This page has only limited features, please log in for full access.
Background Climate change presents an increasing challenge for food-nutrition security. Nutrition metrics calculated from quantitative food system projections can help focus policy actions. Objectives To estimate future chronic and hidden hunger disability-adjusted life years (DALYs)—due to protein-energy undernutrition and micronutrient deficiencies, respectively—using food systems projections to evaluate the potential impact of climate change and agricultural sector investment for adaptation. Methods We use a novel combination of a chronic and hidden hunger DALY estimation procedure and food system projections from quantitative foresight modeling to assess DALYs under alternative agricultural sector scenarios to midcentury. Results Total chronic and hidden hunger DALYs are projected to increase globally out to 2050—by over 30 million compared with 2010—even without climate change. Climate change increases total DALY change between 2010 and 2050 by nearly 10% compared with no climate change. Agricultural sector investments show promise for offsetting these impacts. With investments, DALY incidence due to chronic and hidden hunger is projected to decrease globally in 2050 by 0.24 and 0.56 per 1000 capita, respectively. Total global DALYs will still rise because projected population growth will outpace the rate reduction, especially in Africa south of the Sahara. However, projections also show important regional reductions in total DALYs due to chronic (13.9 million in South Asia, 4.3 million in East Asia and the Pacific) and hidden hunger (7.5 million in East Asia and the Pacific) with investments. Conclusions Food system projections to 2050 show a decreasing DALY incidence from both chronic and hidden hunger. Population growth is projected to outpace these improvements and lead to increasing total chronic and hidden hunger DALYs globally, concentrated in Africa south of the Sahara. Climate change increases per-capita chronic and hidden hunger DALY incidence compared with no climate change. Agricultural sector investments show the potential to offset the climate impact on DALYs.
Timothy B Sulser; Robert H Beach; Keith D Wiebe; Shahnila Dunston; Naomi K Fukagawa. Disability-adjusted life years due to chronic and hidden hunger under food system evolution with climate change and adaptation to 2050. The American Journal of Clinical Nutrition 2021, 114, 550 -563.
AMA StyleTimothy B Sulser, Robert H Beach, Keith D Wiebe, Shahnila Dunston, Naomi K Fukagawa. Disability-adjusted life years due to chronic and hidden hunger under food system evolution with climate change and adaptation to 2050. The American Journal of Clinical Nutrition. 2021; 114 (2):550-563.
Chicago/Turabian StyleTimothy B Sulser; Robert H Beach; Keith D Wiebe; Shahnila Dunston; Naomi K Fukagawa. 2021. "Disability-adjusted life years due to chronic and hidden hunger under food system evolution with climate change and adaptation to 2050." The American Journal of Clinical Nutrition 114, no. 2: 550-563.
Mitigation pathways by Integrated Assessment Models (IAMs) describe future emissions that keep global warming below specific temperature limits and are compared with countries’ collective greenhouse gas (GHG) emission reduction pledges. This is needed to assess mitigation progress and inform emission targets under the Paris Agreement. Currently, however, a mismatch of ~5.5 GtCO2 yr−1 exists between the global land-use fluxes estimated with IAMs and from countries’ GHG inventories. Here we present a ‘Rosetta stone’ adjustment to translate IAMs’ land-use mitigation pathways to estimates more comparable with GHG inventories. This does not change the original decarbonization pathways, but reallocates part of the land sink to be consistent with GHG inventories. Adjusted cumulative emissions over the period until net zero for 1.5 or 2 °C limits are reduced by 120–192 GtCO2 relative to the original IAM pathways. These differences should be taken into account to ensure an accurate assessment of progress towards the Paris Agreement. There is a mismatch between emission estimates from global land use calculated from IAMs and countries’ greenhouse gas inventories. This study presents a method for reconciling these estimates by reallocating part of the land-use sink, facilitating progress assessment towards climate goals.
Giacomo Grassi; Elke Stehfest; Joeri Rogelj; Detlef van Vuuren; Alessandro Cescatti; Jo House; Gert-Jan Nabuurs; Simone Rossi; Ramdane Alkama; Raúl Abad Viñas; Katherine Calvin; Guido Ceccherini; Sandro Federici; Shinichiro Fujimori; Mykola Gusti; Tomoko Hasegawa; Petr Havlik; Florian Humpenöder; Anu Korosuo; Lucia Perugini; Francesco N. Tubiello; Alexander Popp. Critical adjustment of land mitigation pathways for assessing countries’ climate progress. Nature Climate Change 2021, 11, 425 -434.
AMA StyleGiacomo Grassi, Elke Stehfest, Joeri Rogelj, Detlef van Vuuren, Alessandro Cescatti, Jo House, Gert-Jan Nabuurs, Simone Rossi, Ramdane Alkama, Raúl Abad Viñas, Katherine Calvin, Guido Ceccherini, Sandro Federici, Shinichiro Fujimori, Mykola Gusti, Tomoko Hasegawa, Petr Havlik, Florian Humpenöder, Anu Korosuo, Lucia Perugini, Francesco N. Tubiello, Alexander Popp. Critical adjustment of land mitigation pathways for assessing countries’ climate progress. Nature Climate Change. 2021; 11 (5):425-434.
