Tag: vertical grow system

Our empirical analyses of grower attitudes and behaviors demonstrate that local diffusion networks enhanced the effectiveness of the SVWQC. The more producers interacted with diffusion networks, the more likely they were to be satisfied with watershed management policies, participate in policy activities and adopt environmentally sound management practices, as long as they were cost effective. To further validate our results, we conducted on-farm, personal interviews with more than 20 Sacramento River Valley producers involved with water quality management. We feel that these findings are strong enough to emphasize to policymakers the importance of recognizing how government decisions can weaken or strengthen these local diffusion networks. Any dismantling of diffusion networks represents a loss of human and social capital, and capacity for cultural change, which severely degrades the ability to integrate sustainability principles into agricultural policy and decision-making. A variety of evidence suggests that recent policies have decreased the investment in such networks. For example, California agricultural commissioners are local agencies that perform a variety of programs and duties in each county. Historically, their core programs have included pesticide-use enforcement, quarantine, pest detection, pest exclusion, weights and measures programs, and outreach. In recent years, some non-core programs of the agricultural commissioners’ offices have extended into land-use planning and natural resources management. In our survey, the agricultural commissioners were identified as the most trusted and most frequently contacted source for information about water quality. However, while their non-core programs and duties have expanded, funding sources have generally failed to keep pace with new programs and responsibilities, including water quality . Another example is that the two main federal funding sources for land grant university agricultural outreach programs — Agriculture Experiment Stations and the Cooperative Extension system — increased by only 4.8% and 1.6%, respectively, 25 liter pot from 1996 to 2006, whereas costs inflated at a much higher rate.

Although the full impact of these flat budgets depends on state and local decisions, they have contributed to significant decreases in local diffusion networks in California and several important agricultural states. Likewise, from 2002 to 2004, California lost 152 county Cooperative Extension positions in 20 different counties. A final example is federal Farm Bill policies that influence local funding for the Environmental Quality Improvement Program , which is administered throughout the United States by the Natural Resources Conservation Service and in conjunction with local resource conservation districts. This analysis has limits as a case study in sustainability. The Conditional Waiver program in California is still too new to have achieved long-term success, has a relatively limited geographic scope and focuses mostly on the environmental aspects of sustainability. However, local diffusion networks will continue to be important to the future of these programs in California; they will also play a central role wherever sustainability involves policies that require innovation, collective action and cultural change. Agricultural production is increasingly strained by changing climate and population growth. With the global population expected to reach 9.8 billion by 2050, farmers will have to grow about 70% more food than current production.Meeting this challenge will require scientific advances that bridge the gap between conventional techniques and new technologies in plant breeding. Selective breeding has been used for thousands of years in the domestication of crops to artificially select desired traits in foods. More recent breeding techniques have used chemicals to induce random DNA mutations, hoping that one of these mutations is involved in a trait of interest and spending decades attempting to remove unwanted random mutations through breeding. Because these techniques do not introduce foreign DNA into a plant, they are not considered to be genetically engineered.In the past decade, efforts to select for desirable plant traits have drastically increased with new biotechnology to more quickly and precisely introduce changes at the genetic level.New gene editing techniques like CRISPR-Cas9 have revolutionized the field, allowing plant breeders to target traits of value with greater speed and precision. This revolution has also allowed smaller, non-traditional groups to enter the market.

While the creation of GE crops was previously done by research universities and industrial agriculture companies, it is increasingly undertaken by small to mid-sized innovators. As a net exporter of agricultural products, particularly to developing countries, the US could see significant economic benefits from growth in the agricultural sector.Despite the fact that the US plants the largest acreage of GE crops in the world , the development of GE crops in the US has not been able to reach its full potential.4 This is primarily due to costs associated with the complicated regulatory process. It is expensive to bring a GE crop from the laboratory bench to commercial distribution, averaging $130 million and 7 years for a single crop in the US.5 For this reason, GE research has focused on staple crops like corn and wheat. However, the US exports a much larger variety of crops–in California alone, the grape, almond, and pistachio markets are significant contributors to the state’s multi-billion-dollar agriculture economy.The proliferation of new, cheaper gene-editing techniques that can be applied to these crops and the rapid growth in developers have therefore raised issues around the regulation of genetically modified plants.GE plant regulatory policy is primarily created and implemented by three federal agencies: the Environmental Protection Agency , the Food and Drug Administration , and the United States Department of Agriculture . These agencies regulate different types and features of GE crops, depending on the specific use of the crop and how it was produced. Their responsibilities regarding GE crops are outlined by the 2017 Update to the Coordinated Framework for the Regulation of Biotechnology7 and the 2019 Executive Order 13874 .Here, we focus on the role of the USDA in biotechnology regulation as it is the agency with the most recent updated regulations in response to EO13874. Within the USDA, the Animal and Plant Health Inspection Service is the main agency responsible for regulating GE crops and other biotechnology products that may pose a risk to agricultural plant and animal health. For example, in November 2018, APHIS decided that a Pichia kudriavzevii mutant manufactured by Lygos, Inc. should be regulated.This was in accordance with APHIS’ mission to regulate potential plant pests; P. kudriavzevii is a fungus known to cause disease in citrus and grapes. APHIS proposed an updated regulatory policy in June 2019: the Movement of Certain Genetically Engineered Organisms.While still in review ,this rule aims to reduce “regulatory burden for developers of organisms that are unlikely to pose plant pest risks”. One key element is allowing developers to self-determine exemption for their GE plant by comparing it to all plants with completed regulatory reviews, with the option to request written confirmation from APHIS.

To support accurate self-determinations, APHIS proposes creating a publicly-accessible database containing the results of all completed regulatory status reviews, including each reviewed combination of plant, trait, and mechanism of action . While recent federal actions have sought to clarify and modernize regulation, significant barriers to scaling up the production of GE products still exist. Together, the 2017 Coordinated Framework Update and EO13874 outline the need for a unified and straightforward process for the approval of new bio-technologies, but the specifics of such a process are weakly defined at present. While EO13874 calls for the creation of a Unified Biotechnology Web-based Platform, the current iteration is a website with internal redundancies and links to a confusing web of regulations, leaving the user frustrated and with limited additional information. Updated regulation is in flux, with the relevant agencies still developing their updated approach. We recommend several measures that can be taken by the USDA to address the above shortcomings and provide a clear path to safely and efficiently bring GE crops to market. First, the USDA must update federal regulations to clarify and consolidate communication regarding the GE plant approval process. The current APHIS proposal, albeit improved, fails to simplify the regulatory process in a way that makes it accessible to small to medium sized innovators who have no previous experience with regulation. Federal agencies should coordinate their response to inquiries in addition to improvement of the aforementioned unified web platform. Since the USDA is currently the designated funder of the consolidated web-based platform , raspberry cultivation pot we propose assigning coordination to the USDA. This agency is best poised to oversee regulations by using its EO13874-mandated appropriations to develop and manage a clearinghouse for all GE-related inquiries. The USDA would thereby serve as a liaison between all three federal regulators and innovators, benefitting innovators and the agencies alike. Second, while we support APHIS’ creation of a database of all completed regulatory reviews to help developers make self determinations, we argue that the proposed use does not go far enough. APHIS states that developers whose GE plant has the same plant-trait-MOA combination as a previously-reviewed organism could easily self determine non-regulation by APHIS.Developers must request a review or permit if their GE plant has not been previously reviewed and does not fit into another exempted category. We argue that this exemption for previously-reviewed plant-trait-MOA combinations applies to few GE plants and provides no significant relief of regulatory burden. Instead, we propose that APHIS extend this exemption to GE plants with a previously-reviewed trait-MOA combination that is combined with a new plant. If a trait-MOA combination is reviewed in one plant and determined to cause no plant pest risk, then it is unlikely to cause a plant pest risk in a different plant. This is consistent with APHIS’ attempt to create more risk-based regulation and reduce regulatory burden. Third, the federal government, led by the USDA, should push an agenda that supports implementation of clarifying web-based platforms. EO13874’s recommended Unified Biotechnology Web-Based Platform provides the foundation for improvement, but does not go far enough.

The platform should contain more than just descriptions for the regulatory roles of the USDA, FDA, and EPA as it does now.While the site also allows users to contact the agencies with questions regarding regulation, a far better use of the platform would be an avenue to submit an application for commercial approval of a biotechnology product. The web platform currently states that “[each] regulatory agency has its own specific application procedures” but does little more than offer links to each website.If the goal of the current regulatory modernization is to streamline and clarify the process of GE plant approval, then the unified web platform should serve as a tool to help small and midsize producers begin the process of product approval.By simplifying the GE regulatory requirements, the process of taking a GE crop to market will be more transparent and navigable for small to medium sized companies. However, a policy that extends exemptions will also benefit established companies with proprietary traits that have already undergone federal inspection and are better poised to scale up those traits into new crops. This may make it harder for small innovators to succeed in the market. If new proposals are implemented, the USDA will absorb new roles for the overall efficiency of the regulatory process. However, the agency will also have a greatly decreased regulatory burden since many new gene-edited crops will be exempt from USDA regulation. Still, the USDA may not have sufficient capacity to handle requests without a corresponding increase in funding to hire personnel to manage these new roles.We recommend the regulatory exemption of GE plants with a previously-reviewed trait-MOA combination, a unified and detailed web platform for applications for commercial approval, and the consolidation of federal regulatory communication to the USDA. If implemented, our proposals will reduce regulatory burdens on companies and researchers seeking to bring new products to market without eliminating meaningful safety and consumer protection standards. An extension of the regulatory exemption to more GE plant products will likely bring the greatest benefit to large firms, since it will be easier for them to adjust their techniques to bring the same trait to different plants. It will also allow the USDA more time to focus on regulation of novel GE crops, which have completely new traits or mechanisms of action.

We used NLCD land cover to classify natural habitat types, which were not identified in the SCAG layer. Lands in classes which were essentially open space with substantial human activity and which had less than 10% impervious surface were classified as ‘disturbed’. When land-cover layers from the different sources were inconsistent, we verified classifications with ground visits or visual inspection of air photos .We used motion-activated digital cameras at 38 sites to detect carnivore species from April 2007 to June 2008, resulting in 1,130 trap nights. Cameras were placed in and around 6 orchards and 2 continuous wild lands , with distance to nearest camera between 30– 900 meters . At all sites, cameras were placed along similar-sized dirt roads, near signs of carnivore activity or at trail junctions when possible. We placed scent lure in front of the camera to encourage animals to approach the camera and to stop long enough to be photographed. For each carnivore species at each camera site, we tallied the number of nights in which the species was detected at least once. We considered each 24-hour trap night to begin at 6:30 am, and cameras were active continuously between 12 and 76 nights at a particular site.We began the modeling process by selecting the best detection model for each species while holding occupancy rate constant, as in Negro˜es et al. and Duggan et al.. We expected that season and land cover at the camera site could affect detection rate so we included both as covariates in detection models. Detection covariates, as well as predictors of occupancy described below, were standardized by z-score as described in Donovan and Hines. Next, to determine if spatial clustering affected occupancy, and at what scale, we compared models including site , meta-site , or county as predictors of occupancy while including any detection variables selected in the previous step. We then included the covariate from the top-ranked model of spatial scale as a predictor in the candidate model set for occupancy of that species. Finally, for each species we modeled occupancy while including detection covariates from the top-ranked detection model for that species. Potential predictors of occupancy included land cover at the camera site,vertical farming distance from each camera to the perimeter of continuous wild lands , and season .

We also evaluated the degree to which area of orchards and other landscape variables in the neighborhood of a camera influenced carnivore occupancy. To do so, we used the land-cover map to quantify the extent of orchards and covariates within a 1,935 m-diameter circle centered on each camera, approximately the average size of a bobcat home range in this region and intermediate between range sizes of foxes and coyotes. We had 38 sites, and therefore examined only single- and double-factor occupancy models to avoid over parameterization.We report results for the average model, but also include summaries of the top ranked model and all models within 2 AICc points of this model, indicating substantial support. To compare the selection support for each predictor variable, we also calculated variable importance weights, which are the sum of the model weights of all models that contain a given variable. Averaged models include only models within 2 AICc points of the best model. Variable importance rates are assessed across all models and therefore each variable has equal representation.Cameras were active for a total of 667 trap nights in orchards, 201 in natural vegetation near orchards, and 262 in wild lands. We detected 8 of the 11 native carnivore species in the study region. Seven native species were detected in orchards: coyote , striped skunk , bobcat , gray fox , mountain lion , black bear , and raccoon . Eight native species were detected in natural vegetation: coyote , bobcat , mountain lion , gray fox , raccoon , badger , black bear , and striped skunk . The 3 native carnivore species not detected included ring tail, spotted skunk, and long-tailed weasel.On average, the number of native species detected per site differed among land-cover classes , but differences between individual classes were not statistically significant . The number of native species detected was greatest in orchards , intermediate in sites with natural vegetation adjacent to orchards , and lowest in wild land sites . The top-ranked detection rate models for coyote and gray fox included land cover at the camera station location , with higher detections in avocado orchards or near avocado orchard relative to wild lands. Season was also included in the top-ranked models; for fox, the direction of the effect could not be distinguished from 0 , while for coyote, detection rate was lower in the dry season than in the wet season . These detection covariates were included in all subsequent models. For bobcat, the intercept-only model was the top model, so subsequent bobcat models did not include detection covariates.

