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Similar findings have been replicated in various crops and locations around the world

The amounts of greenhouse gas emissions produced, by feces, pesticides, and fertilizers, is more than all means of transportation, combined . As more space is needed for the farming of these animals, rainforests are cut down, and species habitats are destroyed; thus, killing off the populations . Because of the “efficient” way cattle, pigs, and chickens are slaughtered, food quality has declined, and even though 70 billion animals are slaughtered for food a year, 340.6 million never make it the the shelves of the grocery store. . If slaughter houses had glass walls, everyone would be vegetarian.Previous research shows that omnivorous diets cause individuals to be increasingly susceptible to a variety of chronic diseases . College students with unbalanced diets, lacking a sufficient amount of fruits and vegetables, face short-term and long-term effects. Short-term effects include decreased energy and focus, while long-term effects include risk of cardiovascular disease, osteoporosis and cancer. Students that are unable to plan meals, snack frequently, and lack time and money, find themselves eating an abundance of processed foods . A healthy diet enables students to have the energy and focus to study more efficiently, as the right diet is crucial in being successful and healthy in college. A study, conducted by Beezhold et al, shows the effects of a plant-based diet, a vegetarian diet, and an omnivorous diet, on an individual’s mental health. Individuals from the ages 25-60 years old were asked questions, via an online survey, regarding their diet, health, lifestyle, wellness, and questions that measured their stress, anxiety, and depression levels. The results showed that age and gender related directly to the levels of stress and anxiety. Overall, individuals with a pant-based diet, showed a decrease in stress and anxiety levels. This study shows how plant-based diets have a positive effect on an individual’s mental health; in addition to their physical health – which has already been previously proven . Alessandra Seiter, in her article “From My Eating Disorder to My Life’s Purpose” explains how she saved her mind, body, and spirit from being overtaken by her eating disorder,procona valencia by adapting to a plant-based diet. After a year and a half of strict meal times and cardio routines, Seiter was introduced to veganism.

At first, Seiter used veganism as another excuse to reject high calorie foods, and she used veganism to mask her eating disorder. After listening to Colleen Patrick-Goudreau’s Vegetarian Food for Thought podcast, Seiter realized the devastating injustices inflicted onto the beautiful beings that reside with humans. The pain and sorrow that Seiter felt towards the individuals inflicting this pain on innocent creatures, was enough to drive her out of her eating disorder. This article specifically describes how veganism can be the driving force into recovery and the power of healing that a plant-based diet has . Further investigation will show how it is sustainable for the University to adapt a plant-based menu — or at the very least, plant-based options — and how those options can provide pathways of health, prosperity, and sustainability of the planet and its inhabitants. In the Central Valley of California, eating a plant-based diet is extremely uncommon, as it is the prime area of animal agriculture, as well as part of the culture. Therefore, college students at the University of California, Merced, that have adapted the plant-based lifestyle are likely to have difficulty finding healthy foods that are in line with their eating habits. While dining at the University provides vegetarian options, they have yet to offer options that are strictly vegan. Supplying plant-based food options is a simple and easy solution when compared to the severe destructions of animal agriculture. If the University continues neglecting to provide healthy food options, individuals and the environment will greatly suffer. In addition to supplying more food options, the University should advocate for vegan clubs and demonstrate the unsustainability of animal agriculture. Workshops and courses should be offered to teach students the importance of being knowledgeable of their food choices. These clubs and workshops would show how animal agriculture is unsustainable –– farmers are unable to keep up with the growing population and the growing demand for meat, which leads to the destruction of rainforests, species extinction, ocean dead zones, water and air quality, climate change, and disease. The perfect opportunity to discuss and teach students about animal agriculture is in the required “CORE 001” class. The class addresses water conservation and the triple zero affect; however, it fails to mention the root cause of such deprivations and overuses.

