Download Arunanondchai, P., C.C. Fei, A.C. Fisher, B.A. McCarl, W.W. Wang

Table of Contents
1
Introduction ............................................................................................................................. 2
1.1
Recent History of Climate Change and Drivers ............................................................... 2
1.2
Projected Climate change ................................................................................................. 3
1.3 Broad Ways Climate Change Affects Agriculture.............................................................. 5
2
Issues and findings from the Literature .................................................................................. 5
2.1
Effects of Climate Change on Agriculture ....................................................................... 5
2.1.1
Crops ......................................................................................................................... 6
2.1.2
Livestock ................................................................................................................... 8
2.1.3
Regions and Land values .......................................................................................... 8
2.2
Adaptation ........................................................................................................................ 9
2.2.1
Observed adaptation actions ................................................................................... 10
2.2.2
Adaptation benefits and costs ................................................................................. 11
2.2.3
Adaptation constraints, economic barriers:............................................................. 11
2.2.4
Deficits, residual damages and maladaptation ........................................................ 12
2.3
Mitigation ....................................................................................................................... 12
2.3.1
Greenhouse Gas Emissions Sources ....................................................................... 12
2.3.2
The Mitigation Imperative ...................................................................................... 12
2.3.3
Potential Agricultural Role ..................................................................................... 13
2.3.4
Polices, Measures, and Instruments ........................................................................ 13
2.3.5
Economic Appraisal of the Effects of Agricultural Mitigation Actions ................. 14
2.3.6
Challenges in implementing agricultural Mitigation .............................................. 15
2.4
Towards Societal Action ................................................................................................ 15
2.4.1
Mitigation and Adaptation Incentive Program Design ........................................... 15
2.4.2
Mix of Adaptation and Mitigation .......................................................................... 16
3
Concluding comments .......................................................................................................... 17
4
References ............................................................................................................................. 17
1
How Does Climate Change Affect Agriculture?
Panit Arunanondchai1, Chengcheng Fei1, Anthony Fisher2, Bruce A. McCarl3, Weiwei Wang4,
Yingqian Yang1
1
Research Assistant, Department of Agricultural Economics, Texas A&M University
2
Professor, Department of Agricultural and Resource Economics, University of California,
Berkeley
3
Distinguished Professor, Department of Agricultural Economics, Texas A&M University
4
Post Doc Research Associate, Department of Agricultural and Consumer Economics,
University of Illinois at Urbana-Champaign
1 Introduction
Climate 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 Drivers
The IPCC, has devoted substantial effort to documenting the extent of climate change with the
most recent report (IPCC 2013) indicating that:



2
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;


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 Change
Climate 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).
4°
2°
Inevitable amount
Era 1
Era 2
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.
3
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
4
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 Agriculture
The 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 Literature
2.1 Effects of Climate Change on Agriculture
Climate 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
5
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 (𝐶𝑂2) 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).
7
2.1.2 Livestock
Climate 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 Values
Most 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
8
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 security
Welfare, 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 Adaptation
Adaptation 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
9
“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 Actions
A 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 Cropping
The 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 Livestock
Climate 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).
11
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 Mitigation
Mitigation 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.
12
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:


13
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


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:






14
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-


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 Action
Society 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).
16
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 Comments
Climate 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.
4 References
Adams, R.M., R.A. Fleming, C.-C. Chang, B.A. McCarl, and C. Rosenzweig. 1995. “A
Reassessment of the Economic Effects of Global Climate Change on U.S. Agriculture.”
Climatic Change 30(2):147–167.
Adams, R.M., B. McCarl, K. Segerson, C. Rosenzweig, K. Bryant, B. Dixon, R. Conner, R.
Evenson, and D. Ojima. 1999. “Economic Effects of Climate Change on US
Agriculture.” In In: Mendelsohn R, and JE Neumann (eds) The impact of climate change
on the US economy. Cambridge University Press, Cambridge, pp 18–54.
