Hemp Growing

The effect of zero tillage is dependent on climate, especially on rainfall, and the effect is more pronounced in drier areas . The energy requirements of zero tillage and reduced tillage are less, so GHG emissions are lower . GHG emissions were reduced by 1.5 Mg CO2-e ha 1 year 1 in zero tillage-based wheat and maize systems .Crop residue return has positive impacts on SOC, however, its effectiveness varies with tillage practices . Retaining residues on the soil surface increases the soil C sequestration , whereas residue incorporation with inversion tillage may lead to higher N2O and CH4 emissions . Amount of residue return is positively related to the C sequestration . Residue return with optimum fertilizer input, paddy-upland rotation, improved crop cultivars, and use of legumes in rotation are some of the improved management practices for enhancing amounts of crop residue return to the soil . Crop retention can reduce the requirement of fertilizer and therefore, may limit the GHG emission. The application of bio-char to soil has the potential to offset 12% of global GHG emissions, as it can stabilize decaying organic matter and associated CO2 release, and can remain in soil for hundreds or even thousands of years . The retention over longer period is due to reduction in mineralization rate by 10–100 times from that of crop biomass . A meta-analysis reported that bio-char can either increase or decrease soil C depending on the types of bio-char/soil and duration . In addition to its effect on SOC, bio-char application may decrease soil N2O emissions to an extent of 9–12% or even 50% .Improved water management enhances C sequestration by increasing NPP and the subsequent addition of biomass to soil . It is estimated that improved water management could mitigate 1.14 t CO2-e ha 1 year 1 of GHG emissions .

In dryland agricultural system, drying weed crop productivity and the above- and below-ground inputs of C to the soil can be improved through efficient water management practices which enhances the plant-available water . However, drip irrigation with frequent wetting-drying cycles may promote soil CO2 emission through greater microbial activities . Micro-irrigation/fertigation also reduces N losses and hence lower GWP . In rice cultivation, soil flooding is known to emit a large amount of CH4 , which can significantly be reduced from improved water management such as alternate wetting and drying , also called intermittent flooding . However, the intermittent flooding may result in higher N2O emission , which necessitates water management to be in synchrony with inorganic fertilizer and organic matter inputs. Reduced water application reduces the C footprint of pumping water .The application of N fertilizer from the right source, at the right dose, right time, and in the right place enhances crop yield, N use efficiency, and SOC storage, and mitigates GHG emissions . Optimum and balanced doses of nutrients maximize crop yields, resulting in relatively more C inputs from both above- and below-ground plant biomass to the soil. Nitrogen can be applied effectively by correlating the leaf greenness with the leaf N content, and this can be done with a chlorophyll meter, leaf color chart, or optical sensors . Decision support systems like Nutrient Expert and Crop Manager are becoming popular for efficient nutrient management . ‘Nutrient Expert’-based management reduced on average 13% of GHG emissions from rice, wheat, and maize compared with farmers’ fertilizer practices. Studies conducted by Gaihre et al. reported that in Bangladesh, the deep placement of urea in a rice-rice cropping system reduced N loss as N2O and improved the crop yield. Thus, deep placement of urea can mitigate global warming and improve SOC by producing more biomass than traditionally applied urea. Enhanced fertility management can improve SOC content at the rate of 0.05–0.15 Mg ha 1 year 1 . In a meta-analysis conducted by Ladha et al. , it was reported that N fertilization promotes SOC storage in agricultural soils throughout the world. Benbi and Brar reported that the application of balanced fertilization positively impacted the soil C sequestration due to its effects on crop growth.

Balanced fertilization improved SOC concentration in rice-wheat and maize-wheat cropping systems because of the greater C input associated with enhanced primary production and crop residues returned to the soil . To improve soil health and soil productivity through balanced fertilization, the Government of India has started a “Soil Health Management ” program under the National Mission for Sustainable Agriculture . In India, the Soil Health Card has been useful in assessing the status of soil health, and when used over time. The SHM program aims to promote Integrated Nutrient Management through the judicious use of chemical fertilizers including secondary- and micro-nutrients in conjunction with organic manures and bio-fertilizers. The SHC-based recommendations have shown an 8–10% reduction of chemical fertilizer use with a 5–6% increase in crop yields .In India, the availability of manure as a source of nutrients and C in agricultural practice reduced from 70% of the total manure produced in the early 1970s to 30% in the early 1990s . Three hundred and thirty-five Mt of dung is produced per annum in India, out of which 225 Mt is available for agricultural use . This is only one third of the FYM requirement of the country that is needed to achieve the full C sequestration potential . Use of organic manure such as compost can enhance soil C stocks but may also result in higher CO2 emissions . Application of organic manure can improve SOM by supplying enzyme-producing microorganisms with C and N substrates , thus enhancing the structure and diversity of the microbial community . However, application of inorganic nutrients with FYM sequestered C at the rate of 0.33 Mg of C ha 1 yr 1 compared to 0.16 Mg of C ha 1 yr 1 in NPK application alone . Even in a hot, semi-arid climate, balanced and integrated nutrient management along with FYM could increase SOC in soil . Regmi et al. , in a long-term study, reported the accumulation of soil C in a triple-cereal cropping system with organic amendment. In a rice-wheat cropping system, compared to NPK, the use of organic material increased SOC ranging from 18 to 62% . Likewise, Duxbury reported SOC accumulation from 0.08 to 0.98 Mg C ha 1 yr 1 in rice-wheat cropping systems through addition of FYM in India and Nepal. Several researchers have reported higher GHG fluxes in different types of soil when manures were added .

In a soybean-wheat cropping systems with an organic amendment, Lenka et al. reported increases in SOC stocks and N2O and CO2 emissions but the annual GWP was lower.Deep-rooted crops and crop varieties can sequester more CO2 in lower soil profiles . Growing deep-rooted crops also reduces nitrate leaching to the groundwater and thereby reduces N2O emission , curing weed improves SOC stocks, and extracts nutrients and moisture from deeper soil layers . Deep-rooted perennial crops could also significantly decrease the requirement for tillage . Plants with improved root architecture can improve soil structure , hydrology , drought tolerance , and N use efficiency . Van de Broek et al. compared the amount of assimilated C that was transferred below ground and potentially stabilized in the soil from old and new wheat varieties. The authors reported that old wheat cultivars with higher root biomass transferred more assimilated C down the soil profile over more recent cultivars. Recently, Dijkstra et al. proposed a new ‘Rhizo-Engine framework’ emphasizing a holistic approach for studying plant root effects on SOC sequestration and the sensitivity of SOC stocks to climate and land-use changes. Mycorrhizal association is another important trait that could play a crucial role in moving C into soil through active participation with plants. It is reported that plants with mycorrhizal associations can transfer up to 15% more C to soil than their non-mycorrhizal counterparts . The most common mycorrhizal fungi are marked by thread-like filaments, hyphae that extend the reach of a plant, increasing its access to nutrients and water. These hyphae are coated with a sticky substance called glomalin which are known to improve soil structure and C storage. Glomalin helps the organic matter bind with silt, sand, and clay particles, and it contains 30–40% C and helps in forming soil aggregates . Averill et al. using global data sets, observed 70% more C per unit N in soil dominated by ectomycorrhizal and ericoid mycorrhizal-associated plants than arbuscular mycorrhizal-associated plants. Another recent synthesis by Verbruggen et al. opined that the mycorrhizal fungi can increase C sequestration through “enhanced weathering” of silicate rocks through intense interactions.The excessive use of pesticides in crop production has amplified to fight against insect pests and diseases. While the use of pesticides captures more C from improved crop production, it also increases GHG emissions from the processes involved in the use of synthetic pesticides . Integrated pest management can reduce pesticide use and increase crop yields. A study conducted in 24 countries of Asia and Africa has shown that the use of IPM to control pests can increase crop yields by more than 40%, and can reduce pesticide use by 31% . Research has shown that any pest management practices that lessen foliar spraying are able to reduce GHG emissions . CSPM is proposed by the FAO , and its aim are to reduce crop losses due to pests, improve ecosystem services, reduce GHG emissions, and make the agricultural system more resilient .A cover crop used to cover the ground surface during the fallow period prevents nutrients leaching from the soil profile, and provides nutrients to the main crops . Poeplau and Don reported a reduction in SOC loss by cover cropping. A significant area in South Asia, where cultivation of a single crop is the practice, provides an opportunity for cover cropping. Likewise, in intensive double-cropping areas, a short-duration cover crop such as sesbania can be grown to improve soil fertility including soil C . In a meta-analysis, Poeplau and Don estimated that using cover crops in 25% of the world’s farmland could offset 8% of GHG emissions from agriculture. Cover cropping has also been reported to reduce N2O emissions . Aryal et al. reported that cover crops and fallow rotation in warm and moist climates can reduce a net loss of 0.98 Mg C ha 1 in 7-year period. Creating borders of permanent vegetation along the edges of the field is another way to provide continuing live cover for agricultural soils . The possible effect of no-till in increasing SOC is more prominent when cover cropping is included in the system . Cheng et al. and Dignac et al. reported improvement in SOC stocks through rhizodeposition and root litter addition, which is greater with perennial crops than with annuals. In a policy analysis report on soil health and C sequestration in US croplands, Biardeau et al. reported that agroforestry, in which crop cultivation is intermixed with growing trees and sometimes with grazing livestock, has the highest potential to hold C, ranging from 4.3 to 6.3 MT CO2-e per ha annually.Inclusion of a dual- or multi-purpose legume in a rotation is likely to balance the organic and inorganic fertilizer inputs and its effect on SOC stocks . In South Asia, several researchers have shown similar benefits at the system level of optimizing crop rotations in CA mode in rice-wheat and rice-rice rotations . Legumes with the ability to fix atmospheric N benefit subsequent crops by increasing biomass production, crop residue inputs, and subsequently the total SOC in legume-cereal crop rotations . Reducing overgrazing ; balancing SOM decomposition through manures, crop residues and litter; and enhancing the mean annual NPP, are known to improve SOC in agricultural soils . Greater SOC stocks and more stabilized SOC can be obtained by increasing soil biodiversity . Havlin et al. reported that instead of continuous soybean cultivation, the inclusion of grain sorghum in a rotation increased soil organic C and N and that growing high residue crops along with reduced tillage could increase productivity. Ladha et al. reported that in different parts of the Indo-Gangetic Plains, the implementation of CA along with intensive crop diversification resulted in a 54% increase in grain energy yield, with 104% more economic returns, a 35% reduction in total water input, and a 43% lower global warming potential intensity compared to farmers’ conventional management practices. Improved agronomic practices can lead to SOC changes which are often higher than the proposed 0.4% .

The eddy covariance method provides valuable information to better understand temporal variability and estimates an annual CH4 emission average that can be compared to inventories. Only a select number of studies have conducted in situ field measurements of CH4 from California dairy manure lagoons. The magnitude and temporal patterns of CH4 emissions from manure lagoons often vary depending on the method used to estimate emissions. There is also an important role of seasonality of CH4 emissions that might confound comparison of atmosphere-based estimates with inventory. For example, Arndt et al. showed that summer CH4 emissions were comparable to inventory estimates, but not during winter measurements. In addition, emissions from manure liquid storage were 3 to 6 times higher during the summer measurements than during the winter measurements using three different techniques . In a recent study, statewide emission factors were comparable to ground-level measurements during the summer and fall seasons, but airborne measurements were 8% higher than the statewide inventories . Methane emissions from dairy manure lagoons may also differ by as much as a factor of two using different dispersion models . Other important gaseous emissions are also co-emitted with CH4 at dairy farms, but have different spatial patterns because they are coming from different sources . Additional observations at the seasonal and diel scales are needed to address uncertainties in CH4 emissions from dairy manure lagoons in California. In this study, we investigate seasonal and diurnal CH4 fluxes from manure lagoons at a dairy farm in Southern California using the eddy covariance technique. We pair our CH4 fluxes with micrometeorological measurements, air racking including wind speed, surface pond temperature, air temperature, among other parameters.

