Fourth National Climate Assessment

USGCRP

TRACEABLE ACCOUNTS

Process Description

Each regional author team organized a stakeholder engagement process to identify the highest-priority concerns, including priorities for agriculture and rural communities. Due to the heterogeneous nature of agriculture and rural communities, the national chapter leads (NCLs) and coauthor team put in place a structured process to gather and synthesize input from the regional stakeholder meetings. Where possible, one or more of the authors or the chapter lead author listened to stakeholder input during regional stakeholder listening sessions. Information about agriculture and rural communities was synthesized from the written reports from each regional engagement workshop. During the all-authors meeting on April 2–3, 2017, the NCL met with authors from each region and other national author teams to identify issues relevant to this chapter. To finalize our regional roll-up, a teleconference was scheduled with each regional author team to discuss agriculture and rural community issues. Most of the regional author teams identified issues related to agricultural productivity, with underlying topics dominated by drought, temperature, and changing seasonality. Grassland wildfire was identified as a concern in the Northern and Southern Great Plains. All regional author teams identified soil and water vulnerabilities as concerns, particularly as they relate to soil and water quality impacts and a depleting water supply, as well as reduced field operation days due to wet soils and an increased risk of soil erosion due to precipitation on frozen soil. Heat stress in rural communities and among agricultural workers was of concern in the Southeast, Southern Great Plains, Northwest, Hawaiʻi and Pacific Islands, U.S. Caribbean, and Northeast. Livestock health was identified as a concern in the Northeast, Midwest, U.S. Caribbean, and Southern Great Plains. Additional health-related concerns were smoke from wildfire, pesticide impacts, allergens, changing disease vectors, and mental health issues related to disasters and climate change. Issues related to the vulnerability and adaptive capacity of rural communities were identified by all regions. Discussions with the regional teams were followed by expert deliberation on the draft Key Messages by the authors and targeted consultation with additional experts. Information was then synthesized into Key Messages, which were refined based on published literature and professional judgment.

KEY MESSAGES

Key Message 1: Reduced Agricultural Productivity

Food and forage production will decline in regions experiencing increased frequency and duration of drought (high confidence). Shifting precipitation patterns, when associated with high temperatures, will intensify wildfires that reduce forage on rangelands, accelerate the depletion of water supplies for irrigation, and expand the distribution and incidence of pests and diseases for crops and livestock (very likely, high confidence). Modern breeding approaches and the use of novel genes from crop wild relatives are being employed to develop higher-yielding, stress-tolerant crops.

Description of evidence base

The Key Message and supporting text summarize extensive evidence documented in the U.S. Global Change Research Program’s (USGCRP) Climate Science Special Report⁸⁴ indicating increasing drought frequency or severity in many parts of the United States, increased temperature, and increased frost-free days. An increased probability of hot days concurrent with drought has been reported by Mueller and Seneviratne (2012),²³⁵ Mazdiyasni and AghaKouchak (2015),²³⁶ and Diffenbaugh et al. (2015).¹⁰⁷ The warming of minimum temperatures (lack of hard freezes) is contributing to expanding ranges for many insect, disease, and weed species.²³⁷ Bebber et al. (2013)²³⁸ report an average poleward shift of 2.7 km/year (1.68 miles/year) since 1960 of numerous pests and pathogens.

Agricultural production: Walthall et al. (2012)³⁸ synthesize a wide body of literature that documents the impacts of climate, including drought, on crop and livestock productivity and on the natural resources that support agricultural production. Marshall et al. 2015⁹⁷ also quantified climate change impacts on the yield of major U.S. crops as well as the reduced ability in the future to mitigate drought by irrigation. Havstad et al. (2016)²³⁹ describe the resilience of livestock production on rangelands in the Southwest and identify adaptation management strategies needed in an increasingly arid and variable climatic environment. Liang et al. (2017)²⁴⁰ found that total factor productivity (TFP) for the U.S. agriculture sector is related to regional and seasonal temperature and precipitation factors. Rosenzweig et al. (2014)²⁴¹ indicated strong negative effects of climate change on crop yields, particularly at higher levels of warming and lower latitudes. While technological improvements have outweighed the aggregate negative impacts of climate to date, projected climate change indicates that U.S. agriculture TFP could drop to pre-1980s levels by 2050. Ray et al. (2015)²⁴² estimate that climate accounts for about one-third of global yield variability.

Crop heat stress: Novick et al. (2016)²⁴³ indicate that atmospheric vapor pressure deficits play a critical role in plant function and productivity and that it will become more important at higher temperatures as an independent factor, relative to available soil moisture. For instance, high temperature has been documented to decrease yields of major crops, including wheat, corn, rice, and soybean.⁹²^,¹¹³^,¹²⁰^,²⁴⁴ Multimodel simulations indicated that grain yield reductions of wheat at high temperature were associated with reduced grain number per head¹²⁰ and that yield reductions were increased with higher temperature increases across a wide range of latitudes.²⁴¹ Hatfield et al. (2017)²⁴⁵ report that yield gaps for Midwest corn were negatively related to July maximum and August minimum temperatures but positively related to July–August rainfall, and that soybeans were less sensitive to projected temperature changes than corn. For corn, projected yield gaps showed a strong North–South gradient, with large gaps in southern portions of the region. Kukal and Irmak (2018)²⁴⁶ reported that changes in the variability of maize, sorghum, and soybean yield patterns in the Great Plains from 1968–2013 were linked to temperature and precipitation, with irrigated crops showing low variability compared to rainfed crops. Temperature increases were detrimental to sorghum and soybean yield but not to corn during this period. Tebaldi and Lobbell (2015)²⁴⁷ projected that corn would benefit from greenhouse gas mitigation to limit temperature increases throughout this century. For wheat, but less so for corn, impacts of exposure to extremely high temperatures would be partially offset by carbon dioxide fertilization effects. Tack et al. (2015)²⁴⁸ report that the largest drivers of Kansas wheat yield loss over 1985–2013 were freezing temperatures in the fall and extreme heat events in the spring.²⁴⁹^,²⁵⁰ The overall effect of warming on yields was negative, even after accounting for the benefits of reduced exposure to freezing temperatures. Warming effects were partially offset by increased spring precipitation. Of concern was evidence that recently released wheat varieties are less able to resist high temperature stress than older varieties. Gammans et al. (2017)²⁵¹ found that wheat and barley yields in France were negatively related to spring and summer temperatures. Liu et al. (2016)²⁵² report that with a 1.8°F (1°C) global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%, with the greatest losses in warmer wheat-producing regions. Wienhold et al.(2017)²⁵³ identify an increase in the number of extreme temperature events (higher daytime highs or nighttime lows) as a vulnerability of Northern Great Plains crops due to increased plant stress during critical pollination and grain fill periods. Burke and Emerick (2016)²⁵⁴ found that adaptation appeared to have mitigated less than half of the negative impacts of extreme heat on productivity.

Wildfire and rangelands: Margolis et al. (2017)²⁵⁵ report that fire scars in tree rings for the years 1599–1899 indicate that large grassland fires in New Mexico are strongly influenced by the current year cool-season moisture, but that fires burning mid-summer to fall are also influenced by monsoon moisture. Wet conditions several years prior to the fire year, resulting in increased fuel load, are also important for spring through late-summer fires. Persistent cool-season drought lasting longer than three years may inhibit fires due to the lack of moisture to replenish surface fuels. Donovan et al. (2017)⁹⁵ reported that wildfires greater than 400 hectares increased from 33.4 ± 5.6 per year during the period 1985–1994 to 116.8 ± 28.8 wildfires per year for the period 2005–2014 and that the total area burned in the Great Plains by large wildfires increased 400%.

Water supply: Dai and Zhao (2017)²⁵⁶ quantify historical trends in drought based on indices derived from the self-calibrated Palmer Drought Severity Index and the Penman–Monteith potential evapotranspiration index. For greater reliability, they compare these results with observed precipitation change patterns, streamflow, and runoff in three different periods: 1950–2012, 1955–2000, and 1980–2012. They indicate that spatially consistent patterns of drying have occurred in many parts of the Americas, that evaporation trends were slightly negative or slightly positive (exclusive of 1950–1980), and that drought has been increasingly linked to increased vapor pressure deficits since the 1980s.

Pest pressures: Integrated pest management is rapidly evolving in the face of intensifying pest challenges to crop production.²⁵⁷ There is considerable capacity for genetic improvement in agricultural crops and livestock breeds, but the ultimate ability to breed increased heat and drought tolerance into germplasm while retaining desired agronomic or horticultural attributes remains uncertain.²⁵⁸ The ability to breed pest-resistant varieties into a wide range of species to address rapidly evolving disease, insect, and weed species²³⁷ is also uncertain.

Major uncertainties

Drought impacts on crop yields and forage are critical at the farm economic scale and are well documented.³⁸^,⁹⁷ However, the extent to which drought impacts larger-scale issues of food security depends on a wide range of economic and social factors that are less certain. Chavez et al. (2015)²⁵⁹ lay out a framework for food security assessment that incorporates risk mitigation, risk forecast, and risk transfer instruments. There is considerable uncertainty in what is expected for the frequency and severity of future droughts.²⁶⁰ However, retrospective analyses and global climate modeling of 1900–2014 drought indicators show consistent results. The applied global climate models project 50%–200% increases in agricultural drought frequency in this century, even under low forcing scenarios. There is uncertainty about the interactive effects of carbon dioxide concentration, temperature, and water availability on plant physiological responses, particularly in highly dynamic field environments. There is uncertainty about future technological advances in agriculture and about changes in diet choices and food systems.

Description of confidence and likelihood

The USGCRP⁸⁴ determined that recent droughts and associated heat waves have reached record intensities in some regions of the United States; however, by geographic scale and duration, the 1930s Dust Bowl remains the benchmark drought and extreme heat event in the historical record since 1895 (very high confidence). The confidence is high that drought negatively impacts crop yield and quality, increases the risk of range wildfires, and accelerates the depletion of water supplies (very likely and high confidence).

Key Message 2: Degradation of Soil and Water Resources

The degradation of critical soil and water resources will expand as extreme precipitation events increase across our agricultural landscape (high confidence). Sustainable crop production is threatened by excessive runoff, leaching, and flooding, which results in soil erosion, degraded water quality in lakes and streams, and damage to rural community infrastructure (very likely, very high confidence,). Management practices to restore soil structure and the hydrologic function of landscapes are essential for improving resilience to these challenges.

Description of evidence base

Evidence of long-term changes in precipitation is based on analyses of daily precipitation observations from the National Weather Service’s Cooperative Observer Network.²⁶¹

Groisman et al. (2012)²⁶² reported that for the central United States, the frequency of very heavy precipitation increased by 20% from 1979–2009 compared to 1948–1978. Slater and Villarini (2016)²⁶³ report a significant increase in flooding frequency in the Southern Plains, California, and northern Minnesota; a smaller increase in the Southeast; and a decrease in the Northern Plains and Northwest. Mallakpour and Villarini (2015)²⁶⁴ report an increasing frequency of flooding in the Midwest, primarily in summer, but find limited evidence of a change in magnitude of flood peaks.

Infrastructure: Severe local storms constituted the largest class of billion-dollar natural disasters from 1980 to 2011, followed by tropical cyclones and nontropical floods.²⁶⁵ Špitalar et al. (2014)²⁶⁶ evaluate flash floods from 2006 to 2012 and find that the floods with the highest human impacts, based on injuries and fatalities, are associated with small catchment areas in rural areas. Rural areas face particular challenges with road networks and connectivity.²⁶⁷

Soil and water: Soil carbon on agricultural lands is decreased due to land-use change and tillage,²⁶⁸^,²⁶⁹ resulting in decreased hydrologic function.¹⁰¹ Practices that increase soil carbon have an adaptation benefit through improved soil structure and infiltration, improved water-holding capacity, and improved nutrient cycling. There are many practices that can enhance agricultural resilience through increased soil carbon sequestration.⁷⁵^,²⁶⁸^,²⁷⁰^,²⁷¹^,²⁷²^,²⁷³ Houghton et al. (2017)²⁷⁴ identify the health effects associated with poor water quality that can be associated with nutrient transport to water bodies and subsequent eutrophication.

Major uncertainties

Floods are highly variable in space and time,⁸⁶ and their characteristics are influenced by a number of non-climate factors.²⁷⁵ Groissman et al. (2012)²⁶² note that the lack of sub-daily data to analyze precipitation intensity means that daily data are normally used, which limits the ability to detect the most intense precipitation rates. While many practices are available to protect soil and reduce nutrient runoff from agricultural lands,²⁶⁸^,²⁷² adoption rates by producers are uncertain. Additionally, there is uncertainty about the extent to which agribusiness will invest in soil improvement to mitigate risks associated with a changing climate and its effects on water, energy, and plant and animal supply chains.²⁷⁶

Description of confidence and likelihood

The evidence on increasing precipitation intensity, with the largest increases occurring in the Northeast, is high (very likely, high confidence). The increase in flooding is less certain (likely, medium confidence). The evidence of the impact of precipitation extremes on infrastructure losses, soil erosion, and contaminant transport to water bodies is well established (very likely, high confidence). Based on medium confidence on flooding but high confidence in increasing precipitation intensity and the impacts of precipitation extremes, there is high confidence in this Key Message.

Key Message 3: Health Challenges to Rural Populations and Livestock

Challenges to human and livestock health are growing due to the increased frequency and intensity of high temperature extremes (very likely, high confidence). Extreme heat conditions contribute to heat exhaustion, heatstroke, and heart attacks in humans (very likely, high confidence). Heat stress in livestock results in large economic losses for producers (very likely, high confidence). Expanded health services in rural areas, heat-tolerant livestock, and improved design of confined animal housing are all important advances to minimize these challenges.

