The Conservation Reserve Program Choice

The Conservation Reserve Program was first established by the Food Security Act of 1985, with the primary purpose of preventing damage to highly erodible soils, made worse by intensified farming practices. Since its inception, the CRP has grown to become the largest federal, private-land retirement program in the United States with an approximately $2 billion annual budget. The Agricultural Act of 2014 mandates a reduction in the enrollment cap from 32 million acres to 24 million acres by 2018. The reduction coupled with the higher than average commodity prices makes the decision of whether or not to reenroll in to the CRP a difficult one for producers with expiring land. Expiring lands will equal almost 2 million acres in the year 2015, and approximately 7.1 million acres over the life of the farm bill. This research will develop a computer based decision aid that incorporates all major aspects of the decision when considering enrollment in the CRP, to be used by landowners and producers. These considerations include eligibility, the Environmental Benefits Index (EBI), the producers bid level, and evaluation of practice options within the CRP and options outside the CRP. The goals of this research are to produce a computer web based decision aid, as described above, with specific emphasis on a few key outputs. These include a probability of acceptance measure, the Net Present Value of all options available to the landowner/manager, and a measure of what that landowner’s/manager’s optimal bid is. The methodology of this study relies on the use of simulation using the excel add-in Simetar. Users of the program are allowed to enter details about the land being considered for CRP enrollment that the decision aid then uses to test scenarios for the land. Five hundred randomized point estimates are generated and compiled as a cumulative distribution function comparison chart, stoplight chart, and several other customized output representations for the user’s consideration. This thesis details a test of an Agriculture and Food Policy Center representative farm. The results, given the input data taken from the farm, suggest that the least risky option for this farm with the highest net returns is to enroll the land in CRP. It is important to note that this is simply a test of one farm and not a recommendation for all producers. Also, the results could be changed given different assumptions about the producer’s goals. The study concludes that including risk in the decision making process regarding CRP enrollment is a critical factor when determining the most financially rewarding result. Including riskiness in the decision making process warrants the use of a decision tool, like the one presented in this thesis

Analyzing Animal Disease, Stocker Cattle Production Systems, and Policy Choices in Production Agriculture

Agricultural producers across a diverse set of enterprises face significant risk each year when planting begins, livestock are purchased, or a new investment is made in machinery or facilities. Participants in other industries face risk from financial markets, global trends, and the preferences of customers. Unique to agriculture is risk from biologically-induced time-lags in production, climate variability, invasive species and pests, and disease in addition to the risks faced by other industries. Where some industries are able to spread risk over dozens, hundreds, even thousands of shareholders, the risk from working in production agricultural commonly accrues to a single nuclear family, or a small number of relatives. Farm managers face different decisions daily, and a single choice can significantly impact profitability. The collection of research in the following essay models under widely different circumstances in which management must choose between options that represent significantly different levels of profitability. The first essay included in this research estimates the cost of a Cattle Fever Tick eradication procedure in South Texas to an individual ranch and government agencies. The second essay estimates average daily gain in stocker enterprises based on different levels of days on pasture, stocking rate, and supplementation, and determines whether days on pasture are significantly impacted by changing temperature and precipitation. The third essay determines the value of a theoretical mix of the agricultural revenue coverage (ARC) and price loss coverage (PLC) programs

Poo Power: Revisiting Biogas Generation Potential on Dairy Farms in Texas

Biogas created from anaerobic digestion on dairy farms can be used to generate electricity, produce coproducts, and reduce reliance on off-farm inputs. We incorporate risk into simulation models representing dairy farms in Texas and demonstrate the profitability of new anaerobic digester installation. Based on this market, results indicate projects that have low investment costs, receive grant support for construction, utilize coproducts, or have some combination of these factors have higher net present value at the end of the study period; however, even with generous grant support and high electricity prices, projects with average investment costs remain unprofitable