We then discuss the impact of lagoon agitation events, such as precipitation and manure management practices, on CH4 fluxes. Finally, we compare our CH4 flux estimates using the eddy covariance technique with other methods deployed at the same location. We hypothesized that manure lagoon CH4 emissions would follow seasonal patterns, with higher fluxes in spring and summer when manure substrate availability and temperature are higher. We also surmised that higher wind speeds would increase CH4 fluxes through increased turbulence and mixing of the lagoon surface. Finally, we hypothesized that manure management practices would have a measurable impact on measured CH4 emissions.Our study site is a manure storage lagoon on a typical dairy in southern California, located near 33.8º, -117.0º . The site has a semi-arid climate, with a mean annual temperature of 19⁰C and mean annual precipitation of 0.5 ± 2.6 mm that mostly falls between November and March. It is an open dry lot dairy—meaning that milk cows are housed in open corrals with dirt surfaces, and manure deposited in feed lanes is primarily scraped off the lot rather than flushed with water. The manure that is scraped from the corrals is stored as dry manure piles south of the dry lot. Water is used to flush out manure deposited in the milking parlor into manure ponds via the subsurface and above ground channels . Corral runoff flows to the channels via drainage pits,with four weeping walls present to retain solids. Approximately 227,100 L of storm water runoff from corrals and feed lanes , milk parlor wash down water, and wash pen water enters the manure pond system daily. Manure ponds receive about 38,000 L of fresh dairy flush manure daily. From December 2016 to June 2018, 56,775 L per day of green waste digestate was also introduced to the manure lagoons for testing their Ag Waste Solutions system that converts cow manure into bio-fuel, primarily diesel fuel, and bio-char . Occasionally, solids are removed from the above ground channels and stored as dry manure storage piles . The dairy farm’s population consist exclusively of Holstein cows. Demographics are relatively stable between seasons since it is a closed herd—births are on site and cows only leave once they retire or pass away.

There are approximately 1066 milking cows, 200 dry cows, 685 heifers, and 370 calves. The dairy manure flush system only receives input from the milking cows and calves. The total annual manure produced from dry corral production is 6300 tons.The manure pond system consists of five manure ponds , wherein the liquid manure navigates from manure pond 1 to manure pond 5 via gravity, decreasing the content of suspended volatile solids through anaerobic decomposition and settling as it navigates from one manure pond to the next. Throughout the study period , the surface of manure pond 1 underwent a drastic change in vegetation and surface variation . To quantify the percentage change in crust/vegetation,we calculated the change in vegetation/crust area using Google Earth satellite imagery between 2019 and 2021. There was a 147% increase in area covered by the crust layer and vegetation on manure pond 1 from June 2019 to June 2021. Peak vegetation growth occurred during the summer months , followed by a dry period. We define the pre-sedimentation stage occurring from June 2019 to May 2020 and the postsedimentation stage occurring from June 2020 and June 2021 when a substantial crust and sediment layer formed on the surface of manure pond 1. A common practice is to dredge dairy manure ponds periodically. However, the Southern California dairy farm has not dredged their manure ponds since it was constructed in 2006, thus solids also accumulated throughout this study period. The solids in the channel leading to the manure pond system were dredged in March 2020 following rain events and December 1, 2020 . Typically, the channels are dredged twice a year.We installed an eddy covariance flux tower at a height of 4 m on the southeastern edge of Lagoon 1 . The eddy covariance flux tower consisted of an open-path CH4 analyzer , integrated CO2 and H2O Open-Path Gas Analyzer and 3-D Sonic Anemometer . The analyzers measured at a rate of 10 Hz. They were calibrated before and after the field measurements using zero air and custom gas mixtures that were tied to the scale set by the NOAA Global Monitoring Division by measurement against NOAA certified tanks. We also measured air temperature and relative humidity , the surface temperature of the pond with an infrared radiometer , and precipitation with a rain gauge.

The data were recorded using a CR3000 datalogger. Instruments were powered using three solar panels, seven deepcycle. Dust was removed using an automatic cleaning system.The footprint of an eddy covariance flux measurements represents the upwind area that contributes to the fluxes at the location of measurements. The extent of the footprint depends on the micrometeorological conditions such as stability of the boundary layer and wind speed. A flux footprint model by Kljun et al. was used to estimate the footprint of the eddy covariance flux measurements. The algorithm uses the following inputs to calculate the footprint: mean wind speed, wind direction, weed dryer standard deviation of the horizontal wind speed, friction velocity, planetary boundary layer height, and Obukhov length. Figure 4.3 shows the upwind area that contributes to the flux observations with friction velocity greater than 0.1 m s-1 , wind direction between 270⁰ and 340⁰, and wind speed greater than 0.2 m s-1 . The distance of footprint contributions were calculated for each half-hour flux using the EddyPro software. The extent of the footprint captures manure pond 1, manure pond 2, and a portion of manure pond 3. As shown in Figure 4.3, 70% of the footprint primarily covers less than 50% of the area of manure pond 1.On August 28, 2019, we sampled the manure lagoon complex for various biophysical parameters using a boat at three different locations and depths. We sampled at three locations shown in Figure 4.4 and Figure 4.10. L1 and L2 were sampled at 0 and 0.3 m and L3 was sampled at surface level, 0.3, and 0.8 m. L1 and L2 were only sampled at the surface level and 0.3 depth since the high volatile content limited the instrumentation’s reach. We measured pH and temperature with an Oakton PCTS 50, PCSTestr 35 or pHTestr 30. Oxidation-reduction potential was measured with anOakton ORP Testr 10 that was calibrated with Zobell’s solution from VWR Scientific in the lab 24 hours prior to field work. Electrical conductivity was measured on each liquid sample in the laboratory using an Oakton Con 100 series meter and conductivity probe. The probe was calibrated according to manufacturer’s recommendations with 1413 uS standard solution from Fisher Scientific. Samples were removed from the 4 °C cold room and each was inverted gently 2-3 times to mix contents just prior to measurement. The probe was calibrated after every 10-15 readings to reduce drift. Total solids concentration , which is the solid concentration of biomass, was determined by weighing and drying 15-25 ml aliquots of each sample in triplicate in a 120 °C oven for 4- 16 hours, weighing the residual, then dividing by the wet weight. Aliquots were made using the shake and pour method . Fixed solids concentration , which is the inorganic fraction of total solids, was determined by further combustion of the dried samples in a muffle oven at 540 °C for 4 hours, weighing the residual, then dividing by the dry weight . Volatile solids concentration , which is the organic fraction of total solids, is the difference between TS and FS divided by wet weight. On August 14, 2018, stationary measurements of CH4 mole fractions downwind of manure pond 1 were collected with a cavity-ring down spectrometer . Dispersion models were then used to estimate CH4 emissions and showed that CH4 emissions were heterogenous, with higher CH4 emissionsnear the manure stream inlet . In a pilot study on August 27, 2019, CH4 emissions were estimated using an auto-ventilated floating chamber connected to a CRDS .

Figure 4.5 shows the timeline of measurements conducted at manure pond 1.During the study period, observed air temperatures were on average 19 ⁰C, with the highest temperatures measured during the summer . Sensible heat flux was on average 41 W m-2 . Mean surface pond temperatures were comparable to mean air temperatures with 20 ⁰C. Friction velocity was on average 0.2 ± 0.1 ms-1 . Lastly, incoming shortwave radiation near the manure ponds was 75±71 Wm-2 , on average . In our study site, precipitation events were highest during the winter and spring seasons. The highest precipitation events occurred during March and April in the year 2020. Daily CH4 fluxes were also highest during this time . Surface and pond temperatures were on average highest during the summer months of August and September. Similarly, incoming shortwave radiation was strongest during the summer months of August and September in the year 2020. There were no overall seasonal patterns observed for friction velocity and wind speed.At the diurnal scale, the micrometeorological factors that had the strongest correlations with CH4 fluxes were air and surface pond temperature, wind speed, and friction velocity based on linear regression models. The micrometeorological factors that had the strongest effects differed between the pre-sedimentation stage and post-sedimentation stage . There was a strong diurnal relationship between CH4 fluxes and surface pond temperature fluxes, especially during the pre-sedimentation stage of manure pond 1 . However, the diurnal connection between CH4 fluxes and pond temperature weakens postsedimentation . Methane fluxes and latent heat fluxes follow a similar diurnal pattern , with peaks during the early afternoon, when pond and air temperatures were also the highest . Wind speed also had a significant effect on diurnal CH4 fluxes during both pre-sedimentation and post-sedimentation conditions. Friction velocity had a stronger influence on CH4 fluxes during the post-sedimentation phase than during the pre-sedimentation phase of manure pond 1. During our study period, CH4 fluxes from manure pond 1 decreased from 2019 to 2021, with the highest CH4 fluxes observed during the spring period in 2020 . Spring CH4 fluxes decreased on average by 70% from 2020 to 2021 and summer CH4 fluxes decreased on average by 57% from 2019 to 2021. Monthly CO2 fluxes increased during the spring season and then decreased during the summer months, when there was vegetation growth in manure pond 1, driving photosynthesis and carbon uptake. Methane fluxes and CO2 fluxes followed a similar seasonal pattern . In contrast to diurnal CH4 fluxes, seasonal CH4 fluxes were not significantly correlated with seasonal latent heat flux . Monthly latent heat fluxes increased during the summer, whereas monthly CH4 fluxes decreased during the summer.

The other by-products, acetate and butyrate, help induce methanogenesis. Manure management systems vary among dairy farms but generally consist of dry and wet management practices . Dry manure management consists of deep pits, solid manure storage, dry lots, and daily spread . In a wet manure management system, manure waste from animal housing areas are washed and typically collected in manure lagoons, where anaerobic conditions produce CH4 . Dry manure handling practices reduce anaerobic conditions since they do not flush waste with water. So far, however, there are only two studies on seasonal CH4 emissions from anaerobic lagoons in California, but none have studied emissions from all four seasons . Measuring and modeling emissions from dairy manure management are challenging given the variability of practices . It is only recently that mobile measurement campaigns measured CH4 emissions from a small number of dairies with anaerobic lagoons . Given that field data is still variable, the majority of N2O emissions is estimated to originate from barns, unlike dairy CH4 emissions, which are mostly expected from anaerobic lagoons and slurry systems . The next largest emitter of N2O from dairy manure management is estimated to come from corrals and solid manure piles . Corrals include loafing pens, hard standings, and dry lots. Studies have also measured N2O emissions from anaerobic lagoons and slurry stores, which was unexpected since anaerobic conditions are dominant in wet manure storage . In anaerobic wet manure, nitrogen is mostly found in the form of ammonium and organic nitrogen, cannabis curing but denitrification is possible at inlets from wet manure storage systems if aerobic conditions are present . Nitrous oxide can also form through the denitrification of nitrate generated by Feammox, Mnammox, or anammox in the cases where NO3 – is present .

Nitrification can also occur under aerobic conditions, where N2O is emitted as a by-produced when NH4 + is first oxidized to nitrite and then converted to NO3 – . Ammonia is formed and volatilized from dairy manure almost immediately after urine and feces are excreted. Ammonia travels to the manure surface via diffusion and is released to the atmosphere via convective mass transfer . In general, NH3 volatilization increases with higher concentrations of NH4 + /NH3, substrate temperature, wind speed and turbulence . Ammonia emissions are highest between a pH of 7 to 10 and decrease with lower pH and is impacted by the pKa of the reaction .Methane is the second most important anthropogenic greenhouse gas after carbon dioxide and is increasingly becoming a critical priority for near-term climate action, given its relatively short lifetime and substantial potential for rapid mitigation . Over the last several decades, the growth rate of atmospheric CH4 has significantly changed, reaching stable zero growth from 1999 to 2006, followed by an increase beginning 2007 . This rise in the global mole fraction of atmospheric CH4 has been the subject of several studies that focus on explaining this phenomenon, without a definitive explanation. A rise in CH4 emissions could be indicative of changes in total emissions from various sources, including from biogenic, thermogenic, and pyrogenic CH4 and/or changes in the atmospheric sink of CH4 . The isotopic signature of CH4 is an important tool to diagnose the source of this increase in CH4 . The global stable carbon isotope ratio of atmospheric CH4, expressed as δ 13CCH4, has shifted towards more negative values simultaneously with the rise of the atmospheric mole fraction of CH4 . Recent isotopic evidence suggests that this rise in CH4 is likely dominated by increased emissions of biogenic CH4, which are more depleted in 13C relative to fossil and pyrogenic CH4 sources. Based on this explanation, possible biogenic sources responsible for the rise in atmospheric CH4 include ruminants, rice paddies, and wetlands, among others. Previous work have shown that isotopic signatures of CH4 emitted by enteric fermentation depend on the carbon isotopic ratio of diet composition, driven by the proportion of plants with C3 and C4 photosynthetic pathways, with estimates δ 13CCH4 of about -60‰ for C3-fed ruminants and about -50‰ for C4-fed ruminants . Other conflicting hypotheses about the CH4 budget include an underestimate of fossil-derived sources in CH4 inventories based on an isotope mass balance . Further studies, however, show that an increase in fossil-derived CH4 emissions is inconsistent with the observed trend in atmospheric δ13CCH4 . Additionally, there are large uncertainties in the magnitude and trends of atmospheric sinks of CH4 . Given that our understanding of the CH4 budget remains incomplete, there is a clear need for sufficient in situ isotopic characterization of CH4 at the local level to identify the location and type of sources that dominate the current rise in global CH4 emissions . Even at local to regional scales, the budgets of both CH4 and its stable carbon isotope remain uncertain . Improved knowledge is particularly important for ensuring effective mitigation of CH4 at scales where policies to reduce CH4 are being enacted . In California, there are statewide efforts underway to reduce CH4 emissions, but it remains challenging to accurately monitor progress given the large inconsistencies between atmospheric observations and greenhouse gas inventories . Atmospheric observations have inferred higher CH4 emissions than reported in GHG inventories at the statewide and regional levels and from individual sectors, including dairies . However, there is little information about the processes that produce this apparent discrepancy.