Adams, R.M., C. Rosenzweig, R.M. Peart, J.T. Ritchie, B.A. McCarl, J.D. Glyer, R.B. Curry,
J.W. Jones, K.J. Boote, and L.H. Allen. 1990. “Global Climate Change and US
Agriculture.” Nature 345(6272):219–224.
Ahmed, S.A., N.S. Diffenbaugh, and T.W. Hertel. 2009. “Climate Volatility Deepens Poverty
Vulnerability in Developing Countries.” Environmental Research Letters 4(3):034004.
Aisabokhae, R., B.A. McCarl, and Y.W. Zhang. 2011. “Agricultural Adaptation: Needs,
Findings and Effects.” In Chapter 1 in Handbook on Climate Change and Agriculture,
Edited by R Mendelsohn and A Dinar. Published by Edward Elgar, Northampton, MA, pp
327-341.
Antle, J.M., S.M. Capalbo, S. Mooney, E.T. Elliott, and K.H. Paustian. 2001. “Economic
Analysis of Agricultural Soil Carbon Sequestration: An Integrated Assessment
Approach.” Journal of Agricultural and Resource Economics 26(2):344–367.
Arrow, K.J., M.L. Cropper, C. Gollier, B. Groom, G.M. Heal, R.G. Newell, W.D. Nordhaus,
R.S. Pindyck, W.A. Pizer, P.R. Portney, T. Sterner, R.S.J. Tol, and M.L. Weitzman.
2014. “Should Governments Use a Declining Discount Rate in Project Analysis?” Review
of Environmental Economics and Policy 8(2):145–163.
17
Attavanich, W., and B.A. McCarl. 2014. “How is CO2 Affecting Yields and Technological
Progress? A Statistical Analysis.” Climatic Change 124(4):747–762.
Attavanich, W., B.A. McCarl, Z. Ahmedov, S.W. Fuller, and D.V. Vedenov. 2013. “Effects of
Climate Change on US Grain Transport.” Nature Climate Change 3(7):638–643.
Baldos, U.L.C., and T.W. Hertel. 2014. “Global Food Security in 2050: the Role of Agricultural
Productivity and Climate Change.” Australian Journal of Agricultural and Resource
Economics 58(4):554–570.
Barnett, J., and S. O’Neill. 2010. “Maladaptation.” Global Environmental Change 20(2):211–
213.
Bosello, F., C. Carraro, and E. De Cian. 2010. “Climate Policy and the Optimal Balance
Between Mitigation, Adaptation and Unavoided Damage.” Climate Change Economics
01(02):71–92.
de Bruin, K.C., R.B. Dellink, and R.S.J. Tol. 2009. “AD-DICE: An Implementation of
Adaptation in the DICE Model.” Climatic Change 95(1-2):63–81.
Burton, I., and E. May. 2004. “The Adaptation Deficit in Water Resource Management.” IDS
Bulletin 35(3):31–37.
Butt, T.A., B.A. McCarl, J. Angerer, P.T. Dyke, and J.W. Stuth. 2005. “The Economic and Food
Security Implications of Climate Change in Mali.” Climatic Change 68(3):355–378.
Butt, T.A., B.A. McCarl, and A.O. Kergna. 2006. “Policies for Reducing Agricultural Sector
Vulnerability to Climate Change in Mali.” Climate Policy 5(6):583–598.
California Air Resources Board (CARB). 2011. Compliance Offset Program. Available at:
http://www.arb.ca.gov/cc/capandtrade/offsets/offsets.htm. (Accessed July 27, 2016).
California Air Resources Board (CARB). 2007. “Low Carbon Fuel Standard.” Available at:
http://www.arb.ca.gov/fuels/lcfs/lcfs.htm.( Accessed July 27, 2016).
Chen, C.C., and B.A. McCarl. 2001. “An Investigation of the Relationship Between Pesticide
Usage and Climate Change.” Climatic Change 50(4):475–487.
Chen, C.C., and B.A. McCarl. 2009. “Hurricanes and Possible Intensity Increases: Effects on and
Reactions From US Agriculture.” Journal of Agricultural and Applied Economics
41:125–144.
