The U.S. food system (described in Chapter 2) is widely recognized to have direct and indirect effects on the environment. The degree to which each sector of the food system affects the environment depends on a variety of natural and human-driven processes. For example, increased use of mineral fertilizers is responsible for much of the growth in productivity in U.S. agriculture over the past 50 years, but it also has led to negative impacts on the environment, such as greater greenhouse gas (GHG) emissions and deterioration of water quality. GHG emissions also can result from the burning of fossil fuels in the food manufacturing process and during food distribution.
The ongoing intensification of agricultural production1 has had particularly notable effects on the environment. According to the 2012 Agricultural Census, 2.1 million farms and ranches operate in the United States, of which two-thirds sell less than $25,000 worth of livestock or crops. In contrast, large farms (about 80,000 of them) represent only 4 percent of the total farm population but are responsible for two-thirds of the agricultural production in the United States today (USDA, 2014b). Intensive agricultural production has become highly efficient, which reduces costs per unit of product (thus, likely reducing costs to consumers) and can alter environmental impacts per unit of product. For example, Capper et al. (2009) showed historic advances in dairy production, where 2007 cows produced
1 There are a variety of definitions of agricultural intensification but they all refer to increasing agricultural inputs to improve productivity or yields of a fixed land area rather than expanding land under cultivation.
43 percent less methane and 56 percent less nitrous oxide per 1 billion kilograms of milk than did 1944 cows. Similar trends have been described for the beef sector (Capper, 2011), where the number of cattle was reduced by 40 percent over this time span, but the total amount of beef produced remained the same (USDA, 2014b). On the other hand, large concentrations of livestock (concentrated animal feeding operations,2 or CAFOs) can lead to regional air and water quality issues if the animal waste is not properly managed. CAFOs can cause nuisance and health issues for neighboring communities—including dust, odors, flies, and gaseous emissions—and therefore often face public scrutiny. In addition, runoff from CAFOs can create food safety problems by contaminating water or downstream agriculture fields with pathogens. Increasingly, livestock CAFOs attempt to counteract these challenges by collecting manure from the animal housing and placing it into treatment facilities like composters or anaerobic digesters, which can convert waste to energy.
The impact of contaminated surface or groundwater from excessive nitrogen fertilizer applications, in both inorganic and organic forms, may affect a local community over a short period of time, or decades later, sometimes miles from the initial nutrient inputs. The impact within a community also may be disparate, as disadvantaged portions of the community may not have the resources to ensure a safe drinking water source. (Health effects related to environmental contaminants and their differential effects on the general population are discussed in Chapters 3 and 5, respectively.) Although the U.S. food system’s impacts on the environment are often undesirable, the current system can provide environmental benefits as well (see Figure 4-1 for examples). Benefits such as carbon sequestration, biodiversity conservation, aesthetically pleasing landscapes, and sustained food and fiber production can all be realized, particularly when an ecological approach is used by agricultural producers (Robertson and Swinton, 2005; Swinton et al., 2007; Zhang et al., 2007). An ecological approach requires actors to recognize not only how management choices affect the environment, both temporally and spatially but also how managing the system for multiple ecosystem services3 can often result in significant mitigation of these impacts, acknowledging also that trade-offs are inevitable (Robertson and Swinton, 2005).
Agricultural producers are chiefly in business to produce food, fiber, and fuel products for sale, but most also place a high value on ecosys-
2 CAFOs are agricultural enterprises where animals are raised in a confined, small land area and feed is brought to the animals. The Environmental Protection Agency has delineated three categories of CAFOs, ordered in terms of capacity: large, medium, and small. The relevant animal unit for each category varies depending on species and capacity.
3 Ecosystem services are any positive benefit that wildlife or ecosystems provides to people. The benefits can be direct or indirect, small or large.
FIGURE 4-1 Examples of ecosystem services to and from agriculture.
SOURCE: Swinton et al., 2007. Reprinted with permission.
tem services from their farms, especially those that offer private benefits (e.g., enhanced soil fertility and organic matter). However, many producers believe ecosystem services that offer distant benefits (e.g., climate or water quality regulation) are costly to provide without financial incentives and technical resources (Ma et al., 2012; Smith and Sullivan, 2014). Understanding how actors in the food system make decisions is important when assessing the environmental impacts of the system.
Broadly, the U.S. food system’s environmental effects can be grouped into three categories: (1) environmental contaminants/pollutants, (2) depletion and replenishment of natural resources, and (3) population and community disruption. In this chapter, each of these broad effects categories is described briefly, highlighting the major environmental features and mechanisms of each category. The chapter further discusses the dynamic nature of environmental effects, including the importance of understanding how human behavior influences direct and indirect, and positive and negative, impacts on the environment. The chapter concludes with a basic overview of the various approaches used to quantify the performance of a dynamic environmental system, including direct measurement, the use of indicators, and simulation modeling. A comprehensive list of environmental data sources, metrics, and models commonly employed to quantify environmental impacts is included in Tables B-1 through B-4 of Appendix B.
CATEGORIES OF POTENTIAL ENVIRONMENTAL EFFECTS AND ASSOCIATED MECHANISMS
Environmental Contaminants and Pollutants
The U.S. food system has seen a substantial increase in product output over the past 50 years. Although more food is produced than ever, the current system also leads to unintended environmental consequences depicted in the pollution life cycle shown in Figure 4-2. Contaminants are emitted into the environment, are transported and/or transformed, and eventually are deposited in a location where they may negatively affect human and ecosystem health. These negative effects on human and ecosystem health are most often dealt with through the implementation of regulations to reduce or eliminate emissions of the contaminant.
A considerable amount of effort by the scientific community has gone into determining the identity, fate, and transport paths of environmental contaminants associated with the various components of the U.S. food and agriculture system. These contaminants include nutrients (i.e., nitrogen and phosphorus), pesticides, pharmaceuticals, pathogens, gases and inhalants (i.e., ammonia, nitrogen oxide, methane, odors, and fine particulate matter, or PM), and soil sediment (including the chemicals and organisms it may contain). When a contaminant reaches pollutant levels, it leads to the
FIGURE 4-2 The pollution life cycle. Regulations at various levels (federal, state, and local) address negative impacts to human and ecosystem health.
degradation of water, soil, air, or habitat and to potential consequences on human health. For example, nutrient-laden runoff can lead to eutrophication4 of downstream waters (EPA, 2011), excessive GHG emissions can contribute to global warming (EPA, 2013), and pesticides transported in runoff or in groundwater recharge can result in toxicity to humans, aquatic life, and wildlife (Gilliom et al., 2006). The extent to which these contaminants result in environmental degradation depends on a number of factors, including but not limited to contaminant concentration, timing of exposure, extent of biodegradation and bioaccumulation, and the frequency of exposure. The following discussion focuses on the major classes of contaminants (nutrients, pesticides, sediment, and pathogens) and the mechanisms leading to environmental contamination. An extensive discussion of nitrogen as a nutrient contaminant and pollutant in agricultural production can be found in Annex 4 of Chapter 7.
Agricultural activities in the United States contribute significantly to the release of numerous air quality and climate change-related emissions, especially those of ammonia (agriculture contributes to ~90 percent of total U.S. emissions), reduced sulfur (unquantified), PM2.55 (~16 percent), PM10 (~18 percent), methane (~29 percent), and nitrous oxide (72 percent) (Aneja et al., 2009). Once these materials are released into the air, they can undergo various transformational steps (Aneja et al., 2001). For example, a large percentage of ammonia is deposited near its source. However, ammonia can readily transform into ammonium, which can be transported over greater distances from the source. As the most prevalent base found in the atmosphere, ammonia can also readily react with acidic nitrogen and sulfur species, forming fine particulate matter (i.e., PM2.5). Carbon molecules also can transform from one form to another. For example, volatile organic compounds6 (VOCs), which are produced during fermentation and decomposition of organic materials as well as during combustion of fossil fuels, contribute to ozone formation when combined with oxides of nitrogen (NOx) and sunlight (Shaw et al., 2007). Ozone can form smog, which constitutes one of the most pressing air quality issues in parts of the United States, such as California. Some VOCs also cause health effects such as eye, nose, and throat irritation (EPA, 2014).
