Horticulture

We refer to a farming system as “diversified” when it intentionally includes functional biodiversity at multiple spatial and/or temporal scales, through practices developed via traditional and/or agroecological scientific knowledge. Farmers manage this functional biodiversity to generate critical ecosystem services to agriculture . At the plot scale, diversified farming systems may include multiple genetic varieties of a given crop and/or multiple crops grown together as polycultures, and may stimulate biodiversity within the soil through addition of compost or manure . By crops, we mean either annual or perennial crops, including tree crops. At the field scale, DFS may include polycultures, non-crop plantings such as insectary strips, integration of livestock or fish with crops , and/or rotation of crops or livestock over time, including cover cropping and rotational grazing. Around the field, DFS may incorporate non-crop plantings on field borders such as living fences and hedgerows. At the landscape scale, DFS may include natural or semi-natural communities of plants and animals within the cropped landscape/region,4x8ft rolling benches such as fallow fields, riparian buffers, pastures, meadows, woodlots, ponds, marshes, streams, rivers, and lakes, or combinations thereof . The resulting heterogeneous landscapes support both desired components of biodiversity and “associated biodiversity”; together these two elements make up agrobiodiversity .

Components of the agrobiodiversity within DFS interact with one another and/or the physical environment to supply critical ecosystem services to the farming process, such as soil building, nitrogen fixation, nutrient cycling, water infiltration, pest or disease suppression, and pollination, thereby achieving a more sustainable form of agriculture that relies primarily upon inputs generated and regenerated within the agroecosystem, rather than primarily on external, often nonrenewable, inputs . Spatial considerations are important, since different components of the system must be in sufficient proximity, at each relevant scale, to create needed interactions and synergies. For example, the utility of intercropping for reducing below ground soil disease depends on spacing the different crops such that their root systems interact . Similarly, wild bee communities can only provide complete crop pollination services when a sufficient proportion of their natural habitat occurs within a given distance of crop fields . A DFS is not only spatially heterogeneous, but is variable across time, due both to human actions , and natural successional processes. Figure 1 presents the conceptual model of a DFS. The term agroecology goes back more than 80 years and originally referred to the ecological study of agricultural systems . Much agroecological work seeks to bring Western scientific knowledge into respectful dialogue with the local and indigenous knowledge that farmers use in managing ecological processes in existing agroecosystems . More recently this hybrid science has evolved to include the social and economic dimensions of food systems .

Partly in response to the industrialized agriculture of the Green Revolution , agroecology also came to mean the adoption of sustainable agricultural practices , and became an integral component of various social movements seeking alternatives to industrial agri-food systems. Thus agroecology currently holds multiple meanings, and can refer to an inter- or transdisciplinary science, a set of sustainable farming practices, and/or a social movement . DFS is not an alternative to agroecology. Rather, DFS is a framework that draws from agroecological, social, and conservation sciences to focus analytical and action-oriented attention toward farming systems in which cross-scale ecological diversification is a major mechanism for generating and regenerating ecosystem services and supplying critical inputs to farming. Agroecological principles and methods can be used to evaluate DFS and to design or revive processes of diversification . In this essay and series of articles, we explore the ramifications of DFS for both ecological health and socioeconomic welfare, as well as examining the intersection of DFS with existing industrialized agricultural systems, supply chains, and national and international policies. DFS are complex social-ecological systems that enable ecological diversification through the social institutions, practices, and governance processes that collectively manage food production and biodiversity . As many political ecology scholars emphasize, ecosystems are densely interconnected with social relationships . Ecological variables such as soil, water, and habitat help configure an array of farming practices, exchanges of food and resources, and landscape management decisions that, in turn, influence the structure and function of the ecosystem. Further, as ecosystem services are generated and regenerated within a DFS, the resulting social benefits in turn support the maintenance of the DFS, enhancing its ability to provision these services sustainably . This interplay underlies numerous historically occurring and emerging DFS worldwide. Conversely, socio-political and economic processes such as the decrease of access and control over seeds or increased dependence on commodity markets can intervene to disrupt such feedback cycles, thus weakening DFS. The industrialization of agriculture has led to growing homogeneity across food systems as farming techniques and markets become more standardized .

As a consequence, the complex social relationships underlying agriculture and ecosystem service provision have become less visible. Focusing on DFS can help farming communities, researchers, policy makers, and industry recognize and restore these relationships. At their core, DFS depend on agroecological principles that are developed in and through the social relationships among working farmers, their communities and environments, and researchers, including ecologists, anthropologists, agronomists, and ethnobiologists . As seen in the Kreman et al. examples these principles take varied forms depending on local conditions. To understand how DFS may develop, function, and evolve over time and space, the particular context of each DFS needs to be studied, paying particular attention to the politics and power relations that reciprocally shape its ecological conditions. Many DFS were developed through traditional and indigenous farming knowledge and agrobiodiversity that was accumulated over millennia . More recently, other DFS have been created through targeted agroecological studies designed by scientists to solve particular problems . Historically, much knowledge about biologically diverse farming practices has been created and shared through peer-to-peer learning within traditional farming communities and, more recently, also through their collaboration with researchers interested in further developing agroecology . These relationships continue to be critical to the growth of DFS in new societal contexts and geographic locations. Since the 1980s, with the rise of the Campesino-a-Campesino and La Via Campesina movements, institutions such as government agencies, domestic and international NGOs, and universities have become increasingly active in promoting and diffusing agroecological principles through research networks and programs . These actors have added new institutional dimensions to the social relationships that help sustain DFS. An illustration of how social and ecological systems interpenetrate within DFS is in the Andean highlands, where indigenous farmers have managed their lands agroecologically for 3,000 years . The ongoing interplay between human management and physical ecology has created a landscape of agroclimatic belts at different altitudes, each characterized by specific field rotation practices, terraces, and irrigation systems, and the selection of specific animals, crops, and crop varieties . Within these belts, traditional knowledge has helped sustain tremendous genetic diversity, by perpetuating adapted land races and wild relatives of crops. Social cooperation is essential to managing the verticality and heterogeneity of the Andean ecosystem. A barter economy based on reciprocity, for example, facilitated complementary exchanges of plants and animals between ecological zones along the steep elevation gradient . In industrialized systems in both developed and developing countries, farmers must now negotiate with corporate food buyers, buy agrochemical and seed inputs from agents, seek loans from bank officials, and work with agricultural extension experts trained in pesticide use. Farmers rely on such relationships to compete effectively in supply chains and to manage changing ecological conditions, such as pest outbreaks. Nonetheless, these particular types of relationships often push individual farms to increased dependence on banks, damaging livelihoods, and undermining collaborative social learning groups as farmers specialize in a single crop and maximize short-term yields through the use of external inputs, to meet loan repayments.

The economic pressures in these tightly linked systems generally corrode ecosystem services, which are the very foundation of support for potential DFS. Farmers in industrialized systems may also engage in exploitative relations with immigrant or impoverished laborers, paying inadequate wages and enforcing long hours,flood and drain table helping perpetuate the apparent cheapness of food. Industrial production creates a number of “distances” between producers and consumers such that information flow diminishes across the supply chain . Thus within the industrial agri-food system, consumers remain relatively ignorant about the conditions of production, and would be less able to choose between products based on sustainability criteria, if they value these, and to exercise their buying power in favor of DFS. In turn, the risk perceptions of consumers and corporations may inhibit the growth of DFS. For example, during the recent food safety scare in fresh leafy vegetables in California, corporate buyers insisted that growers remove native vegetation bordering fields that might attract wildlife. This action was taken largely to assuage consumer concerns, despite the lack of scientific support . In alternative agricultural systems such as organic or low-input farming, farmers can build particular forms of relationships that help sustain ecosystem services and social infrastructure more effectively. We discuss many of these relationships, including direct marketing, fair trade certification, and food justice movements. In developing and studying these alternative systems, however, researchers, policy makers, and NGOs often neglect race, socioeconomic, and gender issues, or sublimate them into a broad social justice category. Finding ways to be far more inclusive of diverse racial, gender, and socioeconomic groups can help strengthen the socialecological basis of agriculture. For instance, African-American growers once represented a sizable proportion of the U. S. farmer population, or one million in 1910, declining to 18,400 by 1997, due to race discrimination and violence, lack of land tenure , and multiple waves of economic migration from the South to urban centers . Many of these black farmers used DFS practices; their displacement helped create an opening for industrialized monocultures. Now, many new farmers in rural and urban areas are black, Latino, or Asian; there is evidence that these farmers are more likely than their established peers to embrace sustainable agriculture practices if adequately supported . Immigrants such as the Hmong may sometimes develop culturally relevant, more diversified food production enclaves within industrialized systems that preserve their traditions and provide livelihoods.They are developing new linkages between cities and nearby rural areas, potentially helping recreate DFS. For example, Will Allen founded Growing Power, an urban farming NGO that serves disadvantaged neighborhoods in Milwaukee and Chicago, attempting to encourage youth of all races to take up diversified farming. In Chicago, black activists and physicians have formed the Healthy Food Hub, a food aggregation NGO which sources produce from a historically black farming community, Pembroke Township, about an hour from Chicago. These efforts show how people can demand greater political agency in building a democratic DFS . New quantitative and qualitative research is badly needed to evaluate and critique the social benefits that DFS may provide in contrast to industrialized systems. In general, further analysis is needed to understand how the social elements of DFS can help generate and regenerate ecosystem services, thus maintaining diversified farming systems. In turn, more research is required on the political and socioeconomic interventions that could help rebuild or sustain the socialecological cycles that underlie DFS.DFS are often embedded in social, political, and economic conditions that differ from those accompanying industrialized monocultures , particularly with respect to core stakeholders, markets, and distribution systems. Yet, DFS may not always be able to realize their potential social-ecological benefits due to the lack of enabling environments. We explore how alternative agri-food networks and social movements relate to DFS and assess their potential to both maximize social benefits and promote DFS through their demands for food sovereignty and food justice. The agri-food systems approach reveals the interconnected systems of inputs, labor, land, capital, governance and knowledge that maintain specific types of agricultural production, distribution, and consumption systems . The governance and structure of the food system upstream from the farm, such as international agricultural trade liberalization policies that promote cheap food imports from industrial into developing countries, government subsidies for fossil fuel-based agrochemicals and commodity crops and irrigation projects that primarily benefit larger landholders , all help to maintain the industrialized agri-food system .

