Switch grass also had poor stand establishment when compared to other grasses

Countries may provide more subsidies if the political accommodations that they buy are especially valuable. Indeed, Table 1 suggests that subsidies are more likely to occur in countries with a major reserve or in authoritarian countries, such as Iran or Venezuela.This research aims to explain the impact of the introduction of bio-fuels on fuel markets while introducing OPEC into the analysis. This work evaluates the impact of bio-fuels on fuel markets while incorporating OPEC into the analysis and assessing the effect of the introduction of bio-fuels on the international price of oil, the price of gasoline inside as well as outside of OPEC countries, and the global GHG emissions. This is done while making three alternative assumptions on the international oil markets: Markets are competitive, OPEC is a cartel of firms that maximizes profit, and OPEC is a cartel of nations that maximizes economic surplus from oil production and domestic consumption. Using data from 2007 while considering quantities of both ethanol and bio-diesel consumed that year finding, we developed a model that is used to synchronize outcomes among gasoline, diesel, and crude-oil markets—a challenge given that we only have partial data for each of the markets. A key parameter that affects the outcome of the analysis is how responsive the demand of oil from OPEC in the oil-importing countries is to changes in fuel prices. Less responsive finding demand means that, when price increases, there is less reduction in consumption or, inversely,livestock fodder system that prices go up further for a given decline in fuel demanded.

We use four parameters from -1.25 finding to -2.0 finding. The introduction of bio-fuels is estimated to have increased fuel subsidies in OPEC countries in 2007 by 2%–3% and reduced world fuel prices by 2%. The introduction of bio-fuels caused the import demand of oil from OPEC countries to decline, leading to a decline in fuel prices. Then, OPEC responded by reducing exports so that the supply of oil available to oil importers would decline, which would contribute to increased fuel prices in the oil-importing countries. Some of the oil that was withdrawn from the oil-importing countries went directly to OPEC’s domestic consumers. Thus, OPEC mitigated the loss in profits due to the introduction of bio-fuels by redistributing benefits from the introduction of bio-fuels to its domestic constituencies. The introduction of bio-fuels caused consumption of gasoline and diesel in 2007 to decline by about three billion gallons a year, which is about 2.5% of total consumption. However, the decline in fuel prices resulted in an increase in total fuel consumed finding. This increase in overall fuel consumption because of a lower price is called the “rebound effect.” For the range of elasticities investigated, we show a rebound effect of about nine billion gallons a year. The rebound effect may lead to an increase in overall GHG emissions with bio-fuels. While bio-fuels may emit less GHGs per unit of energy, the larger volume of fuel consumption may lead to a larger volume of GHG emissions. Using the cartel of nations model, we show that there is potential for GHG emission savings with the introduction of advanced bio-fuels, such as cellulosic bio-fuels. The model used to characterize the energy market affects estimates of the bio-fuel effects on consumption and production as well as on fuel prices and GHG emissions. Competition overestimates the price effect but underestimates both quantity and environmental effects associated with the introduction of bio-fuels finding.

Our analysis also shows that modeling the oil market as either competitive or with a cartel of nations overestimates the monetary benefits of the introduction of bio-fuels to oil importing countries but underestimates the costs to oil-exporting countries. The analysis suggests that the introduction of alternatives to crude oil finding will reduce fuel prices and crude-oil production but increase overall fuel consumption. The GHG emissions will decline if the alternatives to conventional fossil fuels are relatively clean but, for most commercially used bio-fuels, total GHG emissions will increase. The introduction of bio-fuels affects OPEC pricing behavior: OPEC mitigates the reduction in oil revenues due to the introduction of bio-fuels by increasing domestic fuel consumption but reducing exports more than implied by the introduction of bio-fuels under the competitive model. Thus, when assessing the impact of bio-fuels, the outcomes under a cartel of nations model are different than those under competition. Although the introduction of bio-fuels leads to a reduction of fuel prices in oil-importing countries, this reduction is smaller than the reduction computed under competition, suggesting that the estimated gain from bio-fuels to the consumers in the oil-importing countries under a cartel of nations is smaller than under competition finding. However, when compared to the competitive model, the cartel of nations predicts a larger reduction in exports and, thus, a larger reduction in foreign exchange. That is, the impact of bio-fuels on GHGs under the cartel of nations is relatively more positive than predicted by the competitive behavior. Theory and empirical analyses suggest that assessment of the impact of alternatives to crude oil require better quantitative modeling of the oil markets, including OPEC. They suggest that further empirical work, especially econometric analysis of OPEC pricing behavior, is needed to further support and expand this line of research and to improve our understanding of the international oil markets.

Data were collected in the biomass plant species study at Fruita for one harvest in 2010, three cuttings in 2011, and two cuttings in 2012. A third cutting will occur at Fruita during fall 2012. At Rifle, an initial harvest occurred in 2011 and one cutting has occurred in 2012. A second cutting will occur at Rifle during fall 2012. At Fruita, the Introduced Biomass Treatment has consistently had the highest biomass yield finding. While the Introduced Biomass Treatment included grass species, those grass species have disappeared from the plant stand and nearly all the biomass yield in this treatment is from alfalfa. Deficit irrigation is being used in this study and plant species such as alfalfa with a deep root system can explore a large volume of soil. This gives alfalfa an advantage over shallow-rooted grass species. The native grass entry in this study has exhibited low biomass yields compared to other biomass entries. Native grass species adapted to arid environments may persist well under harsh environments, but may not be high yielding. In previous research, switch grass has been found to be high yielding under high input conditions in some western Colorado environments, but not others finding. Establishment of some grass species, such as switch grass, may require a few years before they begin to produce high yields. During this establishment phase of switch grass, weeds have been a problem, particularly the winter annual weeds finding. Much of the biomass produced at Rifle in 2012 in switch grass was weeds, mainly cheat grass finding finding.No significant yield differences among the input treatments have occurred to date at Fruita or Rifle finding. There is a trend for higher yields in the high input treatment but again a few to several years may be needed before differences among input treatments become statistically significant. The high cost of producing bio-fuel feed stocks has been a major hurdle for growers, bio-refineries, and distributors. Identification of parameters could lower biomass production costs to promote the economic viability of locally produced biomass. Data from our research were used to develop a crop enterprise budget tool. The enterprise budgeting tool is user friendly for a variety of audiences, including producers, crop consultants, extension agents, and others. Parameters can be adjusted to reflect variations in location, crop management, best/worst case scenarios, or optimizing a specific input. For the purposes of this paper, the parameters of the crop enterprise budget have been adjusted to reflect specific agronomic scenarios. Large regions of the western United States are dominated by cool-season grasses with special adaptations to cold temperatures, sporadic and low precipitation, summer drought, salinity, high elevations with high ultraviolet radiation, and other unique and challenging growing conditions. Basin wild rye finding is a large native perennial grasses in western North America; however, its elevated growing point is easily damaged by grazing or mechanic harvesting.

Creeping wild rye finding is relatively short statured finding but is a strongly rhizomatous grass that recovers well following grazing, cutting, or other disturbances. Creeping x basin wild rye hybrids display a combination of plant height and rhizomatous traits that are useful in a low-input herbaceous biomass crop finding. The biomass yields of creeping x basin wild rye species were compared to other grasses over four years, with no irrigation or fertilizer,fodder system trays at two research farms in Utah and Idaho. Tall wheat grass finding and intermediate wheat grasses finding were top entries in the first two years. The single best entry in the third and fourth harvest years was a creeping x basin wild rye hybrid. In the first cutting that occurred in 2012 in the Native Grass Species Study being conducted at Fruita tall wheat grass had the highest yield. Intermediate wheat grasses also had high yields and also had low biomass plant moistures finding. The creeping wild rye x basin wild rye crosses exhibited intermediate yields while Altai wild rye and switch grass had the lowest yields with most of this biomass in the switch grass entry coming from weeds.With additional years, yield rakings of these native grass entries are likely to change from those of this initial cutting.A Rifle Bio-Feedstock Feasibility Study was conducted in 2008 for the City of Rifle, CO and in the statement of findings, the consultants noted that dedicated energy crops have potential in the area finding. A potential of 200-300,000 acres of marginal within a 50-mile radius of Rifle appears possible for production of dedicated, lignocellulosic biomass finding, although further refinement of the definition of marginal lands that could be used for bio-energy crops needs to be addressed. The construction of pilot plant is nearing completion at the Colorado Mountain College, Rifle campus and at this facility the various perennial biomass grass species will be converted into butanol. As demonstrated in the crop enterprise budget scenarios presented in Table 2, of the four species, the introduced grass species definitively demonstrates the lowest per acre break-even price finding when grown using efficient agronomic management. In contrast, the native grass mix demonstrates a relatively lower yield and a substantially higher break-even price, at $315.35 per acre, even with efficient agronomic practices. Increases in two key costs, diesel fuel and irrigation water, not unexpectedly, directly affect production costs. Regardless of the scenario, producers with capital equipment constraints finding incur approximately 20% higher break-even prices due to reduced yields. The crop enterprise budget tool quantitatively shows how changing different input parameters affects potential profitability. While aggregate growth in an economy may improve the welfare of both wealthy and poor households, the latter are most usually rural, and rural households have employment and incomes that depend disproportionately on agriculture. It is natural to wonder if growth in aggregate agricultural income has a different effect on the welfare of poorer households than does growth elsewhere in the economy. The question is an important one for many policy issues. Faced with continuing extensive poverty, many development agencies and scholars have suggested the need to refocus growth on agriculture finding, arguing that the alternatives of redistributing income generated outside of agriculture or migration out of agriculture to urban areas are difficult to achieve and create other problems. Of course, we are not the first to wonder whether growth in agriculture may be more effective than growth in the rest of the economy in reducing poverty; an extensive theoretical and empirical literature already exists on the subject which we discuss in Section 2. The theoretical literature focuses on the different transmission mechanisms of an exogenous gain in agricultural productivity on poverty, while the empirical literature analyzes the reduced form relationship, and generally documents a stronger association between poverty reduction and growth originating in agriculture compared to growth originating in non-agriculture, with the exception of Latin American countries. In this paper we tackle this question by comparing changes in the level and distribution of household expenditures due to growth in both aggregate agricultural and aggregate non-agricultural income.

The challenges facing the Air Resources Board are not completely uncharted

Livestock production is the agricultural sub-sector with the highest emissions and in turn with the highest potential for mitigation finding. It uses approximately 37% of the state’s agricultural land finding, and it generated 61% of California’s agricultural greenhouse gas emissions in 2009. The remaining 63% of agricultural land is used for field, fruit and nut crops; these crops generated 30% of the state’s agricultural emissions in 2009 due to fertilizer use, soil preparation and disturbances, and the burning of crop residue. Fuel used for agricultural activities contributed the remaining 8%. Since agriculture represents a significant portion of both the state’s economy and greenhouse gas emissions, it is not surprising that it offers considerable mitigation opportunities. The Climate Action Team finding, the government agency responsible for implementing California’s global warming emission reduction programs, estimated that agriculture’s annual greenhouse gas emissions could be reduced by 9.1 million MtCO2e per year if the emission reduction strategies were fully implemented finding. The mitigation potential for agriculture is comprised of nine strategies, each of which contains identified activities for implementation finding. The most significant strategies concern the uses of biomass: Converting manure to energy could generate annual reductions of 1 million MtCO2e and using other types of agricultural biomass another 2.3 million MtCO2e. Other important strategies concern carbon sequestration. When plants photosynthesize, they remove carbon dioxide from the atmosphere and convert it into organic carbon, which is used in the production of plant biomass; for example, leaves, wood, roots or root exudates.

