Country representatives and leading scientists met at the Food and Agriculture Organization of the United Nations (FAO) in November to identify how to reduce the cost of estimating greenhouse gas emissions from agriculture. The workshop was organized by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) and the Mitigation of Climate Change in Agriculture (MICCA) Programme of FAO.
The demand for improved emissions data is growing across the globe.
“Vietnam has set a goal, as part of our green growth strategy, to reduce the intensity of greenhouse gas emissions by 8 to 10 percent by 2050, compared to 2010 levels. In the agriculture sector, we want to increase agricultural production by 20% and reduce emissions and poverty by 20% by 2020. We need to be able to measure our progress,” said Mai van Trinh, Deputy Director General at Vietnam’s Institute for Agricultural Environment.
Reducing the cost of agricultural greenhouse gas quantification is critical to identify climate-smart priorities and to support measurement, reporting and verification related to Biennial Update Reports (BURs) and Nationally Appropriate Mitigation Actions (NAMAs). Climate-smart agriculture increases productivity and incomes, adaption and resilience to climate change, and reduces and/or removes greenhouse gas emissions wherever possible.
Links to all presentations, including this slide from Francesco Tubiello of FAO, are available at the end of this article.Challenges to estimating and monitoring emissions
Collecting data on farm activities, making measurements to establish emission factors, and establishing national systems for compiling and analyzing data are expensive, and uncertainties in current data remain high. In response, country representatives identified several key challenges to agricultural greenhouse gas accounting in developing countries.
Poor or insufficient data on agricultural activities: Countries need multiple kinds of data in order to estimate emissions, but these are often not available. For example, agricultural ministries may have national statistics on fertilizer imports and exports, but little data on crop-specific fertilizer use and area under each crop—necessary pieces of information for estimating emissions from fertilizer use.
Lack of emission factors: Emission factors are values that are used to relate a greenhouse-gas-generating activity (such as cattle production) with the quantity of a greenhouse gas released into the atmosphere. Such values are specific to particular environments and management systems, and they are often unavailable for developing country conditions. The relationship between activities and emissions can also be quantified using complex models, but both approaches require numerous field measurements to calculate emission factors or calibrate and validate models. There is particular scarcity of data on livestock systems.
Access to data and coordination: Information on agricultural activities is sometimes collected by multiple institutions for their own uses. According to Michael Phiri, Monitoring and Evaluation Specialist at the Zambia Environmental Management Agency, “Data sharing becomes a challenge because the data are in formats that are not compatible, or different ministries collect the same information but their statistics conflict each other. Then, which version should be used?”A preliminary action plan for reducing costs
Workshop participants developed action points for reducing the cost of greenhouse gas emission estimates in different agriculture sectors.
Incorporate climate-relevant data into agricultural censuses and surveys. Integrating GHG-relevant information into agricultural censuses is an efficient way to collect such data. This may become standard in 2020 census rounds, as FAO has just developed a new module for GHG-relevant data within the World Census of Agriculture. Look for the module to be published soon. Such data can also be included in other national surveys; George Phiri, Coordinator of FAO’s Climate-Smart Agriculture project in Malawi, described in his presentation how Malawi’s National Statistics Office has incorporated questions on land management into its Integrated Household Survey.
Outsource data collection to the crowd. New applications such as Geo-Wiki ask people to interpret visual images in order to improve land cover data. With the spread of texting and smartphone technology in developing countries, such “citizen science” approaches have big potential. Other applications such as Collect Earth combine freely available visual data from NASA and USGS with cloud-based processing services like Google Earth Engine to allow desk-based data collection by in-country experts.
Integrate measurements and modeling. Models are key to estimating emissions without the need for direct measurement, but models need to be validated and calibrated to local conditions. Researchers undertaking measurements could collect auxiliary data such as rainfall, temperature, and crop performance to support models. Klaus Butterbach-Bahl described guidelines for selecting auxiliary variables when measuring greenhouse gas emissions from soils. Models can be used to identify areas of greatest uncertainty in order to prioritize measurements.
Target measurements to maximize usefulness. In addition to prioritizing based on areas of greatest uncertainty, targeting key farming systems and practices and using statistical sampling to efficiently capture information can reduce data needs.
Mauricio Chacon, coordinator of Costa Rica’s NAMA for livestock, described the approach he and his colleagues used: “We developed 17 clusters of livestock systems according to agro-ecological zones and animal management, and these clusters explain most of the variability in emissions. Now we can develop emission factors for these clusters, and not spend money on unnecessary measurements. We also reduced the uncertainty of estimates, because for each cluster we could describe in better detail the feeding and management of the animals.”