Coupling with landscape microclimate models provides not only the vertical inputs used by agricultural models, but also gradients along the landscape. Coupling with hydrological models provides water flow paths such as surface runoff, vertical and lateral groundwater flow, and interactions between shallow soil and groundwater zones and with adjacent surface water bodies . Water quality models provide sediment and solute transport along the landscape controlled by water flows, and other effects such as wind erosion. Integration and upscaling of landscapes into the watershed scale requires three-dimensional coupling of the surface and subsurface water, energy and mass transfers. Condon and Maxwell and Maxwell et al. provide more details on coupled versus integrated models. At this scale, the groundwater aquifer system typically transcends the boundaries of the watershed, necessitating regional scale analysis to evaluate not only the impacts of cropping and animal production systems on water quantity and quality, but also feed backs from the hydrological system into the agricultural system . Further, meso-scale rainfall and evapotranspiration distribution models control the local surface and subsurface flow intensities, pollution and abatement . At this scale, human effects through land use changes, and ecological dynamics and transitions on natural or protected lands are also important components needed to evaluate overall sustainability of agricultural systems .Although some efforts have gone into integrating biophysical models ,mobile vertical rack more is needed to enable comprehensive assessments of agricultural systems across scales and adequately address environmental and economic responses to decisions and policies.

The need to address decisions and policies at scales arises frequently in agricultural system modeling. Resolving the time and space scale differences among model components is often a major issue, particularly when component models are developed independently for different purposes. This problem arises, for example, when one attempts to create a model that combines crop and hydrology models, crop and economic models, or crop and climate models . There have also been efforts, starting in the early 2000s, in which dynamic models have been developed to provide forecasts over aggregated areas . Traditionally, climate model output for a grid cell is down scaled to produce weather data time series for points that are then fed into crop models. However, the land surface also influences climate; processes within the atmosphere and oceans, and on the land, are coupled and dynamically interact over space on timescales from fractions of seconds to thousands of years. Crops are a major component of the land surface of the globe, occupying about a quarter of all land area. Regional climate can be sensitive to large-scale changes in cropped areas that can result from changes in economic or climate conditions . Therefore, another direction for agricultural impact assessments at a large-scale is to dynamically couple crop simulation with models of land and atmospheric processes.Osborne et al., 2009 showed that, in some parts of the world, the impact of changes in cropped area on regional surface temperature can be of the same magnitude as regional human-induced climate change.

This result raises the question of whether or not new fully-coupled climate change impacts studies will revise our previous estimates of food security impacts. It is clear that the full coupling of crop simulations within global climate models is opening up new possibilities for studies of the impact of climate change on agricultural production – studies that capture some of the complex and important feed backs within the Earth system at a large scale. Limitations in the skill of large-area modeling of crop production and yield is dominated by the density of data used in the simulation. More data should equate to better skill. However, the skill of large-scale modeling is determined by the smallest data set, whether this is the grid cell with the shortest run of observed yields, or the data grid with the largest resolution . We have seen recent increases in the resolution of climate input data and global grids of crop management and soil information. In this field of agricultural modeling, any future increase in data resolution should produce more skillful model simulations.We next discuss the state of current agricultural system science relative to its capabilities and limitations in providing information to assist a wide range of decision makers represented by the five Use Cases. Each Use Case contains a set of interactions between systems and users in a particular environment in a systems analysis. The Use Cases are for developing and developed country settings, demonstrating a range of needs for widely different applications at different scales and levels of intensification. Antle et al. indicated that these Use Cases need crop, livestock, and farming system models. The question that we address here is whether current agricultural system models, existing sources of data, and existing decision support systems are adequate for providing information needed for these Use Cases.Can existing crop, livestock, and farming system models, data, and ICT tools provide the information that Sizani needs to advise the small farmer? The short answer is “No”; there are currently no easily accessible and usable applications that would allow her to analyze the particular farmer’s situation. Or apps that can connect with models in the “cloud” to make runs needed for her to advise the farmer. Although there are models that partially meet her needs, and there are well documented examples of using models to develop insights on productivity enhancement strategies in the face of resource constraints and climate risk they have not been integrated or are not packaged for use by this type of non-expert user.

Models can, for example, simulate responses of crops to soil and weather conditions as well as water and nitrogen fertilizer input but do not generally simulate actual yield in production situations where, weeds, pests or diseases are not controlled. Two of the most serious limitations of many crop-soil models are their inabilities to accurately simulate soil infertility and their failure to represent losses associated with the wide range of pest, disease, and weed species that damage crops. In many intensive production systems, soil fertility, weeds, pests, and diseases are controlled so that responses in those situations can be represented by the costs of management inputs and the production responses to climate and water management. Typically, cropping system models simulate yields that are higher than actual yields in farmers’ fields, which are reduced due to poor management. In addition, fields are usually not homogeneous; for example, spacing between plants may vary considerably,whereas the models assume homogeneity. However, if pest and disease data are observed and available, these data can be input to some existing crop models to compute yield loss associated with specific pests and to diagnose the reasons for the gap between potential and actual yield . Keating and McCown have shown, however, that expert application of well adapted models can still lead to useful insights on many of the key constraints to productivity enhancement in small-holder situations. Generally, farming system models now in use have some capabilities needed to analyze this Use Case. However, most farming system models are not developed to be easily implemented by non-expert users nor for farms with characteristics different from those for which they were developed. An exception to this is the TOA-MD farming system model , although that model also needs reliable data from farm surveys to simulate a population of farms in contrast to a particular farm.It is impractical for Sizani to collect information on a particular farm, go back to her office and work with an analyst to evaluate options for the farmer. Instead, data are needed to describe a range of farming systems so that she could select the combination of biophysical, farming system, and household characteristics from available data. This would include information to allow her to tailor inputs to most closely match the conditions of specific farms. This includes climate, soil, management practice, labor and other inputs available for production and marketing of outputs, typical pest and disease pressures, availability and prices for farming inputs, and other farm, economic, and environmental information. Generally, sufficient data on the biophysical, environmental, and socio-economic conditions of each farm or for a range of farm typologies in the regions are not available. Although some data, such as climate and soil data, are available, generally these are not organized nor are they sufficiently site-specific that agricultural systems models can readily access them for analysis of specific farms. Although research has shown that some analyses needed to advise a farmer can be made, the availability of input data for agricultural systems models remains a major limitation.Most existing DSS tools that are available in Apps are focused on relatively narrow issues ,vertical grow rack such as when to apply a fungicide to a particular crop, when to apply the next irrigation, or how much N fertilizer to apply to a particular crop that will be grown on a particular type of soil in a specific setting. There are few DSS tools that make use of more integrated models to help advisors advise farmers in making farming system decisions . We envision a DSS platform that will connect various models, databases, analysis, and information synthesis tools in an easy-to-use interface for Sizani to set up the analyses and outputs to answer questions about the management of that particular farms’ biophysical and socioeconomic situation and the uncertainties in those estimates. Such DSS platforms are possible, but not yet constructed.Models of maize and other crops, livestock, and the farm household are also needed for this Use Case. These models are available for at least partially performing this type of analysis. Starting in the 1980s, several groups began using crop simulation models to evaluate alternative management systems in developing countries .

