September 2023 – Nature Ecrogrow

What might be the implications of MCE technologies in a broader sense?

The climate prediction data produce a point estimate of chill portions for each year in 2020-2040. For a given set of model parameters and climate predictions for 2020-2040, the model is solved numerically twice for each year in this range. The consumer, grower, and welfare gains are calculated for each year using these two simulations. Using a discount rate of 5%, I can calculate the Net Present Value of the MCE gains in 2019. For each scenario, I run this procedure for 100 “independent draws” of 2020-2040 prediction paths. For each one, an entire simulation is run to produce an NPV of the gains. I report the Expected NPV , the mean of this distribution, and standard errors around it. More details on the numerical solution of the model can be found in appendix A.3.Before I present the simulated welfare gains, there is one more piece in the puzzle. The calibrated model is set with 2016 acreage . Pistachio acreage through 2020- 2040 is likely to be different, and most likely higher than that. However, the model does not include endogenous growth of planted and harvested pistachio acres. To give some bounds on the expected gains, I run the simulations with four different acreage growth scenarios, each specifying a different pistachio acreage growth path until 2040. All scenarios assume some growth path until 2030, when acreage stabilizes and stays fixed through 2040. The first scenario is “No Growth”, meaning that 2020-2040 climate predictions are cast over the 2016 acreage. This should give a lower bound for gains, as acreage is predicted to grow and not shrink. The second scenario is “Low Growth”, which sets the yearly growth of harvested acres until the year 2022 at 9.6%, the average rate since 2000,macetas de plastico 30 litros and then sets zero growth . The growth until 2022 is attributed to currently planted but not yet bearing acres.

This assumes that we are on the brink of a dynamic equilibrium in growth, and therefore no new acres will be planted in California. This scenario should give estimates that are higher than the “No Growth” scenario, but still rather conservative. The third scenario is “High Growth”. This one sets the growth rate until 2022 at 14.6%, the average rate since 2010, and then lets pistachio acreage follow the historic path of almonds in California . That is, the growth rate of almonds when they had the corresponding pistachio acreage. This very optimistic growth prediction makes the “High Growth” scenario the upper bound for the gains from MCE. One potential concern with acreage growth is that growers might switch new acreage to unaffected counties, or plant more heat tolerant varieties. For this, the “High North” scenario takes the high growth rate, but all new acreage harvested from 2023 is located in an imaginary “North” county, where chill damages are virtually zero. Note that planting in the unaffected north has the same effect on supply as planting a more heat tolerant variety near the existing locations . This last scenario is, in my opinion, the most plausible in terms of MCE gain magnitudes. A summary of the growth rates is depicted in Figure 4.2. In all scenarios, demand grows by the total rate of acreage growth. MCE could help overcome a climate challenge for California pistachios. I model the market and assess the potential welfare gains from a reflective coating technology that lowers the effective temperatures in pistachio orchards. The expected NPV in 2019, for the gains from this technology between 2020 and 2040, is predicted to be around $2.7-3.5 billion. These come from consumer surplus gains, as the total gains for growers in the main specifications are negative. The latter result is not unheard of in agricultural settings, where a negative supply shock can actually increase grower profits. For example, Carter et al. show that the 1979 labor strikes in California actually increased revenues and profits for lettuce growers.

The simulation results shows the flip side of the coin: solving a supply shock can lower grower profits. While less tangible than actual registered profits, consumer surplus gains are real economic gains enjoyed by the public. This point holds even when discussing a narrower welfare framework for California alone. Part of the modeled gains in consumer surplus are enjoyed elsewhere, as the majority of pistachio output is currently exported. However, export demand is usually considered more elastic than domestic demand, making the share of local consumer surplus gains disproportionate to the share of local consumption. At a share of 1/3 of total consumption, let us assume that Californians still enjoy half of the consumer surplus gains from MCE . Adjusting Table 4.1, the total welfare gains in California are strictly negative when the demand is unrealistically inelastic, εD = −0.5, and strictly positive for more realistic demand assumptions . The scope of consumer surplus gains brings us to the potential gains from public investment in R&D for MCE solutions. With social returns from investments largely exceeding private ones, this type of research is a good candidate for prioritizing in public research fund allocation . The case for public research is made stronger by the fact that there seems to be little private incentive to invest in MCE, at least in this case. I see MCE technologies mostly as an adaptation of existing ones to solve a climate problem. Therefore, innovations in the field would be hard to make proprietary by the innovator. Moreover, innovators are likely to come from the industry: a large growing firm would have the resources and access to enough pistachio acreage to run experiments and develop new MCE solutions. But if this firm sees that a world with MCE is worse, why invest in innovation? Adding market power to the equation makes an even stronger potential case for public R&D: the total welfare gains are higher, and the incentives for innovation could be even lower.

One could imagine, with further agronomic research, other MCE technologies applied to other fruit and nut crops, and even for annuals such as corn or soybeans. Of course, these are less profitable than pistachios, but they face similar challenges, and MCE solutions are not necessarily very expensive. Other implications could be with the distribution of climate change damage incidence. Technologies might only be available to growers in countries better off financially, further exacerbating international income disparities. An interesting potential for MCE technologies could be in accelerating the transition of agricultural practices closer to the poles, sometimes referred to as the “crop migration” . For example, MCE solutions for frost could accelerate the expansion of viticulture to higher latitudes. The simulation based valuation methodology in this chapter has its caveats. Modeling supply and demand as linear is obviously a simplification. The assumptions on growth and distribution of acreage are based on past growth patterns, and might not reflect unexpected future changes in market conditions. The future chill predictions are in line with other predictions by climatologists, yet might fail to materialize. Nevertheless, by choosing various scenarios, basing the parameter ranges in the literature, and choosing conservatively when possible, I believe to have gotten a reasonable range for the potential gains from MCE in California pistachios. They are in the low billions for a crop of secondary importance to California agriculture. I believe this shows a great potential of MCE technologies for climate change adaptation in general.South Asian agriculture is a global ‘hotspot’ for contemporary and future climate vulnerability. Further, 1.7 billion people live in South Asia,cultivo hidroponico and by 2050, that number is expected to rise to 2.4 billion. Although the region enjoys high economic growth, it suffers from extreme poverty, undernourishment and the deterioration of natural resources1 . South Asia has more than 42% of the world’s poor , about 21% of the population is undernourished, and more than 41% of children are underweight2 . Rapid population growth will increase the demand for cereals by about 43% between 2010 and 2050. Meeting this projected need is doubly challenging considering 94% of the land suitable for farming is already in production and 58% of agricultural areas face multiple climatic hazards such as water shortage and extreme heat stress. The present situation is anticipated to worsen with climate change, with rising temperatures and changing monsoon rainfall patterns projected to cost India 2.8% of gross domestic product. Although global crop productivity has more than doubled during the past decades, negative impacts on environment, biodiversity, soil quality and air quality are common. Future food production in South Asia requires new management approaches that are efficient and climate smart to make tangible contributions to the United Nations’ Sustainable Development Goals . Conservation agriculture has emerged as an alternative to an inefficient tillage-based conventional agriculture. CA is an ecosystem approach to regenerative sustainable agriculture and land management based on three interlinked principles: continuous no or minimum mechanical soil disturbance, permanent maintenance of soil mulch and diversification of cropping system , along with other complementary good agricultural production and land management practices. CA helps in managing agroecosystems for improved and sustained productivity, increased profits and food security while preserving and enhancing the resource base and the environment.

It is estimated that a partial CA-based system is spread to over 2.5 millionha in South Asia . Numerous favourable impacts have been reported in the global literature on CA, including for crop yields, resource use efficiencies, timeliness of cropping practices, soil quality and ecosystem services. Nevertheless, a meta-analysis of global yield data from 48 crops across 63 countries reported limited yield gains with full CA or with some components of CA14, a result that has drawn into question the wisdom of making CA a sustainable intensification priority for agricultural development programs. Although the benefits derived from CA have been broadly questioned, there has been gradual increase in adoption of CA over time. Zero-tillage wheat has been adopted on a significant area in the rice–wheat system of the northwestern Indo-Gangetic Plains and in the Eastern Gangetic Plain with positive impacts on wheat yield, profitability and resource-use efficiencies. The national governments in South Asia are actively promoting CA to address sustainability problems. Although numerous on-station and on-farm studies have been carried out during the past two decades to evaluate CA in South Asia, a systematic synthesis of evidence is lacking. To clarify the regional potential of CA as a full package or combination of its components in South Asia, this study presents a comprehensive meta-analysis on data from on-station and on-farm studies in South Asia’s dominant cereal-based cropping systems. Performance parameters considered in the analyses included grain yield, protein-equivalent yield , water use efficiency, cost of cultivation and net economic return, and emission of GHGs and global warming potential . Results are contrasted with conventional best practices and contextualized with respect to potential contributions to the SDGs related to poverty, hunger, health, climate action and clean water.The first-stage analysis showed improvements in all the measured performance indicators . Compared with conventional practice, CA had 4.6% higher grain yield, which was very similar to PEY. A 14.6% increase in water use efficiency was observed with CA. The net economic return increased by 25.6% . Segregating on-station and on-farm studies revealed higher CA responses in the former than in the latter. On-station crop yields increased by 11.1% and on-farm by 4.7%, while water use efficiency was 29.3% and 9.3% higher in the on-station and on-farm studies, respectively. However, the changes in the economic return in on station and on-farm studies were similar. Analysis based on cropping system revealed that the maize– wheat system had the highest grain yield increase with CA , followed by rice–wheat and rice–maize . The ‘others’ category also demonstrated improvement in grain yields . Similar trends were obtained in on-farm studies. In on-station studies, however, all cropping systems showed no change except maize–wheat, which had a 5.8% higher yield with CA . The PEY followed a similar trend as in grain yield . Water use efficiency with CA improved by 28.5% in the maize–wheat system, which was higher than in rice–wheat , rice–maize and other crop systems . Water use efficiency in rice–wheat was higher in the on-station studies compared with the on-farm trials, while the rest of the cropping systems could not be compared between on-station studies and on-farm trials due to nonavailability of data in one or the other .

Agronomists and stakeholders in California pistachios recognize this as a threat to this valuable crop

Anecdotal yield losses due to low chill have happened on relatively small scale and passed undetected in the county-level statistics, especially when only one or two chill measures per county were considered. In this case, while the resulting curves are very similar, I find the structural approach more convincing. First, it has a smaller confidence area, and therefore seems more precise. Second, a polynomial of low order will not approximate the process described by agronomists very well. However, estimating higher order polynomials results in estimates that are not statistically significant. The implications of my estimates for pistachio yields are depicted in the lower half of Figure 3.1. The bottom left panel shows the effects on the 1/4 warmest years in 2000– 2018. They are mostly between 10-20% yield decline. These rates are easy to miss due to substantial yield fluctuations in pistachios. What do these estimates mean for the future of California pistachios? Prediction of yield effects for the years 2020–2040 are depicted in the bottom right panel, again for the 1/4 warmest years in the 2020-2040. They show substantial yield drops, which could amount to costs in the hundreds of millions of dollars. Chapter 4 in this dissertation explores the potential gains from a technology that could help deal with low chill in pistachios: applying kaolin clay mixtures on the dormant trees to block sunlight. Thee expected net present value of this technology is estimated at the billions of dollar in economic gains. Considering my results, there may be significant gains from using these technologies even in warmer years today. Concluding this chapter, I want to stress the fact that even in the era of “big data” in agriculture, data availability is still a challenge when estimating yield responses to temperature in some crops, especially perennials and local varieties.

Weather information required for assessing potential damages and new technologies might not always be available for a researcher. This chapter develops a methodology to recover this relationship,raspberry grow in pots using local weather data and techniques for dealing with aggregated observations. I use this setup to empirically assess the yield effects of insufficient chill in pistachios, recovering this relationship from commercial yields for the first time in the literature. I then look at the threat of climate change to pistachio production in southern California. As winters get warmer, lowering chill portion levels are predicted to damage pistachio yields and disrupt a multi-billion dollar industry within the next 20 years. These results were made possible by using precise local weather data, applying relevant statistical methods, and using agronomic knowledge in the modeling process. This approach for information recovery from a small yield panel, with limited useful variability at first sight, could be useful for other crops as well.In the introduction chapter, I discuss the nature of temperature challenges posed by climate change. The rising average temperatures, according to the empirical literature, might not be the major source of potential loss. Rather, it’s the elongating and fattening temperature distribution tails that would be responsible for much of the damage. Could there be a way for farmers to target these tails directly? If so, such technologies could have potential uses for climate change adaptation. It so happens that farmers already deal with temperature extremes, and are capable of tweaking the tails of temperature distributions to avoid losses. The introduction already discussed “air disturbance technology”, basically large wind generators, used to deal with some types of frosts . Solutions for right side temperature tails exist as well.