Chen, C.C., B.A. McCarl, and R.M. Adams. 2001. “Economic Implications of Potential ENSO
Frequency and Strength Shifts.” 49(1):147–159.
Chen, C.C., B.A. McCarl, and C.C. Chang. 2012. “Climate Change, Sea Level Rise and Rice:
Global Market Implications.” Climatic Change 110(3-4):543–560.
18
Cho, S. 2015. Three Essays on Climate Change Adaptation and Impacts: Econometric
Investigations. Doctoral Dissertation, Texas A&M University.
Cline, W.R. 1992. The economics of global warming. Washington, DC: Institute for International
Economics.
Craine, J.M., A.J. Elmore, K.C. Olson, and D. Tolleson. 2010. “Climate Change and Cattle
Nutritional Stress.” Global Change Biology 16(10):2901–2911.
Cramton, P. and S. Kerr (2002), “Tradeable carbon permit auctions: How and why to auction
not grandfather”, Energy Policy 30(4): 333–345.
Elbakidze, L., and B.A. McCarl. 2007. “Sequestration Offsets Versus Direct Emission
Reductions: Consideration of Environmental Co-effects.” Ecological Economics
60(3):564–571.
EPA. 2013. Climate Change Indicators in the United States: Length of Growing Season.
Available at: www.epa.gov/climatechange/indicators. (Accessed July 27, 2016).
EPA. 2011. Draft: Global Anthropogenic Non-CO_2 Greenhouse Gas Emissions: 1990-2030.
Available at:
https://www3.epa.gov/climatechange/Downloads/EPAactivities/EPA_NonCO2_Projectio
ns_2011_draft.pdf. (Accessed July 27, 2016).
EPA. 2015. Fact Sheet: Overview of the Clean Power Plan. Available at:
https://www.epa.gov/cleanpowerplan/fact-sheet-overview-clean-power-plan. (Accessed
July 27, 2016).
EPA. 2016. The Renewable Fuel Standard. Available at: https://www.epa.gov/renewable-fuelstandard-program. (Accessed July 27, 2016).
Fawcett, A.A., and R.D. Sands. 2006. “Non-CO2 Greenhouse Gases in the Second Generation
Model.” The Energy Journal SI2006(01):305–322.
Feng, S., B.A. McCarl, and P. Havlik. 2011. “Crop Yield Growth and Its Implication for the
International Effects of US Bioenergy and Climate Policies.” Paper presented at the 2011
Agricultural & Applied Economics Association (AAEA) Annual Meeting, Pittsburgh,
Pennsylvania.
Fisher, A.C., and P.V. Le. 2014. “Climate Policy: Science, Economics, and Extremes.” Review of
Environmental Economics and Policy 8(2):307–327.
Gale, P., T. Drew, L.P. Phipps, G. David, and M. Wooldridge. 2009. “The Effect of Climate
Change on the Occurrence and Prevalence of Livestock Diseases in Great Britain: a
Review.” Journal of Applied Microbiology 106(5):1409–1423.
Gaughan, J., N. Lacetera, S.E. Valtorta, H.H. Khalifa, L. Hahn, and T. Mader. 2009. “Response
of Domestic Animals to Climate Challenges.” In K. L. Ebi, I. Burton, and G. R.
19
McGregor, eds. Biometeorology for Adaptation to Climate Variability and Change.
Dordrecht: Springer Netherlands, pp. 131–170. Available at:
http://link.springer.com/10.1007/978-1-4020-8921-3_7 (Accessed July 27, 2016).
German Climate Computing Center (DKRZ). 2014. “Laboratory for Climate Researchers.”
Available at: http://www.dkrz.de/Klimaforschung-en/konsortial-en/ipccar5/ergebnisse/Mitteltemperatur-en (accessed July 27, 2016).
Goulder, L.H., and R.C. Williams. 2012. “The Choice of Discount Rate for Climate Change
Policy Evaluation.” Climate Change Economics 03(04):1250024.