Models used in those efforts were generally based on CERES and other crop models now in DSSAT and on the ORYZA rice model developed by IRRI. More recently, the Global Futures and Harvest Choice CGIAR research projects led by the International Food Policy Research Institute have used crop and economic models to evaluate the potential benefits of developing new technologies, including new crop varieties . For example, Singh et al. used the DSSAT CROPGRO groundnut model with climate and soil inputs at six locations in India to evaluate different crop traits being targeted by CGIAR plant breeders. They found that the effect of combining various traits was beneficial, with estimated yield gains varying, depending on location and climate change conditions. Rapid advances in biotechnology and molecular plant breeding are helping researchers incorporate molecular markers and genes into models so that ultimately genetic composition of crops can be used to predict performance of future varieties to help target expensive and time consuming plant breeding efforts . The paper by Hwang et al. presents some concepts now being explored for next generation crop models. Similarly, considerable work has been done on farming system models to evaluate options for improving the livelihoods of farmers. These include farm simulation models , optimization models that attempt to select the best combination of enterprises and their management to achieve one or multiple goals of the farmer . Also, the Trade off Analysis model is currently being used as the basis for model-based impact assessments . Furthermore, this approach can incorporate results from crop and livestock models, as well as environmental and social outcome models, and it can be adapted for smallholder or large commercial farming systems. However, there are important limitations in the capabilities of these models, similar to those mentions in Use Case 1 Thus, there may be large yield gaps between actual yields in farmers’ fields and the potential productivity in those fields . When water, nitrogen, and climate are the major limitations in crop productivity, current models are highly useful, assuming that soil, weather, cultivar, and management input data are available for the analyses. In this Use Case, it is likely that other factors, including other soil nutrients, pests, diseases, and weeds, need to be taken into account. The challenge for next generation models includes not only modeling those factors but also collecting data that describe the production situation with all of the important yield-limiting and reducing factors. Another question is whether existing biophysical models can predict performance of the wide range of intensification options that may be used by farmers for this Use Case.

A variety of labels have been used for this emergent industry: precision agriculture, e-agriculture, smart agriculture, and digital agriculture, among others. Despite early critical use of precision agriculture, the term tends to be used in the industry to signify a specific suite of production-oriented technologies.However, information technologies are also used to open new markets and new territories for production. For example, digital platforms have become increasingly important for individual producers to bring their goods to market. Figure 1 shows how information technologies are intertwined throughout the cycle of agricultural production and sale.We use digital agriculture for its semantic breadth and increasing currency. In our taxonomy, precision agriculture is a subset of digital tools which improve efficiency through careful management of inputs. Three other types of tools—marketplace and financial platforms, e-extension, and smallholder management—are typically platform-based systems that mediate the social relation between farmers and the outside world. Marketplace and financial technologies help farmers access new credit lines and optimize their market behavior. E-extension is the digitalization of the practice of implementing technological innovations through farmer education, particularly in the international development context. E-extension, like the analog version that preceded it, dutch buckets system is largely reliant on insights produced far from the farm.

Finally, smallholder management platforms allow larger agribusinesses to exert control over smallholder farmers through close management of their inputs, products, and so forth. This may allow major actors to divest themselves of the risk inherent in owning land and instead subcontract smallholders in a relationship analogous to other platforms in the gig economy.For digital agriculture’s boosters, it has the potential to be the much-needed “fourth agricultural revolution” . In particular, it is framed as a climate-friendly way to feed the world and improve the lot of farmers around the world. By making the application of inputs more efficient, digital agriculture can indeed lessen the environmental impact and yield of agriculture. By increasing input efficiency and improving knowledge of market demand, digital agriculture may indeed improve the fortunes of producers. The rhetoric is not dishonest, but it is incomplete.Optimizing inputs enables the continued use of ecologically-harmful chemicals and practices, which would otherwise be abandoned if their effects were not actively mitigated . Digital agriculture’s marketing claims it will improve efficiency, increasing yield and minimizing the use of inputs—many of which are harmful and unsustainable. The externalities produced by using these inputs are the “un- and undervalued costs of industrial capitalist agriculture” .

A team at Cornell, for example, has developed a model that recommends ideal fertilizer application rates for each section of a farmer’s field in order to minimize nitrogen run of into the Gulf of Mexico, which causes algal blooms, depletes oxygen levels in the water, and kills fish and wildlife.While optimization limits the short-term damage of unsustainable practices, it also makes those practices more politically permissible and financially feasible. Thus, by making unsustainable practices appear sustainable, the necessity of adopting more ecologically and socially sustainable and just practices is delayed. By focusing on input management, these technologies advance a limited interpretation of sustainability that still depends on of-farm inputs, rather than a more radical shift to permanently sustainable practices . Just as digital agriculture promises to minimize inputs, it also promises to maximize yield—yet yield is not the problem. In the 1970s Amartya Sen noted that while starvation was increasing globally, food per capital was also increasing —as population grew, food production grew at a greater rate, not only globally but even regionally. While some scholars have taken issue with Sen’s empirical basis, an updated analysis using 2010 statistics found the same results . The direct relationship between hunger and food per capital, when we would expect an inverted one, betrays the simple thesis that hunger is due to a lack of food availability. Instead, Sen attributes hunger to an inability to exchange for food. Davis similarly notes the disconnect between food availability and hunger, finding that famine can occur in areas of grain surplus because it is more attributable to rural food management and exploitation than to production .

The “solution” to hunger, then, lies not in yield. Yield has increased; food per capital has increased; hunger persists. Therefore, stretching yield through digital agriculture is insufficient and does not address the political-economic basis of systemic hunger.The third key claim made by digital agriculture’s boosters is that it will improve farmers’ welfare, in particular their profits. Profits may be found in better decision-making, better yields, and better access to market information . In the Global North, such increased profits may be plausible. However, a primary mode for digital agriculture, the platform service, means that the data produced typically becomes the property of the platform provider. Weersink et al. note that a key challenge for digital agriculture is making this data useful; this, in turn, may favor larger companies with the capacity to process the data. Bronson notes this dynamic and warns that it may reproduce the distributional effects of the Green Revolution—that is, to concentrate wealth and power in the hands of major agribusinesses. In the Global South, digital agriculture presents a different set of problems for farmers’ welfare. Technological innovation that increases a crop’s yield in turn increases supply and undercuts the socially necessary labor time required to produce it. This dynamic lowers the crop’s exchange value at the expense of those at the bottom of global commodity chains, in particular the growers’ compensation per unit of crop. As this price drop is not accompanied by any increase in production for farmers without access to this technological innovation, this drop translates to lower overall compensation and to “exchange entitlement decline” . If they depend on exchange for subsistence, the decreased compensation translates to hunger as well.In reflecting on these mainstream claims, a different theme emerges. Rather than sustainability, nourishment, or farmer welfare, digital agriculture is fundamentally about securing the conditions to generate profit in the food system. Crucially, however, this is not about profit in food production alone, but in the wider capitalist economy for which food is obviously a fundamental input. Therefore, we submit that digital agriculture must be understood as addressing a specific set of crisis tendencies that have emerged at a particular juncture in the social, ecological, and spatial history of capitalism. This juncture is defined by interlocking moments of ecological disaster; enormous advances in information production, gathering, and processing; and “hypertrophic” urbanization . In this section we argue that rather than a solution to the climate crisis, hunger, or farmer welfare, the rise of digital agriculture can better be understood as an attempt to overcome crisis tendencies of “the relentless growth imperatives of an accelerating, increasingly planetary formation of capitalist urbanization” .

