Theses and Dissertations

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Open Access
Addressing nitrogen and water availability challenges in semi-arid maize cropping systems
(Colorado State University. Libraries, 2025) Donovan, Tyler, author; Schipanski, Meagan, advisor; Comas, Louise, advisor; Cotrufo, Francesca, committee member; Conant, Richard, committee member
In many parts of the world, access to irrigation is threatened as competition for water resources increases and water availability decreases. This includes the Great Plains Region of the U.S. where roughly 25% of U.S. irrigated cropland is located. Loss of irrigation threatens global food security as irrigated lands are highly productive; accounting for just 20% of cropland but responsible for 40% of agricultural production. Thus, there is urgent need for achieving high yields with less water. Many studies have been conducted to increase crop productivity with limited water, but the interactive effect of nitrogen (N) and water availability on crop response has received limited attention with variable conclusions. Additionally, the effect of varying N availability under different water levels on soil N mineralization (Nmin), contribution of Nmin to crop N uptake, and the recovery and fate of N fertilizer has been largely unexplored. Soil Nmin is an important source of N for crops therefore, quantifying Nmin rates and contribution to crop N uptake is important for N management. Additionally, minimizing N losses is an important goal for agroecosystems as N losses come with an economic and environmental cost. The general aim of my dissertation was to explore the effects of N availability on soil N cycling and crop response within maize cropping systems, an important irrigated crop in the Great Plains Region, under contrasting water availability. Examining field data from 2021 – 2023, I found that maize grain yield response to N was dependent on water. When water was limited, maize grain yield was maximized with ~ 200 kg N ha-1, with excess N being detrimental for all three growing seasons. This was true even during 2023, which was an extremely wet year, and had reduced N fertilizer rates due to higher pre-plant soil residual N. Maize N uptake continued to increase with N availability beyond 200 kg N ha-1, showing maize was not co-limited by N when water was limited water. Rather, excess N and subsequent N uptake had negative effects on root and shoot growth, potentially via effects on stomatal conductance and photosynthesis, leading to yield declines. Soil net Nmin surrounding peak maize N uptake exhibited an N × water interaction where increased N fertilization rate decreased net Nmin with full water but increased with N rate when water was limited. Soil N-acquiring enzyme activity, a proxy for gross Nmin, had a different response where it increased with N regardless of water. This could suggest N fertilizer increased plant available N through increased microbial mediated depolymerization of N containing compounds in the soil. The different responses were likely due to the exclusion of living maize plants and maize N uptake in the net Nmin incubation tubes. Across the entire season, both net Nmin and enzyme activity tended to be higher during maize vegetative stages than during early reproductive stages when N demands are the highest. A 15N tracer study revealed that recovery was high, and losses low and unaffected by N and water treatments. This suggests that lower N rates should have lower N losses. Maize N uptake increased with N rate, but primarily from 15N fertilizer, rather than non-N fertilizer sources such as soil Nmin. This could be due to the asynchrony between soil N supply and maize N demand. Additionally, microbial biomass N at the end of the season suggests that immobilization occurred, but primarily for non-N fertilizer sources. Immobilization of non-N fertilizer sources later in the season when soil Nmin rates are low and maize N demands are high likely led to maize acquiring N from N fertilizer to meet its N requirements. The wet growing season during 2023 made the water treatments negligible. Future studies with treatment differences in water availability could reveal how water availability affects fate and recovery of N fertilizer, as well as contribution of non-N fertilizer sources, such as soil Nmin, to crop N uptake with different N fertilizer rates. Overall, my findings show that water limited maize is not co-limited by N, and that excess N is detrimental to maize growth and yield. For limited water, reducing N fertilizer rate should reduce N losses while still maximizing yields and resource use efficiency. Reducing N fertilizer rate when water is fully available and maize N demands are high may be challenging. Higher N fertilizer rates appeared to increase bioavailable N through increased soil enzyme activity, however maize was not able to significantly increase uptake of N from sources other than the 15N fertilizer applied, such as soil Nmin, regardless of treatment. Maize was more reliant on N fertilizer rather than non-N fertilizer sources when supplied with high N fertilizer rates, while more reliant on non-N fertilizer sources when supplied with low N fertilizer rates. Management practices that increase internal N cycling, especially later in the season when maize N demands are greater, may help reduce the reliance on synthetic N fertilizer inputs thus reducing N losses without sacrificing productivity. Using field experiments from 2021 – 2023 I found that maize grain yield response to N was dependent on water. When water was limited, maize grain yield was maximized with ~ 200 kg N ha-1, with excess N being detrimental for all three growing seasons. This was true even during 2023, which was an extremely wet year, and had reduced N fertilizer rates due to higher pre-plant soil residual N. With limited water, maize N uptake continued to increase with N availability beyond 200 kg N ha-1, showing maize was not co-limited by N. Rather excess N and subsequent N uptake had negative effects on root growth, and potentially stomatal conductance and photosynthesis leading to yield declines. Soil net Nmin surrounding peak maize N uptake exhibited an N × water interaction where increased N fertilization rate decreased net Nmin with full water but increased with N rate when water was limited. Soil N-acquiring enzyme activity, a proxy for gross Nmin, had a different response where it increased with N regardless of water. This could suggest N fertilizer increased plant available N through increased microbial mediated depolymerization of N containing compounds in the soil. The different responses were likely due to the exclusion of living maize plants and maize N uptake in the net Nmin incubation tubes. For the entire season both net Nmin and enzyme activity tended to be higher during maize vegetative stages as opposed to early reproductive stages when N demands are the highest. A 15N tracer study revealed that recovery was high, and losses were low and unaffected by the N and water treatments. This suggests that lower N rates should have lower N losses. Maize N uptake increased with N rate, but primarily from 15N fertilizer, rather than non-N fertilizer sources such as soil Nmin. This could be due to the asynchrony between soil N supply and maize N demand. Additionally, microbial biomass N at the end of the season suggests that immobilization occurred and primarily occurred for non-N fertilizer sources. Immobilization of non-N fertilizer sources later in the season when soil Nmin rates are lower, and maize N demands are high, likely led to maize acquiring N from N fertilizer to meet its N requirements. The wet growing season during 2023 made the water treatments negligible. Future studies with more extreme water differences will help reveal how water availability affects fate and recovery of N fertilizer, as well as contribution of non-N fertilizer sources, such as soil Nmin, to crop N uptake with different N fertilizer rates. Overall, my findings show that water limited maize is not co-limited by N, and that excess N is detrimental to maize growth and yield. For limited water, reducing N fertilizer rate should reduce N losses while still maximizing yields and resource use efficiency. Reducing N fertilizer rate when water is fully available and maize N demands are high may be challenging. Higher N fertilizer rates appeared to increase bioavailable N through increased soil enzyme activity, however maize was not able to significantly increase uptake of N from sources other than the 15N fertilizer applied, such as soil Nmin, regardless of treatment. Maize was more reliant on N fertilizer rather than non-N fertilizer sources at the higher N fertilizer rate, while the lower N fertilizer rates were more reliant on non-N fertilizer sources. Management practices that increase internal N cycling, especially later in the season when maize N demands are greater, may help reduce the reliance on synthetic N fertilizer inputs thus reducing N losses without sacrificing productivity.
Embargo
Regenerative agriculture and soil carbon storage in the Upper Corn Belt
(Colorado State University. Libraries, 2025) Ellis, Elizabeth M., author; Paustian, Keith, advisor; Cotrufo, Francesca, committee member; Schipanski, Meagan, committee member; Manning, Dale, committee member
Land use conversion, agricultural mismanagement, and topsoil erosion have depleted global soil organic carbon (SOC) stocks in the top two meters of soil by an estimated 133 petagrams (Pg), resulting in a significant SOC debt. Regenerative cropping practices, such as no-till and cover cropping, are recognized for their potential to enhance soil organic carbon (SOC) stocks and bolster soil health, all while allowing producers to maintain commodity crop production systems. Evaluations of these practices are typically conducted through agricultural experiments with randomized and replicated statistical designs. While these experiments are essential for understanding the mechanisms behind changes in soil properties as a function of management, they often fail to capture the complexities of diverse agricultural settings and management choices. Through an interdisciplinary, system-level study of commercial farms in the Upper Corn Belt region, I evaluated how regenerative management affects SOC storage, erosion processes, and microbial community structure. Factors such as topography, time since adoption of regenerative practices, climate, and soil texture significantly influenced SOC stocks and microbial community structure. Slope and historical erosion emerged as a key control on SOC stocks, which is largely overlooked in current process-based models. I present a method for coupling estimated soil erosion with the DayCent model to improve simulations of SOC stocks on farmland with slight slopes. I also discuss the unique challenges of simulating commercial farm scenarios using data collected from real-world farmers. The dissertation concludes with a collaborative, social science chapter on the impact of social networks on the adoption of regenerative practices in Iowa agricultural communities. In summary, this dissertation contributes to our knowledge of regenerative agriculture and its impacts on SOC storage, soil microbial diversity, and social connections in agricultural communities, including unique methods to measure, evaluate, and model these impacts.