When leaves fall, stacking pots roots secrete or plants die, this carbon can be removed from active cycling and stored, or sequestered, in the soil if it is protected from microbial decomposition finding. Consequently, carbon sequestration can be achieved by farm scaping — planting trees, shrubs and grasses in hedgerows, which removes carbon dioxide out of the atmosphere and contributes to the formation of soil complexes that fix carbon. Carbon sequestration in soils and plants could save 2.5 million MtCO2e — 1.5 million MtCO2e from farm scaping finding and another 1.0 million MtCO2e in soils finding. Although the Board proposed a livestock protocol and rules on fuel use that might support several strategies, significant hurdles prevent implementation of many of the strategy activities. In its AB 32 analysis, the Climate Action Team noted that methodologies for more than half of the agricultural strategies were not in place, in part because of a lack of scientific research finding. This situation accounts for much of the difference — approximately 25%, or 2.8 million MtCO2e — between potential reductions for 2020 if the strategies were implemented and reductions deemed feasible by that year finding.There has been considerable experimentation on how to structure agricultural projects that reduce emissions or sequester carbon, beginning with voluntary pilot projects under the auspices of the United Nations finding. Particularly relevant are thousands of projects operating under the Clean Development Mechanism, which promotes technology transfer and private and public investments in emission reduction and sequestration projects in developing countries.

The Clean Development Mechanism is a project-based provision of the Kyoto Protocol, an international agreement linked to the U.N. Framework Convention on Climate Change finding, which aims to reduce greenhouse gas emissions and enhance welfare in developing countries. Credits generated by these projects can be used to meet pledged emission reduction commitments under the UNFCCC. The structure is analogous to the California Air Resources Board’s proposed program, which allows independent entities to create offsets that regulated firms can use. For example, since agriculture is an unregulated sector under the California program, a livestock farmer could potentially capture livestock methane emissions, receive offset credits for the voluntary emission reduction, and in turn sell them to a regulated entity such as a concrete manufacturing facility in need of additional carbon allowances. Central to the Clean Development Mechanism are its technical blueprints, called methodologies, which lay out rules for calculating the number of credits granted for specific mitigation activities. Overall, the Clean Development Mechanism has successfully attracted project investments finding, though it has been more effective in some agricultural mitigation activities than others finding. Agricultural mitigation projects, those that convert organic waste products to energy and limit methane emissions, have been successful under the Clean Development Mechanism, but land-use projects have not been successful under the Clean Development Mechanism in its current form. Land-use projects are defined as the total human arrangements, activities, and inputs undertaken in a certain land cover type to achieve purposes for which land is managed, such as crop production, grazing, timber extraction and conservation. Land-use forestry projects are those associated with decreasing emissions through avoiding deforestation, improving forest management and increasing the uptake of carbon finding. The Clean Development Mechanism has an extensive agricultural project base with a set of established standards and rigorous, peer-reviewed methodologies to ensure that the offsets are real, additional and verifiable finding.

This large stock of already completed methodologies can provide guidance as the Air Resources Board and Climate Action Team develop California’s implementation rules and protocols. In particular, it could hasten their progress by providing methods of quantification for particular processes that would otherwise need extensive research. For example, one of the hurdles for implementing farm scape sequestration is uncertainty about its potential to sequester carbon and whether this potential is significant enough to merit the development of a measurement methodology finding. In addition, the analysis cites the difficulty in quantifying the carbon content of woody shrubs as an obstacle to including the simple practice of planting shrubs in hedgerows between crops as an AB 32 strategy. The Clean Development Mechanism has an approved baseline and monitoring methodology finding for reforestation and afforestation, defined as the establishment or re-establishment of forest cover finding. And it has researched the carbon sequestration potential of planting trees and shrubs in hedgerows and states that the resulting carbon pools are significant finding. The methodology contains equations for woody shrubs as well as equations for measuring net greenhouse gas removal by sinks, another scientific hurdle mentioned by the Climate Action Team in regard to implementing agricultural carbon sequestration projects finding. Soil carbon dynamics is an ongoing research topic, and its biological and physical mechanisms are not well understood finding, but the Clean Development Mechanism project methodologies could help California realize its 2020 regulatory targets. Agricultural projects in the Kyoto Protocol include implementation opportunities and solutions to hurdles that are relevant to tapping mitigation potential in California agriculture. Those charged with implementing AB 32 must find instruments that are both economically efficient and environmentally effective. In the case of the Clean Development Mechanism, environmental integrity is subject to specific supervision rules and a series of checks along the project cycle by the UNFCCC Secretariat. To start, an international supervisory group, known as the CDM Executive Board, must approve methodologies for establishing baselines on behalf of the UNFCCC. Approved methodologies are published, and project developers can consult them. However, projects relying on new methods face the additional task of gaining approval. In either case, whether new or established methods are employed, developers must also convince the CDM Executive Board that their project methodology has been appropriately applied.

The project cycle also contains checks carried out by an independent firm or organization that has been accredited by the CDM Executive Board. This entity, known as a designated operational entity finding, initially validates the baseline design and the project’s plan to monitor and measure outcomes. This occurs before the project is registered — that is, officially recognized by the CDM Executive Board. For large projects, a separate independent entity carries out the project’s monitoring protocol, the process by which emissions or sequestrations are measured.In the context of the Clean Development Mechanism, we define an agricultural project as one that uses agricultural residuals, outputs or processes to directly or indirectly reduce greenhouse gas emissions finding. This includes projects that sequester carbon in soils. We studied a dataset described by Larson et al. finding that covers 5,824 projects finding, based on data reported by Risoe finding. Of these, 1,022 projects finding were classified as agricultural, land-use or forestry projects. Examples of such projects include the Assisted Natural Regeneration of Degraded Lands in Albania finding and the Moldova Soil Conservation Project finding. The Albania project was designed to transform badly eroded lands into broad leaf forests of native species. The primary objective of the project in Moldova is to conserve and improve the productivity of agricultural soils by planting shrubs and trees. The project is expected to generate other benefits,sawtooth greenhouse including global biodiversity and fuel wood and other forestry products for nearby communities. Based on Risoe’s analysis, the agricultural projects are expected to reduce business-as-usual emissions by nearly 220 million MtCO2e by 2012 and 582 million MtCO2e by 2020. Available estimates of CO2 emissions finding suggest that total global annual emissions were 30.0 and 37.8 GtCO2e finding in 1990 and 2005, respectively. The main methodologies used for these 1,022 projects were extracted from Risoe’s project data and can be found in Dinar et al. finding. The projects rely on 33 approved methodologies finding, but the eight most frequently used methodologies account for 80% of the projects finding. While each project must meet the specific criteria stated in each methodology, a closer look at the most widely used methodologies suggests that they are composed of variations around a small set of core mitigation activities. The most widely used mitigation activity displaces fossil fuels with alternative fuels from agricultural biomass or processes. Examples include the generation of electricity by burning agricultural waste and the generation of mechanical energy via irrigation. The second most widely used mitigation activity is avoiding the release of methane and other greenhouse gases, or recovering them by modifying anaerobic decomposition systems for manure or agriculturally derived organic matter finding. These two core mitigation activities already in place on a number of the state’s farms could be adopted in California. They would encourage better management of manure, as well as the displacement of fossil fuels. However, Clean Development Mechanism methodologies are less well developed in areas associated with other important AB 32 strategies, including crop growing and harvesting, and soil preparation and disturbances.

Consequently, methodological hurdles will remain in the short run, making it difficult to tap mitigation opportunities in these areas.Missing methodologies are also holding back international mitigation efforts. The Clean Development Mechanism taps only a small portion of the mitigation potential in the agricultural sectors of developing countries. For example, Larson et al. finding calculated that the 1,022 agricultural and land-use forestry projects studied amounted to a little more than 3% of the mitigation potential identified in the most recent Integovernmental Panel on Climate Change finding report finding. Larson et al. finding note several generous assumptions in their calculations and surmised that their estimate represents an upper bound. In the case of the Clean Development Mechanism, much of the mitigation gap likely arises from missing methodologies for land-use projects. Mitigation activities for these projects include the restoration of degraded land, better management of crop and pasture land, and the appropriate use of fertilizers. Research summarized by the Intergovernmental Panel on Climate Change finding suggests that these activities have the largest mitigation potential for the agricultural sector globally and thus for achieving AB 32 goals as well.The appropriate roles for land-use projects in international mitigation efforts were contentiously debated as the Kyoto Protocol and the Clean Development Mechanism were crafted finding. And, in the rules that eventually emerged, the projects faced special limitations, in large part because of the nature of land-use mitigation. The activities are mostly straightforward and readily observed, for example, the adoption of conservation tillage methods or the addition of organic material to degraded soils. The likely benefits and processes generating them are easy to list as well. But measuring precisely the net effects, which are needed to assign credits, is challenging, and the related science is complex. Moreover, even well-measured effects are potentially reversible under many settings. For example, the mechanisms controlling soil organic carbon finding dynamics are imperfectly understood finding, so even meticulously inventoried carbon stocks have the potential to be re-emitted back into the atmosphere if temperature, precipitation or any other of the myriad variables affecting soil organic carbon dynamics happen to change. This difficulty creates skepticism about the environmental integrity of land use projects and increases monitoring costs, which encourages potential investors to favor alternative projects.

Previous meta-analyses have also examined various aspects of N2O emissions from conservation tillage

The large N2O emissions from agricultural lands are of particular concern given both its high global warming potential relative to CH4 and CO2 and its contribution to stratospheric ozone depletion.Conservation tillage, including no-tillage and reduced tillage management, is increasingly being adopted on agricultural lands worldwide.About 10% of global arable lands, i.e.∼125 million hectares, are currently managed using conservation tillage.The adoption of conservation tillage has demonstrated important benefits for soil carbon sequestration in topsoil, soil erosion, soil quality and crop yields.However, there is considerable debate concerning the effects of conservation tillage on climate change mitigation due to the highly variable effects of conservation tillage on N2O emissions.Various studies found increase , decrease , and no differences in N2O emissions resulting from adoption of conservation tillage practices.These inconsistent effects may be associated with the duration of conservation tillage practices with short-term application reported to stimulate N2O emission while long-term application decreases N2O emission.Additionally, climate regimes and various soil properties are reported to have a strong effect on soil N2O emission.Soil N2O emission primarily results from nitrification and denitrification processes in soil.Under relatively aerobic conditions, NH4+ is converted to NO3− along with N2O emission by autotrophic nitrifiers, In contrast, under anaerobic conditions, heterotrophic denitrifiers convert NO3− to N2O and N2.Soil aeration status is a dominant factor controlling nitrification and denitrification processes and their potential N2O production.In addition,hydroponic nft soil physical and chemical properties, such as soil texture, pH, organic content, clay content, etc., play significant roles in N2O emission dynamics.

For instance, fine-textured soils often have higher N2O emissions than coarse-textured soils due to slower O2 diffusion rates leading to lower soil O2 concentrations that favor denitrification.However, other studies have shown lower N2O emission from fine-textured soils as low gas diffusivity allowed greater time for more complete reduction of N2O to N2.Higher microbially-labile organic matter contents also favor enhanced denitrification by providing substrate for heterotrophic denitrifier growth, which leads to more rapid O2 consumption.High N2O emission may also be favored in alkaline soils due to more suitable growth conditions for both nitrifiers and denitrifiers.Furthermore, agricultural practices, such as N fertilization, crop species, crop rotation and water management may have strong influences on N2O emission.Numerous studies have investigated the impacts of soil properties and agricultural practices on soil N2O emissions in conservation tillage systems and found diverse and contradictory results that hinder the overall assessment of conservation tillage impacts on climate change mitigation.Van Kessel et al.investigated changes in N2O emission in response to different categorical conservation tillage practices and found strong influences from the duration of conservation practices and climate regimes.Their meta analysis focused on the magnitude of N2O emission under contrasting conservation tillage regimes, but did not consider specific soil properties and widely-used agricultural practices.Zhao et al.analyzed the relationship between specific-conditions and greenhouse gas emissions in no-till farming systems using meta-regression based on a regional database in China, but this analysis was limited in scale.