After briefly excavating the informational dynamics latent within the framework of extended and concentrated urbanization, we describe how digital agriculture functions as a “data fix” by allowing the intensification of agricultural industrialization and the extraction and enclosure, for eventual profit, of the data produced by digital agriculture technologies. An early theme in globalization literature was a tendency to embrace the rise of information technologies in a way that dematerialized the now planetary systems of extraction, production, and consumption . Such concepts, however, have largely been absorbed by analyses which show that a deterritorialized “information society” is not displacing traditional modes of production and social relations as much as emerging as a financial-managerial stratum in a “new international division of labor.” Another major theme in globalization studies is the ‘global city network,’ a set of nodes in the global space of flows from which the global economy could be commanded and controlled . In describing such cities as “strategic sites where global processes materialize” , they appear to be material sites floating in a sea of immaterial processes. In this model, cities are simultaneously the result of, yet alienated from, specific material processes— such as agricultural production—taking place beyond their bounds. In both concepts the informational nature of globalization is over-emphasized at the expense of its material effects. In an era of climate crisis, this shortcoming is glaring.One response has been to radically reframe globalization as a material process of urbanization,dutch buckets which unfolds as the product of dialectically-entwined moments of extension and concentration . Concentrated urbanization signifies the moment of agglomeration where the material flows of global capitalism accumulate into cities, megalopolises, and mega-regions. On the flip side, extended urbanization is the moment where remote territories are enclosed and transformed into operational landscapes that funnel energy, materials, and food into areas of accumulation. Both moments cause and are caused by the other: “The urban unfolds into the countryside just as the countryside folds back into the city” . Global capitalist urbanization is a metabolic process of moving and consuming the material world . This involves both fragmentation and homogenization —for example, the simultaneous expansion of monoculture agriculture and of liberal private property regimes. At the same time, enclosure and technological advances deprive peasants of their livelihoods; ‘depeasantization’ is the mirror of urbanization. However, the desire to develop a more materialist model of globalization leads to the black-boxing of information‘s role in facilitating vast networks of production and exchange. To bring information back in requires recognizing that something happens at the moment of concentration which sets the stage for extension. In the present framework, production and the growth imperative drive a search for more raw materials. But extension also depends on informational infrastructure to make a massively decentralized network of global supply chains profitable. Indeed, another way to describe capitalist geography is as “a skein of somewhat longer networks that rather inadequately embrace the world on the basis of points that become centers of calculation” . Information, along with material, is being drawn inwards in the moment of concentration; the processing of raw information—which is “what remains after one abstracts from the material aspects of physical reality” —into actionable knowledge informs extension processes. “Information processing” is computation, and computation at the scale required to make legible the vast amounts of data produced in the contemporary economy involves enormous physical infrastructural investment in data centers, undersea cables, and satellite networks . Such computational capital consists also of intellectual and human capital in the form of models, algorithms, and the expertise to deploy them.

There is a potential for the over accumulation of computational capital, however; as a result, there is a constant drive for firms to find productive outlets. This is what leads firms like Amazon, Microsoft, Google, Oracle, and Cisco—as well as funds invested in and consultancies hired by them—into digital agriculture. By locating, extracting, and enclosing data relevant to another materially productive sector , a firm like Amazon—whose cloud computing infrastructure Jef Bezos has compared to power utilities—can continue to grow. This applies at the worker level, too. Just as a glut of NASA-trained engineers and physicists became quants for hedge funds after the Space Race , a glut of software engineers and data scientists which Silicon Valley cannot absorb find employment outside of the tech sector, including at digital agriculture startups or divisions within larger agribusinesses. Indeed, agribusiness are planning for a future in which they become tech companies themselves: the head of digital agriculture at Bayer Monsanto, for example, has described the future of the conglomerate as a digital platform . The fundamental material crisis that digital agriculture attempts to fix through the manipulation of data is in the sociol-metabolic processes of capitalism and capitalist urbanization. To support social reproduction for a growing non-agrarian population, present-day industrial agriculture destroys its own ecological foundations. As the consequences of climate change become ever more apparent and render growing conditions ever more difficult, a new ecological regime is needed to prolong the production of cheap food and ensure future accumulation in the face of known crises . But not only is fossil fuel-based industrial agricultural production partially responsible for climate change—up to one-fifth of all greenhouse gas emissions—it also exhausts the ecologies within which it is practiced. The search for the fourth agricultural revolution is not a straightforward matter of addressing a Malthusian crisis of natural population growth, but a crisis of capitalism itself. This crisis tendency arises from capitalism’s dependency on the “four cheaps”— labor, food, energy, raw materials—to maintain each cycle of accumulation.

During the rest of the year, there are much less employment opportunities for rural than urban households, with the former working about half the time worked by urban households during the low season . Lack of labor smoothing across months can thus be a major cause of income differentials between rural and urban households. Measuring annual labor productivity as median household real consumption per capita, rural households are at 57% of individuals in urban households. When this is measured not per year but per hour worked, rural households are at 81% of individuals in urban households. With high urban unemployment in Malawi limiting the option of reducing rural poverty through permanent or seasonal rural-urban migration, this suggests that a key instrument for rural poverty reduction is to have less idle time for land and labor throughout the monthly calendar. For Bangladesh, Lagakos et al. proposed filling labor calendars for rural households through migration to cities during the lean season. When this option is not available due to high urban unemployment filling and smoothing labor calendars in rural areas becomes a key dimension of poverty reduction. This can involve employment both in agriculture with more diversified farming systems and in the local rural non-farm economy. This is the purpose of the agricultural and rural transformations that are important in redefining how to use agriculture for development.

Based on work done for the IFAD Rural Development Report led by Binswanger, for China by Huang , by BRAC on graduating the ultra-poor out of poverty ,nft hydroponic for the Gates Foundation by Boettiger et al. , and for the ATAI project , a strategy of using agriculture for development would involve the following five steps: Asset building, Green Revolution, Agricultural Transformation, Rural Transformation, and ultimately Structural Transformation as described in Table 1.Minimum asset endowments for SHF under the form of land, capital, health, knowledge and skills, and social capital are needed to initiate production for the market and participation in a value chain. This corresponds to minimum capital endowments to get started in production in farm household models such as Eswaran and Kotwal’s , and to asset thresholds to escape poverty traps in Barrett and Carter . The BRAC graduation model for the rural ultra-poor thus importantly starts with achieving minimum asset thresholds for households to engage in self-employment in agriculture , with rigorous impact evaluations demonstrating success in raising household consumption in five of six case countries. Evaluation with a randomized experiment of a BRAC credit program for landless workers and SHF in Bangladesh shows that loans can be used to achieve minimum asset endowments by renting land and selecting more favorable fixed rent over sharecropping contracts . The Green Revolution, whereby productivity growth is achieved in staple crops through the adoption and diffusion of high yielding variety seeds and fertilizers is the initial step in agricultural modernization. It has been actively pursued to achieve food security and is a learning ground for the subsequent transformations of agriculture and rural areas.

It has been a major success of the Consultative Group in International Agricultural Research and is still an ongoing effort in Sub-Saharan Africa and Eastern India. A key objective of the Agricultural Transformation is to fill in rural households’ labor calendars over as much of the year as possible through multiple cropping — which typically requires water control to cultivate land in the dry season–, the development of value chains for new crops, and contracting among agents in these value chains. An example is the introduction of short duration rice varieties in Bangladesh that frees the land for an additional crop, typically high value products such as potatoes and onions, between rainy season and dry season rice crops. This makes an important contribution to filling land and labor calendars and to reducing the length of the hungry season . Because the Agricultural Transformation implies diversification of farming systems, it is a key element of national food security strategies where diverse diets, including perishable goods such as fruits and vegetables, dairy products, and meats that are less traded than staple foods, are an important element of healthy diets . SHFs are engaged in value chains that define the way they relate to markets. Value chains for agricultural products link farmers backward to their input and technology suppliers and forward to intermediaries, processors, and ultimately consumers . Relations within value chains often take the form of contractual arrangements. Induced by income gains for consumers, urbanization, and globalization, there has been in recent years a rapid development of value chains not only for low-value staple food crops, but also for medium value traditional domestic consumption and export crops, and high-value non-traditional export crops. Their structure can take a wide variety of forms in linking SHF to consumers, ranging from traditional spot markets to elaborate contract farming, productive alliances , and out-grower schemes.Contracts can be “resource-providing”, thus contributing to solve market and institutional failures for participating SHFs.