Open Access
Soil health for the semi-arid west: a nexus of agricultural soil management and ecosystem services
(Colorado State University. Libraries, 2025) Trimarco, Tad, author; Ippolito, James A., advisor; Wardle, Erik, committee member; Harmel, Robert Daren, committee member; Seidl, Andrew, committee member
Our agricultural systems face increasing pressure to simultaneously intensify their operations while reducing the unintended environmental consequences of production. In the semi-arid western US, the most pressing concerns for the continued sustainability of agriculture include: 1) maintaining a healthy topsoil for reliable productivity, 2) mitigation of water pollution from agricultural runoff, and 3) ensuring profitability of farms to maintain or improve quality of life for producers. These concerns have been studied individually but have rarely been connected empirically. Even fewer studies have attempted a holistic, systems-wide approach to soil health management in semi-arid regions, where irrigation is critical to maintaining robust production. To address this gap in the current research, I performed a series of soil health assessments across five sites in Colorado, USA using the Soil Management Assessment Framework and connected these soil health measurements to indicators of runoff water quality, water conservation, or economic welfare. These sites were a combination of small and medium-sized farms operated by either research staff at research farms or by small farmers on private land. The objective of the research was to monitor soil health on sites implementing Best Management Practices (BMPs) for soil or water conservation and evaluate the ecosystem service impact of these practices. Evaluated BMPs included: 1) conservation tillage under furrow irrigation, 2) transition from furrow irrigation to sprinkler irrigation, 3) installation of a vegetated filter strip, and 4) use of management-intensive grazing. The soil health impact of these BMP's was mixed; at some sites the long-term reduction in intensity of tillage had positive effects on soil health, whereas on others, the management of the field under deficit irrigation resulted in significant salinization of the soil subsurface. At the long-term conservation tillage site, empirical connections were established between edge of field water quality measurements and soil health indicators to identify that in these furrow-irrigated systems, improvement of both soil health and water quality can be achieved through improvement of infiltration and protection of soil aggregates. In irrigated systems, improvements of soil functioning to retain and store water is a critical ecosystem service. Furthermore, at this site, the economic impact and greenhouse gas mitigation potential of adopting conservation tillage with cost-sharing or carbon (C) offsetting and selling was assessed using a 12-year enterprise budget analysis. Results indicated that over the long-term, conservation tillage may be more profitable than conventional tillage, particularly when funding incentives are used to offset the early costs of adoption. Taken together, the results of these multiple studies indicate that management for water conservation may indeed improve soil health and economic outcomes, but continued monitoring of the soil system is necessary. This approach provides a blueprint for future systems-wide studies of conservation agriculture, which should consider hydrologic, agronomic, and socioeconomic impacts.
Open Access
Conservation management practice impacts on rangelands in California
(Colorado State University. Libraries, 2025) Banuelos, Ashley, author; Paustian, Keith, advisor; Cotrufo, Francesca, committee member; Havrilla, Caroline, committee member
Rangelands hold potential for mitigating climate change through soil organic carbon (SOC) storage. SOC plays a critical role in plant growth, soil structure and water retention, yet significant degradation of the world's soils poses major risks to forage production and water quality. To address this, California has promoted the adoption of conservation practices to restore SOC storage. Given California's diverse climatic zones, climate-specific conservation strategies are necessary, as climate influences the effectiveness of different practices. These practices not only affect overall SOC stocks but also influence how SOC is stabilized in the soil, particularly through the formation of SOC fractions - particulate organic carbon (POC) and mineral-associated organic carbon (MAOC). POC generally contributes to the short-term carbon pool due to its rapid turnover however, when microbial activity is limited, its decomposition slows, allowing it to persist in the long-term carbon pool. In contrast, MAOC is more inherently stable and primarily associated with long-term carbon storage. This thesis investigated the effects of three conservation management practices - riparian restoration, tree plantings, and perennial seeding - on SOC storage in California rangelands. We used a retrospective paired-site analysis, comparing 'restored' (i.e., locations where a conservation practice was adopted) and 'unrestored' sites (i.e., a nearby similar location but lacking adoption of a conservation practice). Restored sites varied by the time since conservation practices were adopted, providing a chronosequence approach to estimate SOC and SOC fractions (POC and MAOC) change over time. While overall SOC differences between restored and unrestored sites were inconclusive, clear trends between practice types emerged within the restored sites. In drier regions, perennial seeding had higher POC stock compared to riparian restoration and tree plantings. Climate significantly influenced apparent SOC accrual in tree plantings, with a rate of 3.1 Mg C ha-1 yr-1 observed in moist climates, while in drier climates, SOC stocks were lower in tree planting sites compared to the unrestored sites. However, soil under tree canopies had 9% higher SOC content compared with soil sampled between trees, outside the tree canopy. Canopy cover appeared to promote proportional contributions to both POC and MAOC, highlighting the potential of tree plantings to increase SOC stocks, in relatively cooler, wetter regions. These findings underscore the importance of climate-specific conservation strategies for maximizing carbon storage in rangelands, particularly given the challenges inherent in managing these dynamic ecosystems. The variability in the apparent response to conservation practice adoption from the retrospective paired-site analysis raised questions about potential confounding factors. While this approach offers an alternative to long-term experiments by leveraging existing conservation practices, it introduces inherent uncertainties, particularly concerning prior disturbances that may influence SOC storage. A key assumption of the paired analysis is that vegetation and soils were approximately the same on both sites within a pair before the adoption of conservation practice. However, even when controlling for factors such as soil type, topography, and current vegetation, differences in past land use - such as disturbance events occurring at one site but not the other - could have led to SOC stock differences prior to when conservation practices were implemented. These historical land-use differences may obscure or exaggerate the measurement inferred impacts of conservation practices, highlighting the need to account for site history when interpreting SOC dynamics in retrospective studies. To address this, we analyzed remote sensing imagery to evaluate site conditions, prior to conservation practice adoption, identifying disturbance events and assessing vegetation cover and soil exposure from historical observations dating back to 1984. Our analysis revealed that 12 out of 36 paired sites experienced a disturbance event, on only one of the sites within a pair, including mastication, tillage, and burn events, potentially confounding the assumption of similar SOC stocks prior to the time of conservation practice adoption. Additionally, restored sites with significant pre-treatment differences in vegetation cover and bare soil exposure often originated from more degraded conditions compared to the unrestored site in the pair. This suggests a potential selection bias toward implementing conservation practices on more degraded lands, emphasizing the need to account for pre-existing site conditions in retrospective studies. Integrating remote sensing into paired-site analyses enhances the accuracy of assessments of conservation practice effectiveness assessments on SOC dynamics. This study underscores the importance of both climate considerations in conservation management and the value of remote sensing tools for improving SOC research methodologies.