The California Air Resources Board GHG inventory estimates that dairies contribute about half of statewide CH4 emissions, with contributions from enteric fermentation by ruminant gut microbes and manure managed in anaerobic conditions. However, these estimates are based on emission factors derived from a few pilot and lab-scale studies conducted outside of California and thus likely not representative of California’s climate and unique bio-geography . Given that mitigation practices are targeted towards the bio-geochemical and management processes that produce CH4, new tools for source apportionment and process understanding are required . Stable isotopes of CH4 may be a promising way forward. The few studies that have measured isotopic signatures of CH4 from dairies in California were done in the Los Angeles Basin. Townsend-Small et al. investigated the isotopic signature of major sources of CH4 in the Los Angeles megacity and found that isotopic values of δ13CCH4 from fields applied with cow manure were characterized by values between -62.1 per mil to -59.2‰, whereas δ13CCH4 of manure bio-fuel from a manure digester facility ranged from -52.4‰ to -50.3‰. Cow breath, on the other hand, had more depleted δ13CCH4 source signatures between -64.6‰ and -60.2‰. A more recent study by Viatte et al. measured isotopic signatures of δ13CCH4 from the largest dairy farms in Southern California, and observed values between -65‰ to -45‰, attributing the most depleted observations to enteric fermentation. In Europe, grow room previous research has shown that δ 13CCH4 signatures vary dependent on the type of dairy manure storage. In Heidelberg, Germany, Levin et al., observed more enriched δ13CCH4 from manure piles and a biogas generator than liquid manure . Two recent studies used mobile surveys to measure δ 13CCH4 in Europe. In Germany, Hoheisel et al. conducted mobile measurements to determine δ 13CCH4 signatures around Heidelberg and in North RhineWestphalia. The δ13CCH4 signatures ranged from -66.0‰ to -40.3‰ for three dairy farms with biogas plants. More enriched δ13CCH4 signatures were observed from plumes downwind of the biogas plant relative to plumes downwind of the animal housing. In Northern England, Lowry et al., found that methane plumes downwind of dairy farms had δ 13CCH4 signatures from -67‰ to -58‰. Atmospheric measurements downwind of manure piles were more enriched in 13CCH4 with values close to -50‰ relative to cow breath, which were close to -70‰.

Isotopic endmembers were variable downwind of animal housing dependent on the cattle population and amount of manure waste present. In general, CH4 from barns with fewer cows and more manure waste were more enrichedin 13C. In comparison, beef cattle feedlots have isotopic signatures within the range of expected enteric fermentation, with δ13CCH4 signatures of -66.7 ± 2.4‰ in Alberta, Canada to -56.2‰ ± 1.2‰ in the Colorado Front Range, USA . Beef cattle are generally pasture raised until they are sent to feedlots, where their diet is primarily maize with varying proportions of wheat . In this study, we present seasonal atmospheric measurements of δ 13CCH4 from dairy farms located in the San Joaquin Valley, California, where 91% of the state’s dairy herd resides . Our primary objective was to measure δ 13CCH4 emitted from anaerobic manure lagoons and enteric fermentation source areas across seasons. Our second objective was to use δ13CCH4 source signatures from enteric fermentation and anaerobic lagoons to identify the dominant source responsible for CH4 hotspots detected from downwind plume sampling of other dairies in the region. We hypothesized that the δ 13CCH4 signatures from dairy anaerobic manure lagoons and enteric fermentation can be used to apportion CH4 emissions between these two dairy farm source processes. These isotopic signatures can help contribute to the body of knowledge that aims to resolve the CH4 budget in California and globally.Ground-based mobile measurements were collected at a dairy in Tulare County , California, in the fall, spring, summer, and winter seasons from 2018 to 2020. Hereafter, we will refer to this dairy as the reference test site farm. Figure 2.1shows a schematic of the reference test site farm layout. The reference test site has on average 3070 milking cows that spend most of their time in free stall barns, with an additional ~400 dry cows and ~3000 heifers that are primarily in open lots . Wet manure management is used for waste deposited in the free stall barns, where manure waste is flushed from barn floors and diverted to a processing pit. Wastewater from the milking parlor also enters the processing pit. Processing pit water is reused to flush lanes or is pumped over stationary inclined screen . A manure separator then removes coarser solids from liquid effluent, which gravity flows into cell 1. The liquid manure navigates from separation cell 1, cell 2, the primary lagoon, and finally into a holding pond via gravity, decreasing the content of suspended volatile solids through anaerobic decomposition and settling as it moves from one component to the next. Water waste from the holding pond is later used as irrigation water for cropland. Hereafter, manure lagoons refer to cell 1, cell 2, primary lagoon, and the holding pond. Dry manure management refers to the fraction of waste that is separated from the liquid waste stream, which is spread out on the ground and solar dried. Once dry, this manure is distributed into free stall beds or stacked and covered in the dry bedding. The primary forages are wheat and maize preserved as silage. Silage piles are covered with a double layer of plastic. The feed composition for different seasons was obtained by weighing each feed ingredient as it was included into the mixer wagon. All weights were transferred electronically to feed management software . FeedWatch data were retrieved once monthly for ingredient identification, quantity fed per pen, pen population and dry matter composition. Each ingredient was identified as C3 or C4 except for distiller’s grain, which could be a changing combination of C3 and C4 sources. Sum of dry weights by pen for C3, C4, distillers feeds were calculated. The feed composition by cattle production group is presented in .We also made measurements at other dairies within a 10 x 10 km region of agricultural land in the same county, which includes additional dairy farms, beef feedlots, poultry farms, and a landfill that are also emitting CH4 . Other potential sources of emissions surround the region, including a wetland, plugged and abandoned oil and gas wells that are permanently sealed, and a wastewater treatment plant. Residential land is primarily located south of the region and contains an extensive natural gas pipeline network. Globally, the δ 13CCH4 signatures from fossil fuel sources are typically around – 44‰ , with δ 13CCH4 signatures between −50‰ to −36‰ from fugitive natural gas in urban settings . Urban studies also use ethane to CH4 ratios as a tracer to distinguish between sources in mixed source regions .

Significantly, such payments are not entirely mitigated by higher rental payments for land. That is, the potential for profit is still great, with only 25% going toward rent, and with only 64% of farmland itself rented. Finally, increasing corporate influence, which has further entrenched and profited off large scale, specialized, and commodity crop-oriented production—and ensured that it does so by way of federal commodity support programs—subsequently exacerbates such trends in wealth accrued by white farmland owners. That is, corporate influence, which has pushed for increasingly specialized and large-scale commodity crop production on prime farmland, has facilitated and secured further accumulation of wealth by whites, particularly by way of plentiful government payments. Thus, despite the widely experienced loss of farmland by way of consolidation and specialization, such trends ultimately undergird white land ownership and wealth in the United States, and exacerbate the marginality that people of color face in accumulating wealth in relation to white people.The third major channel within the Farm Bill and other federal food and agricultural policies that has played a historic and ongoing role in structural racialization is the Farm Bill’s Rural Development programs, which are intended to help strengthen small communities by investing in water systems, housing, new businesses, infrastructure, and similar projects. Because many farms owned by people of color are in counties with little wealth and limited opportunities for non-farm employment, and because many rural and small town communities of color are faced with persistent poverty, Rural Development programs have the potential to promote socio-economic well-being for people of color and other historically marginalized communities. As of 2012, there is a larger percentage of whites in rural communities than in urban communities . Yet, cannabis drying rack ideas within rural communities, people of color face higher rates of poverty: while only 14% of rural whites live in poverty, 34% of rural Blacks live in poverty. Additionally, as of 2010, Latinos/as, Blacks, and Pacific Islanders have the lowest homeownership rates compared to homeownership rates for whites.  Thus, it is unsurprising that, according to a 2013 Tuskegee University study, farmers and rural communities of color have had particularly high participation rate in three major Rural Development programs: Rural Housing and Community Facilities; Rural Business; and Rural Utilities. 

Even though the Farm Bill’s Rural Development programs hold great potential for farmers of color and rural communities of color, barriers to participation reflect those that characterize other Farm Bill programs, marking how such support programs actually contribute to structural racialization. The Tuskegee University study, for example, found that regarding the delivery of such programs, farmers of color experience five major barriers: lack of program knowledge, impersonal workplace environment, “facially neutral eligibility requirements” that do not address the historic and systemic exclusion, remote locations, and sub-par outreach efforts. The Value Added Producer Grant program, for example, is a major Rural Development program that supports innovative marketing and product development strategies for the added processing of agricultural goods that can generate additional income. The VAPG program could be of great benefit to producers of color who grow a variety of nongrain and oilseed crops with value-added potential.Yet despite the Farm Bill itself requiring the USDA to prioritize projects by socio-economically disadvantaged farmers, a short application period and complex application form, and a requirement that recipients provide 1:1 matching funds, puts the VAPG program out of reach for some farmers of color. Finally, insufficient funding has long marked the Farm Bill’s rural development title and programs. Although, overall program spending within the 2014 Farm Bill averages $95.6 billion per year for the next ten years, the rural development title will receive less than 0.024% of that, only $22.8 million per year. The Value Added Producer Grant program, in particular, although originally authorized in 2000 to receive $20 million per year in funding, has been cut to $12.5 million annually under the 2014 Farm Bill. Collectively, such barriers limit the potential benefit of the Farm Bill’s Rural Development programs with regard to the dire situation many farmers of color and rural communities of color face.

Ultimately, they highlight the central contradiction that farmers of color face with regard to such commodity support programs and other support programs for farmers and rural communities: inclusion in the benefits of such programs does little to destabilize the historic and structural outcomes that they have reinforced, to undergird the wealth of whites in the United States, and to ensure that it is white communities that fare best regardless of what happens to the structure of US agriculture.PART III OUTLINED HOW LENDING,commodity, and rural development programs have historically undergirded white farmland ownership at the expense of people of color farmland ownership, and how long term changes in the structure of US farmland—the consolidation and specialization of agricultural production, in particular—have exacerbated such trends. Part IV continues this line of argumentation regarding the structure of US farmland and examines how programs geared toward supporting supposedly environmentally sustainable management practices also shape the socio-economic well-being of and farming and rural communities of color relative to white farming and rural communities. First, this part does so by providing a snapshot of the racialized distribution of costs and benefits regarding programs under the conservation title of the Farm Bill . It then outlines the significance of the historical continuity between environmentally-oriented programs and commodity support programs. Finally, it outlines the significance of four federal rural and agricultural support programs in particular—the Conservation Reserve Program , Environmental Quality Incentives Program , organic agriculture programs, and outreach and assistance programs—as well as recent corporate-backed trends in increased bio-fuel production. Part IV argues that, because of their inseparability from commodity crop production, and the consolidation and specialization of agricultural production, and despite the countless environmental benefits they produce, Farm Bill programs under the conservation title also undergird white farmland ownership at the expense of farmland ownership by people of color. Ultimately, they do so by funneling benefits primarily to white large-scale landowners on high quality land and keeping even low quality white-owned farmland profitable—an inadvertent result of the history of farmland ownership in the United States that cannot be seen as separate from the history of racial discrimination. This part argues, furthermore, that this is the case not only with commodity crop and acreage-based conservation programs , but that management practice-based conservation programs have similar effects. Furthermore, a fourth program, commercial weed the Outreach and Assistance for Socially Disadvantaged Farmers and Ranchers and Veteran Farmers and Ranchers Program, contributes to the social and economic inequities that characterize commodity and conservation programs alike, yet holds great potential as a strategic rallying point against structural racialization.