The University of California, Merced will not reach their goals of sustainability without addressing animal agriculture. Thus, the University should add to their statement of sustainability that sustainability means the ability to provide enough food to nourish the world. Plant-based diets rely heavily on fruits, vegetables, whole grains, beans, legumes, nuts and seeds; therefore, individuals eating plant-based obtain a higher number of vitamins, minerals, phytochemicals, and fiber. Purchasing these foods saves an individual $750 a year. Health benefits for these individuals include a reduced risk of many conditions such as: type 2 diabetes, cardiovascular disease, heart disease, hypertension, stroke, obesity, and some cancers, because the cholesterol is not consumed, and plant-based foods are free of added hormones and antibiotics. In a well planned plant-based diet, little risks of deficiency exist, and the diet is fit for all individuals including children, pregnant women, and elderly . The students and faculty on campus would experience an increase in energy and focus, that is much needed to fit the high demands of student and teacher lifestyles. Thus, students struggling with stress, anxiety and depression, will find themselves overcoming such struggles. As the University shifts to offering more plant-based foods, the overall health, well being, and productivity of students and faculty will increase. As previously described, breeding, raising, and feeding animals for food is an extreme waste of the worlds natural resources. Agricultural land and the resources used in animal agriculture, takes up 40% of the earths land, while a plant based diet requires a significantly less amount of land, water, and fossil fuels. Ten billion individuals could be well nourished with the food that is grown to feed cattle, whereas only 82% of the starving children see food fed to animals that are sent to be eaten in westernized countries. Thus, as less of the worlds land is used for animal agriculture, more space is available for the growing population and the food used to feed the animals can be used to nourish the entire world. If the University can encourage and support individuals that live a plant-based lifestyle, other students and faculty will be influenced to follow suit, along with their families. Since the University is advocating that they are the most sustainable campus, they should be addressing the many destructions that animal agriculture has on the planet. Once they do, the University will be “the most sustainable” campus. As stated earlier, as the University begins to offer more plant-based food, the overall health, well being, and productivity of students and faculty will increase. Weather is a key input for agricultural production.

A vast economic literature is dedicated to the role of weather information in grower decision making, market outcomes, and commodity futures. On one hand, better information about the weather can help growers optimize their use of other inputs, increasing efficiency in production and avoiding costs related with uncertainty. On the other hand, some economic models can show—under some assumptions—that more precise weather information might not be welfare increasing, as ex-ante uncertainty about the weather can lead to extra investment in other inputs. That is, when growers have better forecast of adverse weather, output would be further reduced from its level under uncertainty . There is also some concern about weather forecasts acting as signals for collusion among growers,flower bucket but simple price mechanisms can technically reduce output and welfare with better weather prediction even in a competitive market . Notwithstanding these warnings by economists, the economic gains from weather information are usually deemed positive, even if their magnitude is sometimes contested . Much of the seminal economic literature on the value of weather information was written between the 1960’s and the 1990’s, when significant improvements in forecasting was achieved with the advance of computing power and complex meteorology models . This literature is based on the agricultural practices and available data of that time. While literature about the value of weather information seems to have plateaued in the 2000’s, perhaps as forecasting technologies matured and stabilized, the surge of precision agriculture could re-ignite interest in this topic. Heterogeneity within fields and precise growing strategies, based on exact measurement of weather variables , is increasingly the subject of research and technological application . Uncertainty regarding real-time weather on micro scales poses conceptually similar questions to those dealt with by the weather forecast literature in the past. At the same time, new discussions on the value of weather information and the government’s role in providing it have been revived with advances in remote sensing and satellite technology . The technical and scientific capabilities required to gather and analyze weather data, as well as the non-rival nature of weather information as a product, meant that much of the development of weather services has been done by governments. Johnson and Holt point out that this led to a significant economic literature, assessing the potential gains from better weather information given the public expenditures.