A key objective of the Rural Transformation is to give access to smallholder households to sources of income beyond agriculture. In Ghana, income derived from the rural non-farm economy for rural households is about 40% of total income, a share that increases as land endowments fall . It is indeed the case that, with land limitations, smallholder households rarely exit poverty with agriculture alone. A rural transformation requires the development of land markets and of labor markets . This process will typically happen first in the more favorable areas where a rural non-farm economy linked to agriculture can develop through forward, backward, and final demand linkages. It corresponds to the Agriculture Demand-Led Industrialization strategy advocated by Adelman and Mellor that is actively pursued in countries such as Ethiopia and Rwanda, and through CAADP in much of Sub-Saharan Africa. There are basically two contrasted approaches to potentially overcoming the problems that obstruct an Agriculture for Development sequence. The first consists in focusing on particular groups of farmers and addressing each of the problems in their own shapes and forms that affect them in modernizing. We can label this a “supply-side” approach to modernization and transformations. It consists in securing the existence and profitability of innovations, ensuring their local availability, and then overcoming each of the four major constraints to demand and adoption through either better technology or through institutional innovations . The agents for this approach are principally public and social such as governments, development agencies, NGOs, and donors. The second consists in creating incentives for SHF to modernize by building value chains for the particular product, and managing vertical and horizontal coordination within the value chains to overcome the profitability-availability-constraints obstacles as they apply to inclusion and competitiveness of SHF in the value chain. This is a “demand-side” approach to modernization and transformations. It consists in creating the demand for innovations in order to establish SHF competitiveness within a value chain, and then securing the existence, availability, and conditions for adoption of innovations. The approach thus requires both value chain development and value chain inclusion of SHFs. In this case, the agents are principally private such as enterprises and producer organizations for contracting, and lead firms, multi-stakeholder platforms, and benevolent agents for coordination. Public-private partnerships can be found among both supply- and demand-side initiatives.Technological innovation are first analyzed in experimental plots, usually for yield and resilience to specific shocks. But this does not tell us whether the innovation is likely to be adopted by SHF. Analysis of the adoption problem should start with verification that the innovation is indeed profitable for the intended SHF under their own circumstances, objectives, and capacities. Measuring profitability in farmers’ plots is however very difficult . There are data problems in observing family labor time and definitional problems in establishing the opportunity cost for family labor and self-provided inputs. Conditions also vary year-to-year due to weather conditions, with only short time series to observe how climate affects outcomes, made even more difficult to interpret with climate change. And there are many unobservable conditions and complementary factors that affect profitability and compromise the external validity of any measurement made at a particular time and place. An alternative approach is to verify profitability without measuring it. Some among the best endowed and best located farmers have to be able to make sustained use of the innovation for the innovation to have adoption potential by others under current market, policy, nft system and complementary input conditions. This can be established by observation, experimentation, or simulation.

Once the innovation is proven profitable and is locally available, its adoption may still be hampered by constraints facing SHF in accessing liquidity, risk-reducing instruments, information, and markets. These four categories of constraints have been extensively analyzed using in particular randomized control trials to identify their causal relations to adoption . These studies typically seek to identify ways of overcoming these constraints that could be implemented by governments, international organizations, NGOs, and benevolent agents such as philanthropic foundations and corporate social responsibility initiatives. Due to seasonality, especially under rainfed farming conditions which is where most of the lag in modernization currently prevails , there is a lack of correspondence between the timing of agricultural incomes and that of expenditures. As a consequence, the inter-temporal displacement of liquidity through credit and savings appears to be important for farmers to invest in new technologies, purchase inputs, optimize the timing of sales, buy consumption goods, and cover timely expenditures such as school fees. Financial services for SHFs appear to frequently be ill-designed for their purpose, expensive, excessively risky, and not easily available. Even when they have formal land titles, SHF are typically unwilling to put their land at risk as collateral with a commercial bank, thus acting as “risk constrained” . Microfinance products that effectively circumvent the collateral problem by relying on group lending and joint liability tend to be too expensive for the long agricultural cycles and have repayment conditions that are typically ill adapted to the timing of farmers’ capacity to pay . Availability of credit from formal sources, both commercial and non-profit, is consequently limited, and SHFs must either self-finance or rely on informal lenders with prohibitive interest rates. Hence, there would appear to exist a largely unresolved liquidity constraint on adoption originating on the supply side of the financial market. Yet, this is often not the main reason for low adoption which may be on the demand side. Recent field experiments are providing evaluations of interventions aiming at relaxing the liquidity constraint on SHFs, with fertilizer the most commonly used indicator of technology adoption because of its ubiquitous recognition and yet massive under use. While contexts and interventions vary for these experiments, they surprisingly tend to show that a liquidity constraint is not the reason why a majority of SHFs are under-investing in fertilizers. The main constraint may be instead lack of profitability in adopting fertilizers.A first category of experiments consists in providing unrestricted access to credit to a defined eligible population, as was done in Morocco , Mali , and Ethiopia . While interest rates in these studies were variously subsidized , uptake remained low: only 17% of eligible farmers took a loan in Morocco, 21% in Mali, and 36% in Ethiopia. Furthermore, farmers that did take a loan only used a small fraction of the liquidity to increase their expenditures on fertilizer or other agricultural inputs . Other experiments offered restricted credit that can only be used to purchase agricultural inputs. Such credit displaces the equilibrium allocation of liquidity in favor of the targeted inputs, similarly to what a price discount would do. And yet, uptake remained low. In Malawi input credit for high-yielding maize and groundnuts was taken by 33% of the farmers . This low demand for credit thus seems to be reflective of a low demand for the inputs themselves. Low demand for fertilizer is exemplified in two rather extreme experiments. In Mali, Beaman et al. provided to another group of farmers a pure cash grant, rather than the credit described above. This only increased expenditures on fertilizer by 15%, in comparison with 11% with a credit that had to be paid for, showing that credit is not the major constraint to adoption.

International experience shows that in the long run, increased foreign participation in the financial sector will have a positive effect on country’s development as a whole. However, in the period immediately following its WTO accession and the removal of protective measures in the financial sector, China may face one of its biggest challenges. There is a good possibility that the nation’s banks will suffer financially. Hence, it might be expected, the leader’s policy response to reform the current banking system will be a strong one. For example, financial sector officials are already mandating the government interventions fall, state banks recapitalize themselves, and nonperforming loans be transferred to asset management companies.While one might think the agricultural sector and poor regions in the rural economy could suffer from liberalization, it is not clear if things will be worse than before the reforms. In the past, agriculture in China was squeezed. Huang and Ma have shown how the financial sector has systematically shifted funds away from faming. Throughout the entire reform period, there was a net capital outflow by means of the financial system. Hence, it is hard to see how a reformed banking sector will treat agriculture any worse. Though,flood and drain table the experience of other countries most likely mean that in the short run small, poor farmers will be rationed out of financial markets.

Tax reform also is underway. In 2001, there were three major types of taxes levied on products and services: a VAT levied on goods and services for processing, maintenance and assembling; a Consumption Tax levied on some selected consumer products; and a Business Tax on services and the sales transaction involving assets . Both the VAT and Consumption Tax are applied to imported goods. Tax laws, however, have offered producers several exemptions. In many cases, part or all of the VAT is reimbursed when the goods is exported. All goods to be exported are not subject to the Consumption Tax. Although subject to a number of technicalities, there is some concerns are some of these tax rebates may not be consistent with the requirements of the 1994 GATT rules. Since, China has agreed that it would ensure that its laws, regulations and other measures relating to internal taxes would be in full conformity with its WTO obligations, some adjustments may have to be made. Perhaps the best example of this may be in the area of the assessment of the VAT on agricultural imports and the possibility that such an act may violate the national treatment clauses of the WTO accession agreement. Specifically, while the VAT is charged in full at the border for all imports . Although some observers in China have tried to argue that since farmers in rural areas already pay high land- and head-taxes, they can fairly be exempt, such a tax is not commodity specific and such unequal taxation of imports and domestically procured crops almost certainly violates WTO. If such a tax policy is challenged, China will have two options: assess the VAT on all domestic procurement or eliminate the VAT at the border on agricultural goods. More generally, as China attempts to make it economy more competitive in a post accession world, it has announced that in some areas it will lower taxes. The primary objective would be to lower the burden of domestic enterprises and attract new foreign investment. Tax cuts would also increase the competitiveness of its domestic products in the international markets.

Moreover, tax officials also have plans to continue to push on tax reform that shift China from a system that primarily uses a production-based tax system to a more consumer oriented tax regime. While desirable, it should be noted that the timing of implementing this tax reduction necessarily will depend on the impacts that the reform would have on the government’s revenue-earning capacity. An official from the State Council recently claimed that a major move to realign China’s tax system towards a more consumer-oriented one may begin as soon as 2003. To make the rural economy more competitive and to remove a set of institutions that have historically caused a lot of frustration among rural residents, officials have also begun to experiment with rural tax reform. The most bold experiment to date is based on a movement that seeks to “convert fees into taxes.” The earlier experiments began in Anhui province in 2000. The reform was implemented to reduce the burden of various fees imposed on farmers to a maximum level of 5 percent of the income of farmers. By reducing the tax burden of the farmer, officials hope to reduce the cost of agricultural production, since many fees are collected from farmers by local government and village committee on the basis of their sown area or level of livestock production. Originally, it was planned to extend this reform from Anhui to the rest of China within several years after the start of the experiment. The State Council hoped to spread Anhui’s rural tax reform in one third of all provinces in 2002. However, recent problems with the system have appeared in Anhui. Although fees and taxes have been reduced, the fall in local revenues have limited the ability of the local government to implement a number of basic mandated expenditures, including the support of schools, health systems, and basic infrastructure maintenance. Recent government pronouncements have actually put the Anhui experiment on hold.