Improve use of global databases for emissions. Stephen Ogle of Colorado State University suggested that an expert group could support data synthesis and modeling from existing literature. This would generate much-needed additional emissions factors for more locations and management practices. Further, people conducting measurements and calibrating models should make concerted efforts to share their information in platforms such as the Emissions Factor Data Base (EFDB) and Global Research Alliance Modeling Platform (GRAMP) so it can be used at national, sub-national and international levels.
Build the right capacities. “We always just say ‘we need more capacity’! But we need the right capacity,” several workshop participants emphasized. Developing countries need not only training, but also long-term mentoring and follow-up. Capacity is needed locally for field data collection, and nationally for identifying relevant tools, analyzing and interpreting data, and modeling.
Link adaptation and mitigation to motivate action. Participants repeatedly emphasized that there are complementarities between adaptation- and mitigation-related information. Explicitly linking the two can both reduce data needs and provide incentives for action.
Workshop participants committed to furthering these initiatives, and CCAFS and FAO will use this information to inform policies, protocols, and decision-making.The action points were further discussed at an FAO-IPCC-IFAD expert meeting on use of FAO data and IPCC GHG inventory guidelines for agriculture and land use, held immediately following at FAO. A complete set of action points, video interviews, and progress made to date will be released in a forthcoming workshop report. More information about the workshop is available from FAO-MICCA.Presentations
Challenges for agricultural greenhouse gas quantification
- Challenges for agricultural greenhouse gas quantification. Fahmuddin Agus, Indonesian Soil Research Institute
- GHG emission in agriculture in Vietnam. Mai van Trinh, Institute for Agricultural Environment, Vietnam
- GHG estimations for agriculture in Kenya. Michael Okumu, Ministry of Agriculture, Livestock and Fisheries, Kenya
- GHG inventory in Zambia. Michael Phiri, Zambia Environmental Management Agency
Emissions data guidelines of UNFCCC and climate finance mechanisms
- UNFCCC inventory reporting needs, collecting data and using this information to inform nationally appropriate mitigation actions (NAMAs) and low-emissions development strategies (LEDS). Stephen Ogle, Colorado State University, USA
- GHG accounting methods and requirements for Global Environment Facility projects. Ulrich Apel, Global Environment Facility (GEF)
- Clean Development Mechanism methodologies for the agriculture sector. Kenjiro Suzuki, United Nations Climate Change Secretariat
Innovations that decrease the costs of collecting biophysical and activity data
- Refining estimates with national survey data: example of the Malawi Integrated Household Survey. George Phiri, Food and Agriculture Organization Office, Malawi
- Collect Earth: multi-purpose land monitoring. Remote sensing activity data: Open Foris suite Alfonso Sánchez-Paus Díaz, FAO
- Using new soil data products for GHG estimation. Freddy Nachtergaele, FAO
- Informed sampling for testing mitigation options to reduce costs. Mariana Rufino, Center for International Forestry Research (CIFOR), Indonesia
- Potential for crowdsourcing and using mobile phone technology. Linda See, International Institute for Applied Systems Analysis (IIASA), Austria
- Approaches to activity data collection in livestock systems. Ed Charmley, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia
Available emission factor data and low-cost methods for greenhouse gas data estimation
- FAOSTAT emissions database: available data and major gaps. Francesco Tubiello, FAO
Methods for low-cost field measurement
- Soil carbon stocks and changes: Land Degradation Surveillance Framework. Vince Lang, Szent Istvan University, Hungary
- Quantifying greenhouse gas emissions from managed and natural soils. Klaus Butterbach-Bahl, International Livestock Research Institute (ILRI), Kenya
- Developing country-specific emission factors for livestock systems in Colombia. Edgar Cardenas, Universidad Nacional de Colombia
- Global Livestock Environmental Assessment Model – GLEAM. Carolyn Opio, FAO
- CCAFS-MOT: a decision support tool for geographic optimisation of agricultural mitigation options. Diana Feliciano, Jon Hillier, Sylvia Vetter, University of Aberdeen, UK
- EX-ACT introduction and training. Louis Bockel, FAO
The German Ministry for Economic Cooperation and Development (BMZ) has just approved a small grant to the International Center for Tropical Agriculture (CIAT) for a project entitled the ‘potential farm to landscape impact and adoption of forage technologies in smallholder dairy production systems in Tanzania.’ The project will start in January 2015 and run for two years. It is aligned to the CGIAR research program on livestock and fish.
The overall project goal is to improve the productivity and livelihoods of smallholder dairy farmers with minimum trade-offs for the environment through increased adoption of improved forage technologies. It will raise awareness among stakeholders (development organizations, policy makers, farmers) about potential impacts of forage technologies on productivity, environment, and livelihoods and adoption potential and barriers so that they can better target their interventions.
The first step in the project is to classify the crop-livestock systems with special regard to feeding systems, using existing household datasets, feeding system assessment and newly collected data. The aim is to quantify feeding baskets and feeding gaps, thereby identifying bottlenecks and entry points and providing necessary input data for modeling efforts.