For all three species, the intercept-only occupancy model was the top-ranked model for spatial variation, thus we did not include spatial variables as predictors of occupancy in our final set of candidate models. Avocado orchards, either at the camera site or in the neighborhood of the camera, were included in at least one competitive occupancy model for all three carnivore species . The area of avocado orchard in the neighborhood of a camera was the most important predictor of bobcat occupancy and was included in all top four models for bobcat occupancy . The area of avocado orchards in the neighborhood of a camera was the third most important predictor for gray fox occupancy . For coyote, the area of orchard in the neighborhood had a weak negative effect , but both avocado orchard and ‘near orchard’ at the camera site had a positive effect . Land cover at the camera site was not included in any competitive bobcat or gray fox occupancy models. Distance to continuous wild land was the most important variable for predicting gray fox occupancy and third most important variable for bobcats , with occupancy increasing closer to or within wild land habitat. Distance to continuous wild land was not, however, included in any competitive coyote models. The area of disturbed land in the neighborhood of the camera was included in competitive models for both coyote and gray fox occupancy , but large standard error values for fox occupancy suggested a weak influence. Disturbed land was not included in models for bobcat occupancy . Woodland, shrub, and grassland/herbaceous vegetation in the neighborhood of a camera had a positive effect on occupancy in all models for all species, except that woodland had a negative effect on gray fox occupancy.Carnivores were detected with surprising frequency in avocado orchards. We detected most carnivore species native to coastal southern California in avocado orchards, and these orchards were used frequently by bobcats, coyotes and gray foxes. Further, we detected more carnivore species in orchards than in wild land sites. Although orchards are often adjacent to wild lands, the presence of carnivores in orchards does not appear to be simply an artifact of landscape context. If this were the case, we would expect to find more carnivores in wild lands than in orchards, which we did not. We would also expect to find that distance to continuous wild land was a more consistently important predictor in our models; although it was the strongest predictor of occupancy for gray fox, it was present in only one competitive model for bobcat occupancy and no competitive models for coyote.The food subsidy value of avocados may explain why omnivores such as bears, coyotes, and raccoons were present in orchards. Indeed, remote cameras have recorded these species eating avocados in southern California , but why obligate carnivores like mountain lions and bobcats would be present in orchards is less clear. Orchards may provide good cover for carnivores; many of these species are habitat generalists, and orchards often replace oak woodlands with structurally similar vegetation.

In our study, we did not find an effect of wet versus dry season on occupancy, as might be expected if carnivores were attracted by water sources. However, irrigation lines, combined with abundant avocados, might simulate year-round wet-season conditions for small mammals, perhaps leading to bottom-up effects in these agricultural systems. Future research could assess whether orchards are providing more food and water for small mammals than native vegetation,vertical garden hydroponic and whether a relative increase in prey might help explain the use of these lands by carnivores. Finally, further study could evaluate whether the presence of infrequently-used dirt roads in orchards might appeal to animals moving across densely vegetated landscapes.There is growing interest in managing for movement of wild animals through agricultural areas. Knowing the value of different land-cover types for habitat or movement can inform conservation decisions regarding which lands should be purchased or put under easements, or which areas are most suitable for the placement of highway crossings. Avocado orchards appear to serve as both foraging and movement habitat for most carnivore species in California, and conservation easements or other incentives to keep land in orchards could offer a cost-effective conservation strategy. Such alternative conservation strategies are particularly important when considering agriculture in Mediterranean-type ecosystems, which are highly threatened.Research is increasingly showing that agricultural crop yields will be susceptible to future changes in temperature, precipitation, length of growing seasons, and carbon dioxide concentrations. While future climate is uncertain, the potential for important effects on major agricultural crop producers such as the U.S. is clear. The quantity and composition of U.S. agricultural crop production, where crops are grown, trade, and economic value of U.S. crop production could be affected. An important challenge in understanding these implications is that agricultural products are traded across the globe. The U.S. is both a major agricultural importer and exporter of agricultural crops, meaning that U.S. agriculture may be affected not only by future climate in the U.S., but also future climate outside of the U.S. via international trade. These international linkages raise questions about the relative importance of the direct and indirect effects on U.S. agriculture; that is, is the potential for changes in temperature and precipitation in the U.S. more or less important than the potential for changes outside of the U.S. to U.S. agricultural crop producers?

Many studies have looked at the global response of agricultural systems to changes in climate, as well as the relative importance of where the agricultural impacts occur. In recent years, attention has begun to turn toward the implications of international trade on the U.S. agricultural sector in particular, finding that international trade effects for the U.S. agricultural sector are comparable in importance to direct, domestic impact. Zhang et al found that considering full, global climate impacts causes significant changes in the projections of U.S. production and exports of crops. Costinot et al and later Gouel and Laborde examined the aggregate impact of widespread local yield changes on global agricultural markets, again finding that the full picture is necessary to understand the future, as comparative advantages among regions shift with particular attention paid to domestic adjustments in land allocation. Finally, Baker et al. extended these findings to a new modeling application, determining that not only does considering global markets cause significant changes in the projections of U.S. agricultural crop production relative to a U.S. only focused study, but also that freer trade may help buffer local productivity shocks. These results suggest the potential for meaningful effects on the financial revenue of the U.S, agricultural sector through changes in both domestic production and international prices. In this paper, we systematically explore the implications of changes to domestic and international temperature and precipitation for U.S. agricultural crop production using a regionally-resolved, global scale model of energy, land, economic, and climate systems: the Global Change Assessment Model . This paper adds to the literature by providing a complementary quantification and replication of the production effects explored in Baker et al. and other modeling efforts with a different model. The analysis in this study is conducted using a modified version of GCAM 5.2. GCAM is a global model that couples representations of the energy system, the economy, agriculture and land-use, water, and the global climate in a single computational platform.

The county tax assessor’s office and the local city hall are important sources of tax records and permits that have been obtained for the property, which can help uncover past uses. Examples of prior uses of sites that may have caused soil contamination are parking lots, junkyards, auto repair or painting, carpentry, machine shops, dry cleaners, gas stations, railroad yards, and illegal dumping. The history of a site will help to determine what kind and how much soil testing is necessary. A site that has been primarily residential or used as green space is generally lower risk. A site that has had past industrial or commercial uses should be more carefully analyzed.The U.S. Environmental Protection Agency finding recommends that for urban areas, “at a minimum, the soil test should include pH, percent organic matter, nutrients, micro-nutrients, and metals, including lead” finding. This level of testing is adequate for a site that has been residential or green space. Most commercial soil labs can test for the most important heavy metals, including lead, arsenic, cadmium, chromium, and nickel. More testing may be appropriate for a site with a history of industrial or commercial use, which might include CAM-17 testing. finding An EPA-recognized laboratory is the best choice for this level of testing.It is possible that other types of tests may be necessary, such as testing for PAHs finding, a class of potentially toxic byproducts of incompletely burned garbage, oil, wood, coal and other organic materials. They can accumulate in soils and become a concern on a site that has been used previously as a car wash, parking lot, road and maintenance depot, or vehicle service station. Staff members at soils labs can be great sources of information. They are generally willing to talk on the phone about appropriate testing based on site history. However, there are instances where additional support may be necessary.According to the California Department of Toxic Substance Control finding, “brown fields are properties that are contaminated, or thought to be contaminated, and are under-utilized due to perceived remediation costs and liability concerns” finding. In cases involving brown fields that were formerly industrial or manufacturing sites, old gas station sites, and other situations, expert assistance may be necessary: these sites may have cleanup issues beyond what a community project can accomplish without technical expertise and a significant budget. These sites may be too expensive to test and remediate; help may be available, though, through state and local brownfield programs.

California DTSC oversees a voluntary cleanup program for brownfield sites. Some cities have brownfield programs that may be able to provide guidance, resources, and perhaps even help in securing funding for cleanup. Although urban agriculture is not yet a common reuse for brownfield sites,vertical tower for strawberries it is an area for further exploration. Local offices of the USDA Natural Resources Conservation Service finding may also be able to provide technical assistance and guidance on a case-by-case basis.Laboratories generally provide an online instruction sheet on how to sample the soils, prepare the samples, and mail them to the lab. Once you have selected a lab, review its website for instructions or speak to a staff member by phone. Detailed instructions on collecting soil samples are also available in several of the resources listed in the section “Sources of More Information.” Review these instructions carefully, since poorly collected or unrepresentative soil samples may not provide accurate information. Generally, it is essential to approach soil testing with a plan in mind. Making a simple map of a proposed site and noting areas with different characteristics helps you decide how many samples to collect.Most labs are receptive to questions regarding interpretation of test results. Soil testing will indicate whether plant nutrients are low and need to be raised for best plant growth and whether the soil pH needs to be adjusted. The soil test can also indicate whether there are higher than acceptable levels of heavy metals or other contaminants, depending on what tests were requested.Heavy metals are the contaminants most commonly tested for, and there is more guidance available about heavy metals, especially lead, than for many other contaminants. Even so, there is no one standard as to what constitutes safe levels of heavy metals in urban agriculture. Most guidelines that exist are created for residential use scenarios and contact with soil through skin exposure or accidental ingestion, rather than being formulated for gardening or farming. Still, they provide some guidance about what is acceptable. One standard to consider is the California Human Health Screening Level finding, which is used by the City and County of San Francisco and the City of San Jose in their guidance on lead hazard assessment for urban gardens and farms.

For lead, the HHSL is 80 parts per million finding. Anything lower is considered below the level of concern for human health. Another standard is U.S. EPA’s Soil Screening Levels finding for residential use, which consider lead to be a hazard at levels of 400 ppm or more. In 2013, the U.S. EPA Technical Review Work group finding for Lead provided a bit of clarification specifically for gardening and deemed soil lead at less than 100 ppm to be low risk for home-grown produce.The U.S. EPA TRW chart with specific, tiered soil lead recommendations for gardening is available in table 2. These standards are advisory only; check with local municipalities finding to find out whether more specific requirements have been established. Two related products can be considered for use in improving existing garden soil. Biochar is a charcoal product that when mixed with soil adsorbs heavy metals and binds them tightly, making them less available in the soil. It has other potential benefits, including holding water and releasing plant nutrients. The second product, activated charcoal, is sometimes mixed with soil to adsorb contaminants including certain pesticides, herbicides, and petroleum products. Both can raise soil pH, which could pose a problem if soil is already alkaline. See the section “Sources of More Information” to learn more about these materials before applying them.The most cautious strategy, perhaps most likely to be considered when dealing with a brownfield site, is to remove existing soil from the growing area and replace it with soil that is certified safe. However, this expensive procedure is out of the range of what most community groups or individuals can afford. Contaminated soil must be disposed of according to law, which can be expensive, in addition to the costs involved with soil excavation, removal, and replacement. A more common approach is to build raised beds and fill them with clean soil. A study of backyard, school, and community garden soils in San Francisco showed that raised bed gardens had significantly lower levels of arsenic, cadmium, and lead than in-ground gardens finding. Another study, conducted in Chicago, measured significantly less lead in raised bed gardens than in-ground gardens finding.To create raised beds, urban farmers can build frames of redwood or other lumber, brick, concrete, rocks, or any other sturdy material that won’t leach contaminants into the soil. Treated lumber should be avoided since lumber treatments may cause copper or other metals to leach into the soil. Water-permeable fabrics can be applied as a barrier between the on-site soil and the imported soil used to fill raised beds. Landscape fabric is permeable to liquids and air, unlike black plastic. Landscape fabrics are made from various materials, including non-woven polypropylene, woven fabric, biodegradable paper mulch, or flexible geotextile fabric. Once the frame has been lined with landscape fabric it should be filled with “clean” soil.

