Table of Contents1 Introduction..............................................................................................................................2

1.1 Recent History of Climate Change and Drivers................................................................21.2 Projected Climate change..................................................................................................31.3 Broad Ways Climate Change Affects Agriculture..............................................................5

2 Issues and findings from the Literature...................................................................................52.1 Effects of Climate Change on Agriculture........................................................................5

2.1.1 Crops..........................................................................................................................62.1.2 Livestock....................................................................................................................82.1.3 Regions and Land values...........................................................................................8

2.2 Adaptation.........................................................................................................................92.2.1 Observed adaptation actions....................................................................................102.2.2 Adaptation benefits and costs..................................................................................112.2.3 Adaptation constraints, economic barriers:.............................................................112.2.4 Deficits, residual damages and maladaptation.........................................................11

2.3 Mitigation........................................................................................................................122.3.1 Greenhouse Gas Emissions Sources........................................................................122.3.2 The Mitigation Imperative.......................................................................................122.3.3 Potential Agricultural Role......................................................................................122.3.4 Polices, Measures, and Instruments.........................................................................132.3.5 Economic Appraisal of the Effects of Agricultural Mitigation Actions..................142.3.6 Challenges in implementing agricultural Mitigation...............................................14

2.4 Towards Societal Action.................................................................................................152.4.1 Mitigation and Adaptation Incentive Program Design............................................152.4.2 Mix of Adaptation and Mitigation...........................................................................16

3 Concluding comments...........................................................................................................164 References..............................................................................................................................17

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How Does Climate Change Affect Agriculture?

Panit Arunanondchai1, Chengcheng Fei1, Anthony Fisher2, Bruce A. McCarl3, Weiwei Wang4, Yingqian Yang1

1Research Assistant, Department of Agricultural Economics, Texas A&M University2 Professor, Department of Agricultural and Resource Economics, University of California,

Berkeley3 Distinguished Professor, Department of Agricultural Economics, Texas A&M University4 Post Doc Research Associate, Department of Agricultural and Consumer Economics,

University of Illinois at Urbana-Champaign

1 IntroductionClimate change according to the Intergovernmental Panel on Climate Change (IPCC) refers to a change in the state of the climate that can be identified by changes in the mean and/or the variability of its properties, and that persists for an extended period, typically decades or longer (IPCC 2013). Climate change has been observed to have widespread impacts on human and natural systems (IPCC 2014a) including agriculture. Of course it is not normally possible to attribute all extreme events such as heat waves, hurricanes and droughts to climate change, but a recent study of extreme weather events in 2012 has detected the “finger prints” of climate change in half of them, including “Superstorm Sandy” (Peterson et al. 2013).

The essential questions of this chapter are: 1) How do the effects of and possible scientific responses to climate change affect agriculture?, and 2) How might agricultural economists contribute to understanding and reducing the magnitude of the problem. We will address these items raising issues and providing a supporting literature review (partially because of the vastness of the literature). In doing this we will review recent climate and climate change driver developments, climate change effects on agriculture, possible adaptation strategies and possible agricultural actions to mitigate/limit the future extent of climate change.

1.1 Recent History of Climate Change and DriversThe IPCC, has devoted substantial effort to documenting the extent of climate change with the most recent report (IPCC 2013) indicating that:

Between 1880 and 2012, the combined land and ocean surface temperature increased by 0.85°C with a range of 0.65 to 1.06°C. Additionally it exhibited substantial decadal and inter-annual variability;

Precipitation over the mid-latitude land areas of the Northern Hemisphere has increased since 1901;

Between 1901 and 2010, global mean sea level rose by 0.19 m with a range of 0.17 to 0.21 m. The rate of sea level rise since the mid-20th century has been larger than the mean rate during the previous two millennia;

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4°

2°Inevitable amount

Era 1 Era 2

Increases in extreme climate related events have been observed since about 1950. These include heat waves, extreme precipitation events, droughts, floods, cyclones and wildfires.

Frequency of cold days and nights has decreased and that of warm days and nights has increased.

Natural and anthropogenic processes that alter the earth's energy budget have been identified as drivers of climate change (IPCC 2014b). Anthropogenic greenhouse gas (GHG) concentrations and emissions have greatly increased (with CO2 rising from 275 parts per million (ppm) in the atmosphere in 1850 to over 400 ppm and CO2 equivalent to over 485 ppm (NOAA 2016) yielding concentrations much higher than in the last half million years (IPCC 2014b).

1.2 Projected Climate ChangeClimate change is projected to go on although the extent of it depends upon GHG concentrations in the atmosphere and mitigation efforts to limit net emissions. The future projections are summarized in the graph from Knutti and Sedláček(2012) as modified by McCarl (2015).

Figure 1.1: IPCC AR5 graph of future temperature change under alternative GHG scenarios modified by McCarl (2015)

In Figure 1.1, IPCC (2014a) defines two eras of future climate change. Era 1 is the period between now and 2040 and called the period of committed climate change; Era 2 is the period between 2040 and 2100 and is called the era of climate options (IPCC 2014a). Also in the graph the black line represents the amount of temperature change to date, while the colored lines show climate change evolution under different degrees of GHG mitigation and are called representative concentration pathways (RCPs).