Finally, Part IV then addresses the relationship between structural racialization, industrial agriculture, environmental degradation, and climate change, and argues that farmers of color and communities of color bear the brunt of such environmental change.Conservation programs within the Farm Bill not only emerged from and remain tied to commodity crop production, but also maintained white communities as the primary benefactors of such modes of production in terms of both wealth accumulation and land ownership. The Farm Bill began by joining the re-establishment and maintenance of farm income at fair levels with the promotion of soil conservation and profitable use of agricultural resources. The first Farm Bill, the 1933 Agricultural Adjustment Act, for example, aimed to restore the purchasing power of agricultural commodities by encouraging voluntary acreage reduction of such crops through agreements with producers as well as the use of direct payments for participation in acreage control programs. Five years later, the 1938 Farm Bill was significant for a number of reasons: it secured these acreage restrictions; included new provisions where the federal government—and not corporations—would pay farmers who planted “soil-conserving” crops instead of “soil-depleting” crops ; and it established a series of credit programs that provided farm storage facility loans, purchases, and income support payments. By the mid-20th century, conservation programs were not only tied to, but also upheld, commodity crop production. Years of acreage reductions offset by increased farm productivity after World War II led to the 1956 Farm Bill’s Soil Bank program, a key conservation measure that set aside 4.9 million acres of select commodity crops. The land that the Soil Bank program was applied to, however, was already low-productivity land. In this light, with white landowners holding the vast majority of grain and oilseed farmland, the Farm Bill’s premier conservation program upheld white land ownership by keeping even the least productive grain and oilseed farmland profitable. Later programs, such as the Feed Grains Act of 1961, continued such trends, with farmers often diverting the least productive acres and realizing higher yields on those planted acres.  By the 1970s and 1980s, acreage reduction programs were all but abandoned as farmers began planting “fencerow to fencerow” to meet growing domestic demand for grain, precipitating massive environmental degradation and low prices that bolstered corporate profit. These changes ultimately prompted a new approach to conservation over the next two decades: starting with the introduction of the conservation title and programs in the 1985 Farm Bill; the addition of the Wetland Reserve Program and the Agricultural Water Quality Program in the 1990 Farm Bill; and the eventual separation of commodity programs from conservation programs in 1996 Farm Bill. These programs, as outlined below, however, maintain the structural benefits historically afforded to whites while keeping people of color at a structural disadvantage.One major Farm Bill conservation program that has undergirded white farmland ownership at the expense of farmland ownership by people of color is the Conservation Reserve Program . The CRP is the largest federal, private-land retirement program in the United States, with 27.5 million acres covered at a cost of $20 billion over the next 10 years. It provides financial compensation for landowners to voluntarily remove land from agricultural production for 10 to 15 years in order to improve soil and water quality and create wildlife habitat. Acres enrolled in CRP have indeed shown a number of environmental gains, including reduced soil erosion, water quality improvements, and wildlife population improvement. However, a number of factors shape the purpose the CRP serves and for whom: first, enrollment is considered to be undesirable by some land owners, primarily because of the cost of compliance and the potential loss of farm income due to the prevention of the use of such land for agricultural production. Thus, as with the 1956 Soil Bank Program from which the CRP grew, it is the least productive land and lowest income households that are often enrolled and kept profitable. Second, studies have shown that conservation compliance does not present a strong economic deterrent for landowners who want to crop former CRP acreage after the CRP term is over, thus highlighting the potentially temporary nature of such economic relief. Third, and perhaps most importantly, only lands planted with commodity crops, especially, corn and wheat are eligible for CRP and not fruits or vegetables, or lands used for livestock. Because white farmers have historically owned large-scale grain and oilseed farmland while farmers of color have been relegated to smaller, non-commodity crop farmland, the Conservation Reserve Program potentially undergirds white farmland ownership, both during times of economic hardship and on marginal land. A 2005 Texas A&M University survey study, for example, found that white landowners were more likely to have land qualified for reserve programs—as well as programs such as the Stewardship Incentives Program and the Forestry Incentives Program . Such landowners not only received more favorable program outreach and assistance, as will be addressed below, they also had more incentives to participate due to the economies of scale and tax savings. Toward this end, the study found that white landowners, on average, were enrolled in the CRP longer and signed up more acres than landowners of color .Another Farm Bill conservation program that secures white farmland ownership more so than farmland ownership by people of color is the Environmental Quality Incentives Program . EQIP underwrites part of the cost when farmers and ranchers implement environmentally sound practices tied not only to wildlife habitat but also to nutrient runoff, pest control, water irrigation, and livestock grazing. Eligible land includes cropland, rangeland, pasture, non-industrial private forest land, and other farm or ranch lands, with 60% of total EQIP funding set aside for livestock operations at the national level.

In 1985, Ex Parte Hibberd, an administration decision by the US Patent and Trademarks Office, extended property rights to the individual components of organisms, including genetic information, thus anticipating some of today’s contentious Genetically Modified Organism debates. Ten years later, Asgrow Seed v. Winterboer denied the rights of farmers to save and resell patented seed products, marking the continuation of a series of legislation that progressively placed power in corporate hands. In 2001, J.E.M. AG Supply v. Pioneer Hi-Bred International, a legal dispute between a large seed company and small seed supply center, affirmed that newly developed plant breeds are covered by expansive utility patents. In 2013, furthermore, Bowman v. Monsanto held that patent “exhaustion doctrine” does not cover farmers’ reproduction of patented seeds through planting and harvesting without the patent owner’s permission, further reflecting and securing corporate profit and influence. Lobbying: Although inadequate disclosure laws make it difficult to determine the exact amount expended on the Farm Bill and on other pieces of legislation, during the two years preceding the passage of the Farm Bill on February 7, 2014, at least 600 companies spent over $500 million in lobbying. The largest spenders ranged from Fortune 500 leaders in banking, trade, transportation and energy to non-profit organizations. A joint investigation by Harvest Public Media and the Midwest Center for Investigative Reporting found that the top 18 corporations and groups spent at least $5 million each in total lobbying from 2012 to the First Quarter of 2014. These corporations and groups include: the US Chamber of Commerce, Exxon Mobil, Du Pont, the American Bankers Association, Pharmaceutical Research and Manufacturers of America, Grocery Manufacturers Association, Wells Fargo, AARP, Monsanto, Independent Community Bankers of America, Coca-Cola, Association of American Railroads, Nestle, Nextera Energy, BNSF Railway Company, PMI Global Services Inc., Bayer Corporation, and American Forest & Paper Association.

The commodities support programs outlined above make up one major set of Farm Bill issues influenced by such lobbying efforts. These direct payments have long received the attention of growers groups and other interest groups that are beholden to corporate interests. Specifically, alongside the Farm Bureau, the Farmers Union, pipp vertical racks and other general farm organizations, all major agricultural commodities are represented by a lobbying organization that aims to keep the Farm Bill’s commodity programs intact as per the supposed interest of the producers of such commodities. These organizations include: the National Cotton Council, the Sugar Association, and the National Corn Growers, among others. While indeed all industries are represented by lobbying organizations, the relative political and economic strength of actors within the US food system that are already oriented toward large-scale production, processing, distribution, and service—such as those above—highlights their significance, particularly concerning contemporary campaign finance reform efforts. With the change to crop insurance as the safety net centerpiece, banks and insurance companies spent at least $52.6 million in lobbying the 2014 Farm Bill and other issues in the two years prior to its passage. For example, Wells Fargo, the fourth-largest US bank, spent approximately $11.3 million in lobbying efforts, signaling the potential gain to be had by the company’s Rural Community Insurance Services, the largest crop insurance provider in the country. The American Bankers Association, another group that will benefit most from the boost to crop insurance, reported spending $14 million on lobbying, including advocacy for crop insurance and other rural lending plans. Other lobbyists for crop insurance included Independent Community Bank-ers of America, ACE INA Holdings and Zurich , the National Association of Professional Insurance Agents, and Deere & Co., the large equipment manufacturer that also has a crop insurance arm. 

Private Funding: Private sector spending on agricultural research has risen steeply since the 1970s and 1980s, exceeding public sector spending on agricultural research. From 1970 to 2006, private agricultural research expenditures—both in-house research and donations to land-grant universities—rose from $2.8 billion to over $8 billion, in inflation-adjusted 2014 dollars. Yet total public funding—directed toward land-grant universities and the USDA—rose from $3.1 billion to $6.1 billion in that same period. Federal funding of land-grant universities in particular reflect such trends: by the early 1990s, industry funding had already surpassed USDA funding of agricultural research at land-grant universities and by 2009, private sector funding had soared to $822 million, compared to $645 million from the USDA. Significantly, the economic recession substantially restricted research funding. Yet USDA land-grant university funding dropped twice as fast as private funding between 2009 and 2010, from 39.3% and 20.5%, respectively, reflecting the increasing dependence of university research on corporate funds, particularly during economic downturns. Strategic Mergers: During the 1990s there were numerous mergers between agricultural, pharmaceutical, and chemical firms tied to the global seed industry that aimed to take advantage of potential synergies and secure even greater corporate profit and strength. Because the mergers took place within the globalized market where most seed industry markets exist beyond one nation-state, however, these expected synergies were not realized and resulted in the spin off of numerous agricultural divisions: Monsanto, for example, merged with Pharmacia and Upjohn before a new Monsanto division, now focusing on agriculture, separated to form a new entity. Syngenta began with the merge between the agribusiness divisions of Novartis and Zeneca. However, AstraZeneca, which focuses on pharmaceuticals, remains a separate company. Bayer acquired the agribusiness operations of Aventis, yet Sonofi-Aventis remains a financially distinct pharmaceutical company. By 2009, six companies with pharmaceutical and chemical origins held control over 67% of the global seed industry. “Revolving Door”: Collectively, in addition to the lobbying strength they exert and the private funding they funnel into public institutions, corporations have also been effective in translating their economic power into political power by way of the “revolving door” between corporations and the government.

In 1999, for example, Monsanto was described as a “virtual retirement home for members of the Clinton administration.” The outcome of such tight relationships between corporations and governments is readily apparent in federal legislation that upholds agribusiness power. The “Farmer Assurance Provision,” for example—a provision of a bill that was signed into law in March 2013 by President Obama, yet only remained in effect for six months—undermined the Department of Agriculture’s authority to ban genetically modified crops, even if the court ruled that such crops posed human and environmental health risks. Significantly, Republican Senator Roy Blunt worked directly with Monsanto employees to draft the initial provision. Although supporters stated that the provision was necessary to protect farmers from endless legal complaints by opponents of GMOs that hold up critical research, the Farmer Assurance Provision would have ensured a lack of corporate liability. THE WORLD HEALTH ORGANIZATION defines food security as having consistent access to sufficient, safe, and nutritious food to maintain a healthy and active life. At its core, however, food insecurity is a matter of income and poverty. As such, programs that aim to remedy food insecurity—most notably, the Farm Bill’s Supplemental Nutrition Assistance Program —hold potential not only as key nutrition assistance programs, but also as part of the anti-poverty programs and safety net to support historically marginalized communities in the United States, including low-income communities and communities of color. This is especially the case during times of economic hardship. In this context, Part II first provides a brief snapshot of the state of poverty, food insecurity, pipp grow racks and public nutrition assistance in the United States . It then addresses the origins of SNAP and its supposed concretization as an anti-poverty program in the 1970s, while tracing key periods of the erosion of the program tied to corporate influence and larger trends in public assistance reform. It then addresses in greater detail ongoing corporate influence and gain, particularly in the context of neoliberal economic and political restructuring since the late 1970s and early 1980s, and the myths against public assistance that undergird such gain: anti-poor and racist “culture of poverty” stereotypes, and the stereotype that people on SNAP are “not in a hurry to get off.” Finally, Part II further challenges these and other myths against public assistance and investigates the relationship between SNAP and Unemployment Insurance , another major safety net program, by highlighting their role during the global recession that followed the 2007–2008 financial meltdown. The 2007 subprime mortgage crisis that triggered the “Great Recession” was caused in part by intense financialization: relaxed lending standards and problematic federal housing policies, massive household debt, and the infamous real-estate bubble, among other factors. By exploring the racialized impacts of this decline in economic activity as well as the support available to low-income communities and communities of color—most notably SNAP and UI—this part argues that safety net programs have become essential for such communities. These communities use most of their total expenditures on food and other basic necessities, and are the hardest hit during such economic downtowns. While it also argues that such safety net programs, particularly SNAP, are an important strategy in preventing and alleviating poverty in the United States, Part II ultimately argues that the strong ties between SNAP and corporate control undermine long term and structural work against poverty and structural racialization.The Food Stamps Program, which was later renamed the Supplemental Nutrition Assistance Program , originated in the rural relief and commodity support policies of the New Deal era and, in the wake of the Great Depression, was just as much a farm price support program as an anti-poverty one. As part of the 1933 Agricultural Adjustment Act, the Federal Surplus Relief Corporation facilitated farmer and consumer support by allowing the federal government to distribute farm commodities, purchased at reduced prices, to state and local hunger relief agencies. Spearheading President Lyndon B. Johnson’s “War on Poverty” was the 1964 Food Stamp Act, which gained notoriety as a national anti-poverty program. Under the Food Stamp Act, food stamp benefits were financed by the government and administrative costs shared with states. Only with the 1977 Food and Agriculture Act enacted under President Jimmy Carter was SNAP directly incorporated as part of Farm Bill legislation. Before then, despite the work of the Federal Surplus Relief Corporation, the Farm Bill had long been geared primarily toward commodity support programs. During a decade that saw Black unemployment rise from less than double that of whites to 2.5 times that of whites , this move by the Carter Administration was generally hailed as their principal anti-poverty achievement. Toward this end, in the 1970s alone, federal expenditure on food support grew by about 500%. In 1981, a series of corporate- and government-driven cuts to public assistance began, with SNAP undergoing severe budget cuts of about $1.8 billion, or 16% of its budget, along with cuts to other food and agriculture support programs under the Farm Bill. President Ronald Reagan, who ushered in the era of neoliberalism, made “welfare queens” an epithet, and turned SNAP into a symbol of the ills of big government, made severe cuts to SNAP and other domestic spending, which coincided with the deep recession of the early 1980s. Subsequently, food insecurity in the United States rose during the 1980s and poverty peaked with 15.2% of the population living under the poverty level, the highest since the end of the 1960s. These cuts also facilitated the rapid growth of food banks and grassroots hunger relief agencies—rather than federal public assistance programs—as an appropriate response to the rise in hunger: more than 80% of pantries and soup kitchens currently operating came into existence between 1980 and 2001. Significantly, these cuts mirrored the broader trends in the corporatization of the food system, as outlined in Part I, including scaling back of federal efforts to stabilize prices for farmers and cushion the impact of market volatility, corporate growth, consolidation, and influence in the food system more broadly. In order to combat the growing hunger crisis in the United States, funding was partially restored to SNAP in 1988 and 1990. Funding increases were accompanied by efforts to not only streamline administration of SNAP with an early form of the Electronic Benefit Transfer card, but also to expand eligibility for low-income communities. Yet SNAP’s growth in the early 1990s was countered in the mid-1990s with the conversion of funds into block grants to the states, and the enactment of more strict requirements on SNAP usage and eligibility.