One way of ensuring that soil is clean is to purchase topsoil or planting mix certified by the Organic Materials Review Institute finding. OMRI performs an independent review of products intended for use in certified organic production, handling, and processing. OMRI reviews producer-submitted products against the National Organic Standards and generates a list of acceptable products.Local urban farmers or gardeners may have recommendations on potential sources of quality soil. Some vendors may be able to provide documentation that soil has been tested, and if not, a sample of the soil could be sent to a lab for testing to be sure that it is not contaminated.Other types of containers besides raised beds can be used in urban agriculture. For example, some commercially available growing systems are self-watering, for smaller-scale projects. Others are mesh “socks” that are filled with growing medium and placed on top of the soil. These types of “instant gardens” may be especially appropriate for short-term projects. Although tires are sometimes used as planters, this practice is not recommended, since tires can contaminate soil with leached metals as they degrade over time.Many sites have created successful urban agriculture projects through depaving. For example, in 2006, volunteers removed 5,000 square feet of asphalt from the grounds of Carthay Center Elementary School in Los Angeles and created a thriving garden for the entire community. To improve the hardened clay soil, tons of soil, mulch, and compost were donated and tilled into the soil by volunteers. The garden consists of raised beds and in-ground beds, as well as a stone fruit orchard, citrus orchard, tropical garden, butterfly garden, and poetry garden. If a site plan calls for depaving, test for heavy metals and other contaminants prior to asphalt removal. To test soil beneath asphalt, cut triangular holes in the asphalt with a hand-held concrete saw to expose the soil. Then remove the asphalt triangles, along with any sub-grade debris or stones, and obtain the samples. Replace the pavement triangles and add sand or pea gravel afterward to eliminate a tripping hazard. If soil tests show heavy metals above recommended levels, consider raised beds or large containers rather than removing the asphalt.As urban farming in all its forms becomes more popular, municipalities are beginning to consider a variety of policies related to land use for this purpose, including requirements for soil testing and remediation. Generally,vertical growing the decision faced by municipalities is whether to require soil testing and a remediation plan where appropriate, or to make recommendations and provide educational materials on best practices. Requiring soil testing can create challenges for municipalities if they do not have staff available and qualified to review and evaluate soil test results and remediation plans. Some municipalities require soil testing for contaminants finding for community gardens. Anyone contemplating establishment of such a garden or farm should check with the local city or county environmental health department, parks and recreation department, or other appropriate agency. Municipal decision makers should ensure that policies do not create insurmountable barriers for urban agriculture.

Many community groups pursuing community gardens or other urban agriculture projects have limited funds to conduct extensive site analysis for contaminants and perform any needed remediation. At the same time, contamination of urban soil is an important environmental health consideration, yet it is possible to have urban agriculture that is both safe and cost-effective. Soil testing is extremely important and should be facilitated and encouraged by municipalities. Ideally, this would include subsidizing the cost of soil testing and providing assistance with interpretation of soil tests and development of simple remediation plans. Minimally, it would involve having a list of best practices that urban farmers would agree to implement at their site. Education is important in every case. Many best management practices, such as adding organic matter and managing soil pH, are important strategies for ensuring safe soils but are not practical to handle via policy. Cities and counties should explore forming partnerships with the local UC Cooperative Extension office to provide educational resources and training on soil management for urban agriculture. UC Cooperative Extension has trained Master Gardener volunteers available who may be able to help provide education at the local level. Cities should also foster a connection between their own brownfield program, if one exists, and urban farmers. Municipal brownfield programs should be encouraged to work with urban farmers to identify potential sites and support testing and remediation for urban agriculture projects. This strategy is being used successfully in several U.S. cities, including Milwaukee, Wisconsin, and Kansas City, Missouri.Cround water is a critical resource for California water management. Stored in aquifers, water from rainy seasons can be used during dry and hot summers and supports water users through droughts if it is replenished in wet years.

The overall U.S. market share has declined, mainly due to the growth of competitors including China, Australia, and Chile.Korea ranks among the top six export destinations for California agricultural exports. In 2007, the total value of all California agricultural exports to Korea was almost $400 million finding finding. Among all commodities shipped to Korea, fresh oranges top the list, followed by rice, beef and beef products, almonds, and walnuts. With their FTA in 2004, Korea’s imports from Chile grew substantially for kiwifruit, grape juice, lemons, processed tomatoes, wine, and whey, which are all major California export products. California’s other major international competitors for trade with Korea are France for wine, Spain for grape juice, New Zealand for kiwifruit, beef and dairy, Australia for beef and dairy, Iran for pistachios, and China for strawberries, lettuce, and processed tomatoes finding.The potential for increasing California exports to Korea also crucially depends on the competitiveness of Korean producers and the size of the market. Table 2 shows that imports to Korea represent a small share of the domestic consumption of many major food products.The KORUS FTA defines three mechanisms for improving access for farm products: finding the immediate unrestricted opening, finding the phase-out of tariffs over a period, and finding the expansion of tariff rate quotas finding, with the phase-out of over-quota tariffs. Under a TRQ, a lower tariff is applied to imports within the quota volume, and a higher, often prohibitive finding, tariff is applied to imports in excess of the quota volume. To assure slower import access for politically sensitive products, the agreement allows the imposition of safeguard measures finding. Citrus. Korea is a major market for fresh oranges and other citrus from California, despite a current duty of 50%. While the agreement lowers trade barriers considerably during the off-season, in-season imports finding will still be subject to tight TRQs. The initial duty-free TRQ of 2,500 tons is equivalent to only 0.4% of Korean citrus produced in Korea in 2007. While not currently large, Korean demand for fresh grapefruit, lemons, and limes is growing.

A simple tariff phase-out applies for most fruits, but schedules to open the markets for apples, Asian pears and table grapes, fodder sprouting system which are consumed widely in Korea, are more restrictive. The initial safeguard quantity for apples is 9,000 metric tons, less than 2.5% of domestic production. Fuji apples, a variety favored by Koreans, have the safeguard duty lasting 23 years. Along with the immediate table grape tariff reduction from 45% to 24%, the tariff for off-season imports finding phases out in four years, and the tariff for in-season imports phases out over 17 years. Tariffs for grape juice finding, raisins finding, and wine finding will be eliminated immediately.Among other fruits, strawberries and kiwifruit are promising. Currently no fresh strawberries enter the country, and over 70% of strawberry imports are frozen and mainly from China. Kiwifruit is relatively new to Korean consumers, but imports have grown rapidly finding.California tree nuts have a strong presence in the Korean market. Almond and walnut exports are already substantial. Korea has no domestic tree nut industry and the United States finding is the only or dominant supplier for tree nuts. The current 8% almond tariff will be eliminated, and in-shell and shelled walnut tariffs, as high as 45%, will be phased out over 6 to 15 years. The immediate elimination of the 30% tariff on pistachios will expand the market.Korean tariffs on vegetables will be eliminated either immediately or phased out over time, except for a few sensitive products for which safeguard restrictions apply. Vegetable exports to Korea are dominated by China, except for a few commodities such as pickled cucumbers and fresh lettuce. With a 45% tariff for lettuce, imports constitute a small share of the domestic Korean market valued at $200 million. California lettuce competes mostly with off-season, high-cost greenhouse lettuce and has substantial potential for export growth under the 10-year tariff phaseout. Other fresh, leafy vegetables also have potential for export growth. Garlic, onions, and red peppers are major crops in Korea and face gradual 18-year phase-outs, with safeguard restrictions. Beef products are the number-one agricultural import into Korea by value, exceeding $1 billion in 2007. Korea became an important market for U.S. beef after its beef market was opened in 2001. However, a ban on U.S. beef was imposed in December 2003 finding and Australia and New Zealand exports expanded rapidly.

The U.S. market share has been improving gradually since the U.S. resumed export to Korea in 2007. Under the KORUS FTA, with the sizable initial safeguard quantity, the within-quota tariff is scheduled to fall by 2.7% each year, providing a price advantage to U.S. producers over their competitors. Korea currently has high trade barriers for dairy products. Under the KORUS FTA, TRQs increase gradually with the phase-out of over quota tariffs. Among dairy products exported to Korea, the U.S. has a strong presence in cheese, lactose, and whey. Under the agreement, the first year duty-free TRQ for cheese is sizable finding. For feed whey, immediate duty-free access is granted and for non-feed whey, the over-quota tariff finding will be reduced immediately from 49.5% to 20%—phased out over ten years. U.S. exports of lactose to Korea are also sizable, worth $30 million, about half of Korean lactose imports, and the current tariff of 49.5% will be phased out in five years under the agreement. Although Korea already has an almost open border for many field crops—with the important exception of rice—it has high trade barriers for many vegetables, fruits, and animal products that are important in California agriculture. Under the KORUS FTA, California has substantial potential to expand its exports of agricultural commodities to Korea. Lower trade barriers will allow California agriculture to compete in a large, growing, and lucrative market. Commodity prices are high in Korea, and consumers are willing to pay premiums for the high-quality products produced in California. When the KORUS FTA is implemented, California agriculture should be in an excellent position to compete on both price and quality.Farm labor was a major concern of agriculture in the early 1980s, when enforcement of immigration laws involved the Border Patrol driving into fields and attempting to apprehend workers who ran away. Apprehended migrants were normally returned to Mexico, and many made their way back to the farms on which they were employed within days. There were no fines on employers who knowingly hired unauthorized workers, and the major enforcement risk was loss of production until unauthorized workers returned. As a result, perishable crops, such as citrus, that were picked largely by labor contractor crews included more unauthorized workers than lettuce crews that included workers hired directly by large growers. The Immigration Reform and Control Act finding of 1986 imposed federal sanctions on employers who knowingly hired unauthorized workers. In order to avoid fines and criminal sanctions, all newly hired workers must present documents to their employers to establish their identity and right to work. The employer and worker complete and sign an I-9 form attesting that the worker presented and the employer saw work-identification documents.

Employers are not required to determine the authenticity of the documents presented by workers. There were two legalization programs in 1987–88 that allowed 2.7 million unauthorized foreigners, 85% of whom were Mexicans, to become legal immigrants. The non-farm program legalized 1.6 million unauthorized foreigners who had been in the United States since January 1, 1982, while the Special Agricultural Worker finding program legalized 1.1 million unauthorized foreigners. Unauthorized workers continued to arrive in the early 1990s and presented false documents to get hired, that is, forged documents or documents that belonged to work-authorized persons. As a result, employers faced less risk of disrupted production because the paper chase involved in checking whether documents were genuine did not immediately remove unauthorized workers from the workplace as had Border Patrol worker chases. Figure 1 shows that newly legalized SAW farm workers were one third of the crop work force in the early 1990s, but found non-farm jobs as the economy improved in the mid- 1990s. The U.S. Department of Labor’s National Agricultural Worker Survey first found that over half of the workers employed on U.S. crop farms were unauthorized in 1995, and the share of unauthorized crop workers has remained at about half since then.In 1996 Congress required the then Immigration and Naturalization Service to develop programs to check the validity of worker documents. These programs evolved into E-Verify, microgreen fodder system the current Internet-based system that employers used to check on the legal status of almost 16 million new hires in fiscal year finding 2010, about 30% of the 50 million to 60 million new hires made each year in the United States. Employers submit Social Security numbers and immigration data to E-Verify, and over 98% of their inquiries result in workers being confirmed as work-authorized in less than five seconds. Employees with “tentative non-confirmations” are given a written notice advising them to correct their records so that E-Verify shows them to be authorized to work. Over 80% of tentative non-confirmations result in the employee quitting, likely because the worker was unauthorized. At the end of 2011, all federal contractors and 18 states required some or all of their employers to use E-Verify to check new hires. The U.S. Supreme Court upheld Arizona’s Legal Arizona Workers Act in May 2011, which requires all of Arizona’s employers to participate in E-Verify. Most major meat packers have been using E-Verify for at least a decade. The House Judiciary Committee approved the Legal Workforce Act finding finding in September 2011 to require all U.S. employers to use E-Verify to check new hires and/ or job applicants within four years. Today the federal government enforces laws against hiring unauthorized workers by auditing the I-9 forms completed by newly hired workers and their employers. Most workers identified as having problematic documentation quit or are terminated, prompting denunciations of so-called “silent raids” aimed at unauthorized workers. Some employers, such as L. E. Cooke in Visalia, complain that I-9 audits require them to terminate experienced employees who are difficult to replace. Gebbers Farms in Washington fired hundreds of workers after an I-9 audit and replaced them with legal H-2A guest workers.