Chicago/Turabian StyleGiacomo Grassi; Elke Stehfest; Joeri Rogelj; Detlef van Vuuren; Alessandro Cescatti; Jo House; Gert-Jan Nabuurs; Simone Rossi; Ramdane Alkama; Raúl Abad Viñas; Katherine Calvin; Guido Ceccherini; Sandro Federici; Shinichiro Fujimori; Mykola Gusti; Tomoko Hasegawa; Petr Havlik; Florian Humpenöder; Anu Korosuo; Lucia Perugini; Francesco N. Tubiello; Alexander Popp. 2021. "Critical adjustment of land mitigation pathways for assessing countries’ climate progress." Nature Climate Change 11, no. 5: 425-434.
Future sector-specific water withdrawals at a temporal resolution capable of representing patterns in seasonality and a commonly used spatial resolution are an important factor to consider for energy, water, land and environmental research. Projected water withdrawals that are harmonized with assumptions for alternate futures that capture socioeconomic and climatic variation are critical for many modeling studies on future global and regional dynamics. Here we generate a novel global gridded water withdrawals dataset by coupling the Global Change Analysis Model (GCAM) with a land use spatial downscaling model (Demeter), a global hydrologic framework (Xanthos) and a water withdrawal downscaling model (Tethys) for the five Shared Socioeconomic Pathways (SSPs) and four Representative Concentration Pathways (RCPs) scenarios. The dataset provides sectoral monthly data at 0.5° resolution for years 2015 to 2100. The presented dataset will be useful for both global and regional analysis looking at the impacts of socioeconomic, climate and technological futures as well as in characterizing the uncertainties associated with these impacts.
Zarrar Khan; Neal Graham; Chris Vernon; Thomas Wild; Min Chen; Katherine Calvin. A global gridded monthly water withdrawal dataset for multiple sectors from 2015 to 2100 at 0.5° resolution under a range of socioeconomic and climate scenarios. 2021, 1 .
AMA StyleZarrar Khan, Neal Graham, Chris Vernon, Thomas Wild, Min Chen, Katherine Calvin. A global gridded monthly water withdrawal dataset for multiple sectors from 2015 to 2100 at 0.5° resolution under a range of socioeconomic and climate scenarios. . 2021; ():1.
Chicago/Turabian StyleZarrar Khan; Neal Graham; Chris Vernon; Thomas Wild; Min Chen; Katherine Calvin. 2021. "A global gridded monthly water withdrawal dataset for multiple sectors from 2015 to 2100 at 0.5° resolution under a range of socioeconomic and climate scenarios." , no. : 1.
The world has experienced a vast increase in agricultural production since the middle of the last century. Agricultural land area has also increased at the expense of natural lands over this period, though at a lower rate than production. Future changes in land use and cover have important implications not only for agriculture but for energy, water use, and climate. However, these future changes are driven by a complex combination of uncertain socioeconomic, technological, and other factors. Estimates of future land use and land cover differ significantly across economic models of agricultural production, and efforts to evaluate these economic models over history have been limited. In this study, we use an economic model of land use, gcamland, to systematically explore a large set of model parameter perturbations and alternate methods for forming expectations about uncertain crop yields and prices. We run gcamland simulations with these parameter sets over the historical period in the United States to explore model fitness and to identify combinations that improve fitness. We find that an adaptive expectation approach minimizes the error between simulated outputs and observations, with parameters that suggest that for most crops landowners put a significant weight on previous information. Interestingly, for corn, where ethanol policies have led to a rapid growth in demand, the resulting parameters show that a larger weight is placed on more recent information. We conclude with the observation that historical modeling exercises such as this study are valuable both for understanding real world drivers of land use change and for informing modeling of future land use change.
Katherine V. Calvin; Abigail Snyder; Xin Zhao; Marshall Wise. Modeling Land Use and Land Cover Change: Using a Hindcast to Estimate Economic Parameters in gcamland v2.0. 2020, 2020, 1 -25.
AMA StyleKatherine V. Calvin, Abigail Snyder, Xin Zhao, Marshall Wise. Modeling Land Use and Land Cover Change: Using a Hindcast to Estimate Economic Parameters in gcamland v2.0. . 2020; 2020 ():1-25.
Chicago/Turabian StyleKatherine V. Calvin; Abigail Snyder; Xin Zhao; Marshall Wise. 2020. "Modeling Land Use and Land Cover Change: Using a Hindcast to Estimate Economic Parameters in gcamland v2.0." 2020, no. : 1-25.
Katherine V. Calvin; Abigail Snyder; Xin Zhao; Marshall Wise. Supplementary material to "Modeling Land Use and Land Cover Change: Using a Hindcast to Estimate Economic Parameters in gcamland v2.0". 2020, 1 .
AMA StyleKatherine V. Calvin, Abigail Snyder, Xin Zhao, Marshall Wise. Supplementary material to "Modeling Land Use and Land Cover Change: Using a Hindcast to Estimate Economic Parameters in gcamland v2.0". . 2020; ():1.
Chicago/Turabian StyleKatherine V. Calvin; Abigail Snyder; Xin Zhao; Marshall Wise. 2020. "Supplementary material to "Modeling Land Use and Land Cover Change: Using a Hindcast to Estimate Economic Parameters in gcamland v2.0"." , no. : 1.