It is likely that successful implementation of such a policy will require substantial reforms in other areas and a basic change in the way that government fiscal resources are shifted to poor areas to support basic services.In one of its most fundamental concessions , China agreed to phase out its export subsidies in the first year of WTO accession. Such subsidies have played considerable roles in assisting with the export of maize, cotton, and other agricultural products into international markets and in this way indirectly supporting domestic prices. In fact, after phasing out export subsidies, several of China’s sectors will likely be subject to much intensive competition from imports. Besides the elimination of export subsidies—which are “Red Box” investments, WTO also puts strict controls on the types and amounts of certain investments. In particular, domestic support to agriculture is divided into “Green Box” and “Amber Box” ones. As is the case with other WTO members, China faces no limitations in the amount that the nation can invest into those activities classified as Green Box, but face carefully circumscribed rules regarding the amount that can be invested into those activities listed as Amber Box policy. Hence, WTO will most likely force China to shift the composition of their investment portfolio. In planning their Amber Box investments, China accession protocol allows a de minimis level of investment that is equal to 8.5 percent of agricultural gross value product. After intense negations this level was set somewhat below that enjoyed by other developing countries but above that allowed to developed countries . Moreover, the list of items that are used to in the computation of China’s AMS is wider than that used by other countries. For example, certain investment subsidies are not counted in the computation of AMS in developing countries. Developing countries also frequently can classify input subsidies for poor farmers as Green Box investments. Hence, on paper, China’s hands appear to be quite firmly tied in the scope of the investments that they are able to make after their WTO accession. However, when one begins to add up the amount of fiscal funds that China has historically invested in these areas, it may be that the de minimis limits will not be binding.The biggest impact could be sometime in the future after China grew and its budget constraint was somewhat relaxed. At that time, however, China’s agreement should be thought of as fairly limiting as it closes future options to support its rural areas in ways that its neighbors in East Asia have done . In a post-WTO environment, China’s leaders will give more thought to how it can best use its de minimis budget. Most recently, a study by Huang and Rozelle shows that although most labor intensive agricultural commodities,rolling bench such as livestock and horticulture, had negative NPRs in late 2001, the time just prior to China’s WTO accession, many land intensive products, including maize, wheat, oil seed crops and sugar, had NPRs ranging from 5 to 40 percent. Moreover, the crops with the positive NPRs are almost all under TQR management, a finding that has important implications how China may want to use its scarce AMS funds. Instead of continuing to support or subsidize these products, China may want to promote these crop productions through productivity enhanced investment measures, such as more agricultural research or transportation and communication investments. Since many of such investments have long gestation periods, the sooner leaders make the investments, the smaller the shock will be after China’s TQR management regime is removed. Although there are no limits on Green Box investments, fiscal constraints will make it so leaders must carefully allocate its investment into non-distorting procuctivity-enhancing activities.

Recent increases in the government’s support to enhance agricultural productivity growth indicate that China already has begun to respond to the challenges posed to China under the WTO regime and believes that investment-enhancing investments will play an important role in making China’s farmers competitive. For example, total agricultural research expenditures in real terms grew annually at more than 10 percent. Growth of these expenditures has grown during the late 1990s . Moreover, China currently considers agricultural biotechnology as one of the primary measures to improve its national food security, raise agricultural productivity, and create its competitive position in international agricultural markets. Public agricultural research investment in plant biotechnology has increased at a rate even faster than the rest of the research sectors . However, despite the growth in spending on agricultural research, investment intensity was only 0.44 percent in 1999, one of the lowest levels in the world . Much more needs to be done. Complementary investments are also needed. For example, financing agricultural technology extension is even more problematic . During China’s reform period, the expansion of the output of agricultural production due to the increased incentives from decollectivization ranks as one of the nation’s great achievements, though a significant portion of that gain arose from the mobilization of inputs. China’s future agricultural production increases, however, may not be able to rely on inputs as much as in the past. Other correlates of development, such as rising wage rates, environmental awareness, resource limitations, and recent China’s WTO accession, mean that there will be pressure on farmers to reduce input use and their production costs. As the nation’s farmers near input plateaus, further growth in output must begin to rely more on technological change and systems must be in place to generate the technology and extend it to farmers. The nation needs to continue its recent trends of investment into rural infrastructure. Over the past several decades, tremendous improvements have been made in areas such as transportation, irrigation, and flood control. These projects should be continued in the future. Recent decisions to improve marketing infrastructure, including attempts to set up market and price reporting information and the standardization of agricultural product, are moving the emphasis of officials in the right direction. In other words, it is exactly these types of investments that the government is supposed to and is capable of making. These are all Green Box policies, meaning there is no limit to the support China can give its domestic agriculture through such productivity-enhancing investments. Such investments may have a number of indirect effects, also. A better environment for China’s producers mean that investors, both domestic and from abroad may be will to transfer in better technology. The government should also invest in the activities that will help promote the import of technology and investment. In some case, productivity-enhancing technology can be more easily obtained by importing new technologies and inputs. In the WTO environment, opportunities exist to reduce the barriers that have been keeping China’s farmers from having access to the lowest cost technology in the world. Restrictions on the imports of seed, pesticides and herbicides and barriers keeping out foreign direct investment in the agricultural input sector should be expected to be gradually removed.

In comparison to forest, agricultural habitats are less stable and more regularly disturbed.These attributes could preclude sustained competition and favor related species with traits that allow them to persist in agriculture’s novel and variable conditions . Previous work with the same data set demonstrated that bird functional diversity is lower in intensive mono cultures than in forest reserves or diversified agricultural systems, suggesting that agriculture can act as an ecological filter . We further explored this idea by analyzing whether land use affects the distribution of several functional traits thought to regulate bird responses to environmental disturbances . Indeed, granivores and birds with wider diet breadths and larger clutch sizes had higher colonization rates in agriculture . Additionally, compared with smaller species, larger birds experienced higher extirpation rates in intensive mono cultures but lower extirpation rates in diversified agricultural systems . Our results suggest that both agricultural expansion and intensification threaten evolutionarily distinct species, aligning with earlier findings of heightened global endangerment among birds from basal lineages . In contrast, species from recently diversifying clades appear best able to exploit agricultural habitats and may thus benefit from ongoing agricultural expansion. The persistence of some species from younger lineages cannot prevent the species losses, and concomitant declines in phylogenetic diversity,roll bench that accompany agricultural intensification. Ultimately, protected areas are essential for preserving evolutionary history.

Yet in the absence of a much-expanded global reserve system, prioritizing diversified agricultural systems over intensive mono cultures, especially surrounding reserves, provides a strategy for enhancing the conservation value of human-modified landscapes. About the same number of species persisted in diversified agricultural systems as in forest reserves, and, as a result, diversified agricultural systems maintained 1.5 times the phylogenetic diversity of intensive mono cultures. Shepherding biodiversity through the human pressures of the 21st century will require a shared vision for conservation and agriculture, one that simultaneously preserves species and ecosystem functions while also enhancing food production and human well-being.The air quality in California’s San Joaquin Valley has been a cause of concern for many years. In 2003 there was an increasing sense of urgency to do something about it. One reason is that by many measures it is some of the worst air in the country. In 2003, the counties contained in the San Joaquin Valley Air Pollution Control District1 had the most unhealthy air days as measured by the federal eight-hour smog standard.The short-term one hour smog measure put the San Joaquin Valley in the second to worst category. The San Joaquin Valley is also “considered one of the worst places in the country for tiny particulate pollution” . In addition to the air quality, California’s longstanding exemption of agriculture from the Clean Air Act’s permitting requirements was under serious threat. On May 15, 2002, the Environmental Protection Agency settled a lawsuit with EarthJustice and other litigants that effectively ended the 63-year exemption. In order to ensure legislative action, the settlement stated, “If the state fails to revise its agricultural exemptions, increased pollution offset requirements will take effect on November 15, 2003, and California will lose its federal highway funding on May 15, 2004” .