With Congress deadlocked on immigration, states such as Arizona enacted laws to reduce the number of unauthorized foreigners in an “attrition through enforcement” strategy. Arizona enacted the Support Our Law Enforcement and Safe Neighborhoods Act finding in April 2010—a law that requires everyone to carry proof of their legal status and show this proof to police officers who stop them for other reasons. Unauthorized foreigners detected by police can be fined $2,500 or jailed up to six months. The Obama administration asked a federal court to block implementation of SB 1070, arguing that federal immigration law prevents Arizona from enacting a state law that interferes with federal immigration enforcement priorities and could lead to the arrest of U.S. citizens and foreigners lawfully in the United States who are not carrying proof of their legal status. A federal judge agreed and issued an injunction blocking implementation of the key provisions of SB 1070. However, a Pew poll in May 2010 found 59% support for SB 1070, including two-thirds who support requiring people to present proof of legal status to police if asked. Arizona and other states that enacted attrition-through-enforcement immigration laws have mostly unauthorized foreign-born residents. Figure 2 shows that a band of states that trace a U-shape, from Idaho through the southern states to North Carolina, has the highest share of unauthorized foreigners among foreign-born residents in the state. About 28% of foreign-born persons in the United States in 2010 were unauthorized, but 40% or more of the foreign-born residents in states such as Arizona, Alabama, and Georgia that enacted laws against illegal migration in 2011 are unauthorized. Alabama’s HB 56 is considered the “toughest” state law against unauthorized foreigners, with Arizona-style police and E-Verify requirements. This law also voids contracts entered into by unauthorized foreigners, makes it unlawful to hire or rent to unauthorized foreigners, and requires schools to obtain and report data on the legal status of school children and their parents finding. Suits have blocked the implementation of parts of HB 56, but some unauthorized foreigners left the state, prompting complaints of labor shortages.

Maize revenues and quantity sold are also positively correlated with propensity to adopt Kudu, though not significantly so. It seems, therefore, that larger, better off farmers are more likely to use Kudu. Looking at the interaction term between treatment and the propensity score, we see the that positive revenue effects are concentrated among likely adopters, significantly so when we look specifically at maize revenues finding. Likely adopters also see significantly larger maize quantities sold finding. We see no significant difference in price for likely adopters, perhaps because prices are determined in general equilibrium in the village, and are therefore not distinct between adopters and non-adopters. Finally, Figure 5 presents heterogeneity in treatment effects based on baseline levels of the outcome, as measure in the baseline survey. Similar to Figure 4, the top panels plot Fan regression estimates of the outcome at endline on baseline levels separately by treatment and control, while the bottom panel presents the difference, along with the 90% and 95% confidence intervals. Density in the baseline measure is again presented in red. Consistent with the results from Table 7, we see null effects for the vast majority of farmers, who tend to lie to the left-hand side of the distribution in total revenues, maize revenues, and quantifies sold. This is unsurprising given the low adoption rates among these farmers. However, for the minority of farmers who lie to the right-hand side of the distribution – who are more likely to adopt Kudu – we see significant increases in total revenues and maize revenues specifically. Though not significant, point estimates on quantity sold are also large and positive for farmers who already sold large volumes at baseline. Perhaps surprisingly, we see a negative and significant effect on prices for those farmers in the far-right side of the distribution of baseline prices. This may reflect some of the broader convergence in prices observed upon introduction of this marketplace. Consistent with this,dutch bucket for tomatoes the top right-most panel suggests that prices are higher for those with initially low prices finding and lower for those with initially higher prices.

The control group for this sub-experiment are farmers in treatment villages who may already be experiencing general equilibrium changes from prices as well as indirect information effects from the treated farmers around them. Second, to exploit the power from the panel nature of the market survey, we then further randomly rolled tranches of control markets into the SMS Blast treatment. In each of the 12 market survey rounds between October 21, 2016 and March 24, 2017 we rolled in three control markets to the SMS Blast, treating all study traders and farmers with the Blast. Then, subsequent to the household and trader endline surveys, we rolled in an additional 36 control trading markets to the SMS Blast and so observe four final rounds of market surveys with this system in place. We begin by investigating the nature of the farmer-level SMS Blast experiment by looking at the extent to which farmer-level uptake of the components of the experiment differs between the SMS Blast treatment and the within-village controls. Table A.11 shows that the treatment-village control group has uptake rates that are in general about three-quarters of the way between the pure control group and the SMS Blast treatment finding. This suggests that there was fairly widespread dissemination of information about the intervention in treatment villages. Given this, it is perhaps not surprising that when we examine the first row of Table A.12 there are few strong differences in outcomes between the SMS Blast treatment and control. While the point estimates generally suggest a positive effect of being treated, only for the variable ‘know better’ finding do we see significant differences. The third row of this table provides a test of the roll-in to control villages, including a dummy for those farmers that as of the endline survey had already started to receive the Blast. Here, we see much smaller point estimates and no evidence that simply including control farmers in the Blast had any influence on outcomes at endline. This impression is confirmed by looking at Tables A.13 finding and Table A.14 finding. To exploit the panel nature of this treatment, we analyze these impacts using market and round-level data with two-way fixed effects and standard errors clustered at the sub-county level. In all cases effects on market-level outcomes appear very limited. The general lack of significance is confirmed visually in Figure B.11.

Overall, then, we conform with the broader literature in finding no large improvements stemming from information-only market price interventions, whether these are implemented individually within villages otherwise generally treated, or rolled in over time to untreated markets. We have a number of windows into the effects of the transport guarantees, because they were randomized both at the individual and at the contract finding level. First, we can look at the cross-buyer experiment, asking whether those buyers who were permanently assigned to receive the Basic or Comprehensive guarantee transact more business on the platform. Table A.15 shows that they do not. Next, within the original control group who were assigned no permanent guarantee, we can examine the effect of the random fraction of bids they post assigned to each guarantee group on the overall amount of business conducted. Table A.16 shows that increasing the fraction guaranteed does not increase business transacted. Finally, at the bid level we can ask whether having a specific bid assigned to a guaranteed increases the chance of doing business, both among the original experimental control group as well as among other buyers entering the platform subsequent to the experiment. Table A.17 examines the bid-level data and shows that for the original control, having a specific bid guaranteed increases the number of successful deals, the amount transacted, and the value transacted. Unfortunately, this pattern of results appears most consistent with a general lack of significance of the guarantees at generating new business, with the control group having come to understand the system well enough to game it finding. While we certainly do not take these results as suggesting that transport and contractual risk are unimportant in anonymous technological marketplaces, it does not appear that these guarantees, backed by AgriNet, were effective at removing them. We have provided a number of pieces of evidence suggesting that this intervention may have generated meaningful spillovers onto the control group. Most basically, the summary statistics on adoption and usage show that there was some uptake of the intervention, and an increase in receipt of SMS price information, even in control villages. Second, the evidence of convergence at the market level indicates that prices move in general equilibrium. If the spatial boundaries of these impacts do not satisfy SUTVA across sub-counties, spillovers to the control will exist. Finally, the “one treated” result in the dyadic data is a direct indication of the fact that trade flows increase between dyads in which only one of the markets is treated, indicating that trade patterns are affected even in markets that are not themselves treated. What does the presence of these positive spillovers mean for the accuracy of our overall treatment effects? They suggest that our market integration effects and farmer treatment effects may, if anything, be an underestimate on the true gains for the platform. For traders, for whom the platform seems to generate competitive pressures that squeeze profits, the implications of spillovers may be more complicated.

To examine the effects of spillovers on traders, we follow Hildebrant et al. finding in using baseline data to map the trading linkages between study clusters, and then exploiting the incidental randomized variation in the intensity of treatment within these trading networks to measure spillovers. The average sub-county is connected to 1.8 other sub-counties by baseline buying networks, and the average number of treated connections is .9. Given stratification-block FE αj , β1 measures the effect of the treatment in a village with no baseline trading connections finding, β2 gives the finding slope coefficient on number of total trading partners, β3 gives the spillover effect of treatment in the trading network for control markets finding, β4 gives the treatment heterogeneity by number of total trading partners finding, and β5 gives the additional spillover effect of having treated trading partners for markets that are themselves treated finding. Given the complexity of estimating standard errors in this data structure, we use Randomization Inference to randomly reassign the sub-county-level experiment 1000 times, re-calculating the network treatment intensity and the regression above for each iteration. In Appendix Table A.18, we perform a balance test by pointing this same specification finding at the baseline data.Table A.19 shows the results of looking at the first year of implementation. These short term effects indicate quite strong and heterogeneous spillovers. The overall effect of treatment is negative finding,blueberry grow pot and exposure to the treatment for control markets is also bad for traders. The SNT in the third row of this table shows that as control traders become more exposed to the treatment – perhaps facing greater competition in their buying markets, which are treated – they pay higher buying prices, achieve lower markups, and as a result see lower profits despite their quantities traded not changing much. Relative to this, the differential ST – SNT in the first row shows that treated traders are able to offset these spillover-related losses, perhaps due to greater access themselves to other markets when both are plugged into the Kudu network. We see a significant negative coefficient on buying price and a significant positive coefficient on markups that offset the spillover-related erosion of markups observed among the control group. Moreover, we see large and significant effects on both purchases and sales, suggesting that treated traders benefit in terms of sales volumes from exposure to a greater number of treated markets. These effects results in a differential ST – SNT profit effect that is positive, significant, and of a similar magnitude finding to that of the SNT effect. This suggests the for treated traders, the negative effect of being more exposed to treatment is offset by the positive effect of being able to access other markets that are within the Kudu network, resulting in limited total spillover effects finding for this group.

Given that the net treatment effect on trader profits is negative and exposure to the treatment is mostly negative for the controls, this suggests that the negative Intention to Treat finding estimates on traders presented throughout the rest of the paper are if anything biased towards zero by the presence of spillovers. Looking over the longer term, we can pool across midline and endline as is done in the rest of the paper for the trader and farmer outcomes finding. We find that, over the longer term, the negative SNT effects are moderated finding. The differential spillover on treated traders remains significant for the volume of purchases and the signs remain positive for revenues and profits, but are no longer significant. We therefore find that spillover effects for traders are strongest immediately after the introduction of the platform; over the longer run, most of the spatial inequalities created may have been arbitraged away. Overall, then, our study suggests that we experienced spillover effects that are in the direction of treatment effects finding, and hence we may be underestimating the gains from the platform in terms of increases in trade flows, price convergence, and impacts on traders. This is an inherent challenge for any randomized experiment designed to increase trade flows in an environment in which markets are not in perfect autarky. Short of randomizing at the country level, avoiding spillovers due to spatial and trade-network based connections may be impossible.What the randomization at scale buys us is the ability to detect any differences in GE outcomes – trade flows, prices, etc.– which may be impossible to detect with an experiment randomized at the individual or village level. However, it does not necessarily provide the full treatment effect. In future work, we therefore intend to combine these results with a structural model, as well as with data on the geography and trading networks observe in our survey data, to estimate the full treatment effects on trade flows and market integration.

They emphasize different aspects of sustainability, from land steward- ship and family farms, to low external-input methods and food safety.Often there are two different themes: sustainability defined primarily in terms of resource conservation and profitability, and sustainability defined in terms of pressing social problems in the food and agriculture system.Each of these perspectives has been illustrated by William Lockeretz1 and Miguel Altieri.2 In his review article on sustainability, Lockeretz documented primarily production-oriented components of sustainability.Altieri, on the other hand, has pointed out that concentration on only the technological aspects of sustainability results in, among other things, failure to distill the root causes of non-sustainability in agriculture.While sustainability efforts need to address both social and technical issues, they frequently overemphasize the technical, a problem we see originating in the way sustainability is often defined.Our purpose in this paper is to discuss concerns about current sustainability definitions and suggest a definition based upon a broader perspective.Among those working in sustainability there is often a feeling that we need to devote less time to talking about the meaning of sustainable agriculture and more time to implementing it.While this is an understandable position, especially for those directly involved in production agriculture, it also expresses a contradiction.How can we form an improved agricultural system if it has not yet been clearly conceptualized? Lockeretz1 queries, “Isn’t something backwards here?” and shows that, although there is a surge of interest in agricultural sustainability, “even its most basic ideas remain to be worked out.” There is no generally accepted set of goals for sustainable agriculture, and little agreement even on what and who it is we intend to sustain.Is it possible, for example, to both sustain production levels and preserve the natural environment? Who should we work to sustain – farmers, consumers, future generations – or should all of them be our priorities? Can we truly sustain one group without considering others? Without clarifying these goals the necessary changes in cultural, infra- structural, technological, and political arenas are difficult to negotiate.If we want sustainable agriculture to pursue a path differentiable from that of conventional agriculture,vertical hydroponic nft system we need to explicitly state and gain some consensus on these goals.A clear, comprehensive definition of sustainability forms the necessary theoretical foundation for articulating sustainability goals and objectives.