Figure 4-3 shows an example of how primary (e.g., ammonia) and secondary (e.g., fine particulate matter, PM2.5) air emissions are most often transported by wind and eventually undergo dry or wet deposition. These
4 Eutrophicaton is excessive plant and algal growth due to the increased availability of one or more limiting growth factors needed for photosynthesis, such as sunlight, carbon dioxide, and nutrient fertilizers.
5 PM2.5 refers to particulate matter less than 2.5 μm in diameter.
6 Volatile organic compounds are gases from certain solids or liquids that include a variety of chemicals, some of which may have short- and long-term adverse health effects.
FIGURE 4-3 Atmospheric emissions, transport/transformation, and deposition.
SOURCE: Reprinted by permission from Macmillan Publishers Ltd.: Aneja, V. P., W. H. Schlesinger, and J. W. Erisman. 2008. Farming pollution. Nature Geoscience 1(7):409-411.
can affect both ecosystem (e.g., eutrophication, acidification) and human health (e.g., respiratory conditions).
Water pollution occurs when pollutants are leached through the soil and the unsaturated zone above the water table into the aquifer (groundwater), or when surface water quality is impaired due to runoff or drainage discharge from agricultural land. Major issues related to water quality in agricultural production focus on nitrogen, phosphorus, salinity, and pathogen occurrence. Nitrogen and phosphorus are the principal nutrient pollutants of major concern regarding water quality. Ammonia from manure or other nitrogen forms contained in chemical fertilizers undergoes nitrification in the soil leading to nitrate formation. Nitrate is readily taken up by crops, but if applications are beyond the need of the plant (i.e., agronomic rates), excess will leach into the groundwater (see also Chapter 7, Annex 4). Phosphorus, on the other hand, generally binds to soil particles, and most pollution to water bodies occurs due to soil erosion and direct runoff of soluble reactive phosphate from fields.
Even though the United States has one of the safest food supplies globally, millions of cases of human foodborne illnesses still occur (see Chapter 3). Animal agriculture is a considerable source of microorganisms, some of which are pathogens, including bacteria such as Salmonella, Escherichia coli O157:H7, and Campylobacter. Other pathogens of major importance are Norovirus, Clostridia, and Staphylococcus. Concentrated animal feeding operations, grazing lands, and lands receiving animal waste are all potential sources of pathogens to waterways and agricultural products. Pathogen contamination of manure can lead to foodborne diseases in people when waste is applied as fertilizers to crops and the produce is not washed appropriately before consumption. For example, a large E. coli O157:H7 outbreak in 2006 was associated with contaminated spinach. Similarly, manure has the potential to contaminate meat at the packing plant, which can potentially lead to foodborne illnesses in people, particularly if meat is undercooked.
The advent of synthetic pesticides, much like the rise of synthetic fertilizer use, led to significant increases in crop yields through the protection of crops from destructive pests. Pesticides are predominately used to protect crops from yield reductions resulting from insect damage and competition from weeds. The annual amount of pesticide active ingredients used by the agricultural sector from 1988 to 2007 (shown in Figure 4-4) has remained relatively unchanged except for minor increases and decreases in the specific use of certain pesticide types.
Although agricultural pesticide use has allowed for increased production of food and fiber at a lower cost, widespread use of pesticides in a variety of crops increases the likelihood of negative impacts on the environment.
Pesticides and associated breakdown products are readily mobilized through air, water, and sediment pathways, resulting in the potential exposure of non-target organisms, including humans, to acute and/or chronic toxicity conditions. Depending on a pesticide’s properties, the environmental conditions during and after application, and the management practices used by a farmer, a pesticide or its breakdown products can be: carried in drift during application, in dust created by wind or tillage activities, in surface runoff during irrigation or rainfall, or in sediment carried by runoff; leached through the soil into groundwater; or volatized into the air and deposited onto surfaces near or a considerable distance from the application site. A 2007 U.S. Geological Survey (USGS) assessment reported
FIGURE 4-4 Annual amount of pesticide active ingredient used in the United States by pesticide type, 1988-2007 Estimates Agricultural Market Sector.
SOURCE: Grube et al., 2011.
the detection of pesticide compounds in streams of developed watersheds more than 90 percent of the time (Gilliom, 2007). In agricultural areas of the United States where sampling was conducted, pesticides were detected in 97 percent of samples in streams and 61 percent of samples in shallow groundwater areas. Additionally, organochlorine compounds, the majority of which are no longer used and which are considered “legacy” pesticides, were detected in 92 percent of fish tissue samples and 57 percent of aquatic bed sediment samples.
Because ecosystems are generally exposed to mixtures of pesticide compounds and their degradation products at varying concentrations, assessing environmental toxicity can be difficult, especially if only a single pesticide is evaluated (Gilliom, 2007). The issue is further complicated by toxicity arising from the use of currently registered pesticides and those used historically but with long half-lives, such as organochlorines. In addition, as a result of the lack of a comprehensive pesticide use database, except in certain states such as California, studies evaluating pesticide risk to the environment and human health are limited. Researchers in California studying pesticide risk in almond production were able to overcome this limitation by using the Pesticide Use Reporting (PUR) database and a Pesticide Use Risk Evaluation (PURE) indicator to assess the risks of pesticide use to air, water, and soil (Zhan and Zhang, 2012, 2014). The spatial and temporal data contained within PUR combined with the use of the PURE indicator demonstrated a shift to more environmentally friendly insect control measures, such as the use of oils and Bacillus thuringiensis (Bt) instead of less
water-quality-friendly organophosphate compounds, while also revealing an increasing use of herbicides possibly linked to herbicide resistance (Zhan and Zhang, 2014).
The type and the amount of pesticides used by the U.S. food system are driven by a number of different forces. These forces include food marketing standards and consumer demands, varying pest pressure, real and perceived human health issues through both worker and consumer exposure, detection of pesticide or breakdown compounds in various environmental media (especially water), and increased use of crops with both natural and engineered (i.e., transgenic) resistance to pests. For example, aquatic toxicity and human health concerns attributed to chlorpyrifos and diazinon resulted in a shift away from these organophosphate insecticides to pyrethroid insecticides, which are less water soluble and have lower mammalian toxicity characteristics (Anderson et al., 2003; Bradman et al., 2011; Fenske et al., 2005; Hunt et al., 2003; Loewenherz et al., 1997). See Chapter 5 for a discussion on exposure effects on farmers and farm workers. Although this shift has reduced the impact of organophosphates on water quality and human health toxicity, a significant body of literature now exists demonstrating increased detections and aquatic toxicity of pyrethroids in the sediment downstream of agricultural lands, including in marine receiving waters (Amweg et al., 2005; Anderson et al., 2014; Ding et al., 2010; Domagalski et al., 2010; Weston et al., 2013). Pesticide use in response to pest outbreaks is always variable due to shifting environmental conditions, presence of host plants, and population of natural predators, but use may be more significant in response to invasive pests, especially where existing natural biological control organisms are inadequate or unable to control the pest. The detection of the soybean aphid, Aphis glycines Matsumura, in the United States in 2000 is an example of an outbreak of an invasive pest on an economically important crop that resulted in a significant increase in pesticide use where previously little pesticide was required. Chemical treatment for soybean aphid consists of foliar applications of pyrethroids and organophosphates as well as seed treatments with neonicotinoids (Ragsdale et al., 2011). Figure 4-5 illustrates the increase in the use of the neonicotinoids compounds imidacloprid and thiamethoxam as seed treatments as well as the increase in the use of pyrethroid compound lambda-cyhalothrin as a foliar treatment for controlling soybean aphid.