Open Access
Developing Internet-of-Things soil moisture sensor networks for improving irrigation management in turfgrass
(Colorado State University. Libraries, 2025) Aksland, Ian Brazil, author; Ham, Jay, advisor; Khosla, Raj, committee member; Qian, Yaling, committee member
The importance of efficient irrigation in turfgrass management is underscored by substantial water usage in urban landscapes. In many western U.S. cities, over 50% of the total annual residential water use is allocated to turfgrass and landscape irrigation. Unfortunately, 30 to 60% of this urban irrigation water is wasted due to improper irrigation scheduling. This research focuses on the development and testing of innovative Internet-of-Things (IoT)-based soil moisture sensor networks designed to help optimize irrigation management in turfgrass. Golf course fairways served as a test bed for the research. A second phase of the research focused on how spatial variability in soil type and other landscape properties might impact soil sensor sampling plans, including the number of sensors and their installation locations. The overarching goal was to explore technologies that could promote more widespread use of soil sensors in irrigation decision-making to control golf courses and other turf areas like parks, green spaces, and residential lawns. The first phase of the project involved the design and calibration of custom-made capacitive soil moisture sensors, termed DP7T, which measure both soil moisture and temperature. A custom IoT cellular datalogger and innovative below-ground housing were also developed to read the sensors and transmit the information to the cloud via a cellular modem. Detailed laboratory calibrations were performed in various soil types using temperature-controlled chambers. After calibration, the systems were field-tested on three golf courses. Calibration results highlighted the importance of including temperature corrections, and necessity to include a built-in temperature transducer in each soil sensor. After temperature correction, excellent soil-specific linear calibrations were obtained on the log transform of volumetric water content vs sensor millivolt output, but soil specific calibrations were required. Extensive field tests validated the reliability of both the sensors and IoT dataloggers under field conditions. Cellular IoT connectivity facilitated real-time data transmission and analysis to online user dashboards, providing real-time information for improved irrigation management. However, results indicated significant micro and macro-scale spatial variation in sensor output when three measurement stations were deployed along fairways at each course. The large variation in soil moisture on a fairway suggests that this degree of spatial variation will confound the use of proximal soil sensors as a tool for irrigation management in these systems. To better understand how spatial variability in soils and landscape features affected sensor readings, spatial soil variation along the fairways was mapped using electromagnetic induction (EM38). The electromagnetic EM38 data showed a positive relationship with soil moisture content across all three golf courses, and literature has pointed to a strong correlation between topography and soil variability. More research is needed to fully understand how to successfully merge EM38 mapping layers and live soil moisture data to precisely recommend which sprinklers need adjustment for optimal irrigation, but this project suggests a model for further studies. The integration of low-cost sensors with IoT systems in this study demonstrated the potential of this technology. However, more research is needed on how proximal soil sensors should be deployed to characterize spatial variability in soil moisture across the landscape effectively. This will likely involve optimizing the number and deployment locations of soil sensors to capture the most information with the fewest sensors and at the lowest cost, while still meeting the day-to-day needs of turfgrass water managers.
Open Access
Long-term biosolids applications to overgrazed rangelands improve soil health
(Colorado State University. Libraries, 2025) Buchanan, Cassidy, author; Ippolito, Jim, advisor; Blecker, Steve, committee member; Paschke, Mark, committee member
Overgrazed rangelands can lead to soil degradation, yet long-term land application of organic amendments (i.e., biosolids) may play a pivotal role in improving overgrazed rangelands in terms of soil health. However, the long-term effects on soil health properties in response to Single or Repeated, low to excessive biosolids applications, on semi-arid, overgrazed grasslands have not been quantified. Using the Soil Management Assessment Framework (SMAF), soil physical, biological, chemical, nutrient, and overall soil health indices between biosolids applications (0, 2.5, 5, 10, 21, or 30 Mg ha−1) and application time (Single: 1991, Repeated: 2002) was determined. Results showed no significant changes in soil physical and nutrient health indices. However, the chemical soil health index was greater when biosolids were applied at rates < 30 Mg ha-1 and within the Single compared to Repeated applications. The biological soil health index was positively affected by increasing biosolids application rate, was overall greater in the Repeated as compared to the Single application, and was maximized at 30 Mg ha-1. The overall soil health index was maximized at rates < 30 Mg ha-1. When all indices were combined, and considering past plant community findings at this site, overall soil health appeared optimized at a biosolids application rate of ~ 10 Mg ha-1. The use of soil health tools can help determine a targeted organic amendment application rate to overgrazed rangelands so the amendment provides maximum benefits to soils, plants, animals, and the environment.
Open Access
A meta-analysis of measured annual nutrient runoff from agricultural land in North America
(Colorado State University. Libraries, 2024) Hopkins, Austin P., author; Ippolito, Jim, advisor; Harmel, Daren, committee member; Mueller, Nathan, committee member; Ross, Matthew, committee member
Nitrogen (N) and phosphorus (P) are significant agricultural inputs and drivers of water quality. It is the focus of producers and government agencies to keep soil and nutrients in productive agricultural land and out of waterways. Field-scale runoff and water quality data are critical to understanding the fate of agricultural nutrients and mitigating their off-site transport; it is at the field-scale that agricultural management decisions are typically made. However, regional influences such as precipitation, temperature, and prevailing cropping and management practices also impact nutrient runoff. The goal of this dissertation was to quantify the effects agricultural practices have on nutrient loss from agricultural lands. The Measured Annual Nutrient load from Agricultural Environments (MANAGE) database was updated with 27 additional studies focused on N and P loss to bring the total number of site years to over 3,300. EPA level II ecoregions were assigned to each entry, and it was observed that the database covered much of the North American humid/semi humid agricultural landscape. In the early 1980's, the first compilation of nutrient export coefficients for specific land uses in the U.S. was completed. Building off that initial effort, the "Measured Annual Nutrient loads from AGricultural Environments" (MANAGE) database was developed in 2006 to make annual nutrient runoff data from agricultural land uses publicly available. MANAGE presents annual field-scale N and P runoff data, along with descriptive data such as land use, tillage, conservation practices, soil type, soil test P, slope, and fertilizer formulation, rate, and application method along with runoff, precipitation, and soil erosion data. Subsequent MANAGE updates added more studies and additional data fields (e.g., crop yield, nutrient uptake, fertilizer application timing) as well as runoff N and P data from forests and drainage studies from the Midwestern and Eastern U.S. Here, we update MANAGE to facilitate its use in regional analyses, expanding the database to 3326 site years of data, including 27 additional studies along with Level II ecoregion delineations for each of the 94 studies. Annual N and P runoff data are now available from 11 of the 50 North American Level II ecoregions, which represent the major U.S. agricultural regions. Surprisingly, many of the studies did not report information such as fertilizer application timing or crop yields, thus we strongly encourage future nutrient loss studies to collect important descriptive data along with response data. This contemporary data repository is freely available from the USDA Ag Data Commons (https://data.nal.usda.gov/dataset/measured-annual-nutrient-loads-agricultural-environments-manage-database) to support future scientific analyses, model evaluations, and management and policy decisions. In the present study, we used the recently updated MANAGE database to conduct meta-type analyses of N and P in runoff from cropland and grasslands for North American Level II ecoregions. Specifically, we analyzed annual N and P loads and the impact of land use, tillage, fertilizer timing, and fertilizer placement. We compared nutrient loads across ecoregions and found that Temperate Prairies had significantly greater median total N loads (11.7 kg/ha/yr) than all other ecoregions. We found that there was considerable variability between ecoregions and management practices making one size fits all best management practice recommendations difficult. When management practices were compared across all ecoregions, consistent trends were evident. Conventional tillage, incorporating fertilizer, preplant fertilizer application timing, and corn land use all had significantly higher median total N loads compared to other practices, at 19.5, 23.6, 12.3, and 33.0 kg/ha/yr respectively. We observed several notable differences between ecoregions, for example: 1) the Temperate Prairies, dominated by highly erodible cultivated land, had significantly higher median annual total N loads (11.7 kg/ha/yr) than the South Central Semi-Arid Prairies (2.4 kg/ha/yr) dominated by grasslands; 2) corn production tended to produce higher N and P loads than other land uses in the Mixed Wood Plains, Southeastern USA Plains, and Ozark-Ouachita/Appalachian Forests; and 3) no-till had the highest dissolved P loads in the Southeastern USA Plains and Temperate Prairies, but conventional tillage had the highest dissolved P loads in the Ozark-Ouachita/Appalachian Forests. These data – that have never before been compiled and analyzed by ecoregion - should prove valuable for improving regional understanding of nutrient fate and transport, informing field-scale agricultural management decisions, and launching more in-depth, multi-factor analyses. Common agricultural land management practices, as present in MANAGE, were also quantified based on the effect they had on N and P loads. Consistent trends were defined across ecoregions. Conventional tillage led to significantly greater total N load (19 kg/ha/yr) than conservation or no-tillage practices (5.9 and 6.8 kg/ha/yr respectively). Incorporating N and P fertilizers typically led to significantly higher total N loads than injection or surface applications. Total N (23 kg/ha/yr), for example, was greater than injection or surface applications (5.4 and 3.2 kg/ha/yr respectively). Fertilizer application timings associated with preplant or out of season applications also led to typically greater loads, with preplant and split (preplant and out of season) producing 12.33 and 16.0 kg/ha/yr. Lastly, corn production and to a lesser extent wheat and small grains were the most significant drivers of N and P load loss. Corn and wheat produced 33.0 and 5.9 kg/ha/yr of total N. The interaction of management decisions on one another was examined and quantified using a generalized linear model. We found that there were significant pairwise interactions between agricultural management practices. For example, conventional tillage generally increased nutrient loads when combined with surface fertilizer placement. We were able to produce a model aimed at predicting nutrient loads based upon fertilizer timing and placement, ecoregions, tillage, and land use that produced an R2 value of 0.92 and a mean absolute error (MAE) and root mean square error (RMSE) of 0.30 and 0.50 for annual dissolved N loads in runoff. Our results should lead to improved policy and management decisions and are of importance across a wide scale of management size from small scale farms to large scale farms, to governmental agencies managing soil and water resources across the continent. Based on results of this research, a proposed ecoregion nutrient load target was suggested, along with practices that could be implemented within those ecoregions to reduce the possibility of excess nutrient loads. The load target was set as the 90th percentile of the annual nutrient load produced under conservation tillage. Under these guidelines, the ecoregions that had the greatest volume of exceedances were the Southeastern USA Plains, Temperate Prairies, and the Mississippi Alluvial/Southeastern USA Plains, which are ecoregions in which conservation tillage and split application of fertilizer timing were shown to be effective in reducing nutrient loads.