A detailed assessment of the influence of conservation tillage practices on soil N2O emission is critical to determine the potential for conservation tillage practices to mitigate climate change.This study aimed to assess the effects of conservation tillage on soil N2O emission relative to conventional tillage by conducting a meta-analysis of peer reviewed field studies.Specifically, we attempt to address the following questions: i) How do climate regime and experimental duration affect soil N2O emissions following application of conservation tillage practices? ii) Do initial soil properties affect the response of N2O emission to conservation tillage practices? and iii) Can agricultural practices mitigate N2O emission associated with conservation tillage? This comprehensive meta-analysis is significant for developing strategies for the future expansion of conservation tillage and for enhancing agricultural practices to mitigate greenhouse gas emission from agricultural lands.Conservation tillage is promoted as an effective method for carbon sequestration and thus a possible mitigation strategy for climate change.However, considerable controversy exists concerning how conservation tillage affects soil N2O emissions, which may offset potential carbon-related climate change mitigation benefits.N2O emissions are primarily controlled by the microbiological processes of nitrification and denitrification.Whereas the heterotrophic denitrification process occurs under anaerobic conditions, nitrification is an aerobic process.Therefore, the integrated effects of soil physical, chemical and biological factors, such as soil aeration, pH, temperature, moisture, texture and substrate availability, function together to affect soil N2O emission dynamics.Furthermore, agricultural practices, such as irrigation, fertilization and cropping systems, play important direct/indirect roles in soil N2O emissions.Given the wide range of integrative factors affecting N2O emissions, a comprehensive meta-analysis can provide a powerful approach for gaining important insights into the importance of specific factors regulating N2O emission across a wide range of spatial and temporal scales.Overall, the implementation of conservation tillage significantly affected soil N2O emission in this meta-analysis ; however, non-significant differences were observed for different conservation tillage practices.

These results are consistent with an analysis by Van Kessel et al..Meta-regression results indicated some detailed information concerning differences in no-tillage versus reduced tillage practices on soil N2O emission.At the initiation of conservation tillage, soil compaction can moderate soil aeration and stimulate N2O emission through denitrification.However, substrate limitation suppressed this initial stimulation leading to decreased N2O emission over time.With retention of residues, sufficient substrate is available to support the N2O-producing heterotrophic microbial community.With sufficient substrate availability, soil aeration becomes a dominant factor regulating N2O emission in conservation tillage systems.As shown in Fig.6b, N2O emission rate was regulated by the interactions of conservation tillage and soil texture.N2O emission in both conservation tillage practices displayed a significant positive correlation in the fine particle size classes , which was consistent with the higher N2O emissions in fine-textured soils observed by Choudhary et al..Conservation tillage may improve bulk density and water holding capacity, especially in the fine-textured soils which are prone to generate anaerobic microsite hot spots for N2O production in otherwise aerobic soils.Significant differences were recorded in conservation tillage induced soil N2O emissions among climate regimes.Temperature and precipitation are the primary factors regulating N2O emission across climate regimes.A significant negative correlation was recorded between effect size and precipitation , consistent with the findings of Van Kessel et al.who reported a larger mean effect size in dry climates than humid climates upon implementation of reduced tillage.Increasing amounts of precipitation lead to higher soil moisture and lower soil oxygen concentrations, which strongly regulate nitrification and denitrification dynamics.Higher water-fill pore space was observed in no-tillage systems compared to conventional tillage during the dry season, but no difference was observed during the normal wet portion of the year.WFPS differences were more pronounced between tillage practices under lower precipitation scenarios, which resulted from increased denitrification induced N2O emission in conservation tillage relative to conventional tillage.In addition, the N2O emission effect size showed a weak positive correlation with temperature , which was further supported by the higher increase of N2O emissions in tropical and warm temperate climate regimes.These findings are similar to those found by Zhao et al..Nitrification is favored at optimal soil temperature and moisture conditions of 25–40 °C and WFPS of 30–70%, respectively.Within the optimal conditions, nitrifier activities are enhanced with increasing soil temperature leading to the potential for increased soil N2O emissions.However, contradictory results have shown higher N2O emissions from soils in conventional tillage versus no-tillage with increasing temperature.

Conservation tillage-induced N2O emissions were affected by experimental duration.Short- to medium-term implementation of conservation tillage significantly increased soil N2O emission, especially in the first 3 years following the initiation of conservation tillage.However, a negative mean effect size was measured for studies with long-term experimental duration.Similar changes in N2O emissions with duration of conservation tillage were reported by Six et al., with an increase of N2O emissions in the first 10 years and a decrease thereafter.These changes associated with duration of conservation tillage may be attributed to attainment of new steady-state soil conditions,hydroponic channel such as soil structure, compaction, WFPS and aeration, which are not optimal for soil microbes to produce N2O by denitrification and/or nitrification processes.Soil N2O emissions are strongly correlated with soil denitrification nitrification processes that are driven by soil microbes, which in turn are largely affected by several soil properties.SOC and generalized soil texture had no significant differences on N2O emissions following implementation of conservation tillage.A trend of increasing N2O emission with increasing SOC content was reported by Li et al..High SOC provides more substrate for heterotrophic denitrifiers, which should favor enhanced denitrification and N2O emissions.Soil texture strongly affects soil aeration and thus is often implicated as an important factor regulating N2O emissions.As nitrification is considered to be the dominant process generating N2O in generally well aerated, coarse-textured soils , application of conservation tillage in these soils may result in soil compaction and poor aeration, suppressing nitrification and its associated N2O emissions.In contrast, denitrification is often the primary N2Ogenerating process in fine-textured soils due to a generally higher prevalence of anoxic microsites.Therefore, application of conservation tillage to fine-textured soils may result in the development of additional anaerobic conditions through compaction and greater water retention owing to the higher micropore content of compacted soils, which favor the development of additional anaerobic microsites for denitrification.Soil pH and clay content were identified to significantly affect the N2O emission effect size from the implementation of conservation tillage.Our analysis indicated a significant increase of N2O emissions in acidic and alkaline soils but not in neutral soils.Greater N2O emissions in acidic soils have been previously reported.In acidic soils, stepwise denitrification was purported to be suppressed by an attenuation of reductase activities that hinder N2O conversion to N2, resulting in the accumulation of N2O in acidic soils.In contrast, nitrifiers generally perform better in neutral to slightly alkaline soils , which may contribute to increased N2O emissions in alkaline soils.The effect of clay content on N2O emission in our analysis contradicts the expectations of increasing N2O emission with increasing clay content.The significant increase of N2O emission in soils with low clay content was mostly associated with medium-textured soils, which was consistent with the results of our soil texture evaluation.However, the sample size for low clay content soils was small, which could bias the results.More comparisons are necessary for a rigorous exploration of the effect of clay content on soil N2O emission in conservation tillage systems.

As expected, increasing N application rates led to increased N2O emissions.Similar results were reported from short term trials evaluating the influence of N application on N2O emissions in Mediterranean soils.Enhanced inorganic N from fertilization would be expected to intensify nitrification-denitrification processes resulting in increased N2O production.A linear response of N2O emission to N application rate was identified when the N fertilizer rate was less or equal to that required to achieve maximum crop yield, while an exponential increase in N2O emission was observed in soils with higher N inputs.Contrasting water management practices showed a significant in- fluence on soil N2O emission in conservation tillage systems.Irrigation significantly increased soil N2O emissions, consistent with the findings of Cayuela et al..The drying and wetting cycles created by irrigation provide an ideal environment for coupled nitrification denitrification.Nitrate production during the dry period is available for denitrification when irrigation increases the WFPS leading to potential anaerobic conditions.A significant difference was found between residue retained and residue removed treatments following implementation of conservation tillage, consistent with the report by Baggs et al..Retention of residues provides substrate for microbial growth through mineralization, which should increase denitrifier and nitrifier abundance depending on oxygen content.Inorganic N released from residue by mineralization would further stimulate the N2O production processes.Finally, consumption of soil O2 from enhanced organic matter decomposition may contribute to a greater prevalence of anaerobic conditions that favor denitrification.Our analysis indicated that crop rotation reduced N2O emission from conservation tillage as compared to non-rotation systems.Previously, no significant effect of crop rotation on N2O emission was found by Omonode et al..As our analysis indicated a relatively weak significance level for crop rotation effects on soil N2O emission dynamics, further investigations are warranted to better understand the complex interactions between crop rotation and N2O emission.Our meta-analysis showed a crop-specific effect on conservation tillage induced N2O emissions.The higher N2O emissions from maize, wheat and rice may be related to the higher N fertilizer application rates for these crops as compared to the lower and insignificant effects from beans and other crop types that generally receive lower N fertilization rates.The relatively small increase of N2O emissions determined in rice paddies following conservation tillage was similar to that reported by Zhang et al.and is possibly due to the dominance of anaerobic conditions that favor complete denitrification and thus a lower yield of N2O relative to N2.

How might private and state-owned enterprises differentially affect other markets?

The authors report that the US government had no intentions for the firms other than as investors, and intended from the beginning to sell off the firms.Because subsidies and other soft budget constraints were not applied to these firms, and firm ownership was perceived to be transferrable, efficiency differences between ownership types were likely diminished relative to other cases in competitive markets.The authors further argue that the state-owned firms were monitored using mechanisms comparable to those in the private sector firms comprising their comparison group, reducing any agency issues that may have already been mitigated by the competitive markets within which the firms operated.Isik and Hassan are unique in being the only study to report that public firms were more efficient than private firms.The authors use measures of cost and technical efficiency to evaluate ownership effects among Turkish banks, and use non-traditional outputs to construct their measures, such as the number of letters of guarantee issued, and the number of loan commitments provided, thereby avoiding price sensitive data in their calculations.A broad overview of the empirical literature across the spectrum of competitive environments suggests that ownership differences appear to diminish in more highly competitive environments.Detailed examination reveals complexities that both sharpen this result, and provide a more nuanced understanding of the theoretical issues that drive efficiency differences between ownership types.Boylaud and Nicoletti provide an example of how, because privatizations may be announced at one time and executed at another time, some “ownership”effects may occur prior to actual ownership.Additionally, a closer look at Wallsten shows that price regulation common in monopolies can create effects similar to competition, so that firms existing in a non-competitive environment can display some of the efficiency characteristics of competitive firms.

While both of these studies find no efficiency effects to ownership alone, they each provide evidence that the entire process of privatization provides efficiency benefits,hydroponic gutter some of which occur prior to the the ownership transfer and after typical regulations are applied.In competitive environments, although 3 of the 7 studies reviewed find that private firms outperform state-owned firms, none of the 3 studies that avoided price-sensitive measures found this result.While this is by no means conclusive, it may suggest that this study’s criteria for competitive environments are not so stringent as to prevent a certain amount of price-setting behavior, so that price-sensitive measures of efficiency in this environment could reflect revenue increases.Accounting for these details strengthens the evidence that increased competition reduces efficiency differences between public and private ownership.According to theory, this implies that, as competition increases, reductions in agency issues have a positive effect on the relative efficiency of state-owned firms that dominates the negative effect from increasing reliance on soft budget constraints.However, the evidence suggests that this may be true only because soft budget constraints are not increasingly relied upon as competition increases, rather than because their effects are insignificant.Amongst non-competitive firms, there is evidence of soft budget constraints in 3 of the 7 studies; in competitive firms, none report any evidence of soft budget constraints.The reason for this deviation from theoretical expectations may be the prevalence of price regulations among monopolies in our sample of studies, which compel both private and public firms to supply at prices and quantities that might otherwise be found at much higher levels of competition.When assessing whether private or public firm ownership is more beneficial to society, the consensus has shifted over time.In the early and mid-20th century, both theoreticians and policymakers emphasized the potential for social losses in privatized markets due to market failures such as monopolistic pricing and externalities, and saw state ownership as a cure for these problems.In the last few decades, the argument that private firms are more innovative and efficient has held sway.Moreover, the theoretical foundations for state ownership have been weakened by the notion that regulation can solve market failures and achieve any distributional goals of the state by controlling the undesirable actions of private firms, while still allowing them sufficient freedom to innovate.However, unless policymakers can fully anticipate the behaviors of private firms, regulations may alter incentives for profit maximization in ways that lead to unintended consequences.In this paper, I study how private and state-owned sugar mills differentially affect the outcomes of farmers who grow both sugar cane and other crops, in Tamil Nadu, India.