Depletion and Replenishment of Natural Resources
The U.S. food and agriculture system relies on vast quantities of natural resources, especially arable land and water. The availability and quality of these natural resources is influenced not only by human decisions (e.g., contamination of aquifers with pesticides and fertilizers or excessive erosion
FIGURE 4-5 Estimated agricultural use for imidacloprid (A), thiamethoxam (B), and lambda-cyhalothrin (C), 2011.
SOURCE: Adapted from the Pesticide National Synthesis Project, U.S. Geological Survey. https://water.usgs.gov/nawqa/pnsp/usage/maps/index.php (accessed January 8, 2015).
due to improper tillage practices) but also by factors outside human control (e.g., floods and droughts). In some cases, rates of resource depletion can be matched by rates of replenishment or regeneration: for example, rates of water use in irrigation are matched by recharge of surface and groundwaters by snow melt or rainfall. Alternatively, rates of resource depletion can exceed rates of recharge, leading to slow or rapid degradation of the resource base on which agricultural production depends.
The recognition of the need to better manage soil and water resources on farms, on grazing lands, and in forests began formally in the United States with the formation of the U.S. Department of Agriculture (USDA) Soil Conservation Service in 1935, renamed the Natural Resources Conservation Service (NRCS) in 1994. Financial and technical support provided by NRCS continues to help landowners implement natural resource conservation strategies that address soil erosion, water quality, water conservation, and wildlife habitat. However, climate change and weather extremes,
such as intense rainfall events or drought, as well as the need to produce more food on the same or less arable land, will require a renewed commitment to further research and extension capacity into the development and implementation of economically feasible conservation strategies that minimize imbalances in the stocks and flows of natural resources.
Disruption of the balance between soil erosion and soil formation illustrates how agriculture can have a profound effect on the environment through net resource depletion. Erosion is a natural process that occurs on nearly all soils, though rates depend on multiple site-specific factors that include climate conditions and topography. The process occurs in two stages: detachment of soil particles from the soil surface and their subsequent transport and deposition. Erosion by water can occur in sheets,7 rills,8 and gullies9 when rainfall rates exceed a soil’s infiltration capacity; erosion by wind can occur when soil is dry and loose, the surface is bare and smooth, and the landscape has few physical barriers to block the movement of air (Magdoff and van Es, 2009).
Erosion is perhaps the most important land degradation process associated with agriculture (Cruse et al., 2013). Direct comparisons of soil erosion rates under different forms of land management have shown 1.3- to 1,000-fold differences, with mean erosion rates of 0.05 mm year−1 for sites under native vegetation and 3.94 mm year−1 for agricultural sites managed conventionally (Montgomery, 2007). Soil disturbance and exposure due to tillage and cropping practices are the prime culprits for accelerated rates of erosion on land under agricultural management (Magdoff and van Es, 2009; Montgomery, 2007). Erosion of agricultural soils tends to deplete soil organic matter, fertility, and water holding capacity (Magdoff and van Es, 2009) and, consequently, can cause significant reductions in crop yields (den Biggelaar et al., 2004; Fenton et al., 2005).
Soil formation is the result of the weathering of parent rock materials and additions and transformations of organic matter derived from plants, animals, and microbes. It is a geological process that is slow in comparison to the time span of a human generation and to rates of erosion incurred on agricultural land. In an investigation of 18 watersheds worldwide,
7 Sheet erosion is removal of soil in thin layers by raindrop impact and shallow surface flow. It results in loss of the finest soil particles that contain most of the available nutrients and organic matter in the soil.
8 Rills are shallow drainage lines that develop when surface water concentrates in paddock depressions, eroding the soil.
9 Gullies are channels deeper than 30 cm that occur when smaller water flows concentrate, cutting a channel through the soil.
Alexander (1988) found soil formation rates ranged from 0.002 to 0.09 mm year−1, with a mean value of 0.04 mm year−1.
Wakatsuki and Rasyidin (1992) also studied soil dynamics at multiple sites worldwide and estimated the mean rate of soil formation to be 0.06 mm year−1. Cruse et al. (2013) reported a mean rate of soil formation of 0.11 mm year−1 for four soil series used intensively for crop production in Iowa.
The mean rate of sheet and rill erosion on U.S. cropland in 2010 was estimated by the USDA (NRCS, 2013) at 6.1 megagrams (Mg) ha−1 year−1; the mean rate of wind erosion that year was estimated at 4.6 Mg ha−1 year−1. Erosion due to water in ephemeral gullies can also be an important form of soil loss (Cruse et al., 2013; Gordon et al., 2008), but it is not assessed in widely used soil erosion assessment tools such as the Revised Universal Soil Loss Equation 2 (USDA, 2008) and the Water Erosion Prediction Project model (USDA, 2012). Nonetheless, by combining values for sheet, rill, and wind erosion, the minimum mean value for erosion on U.S. cropland is 10.7 Mg ha−1 year−1 (see Figure 4-6). Assuming a soil bulk density of 1.3 Mg m−3, that rate is equivalent to the loss of 0.82 mm of soil per year−1.
Though erosion of soil from cropland at a rate of 0.82 mm year−1 may seem insignificant, it is at least an order of magnitude greater than the rates of soil formation cited earlier. Consequences of this imbalance can be seen in an evaluation of soil dynamics in Iowa, which contains some of the most productive rain-fed croplands in the United States. Based on the mean rate of soil formation reported by Cruse et al. (2013) for four Iowa soil series (0.11 mm year−1) and the mean rate of erosion due to sheet, rill, and wind losses on Iowa cropland (0.98 mm year−1) reported by the USDA (NRCS, 2013), net loss of soil would be 0.87 mm year−1. Viewed in a more historical context, net loss of soil would be 87 mm per century.
Despite the loss of considerable amounts of topsoil from U.S. croplands due to erosion, crop yields have generally increased over the past century, largely because technological advances, including more intensive use of fertilizers, have been able to mask the potential effects of soil degradation. However, as noted by Cruse et al. (2013), to make use of technological advances in the next century, especially those related to plant genetics, soil quality must be maintained or improved, especially soil’s capacity to supply increasing amounts of water and nutrients. In this regard, changes in tillage and cropping practices that retard erosion will be critical, especially increased adoption of minimum tillage and zero tillage techniques, greater use of cover crops, and more widespread use of perennial, sod-forming crops (Magdoff and van Es, 2009; Montgomery, 2007).
FIGURE 4-6 Estimated mean sheet, rill, and wind erosion on U.S. cropland, measured in megagrams per hectare per year (Mg ha−1 year−1), 1982-2010.
SOURCE: NRCS, 2013.
Though irrigation is used on only 15 to 20 percent of total U.S. cropland, it is used on about 70 percent of land used for vegetable production, about 80 percent of land used for orchard crops, and essentially 100 percent of land used for rice production (Schaible and Aillery, 2012). Changes in irrigation technology, competition for water between urban and agricultural users, spatial and temporal patterns of drought, biofuel production from irrigated crops such as corn, and shifts in domestic and international markets for crops with different water use efficiencies and profit characteristics now intersect with the need to balance between water resource use and water resource replenishment. In general, rates of groundwater
withdrawal are increasing throughout the United States relative to rates of replenishment (Konikow, 2013). In some cases, such as for croplands drawing on the Ogallala (High Plains) Aquifer, the imbalance between water withdrawal and recharge may prove too costly or impractical to maintain current levels of crop production (Konikow, 2013).