Note in Era 1 there is a commitment to an about 1 °C change without very large effects from the different mitigation scenarios. However in Era 2 there is a temperature change spanning between 2 and 4 °C depending on different mitigation effort (where RCP8.5 has much less mitigation effort than RCP4.5). Agriculture will need to operate in both of these Era’s and thus will be affected by climate change and may participate in reaching the lower RCP levels through mitigation actions.

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Before proceeding, we should note that IPCC projections of future climate change indicators such as emissions, temperature change and sea level rise tend to be conservative, with a history of under-predicting these indicators. We briefly note a couple of problems with the most recent projections.

One is that they omit the potential increase in global mean temperature (GMT) due to Arctic permafrost melting and release of carbon dioxide and methane. This omission may be defensible on the grounds that the cumulative release is uncertain at this time, but it is already occurring on a small scale (United Nations Environment Program, 2012). The concern is that this is a positive feedback loop: the greater the release of these greenhouse gases, the greater the increase in temperature, and so on. Moreover, the situation could worsen dramatically, because there are much larger stores of methane in undersea structures (methane clathrates, methane trapped in crystal structures of water found under sediments on ocean floors), already releasing an estimated 19 million tons annually from the East Siberian Arctic Shelf (Shakhova et al. 2013). Under the right circumstances, releases could be much greater, comparable to land-based emissions (Whiteman, Hope and Wadhams 2013).

Also omitted are effects on sea level rise from melting of the two major potential sources: the Greenland Ice Sheet and the West Antarctic Ice Sheet. In this regard there are two recent and concerning discoveries – that the formerly stable ice sheet in northeast Greenland is now melting rapidly (Khan et al. 2014), along with previously known melting in southern Greenland, and that early-stage collapse of the West Antarctic Ice Sheet has begun and is irreversible (Joughin, Smith and Medley 2014). Such findings make more likely and bring nearer in time a massive sea level rise of as much as 15 meters (Poore, Williams and Tracey 2000) and resulting inundation of coastal and low-lying areas, including prime agricultural land. The latter is projected to have major impact in the decades beyond 2100, but this raises another issue: what is the appropriate time horizon for projections?

Temperature increase and sea level rise will continue well beyond 2100, especially under high emissions like those under RCP8.5. A more appropriate end-point for projections, when a natural equilibrium may be reached(Cline 1992; Fisher and Le 2014), is probably around 2300, when the increase in GMT will have reached about 10 degrees Celsius, with attendant catastrophic impacts, according to an extended RCP8.5 scenario developed by the German Climate Computing Center (2014).

An obvious question here is, why should we care about events far in the future which will be heavily discounted in a benefit-cost analysis? Discussions of discounting in the context of climate change policy are often set in the framework of the Ramsey equation, which states that the consumption or goods discount rate is equal to the sum of two components: the pure (social) rate of time preference, and the product of the elasticity of the marginal utility of consumption and the rate of growth in per capita consumption. Although not all would agree, Stern (2007), Heal (2008), and others have argued that the social rate of time preference should be set at or very close to zero, implying a low consumption or goods discount rate. Further, once uncertainty about the course of future consumption growth, affected by, among other things, uncertainty about potential impacts of climate change, is introduced into the Ramsey framework, there are strong theoretical arguments, presented and summarized by Arrow et al. (2014), for a declining discount rate, i.e., a discount rate schedule in which the rate applied to benefits and costs occurring in the future declines over time. The point is that, in thinking about the potential

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impacts of climate change, the future, even the distant future, matters more than in a typical benefit-cost analysis. Interestingly, as they note, this is in fact the practice in evaluating projects and regulations in France and the United Kingdom, though not in the US, where OMB requires use of a constant exponential rate.

We are not predicting that the kinds of catastrophic impacts in the more distant future, beyond the end of the present century, as discussed by Stern (2007), Fisher and Le (2014), and others, will happen, for several reasons, including technical change in the energy sector and adoption of policies to more dramatically reduce emissions. Rather, unless economists and decision-makers have a clear understanding of the potential impacts of unconstrained emissions, analyses and policies that would lead to a timely development of energy alternatives will be problematic.

1.3 Broad Ways Climate Change Affects AgricultureThe agriculture sector is highly dependent upon weather and climate. Thus, it is vulnerable to climate change (called effects). The extent of this vulnerability depends on adaptive actions taken by humans to moderate the effects (called adaptation). Agriculture is also a significant source of anthropogenic GHG emissions (about 24% globally when including deforestation) and may participate in emissions reduction by altering management (called mitigation). Thus the ways the climate change issue affects agriculture depends on the simultaneous extent of three forces

The effects of climate change brought on by altered temperatures, precipitation, extreme events, sea level rise, pest responses and other climate related forces (as reviewed in Porter et al. 2014; Hatfield et al. 2014).