Of course, shading plants using nets or fabric is an existing practice, but these technologies are costly and not very flexible. However, other products that reflect sunlight and lower plant exposure to excess heat are available on the market. Perhaps the most common ones are based on a fine kaolin clay powder, which is mixed with water and sprayed directly on plants to form a reflective coat, sometimes referred to as a “particle film”. These products have been commercially available since 1999, and are shown to effectively lower high temperature damages by literally keeping plants cooler . Some manufacturers report a canopy temperature reduction of up to 6oC when using their products. Spraying of this mix requires special rigs and equipment, but the costs are reasonable, and far lower than setting up shading in the form of nets . This technology can be thought of as cheap, disposable shading. Surprisingly, even though kaolin clay has been used by farmers to deal with other problems, less related to climate change , I could find no economic literature discussing this technology. As with the case of air disturbance technology, these types of technologies have mostly been ignored by economists. One reason for this gap in the literature could be that economists have not yet realized that these individual products and practices share a common conceptual framework: they are tweaking temperature distribution tails, while leaving the main probability mass untouched. This is an approach I call “Micro-Climate Engineering” . These are relatively small interventions in temperature distributions, limited in space and time, which aim to avoid the nonlinear effects of the extremes. Farmers know the available technologies for MCE and use them regularly, but their potential applications for climate change have not really been explored. The concept of MCE could be very important for climate change adaptation in agriculture, especially when considering the role of extreme temperatures on predicted future losses. MCE solutions, where feasible and profitable, could assist in preserving current crop yields and delaying more costly adaptation strategies. This chapter sets to explore the concept of MCE in general, and assess the gains from MCE in California pistachios as a case study. Specifically, pistachios are threatened by warming winter days, which could threaten existing acreage within the next twenty years .

This challenge stands out in the existing literature in three ways: first, while much of the climate change literature focuses on annual crops, pistachios are perennial. This means that the opportunity cost of variety switching are higher. Second, the challenge does not occur in the “growing season”, but on the winter months when trees are dormant and seemingly inactive. This emphasizes the importance of climate change effects year round, rather than just in the spring and summer. Third, the challenge stems from a biological mechanism that is not heat stress. Heat stress is perhaps the most obvious process by which rising temperatures can have adverse effects on yields, and by far the most studied in the economic literature on climate change. However, other biological mechanism are affected by weather as well, and can cause substantial yield losses. This paper incorporates agronomic knowledge on bloom disruption due to increased winter temperatures, a mechanism that is relatively unexplored in the economic literature. Scientists at the University of California Cooperative Extension have been experimenting with kaolin clay applications on pistachios, and the results seem promising . This could mean a great deal to growers and consumers. This chapter analyzes the potential economic gains from this MCE application in California pistachios. Introduced to California more than 80 years ago, and grown commercially since the mid 1970’s, pistachio was the state’s 8th leading agricultural product in gross value in 2016, generating a total revenue of $1.82 billion dollars. According to the California Department of Food and Agriculture , California produces virtually all pistachio in theUS,square plastic pots and competes internationally with Iran and Turkey . In 2016, five California counties were responsible for a 97% of the state’s pistachio crop: Kern , Fresno , Tulare , Madera , and Kings . Since the year 2000, the total harvested acres in these counties have been increasing by roughly 10% yearly. Each increase represent a 6 – 7 year old investment decision, as trees need to mature before commercial harvest . The challenge for California pistachios has to do with their winter dormancy and the temperature signals required for spring bloom. I discuss the dormancy challenge and the Chill Portion metric in Chapter 3. It is worth noting that in fact, for the areas covered in this study, chill portions are strongly correlated with the 90th temperature percentile between November and February, the dormancy season for pistachios. The correlation is very strong, with a goodness of fit rating of about 0.91. In essence, insufficient chill is a right side temperature tail effect, comparable with similar effects in the climate change literature. Chapter 3 estimates the yield response of pistachios to CP. Substantial losses are predicted below 60 CP.

Compared to other popular fruit and nut crops in the state, this is a high threshold , putting pistachio on the verge of not attaining its chill requirements in some California counties. In fact, there is evidence of low chill already hurting yields . Declining chill is therefore considered a threat to California pistachios. Chill in most of California has been declining in the past decades, and is predicted to decline further in the future. Luedeling, Zhang, and Girvetz estimate the potential chill drop for the southern part of San Joaquin valley, where virtually all of California pistachio is currently grown. For the measure of first decile, i.e. the amount of CP attained in 90% of years, they predict a drop from an estimate of 64.3 chill portions in the year 2000 to estimates ranging between 50.6 and 54.5 in the years 2045-2060.Together with increasing air temperatures, a drastic drop in winter fog incidence in the Central Valley has also been observed. This increases tree bud exposure to direct solar radiation, raising their temperature even further . The estimates cited above virtually cover the entire pistachio growing region, and the first decile metric is less useful for a thorough analysis of pistachios. I therefore need to create and use a more detailed dataset, in fact the same one described in Cahpter 3. Figure 3.1 shows the geographic distribution of chill and potential damage in the 1/4 warmest years of observed climate and predicted climate . While not very substantial in the past, these losses are predicted to reach up to 50% in some regions in the future.This section develops a model to assess the gains from MCE. This is a single year, short run market model, solving for price and quantity under different winter chill realizations. Equilibrium price and quantity are used to calculate welfare outcomes such as grower profits, consumer surplus, and the total welfare. For each realization, the model is solved twice: once with an option to use MCE, and one without it. The differences in welfare outcomes under the same conditions, with and without MCE, are the welfare gains from MCE. Note that in both cases, agents act optimally. MCE gains are therefore to be interpreted as the difference in welfare measures between a world with MCE and a world without it. I abstract from a benchmark with increased storage, which could theoretically alleviate inter-year fluctuations. Pistachios are usually stored for up to one year . The potential loss rates in a bad weather year are significant. Coping by storage in a meaningful way would require multi-year, double digit storage rate, which seems technically unfeasible.MCE could help overcome a climate challenge for California pistachios. I model the market and assess the potential welfare gains from a reflective coating technology that lowers the effective temperatures in pistachio orchards. The expected NPV in 2019, for the gains from this technology between 2020 and 2040, is predicted to be around $2.7-3.5 billion. These come from consumer surplus gains, as the total gains for growers in the main specifications are negative. The latter result is not unheard of in agricultural settings, where a negative supply shock can actually increase grower profits. For example, Carter et al. show that the 1979 labor strikes in California actually increased revenues and profits for lettuce growers. The simulation results shows the flip side of the coin: solving a supply shock can lower grower profits. While less tangible than actual registered profits, consumer surplus gains are real economic gains enjoyed by the public. This point holds even when discussing a narrower welfare framework for California alone.

The Arnold series is also considered one of the older soils in the slough

The Arbuckle series contains gravel in banded patterns suggesting the edge of a flood plain subject to major high energy events alternating with low energy events. The soils are well drained, formed on terraces in semi-consolidated alluvium derived from igneous and sedimentary rocks. The soils are used for irrigated field crops, pasture, and dryfarrned grain. The Elkhorn and Elkhorn variant series are among the oldest series in the entire slough. They are derived from the Aromas Red Sands and have a well developed argillic horizon. The soils are on marine terraces and dune-like hills, underlain by weakly consolidated sandy sediments or ferruginous sandstone. Permeability is moderately slow, although the Elkhorn Variant is slow. The argillic horizon has a low porosity, thus water tends to flow laterally in contact with this horizon. The soils are used for Brussels sprouts, strawberries, artichokes, broccoli, annual pasture, hay, or rangeland.It is formed on hill and uplands in old marine sand dunes or in material weathered from soft sandstone. These soils are somewhat excessively drained. There is no argillic horizon. They are most often used for range, wildlife habitat and watershed, with some orchard, row crops, and Christmas trees. We measured seven sediment fans at the base of strawberry roads and paths around the Central Marsh, and estimated they contained 3,745 ft.3 of deposited sediments. The Central Field is approximately 8.8 acres, for an average of 426 ft3/acre,grow bag for tomato deposited sediments. The sediment fans we measured consisted mostly of the heavier sand fraction. Any eroded clays and soil organic matter were not deposited in the fans and were likely carried into the marsh, possibly along with some portion of the heavier sand fraction. We initiated sampling of deposited sediment fans during winter 1993-1994 as a survey technique to help us gain a better understanding of the contribution of surface run-off to nutrient loading in the marshes.

Sediment transport from the strawberry fields occurs whenever there is rain or irrigation, and the amount of sediment carried depends on soil moisture content, time since last rain or irrigation event, rate and total amount of rainfall, time since cultivation, size of berry plants, plus the type and extent of erosion control practices implemented by the growers. While much of the run-off and the finer fractions of suspended sediments ultimately make their way to the marshes, a substantial portion of the coarser sediments are deposited in fans at the bases of field roads along the marsh margins. However, because of the relationships of N and P compounds to water and clay particles, our estimates of the nutrient load in deposited sediments are surely very low in relation to the total amounts of these nutrients entering the marshes. Our results show that nutrient loading in transported sediments is highest at the beginning of the winter rainy season for N03, NH4, and labile P. We did not collect samples from sediment fans deposited after the initial rain events of the season . But based on these numbers from slightly later in the season, we hypothesize that nutrient loading is highest during the first rain events after planting. There are several reasons for this. One is the presence of fertilizer nutrients in freshly cultivated and fumigated soils in the absence of plants with big enough root systems to take up those materials. Establishment of the plants and increased nutrient uptake later in the winter when the later samples were collected may account for decreased levels of N and P in sediments at those times. Enhanced levels of N and P in early winter run-off may also originate from a soil reservoir of fertilizer-applied nutrients applied in years past which are made available by the turning under of the crop and the intense cultivation of the soil prior to fumigation and planting. Lower levels of sediment Nand P later in the rainy season may also reflect a net movement of these nutrients into the wetlands. The macro-vegetation of the mudflat zone consisted of blue green algae, Enteromorpha spp., and Rupia maritima . Blue green algae formed extensive floating mats at three of the four sites. Enteromorpha, not yet identified to species, also formed floating mats and was only absent at one site. Ruppia, an aquatic herb, was present in the Central Marsh but only abundant in the southern marsh. Vegetation in the mid-Pickle Weed zone was dominated by Salicornia, but there were less common species present.

The estimated cover in the transects was 100% Salicornia. There was some variability in the height of Salicornia between sites, but the color was consistently green . Other species noted in this zone included: Atriplex leucophylla , Cuscuta salina, Frankenia grandifolia, Jaumea carnosa, Distichlis spicata, and Elymus sp. The transects through the marsh-field border found a gradient from salt marsh species dominated by Salicornia virginica, Distichlis spicata, and Cuscuta salina to a more species-rich border flora with a maximum of 14 species. The species found are typical of wetland-upland transition zones along the central California coast. The coast line of California contains several distinct vegetation types which are related to the topography, hydrology, soil type, latitude, historical land use patterns, and disturbance regimes. The Azevedo Ranch is in the midst of five vegetation communities: Coastal salt marsh, California annual grasslands, maritime chaparral, north coastal scrub and live oak woodland. The marshes harbored a restricted fauna, relative to the fauna found in the adjoining slough . The South Marsh showed the lowest abundance and diversity, with almost no living macrofauna collected from the benthos. This marsh undergoes the most dramatic changes in water chemistry during the year . In addition, the sediment in the central portion of this marsh was completely anoxic. The Central Marsh likewise showed few infaunal invertebrates. This may also be a reflection of the changeable water quality and anoxic sediments. The North Marsh showed the greatest abundance and diversity infaunal invertebrates of the three Azevedo marshes. This is consistent with the greater flushing of this marsh with tidal water. The distribution of infaunal invertebrates within the three marshes tracks the relative degree of disturbance in each. The least flushed, most disturbed marsh showed no infauna while the largest, best flushed and least disturbed marsh showed the greatest diversity. All of these marshes exhibited a restricted fauna relative to the control pond on the Reserve. Future sampling will examine more of the seasonal changes associated with these ponds and will work to link land use practices with the health of the infauna. The 1 acre South Marsh is the smallest of the three and is cut off from tidal exchange . It has experienced the greatest degree of filing from the adjoining agricultural operations and is surrounded by the smallest buffer of salt marsh. This pond had a growth of Ruppia maritima in July, 1992 that was heavily encrusted with consolidated sediment, perhaps cemented by a bacteria or protozoan. This mat of Ruppia formed a false bottom in the pond above which were pupae of the brine flies and corixid beetles. The underlying sediment was completely anoxic and no living infauna were retrieved from the cores in 1992. The summer 1993 samples contained one oligochaete and several corixid beetles. Again,grow bag for blueberry plants the sediments were completely anoxic, although the Ruppia canopy was not present.