Their survey of the relevant literature mostly includes econometric studies, where the output gains from improved forecasting are estimated and the economic gains from providing them are then calculated per hectare. Other methodologies include survey based valuation, paired with economic data and modeling. Anaman and Lellyett assess the gains from a weather information system for cotton growers in Australia, finding the benefit-cost ratio of the system at 12.6 . Klockow, McPherson, and Sutter conduct a survey based study of the value of the Mesonet network in Oklahoma. Less than 4% of Oklahoma’s cropland is irrigated, and the modest value they find for Mesonet information mostly comes from risk management. Interestingly, there are few such examples of an economic study about a specific weather information system in the published literature, as opposed to numerous studies on the value of information for growers. Johnson and Holt do mention, for example, that weather forecast services in Sweden and New Zealand have gone through “extensive privatization”, but do not cite any articles analyzing these decisions. The first part of this dissertation is an analysis of economic gains from the California Irrigation Management Information System , a network of weather stations and data center run by the California Department of Water Resources. For over 30 years, this system has been used by growers, consultants, and other users in California agriculture. This chapter presents the preliminary findings from a thorough report on the value of CIMIS, showing substantial gains not only in agriculture but also in landscape management, regulation, research, and industry.Climate change poses a major challenge for agriculture, as predicted shifts in temperature and precipitation patterns around the world affect agricultural productivity . Early studies on climate change in agriculture first focused on the impacts of changing mean temperatures, and more recent empirical literature emphasizes the importance of temperature variance and extreme heat on yields, especially during the growing season . For example, Schlenker and Roberts show sharp drops in the yields of corn, soybean, and cotton, when exposed to degree days above 28–300C.Climate scientists affirm that heat waves will increase in frequency and duration as the process of climate change advances . Researching yield responses to high temperatures, especially when the relationship seems non-linear orthreshold like, is therefore essential for prediction of climate change effects on agriculture. This can only be done with adequate weather information. Chapter 3 presents an analysis of the yield response of pistachios to hot winters. This is also a temperature distribution tail problem, at least when looking at temperatures between November and March. Daytime temperatures in California winters have been rising in the past 20 years, and are predicted to rise further in the future. This can have detrimental implications for pistachios, a major California crop, but estimating the yield response function has been a challenge so far. I use CIMIS data and innovative techniques to recover this relationship and predict the potential threat of climate change to California pistachios.

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Climate models are widely used to study the effects of agriculture on climate

With respect to sociodemographic factors, mothers that are exposed to extreme levels of pesticide are more likely to be minorities and have lower education than the sample population as a whole. While we control for these factors, there is potential for the high exposure sample to differ in other unobserved ways that could yield a higher likelihood of adverse birth outcomes. If so, this would result in overestimates of the effects of pesticide exposure on adverse birth outcomes. Additionally, we measure pesticide exposure as all pesticide use on production agriculture in the 2.6 km2 PLS Section encompassing mothers’ addresses. We do so because the diversity of chemicals applied in the San Joaquin Valley is extensive and the cumulative effects of multiple exposures are not well understood. However, some chemicals or combinations of chemicals may not be relevant to reproductive risk. Thus, our coefficients are likely underestimates for individuals exposed to a disproportionately high fraction of chemicals of reproductive concern for their PLS Section, year and birth month. There is some indication that closer proximity to agricultural fields results in increased odds of adverse birth outcomes. For a study of this spatial and temporal breadth it is infeasible to directly measure distance from a sprayed field. However, for the San Joaquin Valley, PLS Sections that have any agriculture generally are agriculturally dominated. Furthermore, the PLS Section is roughly 2276 m on a diagonal. Thus it is highly likely that the vast majority of households in PLS Sections with pesticide use are within 1000 m of a treated agricultural field. If pesticides dissipate much more rapidly,cut flower bucket such that the effect is concentrated within 100 m of pesticide use, our study design would underestimate this relationship due to dilution with individuals living farther away from fields but still within the same PLS Section exposure.

