A Geophysical Foundation for Alternative Farm Policy - Environmental

Apr 19, 2010 - Eshel got his MA, MPhil, and PhD in geophysics from Columbia (1992, ... concerns and growing public awareness have made agriculture an ...
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Environ. Sci. Technol. 2010, 44, 3651–3655

A Geophysical Foundation for Alternative Farm Policy

constraints to demonstrate the generalizability of the tools and their applicability to any arbitrary impact of the Farm Bill whose cost is quantifiable.

GIDON ESHEL* Physics Department, Bard College, Annandale-on-Hudson, New York 12504-5000

Background

SHUTTERSTOCK

An optimization method could aid agricultural decision making by balancing societal desire(s) with resource management.

Few U.S. legislative bills are publicly criticized as regularly and passionately (e.g., (1), (2)) as the Farm Bill, the sweeping legal structure that formalizes the Government’s relationship with, and role in, the national food production system. Most experts and laypersons alike view the U.S. agricultural policy as overdue for overhaul. Yet recommendations for what should replace the current system diverge widely. Some factsslike the (indisputable) high caloric output of the current systemsare even invoked by mutually antagonistic sides to support their opposing views. This apparent paradox stems from, indeed is a manifestation of, the absence of a universallysor even broadlysaccepted metric of farming system performance. A cogent definition of food efficiency is thus clearly needed. While this note will not settle the issue, motivated by the view that the problem is best reduced to tractable, individually treated, subsets, it strives to advance the problem along one of its many dimensions, geophysics. In addition, expanding optimization mechanisms previously developed by the author, the note uses environmental 10.1021/es9032748

 2010 American Chemical Society

Published on Web 04/19/2010

The plethora of geophysical costs exacted by modern food production is well-documented and widely discussed in scientific and popular publications alike (e.g., refs 3–6 and references within refs 4–6). Because any realizable Farm Bill is finite in scope, improving farm legislation requires choosing the subset of issues to be addressed (thereby also implicitly choosing the ones to be short changed). In this Feature, I present a modular framework for logically and quantitatively identifying and ranking various environmental challenges most pertinent to future Farm Bills, thus contributing to rendering the choice process less arbitrary. Although the formalism is motivated by geophysical considerations, also used below to present the framework, it is rather general, and can address a wide range of objectives and priorities. A key historical focus of the Farm Bill is individual diet, ensuring Americans adequate, widely available, and affordable food (7). Consistently, ever since its inception, the Farm Bill has strongly affected national dietary patterns (8, 9). The logic underlying this note is based on following this empirically established strong interconnection between the Bill and the national diet, in reverse: rather than enact the Bill and then face the resultant mean diet, let us start by identifying broad dietary patterns that optimize, as closely as possible, the various societal, nutritional, and environmental issues we wish the Bill to address, and then design a Bill most likely to yield those patterns. Focusing on the mean individual diet the Bill explicitly or implicitly promotes is something of an axiom; one may reasonably argue for alternative foci, say the financial vitality of the agrochemical or grocery retail sectors. My choice is based on subjectively viewing individuals as the prime stake holder in the food production enterprise, the party entitled to most deference. Because the first Farm Bill was conceived during, and in response to, the Great Depression, its principal nutritional focus was caloric intake. Despite massive societal changes and nutritional science developments since the 1930s (10), this emphasis proved slow to evolve (8, 11). Yet future Bills will likely need to balance disparate and competing objectives. In addition to averting hunger, they will probably be expected to make socioeconomic circumstances that breed obesity less common; minimize agricultural land use, thus permitting larger, more diverse and interconnected, wildlife refugia; minimize water use; and reverse depopulation of rural areas, among other adverse effects of the food production system not emphasized by recent Bills. The presented framework is designed to assist in the challenging tasks of (1) identifying from this ever expanding set of objectives the ones that merit the most immediate attention and that are likely to yield the most societal return on investment; and (2) balancing the chosen objectives when their dictates diverge. VOL. 44, NO. 10, 2010 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 1. Land and Nr requirements of personal annual diets. Four diet classes are considered (12): purely plant-based diets (lower left) and mixed ones (upper right), each either with simultaneous land and Nr use minimization (gray), or without such minimization (black). Each dot, of which there are 4000, represents a realistic, nutritionally sound, gross annual diet comprising, like the actual mean U.S. diet (MAD), 3750 kcal day-1 (12). All diets are diverse (comprise at least 18 plant items each) and meet protein, fat, and total mass recommendations (10, 12). Mixed diets reflect the actual composition of the gross mean U.S. diet, comprising 1045 (2705) animal (plant) based kcal day-1. The animal-based portion of mixed diets is assumed to yield 8 × 105 kcal (acre × year)-1 (12) while using 38-59 kg (84-129 lb) Nr (acre × year)-1 (12). The requirements of the plant-based portion of each of the mixed diets are 2705/ 3750 ≈ 0.72 of those of a purely plant-based diet. Tick marks show relevant averages or bounds of the two variables. See ref 12 for more details.