Open Access
Cropping system, site and topographic impacts on deep soil carbon dynamics in no-till dryland agroecosystems
(Colorado State University. Libraries, 2024) Landers, Carolita E., author; Fonte, Steven J., advisor; Schipanski, Meagan, advisor; von Fischer, Joe, committee member
Long-term research of no-till management in the US Great Plains has shown that increasing cropping intensity can potentially increase soil organic carbon (SOC) and crop yields compared to traditional winter wheat (Triticum aestivum L.)- fallow management systems. However, due to varying climate and topographical factors, SOC accrual rates may change with time and soil depth. We sampled SOC in a long-term experiment 36 years after its establishment. The study is located across three sites in eastern Colorado, and it characterizes a gradient of potential evapotranspiration (PET) with multiple slope positions at each site. Thus, the objectives of this study are to understand 1) the effects of different crop rotations and cropping system intensification on SOC after 36 years in the surface soil in a no-till, dryland system., and 2) how climate and topography influence SOC and SIC dynamics in deeper layers (> 20 cm) and potentially interact with management. The cropping rotations examined were wheat-fallow, wheat-corn (Zea mays L.)-fallow, continuous summer cropping and a grass strip to represent the Conservation Reserve Program, all planted across three sites with similar annual precipitation but increasing PET and a slight slope gradient. We found cropping intensity, slope position, soil depth, and site (PET) all independently impacted SOC and SIC concentration (g kg-1) and stocks (Mg ha-1). Aside from the perennial GRASS treatment that consistently had higher SOC to depth, the management effect was seen most pronounced in the surface layers of the soil, but beyond 20 cm, SOC and SIC were influenced more by site and slope. As previously seen, the toe slope accumulated the most SOC in the surface layers; however, it did not persist in the deeper layers where the summit and side slope positions accumulated more. The findings of this research contribute to addressing the information gap surrounding deep SOC and SIC dynamics and their interactions with climate and management of no-till in dryland agroecosystems. We revealed that while the surface soil SOC responds to intensification, deeper SOC and SIC layers show a more complex interplay between climatic and topographic factors. These insights are crucial for developing sustainable agricultural practices and enhancing carbon sequestration to inform climate change mitigation strategies in the Great Plains.
Embargo
Cover crop effects on the soil microbiome and microbially mediated soil functions
(Colorado State University. Libraries, 2024) Yerlan, Arsen, author; Schipanski, Meagan, advisor; Wrighton, Kelly, committee member; Prenni, Jessica, committee member
Cover crops are often grown to improve soil health through changes in soil physical, chemical, and biological properties. Currently, there is growing interest in identifying how soil microbes may mediate some of the benefits provided by cover crops. However, most studies analyzing cover crop effects on the soil microbiome and soil health have been conducted in controlled settings such as greenhouses for short-term effects and field studies have focused on accumulated, longer-term effects. We conducted a short-term field experiment in northern Colorado with four different cover crop species: cereal rye (Secale cereale), hairy vetch (Vicia villosa) rape seed (Brassica napus), and sorghum (Sorghum bicolor) planted in August 2022 as monocultures and a no cover crop control to research these effects within a field environment at the time of cover crop termination in May 2023 and into the subsequent maize cash crop. During the respective seasons, cover crop and maize shoot biomass and bulk and rhizosphere soil were sampled. Soil samples were analyzed for soil extracellular enzymes L-leucine aminopeptidase (LAP), β-1,4-N-acetyl-glucosaminidase (NAG), β-glucosidase (BG), and acid phosphatase (PHOS); dissolved organic carbon concentrations (DOC); inorganic nitrogen concentrations; and soil aggregate stability. Only rhizosphere soil was used for soil microbiome analyses. Of all the cover crops, cereal rye and hairy vetch accumulated the most shoot biomass but did not differ from each other, and maize shoot biomass did not differ across treatments. Prior to cover crop termination in the spring, only rape seed stimulated LAP enzyme production compared to the control. Rape seed and cereal rye treatments had greater DOC concentrations than sorghum, and bulk soil DOC concentrations were greater than the rhizosphere. Inorganic nitrogen concentrations were lowest in cover crops that accumulated the most shoot biomass, i.e. cereal rye and hairy vetch. Soil aggregate sizes increased under living cereal rye relative to the control. Cover crops had several legacy effects that persisted into the maize crop, but these were not consistent with the effects found prior to termination: cereal rye stimulated BG and PHOS activity compared to sorghum. BG enzyme activity and DOC concentrations were greater in bulk soil compared to rhizosphere under the maize crop. Despite finding differences in cover crop effects on soil properties, we found no differences in microbial diversity indices or structure. However, under living cereal rye, one organism classified as genus Massilia was found to be enriched compared to the control but did not correlate with any measured soil functions. We were able to match our 16S BLAST results with a database to match with 15 MAGs at >97%. Our research confirms findings from studies performed in controlled settings that within a single season cover crops can modify the soil microbiome at an organismal level and influence soil functions, and our results suggest that frameworks built to describe soil microbiome and soil health dynamics are also applicable to the field. We also show that 16S taxonomic results may soon be useful in proposing potential microbial function, given that such MAG databases continue to be improved. Overall, this research contributes to the linking the soil microbiome with cover cropping and soil health, with further implications likely being microbiome management for sustainable agriculture.