Relatively inefficient irrigation systems are still used for much of the U.S. irrigated cropland (Schaible and Aillery, 2012). The authors noted that long-term sustainability of irrigated agriculture will depend on adopting innovative, more efficient irrigation systems at the farm level. Some of these innovations include soil- and plant-moisture–sensing devices, commercial irrigation-scheduling services, and simulation models that help producers with irrigation decisions, among others. Another approach, currently being assessed in the Central Valley of California, is the artificial recharge of groundwater using excess surface water in non-drought years (Scanlon et al., 2012).
In areas of the United States where water supplies are limited and groundwater is susceptible to overdraft (most often due to periodic severe drought conditions), reused water is increasingly being used to irrigate both edible and nonedible crops. The 2007 Ag Census, Farm and Ranch Irrigation Survey (USDA, 2009) reported that more than 1.8 million acres of farmland in the United States were irrigated with recycled water, defined as water previously used for irrigating crops. Additionally, more than 700,000 acres of farmland used reclaimed wastewater treated for non-potable reuse (USDA, 2009). USDA, in recognition of the increasing frequency and severity of droughts in many parts of the United States where food and fiber are grown, identified water reuse as one of six broad areas on which to focus research, education, and extension efforts to ensure agriculture water security by 2025 (Dobrowolski and O’Neill, 2005). Water reuse provides significant opportunities to reduce groundwater depletion, but it is not without its challenges. These include matching supply and demand, the risk of contamination of stored water with pathogens from wildlife, negative impacts on crop yields due to increased salinity, health concerns related to emerging contaminants, and the public’s perception of its use on edible crops (Dobrowolski et al., 2008). USGS provides a tremendous amount of information on agricultural impacts on water quality (see also Appendix B on selected metrics, methods, data, and models for USGS data sources).
Population and Community Disruption
Population and community dynamics among species within ecosystems can be affected by contaminants released into the environment at pollutant levels and by shifts in the availability of natural resources. The degree of ecosystem impact at each stage of the food and agriculture system depends
on management decisions and the resulting response of the environment to the stressors created by those decisions.
For example, a broad-spectrum pesticide applied to a crop to control a pest during production may have significant adverse impacts on non-target pollinating insects in both farmed and non-farmed areas of the ecosystem. The loss of pollinators, by pesticide exposure and a variety of other drivers, affects both wild plant population and community diversity as well as yields of insect-pollinated crops, especially fruits and nuts. A current review of the decline in pollinators on a global scale advocates for investment in both a better understanding and implementation of “agri-environment schemes” to protect pollination services (Potts et al., 2010).
The Sacramento-San Joaquin Delta provides another example of how the balance of an ecosystem can be affected by management decisions. Vast acres of farmland in the southern Central Valley of California depend on water withdrawals from the Delta, as do two-thirds of the state’s households. At the same time, the Delta provides critical habitat to a number of native fish, birds, mammals, and reptiles. For example, the Yolo Bypass floodplain is a fertile setting both for salmon reproduction and crop production (Garnache and Howitt, 2011). The high demands on water supply by agriculture as well as the general population, especially during drought years, significantly affect the population and community dynamics of the Delta. Lund et al. (2008) noted the importance of planning efforts to balance the water supply with the Delta’s ecosystem needs. Keeping this idea at the forefront of any decision making would improve the likelihood of providing benefits to agriculture and the environment. The report identified an “ecosystem solution” that includes strategies such as coordinating planning efforts, minimizing the entry of toxicants and invasive species into the Delta, creating wildlife-friendly agriculture, and restoring habitat diversity. These two examples demonstrate how management decisions can have intended and unintended consequences on ecosystem health, emphasizing the importance of a more thorough understanding of the interconnectedness of agriculture and the environment as well as a recognition of the complex nature of these connections.
COMPLEXITIES ASSOCIATED WITH ENVIRONMENTAL EFFECTS
As should be clear from Chapter 2 and the previous discussion in this chapter, the U.S. food and agriculture system constitutes a prominent example of a coupled social–ecological system, in which people are inextricably linked with key components of the environment, including soil, water, air, sunlight, and a diverse biota (Rivera-Ferre et al., 2013). Natural resources are used to produce food, feed, fuel, and fiber for residents of the United States and other countries, thereby supporting a considerable portion of
the U.S. economy. However, in recent years, societal demands on the food and agriculture system have expanded beyond production and profitability to include better stewardship of natural resources and improved protection of environmental quality.
Unlike most other ecosystems, agroecosystems explicitly reflect human knowledge, technology, labor, attitudes, and intentions, which in turn are affected by broader socioeconomic factors like markets, regulations, and education. Farmers, policy makers, businesspeople, and consumers repeatedly make decisions that affect the components and performance of agroecosystems. Consequently, agroecosystems are dynamic and can change quickly in response to social, economic, physical, biological, and technical factors.
Because the U.S. food and agriculture system has many interrelated components and processes, decisions about ways to adjust or refine one portion of the system can have significant consequences for other portions. Optimizing system performance in relation to productivity and environmental goals depends on several sets of tasks and types of information. These include identifying the multiple interacting and interdependent parts of the system; understanding how these parts are related; quantifying the status of system components; monitoring fluxes of materials and energy into, within, and out of the system; and determining key decision points affecting system dynamics. In some cases, empirical experiments can be designed, implemented, and monitored to compare the performance of contrasting systems of agricultural production, processing, and distribution. In other cases, empirical data derived from a range of sources can be used to develop models with which to compare system performance characteristics. For both approaches, it is important to recognize the dynamic characteristics of relevant environmental effects.
Characteristics of Environmental Effects
Interactions among food, agriculture, and the environment are of major importance in the United States for three reasons: the large land area the system occupies, the large quantities of resources it consumes, and the strong connections that can exist between agricultural and nonagricultural ecosystems. Of the 9.16 million square kilometers of total land in the United States, 18 percent is used for cropland and 27 percent is used for pasture and rangeland; within the continental United States, agriculture occupies 54 percent of total land area (Nickerson et al., 2011). Water use exemplifies the disproportionate impact of the U.S. food and agriculture system on natural resources. Food and agriculture, principally irrigation, account for about 80 percent of the nation’s total consumption of freshwater stocks (ERS, 2013).
Exports (i.e., outflows) of nutrients, pesticides, and other materials from agroecosystems into nonagricultural ecosystems (i.e., inflows) can be substantial. For example, Alexander et al. (2008) estimated that nearly 1 million metric tons of nitrogen are delivered annually into the Gulf of Mexico from agricultural lands lying upstream in the Mississippi River Basin, leading to formation of a coastal hypoxic zone. Of the 34,000 metric tons of the herbicide atrazine that are applied each year to U.S. cropland (Grube et al., 2011), about 1 percent moves into associated streams, creating conditions that can exceed thresholds for safeguarding aquatic organisms and human health (Gilliom et al., 2006; Larson et al., 1999). Heathcote et al. (2013) studied trends in sedimentation for 32 lakes in Iowa and found that agricultural intensification over the past 50 years had led to accelerating increases in soil sediment deposition in the lakes due to erosion, despite soil conservation efforts. Fluxes between farms and the atmosphere also are important. Agricultural practices, principally fertilizer use and manure management, are responsible for about 74 percent of U.S. emissions of the greenhouse gas nitrous oxide and 84 percent of the nation’s emissions of ammonia and other NHx-nitrogen compounds (EPA, 2011, 2013).