Most studies assessing climate impacts on agriculture have focused on average changes in market-mediated responses (e.g., changes in land use, production, and consumption). However, the response of global agricultural markets to interannual variability in climate and biophysical shocks is poorly understood and not well represented in global economic models. Here we show a strong transmission of interannual variations in climate-induced biophysical yield shocks to agriculture markets, which is further magnified by endogenous market fluctuations generated due to producers’ imperfect expectations of market and weather conditions. We demonstrate that the volatility of crop prices and consumption could be significantly underestimated (i.e., on average by 55% and 41%, respectively) by assuming perfect foresight, a standard assumption in the economic equilibrium modeling, compared with the relatively more realistic adaptive expectations. We also find heterogeneity in interannual variability across crops and regions, which is considerably mediated by international trade.
Xin Zhao; Katherine Calvin; Marshall Wise; Pralit Patel; Abigail Snyder; Stephanie Waldhoff; Mohamad Hejazi; James Edmonds. Impacts of interannual climate and biophysical variability on global agriculture markets. 2020, 1 .
AMA StyleXin Zhao, Katherine Calvin, Marshall Wise, Pralit Patel, Abigail Snyder, Stephanie Waldhoff, Mohamad Hejazi, James Edmonds. Impacts of interannual climate and biophysical variability on global agriculture markets. . 2020; ():1.
Chicago/Turabian StyleXin Zhao; Katherine Calvin; Marshall Wise; Pralit Patel; Abigail Snyder; Stephanie Waldhoff; Mohamad Hejazi; James Edmonds. 2020. "Impacts of interannual climate and biophysical variability on global agriculture markets." , no. : 1.
Global future land use (LU) is an important input for Earth system models for projecting Earth system dynamics and is critical for many modeling studies on future global change. Here we generated a new global gridded LU dataset using the Global Change Analysis Model (GCAM) and a land use spatial downscaling model, named Demeter, under the five Shared Socioeconomic Pathways (SSPs) and four Representative Concentration Pathways (RCPs) scenarios. Compared to existing similar datasets, the presented dataset has a higher spatial resolution (0.05° × 0.05°) and spreads under a more comprehensive set of SSP-RCP scenarios (in total 15 scenarios), and considers uncertainties from the forcing climates. We compared our dataset with the Land Use Harmonization version 2 (LUH2) dataset and found our results are in general spatially consistent with LUH2. The presented dataset will be useful for global Earth system modeling studies, especially for the analysis of the impacts of land use and land cover change and socioeconomics, as well as the characterizing the uncertainties associated with these impacts.
Min Chen; Chris R. Vernon; Neal T. Graham; Mohamad Hejazi; Maoyi Huang; Yanyan Cheng; Katherine Calvin. Global land use for 2015–2100 at 0.05° resolution under diverse socioeconomic and climate scenarios. Scientific Data 2020, 7, 1 -11.
AMA StyleMin Chen, Chris R. Vernon, Neal T. Graham, Mohamad Hejazi, Maoyi Huang, Yanyan Cheng, Katherine Calvin. Global land use for 2015–2100 at 0.05° resolution under diverse socioeconomic and climate scenarios. Scientific Data. 2020; 7 (1):1-11.
Chicago/Turabian StyleMin Chen; Chris R. Vernon; Neal T. Graham; Mohamad Hejazi; Maoyi Huang; Yanyan Cheng; Katherine Calvin. 2020. "Global land use for 2015–2100 at 0.05° resolution under diverse socioeconomic and climate scenarios." Scientific Data 7, no. 1: 1-11.
This paper documents the biogeochemistry configuration of the Energy Exascale Earth System Model (E3SM), E3SMv1.1‐BGC. The model simulates historical carbon cycle dynamics, including carbon losses predicted in response to land use and land cover change, and the responses of the carbon cycle to changes in climate. In addition, we introduce several innovations in the treatment of soil nutrient limitation mechanisms, including explicit dependence on phosphorus availability. The suite of simulations described here includes E3SM contributions to the Coupled Climate‐Carbon Cycle Model Intercomparison Project and other projects, as well as simulations to explore the impacts of structural uncertainty in representations of nitrogen and phosphorus limitation. We describe the model spinup and evaluation procedures, provide an overview of results from the simulation campaign, and highlight key features of the simulations. Cumulative warming over the twentieth century is similar to observations, with a mid‐century cold bias offset by stronger warming in recent decades. Ocean biomass production and carbon uptake are underpredicted, likely due to biases in ocean transport leading to widespread anoxia and undersupply of nutrients to surface waters. The inclusion of nutrient limitations in the land biogeochemistry results in weaker carbon fertilization and carbon‐climate feedbacks than exhibited by other Earth System Models that exclude those limitations. Finally, we compare with an alternative representation of terrestrial biogeochemistry, which differs in structure and in initialization of soil phosphorus. While both configurations agree well with observational benchmarks, they differ significantly in their distribution of carbon among different pools and in the strength of nutrient limitations.