The adaptation actions to alter agricultural processes in response to climate change to reduce damages and/or exploit opportunities (as reviewed in McCarl, Thayer and Jones 2016).

The mitigation actions to limit future extent of climate change by altering agricultural management (Smith et al. 2008; Smith et al. 2014).

Thus when one examines how climate change will impact agriculture one needs to consider

What is the extent of the climate change effects? What are the impacts on agriculture of adaptation and mitigation actions? How do these forces jointly interact and what is the total impact on productivity, cost of

production, income, food costs, food security and many other agricultural attributes?

This chapter will provide coverage across all of these items.

2 Issues and Findings from the Literature2.1 Effects of Climate Change on AgricultureClimate change can significantly affect crops, livestock, farmland values, household welfare, and food security. Studies have shown that its overall effect on agriculture can be complicated. For instance, while changes in temperature and precipitation can be beneficial for some crops in some places (areas limited by cold or improper amounts of rainfall), they can be detrimental for

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other crops in other places (places that are hot and dry). Nonlinear climate effects are also expected as low or high extremes in heat or precipitation are detrimental.

In this section, a number of effects of climate change are highlighted with major pieces of research identified. Their main items examined are shown in the following subsections: (i) crops; (ii) livestock; (iii) land values; and (iv) incomes, consumer welfare, prices, food security and poverty.

2.1.1 Crops

Crop yields are strongly affected by temperature, precipitation, and extremes thereof along with carbon dioxide (C O2) plus are affected by sea level rise and pests. Econometric and simulation approaches have been used to examine these issues.

Crop simulation was the original technique used to study crop yield sensitivity. Two studies employing this method are Adams et al. (1990) and Reilly et al. (2002). Collectively these studies found: a) crop yield effects can be positive or negative and vary by region with southern areas generally having larger and more negative effects; b) carbon dioxide is an important factor in yields of some crops and its consideration can reverse the nature of overall effects; and c) effects can be overstated if one does not consider changes in planting dates, varieties and other farm level adaptations.

More recently a number of econometric studies have examined effects using historical yields. For example McCarl, Villavicencio and Wu (2008) developed an econometric estimate of annual average climate change effects on yield distributions using data on major agricultural crops across the U.S. They considered effects of temperature, precipitation, variance of intra-annual temperature, a constructed index of rainfall intensity, and Palmer Drought Severity Index (PDSI) but ignored nonlinearities. Their empirical results show that stationarity of crop yield distributions does not hold for either the mean or the variance. The effects were found to differ by crop and location.

Schlenker, Hanemann and Fisher (2006) studied extremes and found that an increase in very hot days (measured by growing season days with temperatures above 34℃) strongly affects agricultural land values in the US. They projected that an increase in such hot days under a business as usual scenario such as the subsequent IPCC RCP8.5 would have a large and mostly statistically significant negative impact on US farmland value. Land value changes were found to be unevenly distributed with most counties harmed and a few, in a northern tier along the Canadian border, helped by a longer growing season.

More generally changes in the frequency and severity of extreme events, such as droughts and floods, have been found to adversely affect crop production. A few studies of such issues and items focused on are climate variability - Porter and Semenov (2005); shifts in El Nino event frequency - Chen, McCarl and Adams (2001); incidence of very hot days - Schlenker, Hanemann and Fisher (2006); variance of intra-annual temperature, rainfall intensity, and drought frequency- McCarl et al. (2008); and hurricanes - Chen and McCarl (2009).

Schlenker and Roberts (2009) studied the nonlinear impact of climate change and found that crop yields are stable or slowly increase with temperature up to 29℃ for corn and 30℃ for soybeans, but they then fall sharply with additional increases(see Figure 2.1). 6

Figure 2.1 Nonlinear impact of temperature on US corn and soybean crop yields Source: Schlenker and Roberts (2009; Figure 1, p. 15595).

One additional factor that alters crop yield is CO2, which stimulates growth for some crops (C3 crops like cotton, wheat and rice) but has small growth effects on C4 crops (sugarcane, corn, sorghum and millet) except under drought (Attavanich and McCarl, 2014). This is a difficult item to include in models as it has progressed linearly with time and can be confused with technological progress. Attavanich and McCarl (2014) merged a data set of experimental results over alternative CO2 with a historical data set to econometrically investigate the relationship between climate and yield variability. They find that ignoring atmospheric CO2 leads to an overestimate of technical progress and find the expected results that yields of C3 crops positively respond while yields of C4 crops do not except under drought stress. They did find non-linear effects of temperature and precipitation.

Crop yields are not only affected in the short run but there is also the likelihood that longer run technical progress is altered. Additionally, climate change also has been found to influence technological progress and have regionally specific effects on total returns to research investments with southern areas seeing reductions and some northern areas increases (Feng, McCarl and Havlik 2011,Villavicencio et al. 2013).