As these examples illustrate, environmental effects of the U.S. food and agriculture system reveal traits of a complex system. In particular, they can involve spatial displacement, with large distances possible between sites of pollutant discharge and sites of their ultimate impacts. The system’s environmental effects also may be characterized by temporal lags, with effects remaining largely invisible or unrecognized for months or years. For example, following the introduction of chlorinated hydrocarbon insecticides, such as DDT and dieldrin, in the 1940s and 1950s, declines in bird populations were not recognized as being related to use of these chemicals for a number of years. Because their toxic effects included reduced reproductive efficiency, rather than just direct mortality, and because concentrations did not reach critical levels until “biomagnifications” had occurred with movement of the pesticides through the food web (Mineau, 2002), cause- and-effect relationships were initially difficult to discern. By the 1970s, when understanding of the large effects of this class of pesticides on non-target organisms increased, most of the chemicals were banned or severely restricted in many developed countries. Currently, there is concern over the ecological impacts of neonicotinoid insecticides, which were introduced in the 1990s due to their lower mammalian toxicity relative to organophosphate and carbamate compounds and are now widely used throughout U.S. agriculture. Emerging data indicate these compounds may be primary factors in the decline of honeybee populations through chronic effects on behavior, health, and immunity, and increased susceptibility to pathogens and parasites (Di Prisco et al., 2013; Henry et al., 2012; Pettis et al., 2012).
Temporal lags in agroecosystems also may present positive, desirable effects, such as the increase in soil nitrogen fertility and reduced requirement for mineral fertilizer that occur when nitrogen-fixing crops like alfalfa are followed in rotation sequences by cereals and other crops that do not fix atmospheric nitrogen (Peoples et al., 1995).
Environmental effects of the food and agriculture system can be indirect. Indirect effects may occur through loops and webs of interconnected species so that the impact on one species of a change in management practices or system composition and configuration is mitigated by other species. The effects of neonicotinoid insecticides on honeybees by way of pathogens and parasites illustrate this concept. It is also exemplified by the phenomenon known as “target pest resurgence” whereby an insect pest population increases rapidly following application of a chemical intended to control it, often to a level higher than existed before the control measure was applied (Dutcher, 2007). Although an insecticide may destroy more than 99 percent of a target pest population, it rarely eliminates all of the pests; frequently, however, it kills a large portion of the pest’s natural enemies and disrupts food webs that would otherwise promote natural enemy persistence and efficacy (Bottrell, 1979; NRC, 1996). With many fewer natural enemies present, surviving pest populations increase rapidly, posing an enhanced threat to crop production. Alternatively, biological control of crop pests by natural enemies may be enhanced by maintaining natural and seminatural vegetation in agricultural landscapes, thereby allowing natural enemies to move among habitats that provide them with refugia and resources that may be scarce in crop fields (Power, 2010). Losey and Vaughan (2006) estimated that insect predators and parasitoids acting as natural enemies of crop pests save $4.5 billion in the United States each year by reducing crop losses to insect damage and lowering expenditures on insecticides. Thus, ignoring or failing to appropriately manage indirect effects in the U.S. food and agriculture system may have serious economic implications.
Nonlinear effects are common in complex systems like food and agriculture, with small changes in management or system composition or configuration giving little or no response or a disproportionately large response. The latter class of effects can be particularly important for both physical and biological processes in agroecosystems. For example, in a field experiment comparing contrasting patterns of land use in watersheds used for corn and soybean production, Helmers et al. (2012) observed that conversion of 10 percent of the cropland area to filter strips composed of reconstructed prairie vegetation resulted in a 96 percent reduction in the export of soil sediment from the watersheds. Pesticides that disrupt the endocrine system of non-target animals can also exhibit nonlinear, nonproportional effects, with exposure to low or intermediate concentrations causing equal
or larger changes in hormone levels relative to changes elicited by high concentrations. Endocrine-disrupting agricultural pesticides have been found to alter rates of growth and development, immune system function, and other health parameters (Rohr and McCoy, 2010; Vandenberg et al., 2012). Exposure to them at low, ecologically relevant concentrations has been suggested as contributing to population declines of amphibian species (Hayes et al., 2002, 2010).
Though the food and agriculture system exerts substantial pressure on the environment, environmental factors also can have strong effects on various aspects of the food and agriculture system, especially crop and livestock productivity. Environmental stressors, especially droughts, floods, exceptionally high and low temperatures, and pest infestations, are notable for their lack of predictability in both space and time. Consequently, a key system characteristic is the degree of resilience the environment manifests when stressed by physical and biotic factors. Resilient systems resist change due to stressors and rebound quickly after perturbation; non-resilient systems are strongly altered by stressors and recover more slowly, if ever. Pimentel et al. (2005) noted differences in resilience in a long-term cropping systems experiment that included a conventionally managed corn–soybean rotation and two organically managed, more diverse rotations. During 5 drought years when growing season precipitation was less than 70 percent of average levels, corn yields were 28 to 34 percent higher in the more diverse organic systems. This effect was attributed to higher levels of soil organic matter, with concomitant increases in soil water storage and plant-available water. Resilience also can be evident with regard to the effects of crop diversity on pest management. Blackshaw (1994) found that the mean density and year-to-year variance of population densities of the grass weed Bromus tectorum were markedly higher in fields in which wheat was grown continuously compared with wheat grown in rotation with canola. In general, diversified crop rotation systems offer important opportunities for minimizing threats of weed infestation while reducing requirements for herbicide inputs (Nazarko et al., 2005), a consideration that is especially relevant to addressing growing problems associated with the management of herbicide-resistant weeds (Beckie, 2006).
Because the food and agriculture system covers a broad geographic area and intersects with numerous organisms and multiple portions of the economy, changes in the configuration of the system can incur consequences that may be difficult to anticipate without careful analysis. For example, biofuel production from crop materials has been championed as a means of reducing fossil fuel use and limiting GHG emissions, but some analysts have concluded that it can be responsible for environmentally undesir-
able indirect land-use change effects,10 whereby shifts from food and feed production to biofuel production in one region may lead to the conversion of grasslands and forest lands to croplands in others, with concomitant increases in net carbon dioxide (CO2) emissions, soil erosion, and nutrient emissions to water (Fargione et al., 2008; Searchinger et al., 2008; Secchi et al., 2010). The evolution of pesticide resistance in target pests also exemplifies how agricultural management practices can elicit unwanted effects that might be avoided by analysis of alternative management systems. Since the mid-1990s introduction of transgenic crops resistant to the herbicide glyphosate, glyphosate use in the United States has increased 10-fold (USGS, 2014), making it the most heavily used pesticide in U.S. agriculture and a strong selection force acting on weed population genetics. Concomitantly, glyphosate-resistant weeds have become increasingly prevalent and problematic (Heap, 2014). In an analysis of ways to address this problem, Mortensen and colleagues (2012) concluded that simply stacking new genes for resistance to additional herbicides in crop genomes was unlikely to prevent further cases of herbicide resistance in weeds, and that a more efficacious approach would be to develop and implement integrated weed management systems that employ a diverse set of tactics, such as crop rotation, cover cropping, planting of competitive crop cultivars, and appropriate use of tillage and herbicides application.
The multiple dimensions of the food and agriculture system can provide multiple pathways toward solutions to complex problems. For example, increasing food production is not the only pathway to increase food availability to a growing human population. This is fortunate, because increased food production tends to either require more land (through the conversion of more forests and grasslands to arable crop production) or the intensification of fertilizer and pesticide use on existing arable land, with attendant environmental problems such as elevated GHG emissions, loss of biodiversity, water contamination, and soil erosion. Food availability also can be increased by reducing food waste and shifting dietary patterns toward a greater proportion of plant-based foods (Foley et al., 2011). In 2010, an estimated 31 percent of the 195 billion kilograms of food available in the United States at retail and consumer levels was not eaten (Buzby et al., 2013). In an analysis of the consequences of a radical shift in global dietary patterns, Cassidy et al. (2013) concluded that growing food exclusively for direct human consumption rather than animal feed and biofuels could increase available food calories by as much as 70 percent, enough to feed an additional 4 billion people. Such a shift would be particularly profound
10 Indirect land use change effects refers to the effects that increasing biofuel production in one location will have on expanded cultivation of land in other locations.
in the United States, where corn, the nation’s largest crop, is chiefly destined for animal feed and biofuel production (ERS, 2014; Foley, 2013).