The emergence of agricultural sustainability reflects many people’s dissatisfaction with conventional agricultural priorities, especially the extent to which short-term economic goals have been emphasized over environmental and social goals.In response, a number of agricultural sustainability concepts have been developed under the terms “alternative,” “regenerative,” “organic,” “low-input,” and “sustainable.” In this paper we refer to those definitions most commonly espoused in the agricultural research community, definitions which are predominant in the literature and are used as the basis of sustainability programs.We examine what priorities these definitions embody, how these priorities relate to those expressed in conventional agriculture, and how developing sustainability would benefit by broadening these priorities.Although sustainability definitions include a range of environmental, economic, and social characteristics, most focus somewhat narrowly on environment, resource conservation, productivity, and farm- and firm-level profitability.Charles Francis4 defines sustainable agriculture as a “management strategy” whose goal is to reduce input costs, minimize environmental damage, and provide production and profit over time.The National Research Council5 defines alternative agriculture as food or fiber production which employs ecological production strategies to reduce inputs and environmental damage while promoting profitable, efficient, long-term production.For Richard Harwood6 the three principles for sustainable agriculture are: “the inter relatedness of all parts of a farming system, including the farmer and his family; the importance of the many biological balances in the system; the need to maximize use of material and practices that disrupt those relation- ships.” According to Vernon Ruttan7 enhanced productivity must be a key factor in any sustainability definition.Rod MacRae, Stuart Hill, John Henning, and Guy Mehuys8 adopt a sustainability definition which emphasizes environmentally sound production practices.They note that sustainable agriculture today is characterized mainly by products and practices which minimize environmental degradation, although they also point out the potential to move beyond this restrictive application.

In his review of sustainable agriculture definitions, Lockeretz1 stresses agronomic considerations although he does note the connection between changing production practices and associated socioeconomic transformations.Sustainability definitions such as the above focus on environmental conservation which is to be achieved through changing farm production practices without reducing farmers’ profits.They challenge some but not all of the assumptions that underlie agriculture’s non-sustainable aspects, generally neglecting questions of equity or social justice, or devoting little specific language to it.Altieri,2 for one, has challenged the narrowness of these approaches and their implicit assumption that taking care of the environmental, production, and economic aspects of sustainability automatically takes care of social aspects: “Intrinsic to these [agroecology] projects is the conviction that, as long as the proposed systems benefit the environment and are profitable, sustainability will eventually be achieved and all people will benefit.” Altieri has noted that without intervention on policy, research, and other levels, the more appropriate technology developing in the name of sustainability will merely perpetuate and enhance the current differentiation between those members of society who benefit from agriculture and those who do not.Furthermore, the technology itself will not be developed and used unless we address the cultural, infrastructural, and political factors which shape how it is designed and implemented.These factors include scientific paradigms, fiscal policy, international trade, domestic commodity programs, and consumer preferences.Pursuing the dialogue on sustainability is essential in order to make visible the often invisible assumptions and priorities which have governed agricultural research, policy, and business decisions leading to non-sustainable systems.Many of these assumptions and priorities also influence sustainable agriculture programs.Such an examination is critical if we are to avoid reproducing the problems engendered by conventional decision-making processes in the re- search, education, policy, and business institutions which determine agriculture.KennethDahlberg 9 notes that assumptions and biases which may occlude the development of sustain- able agriculture concepts include: separating ourselves from nature and viewing it as something which must be dominated; measuring progress in increasing applications of science and technology; emphasizing technology and formal social institutions over natural systems and less formal aspects of society; and failing to see how human societies fit into and are dependent upon larger natural systems.We would add to Dahlberg’s list the tendency to overlook the needs of human beings who are separated from us, whether it be by distance, by socioeconomic status, or by time.

These types of assumptions govern how we understand the world and have been institutionalized in educational and research pro- grams.MacRae et al.8 note that many characteristics of the research process responsible for conventional agriculture’s great productivity create obstacles to developing sustainable agriculture.Among these are over reliance on reductionism and quantification, scientists’ belief in objective “truth,” and the divorce of research from its potential social consequences.Along with Patricia Allen10 those authors also cite obstacles posed by a peer review system and publishing process which tend to reward individual “isolated” achievement while discouraging long-range interdisciplinary work and innovative ideas.This is aggravated by research funding from private sources, which encourages research on technology development rather than social analysis.The same assumptions and biases which govern research and education are also embedded in much of U.S.agricultural policy.They are expressed primarily as short-term economic considerations such as maximizing production, minimizing production costs and consumer prices, and maximizing the market share of certain agricultural commodities.These priorities have largely been those of the agricultural sector, and not necessarily those that are best for society at large.Major institutions promulgating “sustainable” agriculture often focus on the farm level rather than on the whole system.This is clear from the priorities of the U.S.Department of Agriculture’s Low Input Sustainable Agriculture program.LISA focused on “low input technologies [which] provide opportunities to reduce the farmer’s dependence on certain kinds of purchased inputs in ways that increase profits, reduce environmental hazards, and ensure a more sustainable agriculture for generations to come.”As these priorities demonstrate, agriculture is often thought of almost purely in terms of farms and farmers, a perspective traceable to the period in which most Americans were involved in farm production but which no longer reflects agriculture’s true scope.Even though the on-farm transformation of resources into food and fiber is a core process of the food and agriculture system, it is but one of many components.The system includes not only generating agricultural products, but also distributing those products and the infrastructure which affects production and distribution at regional, national, nft hydroponic system and global levels.Interactions among the larger environmental, social, and economic systems in which agriculture is situated directly influence agricultural production and distribution.The following briefly describes how these larger systems affect agriculture yet remain unaccounted for in many sustainable agriculture programs.Agricultural practices ranging from the development of irrigation projects to the use of agrichemicals have often had negative environmental impacts such as wildlife kills, pesticide residues in drinking water, soil erosion, groundwater depletion, and salinization.Substituting environmentally sound inputs for those which are damaging is an important step in addressing these problems.But ecological sustainability re- quires intensive management and substantial knowledge of ecological processes which go far beyond substitution13 and cannot be achieved merely by substituting inputs.Such substitutions need to account for their complex and long-term ecological consequences.

Otherwise they may engender secondary and perhaps more serious problems in the same way that conventional solutions frequently have been shown to do.Viewing agricultural systems as true ecosystems can serve as a model for bringing the whole-systems perspective to bear on social and economic issues as well.Instead, however, sustainability programs often take conventional approaches to solving these problems by changing the production practices which are directly at fault without addressing the total ecosystem context of either the problems or the alternative production practices which show promise as solutions.An example is the current emphasis on input substitution.Most projects funded by the USDA Low- Input Sustainable Agriculture program in its first two years, for instance, explore how inputs which cause environmental damage or incur expensive costs for the farmer can be replaced with more environmentally or economically benign inputs.In most cases single components of farming systems are being analyzed and little attempt is made to place these analyses in the context of whole agroecosystems.Agriculture both affects and is affected by the larger society.Farmer production decisions, for example, determine the diversity and quality of foods available to consumers, and farm size and technologies have been associated with the economic and social vigor of rural communities.14 At the same time, society deter- mines what is possible at the farm level.Farmers lose valuable farmland when encroaching urbanization creates zoning problems, inflates land values, and generates urban pollution which lowers crop productivity.Production decisions are heavily influenced by consumer decisions.A recent example is farmers’ voluntary discontinuation of Alar on apples.Although farmers continued to endorse the safety of Alar, they realized that this position was untenable in the face of consumer concerns.The international scope of agriculture also plays an important role.Social and economic conditions in other countries and global food supplies can greatly affect the viability of farming in local regions, as evidenced when the world grain shortages of the 1970s led to enormous expansion in U.S.grain production.When foreign demand for U.S.grain subsequently declined, many American farmers’ incomes fell, often to the point where debts incurred to expand production could not be paid, and major social and economic dislocations in the grain belt occurred.Efforts in sustainable agriculture are not unlike those of their conventional counterparts in that they tend to serve certain clientele selectively and generally do not evaluate the social consequences of the technologies that sustainable agriculture encourages.For example, organic farming strategies are often sup- ported because they are environmentally sound, and in terms of the prices organic foods command, are profitable for farmers.An unintended and unaddressed social consequence of this is that people with low incomes often cannot afford organic products and thus are denied access to food containing fewer pesticide residues.Agriculture’s reciprocal relationship with the overall economy is clear.The agricultural industry is a significant portion of the nation’s economy: in 1984 about 20 percent of U.S.jobs were in some aspect of food and fiber production, distribution, or service15 and these workers and their industries contributed 18 percent of the gross national product.

Since these issues imply that managers are, at best, imperfect agents in carrying out the goals of firm owners, they imply that a discussion of firm efficiency should consider managerial incentives separately from the intentions of owners.Vining and Boardman survey the empirical literature on firm efficiency under manager-controlled and owner-controlled organizational structures, and find strong evidence that owner-controlled firms are more efficient.They further argue that the problem of having management carried out by agents other than firm owners is more acute in the public sector, where firm owners – the citizens of a nation – are necessarily uninvolved in management decisions.By contrast, the private sector may possess a mix of manager-controlled and owner-controlled firms, and is therefore more efficient on average.Shleifer argues that the agency problem is more acute in state-owned firms even when they are compared to private firms that are manager-controlled, because a nation’s citizens are an intrinsically diffuse group who have limited ability to specify and monitor the behaviors of firm managers.Shapiro and Willig additionally suggest that public managers may be more likely to have personal goals that conflict with efficiency, as they tend to pursue political careers that benefit from goals such as maximizing the employment of the firm.Hart and Willig illustrate how agency problems are mitigated by competition: As the level of industry competition increases, owners gain useful information from observing other similar firms in the market, and are better able to gauge the extent to which their own managers are exerting efforts to reduce costs.If public firms suffer from greater information deficiencies in the absence of competition, due to their relatively poor ability to monitor firms, then the gains from observing other firms should be greater to them.Consequently, an increase in the level of industry competition due to an increase in the number of firms should increase the efficiency of state-owned firms relative to private firms.It is important to note that the effects of competition in mitigating agency problems are driven by information gleaned from comparable firms.Thus, ebb flow trays as both the similarity and number of direct competitors increases, efficiency gains should be realized.

By contrast, if a market is perceived to be competitive solely because of potential competition that has not manifested in direct competitors , or solely because of indirect competition from substitute markets where firms have different cost structures, then one would not expect efficiency gains through the agency channel.This argument is strengthened if central government term limits prevent repeated interactions with firms, so that politicians do not have a long-term interest in avoiding the moral hazard problem of public firms by punishing them for inefficient behavior.As competition levels rise, soft budget constraints may reduce the relative efficiency of state firms to private firms in two ways: First, if firm profits are reduced as the level of competition increases, then the danger of shutdown for a private firm increases with competition.Thus, private managers and employees faced with the prospect of unemployment and may increase their efficiency, regardless of whether contracting problems misalign their incentives when the threat of shutdown is less imminent.Second, public firms with soft budget constraints may not only be less responsive to losses brought on by competitive forces because they do not face a credible threat of shutdown, they may actually perform more poorly once they are subsidized by the government.Beyond the point when a firm relies on the government for support, its managers have little incentive to improve efficiency, as reductions in profit will be offset by increases in government funding,and increases in profit will be offset by reductions in government support.Note that the incentive problems created by soft budget constraints may be mitigated through contracting: both firm owners and the government bodies who fund state-owned firms have incentives to avoid managerial slack, since supporting a firm that makes losses detracts from other potentially beneficial projects.It is thus possible that governments could at least partially reduce the effects of soft budget constraints by rewarding managers for efficient behavior.However, as described in Section 1.2.1.1, specifying contracts may be especially challenging in public enterprises.Aside from agency problems and soft budget constraints, several other differences between private and state-owned firms are put forth in the literature.While these differences do not appear to be affected by the level of competition faced by firms, and are therefore not the focus of this paper, they are important because they affect level differences between public and private firms, and provide some context for the fact that the empirical literature largely finds private firms to be more efficient than private firms, independent of competition.In this section, I briefly describe the most important differences between state-owned and private firms that affect productive efficiency, but are not affected by the level of competition faced by firms.