In terms of pests, several studies have investigated climate influences on pests and pesticide costs. Juroszek and von Tiedemann (2013) provided a review of the biophysical effects. Chen and McCarl (2001) looked at cost effects under the assumption that pest incidence increases would be matched by pesticide cost increases and examined climate effects on cost. They found that pesticide expenditures rise with increased temperatures and precipitation for the majority of crops. Shakhramanyan, Schneider and McCarl (2013) extended the work looking at individual compounds and their resultant environmental costs finding that climate change induced increased use of pesticides and associated run off and in turn environmental and health costs.

Sea level is also a factor where producing lands can be inundated particularly in low lying areas of countries like Bangladesh, Japan, Taiwan, Egypt, Myanmar and Vietnam. Low lying areas are vulnerable to sea level rise cause land loss and salt water intrusion affecting water supplies. The realization of these threats can cause substantial regional crop productivity losses (Chen, McCarl and Chang 2012).

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2.1.2 LivestockClimate change can alter livestock growth, reproduction rates, death rates, feed supplies and nutritional content; and disease and pest incidence. Some specific findings are:

Heat waves have been found to affect animal performance, animal mortality, illness, feed intake, feed conversion rates, rates of gain, milk production, conception rates and appetite loss (St-Pierre, Cobanov and Schnitkey 2003; Gaughan et al. 2009; Mader et al. 2009; Mader 2014).

A longer animal feeding period will be needed to obtain the same volume of animal products (Mader et al. 2009).

Feed availability and feed quality are altered through effects on crop, pasture, and forage growth and nutritional quality as discussed above plus grasses have altered nutritional value and digestibility (Craine et al. 2010).

Increased rainfall intensity has been observed to increase range and pasture land soil degradation (Howden, Crimp and Stokes 2008).

Pest and disease incidence has been found to increase, altering animal health, disease outbreaks and fecundity (Gale et al. 2009; Mu et al. 2014).

2.1.3 Regions and Land ValuesMost of the early studies predicted adverse effects of global climate change on U.S. agriculture (Adams et al. 1990; Adams et al. 1995). Mendelsohn, Nordhaus and Shaw (1994) used a reduced-form hedonic model with the value of farmland to estimate the impact of climate change and found economic benefits for agriculture. This is possible because their model allows adaptation as conditions change (see Figure 2.2).

Figure 2.2 Hypothetical values of output in four different sectors as a function of temperature Source: Mendelsohn, Nordhaus, and Shaw (1994; Figure 1, p. 754).

Schlenker, Hanemann and Fisher (2005) argue that the hedonic model approach is vulnerable to misspecification problems. They argue in particular that the inadequate treatment of irrigation might bias the results. Hence, they incorporated irrigation into the hedonic model. They find that

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the economic effects of climate change on agriculture need to be assessed differently in primarily rainfed and primarily irrigated areas. In a semi-arid area, climate change is likely to affect agriculture in two distinct ways. One pathway is the direct effect of climate on crop growth. Another potential pathway is through the supply of water for irrigation. The main point is that local precipitation, as used by Mendelsohn et al. (1994), is not the right variable for irrigated areas, as water supplies, are drawn from sometimes distant geographic areas with differing precipitation and from aquifers. Due to this, they limit their analysis to rainfed areas, constituting about 2/3 of U.S. counties, where water supplies are measured by local precipitation. Their results suggest that the economic effects of projected climate change on farmland values are unambiguously negative. In a subsequent study of the effects of irrigation water availability on farmland values in California they find that water availability strongly capitalizes into farmland values and that the anticipated decrease in availability can be expected to have a large and significant negative impact on farmland values (Schlenker, Hanemann and Fisher 2007).

2.1.4 Incomes, income distribution and food securityWelfare, food security and incomes can also be affected by climate change. For instance, climate change may adversely affect agricultural productivity, raising food prices and farm incomes but lowering food supplies and enhancing food insecurity (Butt et al. 2005). Moreover, it may affect poor people’s livelihood through its effects on health, access to water and natural resources, and infrastructure. As stated in previous subsections, several empirical studies provide significant evidence that changes in climate can substantially affect agricultural output. However, there is considerable heterogeneity in outcomes based on geographical location with higher latitude regions and larger countries like the US possible increasing welfare (Malcolm et al. 2012). Furthermore, collective work shows opposite effects of productivity on consumers and producers with producers gaining and consumers losing when productivity is negatively affected and the opposite when it is positively affected (Reilly et al. 2002).

In a global setting Ahmed, Diffenbaugh and Hertel (2009) find that the most significant climate change impacts on poverty are likely to occur among urban wage laborers due to food price increases and that self-employed rural households are less affected because they benefit from higher prices. They also find that climate change exacerbates poverty vulnerability in many nations and that climate extremes exert stress on low-income populations. In terms of food security, Baldos and Hertel (2014) find that climate change is still a key driver of nutritional outcomes particularly in regions where chronic malnutrition is prevalent.