S. M. Burrows; M. Maltrud; X. Yang; Q. Zhu; N. Jeffery; X. Shi; D. Ricciuto; S. Wang; G. Bisht; J. Tang; J. Wolfe; B. E. Harrop; B. Singh; L. Brent; S. Baldwin; T. Zhou; P. Cameron‐Smith; N. Keen; N. Collier; M. Xu; E. C. Hunke; S. M. Elliott; A. K. Turner; H. Li; H. Wang; J.‐C. Golaz; B. Bond‐Lamberty; F. M. Hoffman; W. J. Riley; P. E. Thornton; K. Calvin; L. R. Leung. The DOE E3SM v1.1 biogeochemistry configuration: description and simulated ecosystem‐climate responses to historical changes in forcing. Journal of Advances in Modeling Earth Systems 2020, 12, 1 .
AMA StyleS. M. Burrows, M. Maltrud, X. Yang, Q. Zhu, N. Jeffery, X. Shi, D. Ricciuto, S. Wang, G. Bisht, J. Tang, J. Wolfe, B. E. Harrop, B. Singh, L. Brent, S. Baldwin, T. Zhou, P. Cameron‐Smith, N. Keen, N. Collier, M. Xu, E. C. Hunke, S. M. Elliott, A. K. Turner, H. Li, H. Wang, J.‐C. Golaz, B. Bond‐Lamberty, F. M. Hoffman, W. J. Riley, P. E. Thornton, K. Calvin, L. R. Leung. The DOE E3SM v1.1 biogeochemistry configuration: description and simulated ecosystem‐climate responses to historical changes in forcing. Journal of Advances in Modeling Earth Systems. 2020; 12 (9):1.
Chicago/Turabian StyleS. M. Burrows; M. Maltrud; X. Yang; Q. Zhu; N. Jeffery; X. Shi; D. Ricciuto; S. Wang; G. Bisht; J. Tang; J. Wolfe; B. E. Harrop; B. Singh; L. Brent; S. Baldwin; T. Zhou; P. Cameron‐Smith; N. Keen; N. Collier; M. Xu; E. C. Hunke; S. M. Elliott; A. K. Turner; H. Li; H. Wang; J.‐C. Golaz; B. Bond‐Lamberty; F. M. Hoffman; W. J. Riley; P. E. Thornton; K. Calvin; L. R. Leung. 2020. "The DOE E3SM v1.1 biogeochemistry configuration: description and simulated ecosystem‐climate responses to historical changes in forcing." Journal of Advances in Modeling Earth Systems 12, no. 9: 1.
The Intergovernmental Panel on Climate Change (IPCC) reports provide policy-relevant insights about climate impacts, vulnerabilities and adaptation through a process of peer-reviewed literature assessments underpinned by expert judgement. An iconic output from these assessments is the burning embers diagram, first used in the Third Assessment Report to visualize reasons for concern, which aggregate climate-change-related impacts and risks to various systems and sectors. These burning embers use colour transitions to show changes in the assessed level of risk to humans and ecosystems as a function of global mean temperature. In this Review, we outline the history and evolution of the burning embers and associated reasons for concern framework, focusing on the methodological approaches and advances. While the assessment framework and figure design have been broadly retained over time, refinements in methodology have occurred, including the consideration of different risks, use of confidence statements, more formalized protocols and standardized metrics. Comparison across reports reveals that the risk level at a given temperature has generally increased with each assessment cycle, reflecting accumulating scientific evidence. For future assessments, an explicit, transparent and systematic process of expert elicitation is needed to enhance comparability, quality and credibility of burning embers. Burning embers figures are used to represent climate-change risk and their transitions. This Review outlines the history and evolution of the burning embers concept, focusing on methodological shifts that increase transparency and allow for a more systematic elicitation process in Intergovernmental Panel on Climate Change (IPCC) reports.
Zinta Zommers; Philippe Marbaix; Andreas Fischlin; Zelina Z. Ibrahim; Sean Grant; Alexandre K. Magnan; Hans-Otto Pörtner; Mark Howden; Katherine Calvin; Koko Warner; Wim Thiery; Zita Sebesvari; Edouard L. Davin; Jason P. Evans; Cynthia Rosenzweig; Brian C. O’Neill; Anand Patwardhan; Rachel Warren; Maarten K. Van Aalst; Margot Hulbert. Burning embers: towards more transparent and robust climate-change risk assessments. Nature Reviews Earth & Environment 2020, 1, 516 -529.
AMA StyleZinta Zommers, Philippe Marbaix, Andreas Fischlin, Zelina Z. Ibrahim, Sean Grant, Alexandre K. Magnan, Hans-Otto Pörtner, Mark Howden, Katherine Calvin, Koko Warner, Wim Thiery, Zita Sebesvari, Edouard L. Davin, Jason P. Evans, Cynthia Rosenzweig, Brian C. O’Neill, Anand Patwardhan, Rachel Warren, Maarten K. Van Aalst, Margot Hulbert. Burning embers: towards more transparent and robust climate-change risk assessments. Nature Reviews Earth & Environment. 2020; 1 (10):516-529.