Description of evidence base

The Key Message and supporting text summarize extensive evidence documented in the USGCRP’s Climate Science Special Report.⁸⁴

Humans: Houghton et al. (2017)²⁷⁴ synthesize the literature that presents strong evidence of climate change impacts on human health in rural areas. Anderson et al. (2018)²⁷⁷ find that heat waves pose risks to human mortality but that the risk associated with any single heat wave depends on many factors, including heat wave length, timing, and intensity. On average, heat waves increase daily mortality risk by approximately 4% in the United States,²⁷⁸ but extreme heat waves present significantly higher risks. While research on heat-related morbidity has focused on urban areas, Jagai et al. (2017)²⁷⁹ analyzed heat waves in Illinois over 1987–2014 and found that there were 1.16 hospitalizations per 100,000 people in the most rural, thinly populated areas, compared to 0.45 hospitalizations per 100,000 in metropolitan areas. Consequently, a 1.8°F (1°C) increase in maximum monthly temperature was associated with a 0.34 increase in hospitalization rates in rural areas compared to an increase of 0.02 per 100,000 in urbanized counties. The mean cost per hospital stay was $20,050. Fechter-Leggett et al. (2016),²⁸⁰ Hess et al. (2014),²⁸¹ and Sugg et al. (2016)²⁸² also report an elevated risk in rural areas for emergency room visits for heat stress. Additionally, rural areas have a high proportion of outdoor workers who are at additional risk for heat stress.²⁷⁹^,²⁸³^,²⁸⁴ Merte (2017)²⁸⁵ analyzed data from 1960 to 2015 for 27 European countries and found that 0.61% of all deaths were caused by extreme heat.

Major uncertainties

Humans: Much of the literature focuses on heat-related mortality in urban areas (e.g., Oleson et al. 2015; Marsha et al. 2017²⁸⁶^,²⁸⁷). Vulnerability and exposure in rural areas are not well understood, but Oleson et al. (2015),²⁸⁶ in quantifying projected future temperature impacts, indicate that urban areas will experience more summer heat days and reduced winter cold temperature days than rural areas. Huber et al. (2017)²⁸⁸ identify uncertainties in estimated impacts of death from cardiovascular diseases from a 1.8°F (1°C) increase in global temperature. Anderson et al. (2018)²⁷⁷ discuss uncertainties associated with changes in the size and age of the population and the breadth of plausible socioeconomic scenarios. Jones et al. (2015)²⁸⁹ identify uncertainties in the migration of population due to a changing climate and how that would impact exposure. Hallstrom et al. (2017)²⁹⁰ evaluated the possible effects of future diet choices on various health indicators, many of which would have impacts on an individual’s sensitivity to high temperature.

Livestock: Walthall et al. (2012)³⁸ synthesize a wide body of literature that documents the impacts of extreme temperature effects on livestock health and productivity. Ruminant livestock support rural livelihoods and produce high-quality food products from land that is otherwise unsuited to crop agriculture.²⁹¹^,²⁹²

Description of confidence and likelihood

Extreme temperatures are projected to increase even more than average temperatures. The temperatures of extremely cold days and extremely warm days are both projected to increase. Cold waves are projected to become less intense, while heat waves will become more intense (very likely, very high confidence).²⁹³

Lehner et al. (2017)²⁹⁴ indicate a high likelihood and high confidence that there will be increased record-breaking summer temperatures by the end of the century. Evidence of challenges to human and livestock health due to temperature extremes is well established (very likely, very high confidence).

Key Message 4: Vulnerability and Adaptive Capacity of Rural Communities

Residents in rural communities often have limited capacity to respond to climate change impacts, due to poverty and limitations in community resources (very likely, high confidence). Communication, transportation, water, and sanitary infrastructure are vulnerable to disruption from climate stressors (very likely, high confidence). Achieving social resilience to these challenges would require increases in local capacity to make adaptive improvements in shared community resources.

Description of evidence base

A wealth of data shows that residents of rural areas generally have lower levels of education and lower wages for a given level of education compared to residents of urban areas.²⁹⁵ Higher levels of poverty, particularly childhood poverty,⁷ and food insecurity in rural compared to urban areas are also well documented.⁴⁹ There is also research that documents the disproportionate impacts of climate change on areas with multiple socioeconomic disadvantages, such as an increased risk of exposure to extreme heat and poor air quality, lack of access to basic necessities, and fewer job opportunities.²²⁹

Major uncertainties

There is uncertainty about future economic activity and employment in rural U.S. communities. However, the patterns of lower education levels, higher poverty levels, and high unemployment have been persistent and are likely to require long-term, focused efforts to reverse.⁶^,⁴⁹^,²⁹⁵ There are numerous federal programs (such as the USDA’s regional Climate Hubs, the National Oceanic and Atmospheric Administration’s Regional Integrated Sciences and Assessments program, and the U.S. Department of the Interior’s Climate Adaptation Science Centers) that focus on outreach and capacity building to rural and underserved communities. Additionally, the Cooperative Extension Service and state agencies, as well as various nongovernmental organizations, provide support and services to build the adaptive capacity of individuals and communities.

Description of confidence and likelihood

Lower levels of education, poverty, limited infrastructure, and lack of access to resources will limit the adaptive capacity of individuals and communities (very likely, high confidence). Adaptive capacity in rural communities is being increased through federal, state, and local capacity building efforts (likely, low to medium confidence). However, the outreach to rural communities varies greatly in different parts of the United States.