2.2 AdaptationAdaptation actions can be taken to reduce the negative impacts of climate change or exploit opportunities. There is an inevitable need for agriculture to need to adapt given the future projected temperature path. In particular note in Figure 1.1 that in the next 25 years (era 1) society faces about 1 degree of temperature increase regardless of mitigation effort (see the explanation in McCarl (2015). Such adaptation can be natural or the result of human action. Natural adaptations are those undertaken by ecosystems like changes in bird migrations or the mix of tree species at a site. Human adaptations are commonly classified as autonomous or planned adaptations (IPCC, 2014a). Autonomous adaptation actions refer to those occurred

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“without directed intervention of public agency”, which are generally private actions taken by decision makers in their own best interests. Planned adaptations refer to actions undertaken by public groups resolving public good like market failures (McCarl, Thayer and Jones, 2016). Here we discuss a number of aspects of adaptation including 1) observed adaptation actions, 2) benefits, 3) costs and 4) constraints, and economic barriers and 5) adaptation deficits and maladaptation.

2.2.1 Observed Adaptation ActionsA number of studies have been examined types of agricultural adaptations to climate change that have been undertaken. Here we list some of the adaptations observed grouped under crops and livestock.

2.2.1.1 CroppingThe most common agricultural adaptation involves crop selection and crop timing. In terms of crop timing Sacks and Kucharik (2011) found that farmers are planting soybeans and corn earlier than before. EPA indicates “The average length of the growing season in the contiguous 48 states has increased by nearly two weeks since the beginning of the 20th century.” (EPA 2013).

Park, McCarl and Wu (2016) found in a US based econometric study that temperature and precipitation influence farmers’ crop selection, and that farmers alter crop mix in response to climate. In the coldest areas, barley, soybeans and spring wheat dominate. As the temperature increases, soybeans and winter wheat enter and become dominant, then with more temperature increase we see the entry of upland cotton and sorghum, and finally rice is planted in the hottest area.

Reilly et al. (2002) and Cho (2015) found that many crops in U.S. have shifted to higher latitudes and elevations as temperature increased. Attavanich et al. (2013) found such a crop mix shift and observed this changes demand on the grain transportation system and mode usage.

Employing irrigation, managing water and building infrastructure are also adaptations used in cropping (Howden et al. 2007) as is an increase in pesticide use (Chen and McCarl, 2001) and a movement of land from cropping to pasture/range (Mu, McCarl and Wein 2013).

2.2.1.2 LivestockClimate change also causes producers to make shifts in the livestock species they raise plus the breeds used and the management of the animals. In terms of species choice Seo and Mendelsohn (2008) found in Africa that species incidence shifts with climate. They found farmers in warmer places chose goats and sheep instead of beef cattle, and farmers in wetter places shifted from cattle and sheep to goats and chickens. On breeds, Zhang, Hagerman and McCarl (2013) found that more heat tolerant cattle (Bosindicus) were selected to adapt to hotter conditions and as temperature increases in Texas.

In terms of management, strategies like adjusting stocking rate, varying season of grazing and altering pest management have been used (Joyce et al. 2013). Mu et al. (2013) found that cattle stocking rates are decreased, with reductions in precipitation and an increasing summer temperature-humidity index (THI). Gaughan et al. (2009) observed (1) adjustments in livestock and feed supply mix including altered forages, (2) alteration of facilities like provision of shade, 10

misting and water, and (3) relocation of livestock among different regions. Howden et al. (2007) found that integrated crop and livestock production systems are employed to adapt to climate change.

2.2.2 Adaptation Benefits and Costs

Howden et al. (2007) argue adaption can increase economic benefits, and reduce the impact due to climate change, in turn increasing profit and social welfare, improving food security, and providing valuable time for mitigation to work. A number of studies have addressed such benefits quantitatively including:

Shifts in crop mixes, livestock species and livestock breeds were found to increase yield and decease the costs of drought and heat waves (Adams et al. 1999; Howden et al. 2007; IPCC 2014a).

Butt, McCarl and Kergna (2006) found that crop management adaption (such as crop mixes and drought resistant varieties) and increased international trade could substantially improve food security problems in Mali, as well as increasing social welfare.

Lobell et al. (2008) argued cropping adaptation to climate change is necessary to enhance food security while IPCC (2014a) indicates adaption could contribute to current and future economic growth plus distribute risk.

Aisabokhae, McCarl and Zhang (2011) found adaptation in crop planting dates and time to maturity were the most valuable of the variety of adaptations they studied.

Crop variety shifts have been found to allow producer adaptation and yield increases under increased drought frequency, altered pest populations, and heat increases (Yu and Babcock 2010; Malcolm et al. 2012).

Mendelsohn and Dinar (1999) found farmers in developing countries could reduce the potential damages from climate change by up to one half through adaptation activities.

Increases in technical progress have been found to be strategies to adapt to climate change, sea level induced losses in planted rice areas and yield losses (Chen et al. 2012).