The Central Marsh is 4.1 acres in extent and is intermediate in size and disturbance . The central pond is blocked from tidal action by high culverts and by a low berm across the mouth of the marsh . This marsh also receives direct freshwater input during the rainy season from a culvert draining an agricultural pond above the road. Sediments in this pond were oxidized on the surface, but anoxic a few millimeters below the surface. The infauna reflected these difficult conditions and few species were recovered from either station on either sampling date. The North Marsh is the largest of the three at 10.1 acres . It is connected to the main channel of the slough through two culverts, one at either end of the marsh. This marsh receives the most tidal flushing, though the central portions of the marsh are not well flushed. In all cases, the North Marsh showed the greatest number and diversity of infaunaI species of the three Azevedo marshes. Samples taken in July 1993 showed an absence of many of the soft-bodied species collected in October of 1992. In addition, the presence of a podocopid ostracod in July was notable. Many dead ostracods and shells were recovered from these samples. In some areas, evidence of anoxic waters and sediments was observed, and dead ostracod shells found. The control pond on the National Estuarine Research Reserve served as a contrast to the Azevedo marshes. It is more fully flushed, has never been cultivated, and is undisturbed relative to the Azevedo marshes. Infaunal samples showed greater species diversity in this pond relative to the Azevedo marshes. The invertebrate community in the control pond was more similar to that found in the main channel of the slough than the Azevedo marsh .community. Methyl bromide is a soil fumigant of environmental concern because of its high potential to deplete stratospheric ozone . A treaty signed by 160 nations of the United Nations Environment Program regulates the stepwise decrease of MeBr consumption to a complete phase-out by January 2005 for developed countries and by 2015 for developing countries . The stringent regulations limiting the use of MeBr prior to its complete phase-out stimulated the search for alternative fumigants because soil fumigation remains a central tool in strawberry production. For the past 45 years, preplant fumigation of agricultural soils with a combination of MeBr and chloropicrin has been a reliable and effective tool to control soil borne pathogens, nematodes and weeds in many vegetable, fruit, nuts and nursery crops worldwide. The irritant compound CP is added to the odorless MeBr as a warning agent to reduce the risk of accidents during soil fumigation and because of the synergistic biocidal effect of these two chemicals on soil pathogens . The elimination of MeBr could severely impact growers and farmers in the United States and the Mediterranean region . In continuous strawberry production systems, the soil may host many deleterious nematodes and pathogens such as Phytophtora cactorum, P. fragariae, Verticillium dahliae and Colletotrichum acutatum. In California, where 80% of US strawberries are grown, MeBr + CP combinations effectively control wilt disease , thus playing a crucial role in commercial strawberry production. Currently, there are several available alternatives to MeBr, including an emulsifiable concentrate of CP and 1,3-dichloropropene . Applied alone, CP has high biocidal activity against fungal pathogens but is not as effective as MeBr against weeds and nematodes. Another viable alternative is 1,3-dichloropropene , which is an effective nematicide but has relatively low activity against fungi and weeds . To broaden its biocidal activity, 1,3-D can be combined with chloropicrin as found in various combinations such as InLine . In addition, several experimental chemical alternatives are being studied for their efficacies against pathogens and pests. Iodomethane can be as effective as MeBr, and it is not as likely to deplete ozone because Midas is photolyzed before it reaches the stratosphere . The dilution of Midas with CP can decrease costs for this fumigant and increase efficacy due to synergy with CP . Another experimental chemical alternative is propargyl bromide , which was developed during the 1960s. Although, PrBr demonstrated potential as a viable MeBr replacement it was never registered due to its highly explosive character . With the development of a stabilized formulation of PrBr, research interest in this compound as a soil fumigant has increased recently. Studies have been conducted to determine the biological degradation of various fumigants in soil and their efficacies against soilborne pests and weeds relative to MeBr + CP combinations . Fumigants are among the pesticides with notable effects on soil microorganisms because of their broad biocidal activity . The high biocidal activity of fumigants may cause a “biological vacuum” and increase pathogen re-colonization. Kandeler et al. suggested that the composition of the microbial community strongly affects the potential of a soil for enzyme-mediated substrate catalysis. Consequently, changes in microbial diversity in fumigated soils may also reduce microbial functionality.

The system boundary covers both direct and indirect emissions associated with crop cultivation and harvest

Estimates of the ratio of marginal to average yield for US corn based on different methods range from 47 to 82 % . This range is consistent with estimates on the global scale . In our analysis, we test how different MtA yield ratios affect ethanol’s CPT. We also identify the best scenario for CRP land with comparable fertility because the CRP program can sometimes retire highly productive land . For the carbon debt caused by CRP land conversion, we use the field measurement by Gelfand et al. , estimated at 68 Mg CO2e ha−1, with the assumption that no-till practices are used for corn farming after land conversion. This estimate is similar to that by Fargione et al. for CRP land conversion, i.e., 69 Mg CO2e ha−1. Following Fargione et al., 83 % of the total carbon debt is allocated to ethanol and 17 % to coproducts, primarily distiller grains with solubles , based on their economic values . As discussed in the Introduction section, a number of approaches to accounting for emission timing effects in LCA and carbon accounting are reported in the literature with various rationales. These approaches are referred to as dynamic characterization in this paper. Dynamic characterization uses temporally specific emissions and characterization factors instead of using time-integrated life cycle inventory and characterization factors . In general, emissions and characterization factors are calculated for each annual time-step and summed up to produce a cumulative impact over a certain period of time. Just like any other characterization methods, dynamic characterization approaches are not free from subjective choices. In this study,grow bag we select 100 years as the time horizon, and following the approach by Levasseur et al. , we then calculate the cumulative radiative forcing , over the 100-year time horizon, for 1 kg CO2 emitted in different years.

Similar to Kendall , we further normalize the CRF results of different years by that of the year when the carbon debt occurs . This step yields a set of weights of decreasing value from 1 for year 0, 0.5 for year 60, to nearly 0 towards year 100. Finally, we assume that carbon debt occurs all at once in the year of land conversion . The assumption of instantaneous carbon loss is somewhat unrealistic but can be considered as a worst-case scenario to indicate the impact of considering emissions timing. Following the argument of Hellweg et al. , we do not further discount future emissions, a practice that is common in economics to account for time value of money. The general approach to CPT calculation outlined in this paper could, however, employ other dynamic characterization approaches discussed earlier; we select the approach by Levasseur et al. with 100-year time horizon only for the purpose of illustration. Taking into account potential corn yield differences, productivity improvements within the corn ethanol system, and emissions timing, our analysis shows that the CPT ranges from 43 to 24 years for CRP land with MtA yield ratios from 60 to 80 % , taking 2001 as the base or land conversion year . In other words, these lands would start to generate carbon benefits from year 24 to 43 after land conversion. For CRP land of low soil fertility with 50 % of average yield, however, the CPT is estimated to be 88 years, which is more than double the CPT estimate for CRP land with 60%of average yield. If the converted land, on the other hand, is highly productive with MtA yield ratio of 100 %, the payback time would be as short as 17 years. Previous estimates of 40 and 48 years of payback time are close to our estimate for 60 % MtA yield ratio, which is 43 years , but with very different underlying reasons. We have re-examined corn ethanol’s carbon payback time in the case of converting CRP land for corn ethanol production taking into account three factors that were neglected in previous studies: yield differences on newly converted land, productivity improvements within the corn ethanol system, and emissions timing . Our results show that CPT estimates for converting low-fertility CRP land with 50 % marginal-to-average yield ratio ranges from 65 to 88 years . For highly productive CRP land, the payback time could be reduced to less than 20 years.

For CRP lands with 60–80 % of marginal-to-average yield ratio, which is considered to be a more typical case, the payback time range from 19 to 43 years . Previous estimates of 40and 48 years of payback time are near the upper bound of our estimates. Technological advances within the corn ethanol system are the key for the CRP-corn ethanol system to be able to generate positive climate impacts. Without technological advances, CRP land with ≤80 % of marginal-to-average yield ratio would fail to provide any carbon benefits over the 100 years after the land conversion. Note that our study does not consider the reversion of land use, which, if included, would further shorten our estimates of CPT for the CRP-corn ethanol system . Overall, our study confirms the importance of understanding marginal technologies and efficiency changes in LCA ; LCAs based on a static productivity assumption may fail to recognize the long-term benefits of the technology as it matures. Also, our study demonstrates the relevance of considering the actual yield of the converted land rather than the average yield, as direct corn expansion will most likely bring marginal, less-fertile land into production. One of the key questions in bio-fuel policies is whether additional corn ethanol production would reduce GHG emissions. Therefore, LCA studies based on average data from existing corn ethanol systems fall short of offering adequate insights for the policy questions at hand. Ideally, such policy questions can be answered using a prospective model that embraces the complex dynamics between and within marginal technologies, marginal impacts, displacement mechanisms and behavioral changes. Our analysis highlights the importance of taking the underlying dynamics into account in understanding the implications of a technology, which can be referred to as “consequential thinking” as an analytical paradigm . However, we acknowledge and admit that our analysis neglects many other factors that would influence the system. That is one of the main reasons why we believe that the term, “consequential LCA”, which implies the existence of a well-defined, operational modelthat is capable of showing the future trajectories of human-nature complexity, can be misleading . Instead, our study employs a scenario approach to answer what-if questions focusing on marginal yield and ethanol system productivity.

Needless to say, our results shall be interpreted only under the assumptions employed as well as the limitations associated with them. Agriculture is essential for feeding a majority of the global population, but it has also been identified as one of the major drivers behind various global environmental degradations . For example, due to a quintupling of global fertilizer use in the past decades, agriculture has greatly disturbed the global nitrogen and phosphorus cycles . This results in a wide range of environmental issues from release of N2O, formation of photochemical smog over large regions of earth, to accumulation of excessive nutrients in estuaries and costal oceans . Agriculture dominates pesticide use , which contaminates surface and ground water and threatens human and ecological health . So also does agriculture dominate freshwater withdrawal worldwide ,grow bag gardening adding stresses where there are competing needs for water . Despite the severity of existing environmental impacts of agriculture, the challenge of addressing them is compounded by increasing global food demand . Continuous global population growth and spread of economic prosperity , mainly in developing countries, will likely drive the global food demand to double by 2050 . Over the past decade, life cycle assessment has been increasingly applied to agricultural and food products , with a number of agricultural LCA databases developed worldwide recently . LCA is a tool that quantifies products’ environmental emissions and resource use throughout the life cycle and evaluates the potential impacts they generate on human and ecological health . Impact categories evaluated in LCA span a wide range, from global warming, ozone depletion, acidification, eutrophication, to ecotoxicity, human health cancer, and non-cancer . Applications of LCA in agriculture include comparing the environmental performance of alternative products or technologies , such as organic versus conventional farming , and identifying hotspots and improvement opportunities . In particular, LCA has played an active and important role in assessing the environmental benefits of bio-energy and contributed to the making of public climate policies . As with LCA studies in general, agricultural LCAs often rely on static and single-year inventory data with commonly 5 to 10 years of data age. In Ecoinvent database, for example, the data year for U.S. Corn Farming is around 2005 and for Swiss Corn Farming is around 2000 . Literature suggests, however, that agricultural systems may be highly dynamic due in part to the increasingly changing climate and technological advances such as improved yield and energy efficiency . These factors may bring about substantial changes in the use of input materials and the yield of crops, hence substantial changes in the environmental impacts. For example, direct energy inputs per ha corn produced in the U.S. declined by about 40% between 1996 and 2005 and in the meantime corn yield increased by about 30% .