REFERENCES

The State of Rural Infrastructure, 2017: U.S. House of Representatives, URL. ↩
Abberton, M., J. Batley, A. Bentley, J. Bryant, H. Cai, J. Cockram, A. Costa de Oliveira, L. J. Cseke, H. Dempewolf, C. De Pace, D. Edwards, P. Gepts, A. Greenland, A. E. Hall, R. Henry, K. Hori, G. T. Howe, S. Hughes, M. Humphreys, D. Lightfoot, A. Marshall, S. Mayes, H. T. Nguyen, F. C. Ogbonnaya, R. Ortiz, A. H. Paterson, R. Tuberosa, B. Valliyodan, R. K. Varshney, and M. Yano, 2016: Global agricultural intensification during climate change: A role for genomics. Plant Biotechnology Journal, 14 (4), 1095–1098. doi:10.1111/pbi.12467. ↩
Adler, P. R., J. G. Mitchell, G. Pourhashem, S. Spatari, S. J. Del Grosso, and W. J. Parton, 2015: Integrating biorefinery and farm biogeochemical cycles offsets fossil energy and mitigates soil carbon losses. Ecological Applications, 25 (4), 1142–1156. doi:10.1890/13-1694.1. ↩
Ahn, K.-H., and R. N. Palmer, 2016: Trend and variability in observed hydrological extremes in the United States. Journal of Hydrologic Engineering, 21 (2), 04015061. doi:10.1061/(ASCE)HE.1943-5584.0001286. ↩
Altieri, A. H., and K. B. Gedan, 2015: Climate change and dead zones. Global Change Biology, 21 (4), 1395–1406. doi:10.1111/gcb.12754. ↩
Amundson, J. L., T. L. Mader, R. J. Rasby, and Q. S. Hu, 2006: Environmental effects on pregnancy rate in beef cattle. Journal of Animal Science, 84 (12), 3415–3420. doi:10.2527/jas.2005-611. ↩
Anderson, G. B., and M. L. Bell, 2011: Heat waves in the United States: Mortality risk during heat waves and effect modification by heat wave characteristics in 43 U.S. communities. Environmental Health Perspectives, 119 (2), 210–218. doi:10.1289/ehp.1002313. ↩
Anderson, G. B., K. W. Oleson, B. Jones, and R. D. Peng, 2018: Classifying heatwaves: Developing health-based models to predict high-mortality versus moderate United States heatwaves. Climatic Change, 146 (3), 439–453. doi:10.1007/s10584-016-1776-0. ↩
Anderson, W. F., G. Sarath, S. Edme, M. D. Casler, R. B. Mitchell, C. M. Tobias, A. L. Hale, S. E. Sattler, and J. E. Knoll, 2016: Dedicated herbaceous biomass feedstock genetics and development. BioEnergy Research, 9 (2), 399–411. doi:10.1007/s12155-015-9709-8. ↩
Araya, A., I. Kisekka, X. Lin, P. V. Vara Prasad, P. H. Gowda, C. Rice, and A. Andales, 2017: Evaluating the impact of future climate change on irrigated maize production in Kansas. Climate Risk Management, 17, 139–154. doi:10.1016/j.crm.2017.08.001. ↩
Asfaw, S., and L. Lipper, 2016: Managing climate risk using climate-smart agriculture. I5402E/1/04.16. Food and Agriculture Organization of the United Nations, Rome, Italy, 15 pp. URL. ↩
Asseng, S., F. Ewert, P. Martre, R. P. Rötter, D. B. Lobell, D. Cammarano, B. A. Kimball, M. J. Ottman, G. W. Wall, J. W. White, M. P. Reynolds, P. D. Alderman, P. V. V. Prasad, P. K. Aggarwal, J. Anothai, B. Basso, C. Biernath, A. J. Challinor, G. De Sanctis, J. Doltra, E. Fereres, M. Garcia-Vila, S. Gayler, G. Hoogenboom, L. A. Hunt, R. C. Izaurralde, M. Jabloun, C. D. Jones, K. C. Kersebaum, A. K. Koehler, C. Müller, S. Naresh Kumar, C. Nendel, G. O'Leary, J. E. Olesen, T. Palosuo, E. Priesack, E. Eyshi Rezaei, A. C. Ruane, M. A. Semenov, I. Shcherbak, C. Stöckle, P. Stratonovitch, T. Streck, I. Supit, F. Tao, P. J. Thorburn, K. Waha, E. Wang, D. Wallach, J. Wolf, Z. Zhao, and Y. Zhu, 2015: Rising temperatures reduce global wheat production. Nature Climate Change, 5, 143–147. doi:10.1038/nclimate2470. ↩
Auffhammer, M., and W. Schlenker, 2014: Empirical studies on agricultural impacts and adaptation. Energy Economics, 46, 555–561. doi:10.1016/j.eneco.2014.09.010. ↩
Baenziger, P. S., R. Mumm, R. Bernardo, E. C. Brummer, P. Langridge, P. Simon, and S. Smith, 2017: Plant Breeding and Genetics. A Paper in the Series on The Need for Agricultural Innovation to Sustainably Feed the World by 2050. CAST Issue Paper 57. Council for Agricultural Science and Technology (CAST), Ames, IA, 24 pp. URL. ↩
Balafoutis, A., B. Beck, S. Fountas, J. Vangeyte, T. Wal, I. Soto, M. Gómez-Barbero, A. Barnes, and V. Eory, 2017: Precision agriculture technologies positively contributing to GHG emissions mitigation, farm productivity and economics. Sustainability, 9 (8), 1339. doi:10.3390/su9081339. ↩
Basso, B., A. D. Kendall, and D. W. Hyndman, 2013: The future of agriculture over the Ogallala Aquifer: Solutions to grow crops more efficiently with limited water. Earth's Future, 1 (1), 39–41. doi:10.1002/2013EF000107. ↩
Bassu, S., N. Brisson, J.-L. Durand, K. Boote, J. Lizaso, J. W. Jones, C. Rosenzweig, A. C. Ruane, M. Adam, C. Baron, B. Basso, C. Biernath, H. Boogaard, S. Conijn, M. Corbeels, D. Deryng, G. De Sanctis, S. Gayler, P. Grassini, J. Hatfield, S. Hoek, C. Izaurralde, R. Jongschaap, A. R. Kemanian, K. C. Kersebaum, S.-H. Kim, N. S. Kumar, D. Makowski, C. Müller, C. Nendel, E. Priesack, M. V. Pravia, F. Sau, I. Shcherbak, F. Tao, E. Teixeira, D. Timlin, and K. Waha, 2014: How do various maize crop models vary in their responses to climate change factors? Global Change Biology, 20 (7), 2301–2320. doi:10.1111/gcb.12520. ↩
Beach, R. H., Y. Cai, A. Thomson, X. Zhang, R. Jones, B. A. McCarl, A. Crimmins, J. Martinich, J. Cole, S. Ohrel, B. DeAngelo, J. McFarland, K. Strzepek, and B. Boehlert, 2015: Climate change impacts on US agriculture and forestry: Benefits of global climate stabilization. Environmental Research Letters, 10 (9), 095004. doi:10.1088/1748-9326/10/9/095004. ↩
Bebber, D. P., M. A. T. Ramotowski, and S. J. Gurr, 2013: Crop pests and pathogens move polewards in a warming world. Nature Climate Change, 3 (11), 985–988. doi:10.1038/nclimate1990. ↩
Bendtsen, J., and J. L. S. Hansen, 2013: Effects of global warming on hypoxia in the Baltic Sea–North Sea transition zone. Ecological Modelling, 264, 17–26. doi:10.1016/j.ecolmodel.2012.06.018. ↩
Bevan, M. W., C. Uauy, B. B. H. Wulff, J. Zhou, K. Krasileva, and M. D. Clark, 2017: Genomic innovation for crop improvement. Nature, 543, 346–354. doi:10.1038/nature22011. ↩
Bianchi, T. S., S. F. DiMarco, J. H. Cowan, R. D. Hetland, P. Chapman, J. W. Day, and M. A. Allison, 2010: The science of hypoxia in the Northern Gulf of Mexico: A review. Science of The Total Environment, 408 (7), 1471–1484. doi:10.1016/j.scitotenv.2009.11.047. ↩
Bita, C., and T. Gerats, 2013: Plant tolerance to high temperature in a changing environment: Scientific fundamentals and production of heat stress-tolerant crops. Frontiers in Plant Science, 4 (273) doi:10.3389/fpls.2013.00273. ↩
Black, H., 2008: Unnatural disaster: Human factors in the Mississippi floods. Environmental Health Perspectives, 116 (9), A390-393. doi:10.1289/ehp.116-a390. ↩
Blanc, E., J. Caron, C. Fant, and E. Monier, 2017: Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields. Earth's Future, 5 (8), 877–892. doi:10.1002/2016EF000473. ↩
Blanc, E., K. Strzepek, A. Schlosser, H. Jacoby, A. Gueneau, C. Fant, S. Rausch, and J. Reilly, 2014: Modeling U.S. water resources under climate change. Earth's Future, 2 (4), 197–224. doi:10.1002/2013EF000214. ↩
Blanco-Canqui, H., T. M. Shaver, J. L. Lindquist, C. A. Shapiro, R. W. Elmore, C. A. Francis, and G. W. Hergert, 2015: Cover crops and ecosystem services: Insights from studies in temperate soils. Agronomy Journal, 107 (6), 2449–2474. doi:10.2134/agronj15.0086. ↩
Blanco‐Canqui, H., R. B. Mitchell, V. L. Jin, M. R. Schmer, and K. M. Eskridge, 2017: Perennial warm‐season grasses for producing biofuel and enhancing soil properties: An alternative to corn residue removal. GCB Bioenergy, 9 (9), 1510–1521. doi:10.1111/gcbb.12436. ↩
Board on Agriculture and Natural Resources (BANR), 2016: Genetically Engineered Crops: Experiences and Prospects. The National Academies Press, Washington, DC, doi:10.17226/23395. ↩
Bracmort, K., 2010: Biochar: Examination of an Emerging Concept to Mitigate Climate Change. CRS R40186. Congressional Research Service, Washington, DC, 9 pp. URL. ↩
Brauer, D., D. Devlin, K. Wagner, M. Ballou, D. Hawkins, and R. Lascano, 2017: Ogallala Aquifer Program: A catalyst for research and education to sustain the Ogallala Aquifer on the Southern High Plains (2003–2017). Journal of Contemporary Water Research & Education, 162 (1), 4–17. doi:10.1111/j.1936-704X.2017.03256.x. ↩
Brosse, N., A. Dufour, X. Meng, Q. Sun, and A. Ragauskas, 2012: Miscanthus: A fast‐growing crop for biofuels and chemicals production. Biofuels, Bioproducts and Biorefining, 6 (5), 580–598. doi:10.1002/bbb.1353. ↩
Brown, J. F., and M. S. Pervez, 2014: Merging remote sensing data and national agricultural statistics to model change in irrigated agriculture. Agricultural Systems, 127, 28–40. doi:10.1016/j.agsy.2014.01.004. ↩
Brown, J. R., and J. E. Herrick, 2016: Making soil health a part of rangeland management. Journal of Soil and Water Conservation, 71 (3), 55A–60A. doi:10.2489/jswc.71.3.55A. ↩
Brown, M. E., J. M. Antle, P. Backlund, E. R. Carr, W. E. Easterling, M. K. Walsh, C. Ammann, W. Attavanich, C. B. Barrett, M. F. Bellemare, V. Dancheck, C. Funk, K. Grace, J. S. I. Ingram, H. Jiang, H. Maletta, T. Mata, A. Murray, M. Ngugi, D. Ojima, B. O'Neill, and C. Tebaldi, 2015: Climate Change, Global Food Security, and the U.S. Food System. U.S. Global Change Research Program, Washington, DC, 146 pp. doi:10.7930/J0862DC7. ↩
Brown-Brandl, T. M., C. G. Chitko-McKown, R. A. Eigenberg, J. J. Mayer, T. H. Welsh, J. D. Davis, and J. L. Purswell, 2017: Physiological responses of feedlot heifers provided access to different levels of shade. Animal, 11 (8), 1344–1353. doi:10.1017/S1751731116002664. ↩
Burke, M., and K. Emerick, 2016: Adaptation to climate change: Evidence from US agriculture. American Economic Journal: Economic Policy, 8 (3), 106–140. doi:10.1257/pol.20130025. ↩
Capper, J. L., and D. E. Bauman, 2013: The role of productivity in improving the environmental sustainability of ruminant production systems. Annual Review of Animal Biosciences, 1 (1), 469–489. doi:10.1146/annurev-animal-031412-103727. ↩
Carpenter, S. R., E. H. Stanley, and M. J. V. Zanden, 2011: State of the world's freshwater ecosystems: Physical, chemical, and biological changes. Annual Review of Environment and Resources, 36 (1), 75–99. doi:10.1146/annurev-environ-021810-094524. ↩
Carstensen, J., J. H. Andersen, B. G. Gustafsson, and D. J. Conley, 2014: Deoxygenation of the Baltic Sea during the last century. Proceedings of the National Academy of Sciences of the United States of America, 111 (15), 5628–5633. doi:10.1073/pnas.1323156111. ↩
CDC, 2008: Heat-related deaths among crop workers—United States, 1992–2006. MMWR: Morbidity and Mortality Weekly Report, 57 (24), 649–653. URL. ↩
CENR, 2010: Scientific Assessment of Hypoxia in U.S. Coastal Waters. Interagency Working Group on Harmful Algal Blooms, Hypoxia, and Human Health of the Joint Subcommittee on Ocean Science and Technology. Committee on Environment and Natural Resources, Washington, D.C., 154 pp. URL. ↩
Chai, Q., Y. Gan, C. Zhao, H.-L. Xu, R. M. Waskom, Y. Niu, and K. H. M. Siddique, 2015: Regulated deficit irrigation for crop production under drought stress. A review. Agronomy for Sustainable Development, 36 (1), 3. doi:10.1007/s13593-015-0338-6. ↩
Chakraborty, S., and A. C. Newton, 2011: Climate change, plant diseases and food security: An overview. Plant Pathology, 60 (1), 2–14. doi:10.1111/j.1365-3059.2010.02411.x. ↩
Challinor, A. J., J. Watson, D. B. Lobell, S. M. Howden, D. R. Smith, and N. Chhetri, 2014: A meta-analysis of crop yield under climate change and adaptation. Nature Climate Change, 4 (4), 287–291. doi:10.1038/nclimate2153. ↩
Chapman, S. C., S. Chakraborty, M. F. Dreccer, and S. M. Howden, 2012: Plant adaptation to climate change—Opportunities and priorities in breeding. Crop and Pasture Science, 63 (3), 251–268. doi:10.1071/CP11303. ↩
Chavez, E., G. Conway, M. Ghil, and M. Sadler, 2015: An end-to-end assessment of extreme weather impacts on food security. Nature Climate Change, 5, 997–1001. doi:10.1038/nclimate2747. ↩
Climate Central, 2012: The age of western wildfires. Climate Central, Princeton, NJ, 18 pp. URL. ↩
Coleman-Jensen, A., M. P. Rabbitt, C. A. Gregory, and A. Singh, 2016: Household Food Security in the United States in 2015. Economic Research Report (ERR) 215. U.S. Department of Agriculture, Economic Research Service, Washington, DC, 36 pp. URL. ↩
Cowley, F. C., D. G. Barber, A. V. Houlihan, and D. P. Poppi, 2015: Immediate and residual effects of heat stress and restricted intake on milk protein and casein composition and energy metabolism. Journal of Dairy Science, 98 (4), 2356–2368. doi:10.3168/jds.2014-8442. ↩
Dahl, T. E., and S.-M. Stedman, 2013: Status and trends of wetlands in the coastal watersheds of the conterminous United States 2004 to 2009. U.S. Department of the Interior, Fish and Wildlife Service and National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Reston, VA, and Silver Spring, MD, 46 pp. URL. ↩
Dai, A., and T. Zhao, 2017: Uncertainties in historical changes and future projections of drought. Part I: estimates of historical drought changes. Climatic Change, 144 (3), 519–533. doi:10.1007/s10584-016-1705-2. ↩
Dash, S., A. K. Chakravarty, A. Singh, A. Upadhyay, M. Singh, and Y. Saleem, 2016: Effect of heat stress on reproductive performances of dairy cattle and buffaloes: A review. Veterinary World, 9 (3), 235–244. doi:10.14202/vetworld.2016.235-244. ↩
Davies, J., 2017: The business case for soil. Nature, 543, 309–311. doi:10.1038/543309a. ↩
De Rensis, F., I. Garcia-Ispierto, and F. López-Gatius, 2015: Seasonal heat stress: Clinical implications and hormone treatments for the fertility of dairy cows. Theriogenology, 84 (5), 659–666. doi:10.1016/j.theriogenology.2015.04.021. ↩
Delgado, J. A., and C. J. Gantzer, 2015: The 4Rs for cover crops and other advances in cover crop management for environmental quality. Journal of Soil and Water Conservation, 70 (6), 142A–145A. doi:10.2489/jswc.70.6.142A. ↩
Derner, J. D., and D. J. Augustine, 2016: Adaptive management for drought on rangelands. Rangelands, 38 (4), 211–215. doi:10.1016/j.rala.2016.05.002. ↩
Derner, J. D., C. Stanley, and C. Ellis, 2016: Usable science: Soil health. Rangelands, 38 (2), 64–67. doi:10.1016/j.rala.2015.10.010. ↩
Diaz, R. J., and R. Rosenberg, 2008: Spreading dead zones and consequences for marine ecosystems. Science, 321 (5891), 926–929. doi:10.1126/science.1156401. ↩