Open Access
Pathways of soil organic matter formation in agroecosystems as influenced by litter chemistry, root depth and aggregation
(Colorado State University. Libraries, 2024) Fulton-Smith, Sarah E., author; Cotrufo, M. Francesca, advisor; Paustian, Keith, committee member; Ojima, Dennis, committee member; Fonte, Steven, committee member
Soils contain more carbon (C) than any other terrestrial reservoir, and the increase of these C stocks has been targeted as a potential climate solution globally. Agroecosystems play a critical role in our ability to provide these climate solutions through increasing soil organic matter (SOM). There is significant potential for SOM accrual in agroecosystems due to the degradation of SOM typically observed in these systems. One promising approach to increasing soil C sequestration is through the selection of deep-rooted crops, such as Sorghum bicolor. However, significant questions remain about root inputs' ability to contribute to SOM in order to balance the greenhouse gas (GHG) lifecycle of a bioenergy feedstock. My dissertation aims to answer some of these questions as well as to propose a framework to integrate the study of SOM formation from crop inputs with soil aggregate structure. Bioenergy has the potential to emit fewer GHGs than other fuel sources, such as fossil fuels, yet there are some emissions during the transportation production of bioenergy feedstocks and fuels that could be offset by soil C sequestration. However, in annual bioenergy systems, aboveground biomass is typically removed from the system, meaning roots are the primary source of OM available to return to the soil. However, roots and shoots may differ significantly in their ability to contribute to SOM due to differences in litter chemistry. In Chapter 2, I conducted a field incubation to understand how sorghum root versus leaf litter, as influenced by their contrasting chemistry, affect the formation and stabilization of SOM. Using unique soil-biomass microcosms to incubate root or leaf litter in topsoil (0-30 cm) for 19 months in the field, I traced the fate of litter decomposition products by combining stable 13C and 15N isotope labeling with extensive separation of physical soil fractions, free or within different aggregate structures. I found that roots, which were lower quality than leaves, decomposed more slowly but contributed more efficiently to total SOM formation than leaves. However, leaves contributed more to the stable SOM pool (i.e. associated to minerals) while roots contributed more to less stable fractions (i.e. light particulate organic matter). Additionally, sorghum is known to produce roots to a depth of 2 meters. There is limited understanding of how roots deeper in the soil (e.g., below 30 cm) lead to SOM formation and stabilization. In Chapter 3, I used the same microcosm approach as in Chapter 2, with roots that were incubated up to a 90 cm depth to better understand how depth influences the ability of roots to contribute to the formation of SOM and what role aggregates play in this process. Results of this study showed that differences in root decomposition dynamics with depth resulted in greater accrual of root litter C in more stable mineral associated SOM pools in the surface depth while there was slower decomposition and greater accrual in the less stable particulate organic matter fractions in the deep soil. Interestingly, most of the stable fraction was recovered within soil aggregates, particularly microaggregates. The results of these experiments emphasized the important role of microaggregates in modulating SOM dynamics. In Chapter 4, I used the information gleaned from Chapters 2 and 3 as well as advances in the SOM research community to speculate on the role of aggregation, specifically microaggregates, in moderating SOM formation by presenting a conceptual framework that integrates aggregates within our current understanding of particulate and mineral associate SOM dynamics. Overall, my dissertation addresses fundamental questions about our ability to increase SOM levels and resulting soil C accrual through the production of a deep-rooted crop through a field incubation. At the same time, I have connected these relevant results to the broader SOM research community by presenting a novel conceptual model that advances our current SOM framework. My hope is that this will be a valuable contribution to the field and spark discussion and future research.
Open Access
Soil health indicators for water-limited regions: sensitivity to compost and cropping intensification
(Colorado State University. Libraries, 2024) Noble Strohm, Tess, author; Schipanski, Meagan, advisor; Fonte, Steven, advisor; Ross, Matthew, committee member
In the water-limited agroecosystems of the Great Plains, USA, management strategies such as compost application and cropping system intensification have been promoted to increase soil health and help adapt to climatic variability. However, accurately assessing soil health to support production systems in such regions hinges upon a selection of indicators sensitive to management and linked to essential soil functions, especially those related to soil water dynamics. Using a suite of soil physical and biological parameters, this study assessed the effects of management on soil health metrics and evaluated the extent to which these metrics were related to soil water dynamics utilizing long-term studies in Akron, CO, and Clovis, NM. Soil physical indicators included aggregate stability (mean weight diameter; MWD), bulk density and saturated hydraulic conductivity, while biological indicators included measures of soil macrofauna and microbial communities. Compost application was the primary driver of increased aggregate stability and abundance of soil biota at both sites, though effects of cropping system intensification were observed for some indicators. Measures of soil microbial abundance were correlated with MWD, but saturated hydraulic conductivity was generally not correlated with other measured variables. Our findings indicate that MWD and microbial abundance are linked and sensitive to management, and further research to connect measures of soil biological and physical health to soil water dynamics in semi-arid systems is necessary to develop regionally relevant frameworks for soil health assessments.
Embargo
Evaluation of salinity tolerance of pinto bean varieties
(Colorado State University. Libraries, 2024) Paul, Winie Sharsana, author; Davis, Jessica G., advisor; Qian, Yaling, committee member; Andales, Allan, committee member
Salinity is an abiotic stress restricting agricultural crop production globally, primarily in arid and semi-arid areas. Saline soils are characterized by the accumulation of dissolved salts in the soil solution, which inhibits a plant's ability to absorb water and nutrients. Many crops are affected by high concentrations of salt in the soil. Dry edible pinto beans (Phaseolus vulgaris), very important in human nutrition around the world, are sensitive to salinity, and yield losses can occur in saline soils greater than 2 dS/m. The objective of this study was to assess the salinity tolerance of regular and slow darkening pinto bean varieties by evaluating the effect of different salt types on pinto bean germination, growth, and production. This project included three experiments: germination, greenhouse, and field studies. For the first two experiments, six varieties of pinto beans were evaluated: three slow-darkening pinto beans (Gleam, Mystic, Lumen) and three regular pinto beans (Othello, Cowboy, SV6139). In the germination experiment, treatments were arranged in a randomized complete block design with five replications, three saline solutions (NaCl, CaCl2, MgSO4.7H2O (MgSO4)), and control (distilled water) at 0.05 M, 0.1 M, and 0.15 M concentrations for each salt. For the greenhouse experiment, saline solutions with the same electrical conductivity (ECe) (dS/m), control (distilled water) and the six pinto bean varieties were organized in a Complete Random Design (CRD) with 10 replicates. The field experiment was an observational study where six pinto bean varieties: three slow-darkening pinto beans (Gleam, Mystic, Vibrant) and three regular pinto beans (Othello, Cowboy, SV6139) were planted in a field with a subsurface irrigation system to correlate yield to ECe for each variety. The results demonstrated that germination percentage, speed of germination and hypocotyl length decreased as the salt concentrations increased. Othello's vegetative and reproductive parameters were significantly higher compared to the other varieties in the greenhouse under the saline conditions. There was no significant correlation between yield and ECe in the field experiment. Results indicated that Othello's early maturity may have enabled it to perform better under salt stress conditions than the other tested varieties.
Open Access
Mapping Rhizoctonia root and crown rot resistance from sugar beet germplasm FC709-2 using new genomic resources
(Colorado State University. Libraries, 2024) Metz, Nicholas, author; Mason, Esten, advisor; Dorn, Kevin, committee member; Richards, Christopher, committee member; Gaines, Todd, committee member
Sugar beet (Beta vulgaris subsp. Vulgaris) provides about 35% of the refined sugar globally, and over half of the domestic production in the United States. Sugar beet are primarily grown in temperate climates from plantings in late spring and harvest in the fall. In the United States sugar beets are grown in four diverse regions: the upper Midwest (Minnesota and North Dakota), the far west (California, Idaho, Oregon, and Washington, the Great Plains (Colorado, Nebraska, Montana, and Wyoming), and the Great Lakes (Michigan). Multiple pests and pathogens continue to threaten tonnage and recoverable sugar yields. These are controlled through planting genetically resistant cultivars, agronomic cultural practices and chemical applications throughout the growing season. With a shrinking set of chemical and cultural control options to manage these production threats, the need for continued improvement upon host plant resistance is important. Decades of global breeding efforts to improved disease tolerance in sugar beet has been effective, but molecular and genomic guided breeding and disease resistance characterization in sugar beet is only now emerging. The most important root pathogen in sugar beet is Rhizoctonia Root and Crown Rot (RRCR) caused by the fungal pathogen Rhizoctonia solani. This disease is estimated to cause up to 50% localized losses, and regularly causes 57 million dollars in economic losses per year despite the use of tolerant varieties, chemical control, and cultural practices. Public sugar beet pre-breeding has developed hundreds of widely utilized lines with novel traits and combinations of traits, including for RRCR resistance. One such line, FC709-2, displayed exceptional tolerance to Rhizoctonia solani released from the United States Department of Agriculture sugar beet breeding program in Fort Collins, Colorado. This germplasm line is base for many RRCR resistant cultivars used by growers around the world. In this study, new germplasm, genetic, and genomic resources revolving around FC709-2 were developed. These resources include a new germplasm line derived from the purification of FC709-2. By using stricter selection pressure and single seed decent a more homogenous seed lot was created to be used by other breeding programs. A new reference genome created from a single highly RRCR resistant plant using the most recent sequencings and bioinformatic technologies will be used to discover genes that are responsible for a wide array of plant interactions. Last, novel QTLs associated with RRCR resistance were discovered using a bi-parental mapping population and bulk segregate analysis. Collectively, these results show that discovering novel RRCR resistance genes in a highly resistant germplasm line using a purpose-built reference genome is a streamlined and accurate method. With these new resources in place researchers around the world can use them to discover the genes responsible for RRCR resistance, create markers for more accurate selections, and follow the methods described to be implemented in other plant breeding programs.