However, for this to be occurring, the population residing on-farm or adjacent to fields must be much smaller than the broader population residing in the San Joaquin Valley for us to observe such small coefficients. Indeed, this makes intuitive sense for California, where farm workers overwhelmingly report living independent of their employers in houses or rental units, particularly if they have a spouse or children. However, our results may under predict adverse birth outcomes in regions where a larger proportion of workers reside in employer-provided housing on or adjacent to fields, where a larger fraction of pesticide are applied aerially, or where permissible chemicals are more environmentally persistent or toxic to humans. We also lack information on residence time at mother’s address and employment. Much of the San Joaquin Valley economy is driven by the agricultural industry. If farm workers were mostly migratory and followed the harvest, our measure of residential pesticide exposure would be inaccurate for this subset of the population. Yet, according to the National Agricultural Workers Surveys for 1996–2011, California farm workers, especially if they have a spouse or children in their household, are settled. Our measure of exposure would also be artificially high if women were applying agricultural pesticides during pregnancy. While ~18% of California farm workers are women, only 1.5% of women reported using pesticides in the past 12 months and 0% of women with a spouse or children had reported doing so. Women could get additional exposure via their spouses, and ~16% of male farm workers reported loading, mixing or applying pesticides in the past year. Finally, the San Joaquin Valley is well known to have substandard environmental quality, frequently exceeding EPA contamination levels for air quality. If such exposures co-vary with pesticide use and vary at small spatial and temporal scales, the coefficient on pesticide exposure could capture additional contamination despite our PLS Township-year and birth month controls. While we cannot be certain we have eliminated all sources of contamination that co-vary with pesticides, including a rich set of ambient air quality and temperature metrics did not change the basic results of this paper. In conclusion, there is a growing literature on the relationship between pesticide exposure and adverse birth outcomes. Yet, evidence of a causal link between infant health and agricultural pesticide exposure remains uncertain due to small samples and lack of maternal or birth characteristics.

Our study is the most comprehensive to date, bringing together the largest data file ever compiled on street-address level birth outcomes and fine scale exposure to agricultural pesticides. We provide robust evidence that there are multiple negative effects of residential agricultural pesticide exposure on adverse birth outcomes, but only for births exposed to very high levels of pesticides during gestation. The documented concentration of impacts in the extreme upper tail of the pesticide exposure distribution may explain why previous studies fail to consistently detect effects of pesticides on birth outcomes. Furthermore, the concentration of impacts in the extreme tail of the pesticide exposure distribution provides policy challenges and public health opportunities to balance these potentially serious but rare outcomes with the societal benefits of continued pesticide use.Although the response of agricultural systems to climate is drawing considerable attention because of the potential for a global food crisis, current understanding of how climate affect agricultural production is highly uncertain since the feed backs between them are not well studied. Agricultural systems are highly vulnerable to climate variability, where the area suitable for agriculture, the length of growing seasons and yield potentials are expected to change under warming scenarios [IPCC, 2007]. In addition, crop growth alters some important physical climate forcings, such as latent heat flux, shortwave radiation, long wave radiation and soil moisture. This two-way interaction is often referred to as a feedback, describing a nonlinear cycle between two systems. Clarifying the importance of these feed backs could improve regional climate simulations in agriculturally intensive areas and enable better prediction of crop production. Variability in atmospheric CO2, temperature and precipitation highly affect agricultural production. The elevated CO2 could increase photosynthetic productivity [Aoki and Yabuki, 1977; Cooper and Brun, 1967; Moss, 1962] and therefore lead to an increase of yield. Amthor [2003] reviewed the previous observations and suggested doubling CO2 could increase the yield by 31% in average. At the same time, double CO2 could lead to 34% reduction of transpiration and double water use efficiency [Kimball and Idso, 1983]. In one study, increase in variability of temperature and precipitation resulted in significant increases in yield variability and crop failures [Mearns et al., 1992]. Warming by 2-4 o C could results in substantial shortening of the growing season, and change of crop calendar, particularly in winter [Butterfield and Morison, 1992]. Furthermore, increasing temperature and precipitation could have different impacts on yields for different crops. For example, a simulation study indicated potato production was increasing while wheat and faba bean was decreasing with increased temperature, and increasing of precipitation had no effect on the yield of potatoes or spring wheat, but could reducing winter wheat yield [Peiris et al., 1996]. Meanwhile, agriculture also affects climate by altering the surface energy, water, and carbon cycle. Cropland plays a very important biogeophysical role in changing climate [Feddema et al., 2005; Foley et al., 2005; Pitman et al., 1999].