Diffenbaugh, N. S., D. L. Swain, and D. Touma, 2015: Anthropogenic warming has increased drought risk in California. Proceedings of the National Academy of Sciences of the United States of America, 112 (13), 3931–3936. doi:10.1073/pnas.1422385112. ↩
Donovan, V. M., C. L. Wonkka, and D. Twidwell, 2017: Surging wildfire activity in a grassland biome. Geophysical Research Letters, 44 (12), 5986–5993. doi:10.1002/2017GL072901. ↩
Du, J., J. Shen, K. Park, Y. P. Wang, and X. Yu, 2018: Worsened physical condition due to climate change contributes to the increasing hypoxia in Chesapeake Bay. Science of The Total Environment, 630, 707–717. doi:10.1016/j.scitotenv.2018.02.265. ↩
Díaz, R. J., and R. Rosenberg, 2011: Introduction to environmental and economic consequences of hypoxia. International Journal of Water Resources Development, 27 (1), 71–82. doi:10.1080/07900627.2010.531379. ↩
Easterling, D. R., J. R. Arnold, T. Knutson, K. E. Kunkel, A. N. LeGrande, L. R. Leung, R. S. Vose, D. E. Waliser, and M. F. Wehner, 2017: Precipitation Change in the United States. Climate Science Special Report: Fourth National Climate Assessment, Volume I. Wuebbles, D. J., D. W. Fahey, K. A. Hibbard, D. J. Dokken, B. C. Stewart, and T. K. Maycock, Eds., U.S. Global Change Research Program, Washington, DC, USA, 207–230. doi:10.7930/J0H993CC. ↩
Eisler, M. C., M. R. F. Lee, J. F. Tarlton, G. B. Martin, J. Beddington, J. A. J. Dungait, H. Greathead, J. Liu, S. Mathew, H. Miller, T. Misselbrook, P. Murray, V. K. Vinod, R. V. Saun, and M. Winter, 2014: Agriculture: Steps to sustainable livestock. Nature, 507, 32–34. doi:10.1038/507032a. ↩
Engle, N. L., 2011: Adaptive capacity and its assessment. Global Environmental Change, 21 (2), 647–656. doi:10.1016/j.gloenvcha.2011.01.019. ↩
EPA, 2016: Climate Change Indicators: Heavy Precipitation. U.S. Environmental Protection Agency (EPA), . URL. ↩
EPA, 2018: Inventory of U.S. greenhouse gas emissions and sinks: 1990–2016. EPA 430-P-18-001. U.S. Environmental Protection Agency (EPA), Washington, DC, various pp. URL. ↩
ERS, 2017: County Economic Types, 2015 Edition [website]. USDA Economic Research Service (ERS), Washington, DC. URL. ↩
ERS, 2017: Nonmetro County Poverty Rates, 2011-2015 Average [chart]. USDA Economic Research Service (ERS), Washington, DC. URL. ↩
ERS, 2017: Rural Education At A Glance, 2017 Edition. Economic Information Bulletin 171. USDA Economic Research Service (ERS), Washington, DC, 6 pp. URL. ↩
ERS, 2018: Nonmetro Population Change, 2010-17 [chart]. USDA Economic Research Service (ERS), Washington, DC. URL. ↩
ERS, 2018: U.S. Agricultural Trade at a Glance [web site]. USDA Economic Research Service (ERS), Washington, DC. URL. ↩
Eyshi Rezaei, E., H. Webber, T. Gaiser, J. Naab, and F. Ewert, 2015: Heat stress in cereals: Mechanisms and modelling. European Journal of Agronomy, 64, 98–113. doi:10.1016/j.eja.2014.10.003. ↩
Falco, S. D., F. Adinolfi, M. Bozzola, and F. Capitanio, 2014: Crop insurance as a strategy for adapting to climate change. Journal of Agricultural Economics, 65 (2), 485–504. doi:10.1111/1477-9552.12053. ↩
Fann, N., T. Brennan, P. Dolwick, J. L. Gamble, V. Ilacqua, L. Kolb, C. G. Nolte, T. L. Spero, and L. Ziska, 2016: Ch. 3: Air quality impacts. The Impacts of Climate Change on Human Health in the United States: A Scientific Assessment., U.S. Global Change Research Program, Washington, DC, 69–98. doi:10.7930/J0GQ6VP6. ↩
FAO, 2011: The State of the World's Land and Water Resources for Food and Agriculture: Managing Systems at Risk. Food and Agriculture Organization of the United Nations (FAO) and Earthscan, Rome and London, 285 pp. URL. ↩
FAO, 2016: 2016 The State of Food and Agriculture: Climate Change, Agriculture and Food Security. Food and Agriculture Organization (FAO) of the United Nations, Rome, Italy, xvii, 173 pp. URL. ↩
Farm Service Agency, 2017: Emergency Disaster Designation and Declaration Process. Disaster Assistance Fact Sheet. USDA Farm Service Agency, Washington, DC, 2 pp. URL. ↩
Farrigan, T., 2014: Poverty and deep poverty increasing in rural America. Amber Waves. URL. ↩
Farrigan, T., and T. Parker, 2012: The concentration of poverty is a growing rural problem. Amber Waves. Washington, DC. URL. ↩
Fechter-Leggett, E. D., A. Vaidyanathan, and E. Choudhary, 2016: Heat stress illness emergency department visits in national environmental public health tracking states, 2005–2010. Journal of Community Health, 41 (1), 57–69. doi:10.1007/s10900-015-0064-7. ↩
FEMA, 2004: The California Fires Coordination Group. A Report to the Secretary of Homeland Security. Department of Homeland Security, Emergence Preparedness and Response, Washington, DC, 62 pp. URL. ↩
Field, J. L., E. Marx, M. Easter, P. R. Adler, and K. Paustian, 2016: Ecosystem model parameterization and adaptation for sustainable cellulosic biofuel landscape design. GCB Bioenergy, 8 (6), 1106–1123. doi:10.1111/gcbb.12316. ↩
Fischer, E. M., and R. Knutti, 2016: Observed heavy precipitation increase confirms theory and early models. Nature Climate Change, 6 (11), 986–991. doi:10.1038/nclimate3110. ↩
Fortune, M. K., C. A. Mustard, J. J. C. Etches, and A. G. Chambers, 2013: Work-attributed illness arising from excess heat exposure in Ontario, 2004-2010. Canadian Journal of Public Health, 104 (5), 7. doi:10.17269/cjph.104.3984. ↩
Fournel, S., V. Ouellet, and É. Charbonneau, 2017: Practices for alleviating heat stress of dairy cows in humid continental climates: A literature review. Animals, 7 (5), 37. doi:10.3390/ani7050037. ↩
Frank, D., M. Reichstein, M. Bahn, K. Thonicke, D. Frank, M. D. Mahecha, P. Smith, M. van der Velde, S. Vicca, F. Babst, C. Beer, N. Buchmann, J. G. Canadell, P. Ciais, W. Cramer, A. Ibrom, F. Miglietta, B. Poulter, A. Rammig, S. I. Seneviratne, A. Walz, M. Wattenbach, M. A. Zavala, and J. Zscheischler, 2015: Effects of climate extremes on the terrestrial carbon cycle: Concepts, processes and potential future impacts. Global Change Biology, 21 (8), 2861–2880. doi:10.1111/gcb.12916. ↩
Franzluebbers, A. J., 2002: Water infiltration and soil structure related to organic matter and its stratification with depth. Soil and Tillage Research, 66 (2), 197–205. doi:10.1016/S0167-1987(02)00027-2. ↩
Gallopin, G. C., 2006: Linkages between vulnerability, resilience, and adaptive capacity. Global Environmental Change, 16 (3), 293–303. doi:10.1016/j.gloenvcha.2006.02.004. ↩
Gamble, J. L., J. Balbus, M. Berger, K. Bouye, V. Campbell, K. Chief, K. Conlon, A. Crimmins, B. Flanagan, C. Gonzalez-Maddux, E. Hallisey, S. Hutchins, L. Jantarasami, S. Khoury, M. Kiefer, J. Kolling, K. Lynn, A. Manangan, M. McDonald, R. Morello-Frosch, M. H. Redsteer, P. Sheffield, K. Thigpen Tart, J. Watson, K. P. Whyte, and A. F. Wolkin, 2016: Ch. 9: Populations of concern. The Impacts of Climate Change on Human Health in the United States: A Scientific Assessment., U.S. Global Change Research Program, Washington, DC, 247–286. doi:10.7930/J0Q81B0T. ↩
Gammans, M., P. Mérel, and A. Ortiz-Bobea, 2017: Negative impacts of climate change on cereal yields: Statistical evidence from France. Environmental Research Letters, 12 (5), 054007. doi:10.1088/1748-9326/aa6b0c. ↩
Garbrecht, J. D., J. L. Steiner, and C. A. Cox, 2007: The times they are changing: Soil and water conservation in the 21st century. Hydrological Processes, 21 (19), 2677–2679. doi:10.1002/hyp.6853. ↩
Garner, J. B., M. L. Douglas, S. R. O. Williams, W. J. Wales, L. C. Marett, T. T. T. Nguyen, C. M. Reich, and B. J. Hayes, 2016: Genomic selection improves heat tolerance in dairy cattle. Scientific Reports, 6, 34114. doi:10.1038/srep34114. ↩
Gilly, W. F., J. M. Beman, S. Y. Litvin, and B. H. Robison, 2013: Oceanographic and biological effects of shoaling of the oxygen minimum zone. Annual Review of Marine Science, 5 (1), 393–420. doi:10.1146/annurev-marine-120710-100849. ↩
Giridhar, K., and A. Samireddypalle, 2015: Impact of climate change on forage availability for livestock. Climate Change Impact on Livestock: Adaptation and Mitigation. Sejian, V., J. Gaughan, L. Baumgard, and C. Prasad, Eds., Springer India, New Delhi, 97–112. doi:10.1007/978-81-322-2265-1_7. ↩
Glantz, M. H., René Gommes, and Selvaraju Ramasamy, 2009: Coping with a changing climate: Considerations for adaptation and mitigation in agriculture. FAO Environment And Natural Resources Series 15. Food and Agriculture Organization of the United Nations (FAO), Rome, 100 pp. URL. ↩
Glaser, L., K. Kassel, and R. M. Morrison, 2013: A visual primer for the food and agricultural sectors. Amber Waves. Washington, DC. URL. ↩
Godfray, H. C. J., J. R. Beddington, I. R. Crute, L. Haddad, D. Lawrence, J. F. Muir, J. Pretty, S. Robinson, S. M. Thomas, and C. Toulmin, 2010: Food security: The challenge of feeding 9 billion people. Science, 327 (5967), 812–818. doi:10.1126/science.1185383. ↩
Gourdji, S. M., A. M. Sibley, and D. B. Lobell, 2013: Global crop exposure to critical high temperatures in the reproductive period: Historical trends and future projections. Environmental Research Letters, 8 (2), 024041. doi:10.1088/1748-9326/8/2/024041. ↩
Gowda, P. H., T. A. Howell, R. L. Baumhardt, D. O. Porter, T. H. Marek, and V. Nangia, 2016: A user-friendly interactive tool for estimating reference ET using ASCE standardized Penman-Monteith equation. Applied Engineering in Agriculture, 32 (3), 383. doi:10.13031/aea.32.11673. ↩
Grafton, R. Q., J. Williams, and Q. Jiang, 2017: Possible pathways and tensions in the food and water nexus. Earth's Future, 5 (5), 449–462. doi:10.1002/2016EF000506. ↩
Groisman, P. Y., R. W. Knight, and T. R. Karl, 2001: Heavy precipitation and high streamflow in the contiguous United States: Trends in the twentieth century. Bulletin of the American Meteorological Society, 82 (2), 219–246. doi:10.1175/1520-0477(2001)082<0219:hpahsi>2.3.co;2. ↩
Groisman, P. Y., R. W. Knight, and T. R. Karl, 2012: Changes in intense precipitation over the central United States. Journal of Hydrometeorology, 13, 47–66. doi:10.1175/JHM-D-11-039.1. ↩
Groisman, P. Y., R. W. Knight, D. R. Easterling, T. R. Karl, G. C. Hegerl, and V. N. Razuvaev, 2005: Trends in intense precipitation in the climate record. Journal of Climate, 18 (9), 1326–1350. doi:10.1175/jcli3339.1. ↩
Guerrero, B., S. Amosson, and T. McCollum, 2013: The impact of the Beef Industry in the Southern Ogallala region. AG-001. Texas A&M AgriLife Extension Service, College Station, TX, 17 pp. URL. ↩
Hagy, J. D., W. R. Boynton, C. W. Keefe, and K. V. Wood, 2004: Hypoxia in Chesapeake Bay, 1950–2001: Long-term change in relation to nutrient loading and river flow. Estuaries, 27 (4), 634–658. doi:10.1007/bf02907650. ↩
Hallström, E., A. Carlsson-Kanyama, and P. Börjesson, 2015: Environmental impact of dietary change: A systematic review. Journal of Cleaner Production, 91, 1–11. doi:10.1016/j.jclepro.2014.12.008. ↩
Hallström, E., Q. Gee, P. Scarborough, and D. A. Cleveland, 2017: A healthier US diet could reduce greenhouse gas emissions from both the food and health care systems. Climatic Change, 142 (1), 199–212. doi:10.1007/s10584-017-1912-5. ↩
Hammac, W. A., D. E. Stott, D. L. Karlen, and C. A. Cambardella, 2016: Crop, tillage, and landscape effects on near-surface soil quality indices in Indiana. Soil Science Society of America Journal, 80 (6), 1638–1652. doi:10.2136/sssaj2016.09.0282. ↩
Harwatt, H., J. Sabaté, G. Eshel, S. Soret, and W. Ripple, 2017: Substituting beans for beef as a contribution toward US climate change targets. Climatic Change, 143 (1), 261–270. doi:10.1007/s10584-017-1969-1. ↩
Hatfield, J. L., and C. L. Walthall, 2015: Meeting global food needs: Realizing the potential via genetics × environment × management interactions. Agronomy Journal, 107 (4), 1215–1226. doi:10.2134/agronj15.0076. ↩
Hatfield, J. L., and J. H. Prueger, 2015: Temperature extremes: Effect on plant growth and development. Weather and Climate Extremes, 10 (Part A), 4–10. doi:10.1016/j.wace.2015.08.001. ↩
Hatfield, J. L., K. J. Boote, B. A. Kimball, L. H. Ziska, R. C. Izaurralde, D. Ort, A. M. Thomson, and D. Wolfe, 2011: Climate impacts on agriculture: Implications for crop production. Agronomy Journal, 103 (2), 351–370. doi:10.2134/agronj2010.0303. ↩
Hatfield, J. L., L. Wright-Morton, and B. Hall, 2018: Vulnerability of grain crops and croplands in the Midwest to climatic variability and adaptation strategies. Climatic Change, 146 (1–2), 263–275. doi:10.1007/s10584-017-1997-x. ↩
Hatfield, J., C. Swanston, Maria Janowiak, R. F. Steele, J. Hempel, J. Bochicchio, W. Hall, M. Cole, S. Hestvik, and J. Whitaker, 2015: USDA Midwest and Northern Forests Regional Climate Hub: Assessment of Climate Change Vulnerability and Adaptation and Mitigation Strategies. U.S. Department of Agriculture, 55 pp. URL. ↩
Hatfield, J., G. Takle, R. Grotjahn, P. Holden, R. C. Izaurralde, T. Mader, E. Marshall, and D. Liverman, 2014: Ch. 6: Agriculture. Climate Change Impacts in the United States: The Third National Climate Assessment. Melillo, J. M., Terese (T.C.) Richmond, and G. W. Yohe, Eds., U.S. Global Change Research Program, Washington, DC, 150–174. doi:10.7930/J02Z13FR. ↩
Havlík, P., H. Valin, A. Mosnier, M. Obersteiner, J. S. Baker, M. Herrero, M. C. Rufino, and E. Schmid, 2013: Crop productivity and the global livestock sector: Implications for land use change and greenhouse gas emissions. American Journal of Agricultural Economics, 95 (2), 442–448. doi:10.1093/ajae/aas085. ↩
Havstad, K. M., J. R. Brown, R. Estell, E. Elias, A. Rango, and C. Steele, 2016: Vulnerabilities of southwestern U.S. rangeland-based animal agriculture to climate change. Climatic Change, doi:10.1007/s10584-016-1834-7. ↩
Heisey, P. W., and K. Day Rubenstein, 2015: Using Crop Genetic Resources to Help Agriculture Adapt to Climate Change: Economics and Policy. Economic Information Bulletin No. EIB-139. U.S. Department of Agriculture, Economic Research Service, Washington, DC, 29 pp. URL. ↩
Hertz, T., and T. Farrigan, 2016: Understanding the rise in rural child poverty, 2003-2014. Economic Research Report No. (ERR-208) . USDA Economic Research Service, Washington, DC, 27 pp. URL. ↩
Hess, J. J., S. Saha, and G. Luber, 2014: Summertime acute heat illness in U.S. emergency departments from 2006 through 2010: Analysis of a nationally representative sample. Environmental Health Perspectives, 122 (11), 1209–1215. doi:10.1289/ehp.1306796. ↩
Hewitt, C., V. B. S. Silva, N. Golding, R. Gao, C. A. S. Coelho, R. Duell, J. Pollock, K. Onogi, and W. Secretariat, 2015: Managing risk with climate prediction products and services. WMO Bulletin. URL. ↩