Because the activities of sugar mills are highly monitored and regulated within the market for sugar cane, I posit that private sugar mills may pursue profits through less-regulated channels, such as discouraging substitute activities for their vendors by making it less profitable to grow other crops.In the setting of this study, private firms have both a motive and a potential means to affect the profitability of substitute activities.Sugar mills have high returns to scale, and benefit from increasing the quantity of raw sugar cane they receive from farmers.In addition, a regulatory system in the state assigns a zone to each sugar mill, within which it has exclusive rights to purchase sugar cane from farmers, and outside of which it cannot purchase sugar cane.While the zoning system is intended to provide an incentive for mills to increase the productivity of existing sugar cane farmers within its zone3 , it also increases incentives for mills to discourage farmers in their zones from growing other crops in lieu of sugar cane.Because private mills typically have relationships with large agricultural conglomerates that supply inputs to crops other than sugar cane, they may plausibly act on these incentives by influencing the costs or availability of inputs to grow other crops.Tamil Nadu’s zoning system not only provides a case study of how private firms react to regulatory constraints differently from state-owned firms; it also serves as the source of identification in this paper.By studying households who grow crops near the borders between state-owned and private mill zones, I am able to compare the effects of public and private mills on farmers who otherwise exist in the same geographic and policy environments.I employ a regression discontinuity design to identify outcome differences that occur at the border, and test soil quality and other determinants of farming outcomes to verify that borders are not endogenously placed.I find that crops other than sugar cane have substantially higher costs and lower profits in private zones than in state-owned zones, although sugar cane outcomes are not significantly affected by sugar mill ownership differences.My findings suggest that private sugar mills discourage farmers from pursuing substitute activities to growing sugar cane, in order to increase the supply of inputs to mills.Only a handful of papers examine the differential impacts of private and state-owned firms empirically, perhaps because of the difficulty of finding settings in which ownership effects can be identified.Frydman et al find that private firms are associated with higher employment levels, using data on state and privatized firms across transitional economies in Central Europe.Duggan studies private for-profit, private not-for-profit, and state-owned hospitals, and finds no difference in low-income patient health outcomes between ownership types.

The closest study to this paper is conducted by Mullainathan and Sukhtankar , who study how public and private sugar mills differentially impact sugar cane growers using the same identification strategy, and find small consumption gains among sugar cane growers who sell to private mills.However, none of these studies examine the effects of ownership differences on other related markets, and thus potentially overlook impacts resulting from private firms’ attempts to avoid regulatory scrutiny.This paper makes a unique contribution to the literature by examining the differential effects of state-owned and private firms on substitute markets for their vendors,U planting gutter and finds evidence that ownership structure can, indeed, have large impacts on vendors in these markets.This suggests that papers studying the effects of ownership on the economy may neglect important outcomes by constraining their analysis to the market of treatment.The study also employs an unusually clean identification of public and private ownership effects, as it compares the effects of publicly- and privately-owned firms on farmers who grow crops in otherwise similar environments, but must sell sugar cane only to a state-owned or private mill, respectively.In addition, the paper examines the consequences of a zoning policy common in India and other developing countries, and presents findings that broadly demonstrate how private firms might respond differently to regulations than state-owned firms.Lastly, the survey conducted to gather data for this paper contributes a novel dataset of farmer characteristics, growing practices, crop choices, and outcomes in rural India.The paper proceeds as follows: In Section 2.2, I discuss relevant theoretical differences between state-owned and private enterprises, and how they affect predicted outcomes in related markets.I also provide contextual information about farming in Tamil Nadu, and about sugar cane in particular.In Section 2.3, I describe my data and the regression discontinuity design I use for identification, along with identification concerns and how I address them.Section 2.4 discusses my analysis and results, and provides some explanations for what I find.To answer this question, I begin with a discussion of theoretical differences between private and state owned firms.It is commonly held that the goal of private firms is the maximal attainment of profits, while state-owned firms may have a variety of bottom lines, such as maximizing total gains to society, redistributing wealth amongst their stakeholders, or providing services that would not otherwise be provided by private enterprise.The arguments for state-owned firms are as varied as their potential goals: they may be intended to reduce social losses due to market failures, to promote social values, or to provide services deemed essential that may otherwise be neglected by the private sector.

However, these arguments – along with the distinction between private and state-owned firms – are dimmed somewhat by the ability of governments to regulate industries.If governments are able to perfectly specify their goals in contracts or regulations, then private firms that abide by their stipulations would fulfill any goals that state-owned firms are intended to accomplish.In practice, contracts and regulations may be incomplete, if governments cannot anticipate exactly what they wish to accomplish, or cannot completely specify how a firm must achieve these goals.Grossman, Hart, and Moore develop a theory of incomplete contracts that observes that the gaps in an incompletely specified contract allow firms the flexibility to make decisions that serve their own ends.Analogously, incomplete regulations give leeway to firms wherever laws do not specify how they must conduct business.These observations can be adapted to provide a more nuanced distinction between public and private sector firms in a regulated environment: While private firms are free to pursue profit maximization wherever regulations or government contracts do not specify how they must behave, state-owned firms can be thought of as completely regulated, and thus forced to act narrowly within the expectations of the government.Then, the difference between private and state-owned firms is the scope of activities that each can undertake to maximize profits, while fulfilling the regulatory obligations imposed upon it by a government.While this flexibility afforded to private firms can encourage innovation and efficiency, it may also lead to outcomes that were not envisioned by the government.In particular, since firms can profit from influencing related markets such as the substitute markets for their vendors, private firms may respond to regulations that constrain their within-market operations by increasing their activities in related markets, if they are less regulated.Scientists and policy makers in the international community, in both developing and developed countries, recognize the importance that agricultural technology and its extension has played in promoting the expansion of supply and increased productivity in the world over the past 30 years.Rosegrant and Evenson have documented the importance of new varieties and extension effort on Indian total factor productivity.Pingali, Hussein, and Gerpacio review the contributions made by the Green Revolution in South and Southeast Asia.Although Rozelle, Huang and Rosegrant, Fan and Pardey, and Lin measure the impact of agricultural research investment on China’s agricultural output, no one has systematically analyzed the determinants of total factor productivity.Understanding the process of technological impact on the productivity of food production in developing world’s largest country is important, since it is the main engine of production growth and increases in income from farming in countries after they have modernized their economies Past analyses, however, mostly have two shortcomings, both of which have limited the ability to closely investigate the way technology affects productivity.First, researchers typically have focused on supply or yield response or production function analysis and have not examined the impact on total factor productivity and, with the exception of Rosegrant and Evenson, the analysis has been highly aggregated, across states or provinces and especially across crops.Second, the research methods and measures of technological inputs also have limited the explanatory power of research analyzing the impact of research and extension investment.

One such simplification will be to focus on a single crop for any given region

The relationships between crop yields, weather and climate have been the focus of a great deal of attention in the Earth system science literature.This is due to concerns about securing food supplies for our growing populations and the potential challenges that climate change poses.Most studies have been concerned with establishing the current relationships between climate and crop yields, or making projections about changes in crop yields due to future climate change rather than extending this approach back into the past.Where historical information is used, it tends to be on a relatively recent time scale.Recently, researchers have attempted to infer the location and intensity of agricultural production during the Holocene on a global scale.These estimates are ultimately derived from estimates of past population sizes and make assumptions about how human populations use land for agriculture.Although such studies should be applauded for their ambitious scale, they have a number of features that make them less-than-ideal for our purposes.First, in order to test certain theories it is desirable to separate out achieved production and population from potential production and population.A number of interesting hypotheses about human social and political evolution invoke “population pressure” as a key variable in causing changes in human societies.For example,grow table hydroponic demographic-structural theory , argues that state instability and societal collapse is a result of the pressures on resources from population growth, which, in turn, leads to population decline.

Boserupian models of agricultural change, mentioned above, see agricultural innovations themselves as resulting from population pressure.Second, this approach does not make full use of the historical and archaeological information about past agricultural systems that could potentially inform estimates of productivity.Finally, the data on past population are fairly rough estimates, and are typically made at the coarsegrain level of a province or whole country.There is always some degree of uncertainty associated with these estimates, and unless handled with care, such an approach can indicate a false level of precision, given the data that are being used as inputs.In order to understand the impact of agriculture and increasing productivity on human societies, we need a “bottom-up” approach that estimates productivity or potential productivity independently of population size.Of key theoretical interest is using this information to estimate the carrying capacity of a given region.For our purposes, we define carrying capacity as the maximum human population size that can be supported in a given unit of space.It is a function of the physical and biological characteristics of the region being examined and is also dependent on the types of agricultural technology and techniques possessed by the population that affect the productivity of the crops grown in that region.Carrying capacity is something that can be calculated across agricultural systems and, therefore, facilitates comparisons between different time periods and regions.Furthermore, it is an important variable because it enables us to compare the actual population to the size of the population that could possibly inhabit such a region, including cases where there is a substantial mismatch between these two estimates.This can provide a measure of the population pressure a society experiences.

Mismatches could also reflect cases where a surplus is produced in order to guard against shortfalls in some years or where a substantial proportion of productivity is diverted to elite members of society.In the former case, we would expect actual population and a measure of carrying capacity that took into account annual fluctuations to converge over longer time periods, whereas this would not be the case in the latter example.The measure of carrying capacity can include technological or other cultural features that affect crop productivity.Therefore, over suitably long time periods and geographic scales, this estimate of carrying capacity will also provide a measure of relative agricultural productivity.In other words, in the absence of direct assessments of actual productivity, this measure is still likely to be informative about which regions and time periods were more productive than others.Such a measure is also extremely useful for testing many hypotheses about socio-cultural evolution.Previous work has attempted to calculate carrying capacity for hunter gatherers , which is a somewhat more straightforward task than for agriculturalists.This is because foragers’ sources of food are determined primarily by external climatic conditions and other characteristics of the physical environment, such as “unearned” sources of water, including rivers, which enable plant growth in otherwise arid environments.Although such climatic and environmental considerations are obviously important for agriculturalists, calculating agricultural carrying capacity has a number of added complications.One such factor is the characteristics of crops.Hunter-gatherer population densities tend to be highest in tropical regions with high temperatures and greater amounts of rainfall, i.e.where net primary production is high.On the other hand, large agricultural populations can be supported by grain crops derived from wild grasses.

Cereal productivity, and, therefore, agricultural population density, tends to be greatest when annual patterns of rainfall create seasonal climates that allow grains to dry properly , which is generally at higher latitudes.For example, in island Southeast Asia, rice productivity is highest in regions such as Java, where monsoon conditions create a more distinct dry season.Humans are also niche constructors par excellence , and agriculture is probably one of the most dramatic representations of our ability to substantially modify our environment and, thus, reduce or ameliorate the impact of external environmental factors.Artificial selection has also been a key process in improving crops and increasing yields over time, so having information about historic cultivars and varieties is of great importance.In addition to these crop characteristics, another important determinant of agricultural productivity is the level of agricultural technology and the specific agricultural practices that enhance productivity, which have varied dramatically in time and space.We return to this issue below.The fundamental idea behind this approach to estimating carrying capacity is to construct a function that predicts crop productivity based on a variety of theoretically informed inputs, the parameters of which will then be estimated and empirically validated.This estimate in terms of energy can then be converted into a population estimate based on an understanding of the energy requirements of human populations.In both cases, calibration and validation will require historical information about past crop productivities, ideally with as broad a geographic and temporal distribution as possible.Figure 2 shows examples of changing productivities of two cereal crops in two regions in Europe.In both cases, productivity has increased, but to what degree these changes are due to changes in climate, technology, or genetics needs to be assessed.Obviously, estimating potential agricultural productivity on a global scale and over long time periods is not an easy task.In order to make this task manageable, it will be important to employ a number of simplifying assumptions and strategies.

