. We saw this in the 2003 European heatwave when temperatures rose 6°C above mean temperatures and the amount of CO₂ produced was sufficient to reverse the effect of four years of net ecosystem carbon sequestration.”

One of the greatest uncertainties in climate change is the feedback from changes in terrestrial carbon cycling. “Many scientists think that if soil warms it will release carbon because of the increased breakdown of dead organic matter by bacteria and fungi,” added Friend. “But there’s a lot of debate over whether this stimulation will be sustained over a long time – if it is, then you end up releasing enormous amounts of CO₂ into the atmosphere, causing further global warming.”

Working with PhD student Rozenn Keribin, Friend is using Darwin, the ̽��ֱ��’s High Performance Computing Service’s supercomputer, to run the simulations; what takes a month to perform on a PC can be easily accomplished overnight on Darwin.

As the results of each group’s simulations become available over the coming months, the data will be assembled and compared. Friend fully expects that this process will reveal differences: “each equivalent model has its own strengths and weaknesses. That’s why the comparison process is so valuable – no single model is sufficient but together we can reduce the uncertainty.”

Why is this so important? “To make policy you need to understand the impact of decisions,” said Friend. “There hasn’t been a coordinated impacts project for IPCC across sectors before, and now this is covering four key sectors across four climate change scenarios from multiple climate models. ̽��ֱ��idea is to understand at what point the increase in global temperature starts to have serious effects across all the sectors, so that policy makers can weigh up the probable impacts of allowing emissions to go above a certain level, and what mitigation strategies are necessary to avoid significant risk of dangerous climate change.”

For more information, please contact Louise Walsh (louise.walsh@admin.cam.ac.uk) at the ̽��ֱ�� of Cambridge Office of External Affairs and Communications.

A community-driven modelling effort aims to quantify one of the gravest of global uncertainties: the impact of global warming on the world’s food, health, vegetation and water.

Each model has its own strengths and weaknesses. That’s why the comparison process is so valuable – no single model is sufficient but together we can reduce the uncertainty.

Dr Andrew Friend

Andrew Friend

Initial ISI-MIP simulation showing the effects on vegetation productivity at the highest emissions scenario (reduction: red to yellow; increase: green to blue)

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