Hatfield, J., G. Takle, P. Holden, R.C. Izaurralde, T. Mader, E. Marshall, and D. Liverman. 2014.
“Agriculture. Climate Change Impacts in the United States.” In Chapter Ch. 6 in The
Third National Climate Assessment, JM. Melillo, TC Richmond, and GW. Yohe, Eds. U.S.
Global Change Research Program, 150-174.
Heal, G. 2008. “Climate Economics: A Meta-Review and Some Suggestions for Future
Research.” Review of Environmental Economics and Policy 3(1):4–21.
Howden, S.M., S.J. Crimp, and C.J. Stokes. 2008. “Climate Change and Australian Livestock
Systems: Impacts, Research and Policy Issues.” Australian Journal of Experimental
Agriculture 48(7):780.
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 104(50):19691–19696.
International Energy Agency(IEA). 2012. “CO2 Emission from Fuel Combustion.” In OECD,
Pairs, France. Available at: http://www.oecdilibrary.org/docserver/download/6112181e.pdf?expires=1469659529&id=id&accname=o
cid76019061&checksum=6B7655E61C4F389860D7B0FFFD5E28C6. (Accessed July
27, 2016).
IPCC. 2007. Climate Change 2007: Mitigation of Climate Change. Cambridge, UK: Cambridge
University Press.
IPCC. 2013. Climate Change 2013: The Physical Science Basis. Cambridge University Press,
Cambridge, United Kingdom and New York, NY, USA.
IPCC. 2014a. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Cambridge
University Press, Cambridge, New York, NY.
IPCC. 2014b. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II to
the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Geneva,
Switzerland.
Joughin, I., B.E. Smith, and B. Medley. 2014. “Marine Ice Sheet Collapse Potentially Under
Way for the Thwaites Glacier Basin, West Antarctica.” Science 344(6185):735–738.
20
Joyce, L.A., D.D. Briske, J.R. Brown, H.W. Polley, B.A. McCarl, and D.W. Bailey. 2013.
“Climate Change and North American Rangelands: Assessment of Mitigation and
Adaptation Strategies.” Rangeland Ecology & Management 66(5):512–528.
Khan, S.A., K.H. Kjær, M. Bevis, J.L. Bamber, J. Wahr, K.K. Kjeldsen, Anders A. Bjørk, Niels
J. Korsgaard, L.A. Stearns, M.R. van den Broeke, L. Liu, N.K. Larsen, and I.S. Muresan.
2014. “Sustained Mass Loss Of The northeast Greenland Ice Sheet Triggered By
Regional Warming.” Nature Climate Change 4(4):292–299.
Kim, M.-K., and B.A. McCarl. 2009. “Uncertainty Discounting for Land-Based Carbon
Sequestration.” Journal of Agricultural and Applied Economics 41(01):1–11.
Kim, M.-K., B.A. McCarl, and B.C. Murray. 2008. “Permanence Discounting For Land-based
Carbon Sequestration.” Ecological Economics 64(4):763–769.
Knutti, R., and J. Sedláček. 2012. “Robustness and Uncertainties In The New CMIP5 Climate
Model Projections.” Nature Climate Change 3(4):369–373.
Lee, H.-C., B.A. McCarl, and D. Gillig. 2005. “The Dynamic Competitiveness of U.S.
Agricultural and Forest Carbon Sequestration.” Canadian Journal of Agricultural
Economics 53(4):343–357.
Lobell, D.B., M.B. Burke, C. Tebaldi, M.D. Mastrandrea, W.P. Falcon, and R.L. Naylor. 2008.
“Prioritizing Climate Change Adaptation Needs for Food Security in 2030.” Science
319(5863):607–610.
Mader, T.L. 2014. “Animal Welfare Concerns for Cattle Exposed to Adverse Environmental
Conditions.” Journal of Animal Science 92(12):5319–5324.
Mader, T.L., K.L. Frank, J.A. Harrington, G.L. Hahn, and J.A. Nienaber. 2009. “Potential
Climate Change Effects on Warm-Season Livestock Production in the Great Plains.”
Climatic Change 97(3-4):529–541.