In this study, we seek to evaluate if on-going changes in input use and structure of four major crops in the U.S. might have resulted in substantial changes in their environmental impacts over the past decade, focusing on regional issues such as eutrophication, acidification, and ecological toxicity. The crops studied are corn, soybean, wheat, and cotton, which together account for around 70% of total harvested area domestically . The main objectives of the study are to understand the extent to which different environmental impacts might have changed and to identify major drivers behind such changes. Following previous LCA studies we analyzed the cradle-to-gate life cycle environmental impacts of 1 ton and 1 hectare -year of crop production. Direct emissions, such as nutrient leaching and runoff, result from the use of agricultural inputs, and indirect emissions that occur along the supply chain, including emissions from production and transportation of agricultural inputs like synthetic fertilizers. We focused on the estimation of direct emissions for their substantial contribution to the overall life-cycle environmental impacts of crops , and used the Ecoinvent database to calculate indirect emissions . We began with collecting data on the use of agricultural inputs in different years, and then estimated associated emissions based on emission statistics and models. The emission data compiled were next aggregated using characterization models from Life Cycle Impact Assessment to quantify their relative magnitudes of environmental impact. Major agricultural inputs include fertilizers, pesticides, irrigation water, and energy . Data on fertilizer and pesticide use are from the U.S. Department of Agriculture , which surveys farmers in top-producing states annually on a rotating basis . We selected the years with the largest number of states covered for each crop to best represent U.S. national situations. We found that top producing states were consistently surveyed in the years selected for each crop, which ensures comparability across years. For example, the same 19 states were covered for corn and they accounted for around 95% of total corn area harvested in each of the years selected. Similarly, the same 9, 19, and 15 states were covered for cotton, soybean, and wheat, and these stated accounted for around 92%, 96%, and 88% of total area harvested, respectively.Irrigation water use data are from the Farm and Ranch Irrigation surveys conducted also by USDA , and the most recent three surveys for 2002, 2007, and 2012 were used for our analysis. State-level energy use data were also compiled from the USDA , but the data are somewhat outdated as they reflect crops planted in late 1990s or early 2000s. USDA has unfortunately ceased to update such data for most crops except for corn, which was updated to the year 2005 . On the other hand, farms have become more efficient in response to rise in fuel and fertilizer prices in the last decade . For example, on-farm energy use in corn production reduced by >20% between 2001 and 2005.

Import liberalization has been a theme stressed in many of the above mentioned papers

Future studies focusing on parent compounds or pesticide-specific metabolites may be able to clearly elucidate associations between individual pesticide use and exposure. Additionally, DAPs in urine may reflect exposure to preformed DAPs in the environment or food rather than exposure to the parent compound and thus overestimate OP pesticide exposure. Finally, the modified food frequency questionnaire we used quantified maternal reported servings of fruits and vegetables consumed by the child each day, but was not calibrated to specific portion sizes. Thus, the use of reported servings in the analyses may have introduced uncontrolled variability. However, this type of non-differential exposure misclassification would tend to bias results toward the null hypothesis. In conclusion, we found that children living in an agricultural area are likely exposed to OP pesticides from multiple pathways, and total urinary DAP, in particular DMAP, metabolite levels increased with age. Diet and regional pesticide use are possible exposure sources. Given the health benefits of fresh fruit and vegetable consumption, we do not suggest that children limit intake of these foods but encourage washing of all produce before eating. While the OP pesticide metabolite levels in this population do not appear significantly higher than other populations, there are limited reference data available to make valid comparisons. OP pesticide exposures in children have been associated with poorer neurodevelopmental outcomes. Given the significance of these health studies, additional research is needed to better explain the trend of increasing OP urinary metabolites with age and the dietary, behavioral,square black flower bucket and other factors that determine exposure.Over the past decade, the annual U.S. trade balance with China has gone from a small surplus to a deficit of over $57 billion . The mounting trade deficit has resulted in renewed U. S. pressure to expand access to China’s markets. Recently, there have been intensive U.S.-China discussions over trade concessions and the related issue of China’s bid to join the World Trade Organization .

Agricultural trade is at the center of these negotiations as China’s high trade barriers in agriculture are believed to be partly responsible for the trade deficit.In a typical year, China has neither a large surplus nor a large deficit in its agricultural trade balance. For instance, in 1995, China ran a relatively small agricultural trade deficit of $1.47 billion and then in 1996 the balance shifted to become a small surplus, with agricultural exports exceeding imports by $673 million in that year.Even though its overall agricultural trade balance is small, China is a significant but erratic trader for certain agricultural commodities such as wheat, maize, oilseeds, edible oils, tobacco and cotton. China’s agricultural trade regime has not been liberalized to the same extent as its trade in manufactures . So there is great uncertainty as to what might happen if and when China liberalizes its agricultural trade. Some projections suggest that China will become a consistent net importer of food . Based on its large and growing population and fluctuating grain stockpiles, some fear that China could destabilize world markets after agricultural trade liberalization . Agricultural trade barriers will be a key issue with regard to China’s application to join the World Trade Organization . For instance, China’s non-tariff trade barriers in grains are very controversial. The barriers in grains are not transparent because China’s state trading in grains is conducted through its Cereal, Oil, and Foodstuffs Importing and Exporting Corporation . COFCO is one of the world’s largest STEs in agriculture, and over the past decade, COFCO has imported as much as 17 percent of world wheat traded, and exported as much as much as 10 percent of the world’s corn. The reemergence of China as a significant trading nation in merchandise trade has been described by West , Lardy , World Bank , Wall, Boke, and Xiangshou , and Naughton . Greater integration with the global economy began in the mid 1980s and is now recognized as a fundamental feature of China’s ongoing economic reform. Outside of agriculture, significant import tariff reductions have occurred in the past decade. As a measure of openness, China’s nominal value of exports grew by 13 percent annually from 1980 to 1996.

During the same time period, imports grew by 12 percent per year, on average. By 1997, China’s total trade accounted for about 3 percent of world trade, up from 0.8 percent in 1978. However, the degree to which China’s door is open to the world is debatable and China may be less open to foreign trade than initially appears . From 1986 to 1996, China’s growth in real merchandise trade exceeded growth in real GDP by 2.1 percent, which was not particularly high by international standards. For instance, during the same time period, growth in real trade less growth in real GDP was 6.9 percent in Thailand and 4.5 percent in the United States.China’s ratio of foreign trade to GDP rose from 13 percent in 1980 to about 35 percent in 1996, valued at the official exchange rate. However, this ratio may overstate the relative importance of foreign trade in China’s economy because it is based on the official exchange rate . If instead, the purchasing power parity exchange rate is used, trade as a percent of GDP has not changed all that much since the mid 1980s. Using the real exchange rate, China’s trade as a percent of GDP only grew slightly from 6.6 percent in 1986 to 7.1 percent in 1996 . In relative terms, India’s trade as percent of GDP grew faster than China’s over this time period, going from 3.9 percent to 4.5 percent. In comparison, Thailand’s trade as a percent of GDP grew from 14.7 percent to 31.3 percent from 1986 to 1996. Despite China’s move to lower average tariffs, China continues to restrict imports through a variety of barriers, including tariff-quotas, taxes, import quotas, import licenses, and state trading . In addition, China uses other non-tariff technical trade barriers such as sanitary and phytosanitary measures. These barriers are commonly applied to agricultural products. For instance, under the guise of phytosanitary measures, China prohibits imports of U.S. citrus .Lardy explains that the commodity composition of trade has changed along with domestic market reforms, and that trade patterns are more consistent with China’s comparative advantage, compared with the pre-reform and early reform time periods. China has shifted away from petroleum exports and has increased exports of labor-intensive manufactured goods, to the point where manufactured goods accounted for 85 percent of exports in 1996.

The share of primary commodities in total imports fell from a little over one-third in 1980 to about one-fifth by 1996. China’s agriculture has a comparative advantage in labor intensive crops, not grains . However, policy has tilted China’s agricultural production away from its comparative advantage which lies in non-grain activities. Naughton argues that China’s merchandise exports have shifted to reflect its abundant labor. Has this happened in agriculture? To what degree is agricultural production and trade becoming more specialized to capture its comparative advantage in labor intensive food products? From a conceptual basis, Anderson argued that China’s economic reform would have a significant impact on the pattern of agricultural trade. More recently, the same argument has been made from an empirical perspective by Wang and Wailes, Fang, and Tuan . Wailes, Fang,square black flower bucket wholesale and Tuan point out that the growth rates for China’s agricultural trade are much slower than for total trade and consequently the share of agricultural trade in total trade has declined quite dramatically. However, Wailes, Fang, and Tuan also argue that China’s agricultural trade has expanded rapidly and that the pattern of trade roughly adheres to the laws of comparative advantage. Alternatively, Anderson and Strutt find there has been little growth in China’s food import dependence. Wang has argued that China’s agricultural net trade structure is consistent with its resource endowment. He found that land-intensive bulk4 and processed intermediate commodities account for most of the imports, while labor-intensive horticultural and consumer ready products make up most of the agricultural exports. However, he based his analysis on 1995 and 1996 data, a periodduring which China had a temporary export blockage on grain exports. In late 1994, the central government placed a moratorium on grain exports in an effort to control higher domestic food prices. Rice and maize have traditionally been net exports but they shifted to a net import situation during the export blockade. Yiping Huang has argued that economic reforms in China have generated a significant impact on agricultural trade. He supported this observation with three points. His first point was that the growth of exports outpaced that of GDP during the reform period. Second, he noted that distortions to agricultural trade have been reduced significantly and agricultural trade experienced dramatic expansion. Third, he noted that trade was brought into conformity with the pattern of resource endowments.The trade reforms that have been implemented in China since 1979 are characterized by demonopolisation of foreign trade, the phasing out of trade subsidies, replacing of planned-quotas with a tariff- quota regime , progress toward currency convertibility, and provisions to attract foreign direct investment. The opening-up has been a means to promote economic growth and conform with general international trade rules so as to finally join the WTO. In general, some significant changes in the nature and extent of government trade interventions have occurred in China. Prior to the reform period, the allocation of imports and exports were strictly based on administrative planning and undertaken by only 12 foreign trade corporations.

The process of trade policy reform has involved the introduction of some competition in international trading and the gradual development of policy instruments for indirect controls. In 1984, the foreign trade system was decentralized considerably, when the provincial branches of national foreign trade corporations were allowed to become independent and each province was allowed to create its own FTCs. By 1986 there were about 1,200 FTCs, and by the early 1990’s they numbered more than 3,000. Although firms must obtain approval to engage in international trade, this permission has been granted very liberally and there are now approximately 200,000 firms eligible to engage in foreign trade . On the other hand, the foreign trade of so-called “strategic products” such as food grains, textile fibers, and chemical fertilizers, continue to be restricted to specialized national trading corporations with monopoly trading rights. China’s agricultural trade policy, particularly with regard to grain, is characterized by import/export licenses and quotas. But even in the case of agricultural trade, some progress has been made since the 1980s. The overall purpose of this paper is to measure this progress, relative to trade in manufactures and other primary commodities. Prior to the 1978 reforms, almost all of China’s foreign trade was subject to central planning through a small number of foreign trade corporations. For most sectors, the government has since replaced central planning over trade with import licenses and import and export tariffs. The opening of China’s economy involved policies to promote exports and attract foreign direct investment. However, agricultural trade is a major exception to this move towards decentralization of foreign trade. This is somewhat ironic because agriculture was largely responsible for the initial success of China’s overall economic reform.In China, rapid economic growth has been accompanied by dramatic changes in the structure of the economy. Agriculture’s share in the total economy has declined from about 40 percent of the GDP in 1970 to less than 20 percent in 1997. At the same time, agriculture’s share in total employment declined from 81 percent to 49 percent.5 The declining role of agriculture in the economy means the share of agricultural trade in China’s total trade has decreased significantly. In 1980, agriculture’s share of both exports and imports was around 30 percent, and this declined to about 10 percent in 1997. This is an indication of the improvement in resource allocation among sectors and the shifting of comparative advantage between agricultural and manufactured products. In nominal terms, the value of China’s agricultural exports grew at an average rate of 7.1 percent a year from 1980 to 1996.

