College of Agriculture & Natural Resources
Permanent URI for this communityhttp://hdl.handle.net/1903/1598
The collections in this community comprise faculty research works, as well as graduate theses and dissertations.
Browse
5 results
Search Results
Item Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA(MDPI, 2020-11-25) Paul, Manashi; Dangol, Sijal; Kholodovsky, Vitaly; Sapkota, Amy R.; Negahban-Azar, Masoud; Lansing, StephanieCrop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions.Item MANAGEMENT OPTIONS FOR FARMERS FACING SALTWATER INTRUSION ON THE EASTERN SHORE OF THE CHESAPEAKE BAY(2023) Schulenburg, Alison Nicole; Tully, Kate; Plant Science and Landscape Architecture (PSLA); Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Rising sea levels, storms, and perigean spring tides push saltwater into coastal agricultural fields. This phenomenon, known as saltwater intrusion, alters nutrient cycling and damages crop yields. As sea levels continue to rise, saltwater intrusion will only worsen, with devastating consequences to agroecosystems along the coast of the Chesapeake Bay. Researchers and farmers alike are looking for solutions to adapt to and mitigate the effects of saltwater intrusion. Landowners may respond by altering their management practices. Farmers may 1) adapt by planting a salt-tolerant crop, 2) attempt to remediate soils with trap crops, 3) restore native marsh grasses, or 4) abandon fields altogether. My project investigates the survival of different crops and plant treatments under saltwater-intruded conditions and the potential for these plants to survive and to remove excess nutrients (e.g. sodium and phosphorus) from the soil, with the overall goal to benefit both the farming community and water quality in the Chesapeake Bay. Results from this study will help inform new management practices to increase soil health and maintain crop yields. Finally, the goal of this work is to guide local best management practices and potential easement opportunities for landowners facing saltwater intrusion, and ultimately determine optimal strategies for climate resilience.Item Essays on Climate Change Impacts and Adaptation for Agriculture(2013) Ortiz Bobea, Ariel; Just, Richard E; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Over the past twenty years economists have developed econometric approaches for estimating the impacts of climate change on agriculture by accounting for farmer adaptation implicitly. These reduced-form approaches are simple to implement but provide little insights into impact mechanisms, limiting their usefulness for adaptation policy. Recently, conflicting estimates for US agriculture have led to research with greater emphasis on mechanisms including renewed interest in statistical crop yield models. Findings suggest US agriculture will be mainly and severely affected by an increased frequency of high temperatures with crop yield suggested as a major driver. This dissertation is comprised of three essays highlighting methodological aspects in this literature. It contributes to the ongoing debate and shows the preeminent role of extreme temperature is overestimated while the role of soil moisture is seriously underestimated. This stems from issues related to weather data quality, the presence of time-varying omitted weather variables, as well as from modeling assumptions that inadvertently underestimate farmers' ability to adapt to seasonal aspects of climate change. My work illustrates how econometric models of climate change impacts on crop production can be improved by structuring them to admit some basic principles of agronomic science. The first essay shows that nonlinear temperature effects on corn yields are not robust to alternative weather datasets. The leading econometric studies in the current literature are based on a weather dataset that involves considerable interpolation. I introduce the use of a new dataset to agricultural climate change research that has been carefully developed with scientific methods to represent weather variation with one-hour and 14 kilometer accuracy. Detrimental effects of extreme temperature crucially hinge upon the recorded frequency at the highest temperatures. My research suggests that measurement error in short amounts of time spent at extreme temperature levels has disproportionate effects on estimated parameters associated with the right tail of the temperature distribution. My alternative dataset suggests detrimental temperature effects of climate change over the next 50-100 years will be half as much as in leading econometric studies in the current literature. The second essay relaxes the prevalent assumption in the literature that weather is additive. This has been the practice in most empirical models. Weather regressors are typically aggregated over the months that include the growing season. Using a simple model I show that this assumption imposes implausible characteristics on the technology. I test this assumption empirically using a crop yield model for US corn that accounts for differences in intra-day temperature variation in different stages of the growing season. Results strongly reject additivity and suggest that weather shocks such as extreme temperatures are particularly detrimental toward the middle of the season around flowering time, which corrects a disagreement of empirical yield models with the natural sciences. I discuss how this assumption tends to underestimate the range of adaptation possibilities available to farmers, thus overstating projected climate change impacts on the sector. The third essay introduces an improved measure of water availability for crops that accounts for time variation of soil moisture rather than season-long rainfall totals, as has been common practice in the literature. Leading studies in the literature are based on season-long rainfall. My alternative dataset based on scientific models that track soil moisture variation during the growing season includes variables that are more relevant for tracking crop development. Results show that models in the literature attribute too much variation in yields to temperature variation because rainfall variables are a crude and inaccurate measure of the moisture that determined crop growth. Consequently, I find that third of damages to corn yields previously attributed to extreme temperature are explained by drought, which is far more consistent with agronomic science. This highlights the potential adaptive role for water management in addressing climate change, unlike the literature now suggests. The fourth essay proposes a general structural framework for analyzing the mechanisms of climate change impacts on the sector. An empirical example incorporates some of the flexibilities highlighted in the previous essay to assess how farmer adaptation can reduce projected impacts on corn yields substantially. Global warming increases the length of the growing season in northern states. This gives farmers the flexibility to change planting dates that can reduce exposure of crops during the most sensitive flowering stage of the crop growth cycle. These research results identify another important type of farmer adaptation that can reduce vulnerability to climate change, which has been overlooked in the literature but which becomes evident only by incorporating the principles of agronomic science into econometric modeling of climate change impact analysis.Item Post-bottleneck inbreeding accumulation reduces fitness in laboratory populations of Tribolium castaneum under environmental stress(2008) Choiniere, Ashley Danielle; Siewerdt, Frank; Animal Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Populations are often driven to extinction due to low genetic diversity. One major cause for loss of genetic diversity in a population is a demographic bottleneck. A demographic bottleneck was imposed on twenty-one populations of Tribolium castaneum using multiple strategies. After recovering to original census numbers, the populations were subjected to stressful environments, and fitness was quantified. There was a significant decrease in additive genetic variance in all populations as a result of the bottleneck event (P<0.05). As estimated inbreeding accumulation increased, there was a decrease in the mean of fitness related traits, such as adult weight, total progeny, fecundity and survivorship. This relationship was best explained using quadratic models and became even more significant when the populations were under stress. This suggests that both dominance and epistatic gene effects are playing a role in phenotypic expression of traits and that expression may be flexible, supporting survival and fitness.Item Adaptation of A/Mallard/Potsdam/178-4/83 (H2N2) in Japanese quail leads to Replication and Transmission in Chickens(2005-05-02) Sorrell, Erin Maureen; Perez, Daniel R; Animal Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Influenza is a single stranded, negative-sense RNA virus with a segmented genome that can infect avian and mammalian species. Influenza viruses from the avian reservoir do not seem to replicate efficiently in humans upon direct transmission. Therefore, an intermediate host is involved in generating mutations to create a more transmissible or an avian-human reassortant virus. Quail have been highlighted as a potential reservoir and intermediate host of avian influenza. To assess the potential of quail as an intermediate host, A/Mallard/Postdam/178-4/83, H2N2 was tested to determine if through adaptation in quail a mallard strain can replicate and transmit in quail, as well as other avian species. After six serial passages of lung homogenate a virus arose, which replicated and transmitted directly to contact quail. When chickens were infected with this quail-adapted virus replication and transmission were observed, while no replication was noted in the chickens infected with wild type H2N2 virus.