Malcolm, S., E. Marshall, M. Aillery, P. Heisey, M. Livingston, and K. Day-Rubenstein. 2012.
“Agricultural Adaptation to a Changing Climate: Economic and Environmental Impacts
Vary by U.S. Region.” In U.S. Department of Agriculture, Economic Research Service.
Economic Research Report No. 136. July.
McCarl, B.A. 2007. “Adaptation Options for Agriculture, Forestry and Fisheries. A Report to the
UNFCCC Secretariat Financial and Technical Support Division.” Available at:
https://unfccc.int/files/cooperation_and_support/financial_mechanism/application/pdf/mc
carl.pdf. Accessed July 27, 2016.
McCarl, B.A. 2015. “Elaborations on climate adaptation in US agriculture.” Choices 30(2).
McCarl, B.A., and U.A. Schneider. 2001. “Climate Change: Greenhouse Gas Mitigation in U.S.
Agriculture and Forestry.” Science 294(5551):2481–2482.
21
McCarl, B.A., A. Thayer, and J.P. Jones. 2016. “The Challenge of Climate Change Adaptation:
An Economically Oriented Review.” Journal of Agricultural and Applied Economics
Forthcoming.
McCarl, B.A., X. Villavicencio, and X. Wu. 2008. “Climate Change and Future Analysis: Is
Stationarity Dying?” American Journal of Agricultural Economics 90(5):1241–1247.
Mendelsohn, R. 2008. “Is the Stern Review an Economic Analysis?” Review of Environmental
Economics and Policy 2(1):45–60.
Mendelsohn, R., and A. Dinar. 1999. “Climate Change, Agriculture, and Developing Countries:
Does Adaptation Matter?” The World Bank Research Observer 14(2):277–293.
Mendelsohn, R., W.D. Nordhaus, and D. Shaw. 1994. “The Impact of Global Warming on
Agriculture: A Ricardian Analysis.” The American Economic Review 84(4):753–771.
Mu, J.E., B.A. McCarl, and A.M. Wein. 2013. “Adaptation to Climate Change: Changes in
Farmland Use and Stocking Rate in the U.S.” Mitigation and Adaptation Strategies for
Global Change 18(6):713–730.
Mu, J., B.A. McCarl, X. Wu, and M.P. Ward. 2014. “Climate Change and the Risk of Highly
Pathogenic Avian Influenza Outbreaks in Birds.” British Journal of Environment and
Climate Change 4(2):166–185.
Murray, B.C., B.A. McCarl, and H.-C. Lee. 2004. “Estimating Leakage from Forest Carbon
Sequestration Programs.” Land Economics 80(1):109.
Murray, B., B. Sohngen, A. Sommer, B. Depro, K. Jones, B.A. McCarl, D. Gillig, B. de Angelo,
and K. Andrasko. 2005. “Greenhouse Gas Mitigation Potential in US Forestry and
Agriculture.” In EPA Report 430-R-05-006, November.
NAS. 2010. America’s Climate Choices: Advancing the Science of Climate Change. Chaired by
PA Matson, National Academy of Sciences, Washington, D.C.
NOAA. 2016. The NOAA Annual Greenhouse Gas Index (AGGI). Earth System Research
Laboratory. Available at: http://esrl.noaa.gov/gmd/aggi/aggi.html. (Accessed July 27,
2016).
Nordhaus, W.D. 2007. “A Review of the Stern Review on the Economics of Climate Change.”
Journal of Economic Literature XLV:686–702.
Park, J., B.A. McCarl, and X. Wu. 2016. The Effects of Climate on Crop Mix and Climate
Change Adaptation. Unpublished, Texas A&M University.
Parry, M., N. Arnell, P. Berry, D. Dodman, and S. Fankhauser eds. 2009. Assessing the Costs of
Adaption to Climate Change: a Review of the UNFCCC and Other Recent Estimates.
London: International institute for environment and development (IIED).
22
Peterson, T.C., R.R. Heim, R. Hirsch, D.P. Kaiser, H. Brooks, N.S. Diffenbaugh, R.M. Dole, J.P.