Holt, S. M., J. B. Gaughan, and T. L. Mader, 2004: Feeding strategies for grain-fed cattle in a hot environment. Australian Journal of Agricultural Research, 55 (7), 719–725. doi:10.1071/AR03261. ↩
Houghton, A., J. Austin, A. Beerman, and C. Horton, 2017: An approach to developing local climate change environmental public health indicators in a rural district. Journal of Environmental and Public Health, 2017, 16. doi:10.1155/2017/3407325. ↩
Howden, S. M., J.-F. Soussana, F. N. Tubiello, N. Chhetri, M. Dunlop, and H. Meinke, 2007: Adapting agriculture to climate change. Proceedings of the National Academy of Sciences of the United States of America, 104 (50), 19691–19696. doi:10.1073/pnas.0701890104. ↩
Hu, F., Y. Gan, H. Cui, C. Zhao, F. Feng, W. Yin, and Q. Chai, 2016: Intercropping maize and wheat with conservation agriculture principles improves water harvesting and reduces carbon emissions in dry areas. European Journal of Agronomy, 74, 9–17. doi:10.1016/j.eja.2015.11.019. ↩
Huber, V., D. Ibarreta, and K. Frieler, 2017: Cold- and heat-related mortality: A cautionary note on current damage functions with net benefits from climate change . Climatic Change, 142 (3), 407–418. doi:10.1007/s10584-017-1956-6. ↩
IJC, 2014: A balanced diet for Lake Erie: Reducing phosphorus loadings and harmful algal blooms. International Joint Commission (IJC), Washington, DC, and Ottowa, ON, 96 pp. URL. ↩
Ilut, D. C., P. L. Sanchez, T. A. Coffelt, J. M. Dyer, M. A. Jenks, and M. A. Gore, 2017: A century of guayule: Comprehensive genetic characterization of the guayule (Parthenium argentatum A. Gray) USDA germplasm collection. bioRxiv, doi:10.1101/147256. ↩
Irmak, S., J. M. Rees, G. L. Zoubek, B. S. van DeWalle, W. R. Rathje, R. DeBuhr, D. Leininger, D. D. Siekman, J. W. Schneider, and A. P. Christiansen, 2010: Nebraska Agricultural Water Management Demonstration Network (NAWMDN): Integrating research and extension/outreach. Applied Engineering in Agriculture, 26 (4), 599–613. doi:10.13031/2013.32066. ↩
Issaka, S., and M. A. Ashraf, 2017: Impact of soil erosion and degradation on water quality: A review. Geology, Ecology, and Landscapes, 1 (1), 1–11. doi:10.1080/24749508.2017.1301053. ↩
Jagai, J. S., E. Grossman, L. Navon, A. Sambanis, and S. Dorevitch, 2017: Hospitalizations for heat-stress illness varies between rural and urban areas: An analysis of Illinois data, 1987–2014. Environmental Health, 16 (1), 38. doi:10.1186/s12940-017-0245-1. ↩
Jenny, J., F. Arnaud, B. Alric, J. Dorioz, P. Sabatier, M. Meybeck, and M. Perga, 2014: Inherited hypoxia: A new challenge for reoligotrophicated lakes under global warming. Global Biogeochemical Cycles, 28 (12), 1413–1423. doi:10.1002/2014GB004932. ↩
Jha, U. C., A. Bohra, and N. P. Singh, 2014: Heat stress in crop plants: Its nature, impacts and integrated breeding strategies to improve heat tolerance. Plant Breeding, 133 (6), 679–701. doi:10.1111/pbr.12217. ↩
Johnson, J. M. F., and N. W. Barbour, 2016: Nitrous oxide emission and soil carbon sequestration from herbaceous perennial biofuel feedstocks. Soil Science Society of America Journal, 80 (4), 1057–1070. doi:10.2136/sssaj2015.12.0436. ↩
Johnson, J. M. F., J. M. Novak, G. E. Varvel, D. E. Stott, S. L. Osborne, D. L. Karlen, J. A. Lamb, J. Baker, and P. R. Adler, 2014: Crop residue mass needed to maintain soil organic carbon levels: Can it be determined? BioEnergy Research, 7 (2), 481–490. doi:10.1007/s12155-013-9402-8. ↩
Jones, B., B. C. O'Neill, L. McDaniel, S. McGinnis, L. O. Mearns, and C. Tebaldi, 2015: Future population exposure to US heat extremes. Nature Climate Change, 5, 652–655. doi:10.1038/nclimate2631. ↩
Kant, S., S. Seneweera, J. Rodin, M. Materne, D. Burch, S. Rothstein, and G. Spangenberg, 2012: Improving yield potential in crops under elevated CO2: Integrating the photosynthetic and nitrogen utilization efficiencies. Frontiers in Plant Science, 3 (162) doi:10.3389/fpls.2012.00162. ↩
Karlen, D. L., L. W. Beeler, R. G. Ong, and B. E. Dale, 2015: Balancing energy, conservation, and soil health requirements for plant biomass. Journal of Soil and Water Conservation, 70 (5), 279–287. doi:10.2489/jswc.70.5.279. ↩
Karlen, D. L., S. J. Birrell, J. M. F. Johnson, S. L. Osborne, T. E. Schumacher, G. E. Varvel, R. B. Ferguson, J. M. Novak, J. R. Fredrick, J. M. Baker, J. A. Lamb, P. R. Adler, G. W. Roth, and E. D. Nafziger, 2014: Multilocation corn stover harvest effects on crop yields and nutrient removal. BioEnergy Research, 7 (2), 528–539. doi:10.1007/s12155-014-9419-7. ↩
Kassel, K., A. Melton, and R. M. Morrison, 2017: Selected charts from Ag and Food Statistics: Charting the Essentials. AP-078. USDA Economic Research Service, Washington, DC, 27 pp. URL. ↩
Kaye, J. P., and M. Quemada, 2017: Using cover crops to mitigate and adapt to climate change. A review. Agronomy for Sustainable Development, 37 (1), 4. doi:10.1007/s13593-016-0410-x. ↩
Keller Jensen, J., 2009: Climate Change and Rural Communities in the US. Draft Briefing Paper. Rural Policy Research Institute, Iowa City, IA, 13 pp. URL. ↩
Keown, J. F., Paul J. Kononoff, and Richard J. Grant, 2016: How to Reduce Heat Stress in Dairy Cattle. NebGuide G1582. University of Nebraska–Lincoln Extension, Institute of Agriculture and Natural Resources, Lincoln, NE, 2 pp. URL. ↩
Kerr, A., J. Dialesandro, K. Steenwerth, N. Lopez-Brody, and E. Elias, 2017: Vulnerability of California specialty crops to projected mid-century temperature changes. Climatic Change, doi:10.1007/s10584-017-2011-3. ↩
Key, N., and S. Sneeringer, 2014: Potential effects of climate change on the productivity of U.S. dairies. American Journal of Agricultural Economics, 96 (4), 1136–1156. doi:10.1093/ajae/aau002. ↩
Key, N., S. Sneeringer, and D. Marquardt, 2014: Climate Change, Heat Stress, and U.S. Dairy Production. Economic Research Report No. ERR-175. USDA Economic Research Service, Washington, DC, 45 pp. URL. ↩
Kimball, B. A., J. W. White, G. W. Wall, and M. J. Ottman, 2016: Wheat responses to a wide range of temperatures: The Hot Serial Cereal Experiment. Improving Modeling Tools to Assess Climate Change Effects on Crop Response. Hatfield, J. L., and D. Fleisher, Eds., American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc., Madison, WI, 33–44. doi:10.2134/advagricsystmodel7.2014.0014. ↩
Kisekka, I., A. Schlegel, L. Ma, P. H. Gowda, and P. V. V. Prasad, 2017: Optimizing preplant irrigation for maize under limited water in the High Plains. Agricultural Water Management, 187, 154–163. doi:10.1016/j.agwat.2017.03.023. ↩
Korres, N. E., J. K. Norsworthy, P. Tehranchian, T. K. Gitsopoulos, D. A. Loka, D. M. Oosterhuis, D. R. Gealy, S. R. Moss, N. R. Burgos, M. R. Miller, and M. Palhano, 2016: Cultivars to face climate change effects on crops and weeds: A review. Agronomy for Sustainable Development, 36 (1), 12. doi:10.1007/s13593-016-0350-5. ↩
Kristensen, T. N., A. A. Hoffmann, C. Pertoldi, and A. V. Stronen, 2015: What can livestock breeders learn from conservation genetics and vice versa? Frontiers in Genetics, 6 (38) doi:10.3389/fgene.2015.00038. ↩
Kukal, M. S., and S. Irmak, 2018: Climate-driven crop yield and yield variability and climate change impacts on the U.S. Great Plains agricultural production. Scientific Reports, 8 (1), 3450. doi:10.1038/s41598-018-21848-2. ↩
Kuttner, H., 2016: The Economic Impact of Rural Broadband. Briefing Paper. Hudson Institute, Washington, DC, 29 pp. URL. ↩
Labe, Z., T. Ault, and R. Zurita-Milla, 2017: Identifying anomalously early spring onsets in the CESM large ensemble project. Climate Dynamics, 48 (11), 3949–3966. doi:10.1007/s00382-016-3313-2. ↩
Lal, R., 2015: Sequestering carbon and increasing productivity by conservation agriculture. Journal of Soil and Water Conservation, 70 (3), 55A–62A. doi:10.2489/jswc.70.3.55A. ↩
Lal, R., and B. A. Stewart, Eds., 1990: Soil Degradation. Springer, New York, 345 pp. doi:10.1007/978-1-4612-3322-0. ↩
Lee, M. A., A. P. Davis, M. G. G. Chagunda, and P. Manning, 2017: Forage quality declines with rising temperatures, with implications for livestock production and methane emissions. Biogeosciences, 14 (6), 1403–1417. doi:10.5194/bg-14-1403-2017. ↩
Lehner, F., C. Deser, and B. M. Sanderson, 2018: Future risk of record-breaking summer temperatures and its mitigation. Climatic Change, 146 (3–4), 363–375. doi:10.1007/s10584-016-1616-2. ↩
Li, X., S. Kang, X. Zhang, F. Li, and H. Lu, 2018: Deficit irrigation provokes more pronounced responses of maize photosynthesis and water productivity to elevated CO2. Agricultural Water Management, 195, 71–83. doi:10.1016/j.agwat.2017.09.017. ↩
Liang, X.-Z., Y. Wu, R. G. Chambers, D. L. Schmoldt, W. Gao, C. Liu, Y.-A. Liu, C. Sun, and J. A. Kennedy, 2017: Determining climate effects on US total agricultural productivity. Proceedings of the National Academy of Sciences of the United States of America, 114 (12), E2285–E2292. doi:10.1073/pnas.1615922114. ↩
Lipper, L., P. Thornton, B. M. Campbell, T. Baedeker, A. Braimoh, M. Bwalya, P. Caron, A. Cattaneo, D. Garrity, K. Henry, R. Hottle, L. Jackson, A. Jarvis, F. Kossam, W. Mann, N. McCarthy, A. Meybeck, H. Neufeldt, T. Remington, P. T. Sen, R. Sessa, R. Shula, A. Tibu, and E. F. Torquebiau, 2014: Climate-smart agriculture for food security. Nature Climate Change, 4, 1068–1072. doi:10.1038/nclimate2437. ↩
Liu, B., S. Asseng, C. Müller, F. Ewert, J. Elliott, D. B. Lobell, P. Martre, A. C. Ruane, D. Wallach, J. W. Jones, C. Rosenzweig, P. K. Aggarwal, P. D. Alderman, J. Anothai, B. Basso, C. Biernath, D. Cammarano, A. Challinor, D. Deryng, G. D. Sanctis, J. Doltra, E. Fereres, C. Folberth, M. Garcia-Vila, S. Gayler, G. Hoogenboom, L. A. Hunt, R. C. Izaurralde, M. Jabloun, C. D. Jones, K. C. Kersebaum, B. A. Kimball, A.-K. Koehler, S. N. Kumar, C. Nendel, G. J. O'Leary, J. E. Olesen, M. J. Ottman, T. Palosuo, P. V. V. Prasad, E. Priesack, T. A. M. Pugh, M. Reynolds, E. E. Rezaei, R. P. Rötter, E. Schmid, M. A. Semenov, I. Shcherbak, E. Stehfest, C. O. Stöckle, P. Stratonovitch, T. Streck, I. Supit, F. Tao, P. Thorburn, K. Waha, G. W. Wall, E. Wang, J. W. White, J. Wolf, Z. Zhao, and Y. Zhu, 2016: Similar estimates of temperature impacts on global wheat yield by three independent methods. Nature Climate Change, 6, 1130–1136. doi:10.1038/nclimate3115. ↩
Liu, Z., M. C. Wimberly, A. Lamsal, T. L. Sohl, and T. J. Hawbaker, 2015: Climate change and wildfire risk in an expanding wildland–urban interface: A case study from the Colorado Front Range Corridor. Landscape Ecology, 30 (10), 1943–1957. doi:10.1007/s10980-015-0222-4. ↩
Lobell, D. B., W. Schlenker, and J. Costa-Roberts, 2011: Climate trends and global crop production since 1980. Science, 333 (6042), 616–620. doi:10.1126/science.1204531. ↩
Long, D. S., F. L. Young, W. F. Schillinger, C. L. Reardon, J. D. Williams, B. L. Allen, W. L. Pan, and D. J. Wysocki, 2016: Development of dryland oilseed production systems in northwestern region of the USA. BioEnergy Research, 9 (2), 412–429. doi:10.1007/s12155-016-9719-1. ↩
Luck, J., M. Spackman, A. Freeman, P. Tre˛bicki, W. Griffiths, K. Finlay, and S. Chakraborty, 2011: Climate change and diseases of food crops. Plant Pathology, 60 (1), 113–121. doi:10.1111/j.1365-3059.2010.02414.x. ↩
Mader, T. L., and D. Griffin, 2015: Management of cattle exposed to adverse environmental conditions. Veterinary Clinics: Food Animal Practice, 31 (2), 247–258. doi:10.1016/j.cvfa.2015.03.006. ↩
Mader, T. L., L. J. Johnson, and J. B. Gaughan, 2010: A comprehensive index for assessing environmental stress in animals. Journal of Animal Science, 88 (6), 2153–2165. doi:10.2527/jas.2009-2586. ↩
Mader, T. L., S. M. Holt, G. L. Hahn, M. S. Davis, and D. E. Spiers, 2002: Feeding strategies for managing heat load in feedlot cattle. Journal of Animal Science, 80 (9), 2373–2382. doi:10.2527/2002.8092373x. ↩
Malcolm, S., E. Marshall, M. Aillery, P. Heisey, M. Livingston, and K. Day-Rubenstein, 2012: Agricultural Adaptation to a Changing Climate: Economic and Environmental Implications Vary by U.S. Region. USDA-ERS Economic Research Report 136. U.S. Department of Agriculture Economic Research Service, Washington, D.C., URL. ↩
Malcolm, S., E. Marshall, P. Heisey, and M. Livingston, 2013: Adaptation can help U.S. crop producers confront climate change. Amber Waves. Washington, DC. URL. ↩
Mallakpour, I., and G. Villarini, 2015: The changing nature of flooding across the central United States. Nature Climate Change, 5 (3), 250–254. doi:10.1038/nclimate2516. ↩
Mann, M. E., and P. H. Gleick, 2015: Climate change and California drought in the 21st century. Proceedings of the National Academy of Sciences of the United States of America, 112 (13), 3858–3859. doi:10.1073/pnas.1503667112. ↩
Maresch, W., M. R. Walbridge, and D. Kugler, 2008: Enhancing conservation on agricultural landscapes: A new direction for the Conservation Effects Assessment Project. Journal of Soil and Water Conservation, 63 (6), 198A–203A. doi:10.2489/jswc.63.6.198A. ↩
Margolis, E. Q., C. A. Woodhouse, and T. W. Swetnam, 2017: Drought, multi-seasonal climate, and wildfire in northern New Mexico. Climatic Change, 142 (3), 433–446. doi:10.1007/s10584-017-1958-4. ↩
Marsha, A., S. R. Sain, M. J. Heaton, A. J. Monaghan, and O. V. Wilhelmi, 2016: Influences of climatic and population changes on heat-related mortality in Houston, Texas, USA. Climatic Change, doi:10.1007/s10584-016-1775-1. ↩
Marshall, E., M. Aillery, S. Malcolm, and R. Williams, 2015: Climate Change, Water Scarcity, and Adaptation in the U.S. Fieldcrop Sector. Economic Research Report No. (ERR-201). USDA Economic Research Service, Washington, DC, 119 pp. URL. ↩
Marshall, N. A., 2010: Understanding social resilience to climate variability in primary enterprises and industries. Global Environmental Change, 20 (1), 36–43. doi:10.1016/j.gloenvcha.2009.10.003. ↩
Mase, A. S., B. M. Gramig, and L. S. Prokopy, 2017: Climate change beliefs, risk perceptions, and adaptation behavior among midwestern U.S. crop farmers. Climate Risk Management, 15, 8–17. doi:10.1016/j.crm.2016.11.004. ↩
Mazdiyasni, O., and A. AghaKouchak, 2015: Substantial increase in concurrent droughts and heatwaves in the United States. Proceedings of the National Academy of Sciences of the United States of America, 112 (37), 11484–11489. doi:10.1073/pnas.1422945112. ↩
McGuire, V. L., 2017: Water-level and recoverable water in storage changes, High Plains aquifer, predevelopment to 2015 and 2013–15. 2017-5040. Scientific Investigations Report 2017-5040. U. S. Geological Survey, Reston, VA, 24 pp. doi:10.3133/sir20175040. ↩