Integrated crop and livestock production systems have been found to be a valuable adaptation option that greatly reduces income fluctuation (Howden et al. 2007). A few studies have examined the cost of adaptation considering fixed capital formation, infrastructure development, research and development, extension, transitional assistance and trade policy. As part of the UNFCCC (2007) study, McCarl (2007) developed an estimate that global agricultural public funding needs were about 14 billion U.S dollars per year. Parry et al. 2009) estimated a similar amount.

2.2.3 Adaptation Constraints and Economic Barriers

A number of constraints impede adaptation implementation. According to IPCC (2014a), the main constraints include: a) knowledge, awareness, and technology availability, b) physical and biological limits, c) economic and financial resources, d) human capabilities, e) social and cultural considerations, and f) governance and institutions. Economic considerations pose another set of barriers. These include transaction costs, information costs and adjustment costs, market failure and missing markets, etc. (IPCC 2014a).

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2.2.4 Deficits, Residual Damages and Maladaptation

Adaptation is not only a concern that addresses future climate change, but can involve alterations to accommodate the current climate plus there is the possibility that adaptation by one party can worsen adaption of someone else. Finally adaptation may be unable to accommodate some climate change effects. This raises the issues of adaptation deficits, maladaptation and residual damages.

Decision makers may face an adaptation deficit when current systems are not fully adapted to the current climate (Burton and May 2004). For example, a region facing more intense precipitation may not be well adapted to current heavy precipitation events and when pursuing say flood control actions might correct both current and future issues.

Adaptation actions by one party may cause maladaptation (Barnett and O’Neill 2010). Namely actions by one party may increase climate change vulnerability for: a) the party doing the adaptation through perhaps poor implementation, poor project choice or diverted resources; b) parties somewhere else (for example flood control in one place may worsen it elsewhere); and c) parties in the future (exploitation of depletable groundwater now may worsen adaptation possibilities in the future). Note maladaptation actions may be rational if the benefits to the adapting party outweigh the losses to the maladapted policy in real terms.

Finally, in spite of adaptation measures residual damages are likely to exist. Adaptation cannot totally overcome all climate change effects. For example, sea level rise and loss of coastal property or species extinction may be practically irreversible.

2.3 MitigationMitigation refers to a human intervention to reduce the extent of climate change by limiting climate change drivers. This mainly involves limiting greenhouse gas (GHG) emissions but can also involve geoengineering.

2.3.1 Greenhouse Gas Emissions Sources

IPCC (2014b) states that current GHG emissions mainly arise from: electricity and heat production; agricultural, forestry and other land use; and buildings; transport; and industry. Energy use is the largest contributor. Emissions from electricity and heat generation contributed 75% of the energy total followed by 16% for fuel production and transmission and 8% for petroleum refining (IEA 2012). The agricultural sector accounts for an estimated 56% of 2005 non-CO2 emissions (EPA 2011; IPCC 2014b) and 24% of total GHG emissions (IPCC, 2014b).

2.3.2 The Mitigation Imperative

The need for GHG based mitigation can be highlighted by referring to Figure 1.1.There, the different RCP (essentially representing alternative atmospheric GHG concentrations) scenarios show mitigation makes a huge difference in realized extent of climate change by the end of the century.

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2.3.3 Potential Agricultural Role

Agriculture can play a role in GHG mitigation. McCarl and Schneider (2001) indicate there are four ways agriculture can be involved. First, agriculture is a GHG emitter releasing significant amounts of methane, nitrous oxide, and CO2 (Smith et al. 2008; Smith et al. 2014) and can act to reduce those. Reductions can involve reductions in emissions from livestock, equipment, nitrogen fertilizer, rice and deforestation to mention the large ones. Second, agriculture can increase carbon stores in the ecosystem (sequestration) by using less intensive tillage, afforestation, avoiding deforestation and converting of crop lands to grass among other items. Third, agriculture could provide substitutes for GHG emission intensive products by producing biomass to replace fossil energy or using wood in construction instead of concrete block and steel. Fourth, agriculture could do little direct action but still face higher fossil fuel prices (reflective of emissions control in the energy industry) which in turn stimulates agricultural emissions reductions through substitution for fossil fuels.

2.3.4 Polices, Measures, and Instruments

Climate change is largely an economic externality brought about by market failure. Pricing and regulatory approaches can be used in an attempt to reduce the magnitude of the externality. Economists generally favor sending a price signal to emitters to cut back emissions that is reflective of the externality costs. Several means may be used to send such a signal:

Fuel taxes: one could tax fossil fuel use. Such taxes have low transaction costs and yield revenues that can be used to finance other mitigation policies (Schneider and McCarl 2005). Increased fossil fuel costs have been projected to reduce on-farm fuel usage plus increase bioenergy production (USDA 1999; Schneider and McCarl 2005);

Subsidies: one can lower existing subsidies to fossil fuel production/use or increase subsidies for alternative practices reducing emissions;