Racial/ethnic inequity with regard to land access is a defining feature not only of the corporate-controlled food system, but also of the US government itself, which, even years after emancipation, has made it nearly impossible for Blacks and other communities of color to acquire and keep land in substantial numbers. For example, in 1920, 926,000 US farmers were Black and they owned over 16 million acres of land, and by 1997, fewer than 20,000 US farmers were Black and owned approximately 2 million acres of land. While white farmers were losing their farms during these decades as well, the rate that Black farmers lost their land has been estimated at more than twice the rate of white-owned farm loss.Though the Farm Bill itself does not deal directly with immigration, the impact of the Bill on farmworkers cannot go unnoticed. The combination of an immigration system easily exploited by employers, and workers’ low income, limited formal education, limited command of the English language, and undocumented status, greatly hinders farmworkers from seeking any retribution or recognition of their rights. With limited legal aid, many agricultural workers fear that challenging the illegal and unfair practices of their employers will result in further abuses, jobs losses, and, ultimately, deportation. Given the fact that the Farm Bill supports many of those companies that employ farmworkers, connections must be drawn to highlight how the Farm Bill upholds and perpetuates structural injustice among farmworkers.In the US, vertical weed grow exposures to environmental hazards have disproportionately impacted low-income communities and communities of color.

As a major contributor to global climate change and the racialized distribution of its impacts, conventional agricultural production practices, in particular, have been instrumental in maintaining and upholding these disparities. Furthermore, low-income communities and communities of color in the United States bear the burden of the impacts caused by climate change. For example, these populations breathe more polluted air than other Americans, suffer more during extreme weather events, have fewer means to escape such extreme weather events, and disproportionately experience greater hardship due to rising energy, food, and water costs.This report found a number of structural barriers to addressing these racial/ethnic, gender, and economic inequities. First, the Farm Bill itself is increasingly imbricated in, and ultimately functions as a pillar of, neoliberalism. The long term shift from the subsidization of production and consumption to the subsidization of agribusiness has structurally positioned low-income communities and communities of color on the losing side of such shifts. This population has also been given fewer options for recourse, given the ways in which the Farm Bill has been designed to be insulated from democratic influence, particularly by way of countless layers of congressional committees. Second, under the current Farm Bill, supporting public nutrition assistance programs and fighting poverty and racial/ethnic inequality, are antithetical to one another, despite the evidence that suggests otherwise. Specifically, while such public assistance programs do provide support to some of the most marginalized communities, they ultimately maintain structural inequity, particularly in terms of wealth, by channeling profits to corporations such as Walmart and other large retailers, which benefit greatly from distributing benefits such as SNAP.

Many of these corporations are then able to funnel profits back to their corporate headquarters outside their respective retail sites, while still paying workers low wages and granting few benefits at every level of the food system. Finally, this report found that supporting the inclusion of producers of color into current payment schemes, and fighting poverty and racial/ethnic [ii]Neoliberalism is a new period of capitalism, particularly since 1970s and 1980s, characterized by unparalleled global reach of economic liberalization, open markets, free trade, and deregulation. Such changes have been facilitated by a mix of high-tech globalized financial systems and labor markets, speculative financial markets, corporate control over the public sphere, increased commodification of human heritages , and increased consumerism. inequality, are also antithetical to one another, despite recent gains in terms of USDA Civil Rights settlements and slowly increasing participation in such programs by such producers. Specifically, while such disparities may be addressed in part by better outreach and assistance, these payment programs, and even crop insurance, ultimately maintain structural inequity, particularly in terms of wealth and land access. For example, producers, be they of any racial or ethnic background, are forced to cut costs wherever possible, which includes: deploying environmentally destructive practices and unjust hiring practices, cutting farmworkers’ pay and working conditions, and relying upon troubling international economies of migrant agricultural labor collectively, which result in regressive racialized outcomes.Socially, economically, politically, and environmentally, the US food system has become characterized by widespread inequity. While corporations control agricultural production and prices, and enjoy record profits, many farmers cannot make a living, are increasingly vulnerable to price fluctuations, and struggle for market access in increasingly concentrated commodity markets.

While corporations reap the benefits of an overworked and underpaid work force, both on and off the field, many consumers, including food system workers themselves, do not have access to nutritious and affordable foods. Additionally, soil degradation, water pollution, and global climate change continue to advance, in part due to large-scale industrial agriculture. The US food system today, however, is not only characterized by social, economic, political, and environmental inequity. Our research indicates that inequity within the food system—such as limited access to nutritious and affordable food, high quality land, or farmers support program benefits—cannot be addressed without addressing inequity within society as a whole, such as low income and limited employment benefits, unfair treatment by public institutions, and limited access to positions of power. Of central concern within this report, therefore, are corporate control and structural racialization within the US food system and society as a whole. Significantly, the production of racial/ethnic and economic inequity in the United States, particularly in terms of wealth, land access, access to positions of power, and degree of democratic influence, is more so a product of cumulative and structural forces than of individual actions or malicious intent on behalf of private or public actors. To challenge and eliminate corporate control and structural racialization in the United States, it is necessary to analyze the ways that public and private institutions are structured, and how government programs are administered and operate in such a way that that reproduces outcomes that marginalize low-income commu-nities and communities of color. Additionally, it is crucial to analyze the genesis and formation of institutions and structures themselves. The US Farm Bill has been the flagship legislation of food and agriculture since its inception in 1933 and is at the heart of policies implemented by public and private institutions that comprise most of the US food system. As such, structural change requires a strong and united movement that is capable of organizing and mobilizing at the state and national level, and that aims to produce conditions required for food sovereignty, including food access, health equity, fair and living wages, land access, just immigration policy, restraints upon corporations, non-exploitative farm labor conditions, and environmental well-being, among others, in particular, and racial/ethnic, gender, and economic justice more broadly. It also reflects a prime opportunity to address corporate structural racialization at multiple scales: from the scale of the food system to that of society itself.

As such, structural change requires a strong and united movement that is capable of organizing and mobilizing at the national level, and that aims to produce the conditions that would guarantee food sovereignty, including food access, health equity, fair wages, land access, just immigration policy, restraints upon corporations, non-exploitative farm labor conditions, and environmental well-being, among others. Such a movement would thus need to encompass grassroots and advocacy organizations that are anti-capitalist, new economy, anti-racist, and feminist, and that are oriented toward environmental justice, labor rights, immigration rights, food justice, climate justice, pipp horticulture racks cost and human rights, among other strategies and goals. Toward this end, the US Farm Bill is a challenging, yet promising, target for structural change within such a movement. This report is of particular importance for two reasons. First, the Farm Bill will be under consideration again in 2019, yet there is no comprehensive critique of the Farm Bill that addresses its underlying contradictions, particularly with regard to racial/ethnic, gender, and economic inequity. Second, it is imperative that campaigns by grassroots, community, and advocacy organizations—generally most active during the period of Farm Bill negotiations in Congress—have enough time to gather adequate information and conduct in-depth analysis for targeted yet comprehensive policy change. As such, the timing of this report is also imperative for coalition-building efforts and the growth of an effective broad-based food sovereignty movement.In terms of structure, the food and agricultural provisions and programs of the Farm Bill are divided into overarching categories called “titles.” These titles are not static and can change between Farm Bills during the re-authorization process. The 2008 Farm Bill had 15 titles, for example, while the 2014 Farm Bill has 12 titles: commodities, conservation, trade, nutrition, credit, rural development, research, forestry, energy, horticulture, crop insurance, and miscellaneous. In terms of scale, the 2014 Farm Bill provided $489 billion in mandatory spending for all titles over the next five years and $956 billion in mandatory spending until 2024. Among the titles of the 2014 Farm Bill, programs under the nutrition title are the largest, accounting for 80% of spending. Nutrition is followed by crop insurance, which accounts for 8% of spending; conservation, which accounts for 6% of spending; and commodity programs, which account for 5% of spending. The remaining 1% of spending includes trade subsidies, rural development, research, forestry, energy, livestock, and horticulture/organic agriculture. Finally, in terms of the process itself, the Farm Bill comes up for renewal approximately every five years. Congressional negotiations on the composition of the bill typically take between two to three years. Many interest groups and corporations shape the Farm Bill by way of lobbying, campaign donations, and other such efforts. Though they vary greatly by their degrees of influence, such actors include large retailers and food manufacturers , suppliers and manufacturers of agricultural inputs , members of government and special interest groups , as well as a diverse set of advocacy organizations . Typically, it is corporate interests and actors that have had the greatest influence in pushing for specific language and policies that advance their respective interests in the Farm Bill.The commodity title includes several programs that aim to protect farmers against sharp fluctuations in prices on primary commodity crops and to keep production relatively profitable. In previous years, the commodity title was primarily geared towards providing large “direct payments” to farmers regardless of how much they actually planted or for how much they would sell their crops. The 2014 Farm Bill cut most of these direct payments by about $19 billion over 10 years, which was the most drastic policy change in this current Farm Bill. Much of this money has gone into other types of farm aid, particularly disaster assistance for livestock producers, subsidized loans for farmers, and the crop insurance program. For example, the 2014 Farm Bill abandoned the 70-year-old practice of setting minimum prices for milk, cheese, and butter, and instead invested in insurance for dairy farmers to protect themselves against price volatility or rising feed costs. Significantly, the shift toward crop insurance programs has largely benefitted private insurance corporations, banks, and the largest producers more than small and mid-sized farmers. The conservation title includes programs to help farmers protect against environmental degradation and maintain their means of production through the use of sustainable management practices. The conservation title also includes programs that pay farmers to retire some of their land, such as the Conservation Reserve Program, the largest land retirement program in the United States. The $4 billion cut in the conservation title in the 2014 Farm Bill marks the first time Congress has voted to reduce conservation spending since the title first entered the Farm Bill in 1985. In every Farm Bill since then—1990, 1996, 2002, and 2008—funding for the conservation title has increased.Trade funding is used to promote US commodity crops and food aid abroad as well as technical assistance to farmers in developing countries. Although President Obama suggested an overhaul of the food aid program—aiming to replace the processes of selling US-produced food to developing countries with direct payments to developing countries—such reform efforts did not take hold and Congress kept the food-aid program intact.

My model projects the economic effects of Prop 12 on the North American hog/pork supply chain. It incorporates the vertical supply chain of representing farms, intermediaries, and consumers. The equilibrium is derived in the vertical market without regulations, which is then compared to the equilibrium after I incorporate the local jurisdiction limit on sale of pork products determined farm sow housing practices. The model includes two regions – inside and outside California – and three sets of agents along the supply chain – hogs farms, processors and marketers, and consumers in and outside California. Quantitative simulations calibrated on recent market characteristics and response parameters from the literature show that: compliant farrowing operations incur higher costs ; compliant processing and distribution operations incur higher costs ; covered pork products have higher retail prices in the regulated jurisdiction ; impacts on consumers outside the regulated jurisdiction and for the unregulated pork products are minimal, with higher prices, California consumers of uncooked pork cuts have substantial welfare losses , and producer surplus impacts are small because consumers in the regulated jurisdiction pay higher prices that cover compliance costs. Results are robust to reasonable ranges of response parameters. The major hog requirement of Prop 12 is that farrowing operations for which the meat from pigs is destined for California must provide group housing with more than the normal amount of space for sows.