California’s answer was SB 700, which was proposed by State Senator Dean Florez on February 21, 2003 and signed into law in September 22 of the same year. The legislation ended the state’s agricultural exemption to national air permits on January 1, 2004, and sought to reduce emissions from agricultural sources by creating a regulatory system of permits and stringent cleanup standards. These same agricultural sources would now have to apply for permits to cover both operations and the construction activities. SB 700 is an interesting combination of major policy change and status quo politics. On the one hand, it ended the agriculture industry’s exemption to air permits, imposed a permitting system for agricultural operations, and required stringent mitigation standards. On the other hand, agricultural stakeholders gained important concessions. Forty-nine amendments were attached to SB 700 that allowed agricultural interests ample consideration in shaping administrative rules and who/what would be covered under the permit system . They also received financial incentives for compliance and access to information on how to comply with the law. This examines the narratives surrounding SB 700 and their impact on its design. This leads to three main research questions: What are the important narratives making up the SB 700 policy discourse? What are the implications of these narratives for the design of SB 700? What are the implications of these narratives for policy theory and practitioners? In order to properly address the research questions, the paper is organized in the following manner. There is a brief description of the main elements of SB 700. This is followed by the data and methodology used for the analysis of SB 700 and a presentation of the theoretical framework for the paper.It also consists of a combination of Schneider and Ingram’s theory of policy design and Hajer’s discussion of story lines. After this comes a narrative analysis on the policy discourse surrounding SB 700. The analysis shows how various elements of policy design are linked to different policy narratives. The concluding section of the paper examines the important implications of the findings and discusses potential extensions of the research. On introducing his bill, Florez said its purpose was to end the agricultural exemption to national air permits and reduce emissions of air contaminants from agricultural sources.

While the design of SB 700 addresses these goals, the final version of the bill was not as stringent as originally written . The bill encountered strong opposition in the Assembly’s Appropriations Committee . Agricultural interests successfully argued that the regulations would be too tight and costly in terms of production and jobs , and SB 700 failed to pass the committee. The impasse necessitated negotiations between Senator Florez, Appropriations Committee members, environmental advocates, and agricultural industry representatives that produced important changes to the bill. The changes clarified the circumstances under which air districts would track pollution precursors such as ammonia, required consideration of costs for agriculture engine technology and the air districts when dealing with control measures, and extended the permit deadline for confined animal facilities, such as dairies, to allow completion of scientific studies . All told, the bill was amended 49 times before passing the Senate and Assembly . The amended version passed the Assembly 49 to 30 and the Senate by 24 to 14. The governor signed it on September 22, 2003. With the end of the exemption to national air permits, agricultural sources had to comply with both Title I and Title V of the Clean Air Act. The legislation provided the basic outline of this regulatory regime by defining what constitutes agricultural sources, as well as the level of allowable pollution. SB 700 established four main categories of agricultural sources: confined animal facilities ; internal combustion engines; major stationary sources; and sources otherwise not subject to district regulation. Agricultural sources emitting 50% of the major source threshold for a given pollutant would be required to obtain a permit from its local air district.2It now became the task of state and local air district officials to develop rules and detailed definitions of agricultural sources that would ensure compliance under the new regulatory framework. The California Air Resources Board was charged with defining what constitutes a “large” CAF for purposes of meeting the general permitting threshold. This required them to examine all available and relevant scientific information and “consider the emissions from CAFs and how those emissions affect attainment and maintenance of ambient air quality standards in air basins” . It is then the responsibility of the local air districts to adopt rules that require any CAFs meeting the state board’s definition of large to obtain permits from the district . This process does not establish a single rule governing mitigation measures for facilities falling under the “large” designation. Instead, it creates a case-by-case approach in which those applying for permits provide an inventory of emissions and a mitigation plan for reducing emissions to the extent feasible . This varies across air districts. For example, since the SJVAPCD is designated as “severe” non attainment for ozone,commercial greenhouse supplies the mitigation standard would be BACM. Air districts are to “make a good faith effort to minimize the adverse impacts of these rule making procedures” in terms of both feasibility and cost . Local air districts that were in “moderate” or “serious” non attainment of national ambient air quality standards for particulate matter as of January 1, 2004 were required to adopt regulations to reduce emissions from agricultural sources .The regulations were to address both “fugitive” and precursor emissions. Air districts were required to hold at least one public hearing to accept testimony on their proposed rule by September 1, 2004. The final rule was to be adopted on or before July 1, 2005 at a public hearing and be implemented by January 1, 2006. To aid those regulated under the new permit system, SB 700 created two additional instruments. The first is a mitigation clearinghouse. CAPCOA in consultation with CARB will create and maintain a database of mitigation measures or strategies available for agricultural sources. This allows for those seeking permits to view benchmarks and acceptable practices for reducing emissions. The second instrument is access to financial resources.

SB 700 would require the California Pollution Control Financing Authority to expand access to the Capital Access Loan Program for Small Businesses to include outreach to financial institutions that serve agricultural interests for the purpose of funding air pollution control measures . This would help to guarantee loans made for to purchase pollution control equipment. Schneider and Ingram argue that elements of policy design are political phenomena amenable to empirical analysis. In particular, “Data can be generated by the study of texts, such as legislative histories, statutes, guidelines, speeches, media coverage, and analysis of symbols contained therein” . The data used to analyze the policy design of SB 700 was gathered from several sources. The first is the legislative record for the bill. Since SB 700 was passed and signed into law by Governor Davis, material from the governor’s chaptered bill files are part of the database. In addition to the official record of the bill, newspaper articles and editorials concerning SB 700 were included for analysis. Searching the ProQuest newspaper database from February 21, 2003 to September 22, 2003 using the keyword “SB 700” yields 81 newspaper articles and editorials for use in the narrative analysis. Articles and editorials after this date are used to examine the dynamic relationship between narratives, policy tools, and agents and implementation structures in the implementation activities of SB 700. A special report entitled “Last Gasp” published in the Fresno Bee on December 15, 2002 is also included in the narrative analysis. While the report predates the introduction of SB 700, it is included because it is continually cited by the bill’s author and its supporters and opponents in the legislative materials. Its importance in shaping the debate over this bill warrants its inclusion. The specific form of discourse analysis used to analyze the texts of SB 700 will be Roe’s narrative policy analysis, which consists of two stages. The first is the disaggregation of the text into discrete problem statements, which contain the simplest assertions of causal relationships or sets of causal relationships that link problems to their source . The second stage requires the aggregation of all the problem statements across the entire “data set” or texts. This allows the researcher to see the pattern of commonly identified problems and causal relationships concerning the policy. It is these aggregated problem statements that are then identified as narratives . The NPF framework is used to identify and demonstrate the implications of narratives for the design of SB 700 . The framework identifies a basic structure of narratives and provides basic belief system linkages and preliminary hypotheses. The basic structures of a narrative include “a setting or context; a plot that introduces a temporal element . . . providing both the relationships between the setting and characters, and structuring causal mechanisms; characters who are fixers of the problem , causers of the problem , or victims ; and the moral of the story, where a policy solution is normally offered” . This structure is grounded in a belief system that anchors the narrative “in generalizable content to limit variability” .

Rosen wrote ten ‘comprehensive studies’ of American agriculture which totaled over 1,300 pages, which helped him earn his Bachelor of Science degree in agriculture in 1908. In that same year Rosen moved to Minneapolis, Minnesota, and became a U.S. citizen on December 30, 1909. Rosen was, by then, an expert on American farming techniques and technology, knowledge that would serve him well in his capacity as an agronomist. Indeed, after Rosen had closed the Minneapolis office in 1914 and moved to New Jersey, he became an agronomist and principal at the Baron de Hirsch Agricultural School located at Woodbine. Rosen later resigned his position at the Agricultural School and moved to New York where he became the U.S. representative for a St. Petersburg bank.In the early 1920s Rosen traveled back to his native Russia as a member of the United States’ American Relief Administration, headed by the future U.S. President Herbert Hoover. The team assisted the Russians during the massive country-wide famine of 1919-1922. In Russia Rosen served as head of the Jewish Joint Distribution Service. It was in this capacity that Rosen ‘got his feet wet’ as an administrator of the Jewish philanthropy.

Hoover had nothing but fine praise for Rosen writing that he was a fine personality and superb administrator.Rosen later teamed up with his future partner Rosenberg,round plastic pots to administer Jewish settlement schemes in the Ukraine and the neighboring Crimean Peninsula. Rosen’s partner, James Rosenberg, was the business side of DORSA. Trained as a corporate attorney practicing in New York, Rosenberg was the chairman of the Agro-Joint, a Jewish philanthropy that channeled funds to various projects. Rosenberg was the grandson of a German rabbi who had immigrated to Pittsburgh. The Rosenberg family had moved to New York when James was an impressionable youngster. His mother and father had enrolled James in the progressive Society for Ethical Culture, “founded in 1876 to promote the advancement of social justice.”Wells describes the mission of the Society as “one that was rooted in the intellectual mastery of nature, the glorification of life in art and with its consecration in morality.”This grounding in ethics was to serve the future attorney well, guiding him in the decision making processes that occupied his professional career. Rosenberg later entered a ‘Waspish’ private boarding school before his acceptance into Columbia Law School, then considered among the very best universities in the United States.After graduating from law school at Columbia University, New York, Rosenberg set about on the path to success as a corporate bankruptcy attorney, a profession which was soon to provide him with the funds and means to do charitable work. In truth, James Rosenberg was the quintessential American success story. A grandson of immigrants who arrived in America without the safety network of family and friends, he became widely successful in his chosen profession as a lawyer.