DRIVERS OF HUMAN BEHAVIOR AFFECTING THE ENVIRONMENT
It seems paradoxical that humans would undermine the quality of their habitat by depleting, contaminating, and unbalancing the natural environment. But maintaining the natural environment is one among many human goals. Human behavior makes more sense when different kinds of people and different group sizes are examined in their specific socioeconomic and biophysical contexts. Like the environment as a dynamic system, human behavior also displays spatial displacement, temporal lags, and nonlinear feedbacks—all peppered with random effects.
Human decisions are made in the context of desires, incentives, constrained resources, imperfect information, and bounded rationality. Human institutions, like laws and markets, shape incentives for decision makers (Schmid, 2004). Of particular importance for behavior related to the natural environment are property rights—what and how people are allowed to own things. For environmental impacts, two cases of property rights are especially important. When one decision maker’s actions influence the welfare of another person, an economic externality exists. The term comes from the fact that the affected person’s welfare is external to the decision. The externality may be positive (e.g., acquiring honey bees that also pollinate a neighbor’s trees) (Meade, 1952) or negative (e.g., pesticide runoff into a river with swimmers downstream). But the key factor is that the external person lacks the property right to protect himself or herself from the external effect without taking special measures. Hence, the decision maker takes into account some, but not all, of the costs and benefits experienced by the public. What is optimal from a private perspective may not be so from a public one.
The second case of property rights that affect environmental behavior is that of common property resources that are shared (like a grazing commons or the atmosphere) (Blaikie and Brookfield, 1987). In both cases, no one has the right to exclude others from using the resource, creating an incentive for depletion or misuse. Consequently, what is optimal for the individual is not so in the aggregate because the resource gets overexploited.
Because many important environmental impacts of the food system occur during agricultural production, the following sections first examine farmer decision processes and then explore decisions by other food system actors, such as processors, distributors, and consumers.
Private Producer Perspective
Most food is produced by farmers who rely on agriculture for their livelihood. Although evidence abounds that farmers care about environmental stewardship, surveys repeatedly show that profitability is an overriding concern (Ma et al., 2012). Farmers in the United States hold property rights that give broad latitude over how to manage their land so long as they do not cause harm in direct and measurable ways (Norris et al., 2008). However, their actions may cause economic externalities through air, water, or biotic changes that are indirect and often hard to measure.
The profit-maximizing approach to nitrogen fertilizer application on corn illustrates a rational process where an economic externality can lead to environmental degradation. To begin, note that fertilizer, land, and corn are private goods that belong to the farmer. But the aquifer under the farm, the streams nearby, and the atmosphere have no owners—they are common property resources. Corn yield typically increases with increasing applications of nitrogen, but yield increases at a decreasing rate and ultimately reaches a plateau due to genetic yield potential or shortages of other inputs. For a corn producer who is deciding how much nitrogen fertilizer to apply to a corn crop, the standard rule for profit maximization is to apply more fertilizer up to the point where the pay-off from adding more fertilizer just equals the cost of acquiring and spreading that fertilizer. Up to that point, each added unit of fertilizer will fetch greater value of marketable corn. As fertilizer application rises and corn yield tails off, a rising share of fertilizer applied is not taken up by the corn plant. Instead, it converts to nitrate and is carried by water into streams that may contribute to marine hypoxia (Alexander et al., 2008); it may also convert into nitrous oxide and move into the atmosphere as a GHG (McSwiney and Robertson, 2005; Shcherbak et al., 2014). Because no one owns the waterways or the air, the costs to other people of using those environmental media as waste recipients are external to the farmer’s decision. Similar external costs can accrue from other privately rational decisions by farmers. Examples include specializing in highly profitable crops at the expense of biodiverse natural areas that provide habitat for beneficial species, such as songbirds, pollinators, and the natural enemies of certain agricultural pests.
The common property dynamic contributes importantly to depletion of shared resources like the Ogallala (High Plains) Aquifer. In the century since farmers learned that the semiarid High Plains region was underlain by this vast aquifer, irrigation has dramatically expanded crop production. However, due to low rainfall in the current era, the aquifer’s recharge rate is dwarfed by water withdrawals, resulting in a 30 percent depletion of the groundwater supply today in western Kansas, with continuing depletion expected despite rising private costs of withdrawing water from greater
depths (Steward et al., 2013). Because no one owns the groundwater, there is no assurance that if one person conserves, that person will have more of the resource available later.
Societal Perspective and Environmental Policy
Although environmental problems in agriculture are driven by a certain logic, solutions that can protect the public interest are possible. The fact that one decision maker holds the right to take actions that affect others does not mean those actions are inevitable. As Ronald Coase (1960) famously observed, it simply means the affected parties must pay for the right to prevent harm. A variety of regulatory and voluntary approaches to mitigating the impacts of the U.S. food system on the environment have been taken by regulatory agencies, environmental conservation groups, and actors within each of the food system sectors (see Box 4-1).
Because U.S. farmers have broad property rights to manage their land as they see fit, U.S. agricultural environmental protection policy focuses on paying farmers for environmental services. A variety of federal programs under the historic series of farm bills since 1985 (most recently the Agricultural Act of 2014) (USDA, 2014a) pay farmers for environmental services through sharing the cost of environmental stewardship practices (e.g., under the Environmental Quality Incentives Program), renting farmland that offers conservation benefits (e.g., Conservation Reserve Program), or paying for environmental services from working lands (e.g., Conservation Stewardship Program). In the private sector, efforts are expanding to establish markets for ecosystem services, such as the provision of clean water or of wildlife habitat. Although such markets are currently small, their emergence has raised a set of important questions about how to ensure that environmental stewardship practices truly add to environmental quality (“additionality”) and whether it makes sense to pay separately for different services that arise from the same stewardship practice (“stacking” ecosystem services) (Cooley and Olander, 2012; Hanley et al., 2012; Woodward, 2011).
Another approach to protect the public interest is regulation that directly mandates actions or sets limits on pollutants. In this instance, the public holds the right, for example, to clean water and air, so polluters must incur the cost of meeting clean standards. A prime example of this is the multipronged effort to curb the unintended consequences of unwanted nutrient flows and resultant pollutants into air and water using regulations and voluntary programs at the national, regional, and state levels. Often these regulatory approaches mandate emission mitigation to avoid not only ecosystem impacts but also the impacts these emissions have on human health.
Examples of Environmental Mitigation Interventions
- The Clean Water Act
- The Clean Air Act
- Federal Insecticide, Fungicide, and Rodenticide Act
- Endangered Species Act
- Coastal Zone Act Reauthorization Amendments of 1990
- Safe Drinking Water Act
- Resource Conservation and Recovery Act
- Food Quality Protection Act
- Toxic Substances Control Act
- National Ambient Air Quality Standards
- Conservation compliance linked to crop insurance subsidies (Sodsaver Program)
Voluntary (Incentive Programs)
- Agricultural Management Assistance (AMA)
- Conservation Reserve Program (CRP)
- Conservation Stewardship Program (CSP)
- Environmental Quality Incentives Program (EQIP)
- Agricultural Conservation Easement Program
- Healthy Forests Reserve Program (HFRP)
- The U.S. Department of Agriculture (USDA) Natural Resources Conservation Service Conservation Technical Assistance Program
- USDA state and locally funded Cooperative Extension offices
The Clean Air Act mandated the Environmental Protection Agency (EPA) to set air quality standards for six pollutants, namely, carbon monoxide, lead, nitrogen dioxide, PM less than 10 μm in diameter (PM10), PM less than 2.5 μm in diameter (PM2.5), ozone, and sulfur dioxide (EPA, 2009a). Primary standards address public health concerns and secondary standards protect general public welfare (e.g., visibility and environmental effects) (EPA, 2008; Pope et al., 2009). The major agricultural air pollutants are PM, ammonia, and VOCs, as well as hydrogen sulfite. Currently, no federal standards regulate agricultural ammonia and VOC atmospheric emissions
directly, but ammonia can contribute to PM formation (Pinder et al., 2007) and VOCs contribute to ozone formation (EPA, 2008).