Operations that already use group housing have a compliance cost advantage over those that use stall housing. Although California demands pork from less than 10% of North American hogs and 30% of sows in North America are already in group housing, a sufficient share of pork products is available to be diverted to California under Prop 12. However, because the space per sow in the California-compliant group housing was higher than the North American standard, commercial cannabis growers there remained significant costs of compliance at pig farrowing farms. Prop 12 and, more broadly, regulations imposed at a local point of purchase are unlikely to be economically efficient ways to farm practices because they raise costs all along the supply chain as well as at the farm. To highlight the importance of this point, I evaluate an alternative policy under which California would directly subsidize farms to change their housing practices to meet Prop 12 housing standards. The analysis shows that, for the same cost to California residents, the alternative policy would cause more than twice as many sows to be housed in ways that meet California’s standards than would under the Prop 12 regulations of California retail market standards. To explore willingness to pay for product attributes linked to two sets of carrot production practices, organic and fresh cut, I conducted a series of large on-line surveys of U.S. carrot buyers. Starting in December 2019, I asked on-line respondents about their willingness to pay for carrot packages of different attributes in 7 rounds of surveys over about 15 months until March 2021. In all more than 300,000 respondents provided data for my econometric estimation. Respondents face one of two types of survey questions.

The first type of question showed survey respondents a picture of a carrot package and asked which WTP interval represented the most they would be willing to pay for the displayed package. My analysis compared WTP responses from groups that saw packages displaying different attributes. In the other question framework, respondents were shown pictures of two packages side by-side that differed by a single attribute , each with a stated price. Respondents were asked which of the two packages they would be willing to buy at the state price for each. The results of this part of my dissertation are of two types: substantiative about willingness to pay for carrot attributes, and methodological about survey procedures. Main substantiative empirical findings are: Based on the questions for which respondents were shown side-by-side pictures of alternative packages, the median WTP for the organic attribute is estimated to be between $0.19 to $0.23 per pound . Based on the questions for which respondents were shown side-by-side pictures of alternative packages, the median WTP for the fresh cut attribute is estimated to be between $0.47 to $0.56 per pound . Willingness to pay results from the question when respondents faced a single picture of carrot package indicate a large response to price, suggesting that many respondents had a “baseline” market price for carrots in mind. However, this framework was less successful in eliciting differential willingness to pay for attributes in comparison with carrot packages that were not displayed. 

Given the large sample sizes, parameters are precisely estimated, and differ little in response to large economic, supply chain, and social disruption over periods before and during the pandemic. Overall, the research demonstrated that reasonable and useful willingness to pay information can be gathered from cost-effective surveys . I documented stability of parameter estimates over time and found that showing respondents displays of relevant comparisons may be particularly important in framing the question.The first part of the dissertation, dealing with the California Prop 12 regulations of hog and pork regulations, makes three main contributions. The first contribution is to show how economic implications of consumer regulations that apply in a limited jurisdiction have implications for producers that depend on their cost of compliance, and for consumers that depend on whether they are within the jurisdiction of the product regulations. The second contribution is to evaluate how such consumer product regulations that apply in local jurisdictions likely create incentives for only the producers already close to compliance to change their practices. This reduces the costs of the farm practice shifts, but also means that relatively little change occurs in farm practices. The third contribution is to show that consumer product regulations tied to upstream production practices are especially costly ways to achieve changes in farm practices because they impose significant cost on processing and marketing services because of the need for segregation, certification, and traceability. The second part of the dissertation, on consumer demand for carrot attributes, makes several broad contributions. First, although carrots are a widely consumed, staple vegetable in the American diet, very little economic research has been devoted to carrot demand broadly or on demand for organic and fresh cut attributes. My dissertation research begins to fill this lacuna. Second, I find that WTP parameter estimates were constant over periods of massive economic, supply chain, and social dislocation. Third, I show reliable and robust ways to elicit useful estimates from a large and cost-effective online survey. My sampling approach and my empirical procedures offer guidance to empirical research on consumer demand.Foie gras is a food product made of the liver of a duck or goose. Although foie gras can be produced using natural feeding, foie gras production is usually conducted by force-feeding. Force-feeding, growing racks often called gavage, is feeding a duck or goose with more food than they voluntarily eat, fatting the liver. Animal rights activist groups, including the Humane Society of the United States, claim that force-feeding is inhumane treatment of animals . Several countries attempted to prohibit force-feeding practices in production within their jurisdictions. For example, the Israeli Supreme Court ordered the Israeli Ministry of Agriculture to prohibit geese force-feeding to produce foie gras in 2003 . The United Kingdom banned foie gras production under the Animal Welfare Act 2006. However, these examples do not restrict selling foie gras products sold within the regulating jurisdiction. This subsection provides three examples of banning foie gras products sold within the regulating jurisdiction.In 2004, California passed Senate Bill 1520, which changed the California Health and Safety Code. Section 25981 prohibits force-feeding in foie gras production: “a person may not force feed a bird for the purpose of enlarging the bird’s liver beyond normal size” . Section 25982 prohibits selling foie gras products in California: “a product may not be sold in California if it is the result of force feeding a bird for the purpose of enlarging the bird’s liver beyond normal size” . Farms had a seven and one-half year period to modify their production practices. The regulations were implemented on July 1, 2012.

To overturn the foie gras ban, in 2015, the California attorney general appealed to the Ninth Circuit. However, in 2017, the District Court favored the ban, and the law was upheld .In 2006, the Chicago City Council passed an ordinance banning foie gras, City Ordinance PO- 05-1895. The ordinance prohibited selling foie gras in all food dispensing establishments in Chicago. Food dispensing establishments were defined as “any fixed location where food or drink is routinely prepared and served or provided for the public for consumption on or off the premises with or without charges.” The ordinance became operative on August 22, 2006. Soon after the ordinance was passed, the city was sued by the Illinois Restaurant Association and a local Chicago restaurant in the state court, claiming that the ordinance violated the Illinois constitution. However, in 2007, the district court concluded that the ordinance did not violate the Illinois Constitution or the United States Constitution. However, after lobbying by restaurant owners, in 2008, the Chicago City Council repealed the foie gras ban.In November 2019, the mayor of New York City signed the bill banning the sale of force-fed poultry products. The New York City Council introduced the bill in January same year. After a series of hearings and amendments, the council approved the bill in October 2019. The bill is scheduled to take effect three years after it was enacted in November 2022. The new law prohibits selling force-fed poultry products, stated as follows: “No retail food establishment or food service establishment, or agent thereof, shall store, keep, maintain, offer for sale, or sell any force-fed product or food containing a force-fed product.” . According to the definitions in the law, retail food establishment includes supermarkets, grocery stores, specialty food stores, and farmer’s markets. Also, food service establishment includes any type of food service providers, stated as follows: “a place where food is provided for individual portion service directly to the consumer whether such food is provided free of charge or sold, and whether consumption occurs on or off the premises or is provided from a pushcart, stand or vehicle.” .Traditionally, fishers have used dolphins to harvest tuna. Because mature tuna swim below dolphins, fishers use dolphins to locate tuna schools. Drift netting was a widely used fishing practice to harvest tuna. The nets are drawn around located tuna schools, and the bottom of the net is tightened. Then, the fish are trapped inside and hauled onboard. Because dolphins swim above the tuna schools, drift netting catches those dolphins, which frequently kills those dolphins. In response to the reduced number of dolphins by drift netting, consumers boycotted canned tuna in the 1970s and 1980s . One type of consumer response was legislation. In Portland, Oregon, a group of consumers petitioned for an initiative to ban selling canned tuna caught by drift netting in 1990. However, their attempt did not result in legislation .Subnational jurisdictions, e.g., U.S. states and municipalities, increasingly impose farming practices regulations within their jurisdictions . Examples include restrictions on farm organizational structure, regulation of farming practices that cause pollution, setting of minimum wages and working conditions for farm labor, and limiting the use of inputs such as chemicals and fertilizers in crop production and hormones and antibiotics in livestock production . Although such regulations impact the cost of production and competitiveness of farms located within those jurisdictions, the products produced under these various regulatory regimes are eventually commingled in the supply chain without identity preservation and sold to consumers in integrated markets. Such regulations differ significantly in their economic impact from an emerging body of laws and regulations that control production practices for food products sold within the regulating jurisdiction regardless of where the products were produced . A key example is California’s Proposition 12 that was approved by voters in November 2018 and set to be implemented fully in January 2022. Prop 12 sets specific housing requirements for egg-laying hens, breeding pigs, and calves raised for veal and prohibits the sale in California of specified products derived from covered animals maintained in housing that does not meet these standards, regardless of where the covered animals were located. Other examples of such regulations are presented in the previous section.

Our research builds upon this emergent body of work that employs urban agroecology as an entry point into broader policy discussions that can enable transitions to more sustainable and equitable city and regional food systems in the U.S. . This transition in UAE policy making is already well underway in many European cities . As noted, there are many dimensions of agroecology and ways in which it is conceptualized and applied. We employ the 10 elements of agroecology recently developed by the UN FAO in our discussion of urban agroecology1 . These 10 elements characterize the key constituents of agroecology including the social, ecological, cultural, and political elements. Despite the emancipatory goals of agroecology, a recent review of the literature by Palomo-Campesino et al. found that few papers mention the non-ecological elements of agroecology and fewer than 1/3 of the papers directly considered more than 3 of the 10 FAO-defined elements. In an effort to help guide the transition to more just and sustainable food and agricultural systems in cities across the U.S., we propose that food system scholars and activists consider using the 10 elements as an analytical tool to both operationalize agroecology, and to systematically assess and communicate not only the ecological, but also the social, cultural and political values of urban agroecology. “By identifying important properties of agroecological systems and approaches, as well as key considerations in developing an enabling environment for agroecology, the 10 Elements [can be] a guide for policymakers, practitioners and stakeholders in planning, managing and evaluating agroecological transitions 2 .n San Francisco’s East Bay region, urban food production proliferates in schoolyards, vertical growing racks in half-acre lots converted to urban farms, on rooftops, and in backyards reflecting a diversity of participants, goals, impacts and challenges .

The San Francisco East Bay region is also experiencing rapid gentrification and a worsening affordable housing crisis coupled with high rates of income inequality and food insecurity. The challenge of urban soil contamination creates tradeoffs for aspiring growers between vacant lot availability and siting on the most heavily polluted plots . Specific city policies vary in the degree to which they support or discourage urban agricultural activities, and availability of arable land across the East Bay is uneven. Our case study focuses on urban farmers in the East Bay spanning over 28 miles from El Sobrante in the northeastern edge of the bay, to Hayward in the southern East Bay as shown in Figure 1. We include both for-profit and non-profit farms ranging from educational school gardens to roof-top farms marketing microgreens.We employed a participatory and collaborative mixed methods approach, involving diverse stakeholders from the East Bay Agroecosystem. We held two stakeholder input sessions involving over 40 urban farmers and food advocates to co-create the research questions, advise on the data collection process, interpret the results, and prioritize workshop topics for the community. We administered an online Qualtrics survey to 120 urban farms in the East Bay that had been previously identified by the University of California Cooperative Extension Urban Agriculture working group and additional outreach. The survey launched in Summer 2018, which is a particularly busy time for farmers, and in response to farmer feedback was kept open until November 2018. 35 farmers responded in total, representing a 30% response rate.

While there are limitations in our ability to generalize findings to the East Bay urban farming landscape as a whole due to the relatively small sample size, we obtained a fairly representative sample of the diversity of farm types in the East Bay based on our typology of the original 120 farm types . Survey questions fell into nine categories: 1) Background Info, 2) Farm Description, 3) Operating Expenses and Revenues, 4) Land Access and Tenure, 5) Production and Soil Health, 6) Distribution, 7) “Waste” and Compost, 8) Food Access, and 9) Training, Communications, and Follow Up. There were a few open-ended questions allowing farmers to express what they saw as the three largest challenges facing urban agriculture operations in the area, and policy-relevant suggestions for securing spaces for urban farms and increasing community food security. In addition, we interviewed five urban farmers to deepen our understanding of the social, political, economic, and ecological constraints under which their farms operate. These farmers are particularly involved in networking efforts to strengthen urban farm viability in the East Bay. Four out of five represent locally prominent non-profit farms and one subject represents an alternative cooperatively-run urban farm; three interview subjects are women and two are men. Our study complied with UC Berkeley’s Institutional Review Board protocol for the protection of human subjects and all participants gave consent for participation.Most farms including the UC Oxford Tract and Gill Tract Farms, distribute food to a diverse array of community organizations. The two aforementioned farms together distribute food to over 50 community organizations, ranging from food pantries to community health groups to native land trusts seeking to feed and reclaim land for those of indigenous heritage. 52% of respondents distribute all food within 5 miles of their farm, while 70% distribute within 10 miles.