Giovannettone, K. Guirguis, T.R. Karl, R.W. Katz, K. Kunkel, D. Lettenmaier, G.J.
McCabe, C.J. Paciorek, K.R. Ryberg, S. Schubert, V.B.S. Silva, B.C. Stewart, A.V.
Vecchia, G. Villarini, R.S. Vose, J. Walsh, M. Wehner, D. Wolock, K. Wolter, C.A.
Woodhouse, and D. Wuebbles. 2013. “Monitoring and Understanding Changes in Heat
Waves, Cold Waves, Floods, and Droughts in the United States: State of Knowledge.”
Bulletin of the American Meteorological Society 94(6):821–834.
Poore, R.Z., R.S.J. Williams, and C. Tracey. 2000. “Sea Level and Climate: U.S. Geological
Survey Fact Sheet 002–00.” Available at: http://pubs.usgs.gov/fs/fs2-00/.(Accessed July
27, 2016).
Porter, J.R., and M.A. Semenov. 2005. “Crop Responses to Climatic Variation.” Philosophical
Transactions of the Royal Society B: Biological Sciences 360(1463):2021–2035.
Porter, J.R., L. Xie, A.J. Challinor, K. Cochrane, S.M. Howden, M.M. Iqbal, D.B. Lobell, and
M.I. Travasso. 2014. “Food security and food production systems.” In : IPCC 2014 a
Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and
Sectoral Aspects. Cambridge University Press, Cambridge, United Kingdom and New
York, NY, USA, pp. 485-533.
Reilly, J.M., J. Hrubovcak, J. Graham, D.G. Abler, R. Darwin, S.E. Hollinger, R.C. Izaurralde, S.
Jagtap, J.W. Jones, J. Kimble, B.A. McCarl, L.O. Mearns, D.S. Ojima, E.A. Paul, K.
Paustian, S. J. Riha, N.J. Rosenberg, C. Rosenzweig, and F.N. Tubiello. 2002. “Changing
Climate and Changing Agriculture: Report of the Agricultural Sector Assessment Team,
US National Assessment,.” Part of USGCRP National Assessment of Climate Variability.
Cambridge University Press.
Rosenzweig, C., and F.N. Tubiello. 2007. “Adaptation and Mitigation Strategies in Agriculture:
An Analysis of Potential Synergies.” Mitigation and Adaptation Strategies for Global
Change 12(5):855–873.
Sacks, W.J., and C.J. Kucharik. 2011. “Crop Management and Phenology Trends in the U.S.
Corn Belt: Impacts on Yields, Evapotranspiration and Energy Balance.” Agricultural and
Forest Meteorology 151(7):882–894.
Schlenker, W., W.M. Hanemann, and A.C. Fisher. 2006. “The Impact of Global Warming on
U.S. Agriculture: An Econometric Analysis of Optimal Growing Conditions.” Review of
Economics and Statistics 88(1):113–125.
Schlenker, W., W.M. Hanemann, and A.C. Fisher. 2007. “Water Availability, Degree Days, and
the Potential Impact of Climate Change on Irrigated Agriculture in California.” Climatic
Change 81(1):19–38.
Schlenker, W., W.M. Hanemann, and A.C. Fisher. 2005. “Will U.S. Agriculture Really Benefit
from Global Warming? Accounting for Irrigation in the Hedonic Approach.” American
Economic Review, 95(1):395–406.
23
Schlenker, W., and M.J. Roberts. 2009. “Nonlinear Temperature Effects Indicate Severe
Damages to U.S. Crop Yields under Climate Change.” Proceedings of the National
Academy of Sciences 106(37):15594–15598.
Schneider, U.A., and B.A. McCarl. 2005. “Implications of a Carbon Based Energy Tax for US
Agriculture.” Agricultural and Resource Economics Review 34:265–279.
Seo, S.N., and R. Mendelsohn. 2008. “Measuring Impacts and Adaptations to Climate Change: A
Structural Ricardian Model of African Livestock Management.” Agricultural Economics
38(2):151–165.