The anthropogenic GHGs of greatest concern are carbon dioxide, methane, and nitrous oxide. These gases have different potentials for trapping heat in the Earth’s atmosphere, known as global warming potential.11 Currently, the United States neither requires mandatory reporting nor regulates total GHG emissions. At the state level, California became the first state to regulate and mandate reporting of GHG emissions with Assembly Bill 32 (California Global Warming Solutions Act of 2006). This bill does not exempt GHG emissions from the agriculture sector.
The Clean Water Act (CWA), passed in 1972 and significantly amended in 1977 and 1987, provides the basis for EPA to regulate point sources of pollution to surface waters using the National Pollutant Discharge Elimination System (NPDES) permitting system. Except for certain agricultural facilities, such as large animal feedlots, agricultural discharges are classified as non-point sources and therefore exempt from the point source NPDES permitting system. The 1987 amendments to the CWA recognized non-point source pollution (NPS) as a significant impairment to U.S. surface waters and in response created, under section 319, the Nonpoint Source Management Program. This program provides grant money to support the development and implementation of technologies, educational programs, and—most importantly—funds for water quality monitoring to determine the effectiveness of non-point implementation projects. Non-point source pollutants arising from agricultural production and addressed by this program include nutrients, sediment, pathogens, and pesticides.
Agricultural NPS continues to be a significant impairment to surface water quality, as stated in the 2004 National Water Quality Inventory Report to Congress (EPA, 2009b), where it was identified as the leading source of water quality impacts to rivers and lakes. California has implemented additional water quality regulations to address non-point sources from agriculture. The Irrigated Lands Regulatory Program, administered by the California State Water Resources Control Board (SWRCB), issues growers either waste discharge requirements (WDRs) or conditional waivers of WDRs in order to regulate discharges from irrigated agricultural lands. The program allows for irrigated discharges to occur, but under a condition of monitoring the water quality of receiving waters and the implementation of management practices to correct any impairments. In 2014, the SWRCB reported approximately 6 million acres and 40,000 growers had been enrolled in the program.
Apart from payments for environmental services and regulations to
11 Global warming potential is a relative measure of how much heat a GHG traps in the atmosphere.
control pollutants, several other approaches encourage improved environmental stewardship. These incentive-based methods include certifications of good environmental performance. Certifications may serve to inform the consumer about invisible production process traits or to protect the farmer against lawsuits for alleged poor stewardship. The USDA organic label is the best known of these, but a wide variety of certifications of general agroenvironmental stewardship and specific practices exist, such as pesticide safety or groundwater protection (Greene, 2001; Segerson, 2013; Waldman and Kerr, 2014).
METHODOLOGIES TO QUANTIFYING SYSTEM PERFORMANCE
This section identifies some relevant measurement and modeling methods used to capture environmental effects. It describes general methods used to assess environmental effects with the understanding of the difficulty in establishing clear cause-and-effect relationships without using a combination of methods. Assessing environmental effects begins with determining how large they are. Some environmental effects can be measured directly. Others are diffuse or hard to observe, so they are measured indirectly, using indicators, or they are simulated, using mathematical models. Life cycle assessments (LCAs) are typically used to account for environmental effects over the life of a product.
Datasets covering environmental effects are available from EPA, USDA, USGS, and private-sector sources (see Appendix B, Table B-3). U.S. surface water quality is tracked by the USGS National Water Information System. Air quality and chemical toxins are tracked by EPA’s Air Quality System and ECOTOX databases. The environmental effects of farming practices are tracked by USDA’s Agricultural Resource Management Survey and NRCS databases, while pesticide residues on food are covered by the USDA Pesticide Data Program.
Apart from the size of a direct environmental effect, it can be equally important to measure feedbacks and repercussions elsewhere in the food system. Such feedbacks are generally simulated using models.
The direct measurement approach seeks to directly quantify causal relationships between key ecosystem attributes and the entities selected for measurement (Lindenmayer and Likens, 2011). An advantage of the direct measurement approach is that it can result in the development of effective monitoring programs and successful implementation of management practices as long as the entities directly measured are selected based on answering carefully designed questions about the system being studied. For
example, if a question is about whether surface runoff from dairy production in a particular watershed is a source of Giardia or Cryptosporidium detected in a local drinking water supply, then measurement of Giardia or Cryptosporidium at various locations within the watershed would be the most direct and efficient method to answer the question. Direct measurements under situations such as this are used to answer specific environmental questions as long as adequate resources are available.
Although the direct measurement approach has its advantages, significant disadvantages and/or limitations exist with its use in quantifying environmental effects. It is often costly and both labor and time intensive. Moreover, it is frequently impossible to measure and evaluate all the environmental processes and factors needed to thoroughly quantify the system of interest (Bockstaller and Girardin, 2003; Lindenmayer and Likens, 2011). Even with continued advances in technology allowing for easier and more economical analyses of organisms and chemicals (e.g., pathogens, pesticides, nutrients), some ecosystem evaluations, such as soil biodiversity, require the use of alternative measurements that are easier and more cost-effective to conduct (Eckschmitt et al., 2003). Chemical and biological toxicity testing are commonly used to identify the pollutant(s) responsible for water quality impairments, but only after less expensive biosurvey techniques, such as EPA’s Rapid Bioassessment Protocols, detect a potential impairment (Barbour et al., 1999).
Indicators are used to detect and evaluate changes in environmental conditions in response to environmental stressors. Environmental and ecological indicators measure a variety of environmental parameters, including plant health (water stress, nutrient content, and pest damage), biodiversity, ecosystem services, aquatic toxicity, soil erosion, emissions, and water quality. The advantage of the indicator approach over direct measurement is that indicators are generally more cost-effective, require less time to obtain results, and respond predictably to environmental stressors across space and time. Table 4-1 provides a sampling of the types of indicators used to measure environmental conditions affected by the U.S. food system. Box 4-2 describes Daphnia as a biological indicator.
Remote sensing, geographic information systems (GISs), and global positioning systems technology deserve special attention as they allow for the assessment of environmental conditions on both a site-specific and a global scale through the frequent and reliable measurement of a variety of environmental indicators. Atzberger’s (2013) review of advances in remote sensing of agriculture highlights the potential role the technology could provide in reducing the environmental impacts of the U.S. food system.
TABLE 4-1 Example Indicators and the Associated Environmental Condition Monitored
|Indicator||Condition of the Environment Monitored|
|Sun-induced chlorophyll fluorescence (SIF)||Agricultural productivity, crop photosynthesis|
|Aquatic macroinvertebrates||Biological health of streams and rivers, pollution, water quality|
|Heat shock proteins in fish||Thermal pollution of streams and rivers|
|Lichens and mosses||Air pollution|
|Visual and acoustic remote sensing of birds||Biodiversity|
|Fecal indicators (such as E. coli)||Water quality|
|Soil organic matter, pH, bulk density||Soil health|
Daphnia, A Biological Indicator of Environmental Status
Indicator species are frequently employed to evaluate ecosystem integrity in response to environmental stressors. Properly selected indicator species are sensitive to stressors and allow for the integrity of the ecosystem to be examined in a timely and cost-effective manner (Carignan and Villard, 2002). Some of the most common indicator species are those used to examine the impacts of agricultural and nonagricultural activities on aquatic environments.