Cap-and-Trade: one can reduce GHG emissions below current levels with cap and trade schemes that allocate permits to emitters at a level below current emissions and allow them to be traded. Requiring those who want to emit more to acquire additional permits (Tietenberg, 2010). This allows high reduction cost emitters to buy emission rights from low reduction cost emitters. The initial allocation can involve schemes like an auction (Cramton, and Kerr, 2002);

Regulatory approaches towards GHG emission reductions include:

Clean Power Plan: EPA in response to a US Supreme Court ruling on controlling GHGs announced the Clean Power Plan that is aimed at reducing US electric power carbon emissions to 32 percent below 2005 levels by 2030. Implementation is up to US states and the plan mentions use of market-based mechanisms including interstate cap-and-trade programs, carbon taxes and tradable renewable certificates. The use of biomass is explicitly addressed, and states may use qualified biomass resources as a component of their state plan (EPA 2015);

Paris Climate Agreement: The key elements of the Paris Agreement are: (1) limiting the global temperature increase to 1.5 to 2 degrees C; (2) countries must employ transparent standardized accounting, monitoring and verification; (3) developed countries agreed to

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provide a $100 billion per year fund for adaptation and mitigation; (4) subsequent adaption of increasingly ambitious reduction targets. Some other notable features are:

o As of December 2015, Intended Nationally Determined Contributions (INDCs) under the Paris agreement, represent 96% of global emissions as opposed to 14% under the Kyoto Protocol (UNFCCC 2015).

o The US commitment under the Paris Agreement involves reducing GHG emissions 26-28% below 2005 level by 2025 plus a commitment of $800 million per year to the fund (US Whitehouse Press Office 2015).

o Specific mechanisms are up to individual countries. California Air Resources Board (CARB): The CARB program provides a limited number

of tradable emission permits and sets up a trading system, it contains the Low Carbon Fuel Standard (CARB 2007) which is intended to reduce carbon intensity of transportation fuel by at least 10% by 2020. For agriculture there are protocols for livestock, forestry and rice (CARB 2011);

Renewable Fuel Standard: an element of the Energy Independence and Security Act of 2007 that in implementation requires certain volumes of renewable fuel with the fuel in classes depending on their associated GHG emissions (EPA 2016).

2.3.5 Economic Appraisal of the Effects of Agricultural Mitigation Actions

A number of economic studies have examined climate change mitigation in an agricultural setting, here we review some of the important findings:

Agricultural emission reductions and offsets, e.g. agricultural soil carbon sequestration, can contribute net emission reductions at relatively low carbon prices (McCarl and Schneider 2001; Murray et al. 2005);

Agricultural soil based carbon sequestration can be competitive at low carbon prices (Murray et al. 2005). Studies have shown that the realized sequestration acreage is substantially lower than the total estimated potential and the differences narrow as carbon price increases (McCarl and Schneider 2001);

Agricultural mitigation efforts are competitive with food production. McCarl and Schneider (2001) find that there is a substantial decrease in food production and increase in food prices with higher carbon prices;

Among large potential agricultural mitigation contributions is the replacement of power plant coal fired electricity generation with biomass fueled electricity but only at carbon prices above $50 per ton. Afforestation is another large potential contribution. At low carbon prices changes in tillage and forest management dominate but these have limited potential (McCarl and Schneider 2001);

Generally the sequestration possibilities like tillage, land use change, afforestation and forest management only accumulate additional carbon for a limited amount of time and then need to be maintained(Lee, McCarl and Gillig 2005; Kim, McCarl and Murray 2008);

There are co-benefits from agricultural mitigation actions where for example sequestration activities can also create reductions in soil erosion, altered soil organic matter, increased soil water-holding capacity, increased wildlife populations, and lowered fertilizer use and chemical runoff (Murray et al. 2005). However evaluation of such co-

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benefits for a mitigation possibility implies you should also do this for wide variety of competing possibilities and may impose too large a burden (Elbakidze and McCarl 2007);

Competition with food production may reduce production increasing prices and causing emissions to increase elsewhere – called leakage (Murray, McCarl and Lee 2004);

Mitigation activity stimulated by carbon price increases generally improves producers’ welfare and decreases consumers’ welfare (McCarl and Schneider 2001);

2.3.6 Challenges in Implementing Agricultural Mitigation

Many mitigation actions can be identified however in implementing them in agriculture introduces challenges. Here we discuss a few.

One key challenge involves coverage. Agriculture has generally been regarded as a sector which will not be capped in emissions but rather as a producer of offsets (Murray et al. 2005). Rules that have emerged have generally treated agriculture on an item by item basis without coverage of many of the opportunities and with various rules concerning prior use of the practice. Some studies have shown that partial coverage say ignoring the non-CO2 possibilities causes a substantial price increase in the cost of controlling emissions (Fawcett and Sands 2006).

A second challenge involves heterogeneity and management interdependencies (McCarl and Schneider 2001). Agriculture is spatially diverse with respect to soils, climate conditions, and land management history. The three factors combined results in heterogeneous GHG mitigation potential making uniform national policies a challenge (Antle et al. 2001) but transactions cost can be a major difficulty in localizing policies (Murray et al. 2005).