In a second step, environmental effects of forage technologies will be assessed at farm to landscape level. The ‘CropSyst’ model will be used to simulate the growth and yield of crops in response to soil and climatic conditions under a range of environmental effectsm, including soil C dynamics, N2O emissions, N leaching, soil erosion and soil water dynamics. Methane emissions can be modeled with the Ruminant model of CSIRO Australia. The farm level environmental information will be integrated in whole farm trade-off modeling to assess potential multi-dimensional impacts of forage technologies, e.g. using the whole farm model FarmDESIGN hosted by Wageningen University. Similar trade-off analysis will be conducted at landscape level using spatial data, GIS software and modeling tools such as LandscapeIMAGE from Wageningen University.
CIAT and partner staff and students will be trained in all modeling approaches. The Tanzanian Livestock Research Institute (TALIRI) will assist in following up and agronomic and soil data collection from forage trials. They will further take the leading role in capacity building of farmers and extension staff in establishment, maintenance, utlization and conservation of improved forages through training and exchange visits.
Moreover, TALIRI will continue to strengthen the already established feed Innovation Platforms (IPs) by actively engaging all stakeholders along the dairy value chain.
The third output will focus on the adoption potential of forage technologies, and will use a qualitative participatory expert-based assessment approach called QAToCA (delivered by ZALF – the Leibniz Centre for Agricultural Landscape Research in Germany). The adapted version of QAToCA for forage technologies will specifically focus on analyzing the influence innovations, stakeholder capacities, institutional conditions, markets and gender on adoption potential of forage technologies.
The project will interact closely with the dairy platforms of the Livestock and Fish program in Tanzania. Livestock and Fish scientists are participating in different dairy development platforms at national, regional and local level and there is active demand from stakeholders for science-supported development interventions.
The project complements ongoing projects, mainly a) the MilkIT project, which ends in December 2014 and has established participatory on-farm trials with farmers in Tanga and Morogoro provinces; b) the CLEANED project, which finishes at the end of 2014 and established a framework for ex-ante environmental impact assessment of smallholder dairy interventions; c) the Sustainable intensification through forages project which started in July 2014, mainly aiming at assessing potential environmental and productivity impacts of forage interventions at plot to farm level; and the d) the MoreMilkiT project which focuses on value chain aspects (commercialization, institutions, business models, and livelihoods of dairy development.
More information from Ms. Birthe Paul (CIAT)
Filed under: Africa, Animal Feeding, Cattle, CIAT, CRP37, Dairying, Feeds, Forages, Project, Research, Southern Africa, Tanzania, Value Chains
Georgia O’Keefe, Cow’s Skull: Red, White and Blue, 1931 (via Metropolitan Museum of Art).
There’s a new feature article in National Geographic this month titled: Carnivore’s Dilemma. Written by Robert Kunzig and photographed by Brian Finke, the feature asks, and attempts to answer, the question: ‘Is America’s appetite for meat bad for the planet?’
It’s a good, if ambitious, question to set.
For example, check which of the following is true: Meat is ‘Unhealthy. Nutritious. Cruel. Delicious. Unsustainable. All-American.’
‘In the beef debate’, Kunzig begins, ‘there are so many sides.’
Meat is murder. Meat—especially beef—is cigarettes and a Hummer rolled into one. For the sake of the animals, our own health, and the health of the planet, we must eat less of it.
Meat is delicious. Meat is nutritious. Global demand is soaring for good reason, and we must find a way to produce more of it.
In short, meat—especially beef—has become the stuff of fierce debate.
Blek Le Rat, I Love Beef (street art) (via Wikiart).
‘People can’t settle that debate for others—Americans, say, can’t decide how much beef or other meat Chinese should eat as their living standards improve. But each of us takes a personal stand with every trip to the supermarket. Critics of industrial-scale beef production say it’s warming our climate, wasting land we could use to feed more people, and polluting and wasting precious water—all while subjecting millions of cattle to early death and a wretched life in confinement. Most of us, though, have little idea how our beef is actually produced. Last January, as part of a longer journey into the world of meat, I spent a week at Wrangler, in Tulia, Texas. I was looking for an answer to one fundamental question: Is it all right for an American to eat beef? . . .
‘In 1976 per capita beef consumption peaked in the United States at 91.5 pounds a year. It has since fallen more than 40 percent. Last year Americans ate on average 54 pounds of beef each, about the same amount as a century ago. Instead we eat twice as much chicken as we did in 1976 and nearly six times as much as a century ago. It’s cheaper and supposedly better for our hearts. We slaughter more than eight billion chickens a year now in the U.S., compared with some 33 million cattle. . . .