Produce from each farm site reaches approximately 250 people per week on average during the peak growing season, or approximately 7,000 people from all surveyed farms. Customers reached is moderately correlated with total revenue suggesting a growing impact on CFS as farms access additional income. Farmers reported diversified distribution methods including volunteers harvesting and taking food home , on-site consumption , on-site farm stand distribution, CSA boxes at pick up sites, and volunteers delivering produce directly to distribution sites . Some gleaning and second harvesting occurs at urban farms and gardens with potential for growth given reported “unharvested” and “wasted” food percentages. Backyard produce is also exchanged through crop swaps and neighborhood food boxes . Eight operations reported having access to a refrigerated truck for food deliveries, and two are willing to share their truck with other farmers. There is no universally used or city-organized process for distributing produce off of urban farms and into the community, yet there exists great interest in aggregating produce or distribution channels , an unrealized goal of urban farmers in the East Bay. All of the food system stakeholders involved in our study are working towards transformative food system change, focused on increasing equity, food security, and access to healthy, locally sourced food. See Box 1 for a description of one of the non-farmer stakeholders engaged in the food recovery and distribution system, who has recently established an aggregation hub to serve as a network for reducing food waste and channeling excess food in the urban community to those who are food insecure.Farmers in our study stressed the importance of producing non-food related values on their farms, including education and community building. One farmer in particular emphasized their organization’s mission of “growing urban farmers growing food,” or teaching other people how to grow a portion of their food basket, vertical farming racks thus unlocking food sovereignty and food literacy while increasing healthy food access. Another respondent reported that their farm is “highly desirable for adults with special needs that need a safe place to be outside,” echoing respondents who point out the intimate connection between food and health . Farms frequently reported hosting educational and community-building workshops, cooking and food processing demonstrations, harvest festivals, and other open-to-the-public community events enhancing the resilience and connectivity of people, communities and ecosystems. Social networks emerged as an important theme for enabling the establishment of urban farms , and sustaining operations through social connections between urban farmers and other food justice and health advocates.Farmers identified three primary challenges: revenue, land, and labor inputs. Half of all respondents reported farm earnings of $1,500 annually or less, and all four operations receiving over $250,000 in annual revenue are well-funded non-profit operations . Regardless of for-profit or non-profit status, most farms reported multiple sources of revenue as important to their continued operation , with an average of 3 revenue streams per farm. All non-profit farms reported multiple revenue streams except for three, who were sustained entirely by either board donations, membership fees , and grants. The most important revenue sources for non-profits include grants, grassroots fundraising, and unsolicited donations rather than sales. In addition to these monetary sources, all farms reported receiving substantial non-monetary support , which adds to the precarity of operations when these informal support channels disappear.

Land tenure arrangements range from land accessed without payment through contracts with City or School District officials, to arrangements where a token fee is paid , to more formal leasing arrangements at the utility-owned Sunol Ag Park, where land tenants pay $1000/acre/year for their plots, ranging from 1-3 acres. Only five of the respondents owned their land , representing a mix of for-profit and nonprofit operations . Challenges around land access, security, and tenure were the most frequently occurring theme in the survey long response and interview analysis process, including consensus that land access is the largest barrier to scaling UA in the East Bay. The cost of labor, and relatedly, access to capital and grant funding to pay living wage salaries, were also extremely significant challenges identified by survey respondents. The majority of respondents stated that most of their labor is volunteer rather than paid, with nonprofit respondents reporting this more frequently than for profit enterprises . The maximum number of paid staff at any operation is 20 , while the average is 4. Many farms reported the desire to be able to hire and pay workers more, but not having sufficient revenue to accomplish that goal. Annual volunteer labor participants on farms ranged from 0 to 1542 with an average of 97 volunteers, representing a significant public interest in participating in local food production. Not surprisingly, amount of paid labor and total farm income are positively correlated . However, volunteer labor is also positively but more moderately correlated with total farm income .The farmers in our study acknowledged many challenges facing urban agriculture, stemming both from the high economic costs of production and land rents, and insufficient monetary returns from produce sales. They also framed these challenges through a food justice lens, arguing that the current political economy does not fully compensate farmers for the social-ecological services provided from their farms. Farmers articulated many solutions that could improve the viability of their farm operations including: conversion of city parks into food producing gardens with paid staff, government and institutional procurement goals for urban produced foods, municipal investment in cooperatives or other community based food production , and establishment of aggregation hubs and distribution infrastructure.Our survey results describe a highly diversified East Bay Agroecosystem comprising urban farmers and other food system stakeholders that are growing food as well as food literacy, civic engagement, connectivity, and community. Applying an agroecological lens to interpret our findings of East Bay urban agriculture operations reveals the many agoecological practices farms have long been engaged in, as well as the important distinctions of UAE that still need to be explored, and specific threats to agroecology in urban areas. Pimbert suggests that “agroecology’s focus on whole food systems invites urban producers to think beyond their garden plots and consider broader issues such as citizens’ access to food within urban municipalities and the governance of food systems.” We argue that applying an agroecological lens to the urban context also invites researchers and urban planners and policymakers to think beyond garden plots and singular benefits of food production, to consider these sites as part of a larger agro-ecosystem with synergistic social, cultural and ecological dimensions. We reference the 10 elements of agroecology to illustrate the dynamics of how these elements manifest in practice in this urban context.All of the farms in our survey follow agroecological production practices which include a focus on building soil health through, most commonly, cover cropping, compost application, and no-till practices. These practices produce synergistic effects of adding fertility to the soil through organic matter amendments and boosting water holding capacity. Soil building practices are a response to the impetus to remediate toxins present in urban soils , a prerequisite to intensive cultivation and unique consideration of the urban farm environment. Overall, production practices on our urban farms seek to conserve, protect and enhance natural resources. Our survey respondents described numerous strategies for enabling diversified, intensive production of fruits, vegetables, and other agricultural products.

The inventories, however, must then be structured according to the formats usable by openLCA. This modeling process also requires an abrupt switch from a very high level diagram — the flow diagram — to a detailed inventory requiring low-level information about her farm. There is no process connectivity between the two steps and information does not flow between the models. Two: Time and effort overhead. Models must be manually inspected to ensure completeness and correctness. This may result in a suite of errors, such as models that misrepresent the system, models that are missing portions of the real world system, or models that have incorrect connections between processes. Further, the modeling effort expended to create the flow diagram is not utilized to reduce effort in the LCI creation process. The majority of LCI databases are focused on industrial production systems. Those that are concerned with food are oriented toward the production of processed foods as a resultof partnerships with food processing stakeholders. Data required to conduct an LCA of any alternative agricultural systems is unavailable and puts the onus on the system owner to collect primary data. Three: Lack of flexibility. Only one type of granularity, the unit process, can be modeled. There is no support for creating logical groupings of unit processes in the form of components and no capacity to create hierarchies of such components. Alice is locked into two disconnected levels of abstraction: the high-level flow diagram, vertical grow and the low-level inventory. Even once an LCA model is created, current mechanisms only support the sharing of unit process data is shared.

No other reusable portions of the model are explicitly supported. This also means that as things on the farm change, an entirely new LCA model would need to be created.Life cycle assessment has enabled people to investigate, quantify, and understand the environmental impacts of agricultural and industrial systems. On the whole, LCA is useful, but it is not without its limitations. LCA requires meticulous and tedious data collection for every single process within a system. A good LCA is comprehensive and results in detailed models, however it can be a time consuming and cost-prohibitive process, depending on the size, complexity, and novelty of the system under analysis. The development of software also involves modeling, and there has been substantial research into improving the software modeling workflow. In the following analysis, I call on software engineering research and practice to tease apart some of the modeling challenges faced in modeling the environmental impacts of agricultural systems, as well as to propose opportunities for future work. Fred Brooks discriminates between essential difficulties with software — those relating to intrinsic characteristics — and the accidental difficulties — those relating to temporary or circumstantial characteristics. He goes on to state that to address accidental difficulties, one must promote incremental improvements, but to solve essential difficulties, one must promote revolutionary improvements. The challenges faced in the modeling of the environmental impacts of agricultural systems involve addressing both the essential and accidental difficulties. LCA is one of many environmental impact assessment methods that aim to address these difficulties. LCA methods, tools, and data have undergone immense incremental improvements . However, several essential difficulties remain.

Essential difficulties faced when modeling the environmental impacts of agricultural systems involve the representation, or capture, of complexity, change, and context of such systems. Interestingly, some of these mirror the essential difficulties or characteristics of software as defined by Brooks: complexity, conformity, and changeability.Only some of these attributes are represented in current LCA models: the flow diagram informally represents the scope and boundaries of the system and data documentation formats provide structure when representing unit processes. Dependencies, subsystems, and other potentially relevant attributes are linguistically represented, i.e., they are often described in reports that accompany LCA models. Through the structuring of unit processes as prescribed by DDFs and the list-of-unit processes LCI inventory, LCA results in a powerful declarative model: one where within the system boundary, unit processes represent all major flows of material and energy withinthe system, and are connected through the functional unit.Current LCA modeling is similar, in that it is effective at retroactively assessing static systems. Agricultural systems have a symbiotic relationship with the environment, and are closely tied to the health of the environment due to the interconnectedness with many natural systems. These assessment of agricultural systems is unique as not only is one assessing a system that is directly dependent on the natural environment, but that also has a large component of it that are not of human construction, i.e., they are a part of nature: plants, animals, and the land. The quality of the food produced on a farm is related to the quality of the land, air, and water used. These are seasonal systems that are constantly producing, consuming, and evolving over time.

The global warming potential of a farm in Northern California over the Spring of 2014, when they were growing peas and corn, will not be the same five years from now. For this reason, LCA models are time, location, and system sensitive. Dynamic models of agricultural systems that represent changing resource flows, however, are not available in the LCA modeling paradigm to date. Existing LCA models and tools do not capture change effectively. They provide functionality to increment a model version number, but updating and maintaining models to keep up with changes in the real world is difficult. Excel has the “track changes” functionality,which is a helpful collaboration aid that provides different authors with awareness of how a document is changing, but is not explicitly geared toward capturing changes in LCA models. GaBi does something similar. The tool logs all changes to each object at every save . Once again, the goal is to keep track of which user changed the model to support collaboration and not necessarily to augment the capacity of the model to reflect changes in the world. openLCA simply provides a version number for each object in the file that can be incremented as changes are made.State of the art LCA modeling tools do not provide the ability to revert to previous models, compare models over time, or maintain a model history that reflects the changing world. If one is to update and maintain a model over time, it would involve a manual process of backing up and continuing from where one left off. While this is a valid approach, grow vertical given the scale to which some LCA models can grow and the increasing complexity of agricultural systems, more advanced tool support is required.We are constantly producing and trying to connect different types of information in the real world, as well as in our models. A model has two aspects: the representation of a system, and perspective on the system. When these models are treated in isolation, they provide representation without context. Such models cannot be connected with each other to produce meta-models, nor can existing models be reused. When a model is created of an agricultural system, an artificially created system boundary sharply closes off the rest of the world from the system under analysis. The flow diagram tries to capture some contextual information by showing materials and energy flowing into and out of the system as a whole, but, as discussed earlier, the flow diagram is quite disconnected from the eventual LCA model. Trying to capture the context within which a system exists is a difficult problem. After all, one must scope a modeling problem appropriately lest they end up trying to simulate the world. The question remains, however, how does one capture the context of a system? Standalone LCAs are still common as they are conducted when stakeholders of a particular system are interested in self-evaluation and improvement. Comparative LCAs are conducted when stakeholders in an industry are interested in pitting one set of production techniques against another, to analyze whether or not a new or alternative concept is actually better for the environment than an older or standard approach, or any of the other reason discussed previously in this paper. Conducting an LCA that is wide in scope is difficult, and so, when people are interested in understanding wider or more far reaching impacts, existing LCA studies are used to conduct retrospective meta-analyses. Environmental consulting agencies also tend to conduct these analyses, as part of their business model is LCA as a service , where they charge for their expertise, time, and effort. Depending on the intellectual property issues at play, they may own the model details and are not beholden to reveal the raw data to anyone else.