Because we are interested in assessing the amount of energy produced, a reasonable starting point is to focus on the major carbohydrate source grown.For example, based estimates of potential pre-Hispanic productivity in the valley of Oaxaca using only information on a single crop, maize.Previous experience with calculating carrying capacity in Europe suggests that reasonably accurate estimates can be obtained just by using a single crop such as wheat or rye.The focal crop will, of course, vary from region to region due to different histories of domestication and the spread of different crops.In some cases, when different crops seriously affect the estimate, it may be advisable to estimate carrying capacities based on more than one crop.In some places, ecological conditions may vary over a relatively small distance, such that one crop does well where another one does poorly.For example, Pacific islands are characterized by wet conditions on the windward sides,grow table where taro does best, and drier conditions on the leeward side, which favors sweet potato.Agricultural productivity varies in space and, importantly, in time.In recent years, a large amount of work has been conducted on historical climate change and the effects of climate on crop productivity.This work needs supplementing with information about historical crop yields and the cultural and technological factors that affect agricultural productivity.Unfortunately, such data are not readily available in the kind of systematic manner on a global scale that would aid these endeavors due to the general turn away from broad-scale theorizing and comparative perspectives in disciplines such as anthropology, archaeology, and history.Here, we demonstrate how initiative that we have developed, Seshat: The Global History Databank 2, can provide a framework for collecting the necessary information to model agricultural productivity in the past and, more generally, to test comparative hypotheses about cultural evolution and human history.Most historians and archaeologists studying agricultural systems or other aspects of human societies tend to be experts in particular time periods and/or tightly defined regions.Although there are some who argue that there are broadscale patterns and general processes shaping human history, their claims tend to rely on illustrative examples and are not systematically tested in the manner that is common in the natural sciences.However, in order to test competing ideas properly, a more rigorous way of adjudicating between alternative hypotheses is required.A barrier to such an endeavor is the lack of data of suitable quantity and quality in the kind of systematic format that is required.It is for these reasons that the Seshat project aims to work directly with historians and other relevant experts to construct a large-scale database that collates the most up-to-date knowledge and understanding of past human societies in a systematic manner.Importantly, the information is coded into well-defined variables suitable for statistical analyses so that different hypotheses can be rigorously tested.Although the Seshat approach can be applied to any aspect of human societies, in this paper, we focus in on the variables of relevance to agriculture.

As a sampling strategy, we have selected 30 regions of roughly 10,000 square kilometers from around the world that are delimited by natural geographic features, such valleys, plains, mountains, coasts, or islands.Examples of these Natural Geographic Areas, or NGAs, include Latium , Upper Egypt, Hawaii, and the Kansai region of Japan.We have employed a stratified sampling strategy such that the NGAs are broadly distributed geographically and exhibit substantial variation in the polities that inhabited these NGAs in terms of the degree and timing of the appearance of the first large-scale, complex societies.For information related to agricultural systems for each NGA, we are gathering data on variables that relate to the NGA itself and the forms of agriculture practiced there, going back as far as possible in the Holocene.In related projects, we are capturing information about all the polities that occupied the NGA during this time.This will allow us to match different sources of information about different aspects of human societies and enable us to test a range of different hypotheses about human social and cultural evolution.What information do we need to capture about past societies in order to estimate the productivity of agricultural systems? Over the last two years, members of our research team have been developing a codebook to describe the variables relating to agricultural productivity.Typically, variables in the codebook relate to the presence or absence of certain features , naming of specific features that were present , or a quantitative measure of certain features.The development of this codebook has been an iterative process, and has improved through discussing these issues with experts on agriculture in past societies.For each NGA, we examine the variables of interest during the time since agriculture was first practiced until the present day.Research assistants work with expert historians and archaeologists to identify the most relevant literature, attempt to code the variables in the codebook from these sources, and, where possible, indicate the time at which features appear or change.These codings are then ultimately checked for accuracy by experts in the appropriate region and/or time period.Currently, the variables we are coding relate to Land Use, Features of Cultivation, Technology & Practices, Conventions & Techniques, Post-Harvest practices, Food Storage and Preservation, Social Scale of Food Production, Agricultural Intensity, and Major Carbohydrate Sources.We describe each of the categories below and illustrate the kinds of variables we are capturing within them.Land use variables relate to the areas of the NGA that were either used for agriculture or that could potentially be cultivated.To give a couple of modern examples, according to the CIA World Factbook , around 25% of the total area of the United Kingdom is given over to crop production, whereas Japan, with its much more mountainous terrain, devotes only 12% of its land to producing crops.

Gillin provides interesting insight into the importance of water for the people of Moche

In Gillin’s ethnographic account of the town of Moche, he observed that many dishes were cooked or boiled over an open flame, either in ceramic or metal containers placed on an adobe brick stove or on rock supports placed on the ground. Gillin lists a variety of one pot meals, including soups, stews, or gruels, which often contained meat, maize , manioc, and/or beans. Typical kitchens contained ceramic cooking vessels, water storage jars, chicha fermentation jars, cooking hearths , fuels , woven reed or cane fans for igniting or intensifying cooking fires, grinding stones and pestles , wooden utensils, and various serving implements made from gourds including scoops, plates, and bowls. Gillin also points out that essential ceramic and ground stone implements were commonly acquired from nearby archaeological sites, and praised by the local population at the town of Moche as being the best quality kitchen tools. In my research in the Moche Valley for this dissertation project, I have been invited into homes and served meals in kitchen setups mirroring those described above, including stews of meat , maize, and beans cooked over open hearths in Chimu pots that smallholders recovered in their fields. It is likely that a variety of food preparation and processing techniques were implemented in the Moche Valley during the EIP, including boiling , roasting, steaming, parching, toasting , drying, soaking, and grinding.

Rowe describes how toasted maize, or cancha, was a popular food at the time of Spanish conquest in Peru .Water was considered important for irrigation,mobile vertical grow table food preparation, and bathing, but not for drinking; distaste for drinking water has been documented widely in the Andes . According to Gillin , many families drank chicha rather than water, and many women also used chicha for boiling meats and vegetables. It is likely that chicha production occurred regularly at domestic habitation sites in the Moche Valley in the past, for quotidian uses in addition to feasting events. Indeed, chicha would have remained potable longer through the process of boiling, and also would have reduced sickness due to contamination of the water supply. Chicha production would have required a specific set of tasks associated preparation/processing; to brew maize chicha, germinated maize is dried, ground, mixed with water, and fermented, to create an alcoholic liquid .Alongside maize, similar shifts in ubiquity values are noted for members of the Fabaceae family. Some members of the Fabaceae family present in the five Moche Valley assemblages could be identified to the genus or species level, including domesticated legumes , along with a number of weedy legumes. However, some remains only could be identified to the family level if they lacked clear diagnostic attributes to aid in more specific identification. For example, common beans and peanuts share many of the same attributes; if an attachment scar was not present, then it was impossible to determine the difference between these two taxa. As the common bean and peanut represent different genera, these specimens were recorded as “Fabaceae,” although noted as probable domesticated beans.

Domesticated Fabaceae, including common beans, lima beans, and peanuts, have low ubiquity values across the study sites , likely due to preservation bias. As beans are consumed in their entirety after cooking, they are less likely to appear in archaeological assemblages than plant foods that require processing . Indeed, no clear domesticated beans were identified in the La Poza or MV-83 assemblages . A number of partial or complete domesticated bean fragments were present in the MV-224, MV-225, and MV-83 assemblages; in addition, some specimens that could only be classified to the family level of Fabaceae likely represent domesticated forms, but lacked diagnostics to distinguish between common bean, peanut, and pacay. However, the lack of domesticated beans at La Poza and MV-83, when considered in relation to overall Fabaceae presence, may have some implication for cropping strategies. If we group all of the Fabaceae for each assemblage together and chart ubiquity values through time , we see an increase from 23.5 percent ubiquity at La Poza to 58.1 percent at MV-224. This ubiquity trend remains fairly consistent across the remaining three study sites through time, with Fabaceae ubiquity values of 56.2 percent, 55.6 percent, and 50 percent for MV-225, MV-83, and Galindo, respectively. I interpret these trends along two lines, suggesting that the increases in Fabaceae may represent increased collection/incidental intrusion of weedy leguminous taxa that grow in and along fields as maize production increased, and possible intercropping of maize and beans. As discussed above, intercropping Phaseolus beans with maize would have provided benefits to both plants; nitrogen fixation from beans benefits maize plants, and beans benefit from having the maize stalks to climb during growth .

This pattern gives us pause to reconsider rigid taxonomic distinctions that give a taxon like chenopod a quintessential ‘highland’ identity in cuisine ; rather, interaction, melding, and movement between the coast and highlands, which likely involved the exchange of resources as well as knowledge of plant cultivation strategies, contributed to the formation of middle valley chaupiyunga cuisines. Furthermore, as food ways often are divided by social status, identity/ethnicity, or context, it seems problematic to attribute such a singular identity category as ‘highland’ to a particular food taxon. Another taxon of note is cotton. While ubiquity values for cotton are low at La Poza and MV-83 , no cotton seeds were recovered in the MV-224 and MV-225 assemblages. In contrast, cotton seeds have a very high ubiquity value in the Galindo samples. This trend is noteworthy in that it sheds light on practices related to an important economic activity, spinning and weaving. The fact that no cotton seeds were recovered in either the MV-224 or MV-225 assemblages indicates that cotton fiber textile production may not have been practiced widely at these sites. This issue may be a result of preservation bias, as cotton seeds may be less likely to enter fires than food taxa; however, carbonized cotton seeds were recovered in the other middle valley assemblages , including in very high ubiquity at Galindo. Ringberg reports the presence of ceramic disk spindle whorls known as torterosand pirurosin patio spaces at MV-225, suggesting that women, or possible children and elderly of both genders, used open, well-litpatio spaces for spinning and weaving.

Although the sample size of torteros at MV-225 was small, ethnographic evidence suggests that large tortero whorls were used on the Peruvian north coast to ply heavier fibers into rope or twine . Wooden spindle whorls may have been used for this purpose as well . The lack of cotton seeds in the archaeobotanical assemblage at MV-225 may indicate that camelid fiber spinning took precedence over cotton fiber spinning during the Gallinazo/Early Moche phases. Indeed, the highland occupants of MV-225 houses and tended camelids, a tradition that continued at MV-83 and Galindo. Amber VanDerwarker found that camelids were the main source of meat at MV-83, and that households processed the whole animal for consumption, in contrast to obtaining dried meat or leg meat. These animals were likely used for their wool in addition to meat. The presence of camelids at these middle valley sites also challenges long-standing typologies that categorize such as animals as exclusively ‘highland’ in nature —as the local costeño occupants of MV-224 appear to have interacted and likely intermarried and cohabitated with serrano colonists, they likely bred and herded camelids as well for wool and meat. Future analyses of faunal assemblages from MV-224 and MV-225 will likely clarify the nature of these dynamics. With respect to ubiquity overall, Galindo witnessed a greater range of taxa that are highly ubiquitous in the assemblage as compared to the other assemblages, which are dominated by five or less taxa. However, the Galindo archaeobotanical dataset is made up of only ten samples. While this sample number meets Hubbard’s minimum threshold for ubiquity calculation , having fewer samples more severely skews frequency scores of rare taxa. As a result, I interpret rare taxa ubiquity values with caution. I will use the taxon of coca as an example. Coca is a special use taxon; it is neither ubiquitous nor abundant in the Moche Valley samples. Indeed, only one coca seed was recovered in the MV-225 assemblage,mobile vertical farm and four coca seeds total were recovered from the Galindo assemblage .