McPherson, R. A., C. A. Fiebrich, K. C. Crawford, J. R. Kilby, D. L. Grimsley, J. E. Martinez, J. B. Basara, B. G. Illston, D. A. Morris, K. A. Kloesel, A. D. Melvin, H. Shrivastava, J. M. Wolfinbarger, J. P. Bostic, D. B. Demko, R. L. Elliott, S. J. Stadler, J. D. Carlson, and A. J. Sutherland, 2007: Statewide monitoring of the mesoscale environment: A technical update on the Oklahoma Mesonet. Journal of Atmospheric and Oceanic Technology, 24 (3), 301–321. doi:10.1175/jtech1976.1. ↩
Meier, H. E. M., H. C. Andersson, K. Eilola, B. G. Gustafsson, I. Kuznetsov, B. Müller‐Karulis, T. Neumann, and O. P. Savchuk, 2011: Hypoxia in future climates: A model ensemble study for the Baltic Sea. Geophysical Research Letters, 38 (24) doi:10.1029/2011GL049929. ↩
Melillo, J. M., T. (T. C. . Richmond, and G. W. Yohe, Eds., 2014: Climate Change Impacts in the United States: The Third National Climate Assessment. U.S. Global Change Research Program, Washington, DC, 841 pp. doi:10.7930/J0Z31WJ2. ↩
Merte, S., 2017: Estimating heat wave-related mortality in Europe using singular spectrum analysis. Climatic Change, 142 (3), 321–330. doi:10.1007/s10584-017-1937-9. ↩
Mitchell, R. B., M. R. Schmer, W. F. Anderson, V. Jin, K. S. Balkcom, J. Kiniry, A. Coffin, and P. White, 2016: Dedicated energy crops and crop residues for bioenergy feedstocks in the central and eastern USA. BioEnergy Research, 9 (2), 384–398. doi:10.1007/s12155-016-9734-2. ↩
Mittler, R., and E. Blumwald, 2010: Genetic engineering for modern agriculture: Challenges and perspectives. Annual Review of Plant Biology, 61 (1), 443–462. doi:10.1146/annurev-arplant-042809-112116. ↩
Monaghan, J. M., A. Daccache, L. H. Vickers, T. M. Hess, E. K. Weatherhead, I. G. Grove, and J. W. Knox, 2013: More ‘crop per drop': Constraints and opportunities for precision irrigation in European agriculture. Journal of the Science of Food and Agriculture, 93 (5), 977–980. doi:10.1002/jsfa.6051. ↩
Moran, T., and A. Cravens, 2015: California's Sustainable Groundwater Management Act of 2014: Recommendations for Preventing and Resolving Groundwater Conflicts. Stanford University Water in the West, Stanford, CA, 30 pp. URL. ↩
Morello-Frosch, R., M. Pastor, J. Sadd, and S. B. Shonkoff, 2009: The Climate Gap: Inequalities in How Climate Change Hurts Americans & How to Close the Gap. University of California, Berkeley, and USC Program for Environmental & Regional Equity, URL. ↩
MRLC, National Land Cover Database 2011 (NLCD 2011) . Multi-Resolution Land Characteristics (MRLC) Consortium, Sioux Falls, SD. URL. ↩
Mueller, B., and S. I. Seneviratne, 2012: Hot days induced by precipitation deficits at the global scale. Proceedings of the National Academy of Sciences of the United States of America, 109 (31), 12398–12403. doi:10.1073/pnas.1204330109. ↩
Myers, S. S., A. Zanobetti, I. Kloog, P. Huybers, A. D. B. Leakey, A. J. Bloom, E. Carlisle, L. H. Dietterich, G. Fitzgerald, T. Hasegawa, N. M. Holbrook, R. L. Nelson, M. J. Ottman, V. Raboy, H. Sakai, K. A. Sartor, J. Schwartz, S. Seneweera, M. Tausz, and Y. Usui, 2014: Increasing CO2 threatens human nutrition. Nature, 510 (7503), 139–142. doi:10.1038/nature13179. ↩
Myers, S. S., M. R. Smith, S. Guth, C. D. Golden, B. Vaitla, N. D. Mueller, A. D. Dangour, and P. Huybers, 2017: Climate change and global food systems: Potential impacts on food security and undernutrition. Annual Review of Public Health, 38 (1), 259–277. doi:10.1146/annurev-publhealth-031816-044356. ↩
National Research Council, 2009: Nutrient Control Actions for Improving Water Quality in the Mississippi River Basin and Northern Gulf of Mexico. The National Academies Press, Washington, DC, doi:10.17226/12544. ↩
NIFC, 2017: Historical Wildland Fire Information: Suppression Costs (1985-2016). National Interagency Fire Center (NIFC), Boise, ID, 1 pp. URL. ↩
NOAA Fisheries, 2016: Fisheries Economics of the United States, 2014. NOAA Technical Memorandum NMFS-F/SPO-163. NOAA, National Marine Fisheries Service (NOAA Fisheries), Silver Spring, MD, 235 pp. URL. ↩
Norgaard, K. M., K. Vinyeta, L. Hillman, B. Tripp, and Frank Lake, 2016: Karuk Tribe Climate Vulnerability Assessment: Assessing Vulnerabilities from the Increased Frequency of High Severity Fire. Karuk Tribe, Department of Natural Resources, Happy Camp, CA, 205 pp. URL. ↩
Novak, J. M., W. J. Busscher, D. W. Watts, J. E. Amonette, J. A. Ippolito, I. M. Lima, J. Gaskin, K. C. Das, C. Steiner, M. Ahmedna, D. Rehrah, and H. Schomberg, 2012: Biochars impact on soil-moisture storage in an Ultisol and two Aridisols. Soil Science, 177 (5), 310–320. doi:10.1097/SS.0b013e31824e5593. ↩
Novick, K. A., D. L. Ficklin, P. C. Stoy, C. A. Williams, G. Bohrer, A. C. Oishi, S. A. Papuga, P. D. Blanken, A. Noormets, B. N. Sulman, R. L. Scott, L. Wang, and R. P. Phillips, 2016: The increasing importance of atmospheric demand for ecosystem water and carbon fluxes. Nature Climate Change, 6, 1023–1027. doi:10.1038/nclimate3114. ↩
O'Shaughnessy, S. A., and P. D. Colaizzi, 2017: Performance of precision mobile drip irrigation in the Texas High Plains region. Agronomy, 7 (4), 68. doi:10.3390/agronomy7040068. ↩
O'Shaughnessy, S. A., S. R. Evett, A. Andrade, F. Workneh, J. A. Price, and C. M. Rush, 2016: Site-specific variable-rate irrigation as a means to enhance water use efficiency. Transactions of the ASABE, 59 (1), 239. doi:10.13031/trans.59.11165. ↩
Oleson, K. W., G. B. Anderson, B. Jones, S. A. McGinnis, and B. Sanderson, 2015: Avoided climate impacts of urban and rural heat and cold waves over the U.S. using large climate model ensembles for RCP8.5 and RCP4.5. Climatic Change, doi:10.1007/s10584-015-1504-1. ↩
Olson, K., J. Matthews, L. W. Morton, and J. Sloan, 2015: Impact of levee breaches, flooding, and land scouring on soil productivity. Journal of Soil and Water Conservation, 70 (1), 5A–11A. doi:10.2489/jswc.70.1.5A. ↩
Ortiz, R., K. D. Sayre, B. Govaerts, R. Gupta, G. V. Subbarao, T. Ban, D. Hodson, J. M. Dixon, J. Iván Ortiz-Monasterio, and M. Reynolds, 2008: Climate change: Can wheat beat the heat? Agriculture, Ecosystems & Environment, 126 (1), 46–58. doi:10.1016/j.agee.2008.01.019. ↩
Otkin, J. A., M. Svoboda, E. D. Hunt, T. W. Ford, M. C. Anderson, C. Hain, and J. B. Basara, 2018: Flash droughts: A review and assessment of the challenges imposed by rapid onset droughts in the United States. Bulletin of the American Meteorological Society, 99, 911–919. doi:10.1175/bams-d-17-0149.1. ↩
Park, K., C.-K. Kim, and W. W. Schroeder, 2007: Temporal variability in summertime bottom hypoxia in shallow areas of Mobile Bay, Alabama. Estuaries and Coasts, 30 (1), 54–65. doi:10.1007/bf02782967. ↩
Parris, A., P. Bromirski, V. Burkett, D. Cayan, M. Culver, J. Hall, R. Horton, K. Knuuti, R. Moss, J. Obeysekera, A. Sallenger, and J. Weiss, 2012: Global Sea Level Rise Scenarios for the United States National Climate Assessment. NOAA Tech Memo OAR CPO-1. NOAA Tech Memo OAR CPO-1. National Oceanic and Atmospheric Administration, National Oceanic and Atmospheric Administration, Silver Spring, MD, 37 pp. URL. ↩
Parton, W. J., M. P. Gutmann, E. R. Merchant, M. D. Hartman, P. R. Adler, F. M. McNeal, and S. M. Lutz, 2015: Measuring and mitigating agricultural greenhouse gas production in the US Great Plains, 1870–2000. Proceedings of the National Academy of Sciences of the United States of America, 112 (34), E4681–E4688. doi:10.1073/pnas.1416499112. ↩
Paul, B. K., D. Che, and V. L. Tinnon, 2007: Emergency Responses for High Plains Cattle Affected by the December 28-31, 2006, Blizzard. Quick Response Report 191. Natural Hazards Center, Boulder, CO, 12 pp. URL. ↩
Paustian, K., J. Lehmann, S. Ogle, D. Reay, G. P. Robertson, and P. Smith, 2016: Climate-smart soils. Nature, 532, 49–57. doi:10.1038/nature17174. ↩
Pelling, M., 2010: Adaptation to Climate Change: From Resilience to Transformation. Routledge, Abingdon, UK,. ↩
Peterson, A. G., and J. T. Abatzoglou, 2014: Observed changes in false springs over the contiguous United States. Geophysical Research Letters, 41 (6), 2156–2162. doi:10.1002/2014GL059266. ↩
Pimentel, D., and M. Burgess, 2013: Soil erosion threatens food production. Agriculture, 3 (3), 443–463. doi:10.3390/agriculture3030443. ↩
Pitesky, M., A. Gunasekara, C. Cook, and F. Mitloehner, 2014: Adaptation of agricultural and food systems to a changing climate and increasing urbanization. Current Sustainable/Renewable Energy Reports, 1 (2), 43–50. doi:10.1007/s40518-014-0006-5. ↩
Prager, D., C. Burns, and N. Key, 2017: Examining farm sector and farm household income . Amber Waves. URL. ↩
Pragna, P., P. R. Archana, J. Aleena, V. Sejian, G. Krishnan, M. Bagath, A. Manimaran, V. Beena, E. K. Kurien, G. Varma, and R. Bhatta, 2017: Heat stress and dairy cow: Impact on both milk yield and composition. International Journal of Dairy Science, 12 (1), 1–11. doi:10.3923/ijds.2017.1.11. ↩
Pryor, S. C., J. A. Howe, and K. E. Kunkel, 2009: How spatially coherent and statistically robust are temporal changes in extreme precipitation in the contiguous USA? International Journal of Climatology, 29 (1), 31–45. doi:10.1002/joc.1696. ↩
Pugh, T. A. M., C. Müller, J. Elliott, D. Deryng, C. Folberth, S. Olin, E. Schmid, and A. Arneth, 2016: Climate analogues suggest limited potential for intensification of production on current croplands under climate change. Nature Communications, 7, 12608. doi:10.1038/ncomms12608. ↩
Rabalais, N. N., R. J. Díaz, L. A. Levin, R. E. Turner, D. Gilbert, and J. Zhang, 2010: Dynamics and distribution of natural and human-caused hypoxia. Biogeosciences, 7 (2), 585–619. doi:10.5194/bg-7-585-2010. ↩
Ratcliffe, S., M. Baur, H. Beckie, L. Giesler, N. Leppla, and J. Schroeder, 2017: Crop Protection Contributions Toward Agricultural Productivity. A Paper in the Series on The Need for Agricultural Innovation to Sustainably Feed the World by 2050. CAST Issue Paper 58. Council for Agricultural Science and Technology (CAST), Ames, IA, 20 pp. URL. ↩
Ray, D. K., J. S. Gerber, G. K. MacDonald, and P. C. West, 2015: Climate variation explains a third of global crop yield variability. Nature Communications, 6, 5989. doi:10.1038/ncomms6989. ↩
Renaudeau, D., A. Collin, S. Yahav, V. de Basilio, J. L. Gourdine, and R. J. Collier, 2011: Adaptation to hot climate and strategies to alleviate heat stress in livestock production. Animal, 6 (5), 707–728. doi:10.1017/S1751731111002448. ↩
Rippey, B. R., 2015: The U.S. drought of 2012. Weather and Climate Extremes, 10, 57–64. doi:10.1016/j.wace.2015.10.004. ↩
RMA, 2017: The Risk Management Agency Safety Net: Market Penetration and Market Potential. USDA Risk Management Agency, Washington, DC, 58 pp. URL. ↩
Rojas-Downing, M. M., A. P. Nejadhashemi, T. Harrigan, and S. A. Woznicki, 2017: Climate change and livestock: Impacts, adaptation, and mitigation. Climate Risk Management, 16, 145–163. doi:10.1016/j.crm.2017.02.001. ↩
Rosenzweig, C., J. Elliott, D. Deryng, A. C. Ruane, C. Müller, A. Arneth, K. J. Boote, C. Folberth, M. Glotter, N. Khabarov, K. Neumann, F. Piontek, T. A. M. Pugh, E. Schmid, E. Stehfest, H. Yang, and J. W. Jones, 2014: Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proceedings of the National Academy of Sciences of the United States of America, 111 (9), 3268–3273. doi:10.1073/pnas.1222463110. ↩
Rosser, E., 2006: Rural housing and code enforcement: Navigating between values and housing types. Georgetown Journal on Poverty Law & Policy, 13 (1), 33–93. URL. ↩
Rudnick, D., S. Irmak, R. Ferguson, T. Shaver, K. Djaman, G. Slater, A. Bereuter, N. Ward, D. Francis, M. Schmer, B. Wienhold, and S. V. Donk, 2016: Economic return versus crop water productivity of maize for various nitrogen rates under full irrigation, limited irrigation, and rainfed settings in south central Nebraska. Journal of Irrigation and Drainage Engineering, 142 (6), 04016017. doi:10.1061/(ASCE)IR.1943-4774.0001023. ↩
Ruisi, P., S. Saia, G. Badagliacca, G. Amato, A. S. Frenda, D. Giambalvo, and G. Di Miceli, 2016: Long-term effects of no tillage treatment on soil N availability, N uptake, and 15N-fertilizer recovery of durum wheat differ in relation to crop sequence. Field Crops Research, 189, 51–58. doi:10.1016/j.fcr.2016.02.009. ↩
Scanlon, B. R., C. C. Faunt, L. Longuevergne, R. C. Reedy, W. M. Alley, V. L. McGuire, and P. B. McMahon, 2012: Groundwater depletion and sustainability of irrigation in the US High Plains and Central Valley. Proceedings of the National Academy of Sciences of the United States of America, 109 (24), 9320–9325. doi:10.1073/pnas.1200311109. ↩
Scanlon, B. R., R. C. Reedy, C. C. Faunt, D. Pool, and K. Uhlman, 2016: Enhancing drought resilience with conjunctive use and managed aquifer recharge in California and Arizona. Environmental Research Letters, 11 (3), 035013. doi:10.1088/1748-9326/11/4/049501. ↩
Scasta, J. D., D. L. Lalman, and L. Henderson, 2016: Drought mitigation for grazing operations: Matching the animal to the environment. Rangelands, 38 (4), 204–210. doi:10.1016/j.rala.2016.06.006. ↩
Schauberger, B., S. Archontoulis, A. Arneth, J. Balkovic, P. Ciais, D. Deryng, J. Elliott, C. Folberth, N. Khabarov, C. Müller, T. A. M. Pugh, S. Rolinski, S. Schaphoff, E. Schmid, X. Wang, W. Schlenker, and K. Frieler, 2017: Consistent negative response of US crops to high temperatures in observations and crop models. Nature Communications, 8, 13931. doi:10.1038/ncomms13931. ↩
Sharpley, A., 2016: Managing agricultural phosphorus to minimize water quality impacts. Scientia Agricola, 73, 1–8. doi:10.1590/0103-9016-2015-0107 . ↩
Slater, L. J., and G. Villarini, 2016: Recent trends in U.S. flood risk. Geophysical Research Letters, 43 (24), 12,428-12,436. doi:10.1002/2016GL071199. ↩
Smith, A. B., and R. W. Katz, 2013: US billion-dollar weather and climate disasters: Data sources, trends, accuracy and biases. Natural Hazards, 67 (2), 387–410. doi:10.1007/s11069-013-0566-5. ↩
Smith, D. R., K. W. King, and M. R. Williams, 2015: What is causing the harmful algal blooms in Lake Erie? Journal of Soil and Water Conservation, 70 (2), 27A–29A. doi:10.2489/jswc.70.2.27A. ↩
Spokas, K. A., K. B. Cantrell, J. M. Novak, D. W. Archer, J. A. Ippolito, H. P. Collins, A. A. Boateng, I. M. Lima, M. C. Lamb, A. J. McAloon, R. D. Lentz, and K. A. Nichols, 2012: Biochar: A synthesis of its agronomic impact beyond carbon sequestration. Journal of Environmental Quality, 41 (4), 973–989. doi:10.2134/jeq2011.0069. ↩
