Climate change mitigation through livestock system transitions

By Petr Havlík, Hugo Valin, Mario Herrero, Michael Obersteiner, Erwin Schmid, Mariana C. Rufino, Aline Mosnier, P. K. Thornton, H. Böttcher, R. Conant and 5 more. Proceedings of the National Academy of Sciences of the United States of America, 2014

635 citations recorded by the source corpus.

Subfields: Ecology, Economics and Econometrics, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/404640a63f6e048a396d88eb7db696b5eb7063b0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Mario Herrero
2. P. K. Thornton
3. E. Röös
4. M. Patel
5. Christoph Müller
6. Pete Smith
7. D. Little
8. Elke Stehfest

In Economics and Econometrics

1. Volker Krey
2. Keywan Riahi
3. S. Pachauri
4. Pete Smith
5. Joeri Rogelj
6. E. Röös
7. M. Patel
8. H. Meijl

In Environmental Engineering

1. Volker Krey
2. E. Röös
3. M. Patel
4. Michael Obersteiner
5. Mario Herrero
6. Joeri Rogelj
7. Petr Havlík
8. S. Pachauri

Citations in the corpus

• Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science (2017, background): “Havlik et al. (2014) provides an overview of integrated livestock modeling and its use inmitigating climate change.”
• The vulnerabilities of agricultural land and food production to future water scarcity (2019, methodology): “Studies using models such as GLOBIOM and IMAGE (Havlik et al., 2014; Stehfest et al., 2014) provide estimates of the extent of cropland and pasture that are required to feed national and global populations in the future, under different shared socio-economic pathways (SSPs).”
• Greenhouse gas emissions from current and enhanced policies of China until 2030: Can emissions peak before 2030? (2016, methodology): “Both methods were supplemented with land use, land-use change and forestry (LULUCF) CO2 emission projections based on land-use and agricultural policies using IIASA's global land-use model GLOBIOM (Havlík et al., 2014) and global forest model G4M (Gusti, 2010).”
• Assessing global resource use and greenhouse emissions to 2050, with ambitious resource efficiency and climate mitigation policies (2017, methodology): “GTEM carbon prices and biomass demand for the four different scenarios were used to find matching points in the GLOBIOM solution space, and the corresponding results were added to GTEM output.”
• Could consumption of insects, cultured meat or imitation meat reduce global agricultural land use? (2017, background): “Therefore, changing demands on agricultural production, and in particular for animal products (i.e. meat, milk and eggs), has the potential to substantially alter GHG emissions (Bustamante et al., 2014; Havlík et al., 2014).”
• A multi-model assessment of food security implications of climate change mitigation (2019, neutral): “Environmental science & technology 2015, 49(12): 7245698 7253.”
• Comparing impacts of climate change and mitigation on global agriculture by 2050 (2018, result): “These conclusions are consistent with Havlı́k et al (2015a) who considered such scenarios in a single model framework.”
• Greedy or needy? Land use and climate impacts of food in 2050 under different livestock futures (2017, background): “Intensifying (INT) or abandoning (IDP and IDA) pure (non-dairy) beef production would save large areas of land, and reduce greenhouse gas emissions greatly, relative to business as usual projections (de Oliveira Silva et al., 2016; Havlík et al., 2014).”
• Climate-smart agriculture global research agenda: scientific basis for action (2014, background): “adaptation in the face of climate change [90,110] (Figure 4).”