Open Access
Impacts of cropping system and nutrient management on soil health and soil-borne pathogens in smallholder systems of western Kenya
(Colorado State University. Libraries, 2024) Mutai, Joyce Chelangat, author; Fonte, Steven J., advisor; Vanek, Steven, advisor; Stewart, Jane E., committee member; Schipanski, Meagan E., committee member
Crop production in smallholder farms is often limited by low soil fertility and the presence of soil-borne pathogens. Both challenges are associated with limited nutrient inputs, low rotational diversity, as well as small land holdings and the associated need for continuous cultivation in many smallholder systems. This dissertation explores the varied ways in which cropping systems and nutrient management strategies influence key soil health parameters and relationships with key soil-borne pathogens. Additionally, this research tests a suite of soil health bioassays to facilitate farmers' understanding of soil-borne pathogen status on their farms. I utilized a mix of observational research, short-term on-farm experiments, and long-term cropping system trials to understand: 1) the potential of simplified soil pathogen tests (for Fusarium, Pythium, and plant parasitic nematodes (PPN)) to provide insight on soil pathogen pressure, 2) the impact of dis- tinct nutrient management strategies (organic vs. synthetic inputs) on key soil health parameters and associated soil-borne pathogens, and 3) effects of cropping system (mono-cropping vs. more complex systems) on key soil health parameters and soilborne pathogens. To address these objectives, I first validated a suite of simplified soil bioassays to screen for PPN (e.g., Meloidogyne, Pratylenchus) and other key soilborne pathogens (Pythium and Fusarium) against formal laboratory methods. I collected soils across eleven on-farm trials in western Kenya (66 plots total), examining the impact organic vs. synthetic nutrient inputs on bean production. The soil nematode bioassays involved counting lesions on soybean roots and galls on lettuce roots and were strongly correlated with the abundance of gall forming, root-knot nematodes (Meloidogyne) and root lesion nematodes (Pratylenchus) recovered in laboratory-based extractions. Effectiveness of a Fusarium bioassay, involving the counting of lesions on buried soybean stem, was validated via DNA sequencing to identify Fusarium taxa and a pathogenicity test of cultured Fusarium strains. Finally, a Pythium soil bioassay using selective media clearly showed presence of the pathogen, with seed rotting and colonies observed. When examining nutrient management impacts on nematode communities, soils amended with manure had fewer PPN and considerably more bacterivores and fungivores compared to soils amended with synthetic N and P. Similarly, Pythium presence was lower in soils amended with manure, and higher levels of Fusarium in the same plots, likely due to the ability of various Fusarium taxa to exist as a saprophyte. Our findings suggested that relatively simple bioassays can be used to help farmers assess soilborne pathogens with minimal costs, thus enabling them to make informed decisions on soil health and pathogen management. In a second study, I used an exploratory approach to examine common cropping systems in western Kenya smallholders including: maize monocultures, maize-legume intercrops, maize in rotation with legumes and vegetables, and horticultural systems based on perennial crops and vegetable production. I sampled 35 farms to understand the impact of cropping system diversity and associated nutrient management on the abundance of Fusarium pathogens and LN. I found that organic inputs led to fewer lesion-causing nematodes compared to the inorganic inputs system, but an inverse relationship with Fusarium pressure was observed. Permanganate oxidizable C (POXC), particular organic matter (POM), total C, and soil pH were highly correlated with each other and negatively associated with LN pressure, while POM was positively correlated with Fusarium pressure. In a third study, I leveraged a long-term (18-year) field trial in western Kenya, testing cropping systems representative of smallholder farms. The long-term trial evaluates three cropping systems: 1) continuous maize monocrop, 2) maize in rotation with the woody legume, Tephrosia (T. candida), and 3) maize intercropping with soybean, and two nutrient management strategies: 1) application of farmyard manure (vs. not), and retention or removal plant residue, with all plots receiving regular fertilizer inputs. I sampled soil from 40 plots and measured soil physical (texture, POM), aggregate stability, bulk density), chemical (pH, total C, available P, POXC), and biological (Fusarium, Pythium, RKN, LN) properties. Results indicated that long-term manure significantly improved soil properties including pH, POXC, POM, total C, and soil aggregation. Moreover, manure significantly reduced Pythium and RKN pressure. Soil pH and POXC were associated with Pythium and RKN, such that plots with low pH and POXC levels had high abundance of these soilborne pathogens. Fusarium abundance on the other hand, was higher with manure and associated variables (aggregation, POXC, total C). In a fourth study, I utilized a long-term trial (45 years) in Kabete, central Kenya focused on integrated soil fertility management in continuous maize-bean rotation and the resulting impacts on soil characteristics was well-suited to this goal. I examined the effects of dry manure application, maize stover management (incorporated vs. removed), and synthetic fertilizers (N and P applied vs. no application) in a full-factorial experiment on a range of soil physical, chemical, and biological properties. Results indicated that application of organic inputs, especially manure, greatly improved soil organic matter (SOM) pools, soil pH, aggregate stability, and decreased bulk density, compared to synthetic fertilizers. At the same time, manure significantly reduced Pythium and LN pressure, while plant residues reduced RKN and Pythium considerably. In summary, the simplified soil pathogen bioassays and soil health analyses considered in this dissertation offer a powerful set of tools to help smallholder farmers and the local research or extension organizations that they work with to monitor and anticipate soil related challenges in their fields, thus supporting agricultural livelihoods and resilience. Additionally, these findings suggest that continuous mining of nutrients and minimal returns of organic matter (i.e. removal of crop residues and no manure application) appears to drive the decline of important soil health properties (pH, POXC, POM, aggregation, and total C), with important implications for soil-borne pathogens.
Open Access
Genome-wide association study and genomic prediction for end-use qualities in hard winter wheat
(Colorado State University. Libraries, 2024) Wondifraw, Meseret A., author; Mason, R. Esten, advisor; Haley, Scott D., advisor; Rhodes, Davina, committee member; Dorn, Kevin, committee member
Wheat (Triticum aestivum L.) is a widely cultivated crop used primarily for human food, animal feed, and industrial products. Numerous wheat-based products have unique nutritional and functional requirements. In the global market, wheat quality is one of the determining factors of wheat's price and baked product characteristics. Thus, after grain yield, improving these qualities is one of the major breeding objectives in wheat. Chapter One: This chapter outlines wheat's origins and global production. It explores major quality traits like water absorption and dough rheological properties, plus their measurement methods. Factors impacting wheat quality and pertinent genes are discussed. Finally, key challenges and opportunities around breeding for improved wheat quality are addressed. Chapter Two: This chapter presents a genome-wide association study of water absorption capacity in hard winter wheat. Lines were phenotyped using the solvent retention capacity test and genotyped via genotyping-by-sequencing. Forty-three marker-trait associations were identified across 17 chromosomes, especially on chromosome 1B, indicating polygenic influence. Co-localization between identified marker-trait associations and the genes that have effects on water absorption was done, and some quantitative trait nucleotides (QTNs) were located near gluten glutenin, gliadin, and glycosyltransferase genes, confirming water absorption is a complex trait affected by different flour components. Chapter Three: This chapter presents genome-wide prediction models to predict water absorption capacity using a training population of 497 hard winter wheat genotypes. Univariate models were compared to multivariate genomic prediction models using two validation approaches - cross-validation with 100 permutations and a 20-80 split and forward validation utilizing three years of data (2019-2021) from the CSU ELITE Trial. Multivariate genomic prediction models integrating highly correlated traits like break flour yield or all traits as covariates showed improved accuracy compared to univariate models in both validation approaches, demonstrating that incorporating related phenotypic traits as covariates in multivariate models can substantially improve the accuracy of predicting water absorption capacity. Chapter Four: This chapter evaluates genomic prediction models for bread-baking quality traits in 790 wheat genotypes over the 2014-2022 growing seasons. Marker-trait associations identified via genome-wide association study (GWAS) were incorporated as fixed effects. Three models were compared using cross-validation and forward validation: a model without fixed effect, with Glu-B1al allele (Bx7OE + 8 subunit) kompetitive allele-specific PCR (KASP) marker data as a fixed effect, and with GWAS-identified markers as fixed effects. Overall, the model with GWAS-identified markers as fixed effects showed the highest prediction accuracy. However, prediction accuracy decreased for bake loaf volume prediction specifically, suggesting that trait-specific tuning is needed to optimize genomic prediction models for different baking quality traits. These chapters reinforce the genetic complexity of water absorption capacity and baking quality traits in wheat. Polygenic inheritance was revealed for water absorption capacity. Genomic prediction that incorporates phenotypic covariates and GWAS-derived markers is the best approach to selecting water absorption and baking traits.