A Quantitative Metric of Food Production Efficiency The Tool: Introduction. The framework’s main tool is a generalization of the one used in a recent calculation (12) (Figure 1) set out to design (select types and quantities of food items consumed) nutritionally and geophysically sound diets, where geophysical soundness is quantified by land and reactive nitrogen (Nr) needs. This narrow, neither general nor sufficient, definition of geophysical soundness is expanded below and is used here only as a specific example that can be replaced by arbitrarily wide alternative definitions. Similarly, nutritional soundness is only cursorily addressed here by requiring daily diets to comprise 3750 kcal, g100 g protein, e110 g fat, and total mass of approximately 1550 g. Although these bounds exceed reasonable per capita requirements, they follow the actual U.S. gross mean American diet, reflecting the 35-40% caloric losses of that diet. Like the geophysical example, these bounds are best viewed as simply a placeholder for more detailed and current nutritional constraints. Figure 1 shows that plant-based diets require 50- 60% of the land and 1) or demotion (σq < 1) of any term in the series representation of cj. Because of σqs’ seemingly unbridled freedom, some may view eq 5 as limiting the utility of the proposed method. Although not unreasonVOL. 44, NO. 10, 2010 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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able, I believe this concern can be addressed methodologically and politically. The political element is based on transparency. Because βq’s orders of magnitude are known, 1 × 10-1/2 e σq e 1 × 101/2 is reasonable. If a lawmaker argues for letting the qth environmental impact completely dominate the calculation by setting σq to, say, 1 × 104, far in excess of its defensible upper bound, the lawmaker’s choice is numerically transparent, and her record now contains an unambiguous effort to elevate factor q to a game-changing status. Although cogent arguments, external to the technical machinery, in favor of σq ) 1 × 104 may exist, the lawmaker must be able to articulate those persuasively. More importantly, eq 5’s uncertainty can be dealt with by incorporating c’s indeterminacy into the MC formalism. To do that, let Q

cj )

∑ 10

U[-1/2,1/2]

ζqjβq

(6)

q)1

where U[-(1)/(2), (1)/(2)] denotes the uniform continuous distribution over the indicated closed interval. Applied to all of c’s elements, eq 6 leads to the randomized counterpart of the deterministic subsampled ck. Specific subsampled, randomized ck can then be used in the dual MC randomization minimize

(ck)Txk

subject to

(i) Akxk ) b




(ii)

xmin j

e

xkj

e

(7)

xmax , j

blending the nutritional (eq S2 in the Supporting Information) and environmental cost (eq 6) randomizations. A large enough sample of eq 7’s solutions can be condensed into plots like Figure 2, presumably with broader ranges (higher uncertainty bars) due to the dual randomization. The larger solution spread means that it is more difficult for a particular dietary pattern to rise above the variance based expected null range, but it also means that those patterns that do are more robust and believable.

Deployment Views regarding desirable agricultural policies are, and have been, widely divergent in the U.S. and other developed countries. Some of this divergence is rooted in measurable realities and reflects different emphases in balancing competing social, economic, and environmental priorities. Much of the polemics on all sides, however, are insufficiently factual and numerically unsound. To some extent, this reality reflects the need for a quantitative tool that is simultaneously comprehensive enough to address most aspects of food production in a combined framework and flexible enough to entertain statistically numerous and widely varied scenarios. Such a tool would permit a more dispassionate approach to agricultural policies, providing lawmakers with the impartial advice necessary for more rational future policies. The mathematical-statistical construct presented in this paper is meant to provide an initial blueprint for future development of such a tool, using environmental consideration as a testbed. The potential for deploying the proposed machinery is currently seriously hampered by limited availability of necessary data. However, a concerted national effort by the USDA can yieldsat a cost that is significant in absolute terms yet trivial compared to the societal benefits it stands to producesinvaluable results within a year or two, and more definitive ones after a few additional years. Such a time scale should be entirely acceptable given the Farm Bill’s long 3654