A short lasting fall or spring frost lasts a few hours and can cause substantial damages

It turns out that Pistachios, a billion dollar crop in California, could be threatened by warming winter within the next 20 years.While the scope and magnitude of our current climate crisis might be unprecedented in human history, this is not the first time that humans are facing climatic challenges in agriculture. Olmstead and Rhode show how, through the 19th and 20th centuries in North America, wheat growers managed “…to push wheat cultivation repeatedly into environments once thought too arid, too variable, and too harsh to farm”. The transition was made possible mostly by the development of new varieties. Plant breeding toward that end required information on the climate both in the progenitor native areas and the areas where the eventual new varieties would be planted . Adaptation to climate can be on the physical dimension as well. Specific interventions can be designed to change the physical environment surrounding plants. The most obvious intervention is building irrigation systems, to compensate for lack of adequate rainfall and soil moisture. But examples of adaptation to temperature by physical means exist as well. This type of intervention is common for a left tail effect: frost. To avoid it, only a slight increase in temperature is required, and growers know how to do that. Some examples for dealing with frost are hundreds of years old. The Tiwanaku civilization formed a system of raised fields on the shores of lake Titikaka in the 7–12 centuries C.E. Fields in select locations were raised with extra soil,plastic flower bucket up to a few feet above the ground level. Water from nearby springs was diverted and run through canals dug in these raised fields.

This provided not only moisture for the plants, but also converted the top soil level into a large heat storage unit. On frost nights, which are common in this high area, the heat stored in the soil kept the near-surface temperatures on raised fields higher than the normal air temperatures, preventing plants from freezing . Without modern weather instruments, the Tiwanaku realized that slight differences in ambient temperatures can have crucial consequences, and planned their fields according to their understanding of the climate. This system yielded far better than regular dry farming practiced before in this area, and supported a larger population than the one residing on the lake shores in the 1990’s. Eventually, as climate became drier, the water level of lake Titikaka dropped and the springs dried up, resulting in the collapse of the Tiwanaku culture . Despite its eventual failure, this technology was successful in abating frost damage for centuries, maintaining a population of hundreds of thousands and showing the power of human intervention on the field level to tackle a temperature distribution tail challenge. In Europe, traditional methods of dealing with frosts in vineyards include lighting small fires or “frost candles”. A more modern approach uses big fans, circulating the cold air in the inverted layer with the warmer air on top of it. Farmers have been using “air disturbance technology” in the US since the 1950’s . Wind generators are used around the world to protect wine grapes, fruits, and even tea from spring frosts. In some cases, a similar effect can be achieved with sprinklers . Interestingly, little economic literature has focused on air disturbance technologies. Stewart, Katz, and Murphy assess the value of weather information in the Yakima Valley of central Washington, in the context of frost prediction and air disturbance technologies. This descriptive study was published in the Bulletin of the American Meteorological Society. Searching the EconLit database for “frost” in article titles returns only four results involving actual frost in agriculture, none dealing with temperature altering.

A search in the abstracts of papers published by the American Journal of Agricultural Economics results in two papers, neither mentioning air disturbance technologies. The seeming dis-interest in these technologies is even more peculiar in 2019, when weather information is more accessible than ever: air disturbance systems are now sold with online communication to weather services, with the option for automatic operation in case of frost, and can often be switched on and off remotely. They are probably more efficient and valuable than ever before, given advances in technology and the high value of certain frost-sensitive crops. Technologies such as air disturbance are examples of a concept I call “Micro-Climate Engineering” . These are relatively small interventions in temperature distributions, limited in space and time, which aim to avoid the nonlinear effects of the extremes. The frost examples discussed above deal with left tail effects. There are also technologies available to deal with right tail effects, which is the focus of my last chapter. The final chapter of this dissertation deals with an MCE proposal for California pistachios. Chapter 3 deals with the threat of warm winters on pistachios, estimating the potential losses to this high value crop from climate change. Chapter 4 deals with a proposed solution. The MCE technology proposed for this challenge is spraying the dormant trees with kaolin clay, a non-toxic white substance which reflects the sunlight. Sprayed trees have been shown to experience lower temperatures than control trees, and their yields were higher. This intervention requires precise hourly measures of temperature, so growers can track the buildup of special temperature metrics and decide if and how much treatment is required. Using the pistachio yield-temperature response, estimated in the previous chapter, I build a model that integrates MCE in the pistachio market. The model can be solved with and without the option to use MCE, under various weather realizations. The value of MCE for California pistachios is calculated as the difference in welfare measures attained in each case.

The expected net present value of MCE in pistachios for 2020-2040 is assessed in billions of US dollars. This is yet another example of the potential use of weather information for dealing with climate change challenges in agriculture. Micro-Climate Engineering might remind some readers of Geo-Engineering, a controversial climate change adaptation concept. Geo-engineering proposals involve global scale interventions in the atmosphere and hydrosphere that would revert some of the changes in the total temperature distribution worldwide . In contrast, MCE is a small scale concept, aiming to tweak the temperature tail distributions where necessary rather than shifting the entire distribution year round. Many MCE technologies already exist and are used by growers, making sense both on the technical and economic dimensions. I believe many more examples are out there to be found, and many more will evolve as growers adapt to climate change.This chapter assesses the gains from a weather service provided by the California Department of Water Resources : the California Irrigation Management Information System . Established in 1982, it now comprises of hundreds of weather stations, scattered in many of the growing regions in California, and centralized computing systems for distributing the information and interpolating data between the stations. The intended purpose of CIMIS was to provide accurate real-time information for growers to optimize irrigation and save water. Specifically, many CIMIS stations include evapo-transpiration sensors, applied on specially maintained turf. Agronomists have been publishing crop coefficients, which serve to transform the turf-based ET measures for use in various commercial crops. This way,flower buckets wholesale growers can estimate how much water has been used by their plants, and plan replenishment of soil moisture accordingly. CIMIS also reports other weather variables, such as temperature, relative humidity, wind speed and direction, and soil temperature at the station. It does not offer forecast services. CIMIS has become a staple of agricultural practice and research in California. Searching for it on Google Scholar results in 2,860 entries for articles and publications. The gains from CIMIS have previously been analyzed by a team of researchers from the University of California – Berkeley , and the findings were published widely . This report used a survey methodology, and found a 13% applied water reduction with CIMIS, 8% yield increase, and a total economic gain of $32.4 million yearly. The 1996 report also found some examples of unintended use of CIMIS, which in fact delivered a substantial portion of the gains. For example, while the system was mainly designed for improving irrigation performance and water saving, the researching team found that there are many gains from CIMIS use in pest management. CIMIS detailed temperature data are used to calculate pesticide application timing, reducing the amounts of pesticide and increasing yields. This chapter presents and analyzes the main findings from a more recent report, prepared for DWR by David Zilberman, Itai Trilnick, and Ben Gordon. This report was meant to update the knowledge on the current uses and users of CIMIS, its economic gains, and potential future improvements. The full report is yet in the writing process. However, several patterns and conclusions can already be drawn, and are presented in this chapter.

The study is based on a survey of CIMIS users. Before running the survey, extensive interviews were held with various users to gather narratives about the roles of CIMIS in different contexts. These interviews provided a first qualitative picture of current CIMIS uses and interactions with other technologies and practices. They suggest that CIMIS has indeed become a mainstay in California agriculture, especially for growers relying on drip irrigation. However, many farmers access CIMIS indirectly through consultants, and might not be aware of the uses and benefits of the system. With the advance of alternative decision making tools , CIMIS is now part of a larger information eco-system. The interviews showed that the public availability of CIMIS data, including historic records, are highly regarded among users. This historical and cross-sectional information store is extremely valuable for decision-making and research. It is essential for calibrating other weather tools, verifying their results, and designing water management schemes that require knowledge of the historical distribution of weather variables. In addition, it may even be used to more accurately value farmland. Interviews were followed by a small survey, carried out by phone and aimed at assessing the initial insights from the interview. The final step was a full scale online survey, sent to all registered CIMIS users. Results from this survey are the basis for economic value calculations. CIMIS, an invitation to participate was also sent by email to mailing lists provided by the CIMIS team. The survey included some general questions, directed to all audiences, and questions tailored to specific user groups identified in the initial survey: growers, consultants, users in landscape management, regulators, researchers, and others. The CIMIS team decided that the survey will not include direct questions about water use, costs, and willingness to pay for CIMIS services, especially when addressing growers. These questions were deemed too intrusive, jeopardizing both the response rate and general trust of users in the CIMIS system. This meant that a direct WTP approach, like the ones used in the previous study of CIMIS and the one used by Anaman and Lellyett , would not be possible. Most questions were framed either in Likert-like scales or as a relative response . The analysis of the results uses indirect assessing of CIMIS impacts, using these types of responses and outside information. The online survey was done on a commercial platform, Survey Gizmo. It is worth noting that most registered users are not active. In fact, CIMIS user statistics show that a relative small percent of registered users had logged in and extracted data from the system in the year before the survey. Altogether, we have 3,057 responses, out of which 2,358 are complete.The breakdown of self-reported user types is listed in Table 2.1. About 1/4 of our respondents report their primary activity, as it relates to CIMIS, to be agriculture. The second largest category is “other”, encompassing a mix of respondents who, in our opinion, should have picked another definition, and a few others who seem to use the data for personal research. This category has gardeners, nursery workers, water consultants, government workers, and a few retired people working on individual projects. We did not reclassify obvious mis-responses, as that would not change the fact that they ended up answering a different set of questions than their “real” category. The third category is government workers, followed closely by research, environmental consulting and landscape management.

Organic networks had lower normalized betweenness centrality values than conventional networks

The differentially abundant fungi and bacteria were evenly distributed between the two management systems. For fungi, 11 ASVs were more abundant in the rhizosphere of conventional plants and 13 were more abundant in organic. The Mortierellales were the most-represented order with four ASVs, but these were not disproportionately found in CR or OR .We asked how agricultural management and plant roots act individually and in combination to shape microbial community composition, co-occurrence patterns, and N-cycling functions, and whether this interaction leads to system-specific adaptation. In accordance with known management and rhizosphere effects on microbial community structure and N dynamics in agroecosystems, we observed conventional/organic and bulk/rhizosphere differences in many of the parameters measured. Furthermore, many of our analyses supported the hypothesis that plant selective influence varies with management to shape plantassociated microbial community composition and structure . Management, rhizosphere, and M × R effects on microbial communities are likely mediated in large part by soil physicochemical properties, which differed between management systems and soil compartments . Strong effects of management on soil physicochemical properties were visible in the higher NO3-N, P, K, Ca, Na, and SOM levels in the organic system and higher Mg and pH in the conventional system. Rhizosphere soil was depleted in NO3-N, P, and K in both management systems. M, R, and M × R effects on soil properties such as nutrient availability, pH, and organic matter likely contribute greatly to microbial community assembly in these treatments. Significant differences in the direction or magnitude of the rhizosphere effect were observed for bacterial diversity,plastic plant pot community composition, and indicator species .

Plant roots consistently imposed a strong selective filter, and similarity between rhizosphere communities was greater than similarity between bulk soil communities . Nevertheless, rhizosphere communities still reflected the impacts of management on the contributing microbial pool, and rhizosphere communities were more similar to their corresponding bulk soil communities than to one another . The direction of the rhizosphere effect varied with management for bacterial diversity, indicator species, and community structure. This M × R interaction resulted in rhizosphere bacterial communities that were more similar in diversity, composition, and structure than bulk soil bacterial communities. Rhizosphere bacterial/archaeal diversity was lower in the organic rhizosphere but higher in the conventional rhizosphere compared to bulk soil . Although roots are often thought to impose a selective filter that decreases diversity, higher species richness in the rhizosphere as observed here in the conventional system has been reported elsewhere when plants select for enrichment of certain processes . Here, however, whether functional enrichment is related to selection for increased diversity is unclear. Environmental filtering may account for the fact that bacterial rhizosphere networks were more similar than bulk soil networks. Although it has been hypothesized that niche sharing should lead to greater co-occurrence and thus more densely connected networks in the rhizosphere, this effect was seen only in the bacterial organic networks . Viewed in combinationwith previous work showing smaller, less densely connected networks in rhizosphere soil, our results suggest that rhizosphere effects on co-occurrence networks, like other metrics of microbial community structure, may well be context- and system-dependent. The magnitude of plant effects on rhizosphere communities also differed between management systems.