Chicago/Turabian StyleZinta Zommers; Philippe Marbaix; Andreas Fischlin; Zelina Z. Ibrahim; Sean Grant; Alexandre K. Magnan; Hans-Otto Pörtner; Mark Howden; Katherine Calvin; Koko Warner; Wim Thiery; Zita Sebesvari; Edouard L. Davin; Jason P. Evans; Cynthia Rosenzweig; Brian C. O’Neill; Anand Patwardhan; Rachel Warren; Maarten K. Van Aalst; Margot Hulbert. 2020. "Burning embers: towards more transparent and robust climate-change risk assessments." Nature Reviews Earth & Environment 1, no. 10: 516-529.
Robert Fofrich; Dan Tong; Katherine Calvin; Harmen Sytze De Boer; Johannes Emmerling; Oliver Fricko; Shinichiro Fujimori; Gunnar Luderer; Joeri Rogelj; Steven J Davis. Early retirement of power plants in climate mitigation scenarios. Environmental Research Letters 2020, 15, 094064 .
AMA StyleRobert Fofrich, Dan Tong, Katherine Calvin, Harmen Sytze De Boer, Johannes Emmerling, Oliver Fricko, Shinichiro Fujimori, Gunnar Luderer, Joeri Rogelj, Steven J Davis. Early retirement of power plants in climate mitigation scenarios. Environmental Research Letters. 2020; 15 (9):094064.
Chicago/Turabian StyleRobert Fofrich; Dan Tong; Katherine Calvin; Harmen Sytze De Boer; Johannes Emmerling; Oliver Fricko; Shinichiro Fujimori; Gunnar Luderer; Joeri Rogelj; Steven J Davis. 2020. "Early retirement of power plants in climate mitigation scenarios." Environmental Research Letters 15, no. 9: 094064.
Ruth Delzeit; Robert Beach; Ruben Bibas; Wolfgang Britz; Jean Chateau; Florian Freund; Julien Lefevre; Franziska Schuenemann; Timothy B. Sulser; Hugo Valin; Bas Van Ruijven; Matthias Weitzel; Dirk Willenbockel; Krzysztof Wojtowicz. Linking global CGE models with sectoral models to generate baseline scenarios: Approaches, opportunities and pitfalls. Journal of Global Economic Analysis 2020, 5, 162 -195.
AMA StyleRuth Delzeit, Robert Beach, Ruben Bibas, Wolfgang Britz, Jean Chateau, Florian Freund, Julien Lefevre, Franziska Schuenemann, Timothy B. Sulser, Hugo Valin, Bas Van Ruijven, Matthias Weitzel, Dirk Willenbockel, Krzysztof Wojtowicz. Linking global CGE models with sectoral models to generate baseline scenarios: Approaches, opportunities and pitfalls. Journal of Global Economic Analysis. 2020; 5 (1):162-195.
Chicago/Turabian StyleRuth Delzeit; Robert Beach; Ruben Bibas; Wolfgang Britz; Jean Chateau; Florian Freund; Julien Lefevre; Franziska Schuenemann; Timothy B. Sulser; Hugo Valin; Bas Van Ruijven; Matthias Weitzel; Dirk Willenbockel; Krzysztof Wojtowicz. 2020. "Linking global CGE models with sectoral models to generate baseline scenarios: Approaches, opportunities and pitfalls." Journal of Global Economic Analysis 5, no. 1: 162-195.
Taran Faehn; Gabriel Bachner; Robert Beach; Jean Chateau; Shinichiro Fujimori; Madanmohan Ghosh; Meriem Hamdi-Cherif; Elisa Lanzi; Sergey Paltsev; Toon Vandyck; Bruno S L Cunha; Rafael Garaffa; Karl Steininger. Capturing key energy and emission trends in CGE models: Assessment of Status and Remaining Challenges. Journal of Global Economic Analysis 2020, 5, 196 -272.
AMA StyleTaran Faehn, Gabriel Bachner, Robert Beach, Jean Chateau, Shinichiro Fujimori, Madanmohan Ghosh, Meriem Hamdi-Cherif, Elisa Lanzi, Sergey Paltsev, Toon Vandyck, Bruno S L Cunha, Rafael Garaffa, Karl Steininger. Capturing key energy and emission trends in CGE models: Assessment of Status and Remaining Challenges. Journal of Global Economic Analysis. 2020; 5 (1):196-272.
Chicago/Turabian StyleTaran Faehn; Gabriel Bachner; Robert Beach; Jean Chateau; Shinichiro Fujimori; Madanmohan Ghosh; Meriem Hamdi-Cherif; Elisa Lanzi; Sergey Paltsev; Toon Vandyck; Bruno S L Cunha; Rafael Garaffa; Karl Steininger. 2020. "Capturing key energy and emission trends in CGE models: Assessment of Status and Remaining Challenges." Journal of Global Economic Analysis 5, no. 1: 196-272.