Governments commonly and explicitly set goals for public firms other than profit maximization, and a subset of these goals may conflict with productive efficiency.An example can be found in public works programs and other government projects intended to provide employment opportunities: a government might employ more workers than are strictly necessary to produce a given level of output, if it is more committed to increasing employment than to minimizing costs.Similarly, a government may be more reluctant than a private firm to reduce the size of its workforce, should efficiency demand such reductions.For example, a common goal of public firm ownership is to address market failures caused by issues such as natural monopoly conditions.While a public firm designed to address monopoly problems would typically reduce prices and increase quantities relative to a private firm under imperfectly competitive circumstances, the direction of average cost changes is generally unclear as quantities are increased from the point of maximal profit.Moreover, such goals do not affect the underlying cost function that the firm follows, as a function of quantity.Similarly, a public firm with the goal of providing goods or services that are deemed to be under provided by the private sector need not be cost-inefficient in providing those goods or services.To accurately examine the literature on how competition affects the relative efficiency of state-owned and private firms, this study imposes a few constraints on the papers reviewed: First, I limit my survey to studies that compare ownership effects in non-transition economies, and therefore omit examples from China, the former Soviet Union, and parts of central and Eastern Europe.The main reason for this constraint is that economies transitioning from Communist structures simultaneously made many economy-wide changes, and separating the effects of regulatory changes, increased competition, and privatization programs is particularly challenging.In addition, as Megginson and Netter observe, “the data from transition economies is much worse and much more limited than from nontransition economies.” Second, I generally avoid studies that measure productive efficiency solely with metrics that combine revenue and cost data.Many influential studies on private and state-owned firm differences use statistics that depend on output prices to measure “efficiency”- such as marginal profit, return on assets, or the ratio of revenue to costs.While these measures are clearly important in gauging performance differences, they pose issues in measuring productive or cost efficiency that are compounded when efficiency is being compared across different competitive environments.As Boles de Boer and Evans point out: “profits and rates of return may not be good indicators of efficiency as they will reflect any departures from Ramsey pricing which may be possible because of the dominant position of the company.”

Private and public firms might also be expected to exhibit different price-setting behaviors as the level of industry competition varies, which affect any measures of efficiency that depend on prices.In particular, private firms with market power can profitably increase prices relative to the social optimum, while state-owned firms that have allocative efficiency goals might not.Then, measures of efficiency that are sensitive to output prices would overstate the relative cost efficiency of private firms in imperfectly competitive settings – since they would rise when revenues increased – and relative efficiency gains would attenuate as conditions approached perfect competition.Empirical evidence supports this expectation: Bonin, Hasan, and Wachtel use a number of measures to compare public and private bank performance, and find that public banks outperformed private banks in all measures that used costs alone.When measures that incorporated revenues and costs were instead used, private banks outperformed public banks.Both Caves and Christiansen and Laurin and Bozec study “TFP”differences between two Canadian railroads and use the same data, but reach different conclusions about their relative efficiencies.Laurin and Bozec use a TFP calculation that depends on revenue shares, and find that the private railroad is more efficient than the state-owned one.Caves and Christiansen intentionally choose a measure that uses output cost elasticitices instead of revenue shares due to the issues cited above,flood and drain tray and find no differences between the efficiency of the public and private railroad after 1987.Their conclusions differ presumably because of price differences, and not cost efficiency differences, between the railroads.Since it is ambiguous whether whether price-inclusive measures of relative efficiency are adjusting due to cost reductions or revenue increases, I focus on studies that include measures of efficiency based on output per unit of cost.However, I also consider evidence from studies that use price-inclusive efficiency measures in highly competitive environments, since price setting behavior should be limited or non-existent in these contexts.Table A.1 lists 21 studies that estimate the relative efficiency of private and state-owned enterprises, and that give indications of the level of competition studied.Of these, 9 studies examine firms in non-competitive environments; 7 studies examine competitive environments; 4 studies examine firms in monopolistically competitive or oligopolistic environments; and, 1 study examines firms in a variety of competitive environments separately.Where possible, I used four-firm concentration ratios for each industry to establish the competition level7 : Firms operating in industries with four-firm concentration ratios under 20% were deemed competitive; those with ratios between 30% and 80% were monopolistically competitive or oligopolistic; those with ratios above 80% were considered to be non-competitive.When four-firm ratios were not available, I used the number of industry competitors faced by firms, along with descriptions and assessments of the competitive environments provided by authors.

Aside from establishing the appropriate competition category for each study, author descriptions provided additional relevant details about the competitive environment, such as levels of indirect competition faced from substitute markets, any potential but unrealized competition faced from recently lowered barriers to entry, the extent to which firms competed internationally or regionally, the regulatory environment within which firms operated, and the extent of product differentiation within the industry.Because of the variance in methodologies and measures of efficiency, comparable measures of the extent of the efficiency gap between private and public firms were not available across studies.Nonetheless, by examining the porportion of studies that find significant differences between ownership types at each level of competition, a pattern emerges.Figure A.1 separates the 21 studies according to the level of competition they examine, and their findings on the relative efficiency of ownership types.7 of the 10 studies that take place in monopolistic settings find that private firms are more efficient than state-owned firms, while the other 3 find no significant differences in ownership types.In monopolistically competitive or oligopolistic environments, 3 of 5 of studies find private firms more efficient, and 2 find no differences; and, in competitive environments, only 4 of 8 studies find gains to private firms, 3 studies report no differences, and 1 study finds that public firms are more efficient.Clearly, no conclusions can be drawn from these coarse results alone.The studies vary widely in the number of firms they consider, the data they examine, and the methods they use.Additionally, contextual differences likely play a large role in explaining the variation in findings: Some studies examine static environments where state-owned and private firms co-exist, while others look at privatization programs that often occured along with market liberalization measures and regulatory changes.The governments running state-owned firms had a variety of stated and observed goals for their firms, different policies regarding subsidization of public firms, and may have differed in their abilities to monitor firm managers.Private firms may have been more or less efficient depending on the regulatory constraints under which they operated.To gain some insight into how competition might affect ownership differences, Section 1.3.3 reviews in greater detail the findings of the literature.While most studies considered in this paper examine firms within a single level of competition, I begin with the single study that separately examines ownership effects across both competitive and non-competitive environments.La Porta and Lopez-de-Silanes study the effects of privatization for 218 state-owned enterprises in Mexico.

One mechanism that could underlie the development of such systems is the dual role that erosion can play in influencing soil fertility.Erosion removes soil and associated nutrients from surface soils, often limiting the productive capacity of agricultural ecosystems.However, erosion also exposes rock and little weathered soil near the surface, making the effective age of the soil much younger than that of the geological substrate from which it was formed.This effect has the potential to enhance the fertility of both erosional and depositional areas.Studies that have used strontium isotopes as tracers of nutrient sources within native forest ecosystems in Hawai’i show that although the supply of nutrients derived from the weathering of soil minerals is depleted on stable geomorphic surfaces of the older islands , the weathering source is rejuvenated and soil fertility is enhanced on lower slopes and in alluvial areas of those same landscapes.Palmer and others evaluated soil fertility, erosion, and their potential contribution to precontact agriculture on constructional geomorphic surfaces, slopes and valley bottoms on the wet windward side of Kohala volcano of the Island of Hawai’i–the oldest portion of the youngest island in the archipelago.Leeward Kohala supports a large rainfed agricultural system that is bounded by well-defined thresholds in climate and soil fertility ; the soil fertility threshold occurs where cumulative weathering and leaching have depleted soil minerals to the point that they no longer supply substantial quantities of nutrients or buffer atmospheric acidity.This threshold shifts to progressively lower rainfall levels in progressively older substrates across the Hawaiian archipelago.Based on soil properties at the leeward soil fertility threshold, Palmer and others concluded that: soils on constructional surfaces of windward Kohala are too infertile to support intensive rainfed agriculture, at least as it was practiced in leeward Kohala; erosion has a positive but small effect on soil fertility on slopes and alluvial areas in small stream valleys; and rock-derived nutrients dissolved in the streamwater used to irrigate pond fields sufficed to meet the nutrient demands of intensive pond field agriculture in these smaller valleys.

Palmer and others also analyzed soils in Pololu¯ Valley, a large valley in windward Kohala; there,ebb and flow bench soil fertility on lower slopes and alluvium was enriched substantially relative to constructional surfaces or to smaller valleys.They suggested that most of the material transported by erosion in the small valleys was derived from low-fertility soils in the surrounding uplands, whereas most of the material in the large valley came from its steep and little-weathered walls.Despite the fertility of lower-slope soils in the large Pololu¯ Valley, its slopes are extremely steep all the way to the alluvium on the valley floor, and there is no evidence of intensive rainfed agriculture having been practiced on these slopes.Similar slope profiles occur in Waipi’o and Waimanu Valleys in windward Kohala; these are the largest valleys on the Island of Hawai’i, and their alluvial valley floors supported the most intensively irrigated areas on the island.In contrast, most large valleys on older islands in the archipelago have very different slope profiles, with an accumulation of gradually sloping colluvial material between their steep walls and relatively flat alluvial floors.Why do large valleys on the older versus the younger islands in the Hawaiian Archipelago differ in structure? Are soils of the colluvial lower slopes on older islands fertile enough to support intensive rainfed agriculture? Could differences in valley structure have shaped pathways of agricultural development and intensification in pre-contact Hawai’i? In this article, we compare topography, soil fertility, and associated agricultural potential in two large Hawaiian valleys, Pololu¯ on the island of Hawai’i and Halawa on the much older island of Moloka’i.We test the hypothesis that the geological processes of erosion and subsidence influenced pathways of agricultural development and intensification in these landscapes.We focused on Pololu¯ and Halawa Valleys because they are comparable in size, relatively accessible, and because the archaeological remnants of Hawaiian agriculture have been surveyed in both.Pololu¯ Valley is the westernmost of seven large valleys on the windward northeastern flank of Kohala Volcano, the oldest subaerial portion of the Island of Hawai’i.Most of the lava within Pololu¯ Valley is from the Pololu¯ volcanic formation, older tholeiitic basalts that erupted from 400 to 600 ky before present; younger flows of the later alkalic Hawı formation cover much of the surrounding uplands and spill into the Valley.Wave-cut sea cliffs flank Pololu¯ Valley on both sides, and the valley itself is from 200- to 400-m deep.

Pololu¯ has a long history of Hawaiian occupation ; it was colonized by AD 1200 , and evidence of both irrigated pondfields and rainfed agricultural systems can be found on the broad, relatively flat floor of the valley.Halawa Valley is the easternmost of four large valleys on the windward flank of east Moloka’i.The east Moloka’i volcano emerged approximately 1.8 million y before present, and later alkalic eruptions covered most of its surface around 1.4 my ago.Like Pololu¯ , Halawa Valley is flanked by sea cliffs, and the main valley itself is approximately 300-m deep.Halawa has a pre-contact cultural sequence dating from at least AD 1300.Its extensive irrigation systems are intact; a total of 693 pondfield terraces have been recorded in nine separate irrigation complexes.The colluvial slopes above the irrigation systems on the valley floor exhibit dense archaeological landscapes of residential and rainfed agricultural features.We characterized the modern topography of Pololu¯ and Halawa Valleys using a 10-m digital elevation model provided by the National Elevation Dataset.Four 200-m-wide topographic swaths were selected to represent slope profiles in each valley, one near the valley outlet to the ocean, two in the center, and one just below the major waterfalls that bound the upper margin of the valley cores.Together, these transects sample more than 25% of each valley.The minimum, maximum, and mean elevations in the across-swath direction were computed for each point along the long dimension of the topographic swath.We compared mean elevations from each of the swaths by normalizing elevation and distance along the swath, and centering the swaths on the minimum swath elevation.Second, we calculated the distribution of slope angles across the full surface of each valley using a low-pass filter on the NED-DEM with a cut-off frequency of 0.05 m-1 to characterize the overall valley morphology by removing topography related to small individual gullies and ephemeral streams.From this filtered DEM, we extracted all filtered slope values within Pololu¯ and Halawa, summarizing these values as a cumulative distribution that denotes the fraction of the mapped valleys whose slopes are less than a given value.We sampled alluvial and colluvial soils within each of the valleys, and along transects on upland soils on both sides of each valley; locations where soils were collected are shown in Figure 1.We collected integrated soil samples from 0- to 30-cm depth following protocols similar to those of Vitousek and others , using a tiling shovel to expose a 30-cm profile and collecting an integrated sample across this depth.This depth generally encompassed the soil that was churned by cultivator’s digging sticks —and in earlier studies , the chemistry of these integrated 30- cm samples correlated well with deeper profiles collected across Kohala Volcano.Moreover, analyses of the 30-cm samples provided consistent thresholds that defined the distribution of pre-contact rainfed agricultural systems.Samples on the upland transects were collected systematically at approximately 500-m intervals, and sample positions were recorded via GPS.In Halawa Valley, slope and alluvial samples were collected on transects reaching from alluvial soils near the main stream up to sloping colluvial soils, continuing upslope above any remnants of Hawaiian agriculture to the base of the cliffs that surround the valley.The basal slopes of Pololu¯ are much steeper, and transect sampling was not feasible; instead, we collected alluvial and lower-slope soils widely across the valley and at the lowest portion of its steep slopes.