St-Pierre, N. R., B. Cobanov, and G. Schnitkey, 2003: Economic losses from heat stress by US livestock industries. Journal of Dairy Science, 86, E52–E77. doi:10.3168/jds.S0022-0302(03)74040-5. ↩
State of California, 2016: Groundwater Sustainability Plan Emergency Regulations. California Department of Water Resources, Sacramento, CA. URL. ↩
State of California, 2016: Sustainable Groundwater Management. California Department of Water Resources, Sacramento, CA. URL. ↩
Steenwerth, K. L., A. K. Hodson, A. J. Bloom, M. R. Carter, A. Cattaneo, C. J. Chartres, J. L. Hatfield, K. Henry, J. W. Hopmans, W. R. Horwath, B. M. Jenkins, E. Kebreab, R. Leemans, L. Lipper, M. N. Lubell, S. Msangi, R. Prabhu, M. P. Reynolds, S. Sandoval Solis, W. M. Sischo, M. Springborn, P. Tittonell, S. M. Wheeler, S. J. Vermeulen, E. K. Wollenberg, L. S. Jarvis, and L. E. Jackson, 2014: Climate-smart agriculture global research agenda: Scientific basis for action. Agriculture & Food Security, 3 (1), 11. doi:10.1186/2048-7010-3-11. ↩
Storlazzi, C. D., E. P. L. Elias, and P. Berkowitz, 2015: Many atolls may be uninhabitable within decades due to climate change. Scientific Reports, 5, 14546. doi:10.1038/srep14546. ↩
Sugg, M. M., C. E. Konrad, and C. M. Fuhrmann, 2016: Relationships between maximum temperature and heat-related illness across North Carolina, USA. International Journal of Biometeorology, 60 (5), 663–675. doi:10.1007/s00484-015-1060-4. ↩
Swann, A. L. S., F. M. Hoffman, C. D. Koven, and J. T. Randerson, 2016: Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity. Proceedings of the National Academy of Sciences of the United States of America, 113 (36), 10019–10024. doi:10.1073/pnas.1604581113. ↩
Sweet, W. V., R. Horton, R. E. Kopp, A. N. LeGrande, and A. Romanou, 2017: Sea Level Rise. Climate Science Special Report: Fourth National Climate Assessment, Volume I. Wuebbles, D. J., D. W. Fahey, K. A. Hibbard, D. J. Dokken, B. C. Stewart, and T. K. Maycock, Eds., U.S. Global Change Research Program, Washington, DC, USA, 333–363. doi:10.7930/J0VM49F2. ↩
Tack, J., A. Barkley, and L. L. Nalley, 2015: Effect of warming temperatures on US wheat yields. Proceedings of the National Academy of Sciences of the United States of America, 112 (22), 6931–6936. doi:10.1073/pnas.1415181112. ↩
Takle, E. S. T., D. Gustafson, R. Beachy, G. C. Nelson, D. Mason-D'Croz, and A. Palazzo, 2013: US food security and climate change: Agricultural futures. Economics: The Open-Access, Open-Assessment E-Journal, 7 (2013–34), 1–41. doi:10.5018/economics-ejournal.ja.2013-34 . ↩
Tebaldi, C., and D. Lobell, 2015: Estimated impacts of emission reductions on wheat and maize crops. Climatic Change, doi:10.1007/s10584-015-1537-5. ↩
Testa, J. M., Y. Li, Y. J. Lee, M. Li, D. C. Brady, D. M. Di Toro, W. M. Kemp, and J. J. Fitzpatrick, 2014: Quantifying the effects of nutrient loading on dissolved O2 cycling and hypoxia in Chesapeake Bay using a coupled hydrodynamic–biogeochemical model. Journal of Marine Systems, 139, 139–158. doi:10.1016/j.jmarsys.2014.05.018. ↩
Thornton, P. K., 2010: Livestock production: Recent trends, future prospects. Philosophical Transactions of the Royal Society B: Biological Sciences, 365 (1554), 2853–2867. doi:10.1098/rstb.2010.0134. ↩
Tilman, D., 1999: Global environmental impacts of agricultural expansion: The need for sustainable and efficient practices. Proceedings of the National Academy of Sciences of the United States of America, 96 (11), 5995–6000. doi:10.1073/pnas.96.11.5995. ↩
TRIP, 2015: Rural Connections: Challenges and Opportunities in America's Heartland. TRIP, Washington, DC, 43 pp. URL. ↩
Trout, T. J., and K. C. DeJonge, 2017: Water productivity of maize in the US high plains. Irrigation Science, 35 (3), 251–266. doi:10.1007/s00271-017-0540-1. ↩
Turco, M., J. von Hardenberg, A. AghaKouchak, M. C. Llasat, A. Provenzale, and R. M. Trigo, 2017: On the key role of droughts in the dynamics of summer fires in Mediterranean Europe. Scientific Reports, 7 (1), 81. doi:10.1038/s41598-017-00116-9. ↩
U.N. Department of Economic and Social Affairs Population Division, 2017: World Population Prospects: The 2017 Revision. Key Findings and Advance Tables . U.N. Department of Economic and Social Affairs, New York, NY, 46 pp. URL. ↩
U.S. Bureau of Reclamation, 2014: Reclamation: Managing Water in the West, Climate Change Adaptation Strategy. U.S. Department of the Interior, Bureau of Reclamation, Washington, DC, 50 pp. URL. ↩
U.S. Federal Government, 2016: U.S. Climate Resilience Toolkit: Coastal Erosion [web page]. United States Global Change Research Program, Washington, DC. URL. ↩
Upton, J., 2017: Breathing fire: Health is a causality of California's climate-fueled blazes. Climate Central News. Climate Central. URL. ↩
Urdaz, J. H., M. W. Overton, D. A. Moore, and J. E. P. Santos, 2006: Technical note: Effects of adding shade and fans to a feedbunk sprinkler system for preparturient cows on health and performance. Journal of Dairy Science, 89 (6), 2000–2006. doi:10.3168/jds.S0022-0302(06)72267-6. ↩
USDA Forest Service, and DOI Office of Wildland Fire, 2015: 2014 Quadrennial Fire Review: Final Report. Booz Allen Hamilton, Washington, DC, 79 pp. URL. ↩
USDA, 2010: Strategic Plan: FY 2010-2015. U.S. Department of Agriculture (USDA), Washington, DC, 50 pp. URL. ↩
USDA, 2010: USDA Climate Change Science Plan. U.S. Department of Agriculture (USDA), Washington, DC, 21 pp. URL. ↩
USDA, 2014: 2012 Census of Agriculture. U.S. Department of Agriculture, National Agricultural Statistics Service, Washington, D.C., 695 pp. URL. ↩
USGCRP, 2017: Climate Science Special Report: Fourth National Climate Assessment, Volume I. Wuebbles, D. J., D. W. Fahey, K. A. Hibbard, D. J. Dokken, B. C. Stewart, and T. K. Maycock, Eds. U.S. Global Change Research Program, Washington, DC, USA, 470 pp. doi:10.7930/J0J964J6. ↩
USGCRP, 2018: Second State of the Carbon Cycle Report (SOCCR2): A Sustained Assessment Report. U.S. Global Change Research Program, Washington, DC, 877 pp. URL. ↩
Varanasi, A., P. V. V. Prasad, and M. Jugulam, 2016: Ch. 3: Impact of climate change factors on weeds and herbicide efficacy. Advances in Agronomy. Sparks, D. L., Ed., Vol. 135 of, Academic Press, 107–146. doi:10.1016/bs.agron.2015.09.002. ↩
Vose, J., J. S. Clark, C. Luce, and T. Patel-Weynand, Eds., 2016: Effects of Drought on Forests and Rangelands in the United States: A Comprehensive Science Synthesis. Gen. Tech. Rep. WO-93b. U.S. Department of Agriculture, Forest Service, Washington Office, Washington, DC, 289 pp. URL. ↩
Vose, R. S., D. R. Easterling, K. E. Kunkel, A. N. LeGrande, and M. F. Wehner, 2017: Temperature Changes in the United States. Climate Science Special Report: Fourth National Climate Assessment, Volume I. Wuebbles, D. J., D. W. Fahey, K. A. Hibbard, D. J. Dokken, B. C. Stewart, and T. K. Maycock, Eds., U.S. Global Change Research Program, Washington, DC, USA, 185–206. doi:10.7930/J0N29V45. ↩
Wallander, S., M. Aillery, D. Hellerstein, and M. S. Hand, 2013: The Role of Conservation Programs in Drought Risk Adaptation. Economic Research Report ERR-148. USDA, Eonomic Research Service, Washington, DC, 68 pp. URL. ↩
Walsh, J., D. Wuebbles, K. Hayhoe, J. Kossin, K. Kunkel, G. Stephens, P. Thorne, R. Vose, M. Wehner, J. Willis, D. Anderson, S. Doney, R. Feely, P. Hennon, V. Kharin, T. Knutson, F. Landerer, T. Lenton, J. Kennedy, and R. Somerville, 2014: Ch. 2: Our Changing Climate. Climate Change Impacts in the United States: The Third National Climate Assessment. Melillo, J. M., T. (T. C. . Richmond, and G. W. Yohe, Eds., U.S. Global Change Research Program, Washington, DC, 19–67. doi:10.7930/J0KW5CXT. ↩
Walthall, C., P. Backlund, J. Hatfield, L. Lengnick, E. Marshall, M. Walsh, S. Adkins, M. Aillery, E. A. Ainsworth, C. Amman, C. J. Anderson, I. Bartomeus, L. H. Baumgard, F. Booker, B. Bradley, D. M. Blumenthal, J. Bunce, K. Burkey, S. M. Dabney, J. A. Delgado, J. Dukes, A. Funk, K. Garrett, M. Glenn, D. A. Grantz, D. Goodrich, S. Hu, R. C. Izaurralde, R. A. C. Jones, S.-H. Kim, A. D. B. Leaky, K. Lewers, T. L. Mader, A. McClung, J. Morgan, D. J. Muth, M. Nearing, D. M. Oosterhuis, D. Ort, C. Parmesan, W. T. Pettigrew, W. Polley, R. Rader, C. Rice, M. Rivington, E. Rosskopf, W. A. Salas, L. E. Sollenberger, R. Srygley, C. Stockle, E. S. Takle, D. Timlin, J. W. White, R. Winfree, L. Wright-Morton, and L. H. Ziska, 2012: Climate Change and Agriculture in the United States: Effects and Adaptation. USDA Technical Bulletin 1935. U.S. Department of Agriculture, Washington, D.C., 186 pp. URL. ↩
Watson, A., S. Ghosh, M. J. Williams, W. S. Cuddy, J. Simmonds, M.-D. Rey, M. Asyraf Md Hatta, A. Hinchliffe, A. Steed, D. Reynolds, N. M. Adamski, A. Breakspear, A. Korolev, T. Rayner, L. E. Dixon, A. Riaz, W. Martin, M. Ryan, D. Edwards, J. Batley, H. Raman, J. Carter, C. Rogers, C. Domoney, G. Moore, W. Harwood, P. Nicholson, M. J. Dieters, I. H. DeLacy, J. Zhou, C. Uauy, S. A. Boden, R. F. Park, B. B. H. Wulff, and L. T. Hickey, 2018: Speed breeding is a powerful tool to accelerate crop research and breeding. Nature Plants, 4 (1), 23–29. doi:10.1038/s41477-017-0083-8. ↩
Wehner, M. F., J. R. Arnold, T. Knutson, K. E. Kunkel, and A. N. LeGrande, 2017: Droughts, Floods, and Wildfires. Climate Science Special Report: Fourth National Climate Assessment, Volume I. Wuebbles, D. J., D. W. Fahey, K. A. Hibbard, D. J. Dokken, B. C. Stewart, and T. K. Maycock, Eds., U.S. Global Change Research Program, Washington, DC, USA, 231–256. doi:10.7930/J0CJ8BNN. ↩
Wei, X., M. Shao, W. Gale, and L. Li, 2014: Global pattern of soil carbon losses due to the conversion of forests to agricultural land. Scientific Reports, 4, 4062. doi:10.1038/srep04062. ↩
Wiebe, K., 2003: Linking Land Quality, Agricultural Productivity, and Food Security. Agricultural Economic Report No. AER-823. USDA Economic Research Service, Washington, DC, 60 pp. URL. ↩
Wienhold, B. J., M. F. Vigil, J. R. Hendrickson, and J. D. Derner, 2017: Vulnerability of crops and croplands in the US Northern Plains to predicted climate change. Climatic Change, doi:10.1007/s10584-017-1989-x. ↩
Williamson, T., H. Hesseln, and M. Johnston, 2012: Adaptive capacity deficits and adaptive capacity of economic systems in climate change vulnerability assessment. Forest Policy and Economics, 15, 160–166. doi:10.1016/j.forpol.2010.04.003. ↩
Winder, M., and U. Sommer, 2012: Phytoplankton response to a changing climate. Hydrobiologia, 698 (1), 5–16. doi:10.1007/s10750-012-1149-2. ↩
Woodson, R., 2016: The Role of U.S. Research Universities in Meeting the Global Food Security Challenge. 2016 AAAS Charles Valentine Riley Memorial Lecture. American Association for the Advancement of Science, Washington, DC, 19 pp. URL. ↩
Xu, H., D. G. Brown, and A. L. Steiner, 2018: Sensitivity to climate change of land use and management patterns optimized for efficient mitigation of nutrient pollution. Climatic Change, 147 (3), 647–662. doi:10.1007/s10584-018-2159-5. ↩
Yano, M., H. Shimadzu, and T. Endo, 2014: Modelling temperature effects on milk production: A study on Holstein cows at a Japanese farm. SpringerPlus, 3 (1), 129. doi:10.1186/2193-1801-3-129. ↩
Yasarer, L. M. W., and B. S. M. Sturm, 2016: Potential impacts of climate change on reservoir services and management approaches. Lake and Reservoir Management, 32 (1), 13–26. doi:10.1080/10402381.2015.1107665. ↩
Yorgey, G. G., S. A. Hall, E. R. Allen, E. M. Whitefield, N. M. Embertson, V. P. Jones, B. R. Saari, K. Rajagopalan, G. E. Roesch-McNally, B. Van Horne, J. T. Abatzoglou, H. P. Collins, L. L. Houston, T. W. Ewing, and C. E. Kruger, 2017: Northwest U.S. agriculture in a changing climate: Collaboratively defined research and extension priorities. Frontiers in Environmental Science, 5, 52. doi:10.3389/fenvs.2017.00052. ↩
Young, S. L., 2017: As climate shifts, so do pests: A national forum and assessment. Bulletin of the Ecological Society of America, 98 (2), 165–172. doi:10.1002/bes2.1315. ↩
Yue, Y., J. Ni, P. Ciais, S. Piao, T. Wang, M. Huang, A. G. L. Borthwick, T. Li, Y. Wang, A. Chappell, and K. Van Oost, 2016: Lateral transport of soil carbon and land−atmosphere CO2 flux induced by water erosion in China. Proceedings of the National Academy of Sciences of the United States of America, 113 (24), 6617–6622. doi:10.1073/pnas.1523358113. ↩
Zampieri, M., A. Ceglar, F. Dentener, and A. Toreti, 2017: Wheat yield loss attributable to heat waves, drought and water excess at the global, national and subnational scales. Environmental Research Letters, 12 (6), 064008. doi:10.1088/1748-9326/aa723b. ↩
Zhao, C., B. Liu, S. Piao, X. Wang, D. B. Lobell, Y. Huang, M. Huang, Y. Yao, S. Bassu, P. Ciais, J.-L. Durand, J. Elliott, F. Ewert, I. A. Janssens, T. Li, E. Lin, Q. Liu, P. Martre, C. Müller, S. Peng, J. Peñuelas, A. C. Ruane, D. Wallach, T. Wang, D. Wu, Z. Liu, Y. Zhu, Z. Zhu, and S. Asseng, 2017: Temperature increase reduces global yields of major crops in four independent estimates. Proceedings of the National Academy of Sciences of the United States of America, 114 (35), 9326–9331. doi:10.1073/pnas.1701762114. ↩
Zhao, J., Q. Xue, K. E. Jessup, B. Hao, X. Hou, T. H. Marek, W. Xu, S. R. Evett, S. A. O'Shaughnessy, and D. K. Brauer, 2018: Yield and water use of drought-tolerant maize hybrids in a semiarid environment. Field Crops Research, 216, 1–9. doi:10.1016/j.fcr.2017.11.001. ↩
Zhao, T., and A. Dai, 2017: Uncertainties in historical changes and future projections of drought. Part II: Model-simulated historical and future drought changes. Climatic Change, 144 (3), 535–548. doi:10.1007/s10584-016-1742-x. ↩
Zhorov, I., 2013: Why did South Dakota snowstorm kill so many cattle? National Geographic. URL. ↩
Ziska, L., K. Knowlton, C. Rogers, D. Dalan, N. Tierney, M. A. Elder, W. Filley, J. Shropshire, L. B. Ford, C. Hedberg, P. Fleetwood, K. T. Hovanky, T. Kavanaugh, G. Fulford, R. F. Vrtis, J. A. Patz, J. Portnoy, F. Coates, L. Bielory, and D. Frenz, 2011: Recent warming by latitude associated with increased length of ragweed pollen season in central North America. Proceedings of the National Academy of Sciences of the United States of America, 108 (10), 4248–4251. doi:10.1073/pnas.1014107108. ↩
Špitalar, M., J. J. Gourley, C. Lutoff, P.-E. Kirstetter, M. Brilly, and N. Carr, 2014: Analysis of flash flood parameters and human impacts in the US from 2006 to 2012. Journal of Hydrology, 519, 863–870. doi:10.1016/j.jhydrol.2014.07.004. ↩