Regulation of HLH-2/E2A during Caenorhabditis elegans gonadogenesis

Organisms are comprised of many cells with multiple distinct cell types, each of which must be decided precisely to ensure proper formation of a functional organism. In C. elegans, the basic helix-loop helix transcription factor HLH-2 is required for the specification of the anchor cell, or AC. The AC arises from a group of four somatic gonad cells, all of which initially express HLH-2. Two of the four cells, which we call β cells, lose AC competence early and instead become ventral uterine precursor cells, or VUs. We call the remaining two cells α cells. One α cell becomes the AC, while the other becomes a VU. Which α cell becomes the AC is random—50% of the time one α cell becomes the AC, while the other 50% of the time the other α cell becomes the AC. The choice of which cell becomes the AC and which becomes the VU is called the AC/VU decision, and occurs through reciprocal signaling by LIN-12/Notch and its ligand LAG-2/DSL. At first, both α cells express similar levels of lin-12 and lag-2. As the AC/VU decision progresses, the AC expresses higher levels of lag-2, and the VU expresses higher levels of lin-12. By this time, HLH-2 is only present in the specified AC, while it is post-translationally degraded in VUs. The mechanism by which HLH-2 is degraded and the consequences of disrupting its degradation on AC specification are unknown. In this work, we studied the function and regulation of HLH-2 during two stages of somatic gonad development. First, we used long-term fluorescence microscopy to visualize HLH-2 over the course of somatic gonad development. We found that HLH-2 expression begins in the parents of the α and β cells a consistent amount of time after their birth, and that the parent cell that first expresses HLH-2 almost always gives rise to the α cell that becomes the VU, while the second cell to express HLH-2 gives rise to the AC. This led us to study the effect of a loss of hlh-2 activity in the α and β cells. We generated an α and β cell-specific hlh-2(0) allele using genome editing tools and found that LIN-12 protein is not present in the absence of hlh-2 activity. Based on this discovery, we conceived a model where HLH-2 expression biases the first-expressing cell towards the VU fate by endowing it with an edge in lin-12 activity. Next, we focused on restriction of HLH-2 to the AC. Typically, HLH-2 protein is degraded in VUs, which we hypothesized was a crucial step in restriction of the AC fate to a single cell. We found that in a lin-12(0) background, HLH-2 is stabilized in VUs even when the resulting cell does not become an AC, indicating that lin-12 directly promotes HLH-2 degradation. This led us to search for a lin-12-regulated factor that targets HLH-2 for degradation in VUs. We identified seven ubiquitin-related genes whose depletion resulted in stabilized HLH-2 in VUs, but surprisingly did not cause an AC/VU defect. We suspect that HLH-2 degradation in VUs is one of multiple negative regulatory mechanisms that ensure the robustness of the AC/VU decision. The following research contributes new insights into how stochastic cell fate decisions amplify noise to ensure a consistent and reproducible outcome

Analyzing Animal Disease, Stocker Cattle Production Systems, and Policy Choices in Production Agriculture

Agricultural producers across a diverse set of enterprises face significant risk each year when planting begins, livestock are purchased, or a new investment is made in machinery or facilities. Participants in other industries face risk from financial markets, global trends, and the preferences of customers. Unique to agriculture is risk from biologically-induced time-lags in production, climate variability, invasive species and pests, and disease in addition to the risks faced by other industries. Where some industries are able to spread risk over dozens, hundreds, even thousands of shareholders, the risk from working in production agricultural commonly accrues to a single nuclear family, or a small number of relatives. Farm managers face different decisions daily, and a single choice can significantly impact profitability. The collection of research in the following essay models under widely different circumstances in which management must choose between options that represent significantly different levels of profitability. The first essay included in this research estimates the cost of a Cattle Fever Tick eradication procedure in South Texas to an individual ranch and government agencies. The second essay estimates average daily gain in stocker enterprises based on different levels of days on pasture, stocking rate, and supplementation, and determines whether days on pasture are significantly impacted by changing temperature and precipitation. The third essay determines the value of a theoretical mix of the agricultural revenue coverage (ARC) and price loss coverage (PLC) programs

Supplemental Feedstuff Cost and Value Calculator -Beef Cattle Version 2.0: Supporting Information

This decision-making tool is intended to be used to compare the cost and value of different supplemental feedstuffs for beef cattle. In order to make these comparisons, the workbook automatically calculates nutrient cost for up to 5 different supplemental feedstuff options after unique information has been entered for each feedstuff option. This information includes purchase price, unit of purchase and storage, costs associated with transportation or delivery, storage, and feeding, as well as feeding frequency and shrink losses associated with storage, handling, and feeding. After entering supplementation information, which includes the number of head to supplement, amount of supplemental protein and/or energy to provide, and duration of the supplementation period, the workbook calculates the total expected cost of supplementation in order to meet those criteria. Additionally, this workbook allows the user to select whether a feedstuff option is self-limiting and define the expected daily intake of that feedstuff in order to determine if a self-limiting feedstuff option may be a viable option based upon the user-defined supplementation criteria