Third, interdependencies of crop and livestock management actions can interact to affect the costs and the potentials for agricultural GHG mitigations in four ways: (1) many agricultural mitigation strategies compete with traditional agricultural production but some are complementary (i.e. cutting back on livestock herd size reduces methane emissions and those from feed production); (2) mitigation strategies impact one another (using land for bioenergy reduces availability for afforestation); (3) mitigation strategies can have different effects across different GHG gases (adding fertilizer increases the negative contribution through soil carbon sequestration but positively increases nitrous oxide emissions); and (4) management decisions aimed at GHG emission abatement may also impact other environmental properties such as soil erosion and nutrient leaching. As a result, it is important to simultaneously consider the suite of agricultural greenhouse gas mitigation strategies (Murray et al. 2005).

2.4 Towards Societal ActionSociety broadly observed is pursing both mitigation and adaptation. There are some elements of designing such an approach that merit discussion.

2.4.1 Mitigation and Adaptation Incentive Program Design

Programs are emerging that will fund mitigation and adaptation projects. In deciding what to fund, there are a number of issues that affect eventual project success. These include additionality, permanence, uncertainty, and leakage/maladaptation as well as transactions cost (see the review of these in a mitigation context in Murray et al (2005) and in an adaptation context in McCarl et al. (2016)). A brief overview of the listed characteristics is given below: 15

Additionality: in both contexts it is desirable to fund projects that would not have been implemented in the absence of funding. In an adaptation context there is an added meaning that the funding applied to adaptation be additional funds, not repurposed traditional development funds (see McCarl et al. (2016) for discussion).

Permanence: in the mitigation context one worries about the persistence of the carbon offset particularly for sequestered carbon which cannot be guaranteed to be permanent and may be discounted (Kim et al. 2008). Similarly in adaptation one worries about how long the adaptation will be effective and how its benefits evolve over time.

Uncertainty: in both cases one worries about the degree of uncertainty in benefits and may discount the benefits to reach a level one is confident in (see treatment in Kim and McCarl (2009).

Leakage: is mainly a mitigation context issue and arises when a project alters traditional commodities in the market place raising their price and potentially stimulating increased emissions in other regions (Murray et al. 2004).

Maladaptation: refers to cases where actions by one party reduce the adaptation of people elsewhere or in the future (see discussion in McCarl et al. 2016)

Transactions costs refer to the costs of conveying the money to those that will implement the mitigation or adaptation projects plus monitor performance. As such the evaluation at the project level may be misleading on costs and a wider set needs to be included (see mitigation related discussion in Murray et al. (2005)).

2.4.2 Mix of Adaptation and Mitigation

There is a need to simultaneously implement adaptation and mitigation. Mitigation will not prevent much climate change before mid-century but requires substantial near term effort to limit end of century climate change (IPCC 2007; 2014a; 2014b; NAS 2010). Also in some regions, policy action to reduce emissions is progressing at a slow pace while emissions growth continues worldwide. As a consequence, adaptation is needed to reduce current impacts while mitigation is needed to affect the future.

However, the optimal combination of adaptation and mitigation is a challenging problem. First, one should consider interactions between adaptation strategies and mitigation potential. For example, shifting adaptation in the form of intensification may increase sequestration loss and fertilization related emissions. Second, climate change impacts on agriculture will affect not only agricultural productivity, but also sequestration levels (Rosenzweig and Tubiello 2007).

Several studies have investigated the optimal mix of adaptation and mitigation. For example, de Bruin et al. (2009) found that adaptation dominated mitigation initially, while mitigation was predominant in later periods as did Wang and McCarl (2013). On the other hand, Bosello et al. (2010) found that mitigation started immediately while adaptation was delayed.

The discount rate is a key factor in all investment decisions including the mitigation/adaptation mix (Nordhaus 2007). Most of the benefits from current mitigation policy efforts would take the form of avoided damages many years from now, whereas many of the costs of that policy would be borne in the nearer term (Goulder and Williams 2012). Adaptation tends to be more immediate. Thus a high discount rate thus tends to reduce mitigation and favor adaptation (Wang and McCarl 2013).

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The discount rate issue has varied substantially in studies. For example, the Stern Review (2007) applied a low discount rate of 1.4% and advocated substantial mitigation. Others argued that the Review's rate was inappropriately low (Mendelsohn 2008), and Nordhaus (2007) found considerable less mitigation to be appropriate when using a higher discount rate.

3 Concluding CommentsClimate change is certainly an agricultural issue portending negative effects in some regions, positive effects in others including implications for crops, livestock, pests and their variability with a changing environment for all. Society will inevitably need to adapt plus pursue mitigation to reduce the future implications and extent of climate change. Agricultural economists will need to be well engaged in the issue looking at and evaluating vulnerability and appropriate levels of adaptation and mitigation plus in designing effective policy approaches and project evaluation procedures.

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