Rosenberg’s dogged determination served him well as he rose through the ranks of the corporate world as a young and brash attorney to become a member of what Wells termed a ‘sophisticated and elite group.’Joseph Rosen and James Rosenberg joined forces in the early 1920’s to assist the Russian Government in resettling of Jews in the Crimea and Ukraine as agriculturalists. This experience gave them a firm grounding in the nuts and bolts of starting and running agricultural settlements. The estimates of Jewish refugees who were resettled in the Crimean Peninsula and the Ukraine during the years 1924-1938 differ among the available sources. Kaplan uses the figure of 250,000, who ultimately cultivated three million acres, and also imported approximately 1,000 American made tractors.Wells gives slightly different figures, pegging the refugees at upwards of 150,000 Jews, and the land at nearly two million acres. The amount of money that the Joint earmarked for the project was the astronomical sum of seventeen million dollars.The valuable experience that Rosenberg and Rosen gained through the Russian settlement scheme was crucial, and provided a model for the Dominican settlement at Sosúa. The Crimea/Ukraine model that was developed by Rosen, and later put into effect at Sosúa, was based on a three-part plan: crop diversification, new ‘superior’ technology, and cooperative division of land, labor and resources. Rosen firmly believed that this plan could help transform the Jews from a parasitic bunch of rootless wanderers into productive members of society through the cultivation of land.Superior U.S. farm machinery, such as the tractor, translated into more acreage that could be put to use; and the cooperative nature of the settlements meant that all members could share the costs of fertilizers, seeds, and new equipment.

The division of labor was in the main determined by gender, men doing the heavy work such as the plowing and clearing of fields, the women cooking, planting, sewing and caring for the kids. There were doubts, however, that the Crimea program would succeed at all. Rosenberg summed up most succinctly his thoughts regarding the project: “The Crimean scheme had ended in ‘utter, complete, black tragedy.”Again, the political scientist Allan L. Kagedan argued that the Crimea plan was one that seemed to have little chance for success. Many people that were involved in the project believed in the “clear likelihood that the scheme would fail.” The majority of Jews were not, in the main, people of the land but urbanites mostly involved in some form of commerce. Indeed, Kagedan, writing in the academic journal Jewish Social Studies, quotes Rabbi Menachem Mendel Schneerson, the Lubavitcher Rebbe who reminded the JDC in March 1928 “that agriculture is an economic branch which is foreign to the Jews who are neither physically nor spiritually adapted to it.” Kagedan was aware that “not all Jews would transform themselves into farmers, many would abandon the land in short order.”The employment profile of the refugees was heavily weighted towards the professional ranks with very few of them having had any background or experience in agriculture. Yet the ultimate success of the Crimean and Ukrainian settlements gave both men high hopes of a repeat performance at distant Sosúa. The Rosenberg/Rosen partnership endured throughout the 1920’s and 1930’s culminating in the founding of Sosúa in the Dominican Republic. Rosenberg drew up the documents of incorporation for DORSA in New York during December of 1939, with himself as President and Rosen as Vice President. Trujillo was anxious to get the project up and running as soon as feasibly possible. The dictator was in international hot water for the mass murder of Haitians in October of 1937. The Parsley Massacre, in Spanish El Corte, was a stain on Dominican history and needed to be reconciled before the tiny Caribbean nation would again be respected on the world’s stage. Trujillo needed to remain in the good graces of the United States, its giant neighbor to the north, chief trading partner and principal benefactor. The dictates of the Good Neighbor policy of the United States provided that the U.S. not interfere in the affairs of its neighbors and satellite states. This foreign policy was central to F.D.R.’s presidency and “meant that the United States emphasized cooperation and trade rather than military force to maintain stability in the hemisphere.”

The Good Neighbor Policy also gave Trujillo free reign to rule as he pleased, without the fear of further economic sanctions or military intervention from the United States. The Dominican Republic had been subject to crippling economic sanctions since the U.S. took control of the Dominican Republic’s customs house. This was done to secure payment for its debt to bondholders. The receivership was a sore spot that severely strained relations between the two countries, and was something that El Generalíssimo wanted to resolve immediately in favor of his economically strapped nation. Indeed, in 1905 the United States announced that it would “guarantee the territorial integrity of the Dominican Republic [and] assume responsibility for customs house collections…using 55% of receipts to pay outstanding obligations, turning over the remainder for Dominican governmental expenditures”.This policy was eventually overturned on March 31 1941,hydroponic bucket and with its abolition the Dominican Republic now, after a long, humiliating thirty six years, finally controlled its domestic finances. Yet another point of contention involved the importation of Dominican sugar into the United States and its territories. Trujillo desperately wanted the U.S. to increase its import quota of sugar produced in the Dominican Republic, the U.S. instead favoring Cuba and Puerto Rico over the Dominican Republic. The dictator lobbied James Rosenberg for help in providing representation in Washington D.C.. Rosenberg could only promise Trujillo to do what he could to advance the Dominican cause in the U.S. press, thereby avoiding any possible conflict of interest that could derail efforts to reverse the crippling stranglehold that the sugar quota imposed on the Caribbean island nation’s economy. The plan was to create a favorable public relations spin via press releases and the like, which would cast Trujillo in a positive light. Rosenberg goes into some detail in his Diary I regarding exactly what Trujillo wanted from the United States: the abolishment of the Receivership Convention, and an increase of the U.S. sugar import quota. This would then allow the Dominican Republic to increase its sugar exports to its chief foreign market and infuse much needed hard currency into the nation’s coffers.

Trujillo knew the value of having an attorney as well connected as Rosenberg firmly in his corner. Rosenberg notes that an American named Mr. Rickards who had been “working down here first for the Government and then the sugar institute of which he is now head, his title being “Secretary-General,” paid him a visit on behalf of El Generalíssimo.”Mr.Rickards came around with heaps of papers, documents, records, etc. that Trujillo had sent him with…regarding the Convention, regarding sugar, regarding economic or legal problems confronting the country; that the General wanted me to have the facts.” On one of Rosen’s and Rosenberg’s visits to the Generalíssimo, the shrewd New York attorney relates that “Trujillo handed me the memorandum and said he would like to talk to me about it later.”The memorandum presented to Rosenberg spelled out the issues that Trujillo wanted resolved. Rosenberg promised the dictator that he would do everything in his power to effect a positive outcome through the use of politically connected people, mainly lobbyists, who Rosenberg knew well. Rosenberg was adamant that Trujillo needed elite representation in Washington, and told Trujillo that he would make recommendations as to who the Generalíssimo should use to represent the Dominican Republic. The U.S. Receivership of Dominican Customs had long been a source of embarrassment to Trujillo, the nation, and its people. Rosenberg noted in his diary that “…this interference with [Dominican] sovereignty was a constant irritation,” and continued “There are two main problems—sugar—Convention…It would seem to me important that the Dominican Government ought to make itself heard,” and following this line of reasoning Rosenberg continued “because of the many legal, economic and problems as to the Convention, you need able counsel in Washington. You should also see to it that the American public understands something of these problems which confront you.” In spite of Trujillo’s insistence that Rosenberg represent the Dominican Republic’s interests in Washington D.C., Rosenberg bowed out by telling Trujillo that “it was utterly out of the question for me to be the lawyer.” Trujillo pressed Rosenberg to select the lawyer with Rosenberg again turning down the dictator’s request. Rosenberg would, however, recommend a lawyer should Trujillo send the ‘right man’ up to the States.Yet another reason that explains Trujillo’s magnanimous offer at Évian was his desire to ‘whiten’, in Spanish blanquear, the Dominican populace through miscegenation. Trujillo believed that bringing Jews to his country would prompt inter-breeding between Jews and Dominicans, thereby creating a new, whiter breed of Dominican. This was an obsession of Trujillo and the Dominican people at large. The events of El Corte had generated world-wide, negative press, and prompted Trujillo to scramble to repair his damaged image through, among other means, diplomatic maneuvering and slick public relations campaigns. It is estimated that as many as 20,000 Haitians had lost their lives to roving bands of thuggish Dominicans, including some military officers and soldiers.It is ironic that sugar was at the root of the massacre, as it was also the cause of Dominican embarrassment on the world’s stage.