Agricultural expansion in business as usual scenario results in significant additional warming over the Amazon and cooling of the upper air column and nearby oceans [Feddema et al., 2005]. Crops alter the small-scale boundary layer structure [Adegoke et al., 2007], such as surface wind and boundary layer height, by increasing canopy height during the growth process. Compared to natural vegetation,flower display buckets cropland has higher albedo that alters the energy budget when converting between forest and cropland [Bonan, 2008; Oleson et al., 2004]. Cropland also alters the water cycle. Both field observations and modeling have shown that conversion of forest to cropland can reduce evaportranspiration and precipitation at the regional scale [Sampaio et al., 2007]. Moreover, agriculture and associated management practices were found to affect the carbon cycle [Lal, 2004]. Global simulation indicates a 24% reduction in global vegetation carbon due to agriculture [Bondeau et al., 2007a]. Growing biofuel crops at previously natural vegetation land could increase greenhouse gas emissions by 50% [Searchinger et al., 2008]. Both observations and numerical modeling are used to study climate effects on agriculture. Laboratory studies using growth chambers and greenhouses showed elevated CO2 could increase net photosynthesis [Aoki and Yabuki, 1977; Cooper and Brun, 1967; Moss, 1962]. These stuides had a short period measurements and the high CO2 concentrations were not realistic. Free air CO2 enrichment experiments [Ainsworth and Long, 2005; Ainsworth et al., 2002; Long et al., 2006] using long term observation confirmed some chamber experiment results that trees were more responsive than herbaceous species to elevated CO2, but crop grain yields increased far less than in previous enclosed studies. Regression models [Rosenberg, 1982] also have been employed to study how climate affects crop yield and this method is still widely used today [Diffenbaugh et al., 2012; Lobell et al., 2008b]. Finally, crop growth models enable yield prediction and hazard prevention.Climate models were first developed for numerical weather prediction in the 1950s, and had a very coarse resolution only contained atmosphere circulation. In 1960-1970s, the climate model included both ocean and atmosphere circulations. In 1980-2000s, the development of regional climate model and sub-grid physical process model not only aim to improve the forecasting skill but also to study the climate change. In climate model, the land surface model provides sensible, latent, and momentum flux for atmosphere model to solve the atmospheric equations. The potential climate sensitivity to land use change is determined by the difference between two simulations that differ only in land use. A key determinant in accuracy of such research is how well the land surface model simulates the surface energy fluxes . The development of land surface model is getting more and more comprehensive to reflect the reality [Bonan, 2008]. Early land surface models represented the physical processes using simple parameterizations. For example, the soil hydrology was represented as a bucket, which could hold some maximum amount of water filled by precipitation, with the excess water becoming runoff.

Currently, most land surface models include all the major parameterizations, such as vegetation photosynthesis and conductance, snow accumulation and melting, radiation transfer, and turbulence processes above and within the canopy, etc. Moreover, some advanced land surface models include the carbon cycle and dynamic vegetation growth. Coupling a land surface model that incorporates dynamic crop growth into a climate model enables simulation of the two-way interactions between climate and crop growth. Recent work incorporating crop growth models into climate models has revealed that dynamic crop growth strongly influences regional climate patterns by altering land surface water and energy exchange. Most of these studies have not rigorously evaluated results against observations of climate and crop variables. Further, interactions between crop growth and irrigation effects on climate are not well examined. The aim of the work is to improve a regional climate model by incorporating a land surface model that simulates dynamic crop growth. Particularly, my work focuses on the improvement and evaluation of the Weather Research and Forecasting Model with updated Community Land Model , a dynamic crop growth model, and an irrigation scheme. As the next-generation mesoscale numerical model, the standard version of WRF includes relatively simple land surface schemes, which potentially constrain model applications for studying the land surface and ecosystem-atmosphere feed backs. By adding the CLM into WRF, I expected an improvement in surface energy flux simulations. Therefore, I first validated the performance for the surface energy fluxes for four vegetation types across the continental of United States in the first chapter [Lu and Kueppers, 2012]. Since one problem in this model was related to the low crop LAI bias and lack of irrigation, I further incorporated the dynamic crop growth model and irrigation into a new version . I evaluated the crop growth and climate variables in the new version and the influence of dynamic crop growth on irrigation effects was quantified. In the third chapter, I used the coupled model to study irrigation effects on heat wave frequency, duration, and intensity.