We generally found greater differences between bulk and rhizosphere community composition in conventional soils compared to organic . Hartman et al. attribute a similar M × R interaction observed in their study of wheat agroecosystems to the application of management practices immediately before root establishment. This explanation may apply here as well, specifically with regard to the spatial scale of cover crop and fertilizer inputs. Inorganic fertilizer and composted poultry manure were trenched in seed beds and therefore near crop roots, likely favoring divergence of bulk soil and rhizosphere microbial communities. Since cover crops were sown throughout the organic plots, covercropping-induced changes in microbial community composition were likely similar in the bulk soil and early root zone, whereas emerging roots in the conventional plots would likely have encountered a fertilizer-enriched zone already distinct from most of the bulk soil.We further hypothesized that rhizosphere communities would be enriched in system-specific beneficial taxa and functions of importance for plant adaptation to system-specific soil conditions. Although indicator species analysis revealed system-specific taxa, we cannot definitively conclude whether these taxa are beneficial based on amplicon sequencing data. Three members of the order Myxococcales and two members of the order Burkholderiales were indicators of organic environments, in line with previous studies showing these orders to be organic-system-specific. Two strains of the Anaerolineales, an order that displaces other fermenters under high-nitrate conditions, were indicators of the conventional system. Broad ecological information about soil fungi is limited in comparison to bacteria and archaea, despite extensive specialized literature on pathogens of humans and plants or AMF and other endophytes. Many fungal indicators identified here belong to genera known to be pathogenic on other host species, and these were relatively evenly distributed among environments. The significance of pathogens as indicator species in these systems is unclear, especially for pathogens such as Boeremia exigua, which causes leaf spot on diverse host crops including tomato, the other crop in this rotation, but is not known to cause disease in maize. Fewer details of metabolism and ecology are available for non-pathogenic fungal indicators. Mortierella, the most common genus among fungal indicators in this study, are known to be a large genus of saprotrophs.

Exophiala equina and Didymella sp. have been reported elsewhere to be associated with plant roots. Fungi are critical drivers of C/N cycling and carbon sequestration in agricultural systems, and linking specific taxa to roles beyond pathogenic interactions will be a valuable expansion of the existing literature. With regard to N-cycling functions, we quantified six genes involved in different steps of the nitrogen cycle, all of which were affected by plant selection and only two of which were differentially selected between systems . The relative abundance of genes relative to one another was similar across treatments, suggesting that no system-specific bottlenecks in the N cycle were observed . The abundances of the nifH, amoA , nirK, nirS, and nosZ genes were higher in the bulk soil,plastic planter pot in contrast to previous studies that found the maize rhizosphere was enriched in functional genes related to nitrogen fixation , nitrification , and denitrification.That effect was also observed with the addition of artificial maize root exudates, suggesting that exudates are the main mechanisms influencing microbial N cycling independently of other physicochemical characteristics of the rhizosphere. However, mechanisms other than exudates may be responsible for the discrepancy in the direction of the rhizosphere effect between the present study and the literature: while certain root exudates inhibit nitrification in wheat, sorghum, and rice, this effect has not been shown in maize. Sampling in the present study occurred during the silking period of maize, when crop N uptake reaches a maximum. The rhizosphere may be N-depleted in comparison to bulk soil, and microbial N limitation may account for the decreased abundance of these N-cycling genes. Differences in soil organic matter or shifts in root exudation during development leading to altered rhizosphere carbon availability may also account for the change in direction of the rhizosphere effect in the present study as compared to the literature. Increased sampling frequency over the course of the growing season paired with metabolomic analysis of root exudates would provide insight into the mechanisms linking root C release and N uptake dynamics to microbial N-cycling gene abundances. We hypothesized that differences in N-cycling gene abundance between conventional and organic systems would reflect adaptive shifts, increasing the abundance of gene pathways linking system-specific N inputs to plant-available species, but this hypothesis was not supported. Only two of six genes were affected by soil management history. The abundance of the nosZ and bacterial amoA genes, the only genes affected by the M × R interaction, was higher in the organic system . The increase in abundance of the nosZ gene could potentially indicate greater conversion of N2O to N2 and decreased greenhouse gas production, while increased abundance of the amoA gene may reflect increased conversion of ammonium to nitrite and subsequent nitrification products. Higher soil carbon as a result of long-term organic matter applications at this site may contribute to higher abundances of the nosZ gene in bulk and rhizosphere soil in this system. Putz et al. found that higher soil organic carbon under a ley rotation increased expression of the nrfA and nosZ genes relative to the nirK gene as compared to a conventional cereal rotation, favoring higher rates of dissimilatory nitrate reduction to ammonium and lower rates of denitrification. However, previous work in the treatments examined in the present study found that abundances of the amoA and nosZ genes were not correlated with gross rates of N transformation processes. Prediction of cropping system impacts on microbial N cycling therefore requires a nuanced integration of gene abundances with parameters such as carbon availability, moisture content, and temperature within soil aggregate microenvironments over time.

That few differences were observed late in the growing season between N-cycling genes in systems receiving organic or inorganic N inputs is consistent with the results of a meta-analysis by Geisseler and Scow, which found that N fertilizer impacts on microbial communities tend to fade over time. Sampling occurred at silking in the present study, long after the preplant fertilizer and compost applications that likely maximize differentiation between systems. Potential N limitation in the rhizosphere in both systems may also have outweighed management effects. Co-occurrence networks, which provide insight into ecological interactions among microbial taxa, were influenced by M, R, and M × R effects. Bulk and rhizosphere bacterial networks from the conventional system had the same number of nodes but were more densely connected than networks from the corresponding soil compartment in the organic system . Other bulk soil comparisons of organic and conventional agroecosystems using networks constructed from OTU-level data have found conventional networks to have more nodes or, alternatively, fewer nodes and edges than organic networks. Clearly, predicting cooccurrence patterns of incredibly diverse microbial communities based on a conventional-versus-organic classification is too simplistic. Agricultural management is likely better represented as a continuum than discrete categories, and causal relationships between specific practices and network topological properties have yet to be determined. An M × R interaction was also observed for network properties in which size, density, and centralization were lower in the rhizosphere network from the conventional system than from the organic system . These network properties follow the same pattern as alpha diversity of bacterial communities, suggesting a shared yet perplexing cause: while the mechanism remains unclear, rhizosphere communities appear to be converging from very distinct bulk soils towards similar diversity and structural metrics. Conventional agriculture is hypothesized to disrupt the connections between bulk soil and rhizosphere networks, as tillage and mineral fertilization are proposed to disturb fungi and soil fauna that serve as a bridge between bulk soil and rhizosphere environments. While tillage does not differ between the systems we measured, fertilization effects are likely partly responsible for the observed interaction. Regardless of the mechanisms involved, the systemspecific direction of the rhizosphere effect on cooccurrence network properties suggests that management and plant influence interactively determine not only which taxa are present, but how they interact, with potential implications for agriculturally relevant functions and ecological resilience. Hub ASVs were identified in each network based on high values for normalized betweenness centrality, a metric often used to describe keystone taxa. Lower betweenness centrality values for hub taxa may indicate that network structure depends less on individual species, potentially increasing resilience to environmental stresses that could destabilize networks overly dependent on hub taxa sensitive to those specific stresses. Different hub ASVs were identified in each rhizosphere environment, but information on the ecology of these taxa is generally absent from the literature. Although it would be misleading to state that these taxa are keystone species in their respective habitats without experimental validation, the fact that many of these taxa were also identified through indicator species analysis suggests that they play important ecological roles.

Further confounding the issue is the existence of large spatial variability among cornand cotton-growing states

Additionally, diversion of corn to ethanol production essentially reduces food supply, which may lead farmers worldwide to convert natural land to new cropland in order to compensate for the diverted grain . This indirect LUC would generate the same net effects as that of direct LUC as discussed above, although its estimation is much more complicated for the difficulty and uncertainty involved in quantifying the impacts of US bio-fuel policies on global land and agricultural commodity markets . Studies continue to explore the effect of indirect LUC of bio-fuels with refined modeling methodologies , improved understanding of agricultural and food systems around the world , and extended assessment to non-GHG impacts . Yet, there is another consequence of corn ethanol expansion to which relatively less attention has been paid. In conjunction with rising corn prices, substantial land cover shift from cotton to corn has been observed—particularly between 2005 and 2009—through both direct expansion of corn into cotton and indirect expansion of corn into soybean, then of soybean into cotton . This observation is supported by farm-level data, which reveal that as growing corn became more profitable, some farmers reacted by reducing cotton land for growing corn . Furthermore, the National Agricultural Statistics Service Cropland Data Layer provides high-resolution maps derived from satellite imagery clearly demonstrating that land shifts from cotton to corn occurred in several states . Overall, between 2006 and 2009 when corn prices increased substantially relative to cotton prices , cotton area harvested reduced by 40 % , while corn area in the cotton growing states expanded by 1.3 million ha . Despite the potential large-scale land shift from cotton to corn,black plastic nursery pots there have been few studies on associated environmental impacts. Here, we address this knowledge gap.

We note that corn displacing cotton was only part of the complex land use dynamics in the past “ethanol decade” that involved also land shift from, for example, soybeans and hay to corn, cotton to soybeans, and natural vegetations to corn . The reason we focus only on cotton to corn here is that environmental impacts of land shift between cotton to corn, both high-input crops, are less clear than that between relatively low-input crops and high-input crops . In a recent study, Wallander et al. stated that “When acreage shifts from one high-input crop to another , however, ethanol induced changes may be negligible or could even reduce environmental externalities.” In this study, we seek to test the validity of this statement, focusing on regional environmental issues along with a growing body of literature on the non-GHG consequences of bio-fuels expansion . A land shift from one crop to the other can alter both direct, or on-site, and indirect, or offsite, environmental effects. For example, increased use of nitrogen fertilizers as a result of the land shift not only can elevate N related emissions such as NOx and N runoff but also requires more energy and material inputs in the process of fertilizer production. The system boundary of the study, therefore, was drawn to cover both direct and indirect emissions. In particular, we paid a special attention to direct environmental emissions from crop production given their significance relative to indirect emissions . We calculated indirect emissions embodied in input materials that take place along supply chains, using the Ecoinvent database . In our data compilation, we placed an emphasis on the crop growth and agricultural input structures at the state level, as previous studies showed that national, average data may fall short in capturing the environmental impacts of crop production at a regional level . This is because agricultural systems display high degrees of variability across regions in terms of input structure due primarily to differences in geography, weather patterns, soil type, and management practices .

Also, data on major agricultural inputs such as fertilizers and pesticides collected by the US Department of Agriculture are only available at the state level . The reference year of this study is 2005 given that cotton area experienced a substantial decline between 2005 and 2009. Major inputs in crop growth include fertilizers, pesticides, energies, and irrigation water. We obtained relevant state-level data from several USDA surveys and censuses reflecting cotton and corn farming practices around 2005 and then compiled a set of state-specific inventories. Not all inputs data, however, are available for every state that grows cotton and corn. The USDA Farm and Ranch Irrigation survey, for example, includes more states than surveys of energy and agrichemical use. Nevertheless, the states for which all inputs data are available capture the majority of US cotton and corn production. Specifically, the inventories we compiled cover 19 corn growing states, which account for 95 % of domestic corn production in 2005, and 9 cotton growing states, which account for 88 % of domestic cotton production in 2005. Due to use of agricultural inputs like fertilizers and pesticides, crop production contributes to an array of environmental impacts from acidification, eutrophication, water scarcity to human and ecological toxicity . To best capture these impacts associated with US cotton and corn growth, we estimated all potential onsite environmental emissions based on various databases, models, and literature . The emissions data compiled cover >100 different substances, the majority of which are pesticides and volatile organic compound emissions. Numerical information on all emission factors used in this study can be found in the Table S1–S6 . After compiling emissions data for cotton and corn, we evaluated their environmental impacts using characterization factors from life cycle impact assessment . Reflecting the relative significance of an emission or resource, characterization factors are used to aggregate emission results, usually including a large number of different substances, into a dozen of impact category scores that enable better comparison between alternatives . In this study, we focused on regional environmental aspects of cotton and corn, and based on our previous study , we selected eight impact categories to which cotton and corn production potentially contribute.