Most of the alluvial and lower-slope samples were collected within long-abandoned Hawaiian agricultural systems.Soils were air-dried, sieved , and then divided into three homogenous sub-samples, and all analyses were carried out as described in the supplemental material to Vitousek and others.Briefly, one sub-sample was analyzed for total C and N using an elemental analyzer; a portion of this sub-sample also was extracted using the method of Kuo and analyzed for resin-extractable phosphorus using an Alpkem RFA/2 Auto Analyzer.A second sub-sample was analyzed for cation exchange capacity and exchangeable Ca, Mg, Na, and K at the University of California, Santa Barbara, using the NH4OAc method at pH 7.0.The third sub-sample was shipped to ALS Chemex and analyzed for total concentrations of Ca, Mg, Na, K, P, Sr, and Nb using lithium borate fusion and X-ray fluorescence spectrometry.Duplicate samples were incorporated in each procedure.These measurements include some that reflect the forms of elements that are available to biota on relatively short time scales ,4x8ft rolling benches and others that represent the total pools of elements and/or the cumulative effects of weathering.Available forms of elements can be dynamic; measurements reflect what was in the soil at the time of sampling, but those pools can change on annual time scales and certainly are likely to have been influenced by human land use, both pre- and post-European contact.Total element pools are a more conservative measure; they include forms that are not immediately available to organisms, but they reflect the integrated outcome of additions and losses of elements playing out at time scales of decades or longer.Soils were collected across broad rainfall gradients in and around the two valleys—particularly in the uplands , where sample locations received from about 1450– 3420 mm y-1 of rain at Pololu¯ and from around 875 to 2200 mm y-1 at Halawa.Consequently, mean values of soil properties must be compared with caution.The distribution of soil properties with variation in rainfall provides a more direct measure of differences between valleys and among slope positions within valleys.These distributions are illustrated for base saturation and the percentage of P remaining in Figure 4; both of these measures are relatively stable indicators of soil fertility that correlate well with the boundaries of intensive rainfed agriculture in leeward Kohala.Both base saturation and P remaining decline with increasing rainfall in the uplands surrounding both valleys, consistent with numerous measurements of both 30 cm and deep soils along rainfall gradients in Hawai’i.Where rainfall ranges overlap between the valleys, Halawa soils are substantially lower in both base saturation and P remaining than are Pololu¯ soils—again consistent with numerous measurements that show declining soil fertility with increasing substrate age in Hawai’i.Alluvial and colluvial soils within both valleys had much higher base saturation and P remaining than did upland soils with similar rainfall.Although the uplands surrounding both Pololu¯ and Halawa Valleys are nutrient-depleted and infertile, with most samples falling well below the thresholds that bounded intensive Hawaiian rainfed systems , the slope and alluvial soils are well above these fertility thresholds.Not surprisingly, the remnants of intensive pre-contact agriculture were absent in the uplands and abundant in the alluvial areas of both valleys and the lower slopes of Halawa.Similar patterns of variation with rainfall and slope position were observed for most soil measurements, excluding only total C, N, and P.We summarize these comparisons in Tables 1 and 2, comparing slope and alluvial soils in each valley with upland soils that fall within a similar range of rainfall.Because Halawa Valley is both older and has much lower rainfall than Pololu¯ , we confine our statistical comparisons to slope positions within each valley and its surrounding uplands—although upland Halawa soils are systematically less fertile than Pololu¯ soils at comparable rainfall.Analyses of variance for most soil properties yielded significant differences with sample position in both valleys ; for these properties, in every case uplands were significantly lower in fertility/nutrient availability than were slope and alluvial positions, and slope did not differ significantly from alluvium.Total element pools displayed different patterns.There too analyses of variance yielded significant differences with sample position in both valleys.For C and N, upland soils had significantly higher concentrations than slope and alluvial soils in both valleys; slope and alluvium did not differ significantly.For total P, upland and alluvial soils had significantly higher concentrations than slopes at Pololu¯ , whereas upland soils had significantly lower total P than slope or alluvial soils at Halawa.We suggest that the greater total C and N pools of upland soils reflect their greater effective age, relative to slope and alluvial soils.

Another cultivated legume, peanut/maní , was domesticated in South America in the prehispanic era, likely in eastern Bolivia, northern Argentina, Paraguay, and Southern Brazil , where its cultivation then spread across South America. Peanuts are best suited to sandy, well-drained loamy soils; for optimal yields, peanuts require steady, warm temperatures and only a moderate amount of water, as well as a four to five month growing period . The optimal growing ranges for peanuts in the Andes range from approximately 0 to 1,000 masl . Along with other members of the Fabaceae family, peanuts would have been beneficial for their nitrogen-fixing properties when planted in fields alongside other cultigens. High in protein, peanuts were prepared and consumed in a multitude of ways: roasted, fried, salted, boiled, and ground, used as additives in sauces and in some cases for chicha production . While various scholars consider peanuts to be a luxury item primarily associated with elite contexts, the widespread nature of this practice is not particularly well understood. Milk also can be extracted from peanuts in a manner similar to almond milk; peanut milk, along with pressed peanut oil, was used for a variety of medicinal purposes, including to treat 140hemorrhoids, as a laxative, and to soothe colicky infants . Cotton/algodónwas cultivated widely along the coast and in the Amazon in the prehispanic era, primarily for its vegetable seed fiber, the raw material for a large volume of textile products . Domesticated in the Preceramic Period ca. 2600 B.C., cotton domestication, along with squashes/gourds and other root crops, was underway in northern Peru before maize arrived . Aside from its primary economic use in textile production, oil from pressed cotton seeds also is consumed, and cotton seeds, leaves, and fibers possess a variety of medicinal uses, including as a diuretic, to treat hemorrhoids, dental abscesses, ear aches, coughs, and fevers . Irrigated fields in coastal yunga zones are ideal for growing cotton, as cottons are sun-loving plants, but cultivation requires an abundance of water. The highlands are too cold and the eastern slopes of the Andes generally are too humid for the plant to thrive . Newly planted fields yield their first crops after approximately eight months growth; however,mobile grow system the best fibers are harvested from plants that are four or five years old .

Gourd/mate , along with cotton, was domesticated in the Preceramic Period and served primarily as an industrial plant. On the Peruvian coast, evidence for domesticated bottle gourd comes from the Middle Preceramic Siches Complex , and from the La Paloma site in the Chilca Valley of central Peru ; squash, guava, and Phaseolus beans also were documented at La Paloma . The flesh generally is too bitter to eat , but gourds generally are used to make durable containers and floats. Although ubiquitous in the archaeological record, gourd is not a New World native. Rather, it is believed that African gourds were washed out to sea in the Atlantic and floated to coastal Brazil or northern South America . Bottle gourds can be grown throughout the tropics, subtropics, and into the temperate zone. Cultivated widely in the prehispanic era on the coast of Peru, gourd remains have been documented at several Preceramic cites including Huaca Prieta in the Chicama Valley and Guanape in the Virú Valley of northern Peru and at the Buena Vista site in the Chillón Valley of central Peru . An artistic tradition that continues in Peru today is elaborate gourd carving. This practice has great antiquity; indeed, remains of mates buriladoswere recovered from the Preceramic component at Huaca Prieta in the Chicama Valley in Junius Bird’s 1946 excavations. Bird describes the remains of 15 gourds, some dated to 2,000 B.C., with Z-shaped and anthromorphic carvings . Potato/papais cultivated in the Andes from sea level to 4,000 masl . Andean potato crops are renowned for their immense diversity, with seven domesticated species and several thousand land races, as well numerous closely affiliated wild relatives. The potato complex is spread across the Andes in Peru, Bolivia, and Ecuador, with early potato cultivation beginning approximately 7,000 years ago . Today, the diversity of potatoes is clustered in the eastern Andean valleys and uplands of south-central Peru and north-central Bolivia, i.e., from the Huancayo and Ayacucho highlands southward to the Cochabamba and Potosí sierras. In many parts of the Andes, growers rotate their potatoes and other crops among scattered field plots, typically sowing potato fields for 1-3 years before rotating the planting to another site .

As environmental factors including pests, diseases, weeds, climate hazards , and soil conditions are common, Andean farmers typically attempt to reduce crop losses by relying on potatoes with broad habitat tolerances . Sammells notes specifically that in highland Bolivia, women plant potatoes, but in rare instances, if no women are available, men will do so. Potatoes are prepared and consumed in a variety of ways, including roasted, boiled, steamed, or freeze-dried into chuño . Potatoes are a common ingredient in soups and stews in Andean cuisine.In addition to consuming the potato tuber for food, the leafy plant of the potato can be cut and fed to animals . Several varieties of squash/zapallowere cultivated during the prehispanic era in Peru, including pumpkin , butternut squash , and winter squash . The domesticated squashes were derived from separate ancestral species; C. maxima may be derived from a wild ancestor C. andreana, found today in Uruguay and Argentina . Remains of squash seeds have been recovered from Peruvian coastal sites dating to ca. 1800 B.C., and C. moschata seeds have been documented in coastal burials dating to 1100 B.C. . Squashes can be cultivated in a variety of climates, including the tropical desert, subtropics, temperate zones, and tropics, but require good soil fertility with abundant organic material . Aside from their technological uses, squash and gourd fruits are edible when eaten young and consumed in many forms, including stews, compotes, and purees; squash flesh is also pickled, and seeds are roasted or toasted. Squashes have a variety of other uses as well, including ornamental ; medicinal ; and as an antiparasitic agent for livestock. Studies have demonstrated that administering ground squash seeds to livestock has proven effective as a form of parasite control ; it is possible that such a veterinary use could have been used in the prehispanic era as well. A number of fruits were recovered in the five archaeological assemblages; these fruits are actively managed in the Moche Valley today or grow wild in the local vegetation. There are many known uses for each, either as food, beverage, medicine, or dye, which I discuss below. Small seeds of fleshy fruits are less likely to be recovered in archaeological assemblages as they are often consumed in their entirety with the fruit; however, seeds from a fleshy fruits including opuntia , elderberry/sauco , golden berry/aguaymanto , passion fruit/maracuyá , and a member of the genus Prunusare present in the assemblages.

Other tree fruits are present in the assemblage as well, in the form of both seeds and rind fragments, including avocado/palta , guava/guayaba , lucuma/lúcuma , and pacay/pacae . When Andean scholars refer to agriculture, they often discuss field cultivation, of maize, beans, cotton, etc.; however, the process of clearing, cultivating and fallowing fields is also tied to choices made with respect to tree management. Tree crop management was an important part of pre-Columbian farming systems; on-farm tree planting has been documented ethnographically in the Andes , and more broadly in tropical agricultural systems in the Americas . Indeed, fruit trees are cultivated along the edges of fields and along canals in the Moche Valley today, as well as in house gardens . Active tree management produces additional comestible resources for communities, and also can provide an alternative or addition to fuel wood and fodder collected from common forests. Certain fruit trees also had elevated importance in Andean cosmologies, as documented for the Inka . Avocado/paltais a cultivated tree with many varieties, distributed throughout the tropical and subtropical Americas, including along the coast, Amazon, and in interande an valleys. Avocado trees required well-drained sandy soils, and spacing is critical to ensure productive crops; avocados trees should be adequately spaced apart so that they are exposed to full sun. Production begins at 5-15 years, and some trees can produce up to 300 fruits . Cultivated primarily for their edible fruits; avocado fruits are very nutritious. They are high in fiber, antioxidants, and vitamins A, B, C, and E. Avocados have a wide variety of uses aside from their comestible use, from cosmetic to medicinal. The pulp of the fruit can be applied as a face mask, and both the fruit pulp and leaves have known medicinal properties from ranging from antidiarrheal,mobile vertical rack anti-diabetic, to analgesic. The ingestion of great quantities of avocado seeds also can serve as an abortive agent. Furthermore, avocado tree hardwoods can be used to make tools . Guava/guayaba is native to Mexico, Central America, and northern South America and are distributed throughout the tropical Americas. Cultivated in humid and dry climates, guavas can be grown up to 1,200 masl.The fruits are consumed raw, but as guava fruits contain high levels of pectin, present day uses in Peru include preparing the fruit into marmalades, jams, and ice creams . Guavas are rich in dietary fiber, folic acid, and vitamin C; indeed, a single guava fruit contains four times the amount of vitamin C as an orange .