Daphnia, a genus of small freshwater crustaceans, is commonly used in water quality monitoring due to its sensitivity to physical and chemical changes in the aquatic environment, its important role in the aquatic food web, and its ease to cultivate under laboratory conditions. Its wide use as an indicator species in freshwater systems also has created an extensive database of acute and sub-acute responses to numerous environmental stressors, such as pesticides, heavy metals, and sedimentation.
Simulation models are used to estimate the size or probability of environmental effects that are hard to observe. Simulation models that link multiple components of the food system can also predict indirect effects, and dynamic models can capture feedbacks that lead to delayed, indirect repercussions. When simulation models can be run in concert with random variables, like weather data, they also can capture important environmental impacts that occur only under special conditions when a threshold is exceeded. An applicable example to use such a model is in predicting the
impact of algal blooms. Harmful algal blooms are rare, but when heavy rains washed agricultural phosphorus into the Maumee River and temperatures warmed up rapidly in the summer of 2011, devastating consequences ensued for Lake Erie fisheries and beaches (Michalak et al., 2013). The general uses of simulation models are described in Chapter 7, but this section will survey important simulation modeling approaches used for environmental impacts.
For environmental assessments, the two broad classes of simulation modeling are biophysical and socioeconomic. There are ecosystem service models, such as InVEST developed by the Natural Capital Project, that attempt to link biophysical and socioeconomic components in a GIS context, which can be useful for evaluating alternative land-use and land-management scenarios.
Biophysical models vary widely according to the environmental media on which they focus (soil, plants, animals, water, biodiversity, air, climate). They also vary in spatial scale (field, watershed, airshed, globe) (see examples in Appendix B, Table B-4).
Most water and air pollutants are either intermediate or by-products of several basic biochemical or geochemical reactions, namely, decomposition, ammonification, nitrification, denitrification, ammonium-ammonia equilibrium, ammonia volatilization, fermentation, etc. Incorporating the basic reactions in the modeling framework is essential. Biogeochemical models like DNDC (Denitrification/Decomposition) (Li et al., 2012) have been developed to simulate those reactions for soil, livestock, and crop environmental emissions. Models like DNDC predict water and air emissions under both aerobic and anaerobic conditions using theoretical concepts (e.g., water and gas formation and transfer) along with empirical measured parameters that drive these.
One important group of biogeochemical models predicts crop growth and associated environmental consequences (EPIC, CENTURY/DAYCENT) (Gassman et al., 2005; Hanks and Ritchie, 1991; Parton et al., 1987). These models draw parameters from a particular location on soils and weather, and combine these parameters with data on plant genetics and management methods to predict crop growth and yields and the associated movement of key elements (especially carbon, nitrogen, phosphorus) into the plant and in the surrounding soil. They are often linked to erosion models (e.g., RUSLE2 [Revised Universal Soil Loss Equation 2] or WEPP [Water Erosion Prediction Project]) or to hydrological flow models that predict where water carries eroded soil sediments and dissolved nutrients (e.g., SWAT [Soil and Water Assessment Tool] or GLEAMS [Groundwater Loading
Effects of Agricultural Management Systems]) (Arnold et al., 1998), allowing aggregation of geochemical movements at the groundwater or surface watershed level.
Another important class of physical models simulates and predicts climate changes. At the planetary level, general circulation models predict global climate changes at a decadal time step. Such models are widely used both to test policy and technological scenarios to mitigate climate change and to simulate conditions to which humans will need to adapt. Global climate forecasts from the Intergovernmental Panel on Climate Change are frequently used to generate parameters for agricultural models (such as those mentioned above) to simulate how to adapt food production to projected climate change (IPCC, 2013).
For environmental assessments, socioeconomic models aim to simulate human behavior and how it affects the environment. The main economic models used in environmental assessments focus on producers and markets. At local and regional scales, producer models tend to assume that farmers maximize profits, taking prices as given (Weersink et al., 2002). However, large-scale changes in producer or consumer behavior will trigger changes in prices, which are captured in computable general equilibrium (CGE) models (discussed in Chapter 7). Major CGE models used in agricultural environmental impact assessments include FASOM (Forest and Agricultural Sector Optimization Model) and GTAP (Global Trade Analysis Project), both of which have been used to estimate the effects of agricultural policies in the face of climate change (Hertel et al., 2010; Schneider, 2007). The linking of economic and environmental models is discussed further in Chapter 5 in the context of modeling complex feedbacks.
Life Cycle Assessment
LCA is a methodology that describes environmental assessment of a product or service (e.g., a kilogram of beef or lettuce) over its life cycle. Used for biochemical and energy flows, it is based on inventory data of a product and the emissions to the environment at each stage of the life cycle. The data on resources and emissions are measured and aggregated over the whole life cycle and classified into specific environmental impact categories (e.g., climate change, acidification, eutrophication). LCA arrives at values for each impact category and the results are expressed per unit of the studied product (i.e., functional unit), which is often expressed as mass of the product of a certain quality (e.g., carbon emissions per kg of fat and per protein in milk). LCA is overwhelmingly applied to energy use
and GHG emissions; for example, GHG emissions have been closely studied in the dairy sector (Rotz et al., 2010). It is noteworthy that until recently, hardly any consistency was observed for LCAs conducted even within one sector of food production. For example, 21 peer-reviewed LCAs have been conducted for the U.S. beef sector with a wide divergence of methodologies, making comparisons of findings impossible. The most comprehensive cradle-to-grave LCA for the U.S. beef sector was recently conducted by Battagliese et al. (2013). However, the lack of harmonization across global LCA methodologies, especially for the livestock sector, has led the United Nations’ Food and Agriculture Organization to conduct a 3-year project titled LEAP (Livestock Environmental Assessment and Performance Partnership), which aims to develop one global ISO (International Organization for Standardization) standard-compliant LCA methodology to ensure that environmental assessments of the livestock sector follow a scientifically consistent method and not individual bias. It is hoped that the resulting LEAP guidelines will be applicable to other sectors of the food system to allow for a complete and fair environmental assessment of current production processes and potential effects of mitigation.
The U.S. food system depends heavily on the climate, soil, and water resources that allow a highly productive and varied agriculture to flourish. The environmental effects of the current agricultural system in the United States are positive and negative as well as intended and unintended. Any assessment of the current system must recognize that agricultural production systems may in many instances deplete natural resources of land and water, disturb ecosystem balance, involve the use of environmental contaminants such as pesticides and nitrogen that pollute the natural environment, and present challenges to human health. At the same time, many of these effects can be mitigated by management practices that promote soil and water conservation, minimize nutrient and pesticide emissions, foster sequestration of carbon, and allow appropriate manure disposal from animal feeding operations.
This chapter reviews the environmental effects of food production systems and discusses their salient characteristics, along with drivers of human behavior that influence the environmental impact of food systems, including both the perspectives of private producers and broader societal goals.
Assessments of the environmental effects of food systems are often difficult to conduct because there may be long distances between sites of pollutant discharge and the resulting changes in the abundance and health of non-target areas or species. Nitrogen runoff and effects on distant water ecosystems represent an example of such effects. Similarly, long delays may
occur before the effects of some pollutant discharges become evident, with nitrate impacts on groundwater as an example. Webs of interconnectivity among species that are affected by pesticide use also may occur but not be readily apparent. Ignoring indirect effects of agricultural practices that are expressed through multiple species may have serious long-term implications.
The pathways by which a food system leads to environmental effects display characteristics of complex systems, in that they are dynamic and adaptive, are subject to lags and feedbacks, and include many interdependent actors. As this chapter makes clear, the environmental effects of food systems are intertwined with health, social, and economic domains. Measuring interdependencies within and among these domains presents analytical and modeling challenges that require special methods. Chapter 6 elaborates on the characteristics of complex adaptive systems, and Chapter 7 describes analytical methods that are appropriate for assessing the environmental effects of food systems.
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