Roy Lichtenstein, Standing Rib, 1962 (via Wikiart).
In 2013 the U.S. produced almost the same amount of beef as it did in 1976, about 13 million tons. It achieved this while slaughtering 10 million fewer cattle, from a herd that was almost 40 million head smaller. The average slaughter animal packs 23 percent more meat these days than in 1976. To the people at Cactus Feeders, that’s a technological success story—one that meat producers will need to expand on as global demand for meat keeps rising. . . .
‘Are feedlots sustainable? The question has too many facets for there to be an easy answer. . . . The issue that concerns Defoor most is water. The panhandle farmers who supply corn and other crops to the feedlots are draining the Ogallala aquifer; at the current pace it could be exhausted in this century. But Texas feedlots long ago outgrew the local grain supply. Much of the corn now comes by train from the corn belt.
The biggest, most mind-numbing issue of all is the global one: How do we meet demand for meat while protecting biodiversity and fighting climate change? A common argument these days is that people in developed countries need to eat less meat in general, eat chicken instead of beef, and, if they must eat beef, make it grass fed. I’ve come to doubt that the solution is that simple. . . .
Jamie Wyeth, Angus, Study, 1974 (via Wikiart).
‘[W]ould Americans help feed the world if they ate less beef? The argument that it’s wasteful to feed grain to animals, especially cattle—which pound for pound require four times as much of it as chickens—has been around at least since Diet for a Small Planet was published in 1971. The portion of the U.S. grain harvest consumed by all animals, 81 percent then, has plummeted to 42 percent today, as yields have soared and more grain has been converted to ethanol. Ethanol now consumes 36 percent of the available grain, beef cattle only about 10 percent. Still, you might think that if Americans ate less beef, more grain would become available for hungry people in poor countries.
‘There’s little evidence that would happen in the world we actually live in. Using an economic model of the world food system, researchers at the International Food Policy Research Institute (IFPRI) in Washington, D.C., have projected what would happen if the entire developed world were to cut its consumption of all meat by half—a radical change. “The impact on food security in developing countries is minimal,” says Mark Rosegrant of IFPRI. Prices for corn and sorghum drop, which helps a bit in Africa, but globally the key food grains are wheat and rice. If Americans eat less beef, corn farmers in Iowa won’t export wheat and rice to Africa and Asia.
Chairn Soutine, Carcass of Beef, 1924 (via Wikiart).
‘The notion that curbing U.S. beef eating might have a big impact on global warming is similarly suspect. A study last year by the UN Food and Agriculture Organization (FAO) concluded that beef production accounts for 6 percent of global greenhouse gas emissions. But if the world abstained entirely from beef, emissions would drop by less than 6 percent, because more than a third of them come from the fertilizer and fossil fuels used in raising and shipping feed grain. Those farmers would continue to farm—after all, there’s a hungry world to feed.
‘If Americans eliminated beef cattle entirely from the landscape, we could be confident of cutting emissions by about 2 percent—the amount that beef cattle emit directly by belching methane and dropping manure that gives off methane and nitrous oxide. We made that kind of emissions cut once before, in a regrettable way. According to an estimate by A. N. Hristov of Penn State, the 50 million bison that roamed North America before settlers arrived emitted more methane than beef cattle do today.
‘The problem of global warming is overwhelmingly one of replacing fossil fuels with clean energy sources—but it’s certainly true that you can reduce your own carbon footprint by eating less beef. If that’s your goal, though, you should probably avoid grass-fed beef (or bison). . . . If we were to close all the feedlots and finish all cattle on pasture, we’d need more land and a much larger cattle herd, emitting a lot more methane per animal, to meet the demand for beef.
Edward Hicks, The Cornell Farm, 1848 (via National Gallery of Art).
‘Here’s the inconvenient truth: Feedlots, with their troubling use of pharmaceuticals, save land and lower greenhouse gas emissions. . . . “We have got to intensify. We’ve got to produce more with less.”
‘Even proponents acknowledge that grass-fed beef can’t meet the U.S. demand, let alone a growing global demand. . . .
There’s no doubt that eating less beef wouldn’t hurt me or most Americans. But the science is unclear on just how much it would help us—or the planet.
‘What my reporting had really left me wanting to say no to was antibeef zealotry. That, and the immoderate penchant we Americans have for reducing complex social problems—diet, public health, climate change, food security—to morality tales populated by heroes and villains. . . .’
Read the whole illustrated feature article written by Robert Kunzig and photographed by Brian Finke at National Geographic: Carnivore’s dilemma, Nov 2014.
Read more on this topic on this blog:
Filed under: Animal Feeding, Animal Health, Animal Production, Article, Cattle, Consumption, Environment, Farming Systems, Intensification, Livestock Systems, North America, USA Tagged: IFPRI, Livestock goods and bads, National Geographic