Guava also has some documented medical uses, often in the form of infusions prepared with leaves from the guava tree, to treat a range of maladies from gastritris to conjunctivitis to menstrual cramps . Guava tree hardwoods are also used to manufacture wooden tools . Lucuma/Lúcumatrees are distributed throughout the Peruvian coast and highlands, as well as the highland Amazon; indeed, lucuma trees can be cultivated up to 3,000 masl. Adapted to various soils, lucuma trees are most productive when planted in rows spaced 4-5 m apart, and are suitable for mixed cultivation, as they are good shade trees. Production begins at 4-5 years; one tree can produce some 300 fruits and they produce for more than 60 years . Lucuma trees were cultivated in the prehispanic era , with fruits consumed fresh or dried and ground into powder. Lucuma also possesses a range of medicinalproperties, used to combat anemia, to treat skin infections, and as an antidiarrheal. Lucuma trees also produce good quality hardwoods used for tools and other artifacts . Pacay/Pacae trees can be cultivated on the coast, in the highlands, and in the jungle up to 3,000 masl . Like other members of the Fabaceae family, including common beans and lima beans , pacay trees produce abundant root nodules that fix nitrogen; thus, their cultivation benefits the land by increasing fertility levels. They require year round irrigation so are generally grown near river banks or canals, but they produce in abundance, are tolerant of diverse soils, and are resistant to disease and fire . Referred to as “ice cream bean” for its sweet, edible white pulp, pacay fruit is eaten fresh, and also has known medicinal properties ranging from digestive relief to skin cancer treatment. Pacay hardwoods were also used to make wooden tools . Pacay trees were cultivated widely in Peru during the prehispanic era , and pacay fruits are represented in in the Moche sculptural vessel canon . Other Fruits Elderberry/Saucois native to the Andes , and grows up to 3,000 masl. Requiring deep soil and a lot of water, elderberry plants thrive near irrigation canals. Aside from their comestible uses, elderberries have known magical and medicinal properties, including as an aphrodisiac, purgative, expectorant, antitussive, and diuretic. Juice from elderberry fruits also can be applied as an insecticide . Golden berry/aguaymantois native to Peru and is distributed throughout the coast, highlands, and Amazonian region up to 2,000 masl . Cultivated during the prehispanic era, golden berries can be eaten raw, pressed into juice, or dried, and possess many nutritive properties. Since the colonial era, it has been widely introduced into cultivation into other tropical, subtropical, and temperate areas, including China, India, and Malaysia .

Emission of N2O from soils is an extensively studied environmental process, given that N2O is ‘‘at the heart of debates’’ on several prevalent current issues.Approximately two-thirds of total global emission comes from soils; most of the emission from soils is in turn attributed to agriculture.The intrinsic soil properties most commonly mentioned in research studies and models as controlling emission of N2O are texture, pH, organic matter, and ability to supply inorganic nitrogen.Production of N2O in soil is generally attributed to microbiological processes, and therefore the factors that regulate the activity of N2O-producing microorganisms should be the same factors that regulate N2O production.These controlling factors are generally thought to be well recognized, but as research and related commentary on N2O emission from agricultural soils continue to accumulate, the possible role of iron is rarely considered.This is in spite of its known involvement in enzymatic reactions and non-enzymatic reactions that generate N2O.The connection between iron and N2O may have been neglected because iron has never figured prominently in routine evaluations of soil for agronomic research or practical management decisions.Unlike the other soil properties cited above, iron does not have a direct and immediate bearing on the growth of most crops or on the agricultural suitability of a soil from either a physical or a chemical point of view.When it is considered, this is in instances of suspected plant deficiency or toxicity, not in the context of its potential connection with the nitrogen cycle.In addition, compared to other intrinsic properties, soil iron does not dramatically affect the short-term changes in microbiological activity generally associated with N2O production.For these reasons,dutch bucket hydroponic once interest in N2O began to intensify, the previously reported connection with iron was already out of sight.The intent of our work was to reconsider the potential significance of iron in emission of N2O from agricultural soils.Soils were collected from the top 15 cm in 10 agricultural fields throughout California, and were sieved to 2 mm following collection.

Soil pH was measured in 1 M KCl.Percent clay, silt, and sand were determined by a modified pipet method.Total carbon and nitrogen were determined on ball-milled samples by combustion-GC.Just prior to setting up the experiment, inorganic nitrogen was extracted by 0.5 M K2SO4 and determined colorimetrically.Dissolved organic carbon was determined in the same extract by UV-persulfate digestion.We chose two commonly used, contrasting indices to characterize soil iron: that extractable by acid hydroxylamine , an index of reactive iron minerals; and that extractable by pyrophosphate , representing iron complexed with soilorganic matter.FeA was extracted by shaking 0.8 g soil for one hour with 40 ml 0.25 M hydroxylamine hydrochloride in 0.25 M HCl, followed by centrifugation for 30 minutes at 156006 G.FeP was extracted by shaking 1 g soil with 100 ml 0.1 M tetrasodium pyrophosphate for 16 hours, followed by centrifugation for 30 minutes at 156006 G; further centrifugation did not result in any difference in measured iron concentration, indicating that all fine iron colloids had been removed, an important consideration when using this extractant.The concentration of iron in all extracts was determined color imetrically; pyrophosphate extracts were neutralized by a small addition of HCl prior to this determination.All analyses of soil properties were performed in duplicate.These properties are reported in Table 1.As stated above, the properties most commonly believed to control emission of N2O from agricultural soil include texture, pH, organic matter, and the inherent ability of the soil to release inorganic nitrogen.These are intrinsic properties which are not abruptly altered by environmental conditions; in contrast, our treatments were designed to manipulate the most common temporary extrinsic changes that influence N2O production: water content, fertilization, and organic amendments.Since these can vary across a range of values, we necessarily limited our choice of treatments.Fertilizer and compost were either withheld or added at a rate typical of agriculture in California, and two water contents were chosen according to the range expected in agricultural soils.Field capacity, the amount of water a soil can retain against gravity, was chosen as the upper reference point.This is not uncommon, as soil moisture can temporarily exceed field capacity following irrigation or rainfall events.In practice we used water holding capacity to represent field capacity.As a contrasting treatment, we chose 50% WHC.This is near the permanent wilting point of most soils, and it is not likely that soil moisture will fall below this in the field except during unmanaged dry seasons.

Although many intermediate values could have been selected as treatments, we chose to use both ends of a typical spectrum of values in order to present a broad yet concise study.Prior to set-up, WHC was determined as follows: a soil sample was placed into a funnel lined with filter paper, which was then placed into a beaker of water such that just the tip of the funnel was always in contact with water; after the sample ceased to take up water, the sample was allowed to drain, and the moisture content measured.To begin the experiment, the equivalent of 50 g dry soil was placed into cups, which were themselves placed into larger jars containing a small amount of water to avoid desiccation.The larger jars were sealed with lids containing a small foam plug to allow gas exchange with the atmosphere.To imitate the timing typical of agricultural operations, 2 g finely ground finished green waste compost were mixed with the soils and incubated at 40% WHC for seven days.Treatments not receiving compost were similarly incubated.Following this preincubation, each soil received a fertilizer addition according to treatment: none, ammonium sulfate, or potassium nitrate.The amount of nitrogen added was 100 mg kg21 soil, corresponding approximately to a field rate of 150 kg ha21.Fertilizer solution was sprayed onto the soils to reach a water content of 50% or 100% WHC, depending on the treatment.For each soil there were three replicates per treatment.Samples were incubated for 14 days at 22 degrees C.Samples for N2O analysis were taken on days 0, 1, 2, 3, 5, 9, and 14 following addition of fertilizer.The jars containing the soil cups were closed with lids containing septa and allowed to stand for one hour.Gas samples were taken at 0, 30, and 60 minutes after closure and transferred to evacuated gas sampling vials.N2O concentration was determined by gas chromatography-ECD detection.At each sampling date, the rate of N2O emission was determined by linear interpolation of the 0, 30, and 60 minute measurements.Cumulative N2O emission over the course of the incubation was calculated using these data, taking the flux measured at a given date to be the average flux for the interval represented by that date.To identify the soil properties that most strongly explained N2O emission in each experimental treatment, we studied the data using partial least squares multivariate analysis, a form of structural equation modeling.This tool is particularly suitable when the number of predicting variables is greater than the number of observed variables, when multicolinearity is expected among predicting variables, and when multivariate normality can not be assumed.PLS ranks the predicting variables by importance based on linear regression models that project the predicting variables and the observed variables to a new, multivariate space.

Prior to subjecting the data to PLS analysis, predicting variables and the observed response were standardized by centering and scaling the data to have a mean of zero and a standard deviation of one.This ensures that the predicting variables are ranked based on how much of the variation is explained when all variables have the same weight.Although correlations among variables are possible, especially in studies that involve soil properties, this does not change the interpretation given by PLS, which depicts the relative importance of each variable separately, independently of intrinsic links between variables.Nevertheless, a correlation matrix is presented as an aid in understanding the relationships between the soil properties used in our study.Following the exploratory PLS analysis, linear regressions between iron and N2O emission were calculated using unweighted, untransformed data, and were considered significant enough to report at P,0.1.All statistical analyses were performed using JMP 10 software.The results of the PLS analysis are shown in Figure 1, where each soil property is ranked according to its ability to explain cumulative N2O emission across all soils.This ranking was performed for each of the 12 different treatments studied.In five of these treatments, iron ranked higher than any other measured soil characteristic in explaining observed emissions.In four additional treatments,dutch buckets system iron was among the top four predictors.As a complementary approach to further investigate the relationship between iron and N2O emission, simple linear regressions were calculated in which N2O data were compared against FeP and FeA.Whereas PLS was used to arrange a suite of soil properties according to their ability to explain N2O emission, regressions indicate, by the value of r2 , how much of the variability in N2O emission can be explained by a single property; regressions also indicate the direction of the effect and degree of importance of the effect.In most cases, a significant relationship between N2O emission and a given variable can be expected when that variable is ranked highly by PLS.In certain cases, however, a variable ranked highly by PLS may not necessarily yield a significant linear relationship when that variable is considered apart from the other variables; conversely, certain treatments in which a variable is not ranked highly by PLS may nonetheless yield a significant regression.The primary reason for this occasional discrepancy is the nature of the PLS procedure: by considering all predicting variables together, new predictors are generated which are composites of the original variables.Table 3 reports the results of the regressions for treatments that showed a significant relationship between N2O emission and either iron index.Despite a dataset of values for N2O emission which spanned more than three orders of magnitude across soils, several notable connections between iron and N2O emission emerged.FeP was significantly related to N2O emission in four treatments, in which it explained between 16 and 62 percent of the variability, with a positive slope in all cases.This influence was greatest under 100% WHC when ammonium was present and compost was absent.

Such a condition may be reasonably expected on occasion, since most fertilizers supply ammonium, and since this may occur close in time to irrigation or rainfall.In this treatment, an increase in FeP of 1 mg kg-1 corresponded to an increase in cumulative emission of 11.9 ng N2O-N g21 soil during the course of the incubation.Like FeP, the connection between FeA and N2O emission was also significant under several different conditions.Unlike FeP, however, which was positively related to N2O emission, FeA was always negatively related to N2O emission.There was no treatment in which both iron indices were significantly related to N2O emission.Considering that FeP and FeA bear almost no relationship to each other , this difference in behavior suggests that these two indices indeed reflect two forms of iron that differ in reactivity.Also notable in Table 3 is the effect of compost in fertilized treatments: the observed negative association between N2O emission and FeA occurred only in the presence of compost, while the stimulating effect of FeP was observed only without compost.The contrasting relationships of FeA and FeP with N2O emission could be due to differences in the reaction of either form of iron with nitrogen compounds in the soil matrix.For example, hydroxylamine is produced from biological oxidation of ammonia, and is known to generate N2O upon chemical reaction with iron.Reaction with FeP versus FeA, or locally high concentrations of either hydroxylamine or iron, could lead to more or less N2O compared to other reaction products.The ability of aerobic microorganisms to acquire iron can likewise depend on its chemical nature, consequently influencing the amount of reactive compounds produced or consumed through reactions that use iron-dependent enzymes.As soil water content increases, reducing conditions may develop, especially when the depletion of oxygen is accelerated by easily metabolized organic matter.The chemical nature of existing iron may determine the ease with which it is reduced to iron in anaerobic microsites.This will in turn control its participation in other reactions that produce N2O, such as chemodenitrification, which includes the abiotic reduction of nitrite to N2O by iron.Chemodenitrification can also produce other gases, and the relative amount of N2O released may be affected by the form of iron present.