Shakhova, N., I. Semiletov, I. Leifer, V. Sergienko, A. Salyuk, D. Kosmach, D. Chernykh, C.
Stubbs, D. Nicolsky, V. Tumskoy, and Ö. Gustafsson. 2013. “Ebullition and StormInduced Methane Release From The East Siberian Arctic Shelf.” Nature Geoscience
7(1):64–70.
Shakhramanyan, N.G., U.A. Schneider, and B.A. McCarl. 2013. “US Agricultural Sector
Analysis on Pesticide Externalities – the Impact of Climate Change and a Pigovian Tax.”
Climatic Change 117(4):711–723.
Smith, P., D. Martino, Z. Cai, D. Gwary, H. Janzen, P. Kumar, B. McCarl, S. Ogle, F. O’Mara,
C. Rice, B. Scholes, O. Sirotenko, M. Howden, T. McAllister, G. Pan, V. Romanenkov,
U. Schneider, S. Towprayoon, M. Wattenbach, and J. Smith. 2008. “Greenhouse Gas
Mitigation in Agriculture.” Philosophical Transactions of the Royal Society B: Biological
Sciences 363(1492):789–813.
Smith, P., M Bustamante, H. Ahammad, H. Clark, H. Dong, E.A. Elsiddig, H. Haberl, R. Harper,
J. House, M. Jafari, O. Masera, C. Mbow, N.H. Ravindranath, C.W. Rice, R. Abad, A.
Romanovskaya, F. Sperling, and F.N. Tubiello. 2014. “Agriculture, Forestry and Other
Land Use (AFOLU).” In Chapter 11 in IPCC, 2014: Climate change 2014: Mitigation of
Climate Change. Cambridge Press, NY.
Stern, N. 2007. The Economics of Climate Change: The Stern Review. Cambridge and New
York: Cambridge University Press.
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.
Tietenberg, T., 2010. “Cap-and-Trade: the Evolution of an Economic Idea” Agricultural and
Resource Economics Review 39(3):359-367
United Nations Environment Program. 2012. Policy implications of warming permafrost.
Nairobi, Kenya: United Nations Environment Program.
United Nations Framework Convention on Climate Change(UNFCCC). 2007. Investment and
Financial Flows to Address Climate Change. Available at:
http://unfccc.int/resource/docs/publications/financial_flows.pdf.(Accessed July 27, 2016).
24
United Nations Framework Convention on Climate Change (UNFCCC). 2015. Paris Climate
Agreement. Available at: http://unfccc.int/paris_agreement/items/9485.php.(Accessed
July 27, 2016).
United States Department of Agriculture (USDA). 1999. Economic Analysis of U.S.
Agriculture and the Kyoto Protocol. Office of The Chief Economist, Global Change
Program Office.
US Whitehouse Press Office. 2015. Fact Sheet: U.S. Reports its 2025 Emissions Target to the
UNFCCC. Available at: https://www.whitehouse.gov/the-press-office/2015/03/31/factsheet-us-reports-its-2025-emissions-target-unfccc. (Accessed July 27, 2016).
Villavicencio, X., B.A. McCarl, X. Wu, and W.E. Huffman. 2013. “Climate Change Influences
On Agricultural Research Productivity.” Climatic Change 119(3-4):815–824.
Wang, W., and B.A. McCarl. 2013. “Temporal Investment in Climate Change Adaptation and
Mitigation.” Climate Change Economics 04(02):1350009.
Whiteman, G., C. Hope, and P. Wadhams. 2013. “Climate science: Vast costs of Arctic change.”
Nature 499(7459):401–403.
Yu, T., and B.A. Babcock. 2010. “Are U.S. Corn and Soybeans Becoming More Drought
Tolerant?” American Journal of Agricultural Economics 92(5):1310–1323.
Zhang, Y.W., A.D. Hagerman, and B.A. McCarl. 2013. “Influence of Climate Factors on Spatial
Distribution of Texas Cattle Breeds.” Climatic Change 118(2):183–195.
25