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history, the limited success of corrective efforts, and the Bill’s far reaching effects on the health of the nation’s individuals, communities and physical environment. Even more challenging are political aspects of deploying the proposed framework. Neither legislative wrangling nor food production lobbies will be easily persuaded by numerical results gleaned from employing the proposed machinery. Although I am not naive enough to suggest otherwise, I am also mindful of the long history of legislative and political shifts brought about, despite fierce opposition, in part by accumulating knowledge and heightened technical clarity afforded by various sciences transitioning from qualitative to numerical results. In recent decades, the Clean Water and Clean Air Acts were enacted, fuel was unleaded, vast maritime provinces were declared off limits to fishing, power plant sulfur and mercury emissions became regulated, and the U.S. EPA now treats CO2 as a pollutant to which their mandates apply, among numerous other examples. In most aspects of environmental integrity, and despite major setbacks, the U.S. has made significant overall inroads in recent decades. In many of the above and other cases, improved scientific understanding played a key role in propelling the changes against stiff headwinds of skeptical political and business powers. This note takes heart from this tradition; I offer it with the hope of contributing in a small way to slowly and incrementally improving the knowledge needed to perfect the U.S. food production system. Prof. Eshel got his MA, MPhil, and PhD in geophysics from Columbia (1992, 1993, and 1996, respectively), and then did a postdoc at Harvard’s Center for Earth and Planetary Physics (1996-1999). In 1998, he joined the scientific staff at the Department of Physical Oceanography at Woods Hole Oceanographic Institution in Woods Hole, MA. In 1999, he moved to the Department of Geophysics at the University of Chicago, as an assistant professor. In 2007, he moved to the Department of Physics at Bard College in Annandale-on-Hudson, NY. His research has gradually shifted from various aspects of basic climate science to sustainability geophysics, which is now his main line of research. In this line of work, he combines his intimate experience with animal farming (having grown up on a Kibbutz dairy farm in Israel’s north, and raised beef cattle for a number of years as an adult before launching his academic studies) and his scientific knowledge of earth’s geophysical workings. Please address correspondence regarding this article to Eshel at [email protected].

Acknowledgments Numerous discussions with Pamela Martin are enthusiastically acknowledged, as are the thoughtful, pertinent comments of Editor Gentleman and four anonymous Reviewers. I am deeply thankful to the Jeffery Cook Charitable Trust for their generous support.

Supporting Information Available A more detailed mathematical development of the discussed tools (PDF). This information is available free of charge via the Internet at http://pubs.acs.org/

Literature Cited (1) Ray, D.; De La Torre Ugarte, D.; Tiller, K. Rethinking U.S. Agricultural Policy: Changing Course to Secure Farmer Livelihoods Worldwide; Agricultural Policy Analysis Center (APAC), University of Tennessee: Knoxville, TN, Sept 2003. (2) Pollan, M. Big Food Vs. Big Insurance. The New York Times, September 9, 2009. (3) Bittman, M. Rethinking the Meat-Guzzler. The New York Times January 27, 2008. (4) Galloway, J. N.; Townsend, A. R.; Erisman, J. W.; Bekunda, M.; Cai, Z.; Freney, J. R.; Martinelli, L. A.; Seitzinger, S. P.; Sutton, M. A. Transformation of the nitrogen cycle: Recent trends, questions, and potential solutions. Science 2008, 320 (5878), 889–892. (5) Eshel, G.; Martin, P. A. Diet, Energy and Global Warming. Earth Interact. 2006, 10, 1–17.

(6) Eshel, G.; Martin, P. A. Geophysics and nutritional science: Toward a novel, unified, paradigm. Am. J. Clin. Nutr. 2009, 89, 1710S–1716S. (7) Dean, V. An Opportunity Lost: The Truman Administration and the Farm Policy Debate; University of Missouri Press: Columbia, MO, 2006. (8) Nestle, M. Food Politics: How the Food Industry Influences Nutrition and Health; University of California Press: Berkeley, CA, 2002. (9) Monsivais, P.; Drewnowski, A. The rising cost of low-energydensity foods. J. Am. Diet. Assoc. 2007, 107 (12), 2071–2076. (10) Willett, W. C. Eat, Drink and be Healthy; Simon & Schuster: New York, 2001. (11) Nestle, M. Food lobbies, the food pyramid, and U.S. nutrition policy. Int. J. Health Serv. 1993, 23 (3), 1541–4469. (12) Eshel, G.; Martin, P. A.; Bowen, E. E. Land Use and Reactive Nitrogen Discharge: Effects of Dietary Choices. Earth Interact. 2010, submitted.

(13) Galloway, J. N.; Cowling, E. B. Reactive nitrogen and the world: 200 years of change. Ambio 2002, 31 (2), 64–71. (14) Pimentel, D.; Pimentel, M. Sustainability of meat-based and plant-based diets and the environment. Am. J. Clin. Nutr. 2003, 78 (3), 660S–663S. (15) Pimentel, D.; Acquay, H.; Biltonen, M.; Rice, P.; Silva, M.; Nelson, J.; Lipner, V.; Giordano, S.; Horowitz, A.; D’Amore, M. Environmental and economic costs of pesticide use. BioScience 1992, 42 (10), 750–760. (16) Pimentel, D.; Wilson, C.; McCullum, C.; Huang, R.; Dwen, P.; Flack, J.; Tran, Q.; Saltman, T.; Cliff, B. Economic and environmental benefits of biodiversity. BioScience 1997, 47 (11), 747–757. (17) Pimentel, D.; Pimentel, M. Food, Energy and Society; Colorado University Press: Niwot, CO, 1996. (18) Pimentel, D.; Pimentel, M. Food, energy and society; CRC Press: New York, 2008.

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