Timely and accurate agricultural information is needed to inform resource allocation and sustainable practices to improve food security in the developing world. Obtaining this information through traditional surveys is time consuming and labor intensive, making it difficult to collect data at the frequency and resolution needed to accurately estimate the planted areas of key crops and their distribution during the growing season. Remote sensing technologies can be leveraged to provide consistent, cost-effective, and spatially disaggregated data at high temporal frequency. In this study, we used imagery acquired from unmanned aerial vehicles to create a high-fidelity ground-truth dataset that included examples of large mono-cropped fields, small intercropped fields, and natural vegetation. The imagery was acquired in three rounds of flights at six sites in different agro-ecological zones to capture growing conditions. This dataset was used to train and test a random forest model that was implemented in Google Earth Engine for classifying cropped land using freely available Sentinel-1 and -2 data. This model achieved an overall accuracy of 83%, and a 91% accuracy for maize specifically. The model results were compared with Rwanda’s Seasonal Agricultural Survey, which highlighted biases in the dataset including a lack of examples of mixed land cover.
Meghan Hegarty-Craver; Jason Polly; Margaret O’Neil; Noel Ujeneza; James Rineer; Robert H. Beach; Daniel Lapidus; Dorota S. Temple. Remote Crop Mapping at Scale: Using Satellite Imagery and UAV-Acquired Data as Ground Truth. Remote Sensing 2020, 12, 1984 .
AMA StyleMeghan Hegarty-Craver, Jason Polly, Margaret O’Neil, Noel Ujeneza, James Rineer, Robert H. Beach, Daniel Lapidus, Dorota S. Temple. Remote Crop Mapping at Scale: Using Satellite Imagery and UAV-Acquired Data as Ground Truth. Remote Sensing. 2020; 12 (12):1984.
Chicago/Turabian StyleMeghan Hegarty-Craver; Jason Polly; Margaret O’Neil; Noel Ujeneza; James Rineer; Robert H. Beach; Daniel Lapidus; Dorota S. Temple. 2020. "Remote Crop Mapping at Scale: Using Satellite Imagery and UAV-Acquired Data as Ground Truth." Remote Sensing 12, no. 12: 1984.
This study quantifies the potential responses of 11 staple crop yields to projected changes in temperature and precipitation in Rwanda, using a cross sectional model based on yield data collected across more than 14,000 villages. We incorporated a relatively high spatial resolution dataset on crop productivity, considered a broad range of crops relevant to national agricultural production priorities, used environmental data developed specifically for Rwanda, and reported uncertainty both from our estimation model and due to uncertainty in future climate projections. We estimate that future climate change will have the largest impacts on potential productivity of maize, bush bean, and Irish potato. All three crops are likely to experience a reduction in potential yields of at least 10% under Representative Concentration Pathway (RCP) 4.5 and at least 15% under RCP 8.5 by 2050. Notably, these are important crops nationally, and three of the crops targeted by Rwanda’s Crop Intensification Program. We find that the most severe reductions in potential crop yields will occur in the drier eastern savannah and plateau regions, but that the impacts of climate change could be neutral or even positive in the highlands through mid-century. The refined spatial scale of our analysis allows us to identify potentially vulnerable regions where adaptation investments may need to be prioritized to support food security and climate resilience in Rwanda’s agricultural sector.
Kemen Austin; Robert Beach; Daniel Lapidus; Marwa Salem; Naomi Taylor; Mads Knudsen; Noel Ujeneza. Impacts of Climate Change on the Potential Productivity of Eleven Staple Crops in Rwanda. Sustainability 2020, 12, 4116 .
AMA StyleKemen Austin, Robert Beach, Daniel Lapidus, Marwa Salem, Naomi Taylor, Mads Knudsen, Noel Ujeneza. Impacts of Climate Change on the Potential Productivity of Eleven Staple Crops in Rwanda. Sustainability. 2020; 12 (10):4116.
Chicago/Turabian StyleKemen Austin; Robert Beach; Daniel Lapidus; Marwa Salem; Naomi Taylor; Mads Knudsen; Noel Ujeneza. 2020. "Impacts of Climate Change on the Potential Productivity of Eleven Staple Crops in Rwanda." Sustainability 12, no. 10: 4116.
Initial land cover distribution varies among Earth system models, an uncertainty in initial conditions that can substantially affect carbon and climate projections. We use the integrated Earth System Model to show that a 3.9 M km2 difference in 2005 global forest area (9‐14% of total forest area) generates uncertainties in initial atmospheric CO2 concentration, terrestrial carbon, and local temperature that propagate through a future simulation following the Representative Concentration Pathway 4.5. By 2095, the initial 6 ppmv uncertainty range increases to 9ppmv and the initial 26 PgC uncertainty range in terrestrial carbon increases to 33 PgC. The initial uncertainty range in annual average local temperature of ‐0.74 to 0.96 °C persists throughout the future simulation, with a seasonal maximum in Dec‐Jan‐Feb. These results highlight the importance of accurately characterizing historical land use and land cover to reduce overall initial condition uncertainty.
A.V. Di Vittorio; X. Shi; B. Bond‐Lamberty; K. Calvin; A. Jones. Initial Land Use/Cover Distribution Substantially Affects Global Carbon and Local Temperature Projections in the Integrated Earth System Model. Global Biogeochemical Cycles 2020, 34, 1 .
AMA StyleA.V. Di Vittorio, X. Shi, B. Bond‐Lamberty, K. Calvin, A. Jones. Initial Land Use/Cover Distribution Substantially Affects Global Carbon and Local Temperature Projections in the Integrated Earth System Model. Global Biogeochemical Cycles. 2020; 34 (5):1.