LCA models provide perspective on a specific system without any context. They are difficult to connect with each other to provide more holistic environmental impact assessments, and it is difficult to reuse partial models. People all over the world are producing extremely detailed models, with a lot of time, money, and effort going into inventorying complex systems. A vast amount of data and a large number of models are produced through LCA. We are unfortunately, producing, but not connecting, environmental impact models. No explicit interfaces or connectors are available to connect entire LCA models.LCA models are intended to provide efficient and convenient access to information about the environmental performance of production systems, such as agricultural systems. However, due to the mismatch between the current LCA modeling language, workflow, tool, and the systems represented, I believe that an important opportunity has been missed to capture the complexity, change, and context of agricultural systems. In this section, I describe a potential avenue through which to address these modeling difficulties. In software engineering, the Object-Oriented paradigm came about as an attempt at capturing the essential complexity of software. Booch describes two kinds of decomposition: Algorithmic and Object-Oriented decomposition. The algorithmic results in a top down structured model, declarative and directed. On the other hand, in the OO approach, one decomposes the systems using the key abstractions. Booch notes: “[In object oriented modeling,] we view the world as a set of autonomous agents that collaborate to perform some higher level behavior”. Current LCA modeling utilizes a hybrid of the two, where the flow diagram is created using an OO approach, but is then quickly abandoned for a mostly algorithmic decomposition in subsequent models. Given the modeling challenges described in this chapter, I propose that a potential means to capturing the inherent complexity of agricultural systems is through a new modeling language that allows for a more object-oriented approach.A new modeling language would not be a silver bullet. It would not necessarily capture all of the complexities, changes, or context of agricultural systems, nor would it remove all accidental misrepresentation of systems. What it would hopefully do, is make the process of representing the environmental performance of such systems easier and less tedious, providing clear and distinct ways to represent and connect modular system models. They are prone to change over time due to rising environmental issues , advances in agricultural practices and technology, changing needs of an ever-growing human society, and a dynamic economic context. Our farms are part of the highly interconnected web of industrial civilization, with dependencies on many other systems. Environmental impact assessments are conducted, regulations written to govern production, tools built to guide the flows of materials and products through supply chains, and food labels created to assist in consumer decision making. At the core of these issues is a mismatch between existing environmental assessment tools and the needs of small- to medium-scale farmers , who do not engage in large-scale industrialized agricultural practices. In Chapter 3, I described the essential difficulties faced when modeling agricultural systems.The Grounded Theory Method is methodology used to develop theory about phenomena through iterative interrogation of data. GTM offers a means to explore new territory, particularly when there is a lack of dominant theory. While the goal of this study was domain understanding, I used GTM as a means of structuring the design of this study and utilize GTM techniques for subsequent data analysis. Through use of GTM, my broader goal was to develop theories of design for sustainable agriculture. Muller writes that one must “remain faithful to the data, and to draw conclusions that are firmly grounded in the data” . I do this by iterating between recruitment, data collection, and analysis, exploring the different concepts at play, while gradually developing a theory of how to design a consistent mechanism for modeling sustainable farms and their interactions with the environment.

Agricultural systems are a critical component of this infrastructure, providing crucial food products as part of the human food system, but also providing vital agricultural by-products as inputs for other industrial systems. They are deeply coupled with the natural environment and undergird human civilization. As this web of systems — industrial, agricultural, environmental, human — grows more intricate, it becomes increasingly difficult to understand and map out the consequences of our actions. Agricultural systems are, thereby, commonly assessed to improve economic performance, reduce environmental impacts, and improve social sustainability. System assessment begins with the representation of a system through some modeling process, and a subsequent evaluation of the model with respect to certain attributes. This process involves the collection, structuring, manipulation, and storage of a variety of data. System assessment often involves multiple modeling processes as each model is created to represent a particular aspect of a system and its performance. While instrumental in im-proving our understanding of these complex systems, these efforts have led to a fragmented field with tensions and pulls in different directions, and have resulted in a duplication of effort, and moreover, data and processes that are disconnected. Over the past decade, small- to medium-scale sustainable farms have been growing in popularity. There is an increasing demand for food that is grown sustainably, raised humanely, and produced with fair and just labor practices. This has spawned many efforts to curtail environmental impacts: including, numerous regulations, eco-labels, indoor cannabis grow system and certifications. Such efforts often require farmers to engage in additional record keeping that can be both tedious and time consuming.

Farmers, in essence, pay for the privilege of growing food sustainably. Despite growth in this sector, there is a lack of appropriate technological tools, arising in part from a mismatch between existing tools — which are typically designed for large-scale industrialized agricultural practices — and the needs of farmers who work at smaller scales. With this comes a growing need for systemic mechanisms to understand, analyze, manage, and further improve, sustainable agricultural systems. There is no dearth of analyses of the environmental impacts of our food systems, but there is a lack of connectivity across the plethora of models created and a lag with the changing real world that is represented.Agricultural systems are composed of heterogeneous subsystems with varied environmental impacts. For example, Figure 1.1 shows Alegria Fresh Farms, an urban farm in Orange County, California. It is a small-scale farm that produces fruits, vegetables and a variety of agricultural byproducts such as organic soil. It is not a single product system. A number of subsystems are present within the farm for irrigation, solar energy production, hydroponic cultivation, hydroponic vertical cultivation, certified organic cultivation, vermicomposting, and a nursery, among others. To understand which subsystems are more responsible for certain environmental impacts, one would need to be able to attribute impacts to particular subsystems and processes.This would show the farmer which cultivation method, for example, is more environmentally friendly. The hydroponic vertical cultivation subsystem shown in Figure 1.2 exemplifies the complexity of modern agriculture, even at this small scale. Many of the materials described are sourced externally from other industrial systems. Many external data are therefore required to accurately assess the environmental impact of the farm.

Availability and access to the environmental impact data of these external components is not guaranteed. Agricultural systems are also constantly evolving: equipment is upgraded, cultivation methods are refined to optimize certain metrics , subsystems grow and shrink, and food types grown change according to supply and demand, in addition to season. Figure 1.3 shows two satellite images of Alegria Fresh Farms: the image on the left is the farm shortly after it was set up. Alegria Fresh Farms was one of a set of small experimental and demonstration farms that were introduced to the Orange County Great Park in around 2009. The image on the right was taken after several years of farm activity. The farm has since been relocated. As changes are made in an agricultural system, any models that were initially created become outdated. When models are constructed for agricultural systems, they are a static representation of a dynamic system. Once data have been collected and things change, the model is no longer an accurate representation of the system. Over the last six years, the Alegria Fresh Farms has grown, systems have changed, and as a result, the relationship of the farm with the environment has been affected. However, many models, from satellite images to layout diagrams, cannot necessarily capture the change in the system and its en-vironmental impacts. While there are many techniques that allow for detailed analyses of an agricultural system’s environmental performance, they are primarily expert-driven technique, which means that once a model is created, it is difficult for the farmer to maintain or update it for continued use.Software systems for agricultural modeling are primarily designed for activities such as farm simulation and yield maximization.

These can be both computationally expensive. Such work, while interesting, relevant, and timely, primarily addresses the modeling and simulation of agricultural systems to improve crop yields and system management, with only a marginal focus on environmental assessment of these systems. Agricultural Ontologies: The Food and Agriculture Organization of the United Nations has maintained the AGROVOC project since the 1980s. It is a controlled vocabulary, designed for, and used by, information management professionals . It consists of over 32,000 agricultural concepts, gleaned from publications, research artifacts, and external thesauri. Similarly, the United States Department of Agriculture’s National Agricultural Library has provided a more America-centric glossary and thesaurus service since 2002. These initiatives are part of a broader goal within the agricultural information management community to standardize agricultural terms, concepts, and data. There are also several efforts — in early stages of development — to extend tradition agricultural thesauri into fully developed ontologies for use at the farm level to inform crop production, “foods-for-health” knowledge systems in the nutrition space, and to augment precision agriculture with plant-driven decision making capa-bilities. The AGROVOC team is also developing an ontology service in anticipation of semantic web requirements. Crop Modeling: Work in crop modeling tends to focus on operational and yield optimization. For example, Honda et al. present a service platform that uses a network of field sensors to obtain real-time field data to plan large-scale field operations e.g. fertilizer application. Meanwhile, Ponti et al. used statistical models to assess the yield gap between organic and conventional agriculture to obtain a deeper understanding of the range of performance in agriculture. Agricultural Simulation: Agriculture researchers often use simulations to understand and make predictions about the performance of various agricultural systems, while computation researchers apply their expertise to improving the performance of simulations in agriculture. For example, the Agricultural Production Systems sIMulator project is a modular simulation tool that allows for the investigation of relationships between plants, animals, soil, climate, and management involved in agricultural systems. Papajorgji et al. present different ways in which model-driven architecture, in particular the use of the Unified Modeling Language, can be leveraged to improve crop simulation models. Miralles & Libeourel study how Geographic Information System models can be brought to bear on crop simulation to allow for better integration of weather data. Life Cycle Assessment: LCA is a modeling technique used to assess the environmental impacts of products and the processes by which they are constructed. Farmers, along with environmental analysts, can conduct LCAs to quantify the environmental impacts of resource flows in a system, vertical grow racks and subsequently make improvements in the farming processes to reduce undesired impacts. Many software systems and databases exist to support LCAs, most of which are domain agnostic . Models of agricultural products and production systems are commonly created in the academic community using LCA. Examples of systems that have been successfully analyzed using LCA include: a large American feedlot where beef is produced; a soybean meal production chain that spans from Argentina to Denmark; and an Australian corn chips production chain that begins at the corn farm, and ends at the consumer-ready packet. While LCA models are intended to provide efficient and convenient access to information about the environmental performance of production systems, such as agricultural systems, there is a disconnect between the current LCA modeling process, the needs of sustainable farmers, and the systems represented.

The Bruntland report presents an umbrella definition of sustainable development as, “the ability of humanity to ensure that it meets the needs of the present without compromising the ability of future generations to meet their own needs”. While this definition is commonly used in sustainability research, it is too broad to allow us to engage in grounded, sustainable, human computer interaction work, or other forms of sustainable design activities. We often come away from such discussions with difficulty envisioning specific applications to design and actionable interventions to pursue. There have been many explorations of sustainability in the context of HCI, ICT for Development, and the coordination literature. However, just as most “sustainability-oriented work takes place outside HCI” , much design work for sustainable agriculture also occurs at the periphery of applied computing research. In this section, some of the more promising explorations within this periphery are reviewed.HCI and Agriculture: Interest in the intersection of HCI, design, and agriculture is growing. For example: Raghavan et al. recently suggested use of computation to design better agro-ecological systems, and Frawley & Dyson created non-human animal personas to enhance welfare in animal agriculture. For the most part, design for agriculture tends to be for specific subsets of agriculture. For example, Chinthammit et al. ran a Software Interest Group meeting, looking at “HCI in Food Product Innovation”. Whether it is design ideations specifically for urban residential gardeners or the design of platforms to assist in the creation of backyard permaculture systems, Di Salvo et al. point out that “there is a significant gap between the professional fields of industrial and interaction design and design research in sustainable HCI” . In an attempt to bridge this gap, my collaborators and I ran a workshop on at the ACM CHI conference in 2017 on “Designing Sustainable Food Systems”. We aimed to bring together HCI researchers, designers, and practitioners to explore, design for, and reflect on, opportunities for the HCI community to engage in creating more a sustainable food system. Coordination and Collaboration in Agriculture: Food production is an inherently collaborative process, with many stakeholders involved and varying organizational configurations across system types. Examples include: a qualitative study looking at coordination challenges in organic farm families, and an early warning management technique to enable collaboration among rice farmers participating in small-scale precision agriculture. Such work provides valuable context for understanding how the interplay between stakeholders on farms affects tool design. Farm Management: At the time of this writing, the Information Technology startup community began focusing on the design of tools for agriculture. Earnest examples include: precision farming tools, precision agriculture tools requiring specialized hard-ware ; daily farm management tools aimed at agribusiness; inventory management tools; and tools that provide analytics.Agricultural Environmental Policy: Environmental regulations have serious implications on farm-level assessment, data collection, and record keeping that farmers in California must engage in [38]. Regulations, both state-imposed, and federal, typically require some form of record keeping and form filling, and in some cases, the presentation of these documents during site inspections. Environmental policies that California farmers are subject to include: water, pesticides, and emissions regulations. In addition, farmers may participate in voluntary programs to demonstrate commitment to environmental protection, such as the environmental stewardship program. Environmental Labeling and Certification: The primary goal of environmental labeling and certification agencies is to provide farm quality assurance. These labels and certificates provide the purchaser, whether broker, retailer, or consumer, with the validation that a farm meets a particular standard set out by the certifying agency. The efficacy and usefulness of labels has long been debated from the early days of dolphin-safe labels to the present-day quandary of GMO-labeling. Nevertheless, many farms actively pursue labels and certifications, necessitating an additional layer of record keeping and data collection. There are four main types of labeling and certification in sustainable agriculture: government regulated National Organic Program; non-profit regulated ; retailer specific ; and product-specific .