Front Matter

National Topics

National Topics (cont.)

Regions

Responses

Appendices

Key Message 1Reduced Agricultural Productivity

Key Message 2Degradation of Soil and Water Resources

Key Message 3Health Challenges to Rural Populations and Livestock

Key Message 4Vulnerability and Adaptive Capacity of Rural Communities

Key Message 1

Key Message 2

Key Message 3

Key Message 4

Likelihood

Confidence Level

EXECUTIVE SUMMARY: Chapter 10: Agriculture and Rural Communities

Agricultural Jobs and Revenue

Population Changes and Poverty Rates in Rural Counties

CHAPTER 10 Agriculture and Rural Communities

State of the Agriculture and Rural Communities Sectors

Authors

Contributors

Recommended Citation

Related Links

Figure 10.1: Agricultural Jobs and Revenue

Figure 10.2: Population Changes and Poverty Rates in Rural Counties

Reduced Agricultural Productivity

Degradation of Soil and Water Resources

Figure 10.4: Land Area and Extreme Precipitation

Health Challenges to Rural Populations and Livestock

Figure 10.5: Projected Reduction in Milk Production

Vulnerability and Adaptive Capacity of Rural Communities

Emerging Issues and Research Gaps

TRACEABLE ACCOUNTS

Process Description

KEY MESSAGES

Key Message 1: Reduced Agricultural Productivity

Description of evidence base

Major uncertainties

Description of confidence and likelihood

Key Message 2: Degradation of Soil and Water Resources

Description of evidence base

Major uncertainties

Description of confidence and likelihood

Key Message 3: Health Challenges to Rural Populations and Livestock

Description of evidence base

Major uncertainties

Description of confidence and likelihood

Key Message 4: Vulnerability and Adaptive Capacity of Rural Communities

Description of evidence base

Major uncertainties

Description of confidence and likelihood

REFERENCES

Key Message 1
Reduced Agricultural Productivity

Key Message 2
Degradation of Soil and Water Resources

Key Message 3
Health Challenges to Rural Populations and Livestock

Key Message 4
Vulnerability and Adaptive Capacity of Rural Communities

EXECUTIVE SUMMARY:
Chapter 10: Agriculture and Rural Communities

CHAPTER 10
Agriculture and Rural Communities