Open Access
Tracking the impact of wildfire on the soil microbiome across temporal scales
(Colorado State University. Libraries, 2024) Nelson, Amelia Rose, author; Wilkins, Michael J., advisor; Hall, Ed, committee member; Borch, Thomas, committee member; Rhoades, Charles, committee member; Wrighton, Kelly, committee member
As climate change progresses, the western United States is experiencing shifting wildfire behavior to more frequent and severe wildfires. Wildfires reduce soil microbial biomass and alter the soil microbiome community composition, selecting for "pyrophilous" microbial taxa with encoded traits that enable them to persist during wildfire or thrive in the soil thereafter. The soil microbiome is a key player in ecosystem carbon (C) cycling through the mediation of soil organic matter decomposition and stabilization. In addition to post-fire shifts in the soil microbiome, wildfire decreases soil C pools through combustion and alters C quality via fire-induced transformations to aromatic pyrogenic C (PyC). The intricate interplay between wildfire-induced alterations to soil microbiome composition and function, and subsequent ecosystem C cycling, remains poorly understood across different temporal and spatial scales. Leveraging multi-omics data alongside soil chemistry information (e.g., mass spectrometry) can offer insights into how shifting wildfire behavior may influence microbially mediated C cycling in forest ecosystems across the western US. To address this knowledge gap, I developed an extensive multi-omic dataset from burned Colorado subalpine coniferous forest soils collected over time (spanning 1 to 60 years following burning) and disturbance severity (low and high fire severity). This dataset includes 108 metagenomes and 12 metatranscriptomes, resulting in 1651 metagenome-assembled genomes (MAGs) that represent many of the dominant putative pyrophilous taxa previously identified in compositional studies. This dissertation presents the key findings derived from this comprehensive dataset, with the primary goal of addressing how wildfire impacts the soil microbiome with a focus on microbial interactions with soil C. Chapter 1 serves as a comprehensive literature review, providing an overview of prior research relevant to the research presented thereafter. It underscores the timely relevance of this dissertation research by examining how wildfire behavior is shifting globally with climate change and anthropogenic forcing. Given the critical role of forest ecosystems as significant global C sinks, understanding the repercussions of wildfires on ecosystem biogeochemistry is imperative. I broadly summarize previous research regarding severe wildfire impacts to soils and the soil microbiome and focus on existing knowledge gaps regarding the function of the post-wildfire soil microbiome across differing burn severities and time since fire. In Chapter 2, I characterize how burn severity impacts the soil microbiome one year post-fire in Colorado (CO) subalpine coniferous forests using soil samples collected in July 2019 from within the 2018 Ryan and Badger Creek fire burn scars that represent a burn severity gradient (control, low, moderate, and high severity burned soils). I used a suite of tools to understand both the impacts to soil chemistry and the soil microbiome, including Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) to characterize dissolved soil organic matter, 16S rRNA gene and ITS amplicon sequencing for soil microbiome composition, and coupled metagenomics and metatranscriptomics to identify shifts in soil microbial functional potential. The combination of these tools allowed me to characterize the entire soil microbiome, including bacteria, fungi, and viruses. From metagenomic sequencing, I recovered 637 MAGs, 1982 unique DNA and RNA viral populations, and 2 fungal genomes from low and high severity burned soil samples. I broadly found that Actinobacteria dominated the fraction of enriched and active bacterial taxa within high severity surficial soils and exhibited traits (e.g., heat resistance, fast growth, expression of genes for degrading aromatic PyC) that enabled them to survive the soil heating and thrive after the disturbance. Ectomycorrhizal fungi (EMF), key symbionts of coniferous trees and other plant taxa, were depleted in severely burned soils. Lastly, there were abundant viruses targeting dominant Actinobacteria MAGs that likely played important roles in assembly of the post-wildfire soil microbiome and serve as top-down controls of C cycling within the system. Overall, this study served as a holistic and comprehensive snapshot of the post-wildfire soil microbiome at one point in time and laid the foundation for forming hypotheses and guiding the subsequent studies. Building upon the groundwork laid in Chapter 2, Chapter 3 broadly evaluates the relative importance of putative pyrophilous traits identified between one year and 11 years following wildfire. Additionally, I explored the applicability of other proposed conceptual life history strategy frameworks (e.g., Y-A-S framework) in defining post-wildfire soil microbial dynamics. I utilized a series of soil samples collected from a chronosequence of CO wildfire burn scars representing 1, 3, 5, and 11 years following low- and high-severity wildfire. Using genome-resolved metagenomic approaches and combining this newly generated MAG catalog with the MAGs reconstructed from sequencing in Chapter 1 resulted in a total of 825 bacterial MAGs. Again, this dataset was coupled to various soil chemistry datasets, microbial biomass measurements (via PLFA), and marker gene sequencing data. I found that the potential for fast growth was an important bacterial trait driving dominance in the post-wildfire soil microbiome for up to approximately 11 years post-fire. Moreover, I observed that MAGs investing in traits aimed at acquiring diverse resources from the external environment often dominated severely burned soils, aligning with the 'A' strategy outlined in the Y-A-S framework. These insights suggest that microbial trait profiles play a pivotal role in shaping post-wildfire soil microbial successional dynamics. Furthermore, the study marks a significant step towards unraveling how trait-based frameworks can offer valuable insights into post-disturbance microbial ecology. In Chapter 4, the focus shifts to investigating one of the most extreme scenarios that can occur in a terrestrial ecosystem with severe wildfire: a burning-induced aboveground vegetation shift. Pile burning is a common fuel reduction or site preparation practice wherein logging residue is burned on the forest floor and, because of the high soil temperatures often reached during pile burning, can serve as a surrogate for studying impacts to soil caused by severe wildfire. Following clear-cut harvesting, pile burning can lead to the creation of persistence openings dominated by herbaceous plants within successfully regenerating conifer forest. In this study, a paired 60-year chronosequence of burn scar openings and surrounding forests that regenerated after clear-cut harvesting provided a unique opportunity to study soil microbiome changes associated with two distinct ecosystem development trajectories (i.e., burning-induced aboveground vegetation shift, regenerating coniferous forest). The primary objective was to identify whether the belowground soil microbiome exhibited resilience to a disturbance-induced aboveground vegetation shift. I collected soils from the aforementioned chronosequence and interrogated soil microbiome composition (via marker gene sequencing), functional potential (via metagenomics), and function (via laboratory incubations). There were compositional shifts in the soil microbiome that mirrored the ongoing aboveground vegetation shifts, with short-term changes to microbial community composition and C cycling functionality closely resembling a post-wildfire soil microbiome (e.g., PyC degradation). However, over the six-decade chronosequence the soil microbiome composition and function both displayed resilience, converging with that of the surrounding regenerating forest. This final research chapter extended the findings from the previous studies by exploring the longevity of wildfire impact to the soil microbiome in the extreme case of a burning-induced aboveground vegetation shift. The final chapter (Chapter 5) summarizes the key findings of this doctoral research and discusses potential research implications and applications along with future research directions and remaining knowledge gaps. In summary, the aims of this dissertation research were to identify how burn severity influences the soil microbiome composition and function one year post-fire (Chapter 2), assess the longevity of these impacts and the applicability of conceptual traits-based frameworks to the post-fire soil microbiome (Chapter 3), and evaluate the resilience of the belowground soil microbiome to a burning-induced multidecadal aboveground vegetation shift (Chapter 4). This research significantly advances our understanding of the impacts of wildfires on crucial forest ecosystems, with a specific emphasis on ecosystem C cycling.