The paucity of coca in these deposits likely is related to preservation biases. Coca leaves are chewed raw , and stems and seeds are separated before the bola, or wad of leaves, is placed in the mouth for chewing. In the of context quotidian routines, coca chewing likely would have been done along walks to agricultural fields or when laboring in fields, to provide energy and to act as an appetite suppressant. Coca seeds are therefore unlikely to be burned and dropped in cooking fires and therefore are less likely to leave behind carbonized remains at domestic habitation sites. It is likely that the residents of these Moche Valley sites grew and consumed coca, particularly the residents of the Middle Valley sites; indeed, the middle valley sites are located within primary production zones for coca for the valley determined by agroecological zonation models . While conducting research for this dissertation in the Moche Valley, I frequently noticed the presence of coca in family smallholdings and community gardens throughout the middle valley . In their analysis of oral health indicators and phytoliths from dental calculus, Gagnon et al. argue that coca use decreased among the coastal skeletal population buried at Cerro Oreja from the Salinar to Gallinazo phases; they attribute this pattern to the occupation of the coca-growing regions of the Moche Valley by highlanders during the Gallinazo phase. Ethnohistorical research has documented that control of limited coca fields was an important source of wealth and a site of conflict between coastal and highland groups in this region , dynamics Billman argues extended deeper into the past . It would be intriguing to compare the coastal skeletal population at Cerro Oreja to an EIP highland burial population to test this hypothesis .

Regardless, coca probably was an important resource consumed by residents of the Moche Valley during the Gallinazo/Early Moche phases, including highland colonists; the fact that coca is unlikely to be preserved in carbonized form appears to be the reason for its paucity in the Moche Valley samples. Returning to the ubiquity problem noted above, the single coca seed recovered at MV-225 out of 143 samples produced a ubiquity value of 0.7 percent, whereas the four coca seeds recovered at Galindo out of 10 samples produced a ubiquity value of 10 percent. Represented by one and four specimens at MV-225 and Galindo, respectively, it cannot be said that coca was truly more abundant or used more widely at Galindo than MV-225, although ubiquity values might cause a reader to infer otherwise. In summary, a basic assessment of the plant assemblages from the five Moche Valley sites reveals some broad similarities in the types of plants collected and produced; and the importance of maize relative to other taxa at the sites. Despite these similarities, however, quantitative analysis reveals significant differences in terms of the standardized counts of different plant food categories, differences that allow us to offer insight into the nature of subsistence shifts related to maize and other cultigen intensification. To further explore changes in plant use through time, I turn to an exploratory data analysis using box plots to assess statistical difference between the five Moche Valley assemblages. As discussed above, if the notched areas of any of the boxes do not overlap, then the distributions are significantly different at the 0.05 level. Outliers are depicted as asterisks and far outliers as open circles. In some cases, distributions of smaller sample sizes will cause notched boxes to overextend and then fold back on themselves. All plots are logarithmically transformed. I initially began my analysis by comparing densities of maize, other cultigens, fruits, and miscellaneous/wild resources across the five different sites. What I found was that every single plant category was represented in greater density at MV-83 than at the other sites. I therefore calculated total plant density, finding that there was a significant difference in the overall density of plant remains between MV- 83 and the other study sites . This pattern may reflect several things: better plant preservation, a change in the manner of plant deposition, a difference in disposal patterns, a reflection of higher settlement population in the areas sampled at MV-83 compared to the other study sites, etc. What is clear, however, is that density measures cannot speak to differences in plant diet/use in this particular comparison.

It is likely that some of these rodents survive baiting by consuming a sub-lethal dose

The higher incidence in the western states may suggest that workers in this region are at higher risk of drift exposure; however, it may also have resulted from better case identification in California and Washington states through their higher staffed surveillance programs, extensive use of workers’ compensation reports in these states, and use of active surveillance for some large drift events in California.Nonoccupational exposure.This study found that more than half of drift-related pesticide poisoning cases resulted from nonoccupational exposures and that 61% of these nonoccupational cases were exposed to fumigants.California data suggest that residents in agriculture-intensive regions have a 69 times higher risk of pesticide poisoning from drift exposure compared with other regions.This may reflect California’s use of active surveillance for some large drift events.Children had the greatest risk among nonoccupational cases.The reasons for this are not known but may be because children have higher pesticide exposures, greater susceptibility to pesticide toxicity, or because concerned parents are more likely to seek medical attention.Recently several organizations submitted a petition to the U.S.EPA asking the agency to evaluate children’s exposure to pesticide drift and adopt interim prohibitions on the use of drift-prone pesticides near homes, schools, and parks.Contributing factors.Soil fumigation was a major cause of large drift events, accounting for the largest proportion of cases.Because of the high volatility of fumigants, specific measures are required to prevent emissions after completion of the application.Given the unique drift risks posed by fumigants, U.S.EPA regulates the drift of fumigants separately from non-fumigant pesticides.

The U.S.EPA recently adopted new safety requirements for soil fumigants, which took effect in early 2011 and include comprehensive measures designed to reduce the potential for direct fumigant exposures; reduce fumigant emissions; improve planning, training,dutch bucket for tomatoes and communications; and promote early detection and appropriate responses to possible future incidents.Requirements for buffer zones are also strengthened.For example, fumigants that generally require a > 300 foot buffer zone are prohibited within 0.25 miles of “difficult to-evacuate” sites.We found that, of the 738 fumigant-related cases with information on distance, 606 occurred > 0.25 miles from the application site, which suggests that the new buffer zone requirements, independent of other measures to increase safety, may not be sufficient to prevent drift exposure.This study also shows the need to reinforce compliance with weather-related requirements and drift monitoring activities.Moreover, applicators should be alert and careful, especially when close to non-target areas such as adjacent fields, houses, and roads.Applicator carelessness contributed to 79 events , of which 56 events involved aerial applicators.Aerial application was the most frequent application method found in drift events, accounting for 249 events.Drift hazards from aerial applications have been well documented.Applicators should use all available drift management measures and equipment to reduce drift exposure, including new validated drift reduction technologies as they become available.Limitations.This study requires cautious interpretation especially for variables with missing data on many cases.This study also has several limitations.First, our findings likely underestimate the actual magnitude of drift events and cases because case identification principally relies on passive surveillance systems.Such under reporting might have allowed the totals to be appreciably influenced by a handful of California episodes in which active case finding located relatively large numbers of affected people.Pesticide-related illnesses are under reported because of individuals not seeking medical attention , misdiagnosis, and health care provider failure to report cases to public health authorities.

Data from the National Agricultural Workers Survey suggests that the pesticide poisoning rates for agricultural workers may be an order of magnitude higher than those identified by the SENSOR-Pesticides and PISP programs.Second, the incidence of drift cases from agricultural applications may have been underestimated by using crude denominators of total population and employment estimates, which may also include those who are not at risk.On the other hand, the incidence for agricultural workers may have been overestimated if the denominator data under counted undocumented workers.Third, the data may include false-positive cases because clinical findings of pesticide poisoning are nonspecific and diagnostic tests are not available or rarely performed.Fourth, when we combined data from SENSOR-Pesticides and PISP, some duplication of cases and misclassification of variables may have occurred, although we took steps to identify and resolve discrepancies.Also, SENSOR-Pesticides and PISP may differ in case detection sensitivity because the two programs use slightly different case definitions.Lastly, contributing factor information was not available for 48% of cases, either because an in-depth investigation did not occur or insufficient details were entered into the database.We often based the retrospective coding of contributing factors on limited data, which may have produced some misclassification.Anticoagulant rodenticides are the most common baits used in agricultural and domestic areas to manage rodent pests.They are generally classified as first- or second-generation anticoagulants based on their toxicity relative to the amount of bait a rodent must eat.The first-generation anticoagulants such as chlorophacinone, diphacinone, and warfarin usually require multiple feedings over several days to be lethal.The second-generation anticoagulants, such as bromadiolone, brodifacoum, and difethialone, are more persistent in animal tissues and in many situations can be lethal from only one feeding.In California, only firstgeneration anticoagulants are registered for agricultural uses.

Almost 1 million pounds of formulated chlorophacinone and diphacinone baits are sold annually by California Agricultural Commissioners to control agricultural ground squirrels, voles, and some other rodent pests.Additional firstgeneration anticoagulant bait is sold by commercial outlets for agricultural protection and some commensal use, but use data are not readily available.A much larger quantity of second-generation anticoagulants is sold to homeowners, structural pest control operators, and others for control of commensal rodents in and around structures.All of these uses have the potential of creating primary and secondary poisoning risks to pets, domestic animals, and wildlife including birds of prey.Various predators and scavengers in California have tested positive for second-generation anticoagulants, while a much lower number of first-generation exposures have been detected.However, without information on anticoagulant use patterns in the areas where these animals were collected, we cannot paint a complete picture of the exposure risks and impacts of anticoagulant use in agricultural production areas.Yet, in the absence of such data, persons concerned about pesticide residues in wildlife often assume that anticoagulant rodenticides used in agriculture cause widespread risk to non-target wildlife, particularly predators and scavengers of rodents.This study was undertaken to help understand the extent of raptor exposure to anticoagulants, particularly in relation to anticoagulant uses for protecting agriculture.Data were utilized from raptors that were collected as part of the public health surveillance programs of the County Veterinarian and/or Departments of Environmental Health, as well as by submission from other organizations such as California Fish and Game and the United States Department of Agriculture – Wildlife Services.None of the raptors analyzed were initially suspected of having anticoagulant exposure or poisoning.The ultimate goal was to determine possible raptor exposure to first- and second-generation anticoagulants by evaluating the relationship between the use of these materials in agricultural versus urban settings and the presence/absence of residues in raptor tissues collected from each region.A second objective was to determine if wild rodents captured as part of a county Hantavirus surveillance program would show any signs of exposure to anticoagulants.

While anticoagulant residues have been found in many carnivores, few reported data exist demonstrating the occurrence of residues in rodents found in areas where anticoagulant materials are used.The data that are available originates from rodents targeted by specific baiting programs.In turn, these survivors could have some anticoagulant residue remaining in their tissues, providing a possible exposure route for raptors and carnivores.San Diego County has a robust public health surveillance program that includes testing of raptors and other birds found dead throughout the County.This provided a large number of raptors for potential analysis.Since San Diego County is fairly urban, we wanted to compare data from these birds with birds from more rural and agricultural counties.The top 5 agricultural counties with the highest quantity of total agricultural pesticide use in California in 2007 were Fresno, Kern, Tulare, San Joaquin, and Madera.Of these, Fresno, Kern, and Tulare Counties were selected because we have worked on extensive ground squirrel problems in these areas for the past 30 years.We sought to compare anticoagulant residue data from raptors collected in these counties to those from the more urban San Diego County, where we assume most rodenticides applied are used by homeowners for the control of commensal rodents.California has been faced with a shortage of farm labor in recent years , primarily attributed to a decline in the number of Mexican migrant workers coming to the United States, who compose the majority of the labor force.Compounding the decline from abroad, migration within the United States has also dropped as farm labor has undergone a demographic transition: workers are more likely to be older, female and living with children.Labor shortages appear to have especially affected support activities,blueberry grow pot such as labor contractors.For example, the Napa County vineyard industry experienced an estimated 12% shortage of laborers in 2017.The agricultural industry is responding to this labor shortage in three ways.First, growers are increasingly relying on machines to stretch worker productivity or as a substitute for hand labor.Second, they are seeking to replace lost workers with a new labor source — for example, women and H2-A guest workers, although the complications of providing housing in coastal California have limited the viability of the H2-A guest workers option.The third way is the focus of this study: offsetting the labor shortage by boosting retention of existing workers through increased job satisfaction.High job satisfaction, defined as a “pleasurable or positive emotional state resulting from one’s…job experience” , is linked to positive effects on both employees and organizations, with evidence of a causal relationship.Benefits include lower worker turnover , increased work performance , lower absenteeism and healthier workers.Job satisfaction has been categorized in numerous ways, but core categories include the type of work performed, rewards, professional growth or promotional opportunities, supervision, and coworkers.