Chicago/Turabian StyleA.V. Di Vittorio; X. Shi; B. Bond‐Lamberty; K. Calvin; A. Jones. 2020. "Initial Land Use/Cover Distribution Substantially Affects Global Carbon and Local Temperature Projections in the Integrated Earth System Model." Global Biogeochemical Cycles 34, no. 5: 1.
Human land-use activities have resulted in large changes to the biogeochemical and biophysical properties of the Earth surface, with consequences for climate and other ecosystem services. In the future, land-use activities are likely to expand and/or intensify further to meet growing demands for food, fiber, and energy. As part of the World Climate Research Program Coupled Model Intercomparison Project (CMIP6), the international community is developing the next generation of advanced Earth System Models (ESMs) to estimate the combined effects of human activities (e.g. land use and fossil fuel emissions) on the carbon-climate system. A new set of historical data based on the History of the Global Environment database (HYDE), and multiple alternative scenarios of the future (2015–2100) from Integrated Assessment Model (IAM) teams, are required as input for these models. Here we present results from the Land-use Harmonization 2 (LUH2) project, with the goal to smoothly connect updated historical reconstructions of land-use with new future projections in the format required for ESMs. The harmonization strategy estimates the fractional land-use patterns, underlying land-use transitions, key agricultural management information, and resulting secondary lands annually, while minimizing the differences between the end of the historical reconstruction and IAM initial conditions and preserving changes depicted by the IAMs in the future. The new approach builds off a similar effort from CMIP5, and is now provided at higher resolution (0.25 × 0.25 degree), over a longer time domain (850–2100, with extensions to 2300), with more detail (including multiple crop and pasture types and associated management practices), using more input datasets (including Landsat remote sensing data), updated algorithms (wood harvest and shifting cultivation), and is assessed via a new diagnostic package. The new LUH2 products contain > 50 times the information content of the datasets used in CMIP5, and are designed to enable new and improved estimates of the combined effects of land-use on the global carbon-climate system.
George C. Hurtt; Louise Chini; Ritvik Sahajpal; Steve Frolking; Benjamin L. Bodirsky; Katherine Calvin; Jonathan C. Doelman; Justin Fisk; Shinichiro Fujimori; Kees Klein Goldewijk; Tomoko Hasegawa; Peter Havlik; Andreas Heinimann; Florian Humpenöder; Johan Jungclaus; Jed Kaplan; Jennifer Kennedy; Tamas Kristzin; David Lawrence; Peter Lawrence; Lei Ma; Ole Mertz; Julia Pongratz; Alexander Popp; Benjamin Poulter; Keywan Riahi; Elena Shevliakova; Elke Stehfest; Peter Thornton; Francesco N. Tubiello; Detlef P. Van Vuuren; Xin Zhang. Harmonization of Global Land-Use Change and Management for the Period 850–2100 (LUH2) for CMIP6. 2020, 2020, 1 -65.
AMA StyleGeorge C. Hurtt, Louise Chini, Ritvik Sahajpal, Steve Frolking, Benjamin L. Bodirsky, Katherine Calvin, Jonathan C. Doelman, Justin Fisk, Shinichiro Fujimori, Kees Klein Goldewijk, Tomoko Hasegawa, Peter Havlik, Andreas Heinimann, Florian Humpenöder, Johan Jungclaus, Jed Kaplan, Jennifer Kennedy, Tamas Kristzin, David Lawrence, Peter Lawrence, Lei Ma, Ole Mertz, Julia Pongratz, Alexander Popp, Benjamin Poulter, Keywan Riahi, Elena Shevliakova, Elke Stehfest, Peter Thornton, Francesco N. Tubiello, Detlef P. Van Vuuren, Xin Zhang. Harmonization of Global Land-Use Change and Management for the Period 850–2100 (LUH2) for CMIP6. . 2020; 2020 ():1-65.
Chicago/Turabian StyleGeorge C. Hurtt; Louise Chini; Ritvik Sahajpal; Steve Frolking; Benjamin L. Bodirsky; Katherine Calvin; Jonathan C. Doelman; Justin Fisk; Shinichiro Fujimori; Kees Klein Goldewijk; Tomoko Hasegawa; Peter Havlik; Andreas Heinimann; Florian Humpenöder; Johan Jungclaus; Jed Kaplan; Jennifer Kennedy; Tamas Kristzin; David Lawrence; Peter Lawrence; Lei Ma; Ole Mertz; Julia Pongratz; Alexander Popp; Benjamin Poulter; Keywan Riahi; Elena Shevliakova; Elke Stehfest; Peter Thornton; Francesco N. Tubiello; Detlef P. Van Vuuren; Xin Zhang. 2020. "Harmonization of Global Land-Use Change and Management for the Period 850–2100 (LUH2) for CMIP6." 2020, no. : 1-65.
Katherine Calvin; Ben Bond-Lamberty; Andrew Jones; Xiaoying Shi; Alan Di Vittorio; Peter Thornton. Corrigendum to “Characteristics of human-climate feedbacks differ at different radiative forcing levels”. (Global and planetary change 180 (2019) 126–135). Global and Planetary Change 2020, 198, 103189 .