These impact categories are acidification, eutrophication, smog formation, freshwater ecotoxicity, and water use as well as human health cancer, non-cancer, and respiratory effects. Characterization factors for all categories except water use are taken from the Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts developed for the USA by the EPA . Characterization factors for water use were based on the ReCiPe model . Note that TRACI 2.0, compared with its original version , has incorporated the recently developed USEtox model for the ecotoxicty, human health cancer, and non-cancer impact categories .For comparison between the two crops, results are organized on the basis of per hectare produced. Figure 2.1 shows the average environmental impacts, weighted by state area harvested, of corn relative to that of cotton in 2005 in the USA. For most impact categories, corn and cotton per hectare show roughly similar environmental impacts, with relative magnitude ranging from 1.4 for acidification and 0.9 for human health cancer. For freshwater ecotoxicity, however, corn shows about one third of impact by cotton per hectare, and corn’s water use is less than half that of cotton. Above all,greenhouse pot most of the environmental impacts associated with cotton and corn production are due to on-site environmental emissions rather than that embodied in input materials like fertilizers and pesticides. Their acidification effect is due in large part to application of nitrogen fertilizers and diesel combustion . Although N intensity of corn is much larger than that of cotton , corn farming uses much less diesel . Overall, the acidification impact of corn per hectare is 1.4 times that of cotton. The same can be said about smog formation. Not surprisingly, the two crops’ eutrophication impact is caused mainly by use of N and phosphate fertilizers. Although corn has higher nutrient application intensities than cotton, its average N and P leaching and runoff rates are lower ; thus, the two crops have a comparable eutrophication impact. Water use by cotton and corn comes primarily from irrigation: about 400 m3 is applied per hectare corn produced as opposed to 940 m3 applied per hectare cotton produced. Freshwater ecotoxicity for both crops is due in large part to pesticide use, and cotton per hectare has a freshwater ecotoxicity about three times that of corn. This is partly because pesticide application intensity of cotton is approximately twice as much as that of corn . Also, many of the pesticides such as cyfluthrin, lamb dacyhalothrin, and cypermethrin used in cotton growth generally show higher toxicity-related characterization factors than the major ones used in corn growth. The two crops’ potential human health respiratory impacts are comparable, although that of cotton is slightly higher. The respiratory effect is mainly caused by diesel combustion, application of N fertilizers, and emissions embodied in P fertilizers. Human health cancer and non-cancer impacts of corn per hectare are slightly larger than that of cotton.

Heavy metals contained in phosphate constitute the major contributor to both crops’ non-cancer effect, but use of acephate, an insecticide, is also another important source of non-cancer impact for cotton. This is why corn’s relative magnitude of non-cancer effect is not as large as that of phosphate application intensity . The two crops’ potential human health cancer impact is due to a number of factors including diesel combustion and heavy metals brought about by phosphate as well as the cancer impact embodied in fertilizers. The results above indicate that corn and cotton grown per hectare in the USA on average generate roughly comparable impacts for most of the impact categories except for water use and freshwater ecotoxicity, where cotton shows lower impacts. The results seem consistent with the view of a recent USDA study , “When acreage shifts from one high-input crop to another , however, ethanolinduced changes may be negligible or could even reduce environmental externalities.” We argue that, however, the average results as shown in Fig. 2.1 are inadequate to capture the net environmental impacts associated with land cover change from cotton to corn that took place in the USA. First, Fig. 2.1 is largely a portrait of corn and cotton growth in different regions and, weighted by state crop area, mainly represents the major crop-growing states where respective crops are likely the most suitable to grow. But, when land shifts from cotton to corn growth, it happens in cotton-growing areas in the South. Lands in these areas can be by and large considered marginal lands for corn in both geographic and economic senses as they are generally less suitable for corn growth than the Corn Belt.The range of spatial variation in cotton growth is two to threefold for acidification, smog formation, eutrophication, human health non-cancer, and respiratory effects and four to sixfold for freshwater ecotoxicity and human health cancer effect. The range of spatial variation in corn growth is about two to threefold for acidification, smog formation, human health cancer, non-cancer, and respiratory effects and fourfold for eutrophication. Water use can vary by orders of magnitude for both crops as some states use little irrigation water while some rely heavily on irrigation . In short, the results for average corn and cotton as reflected in Fig. 2.1 fall short of representing the environmental performance of marginal corn in cotton-growing states and, therefore, should not be used for evaluating environmental impacts of land use change from cotton to corn or vice versa. Comparing Fig. 2.2 with Fig. 2.1 reveals that corn and cotton growths in 2005 at the state level can be quite different from the average situation. Land shift from cotton to corn in Georgia and Texas would likely aggravate all of the impact categories except freshwater ecotoxicity. For North Carolina, however, the land shift would increase water withdraw and aggravate eutrophication impact, but would not cause substantial changes to human health effects. For TX, land shift from cotton to corn would especially aggravate acidification and smog formation impacts. This is because TX, as the major producer of cotton in the US, applies far less nutrients per hectare cotton produced than per hectare corn produced there .

Low and stable market prices generate large consumer surpluses

Can open trading relationships substitute for direct government price supports in order to stabilize markets? More generally, how should CEEC governments allocate a limited budget amongst alternative forms of agricultural support, including commodity price supports, provision of public goods, and subsidies to restructuring? The goal of this paper is to analyze the effect of alternative accession scenarios and policy choices on the performance of CEEC agriculture, with particular attention to the process of enterprise restructuring. We analyze the decision problem facing a CEEC policymaker contemplating integration of his country’s agricultural sector into the EU, through use of a simulation model of production, trade, and enterprise restructuring in the agricultural economies of the CEECs. We focus particularly on how pre-accession agricultural trade and support policies affect social welfare, under alternative assumptions concerning the form of the “accession contract,” i.e., the terms governing the country’s entry into CAP. We approach the questions highlighted above with a partial equilibrium analysis; we do not address the general eqUilibrium effects that link agriculture to other economic sectors, nor the overall macroeconomic performance of these countries. A maintained assumption throughout is that no major reform in the CAP is presumed to be carried out prior to accession. The paper is organized as follows: Section 2 presents the analytical framework. Section 3 describes the data used to calibrate the simulation modeL In section 4, we present the results of several simulation experiments. Section 5 concludes with the key points learned through the exercise.Simulation experiments were performed using a dynamic model of agricultural production, trade,raspberry container size and enterprise restructuring in a three-region partial equilibrium framework, subject to policy interventions and random shocks.

The first region, called the CEEC, represents a generic Central and East European Country in which farmers hire land, labor, and a composite variable input to produce a homogenous output. The effective price of the variable input depends on the CEEC governments’ expenditure on infrastructure and other public goods. Profits depend on the realization of random variables governing the domestic harvest and the prices prevailing in the other two regions, the EU and the Rest of the World . The commodities produced in the regions are perfect substitutes for one another. Trade flows are affected by tariff rates in the EU and the CEEC. In between production periods, some farm enterprises in the CEEC make investments to restructure their operations, thereby improving production efficiency. There is also a migration of land between the large state and collective farms, and smaller private operations, in response to profit differentials between those types of enterprises. The CEEC government can affect the pace of enterprise restructuring through expenditures on targeted credit subsidies. Simulation experiments were performed on the model calibrated to data and estimated parameters for the Czech Republic drawn from a variety of sources. The Czech Republic was selected as the subject of the simulation experiments due to the availability of a variety of data sources for the Czech agricultural sector, encompassing both basic statistical compendia and summary analyses. Wage rates in agricultural enterprises are drawn from official statistical sources . Data on agricultural labor force participation and capital usage are based on Ratinger and Fischer . Ratinger provides information about the size distribution of farms, national output, tariff rates, national food consumption, farm profits, and other national aggregates. Elasticities of production were based on estimates by Ratinger and Fischer , normalized to correspond to evidence that farming exhibits constant returns to scale.

Information about levels of public investment were drawn from publications of the Organization for Economic Cooperation and Development . CAP policy parameters, including threshold and intervention prices for cereals, are drawn from Weyerbrock . The model is designed to answer general, “big picture” questions about the effect of government policies on developments in the agricultural sector rather than detailed questions about the varying effects on d1fferent crops, growing regions, and so forth. It therefore treats all production as aggregated into one measure of output. We use the cereal grains as a proxy for all crops when carrying out calculations on production levels and prices. When converting between national aggregate measures and measures specific to the cereals sector, we apply a conversion factor reflecting the fraction of cereals in the total value of Czech production . In the absence of comprehensive farm-level data on production efficiency, several model parameters had to be calibrated to the available data. Total factor productivity parameters were derived from the production function [equation ] using the data on total output and factor A intensities described above The parameters b and b governing the size of the CEEC and EU grain markets and , respectively were likewise calibrated from available price and quantity figures using an own-price elasticity of demand for food of -0.3. The costs of enterprise restructuring, and the effectiveness of non-distortive government support for agriculture in lowering production and restructuring costs, are exploratory estimates.13, 14 The constructed model was used to explore a set of questions concerning the effect of various government policies on outcomes in the CEECs’ agricultural sectors. These experiments . . consider policy issues of short-, medium-, and long-tenn importance: price and output stability, farm enterprise restructuring, and convergence with EU nonns. The experiments focus on the interaction between policies that CEEC governments adopt in the current transitional period, and the policies that will apply during the first few years of the CAP. Four sets of pre-accession policies are considered: a laissez-faire approach, a gradual convergence of policy to EU norms, an immediate implementation of “CAP-like” policies, and an activist approach focusing ori targeting government intervention to nondistortive interventions.

For each of these policy paths, the effect on prices and output ; on farm enterprise restructuring; and on the welfare of producer, consumers, and society overall, is investigated. We then examine the effect of accession to the EU in 2001, under alternative assumptions about the form of the accession contract. Taking as given the state of the economy after the implementation of a consistent transitional policy, the effects associated with full admission to an unreformed CAP; with a two-tier CAP system; and with a no-entry scenario are examined. In this set of experiments, the CEEC government follows the advice of “Big Bang” advocates, addressing the agricultural sector with a “hands-off’ approach during the 1993-2000 period. No expenditures on credit subsidies, public goods, or intervention purchases are incurred. The sole protection granted the market is a modest 20% tariff on imports. The result is stagnation. Inefficient producers, lacking any access to long-term credit, and able to borrow for the short term only at usurious rates of interest, are unable to generate the surpluses necessary to undertake efficiency-enhancing investments. The restructuring process barely moves forward; the only notable changes in farm organization come as already-healthy small farms merge into larger units in search of economies of scale . As land is under the control of inefficient production units, output remains low, and prices are governed by the need to purchase expensive imports and to make up for domestic shortfalls . Since the CEEC is presumed to accede to the European Union in 2001, the fate of the agricultural sector in the period after 2001 is affected by the treatment of agriculture under the treaties of accession. Here three possibilities are explored.In this set of experiments, CEEC governments anticipate accession to the EU by instituting preaccession policies that converge gradually with those that will prevail after accession. Thus, price supports and tariff rates are slowly increased over the period, 1993-2000. In addition,raspberry plant container the government expends funds on public goods and restructuring subsidies at modest levels during this transition period. We explore two possibilities, one in which the final accession contract to which the economy converges involves full entry into the CAP, and a second in which the accession contract is a two-tiered version of the CAP, as described above. We also include a modest budget for public goods and restructuring subsidies. As the price floor and tariff protection start to bind in 1997-98, output surges, generating producer surpluses large enough to finance restructuring investments. Taking advantage of the restructuring subsidies, farmers move essentially all land held in “inefficient” states into efficient states, so that by 1998 the inefficiency associated with the legacy of socialism has been squeezed out of the system . As production continues to climb, government spending increases, creating a drag on total social welfare. The EU entry has little effect on these patterns, and there is very little difference in outcomes between the two-tier and full-entry scenarios. Full entry into CAP does involve slightly higher government expenditure on price supports and slightly lower total welfare as a result, but these differences are quite small. Comparing the gradual convergence policy and the laissez-faire approach, the effect most immediately apparent is the difference in the degree of farm restructuring. Consumer surplus after 2001 is independent of the choice of pre-accession policies, since in both instances the prevailing prices are set by a binding government-imposed floor. However, the combination of modest price supports and non-distortive interventions creates the conditions for farmers to improve production efficiency and generate large gains in producer surplus, thus increasing total welfare, even with the modest increase in expenditures needed to maintain the price supports.