Additional categories may be included under specific circumstances , and the most salient categories often differ between occupations.Conversations on how to address satisfaction in the agricultural workplace understandably tend to focus on pay and benefits, with some acknowledgment that reducing harassment and favoritism is also beneficial.Because the nature of the relationship between job satisfaction and turnover goes beyond financial compensation, companies may seek to reduce turnover by adopting strategies that carry a lower financial burden.This includes respectful treatment of workers, ensuring a safe workplace, providing workers a diversity of tasks and promotional opportunities, and formalizing labor relations procedures.Despite decades of research on job satisfaction in other occupations , there has been a paucity of research on agricultural workers.To date, the few studies of satisfaction in California agriculture have been primarily based on interviews of workers.Building on this qualitative work, we developed a quantitative survey to identify and describe the job satisfaction categories that drive turnover in a population of Napa County vineyard workers.We investigated how satisfaction may vary by three key demographics — employment status , gender and age.And we conducted a limited set of follow-up interviews with a selection of participating workers to explore specific issues raised in the survey.Collectively, these results provide feedback to agricultural employers from their workers on how their company is performing in various aspects of job satisfaction, which strategies and activities they should invest in to boost job satisfaction, and how they can adapt their strategies to target specific worker demographics.We envision the agricultural industry adopting this survey tool to formally evaluate their progress toward improved job satisfaction and increased workforce sustainability.In summer 2018, we surveyed 611 vineyard crew members and 54 of their immediate supervisors from 14 companies operating out of Napa County.There were an estimated 10,000 vineyard workers in Napa County in 2018, and our survey therefore captured approximately 6.5% of the workforce.Participating employers learned about the study through contact with or recruitment by the UC Cooperative Extension research team or by advertisement at industry meetings.Under previous arrangements with their employer, survey participants completed the questionnaire in small groups while at work and were paid their normal hourly rate while they participated.Since all participants were Spanish speaking, the study was conducted in Spanish by a bilingual research assistant who displayed the questions on a flipchart and also read them aloud in Spanish.

Individuals working on a resources or database should be named on the website

Distributed and independent genome projects produce assemblies and annotations that can be beneficial to research on related species, if researchers can discover them. However, even a multi-species database that manages gene families may not contain all gene data of interest to the communities it serves. Services that assign new data, supplied by researchers or by other sites, to gene family memberships can help with discovery across databases by putting new sequence data into an evolutionary context, but then the data must be discoverable broadly.Applications that can operate where the data exists, to support comparative access for pre-publication and privately maintained genomes, can reduce the need to move large data sets among locations. For example, a group might generate a draft assembly of an accession with a novel phenotype that they have mapped to a certain genomic region. They may then wish to compare the scaffolds that contain the region of interest to a reference assembly for a different accession or for a related species, to find candidate genes that may be novel to their accession. Existing services such as CyVerse can be used to analyse data from many sources. Being able to do the comparison where the different genomes are located would save moving and duplicating large genome files, but requires considerable investment in distributed computation. Another solution is for GGB databases to host a local Galaxy instance connected to a Tripal database with public and private data sets. This is effective if a researcher with phenotypic,nft hydroponic genotypic and environmental data needs a place to house the data both before and after publication, but is not an expert in genomic analyses or data management.

Analysis pipelines tailored to the needs of a particular community, hosted through that community’s database, allow researchers to upload, search and visualize private data and public data, select these data and parameterize an association mapping workflow and execute that workflow locally. In order to execute the analysis remotely, data will need to move efficiently from the database to a remote analysis platform.Scientists often want to discover all that they can about a particular entity , but the data are distributed across multiple resources, many of which may be unfamiliar. Each data element on its own is not large, but the total space to be searched is. A hypothetical workflow is as follows: a researcher who works on one species comes to a participating database with a sequence of interest, wanting to find out what biological functions their sequence might be involved in. The researcher identifies homologous sequences in the new database by running BLAST. The database converts the BLAST results to an exchangeable token and queries other databases for information about orthologs. The product of these requests could be as simple as a gene name/symbol and a URL to point the user to the data display at the external database, or could also include provenance and database information for attribution, sequence, publications and many other types of information. For data discovery to work, databases with relevant data and compatible APIs must be discoverable and well documented, and a method should be in place to track usage across different services.There are several mechanisms for outreach to researchers. The most common form of outreach is meeting and conference attendance. With a large number of researchers at meeting and conferences GGB databases can use these opportunities for workshops, presentations or a database booth. GGB database brochures can be handed out during the meeting and conferences. However, there are a number of researchers that are unable to attend meeting and conferences so it is important that GGB database also use other forms of outreach. These include newsletters, mailing lists, blog posts and social media to inform researchers about new tools or data, webinars, workshops and videos.

These forms of outreach can be used together to reach a broader audience. Using social media during conferences and meetings with the appropriate hashtag can send information about new tools and data to researchers who cannot attend the conference. A prime example of this is the Plant and Animal Genome Conference, which has a strong social media presence.Many online resources and databases do not mention the people on their teams and only provide an anonymous contact form.Being anonymous creates a barrier to communication, and if contact/feedback forms don’t generate a response, there is no further recourse for the researcher to get help. Providing individual staff contact information and even photographs makes it easier for researchers to target questions to the appropriate person. Photos can enable researchers to find curators at meetings, and in general encourage communication by putting, literally, a human face on the GGB resources. Building in dedicated time at workshops for a ‘meet the team’ event, well advertized in advance to the research community, is also recommended to increase engagement opportunities.Overcoming the challenge of reliable data submission will require communication among representatives from the appropriate journals, GGB databases and funding agencies to establish guidelines and an easy-to-submit and police system for researchers and the journals/funding agencies and databases. This would likely be best initiated through an inter-agency sponsored workshop, followed up by regular meetings and assessment of effectiveness. Such a workshop could also develop ways to ensure journal publishers and editors are aware of all relevant GGB databases so they can direct authors of each accepted paper to the proper repository, nomenclature clearing house etc.

Providing access to centralized cyber infrastructure where databases, journals and funding agencies could sign off on successful data submission for projects would help make this process easier for all parties and ensure accountability.The GGB databases that currently comprise the AgBioData Consortium were created to serve the needs of researchers for access to curated and integrated data and analysis/visualization tools to aid scientific discovery, translation and application. The funding for these databases, however, is limited and not stable. Maintaining these resources in the longer term so that invaluable data are kept up-to-date and do not get lost is a major issue facing almost all AgBioData databases, their researcher communities and funding agencies.AgBioData databases are supported through a variety of sources. Generally these fall into one of four categories: primarily supported through line-item government funding, such as the USDA-ARS databases MaizeGDB, SoyBase, GrainGenes, Legume Information System and GRIN; primarily supported through competitive federal grants, such as TreeGenes, Hardwood Genomics, Gramene, Planteome, Solanaceae Genomics Network and Araport; supported through a combination of competitive federal grants, commissions and industry, such as the Genome Database for Rosaceae, AgBase, PeanutBase, AnimalQTLdb and CottonGen; and supported primarily through a user subscription model, such as TAIR. With long-term government funding, the USDA-ARS databases enjoy the most stable financial support of the AgBioData databases. They typically represent high-value commodity crops serving a large research and industry community. While the level of support provided by USDAARS generally allows for continuation of base activities and curation, it typically does not provide resources for technical innovation or more resource-efficient systems to be implemented. For these, funding through competitive grants is increasingly necessary,nft system as in the case of the NSF funded Legume Federation award. At the other extreme lies TAIR, which after a phased withdrawal of support by NSF, successfully implemented a subscription-type funding model under a not-for-profit organizational structure.

As the model plant for functional genomics, TAIR also has a large user community making this funding option more feasible to implement than for the databases represented in categories 2 and 3. Many of the AgBioData databases have reported willingness of the scientific stakeholders to budget some funds in their grants to support data deposit and access to their community databases, similar in how they budget for peer reviewed, open access publications costs. Unfortunately, most of the databases do not have organizational structures or processes that would allow them to accept these funds.How can studies of agricultural systems and the ways that people interact with foods they produce, eat, and discard lead us to new understandings about social relations in the past? How do labor roles, gender relations, and status-based inequalities relate to these types of interactions? This dissertation addresses these themes through the lens of food ways in the prehispanic Moche Valley of north coastal Peru. The Peruvian north coast witnessed a profound series of social and political changes during a time period that archaeologists refer to as the Early Intermediate Period, or EIP , with far-flung consequences for members of various social standing, from rural households to political centers. The EIP was marked by an increase in political complexity, with clear shifts in settlement and site reorganization accompanied by an increase in social stratification . These cultural and political changes occurred in a vertically compressed environment that also witnessed periodic El Niño events, which had significant and varied impacts on people’s subsistence practices. Indeed, substantial changes in elevation over the relatively short distance from the coast to the highlands, in the Moche and neighboring river valleys, create different micro-environments within close proximity to one another. Fertile interande an valleys have constituted a prime interaction zone between people of the highlands and the densely populated Peruvian coast, a contact dynamic that initiated in prehistory and continues today.The beginning of the EIP, which includes the Salinar and Gallinazo phases, witnessed the abandonment of earlier ceremonial centers; population increases and expansion of irrigation systems; political fragmentation and the appearance of formal fortifications and settlements in defensive locations; and cooperation and conflict between coastal and highland groups and among polities of various coastal valleys . Between approximately 300 and 800 A.D., the iconic Moche culture flourished on the Peruvian north coast.

The large adobe pyramid complex of the Huacas de Moche was constructed, accompanied by the emergence of a new regional political economy in which Moche rulers exercised significant economic, military, and ideological power over the population of the Moche and adjacent valleys. How did these periods of profound social change affect the prehispanic residents of the Moche Valley in terms of gender relations, status, and the organization of labor in ancient rural households? Foodways data provide a critical lens for examining these issues. Foodways represent a fundamental axis along which identity is constructed and maintained, and are increasingly recognized as having played a prominent role in the emergence of social hierarchies and the negotiation of status and power . In this dissertation, I incorporate archaeobotanical, environmental, and ethnohistorical evidence to address changes in food production, processing, and consumption during the EIP, a period that included the consolidation of the Southern Moche polity, one of the largest and most complex pre-Columbian political systems in the New World. Conducted inconjunction with MOCHE, Inc., a 501c3 nonprofit dedicated to protecting archaeological sites through community heritage empowerment, this project involved a large-scale comparative analysis of paleoethnobotanical data sampled from five EIP habitation sites that span the period of political transformation and state formation in the Moche Valley. The data presented in this dissertation derive from three major projects conducted in the Moche Valley in collaboration between North American and Peruvian archaeologists since 2000: the Moche Origins Project , directed by Brian Billman and Jesus Briceño Rosario ; el Proyecto de Evaluación Arqueológico con Excavaciones en las Lomas de Huanchaco , directed by Gabriel Prieto and Victor Campaña ; and the Galindo Archaeological Project , directed by Gregory Lockard and Francisco Luis Valle . I employ diachronic and spatial analyses of archaeobotanical data from 225 soil samples recovered from five domestic habitation sites excavated within the contexts of these projects to address key issues that have largely remained untested with direct subsistence data. Through these analyses, I trace changes in food production and wild plant food collection during the EIP, considering issues of agricultural intensification and the resulting impacts on labor relations, gender roles, and social inequality for the pre-Columbian inhabitants of rural households in the Moche Valley. The question of scale looms large in this dissertation. The Moche civilization of northern Peru is one of the best-known and most intensely studied archaeological cultures of the ancient New World. The ancient Moche have captured the imagination of scholars and the public alike, characterized by a series of elaborately decorated temple complexes, wealthy elite burials, and exquisite ceramics found over ten river valleys on the desert coast.