AMA StyleKatherine Calvin, Ben Bond-Lamberty, Andrew Jones, Xiaoying Shi, Alan Di Vittorio, Peter Thornton. Corrigendum to “Characteristics of human-climate feedbacks differ at different radiative forcing levels”. (Global and planetary change 180 (2019) 126–135). Global and Planetary Change. 2020; 198 ():103189.
Chicago/Turabian StyleKatherine Calvin; Ben Bond-Lamberty; Andrew Jones; Xiaoying Shi; Alan Di Vittorio; Peter Thornton. 2020. "Corrigendum to “Characteristics of human-climate feedbacks differ at different radiative forcing levels”. (Global and planetary change 180 (2019) 126–135)." Global and Planetary Change 198, no. : 103189.
Accurate projections of seasonal agricultural output are essential for improving food security. However, the collection of agricultural information through seasonal agricultural surveys is often not timely enough to inform public and private stakeholders about crop status during the growing season. Acquiring timely and accurate crop estimates can be particularly challenging in countries with predominately smallholder farms because of the large number of small plots, intense intercropping, and high diversity of crop types. In this study, we used RGB images collected from unmanned aerial vehicles (UAVs) flown in Rwanda to develop a deep learning algorithm for identifying crop types, specifically bananas, maize, and legumes, which are key strategic food crops in Rwandan agriculture. The model leverages advances in deep convolutional neural networks and transfer learning, employing the VGG16 architecture and the publicly accessible ImageNet dataset for pretraining. The developed model performs with an overall test set F1 of 0.86, with individual classes ranging from 0.49 (legumes) to 0.96 (bananas). Our findings suggest that although certain staple crops such as bananas and maize can be classified at this scale with high accuracy, crops involved in intercropping (legumes) can be difficult to identify consistently. We discuss the potential use cases for the developed model and recommend directions for future research in this area.
Robert Chew; Jay Rineer; Robert Beach; Maggie O’Neil; Noel Ujeneza; Daniel Lapidus; Thomas Miano; Meghan Hegarty-Craver; Jason Polly; Dorota S. Temple. Deep Neural Networks and Transfer Learning for Food Crop Identification in UAV Images. Drones 2020, 4, 7 .
AMA StyleRobert Chew, Jay Rineer, Robert Beach, Maggie O’Neil, Noel Ujeneza, Daniel Lapidus, Thomas Miano, Meghan Hegarty-Craver, Jason Polly, Dorota S. Temple. Deep Neural Networks and Transfer Learning for Food Crop Identification in UAV Images. Drones. 2020; 4 (1):7.
Chicago/Turabian StyleRobert Chew; Jay Rineer; Robert Beach; Maggie O’Neil; Noel Ujeneza; Daniel Lapidus; Thomas Miano; Meghan Hegarty-Craver; Jason Polly; Dorota S. Temple. 2020. "Deep Neural Networks and Transfer Learning for Food Crop Identification in UAV Images." Drones 4, no. 1: 7.
Neal T Graham; Mohamad I Hejazi; Min Chen; Evan G R Davies; James A Edmonds; Son H Kim; Sean W D Turner; Xinya Li; Chris Vernon; Katherine Calvin; Fernando Miralles-Wilhelm; Leon Clarke; Page Kyle; Robert Link; Pralit Patel; Abigail C Snyder; Marshall A Wise. Humans drive future water scarcity changes across all Shared Socioeconomic Pathways. Environmental Research Letters 2020, 15, 014007 .
AMA StyleNeal T Graham, Mohamad I Hejazi, Min Chen, Evan G R Davies, James A Edmonds, Son H Kim, Sean W D Turner, Xinya Li, Chris Vernon, Katherine Calvin, Fernando Miralles-Wilhelm, Leon Clarke, Page Kyle, Robert Link, Pralit Patel, Abigail C Snyder, Marshall A Wise. Humans drive future water scarcity changes across all Shared Socioeconomic Pathways. Environmental Research Letters. 2020; 15 (1):014007.
Chicago/Turabian StyleNeal T Graham; Mohamad I Hejazi; Min Chen; Evan G R Davies; James A Edmonds; Son H Kim; Sean W D Turner; Xinya Li; Chris Vernon; Katherine Calvin; Fernando Miralles-Wilhelm; Leon Clarke; Page Kyle; Robert Link; Pralit Patel; Abigail C Snyder; Marshall A Wise. 2020. "Humans drive future water scarcity changes across all Shared Socioeconomic Pathways." Environmental Research Letters 15, no. 1: 014007.
Katherine Calvin; Robert Link; Marshall Wise. gcamland v1.0 – An R Package for Modelling Land Use and Land Cover Change. Journal of Open Research Software 2019, 7, 1 .
AMA StyleKatherine Calvin, Robert Link, Marshall Wise. gcamland v1.0 – An R Package for Modelling Land Use and Land Cover Change. Journal of Open Research Software. 2019; 7 (1):1.
Chicago/Turabian StyleKatherine Calvin; Robert Link; Marshall Wise. 2019. "gcamland v1.0 – An R Package for Modelling Land Use and Land Cover Change." Journal of Open Research Software 7, no. 1: 1.