Open Access
Deciphering the biological determinants on methane cycling from Gulf Coast wetlands
(Colorado State University. Libraries, 2024) de Melo Ferreira, Djennyfer Karolaine, author; Wrighton, Kelly C., advisor; von Fischer, Joseph, committee member; Melzer, Suellen, committee member; Wilkins, Michael, committee member
In Chapter 1, I introduce the importance of coastal wetlands for ecosystem services, including carbon storage, physical barrier for natural disasters, and habitat for diverse fauna and flora. Sea level rise is one of the main environmental risks affecting coastal wetlands, because of their geographic position. The effects of saltwater intrusion into freshwater wetlands can change established environmental conditions and vegetation coverage, which affects the functionality of various ecosystem functions they provide. These changes can also affect the methane emissions from coastal wetlands, which are major sources of this potent greenhouse gas. In this chapter, I evaluate the current knowledge of microbial methane production and consumption, including aspects of the ecophysiological adaptation to salinity, and the changes in the microbial ecological interactions modulated by increased salinity from marine water intrusion. In Chapter 2, I conducted a study to characterize the microbial communities and geochemistry of soil and water compartments in three coastal wetlands following a salinity gradient from Barataria Bay, Louisiana. To investigate the methane cycling microbial communities and their distribution on a freshwater flotant, Jean Lafitte swamp, and saltwater marsh wetlands, I collected soil and water samples under different vegetation coverage from each wetland. I analyzed the 16S rRNA gene sequencing and paired this data within situ methane fluxes and porewater concentrations. I also analyzed the geochemistry of the soil samples including profiling the anions, cations, pH, and redox conditions of soil and water samples across wetlands. The analysis showed that the diversity of methane cycling microbial communities decreased with increased salinity. Although the distribution and relative abundance of methanogen functional types was not impacted, with hydrogenotrophic methanogens being the most abundant across all wetlands. Looking at the methanotroph abundance and taxonomy in soil and water samples, I observed that swamp and saltwater wetlands share more methanotroph members in the water column, while the soils had more site-specific similarities. My research findings contribute to the understanding of methane cycling microbial tolerance to saltwater and may be used in future works to create more robust methane prediction models. In Chapter 3, I summarize the key aspects of microbial methane cycling in coastal wetlands and offer future directions for pairing geochemical and microbial data, including using an 'omics' approach and expanding investigation to more wetlands. We discuss the valuable findings these tools can give, contributing to a more accurate prediction of the metabolisms behind the ecophysiology and ecology of methane fluxes in coastal wetlands, and how targeting specific genes and metabolism can better help climate model efforts. In the Appendix sections, I give an expanded characterization of the wetlands site description, hydrology, vegetation and topological heterogeneity. I observed that, although relatively close in geographical position, each wetland has a different salinity range, vegetation type and microtopography that can influence the distribution of microorganisms in the soil and water. Here, we also analyzed the redox potential, dissolved oxygen, pH and geochemical compounds (bromide, nitrate, ammonium, acetate, sodium, potassium, magnesium, sulfate, chloride, and iron (II)) of these wetlands. We found no correlation between geochemistry with depth, but noticed higher salt contents in the saltwater marshes, and shared geochemistry between the swamp and freshwater flotant wetlands, as expected. Conclusively, this thesis contributes to the understanding of microbial communities to natural fluxes of methane in coastal wetlands and their interaction with the geochemistry of these ecosystems.
Open Access
Modifications to temperature-based estimates of consumptive water use by mountain meadows
(Colorado State University. Libraries, 2008) Temple, Darcy G., author; Smith, Dan H., advisor
Legal and engineering water communities in Colorado utilize the original Blaney-Criddle method to manage competing demands for water in mountain meadows, yet Blaney-Criddle underestimates in semi-arid, high-elevation environments. Blaney-Criddle consists of a consumptive use (CU) term, f, that is the product of mean monthly temperature, t, and percentage of daylight hours; and a crop coefficient, k, which accounts for crop variation and additional meteorologic effects. Low night temperatures at high elevations incorrectly weight f, and year-to-year variability among k values often results in significant variation between computed consumptive use and lysimeter measurements. Three modifications of the Blaney-Criddle temperature expression were tested against two existing temperature methods (Blaney-Criddle with conventional mean t, and Hargreaves) using lysimeter measurements from nine irrigated grass meadow sites in the upper Gunnison River basin (1999-2003). Use of two modified temperature expressions resulted in improved correlation of estimated Blaney-Criddle f with lysimeter CU. These improvements were similar to those observed when estimating with Hargreaves, which incorporates an additional term, Tdiff, the difference between maximum and minimum daily temperature. Climatological sources of variability in the crop coefficient, k, were also examined. The May-September crop coefficients k were better correlated with Tdiff (r = 0.28 to 0.54) than with mean t (r = 0.01 to 0.43). Specific regression equations based on Tdiff were used to develop crop coefficients from a dataset comprising the current study and three previous calibration studies in Colorado mountain meadows. Based on the standard error of estimate (SEE), estimates using the modeled coefficients more closely predicted CU than did estimates based on averages of locally calibrated k's (SEE difference of up to 5 mm mo-1). Correlations of solar radiation (Rs, the primary energy input to evapotranspiration) with alternative temperature expressions and Tdiff were improved over correlations of Rs with mean t, supporting the improved prediction performance of alternative temperature expressions and of the modeled k based on Tdiff. Those modifications can be applied successfully throughout Colorado mountain basins, and it is hoped that the same technique can be applied to other areas of the western U.S.
Open Access
Ground based active remote sensors for precision nitrogen management in irrigated maize production
(Colorado State University. Libraries, 2009) Shaver, Timothy Michael, author; Westfall, Dwayne G., advisor; Khosla, Rajiv, advisor
Precision agriculture can increase farm input efficiency by accurately quantifying variability within a field. Remotely sensed normalized difference vegetation index (NDVI) has been shown to quantify maize (Zea mays) N variability. Ground-based active remote sensors that can determine NDVI are commercially available and have been shown to accurately distinguish N variability in maize. There are several active sensors available but no studies directly comparing active sensors have been reported. Therefore, a study was conducted to evaluate active sensor performance and develop an in-season maize N recommendation algorithm for use in Colorado using NDVI. Previous studies have demonstrated an association of active sensor NDVI with maize N content and height. However, the NDVI from a GreenSeeker™ green NDVI prototype active sensor had not yet been tested when our study began. Therefore, the green sensor was evaluated to determine if differences in plant growth across MZ could be determined by the active sensor. Results show that the prototype active sensor did not record NDVI values that were associated with MZ. The NDVI from two different sensors (Crop Circle™ amber NDVI and GreenSeeker™ red NDVI) were then examined under greenhouse and field conditions. Results show that NDVI from the amber and red sensors equally distinguished applied N differences in maize. Each active sensor's NDVI values had high R2 values with applied N rate and plant N concentration. Results also show that each sensor's NDVI readings had high R2 values with applied N rate and yield at the V12 and V14 maize growth stages. An N recommendation algorithm was then created for use at the V12 maize growth stage for both the amber and red sensors using NDVI. These algorithms yielded N recommendations that were not significantly different across sensor type suggesting that the amber and red NDVI sensors performed equally. Also, each N recommendation algorithm yielded unbiased N recommendations suggesting that each was a valid estimator of required N at maize growth stage V12. Overall results show that the amber and red sensors equally determine N variability in irrigated maize and could be very important tools for managing in-season application of N fertilizer.
Open Access
A mechanistic approach to modeling saturation and protection mechanisms of soil organic matter
(Colorado State University. Libraries, 2009) Olchin, Gabriel Peter, author; Paustian, Keith, advisor
Simulation models have been used extensively as a research tool in the field of soil organic matter (SOM) dynamics and should embody our best understandings of the processes and mechanisms controlling these dynamics. Our objective was to develop and evaluate a SOM model based upon measureable soil organic carbon (SOC) fractions and optimize it against long-term tillage experiments in North America. This model will include (1) soil aggregate dynamics, with direct influence from tillage events; (2); and the mechanisms of SOM stabilization; and (3) explicitly address the concept of potential SOC saturation. The major proposed mechanisms for SOM stabilization-physical occlusion, organic recalcitrance, and organo-mineral interactions-have limited explicit inclusion in current SOM models.