Pre-accession policies, rather than trading opportunities, are the most important determinants of this improvement. In this set of simulation experiments, we consider pre-accession policies that seek to bring agricultural supports into immediate alignment with those that will prevail after the accession period. Price floors and tariff rates are raised to CAP levels starting in 1993, and the CEEC government makes no expenditures on non-distortive supports. We again explore two possible forms of the accession contract, one involving full entry into the CAP in 2001, and a second in which a two-tier system is implemented. Comparing these results with those for the laissez-faire baseline, the immediate difference is that restructuring happens rapidly . The price supports and market protections act as a form of credit subsidy, allowing for rapid reorganization of inefficient agricultural enterprises into efficient holdings. As a result, output jumps .As prices are supported, these increases lead to gains in producer surplus which are overshadowed by sharper increases in government spending. Overall, however, outcomes are superior to those associated with laissez-faire policies, for the same reasons as state above: The key is to fmd a mechanism to finance restructuring. Side-by-side comparisons of the full CAP scenarios, one preceded by laissez-faire, the second by immediate implementation, show large improvements in social welfare associated with CAP-like pre-accession policies . , , Comparing the full CAP with the two-tier CAP shows modest differences. As might be expected, higher price supports place more cash into the hands of farmers more rapidly, and therefore induces faster enterprise restructuring, and hence generally higher levels of output and, of course, higher prices. Spending on public goods, in the two-tier version of CAP, shows up in higher levels of output in the long-run. Overall social welfare is slightly higher under the two tier regime than under the full CAP system. In the pre-accession period, restructuring takes place somewhat more slowly than in the other scenarios we have considered. However, the availability of long-term credit eventually drives all land into the control of efficient producers. In fact, the takeover of the large, efficient farms is, by the year 2000, almost absolute . The increased efficiency of production allows for a sharp rise in output, turning the country from an importer to an exporter. Prices nonetheless remain low and stable, dictated more by competition with world markets than by government supports.Producer surplus increases during the simulation period, reflecting the benefits to farmers of reduced production costs. Agricultural social welfare reaches its highest level amongst all scenarios . With respect to alternative accession arrangements, as we move from full CAP to two-tier CAP to no CAP, we are simultaneously decreasing price supports and tariffs while we increase moneys targeted to public goods. This movement corresponds to increase in output decreases in commodity prices, and a dramatic increase in agricultural social welfare. Thus, in this model, entry to CAP can be counter-productive if it requires a diversion of funds away from the maintenance of infrastructure and credit support. In this paper, a model of the agricultural sector for a generic Central and East European nation is developed that attempts to represent the key characteristics of these transition economies.

Population growth rates vary tremendously geographically

The A2 vision focuses primarily on Low Density Residential development, while the B1 scenario is relatively evenly split between Low, Medium, and High Density types, and AB32-Plus favors Medium and High densities. In addition to modeling these three scenarios, we examined additional versions of A2 and AB32-Plus in which we held population constant at the B1 level, and in which we held population, energy efficiency for both homes and vehicles, and utility-portfolio assumptions constant. This step provides a more analogous comparison of the land use influence within the three scenarios.After modeling urban-growth footprints for the A2, B1, and AB32-Plus scenarios, we calculated two main categories of GHG emissions for the new urbanization produced by each scenario. These calculations help provide a ballpark sense of the magnitude of emissions variations that can result from different policy approaches. For the sake of simplicity, we focused on emissions from the operation of motor vehicles and residential structures, not their life cycle emissions from construction and materials, because operating emissions are likely to be a large majority of the total in both cases and thus estimate the emissions trade offs of different urbanization trajectories. Within the transportation category of GHG emissions, many factors potentially affect individual travel decisions within a given type of urban location, including: land use mix and densities in the surrounding area; the availability, attractiveness, and price of alternative travel modes; the nature of the travel route network, including available route choices and congestion; social pressures, influences, and incentives; and self-selection of residents living in that type of urban location.

An extensive field of travel modeling has attempted to take many of these variables into account ,plastic gardening pots usually projecting travel in the future based on changes to current conditions. But given that travel, like many other behavior choices, is highly multi-determined, the process is problematic. Even within time frames of 20 years or less, travel forecasts are often highly inaccurate , and have had particular difficulties in incorporating variables related to land development and urban design. For a longer time frame such as 2050, social factors, economic conditions, and behavioral changes are likely to play a larger role, changing travel demand in unpredictable ways and making modeling even more problematic. Accordingly, we have chosen here to keep our calculations to a very basic level, simply extrapolating travel based on the existing range of travel differences between residents in areas of different densities. Household travel surveys done by SACOG show that household vehicle miles travelled vary by a factor of 6 between households in low-density and high-density locations . Some of this difference may be due to household size, composition, and demographics, but much is probably due to accessibility factors , including proximity to jobs, shopping, and schools, and alternative transportation modes. All of these environmental variables can be assumed to vary in unison: the B1 and AB32-Plus storylines assume improved balance of jobs, housing, and shopping within communities; improved bicycle, pedestrian, and public-transit options; rising gas prices and/or carbon taxes; and other economic incentives such as higher parking and road-use charges. Likewise, we can assume that these multiple changes tend to influence resident behavior in synergistic ways; for example, individuals drive less in a dense urban environment because people discover alternatives and are influenced by their peers. Thus, the assumption of a strong difference in driving between low- and high-density environments in 2050 for purposes of back casting scenarios seems reasonable.

Transportation emissions also depend on the fuel efficiency of motor vehicles. The average fuel efficiency of American vehicles remained more or less unchanged from the mid-1980s through the early 2010s, and so for purposes of illustration we assumed only modest further improvements in the A2 scenario until 2050. In the B1 scenario, we assumed additional efficiency increases of 2% a year , which would plausibly be brought about through improvements in the US national CAFE standards. For the AB32-Plus scenario, we assumed improvements of 4% a year . These assumptions are reasonable given recent efficiency improvements such as the spread of hybrid vehicle technologies. Despite accelerating globalization, food security in most of the developing world depends upon local food production. Most rural citizens in developing nations are involved in agriculture . Also, most locally produced goods are consumed locally, so increasing local productivity and slowing population growth remains a central food security issue . Over the past few years, energy price increases, bio-fuels and food scarcity have led to higher global food prices and price volatility.Rapidly increasing consumer prices limit food access. Increased price volatility reduces the benefit that small scale farmers derive from higher producer prices. Bio-fuels create competition between poor people in the developing world and energy consumers in the developed world. While higher priced commodities can bring direct benefits to farmers, these benefits will not be attained without significant and sustained investments in agriculture to increase production and in programs that reduce price volatility. High and volatile food prices make local production even more important for food insecure regions. With high prices and continually increasing transportation costs, producing more locally will become an important source of vitality for programs focused on reducing poverty .

Connecting new innovations in crop research with improved outcomes in the developing world will likely require public sector investments . The recent entry into small-scale agricultural investment by the Bill and Melinda Gates Foundation has added new vibrancy to efforts focused on understanding barriers to increasing yields and sustaining production in the face of climate change. This paper explores the convergence of three different trends: changes in agricultural production, changing climate and increasing population. Our assumption in the analyses presented is that that some countries will continue to have substantially less purchasing power than others over the next few decades. Although global trade is important, we assume that regions with small agriculturally based economies today are unlikely to transform themselves into industrial nations without first improving their agricultural productivity . The collision between increasing global food demand, competition for food with developed world energy consumers and increasingly difficult production conditions means that the food security situation is likely to worsen. Climate change will potentially bring reduced rainfall over some regions, and increased rainfall over others. The impact of these changes on agriculture must be anticipated and planned for . To this end, this paper examines potential trends in per capita cereal production and rainfall. While other foods make substantial contributions to diets in many areas,blueberry pot size per capita cereal production is indicative of general food availability in most developing countries. If the current rates of yield and population increases persist, many regions will see substantial declines in cereal availability. Greenhouse gas-induced reductions in monsoonal rainfall could exacerbate these grain shortages. On the other hand, relatively modest yield improvements in the least developed nations could lead to improved levels of per capita cereal production by 2030. If done sustainably, raising yields in these poorest nations may be the most technologically feasible way of addressing global cereal demands while reducing poverty and food insecurity.This study uses five sets of data : agricultural statistics, population, observed rainfall and simulated rainfall from 10 different global climate models . Based on simple equations describing the conservation of mass, momentum, radiation and other key dynamic factors, the global climate models simulate the full atmosphere at sub-daily time steps. These models may be constrained by observed sea surface temperatures , or run combined with ocean models in full simulation mode. When constrained by observed SSTs, the models produce circulations resembling the observed atmosphere. This analysis uses 24 of these 20th century simulations from 10 models to examine how well the models recreate observed seasonal rainfall variations between 1980 and 2000 rainfall observations. Our study also examines climate change simulations for the 21st century which predict a doubling of atmospheric CO2 concentrations by 2100 . When combined with ocean models and forced by projected trends in greenhouse gasses and aerosols, climate simulations can be used to examine the impact due to anthropogenic emissions into the atmosphere. This study examines 28 simulations from a standard emission scenario—the Special Report on Emissions Scenarios, SRESA1B. Individual simulations were weighted in such a way as to give each model an equal influence.Between 1961 and 1986, global total cereal yield increased by 89%, harvested area expanded by 11% and global per capita cereal production increased enormously, with a maximum in about 1986 .

Population, meanwhile, grew by 60% over those 25 years, resulting in an increase in per capita cereal production from 284 to 372 kg of grain per person per year. The last 21 years have seen slower population growth accompanied by slower yield improvements and a 2% reduction in the total area harvested. Surprisingly, over this period according to FAO and UN data, per capita harvested area, fertilizer and seed use have all declined by 20–30% . Presumably, higher yielding seeds, double cropping of rice, irrigation and more effective farming techniques have made up for lower per capita inputs. Per capita production is now about 350 kg of cereal per person per year, 6% less than the 1986 maximum. The relative stabilization of global per capita production hides the increased use of cereals for biofuels, alcohol and meat production, as well as significant variations between regions.Four regions have more than doubled their population since 1980: Eastern Africa, Western Africa, Middle Africa and Western Asia. Central America, Southern America, Northern Africa, Southern Africa, Southern Asia, and Southeastern Asia have seen their populations increase by more than 50%. Since 1980, two out of every three people born now live in Asia. Another one out of four lives in Africa. Across most of Africa, harvested area has increased substantially more than yields . In Eastern Africa, for example, yields have only increased by 25% since 1980, while harvested area increased by 55%. In Western Africa yields increased by 42% while harvested area increased by 127%. Yields, per capita harvested area and production remain very low. Across much of the rest of the world, harvested areas have remained fairly steady and yields have been the primary driver of agricultural growth. Our evaluation of FAO statistics shows that Southern America, Northern America, Eastern, Southern and Southeastern Asia have experienced greater than 70% increases in yields since 1980. Today, huge regional disparities in yields remain the norm. In 2007, cereal yields varied by almost 600%, from ~1,000 kg ha−1 in Middle Africa, to more than 5,000 kg ha−1 in Northern America, Eastern Asia, and Europe.4 Given that global and regional tendencies in per capita harvested area and yields appear fairly predictable on 10 year scales , we may plausibly use the observed trends to project to 2030. Table 4 presents the anticipated 2007 to 2030 changes, expressed as kg of cereals per person per year, and as percent changes compared to 2007. Figure 3 shows the historical and projected per capita cereal production for selected regions. Globally, a return to per capita production of the late 1960s, when per capita production was near 327 kg per person,appears likely. Eastern Asia may return to 1980s production levels and Southern Asia to 1960s levels . Declines in heavily populated Asia could re-expose millions of people to chronic undernourishment.5 Central and Southern America may experience 18–20% declines in per capita cereal production levels. Eastern and Middle Africa, however, may be affected most, with more than 30% reductions in already low per capita cereal production levels, with Eastern Africa changing from 131 kg per year in 2007 to 84 kg per person per year in 2030. United Nations projections suggest that the population of Eastern Africa will increase by 191 million people by 2030—a net increase second only to Southern Asia. While imprecise, it is instructive to evaluate simple food balance equations, examining the number of people who could be reasonably supported by the anticipated levels of grain production . We do this by calculating the theoretical population without food . Globally, the 2030 food balance estimates suggest that as now, we will still have enough grain to maintain our human population,albeit at a low baseline value of 1,900 calories a day. This estimate, however, does not take into account grain consumption associated with livestock production, biofuels or industrial applications.