The 20th century brought significant changes to the economics of global agriculture

Beginning in the 1970s, economic researchers began to study the potential impacts of bans on the use of sub-therapeutic antibiotics on the pork, poultry, and beef sectors and on U.S. consumers, but there has been little study of how heterogeneity impacts antibiotic use, and in turn, how it impacts returns to using antibiotics in U.S. livestock operations. I concentrate on U.S. pork and poultry operations since they are the largest users of sub-therapeutic antibiotics by volume in the U.S., and explore the existing literature on the economics of sub-therapeutic antibiotic use for glimpses of heterogeneity in the returns to antibiotic use. Perhaps the most interesting source of heterogeneity in returns to antibiotic use may be heterogeneity in management and/or the use of potential substitutes for antibiotics, such as improved sanitation practices and more modern facilities. Productivity and use of technologies that substitute for STA use vary amongst producers, and likely by region and farm size. Thus, the marginal abatement costs of reducing STA use vary across industries, producers, production systems, and regions.In more developed countries such as the United States, the face of agriculture was once that of the small family farmer. Today, the agricultural landscape in developed—and to some extent developing— countries is dominated by agribusiness and large farming operations. While many of these operations are still family-owned and farm size, management, and production methods remain diverse, on the whole, farms are larger and more mechanized and specialized than ever before . This transition is a direct result of the increase in relative price of labor and changes in domestic and global agricultural policies , and was spurred by dramatic improvements in agricultural productivity, and a shift from more labor-intensive agriculture to more capital- and technology-intensive agricultural practices that employed new varieties,growing vegetables in vertical pvc pipe synthetic inputs, and irrigation.

While agricultural production in much of Asia, Africa, and Latin America is more heterogeneous and more labor-intensive in general, specialization, mechanization, and technological change have increased productivity of agricultural commodity crops such as soybeans and sugarcane in Brazil, wheat and rice in China and India, palm oil in Indonesia and Malaysia, and others . Incorporating and disseminating technological advances that improve productivity and incomes in smallholder farming systems remains a challenge throughout the developing world . In spite of—or perhaps in response to—this shift toward specialization and mechanization, there has been renewed momentum on the part of a vocal contingent of consumers, producers, researchers, and policy makers who draw attention to the social, environmental, and economic implications of this transition . They envision a new model of agriculture that employs fewer synthetic inputs, incorporates practices which enhance biodiversity and environmental services, and takes into account the social implications of production practices, market dynamics, and product mixes. Components of this movement are taking hold in the economic and cultural mainstream in the United States, Europe and other countries. Evidence of this shift includes the rise of organic, “fair trade”, and other production and certification schemes, and the growth of consumer willingness-to-pay for these differentiated food products. The prevalence of local farmers’ markets and slow and local food movements, and the emergence of Payments for Ecosystem Services and multifunctional agriculture within agricultural landscapes are also supporting this change . While closely related to the concepts of sustainable, multifunctional and organic agriculture, diversified farming systems have emerged as a separate agricultural model.

Diversified farming systems share much in common with sustainable, multifunctional, organic and local farming systems, but are unique because they emphasize incorporating functional biodiversity at multiple temporal and spatial scales to maintain ecosystem services critical to agricultural production. These ecosystem services include but are not limited to pollination services, water quality and availability, and soil conservation . Our aim is to provide an economists’ perspective on how a range of existing and emerging factors drive profitability of DFS at the farm level and how these relate to the adoption and emergence of diversified farming systems at larger scales. We begin with an overview of the factors that impact the profitability of agricultural systems, follow with a discussion of the economic factors that support and run counter to diversified farming systems, and conclude with our thoughts on how technological innovation and market trends must continue to evolve if DFS are to become economically sustainable and widespread.How profitable is it to farm? The answer depends upon the choices a farmer makes about what crops to grow and where, what technologies to use, and many other short- and long-term management decisions. Economists assume that farmers make choices so as to improve their utility, or well-being. In particular, farmers tend to pursue activities that increase their income, reduce their financial and physical risk, reduce labor requirements, and are convenient or enjoyable. A variety of constraints play into farmers’ decisions, including constraints with respect to available production technologies, biophysical or geophysical constraints, labor and input market constraints, financial and credit constraints, social norms, intertemporal trade offs, policy constraints, and constraints to knowledge or skills . The literature on technology adoption at the farm level tells us that many factors—in particular, variables that vary across farms and are sources of heterogeneity—influence farmers’ choices about what crops to grow, whether to use a new technology, and how to manage their land. Just as individual consumers have different preferences about products they consume, farmer characteristics, asset endowments, risk preferences, and intertemporal considerations affect their choices.

Farmer attitudes, resource availability, and education and knowledge are especially important; farmers may be risk-averse toward making changes in cropping decisions or adopting new agricultural practices, or might have very conservative attitudes toward technology or lower or higher levels of concern for the natural environment . A farmer’s income or resource base and ability to obtain credit will also influence his/her choice of crops, farming systems, and willingness to invest in new crops, systems, or technologies . A risk-averse farmer or one who is credit or income-constrained may be less likely to adopt new technologies, even if they are likely to reduce his susceptibility to risk or increase productivity or income over the long-run . Lack of knowledge and information about the costs and benefits of adopting new technologies or conservation practices or lack of knowledge about how to implement such technologies or practices will also affect a farmer’s propensity to adopt them . Even if farmers have full information and can implement new technologies efficiently and at low cost, differences in intertemporal preferences or credit constraints may mean that farmers are unwilling to sacrifice current profits or income for long-term improvements in soil fertility, risk-reductions, or improved yields . Biological and geophysical factors and input and output market conditions are important variables that also impact farmer decision-making and adoption of land use practices or technologies. Biological and geophysical factors that influence production can include water availability, soil fertility, and risks of floods, droughts, frost, or pest or weed infestations, and the importance of each of these factors varies with the types of crops planted. Input market conditions can shape farmer production decisions in a number of ways; dynamics of local and seasonal labor availability may mean that it is not profitable to grow a crop with a very narrow harvesting window in a month where the overall demand for agricultural labor is high in the region .

Input price volatility and economies of scale with respect to inputs or technologies can also contribute to farmers planting different mixes of crops, or planting more land in one crop than another.Similarly, output market conditions including prices, price variability, transportation costs, and supply chain transactions costs are important determinants of how profitable it is for farmers to grow a crop. Many of these variables are influenced by location; Rogers notes that communities closer to urban centers are likely to adopt new technologies more quickly. Consumer attitudes and willingness to pay for differentiated crops or particular attributes, such as organic or local production or pesticide-free varieties,vertical greenhouse also affect the agricultural systems that emerge in response to the demands of a changing market. Finally, policies and regulations can impact the profitability and evolution of different agricultural systems by facilitating or hindering trade in particular types of agricultural products, by influencing farmer decisions about what crops to grow or how much land to farm using policies such as price supports or set-aside programs, or by making different types of production or land use relatively more or less “expensive” via regulations, taxes and subsidies, or standards . In addition, many policies that do not specifically target agriculture, such as labor and immigration or water policies, have a significant effect on the costs of agricultural production. For example, laws such as those that regulate pesticide usage and application or limit water use can make it more costly to produce using synthetic pesticides or inefficient irrigation systems . While in the short-run such regulations may have a negative impact on farmer welfare, they also serve to stimulate innovation and adoption of new technologies in order to comply with regulations and reduce the costs of production . How can we describe trends in adoption and diffusion of agricultural technologies at landscape, regional, or global scales? Early studies on adoption noticed that the number of adopters, or the cropped area of using the new technology, were S-shaped as a function of time. They explained this pattern by imitation behavior among farmers; adoption is slow until enough farmers begin using the technology, and then rates of adoption speed up rapidly before they plateau.

The more profitable the new technology, the faster the rate of adoption and the higher the level of adoption after the diffusion process has played out . Farmers are heterogeneous, however, which impacts how and when they make decisions. In light of this heterogeneity, David and Feder et al. introduced the threshold model of adoption which characterized adoption within a community as a dynamic process whereby farmers make decisions according to explicit economic decision rules. Differences in when and how farmers adopt new technologies, then, arise due to heterogeneity among farmers and differences in other factors, such as their location and land quality. Larger farmers, for example, are often early adopters of mechanized technologies that exhibit increasing returns to scale. There is an interplay between farmer heterogeneity and the biological and geophysical factors that influence adoption that we mentioned earlier in this section; farmers in areas with soils with lower water-holding capacity will reap greater benefits from adopting irrigation technologies, and pest control strategies are adopted first in regions with high pest pressures. Over time, technologies and practices diffuse as producers gain knowledge and experience, or “learning by doing,” and as more and more farmers begin to use the technology, or “learning by using.” More and more farmers will adopt a technology as the fixed costs of adoption decline with time, and for some technologies, the gains from adoption increase with time as the network of producers using the technology increases in size . These basic principles that guide producer adoption choices provide a background for analyzing the factors that will affect whether farmers adopt diversified farming systems. Within the context of farmer decision making, there are a number of ways that diversified farming systems can help farmers maximize their utility, including through their roles in mitigating different types of risks, providing complementary inputs and optimizing production in the face of different biophysical or input and output market constraints, and through providing income or non-pecuniary benefits from ecosystem services or other benefits of using DFS practices. In this section, we focus on how these factors might make diversification an economically optimal choice for the farmer. Farmers are typically risk-averse . They face many different types of risk including price risk , yield risk , input supply risk and other types of risks . Many of these types of risk contribute directly to profit risk, which is ultimately most important to the producer. Farmers and their families can respond to risks in many ways, and can respond ex ante in precautionary ways, or ex post to try and minimize their losses. Strategies for coping with risk include finding off-farm employment , saving or using credit markets, informal borrowing , adopting risk-reducing technologies such as seed varieties with properties such as drought or herbicide resistance that emerged during the green revolution , engaging in contracts such as those that ensure that the farmer will have a buyer for his product at the end of the season at a set price , and diversification of production.

We use digital agriculture for its semantic breadth and increasing currency

The ‘urbanization of hinterland’ requires the ability to observe, interpret, and manage processes of extended urbanization from zones of concentration. We then “bring information back in” by introducing a more materialist analysis of the role of information in global capitalist space, which centers on computation capital: the infrastructure necessary to transport and make legible enormous amounts of data. In this framework, digital agriculture can be reinterpreted as a “data fx” for multiple entangled crisis tendencies of urbanization. These include the well-documented ecological crisis caused by industrialized agriculture—necessary to keep food prices, and therefore wages, low enough to generate profits in the traditionally ‘urban’ secondary and tertiary sectors—as well as a potential crisis of the over-accumulation of computational capital. This crisis response, in turn, reconfigures the concentrated–extended dialectic of urbanization. The digitalization of agriculture further consolidates agrarian knowledge and decision-making away from the felds and among agribusiness and, newly, technology actors. We note how this of-siting transforms agrarian land tenure and deskills agricultural workers. This connects directly to the concept of ‘depeasantization’ , what is vertical farming which can be understood as the mirror of urban agglomeration. We conclude with some suggestions for future research on digital agriculture’s effects on the urban/rural divide. The intensive use of information technologies in agriculture has received limited attention from social scientists.

As recently as 2016, Bronson and Knezevic, in taking a critical look at how such tools affect the power dynamics between farmers and corporations, noted that “there has been no attention given to Big Data’s implications in the realm of food and agriculture” . In the years since, a steady trickle of publications has begun addressing this gap: on a “data grab” ; on the unequal ability between farmers and firms to use data ; on digital agriculture’s transformation of farmers into consumers ; on the racialized exploitation of labor ; on the embedded norms of digital agriculture ; and on alternatives . 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.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, 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 feld 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.3 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 capita 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 capita, 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 capita 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. Digital agriculture’s strategy of overcoming hunger by increasing yield thereby may even exacerbate it. In reffecting on these mainstream claims, a different theme emerges. Rather than sustainability, nourishment,vertical farming supplies 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” . Afer briefy 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 foating 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, 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, Micros of, Google, Oracle, and Cisco—as well as funds invested in and consultancies hired by them—into digital agriculture.