Theses and Dissertations

Permanent URI for this collectionhttps://hdl.handle.net/10217/100398

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Exploring radar as a tool for studying migratory birds and their relationships with dynamic landscapes
(Colorado State University. Libraries, 2025) Jimenez, Miguel F., author; Horton, Kyle G., advisor; Yovovich, Veronica, committee member; Koons, David N., committee member; Ruegg, Kristen C., committee member
As a crisis-based discipline, conservation biology necessitates that we make timely management decisions to protect species based on the best available information. In effect, as new scientific tools become available, we must contend with simultaneously applying them in ways that provide novel insights and evaluating their limitations to assess the validity of those insights. The integration of radar with machine learning is one such tool that has revolutionized aeroecology, or the study of airborne organisms. Burgeoning methodologies leverage this integration, offering unique opportunities to understand how migratory birds are responding to large-scale environmental changes, such as urbanization and shifting light regimes. In this dissertation, my goal was to elucidate the promises and shortcomings of radar and machine learning as tools for informing migratory bird conservation management amid rapid global change. As a first step, I focused on validating observations from a local weather radar station. Weather radar systems have become a central tool in the study of nocturnal bird migration. Yet, while studies have sought to validate weather radar data through comparison to other sampling techniques, few have explicitly examined the impact of range and topographical blockage on sampling detection—critical dimensions that can bias broader inferences. In my first chapter, I assess these biases with relation to the Cheyenne, WY Next Generation Weather Radar (NEXRAD) site, one of the large-scale radars in a network of 160 weather surveillance stations based in the United States. I compared local density measures collected using a mobile, vertically looking radar with reflectivity from the NEXRAD station in the corresponding area. Both mean nightly migration activity and within night migration activity between NEXRAD and the mobile radar were strongly correlated (r = 0.85 and 0.70, respectively), but this relationship degraded with both increasing distance and beam blockage. Range-corrected NEXRAD reflectivity was a stronger predictor of observed mobile radar densities than uncorrected reflectivity at the mean nightly scale, suggesting that current range correction methods are somewhat effective at correcting for this bias. At the within night temporal scale, corrected and uncorrected reflectivity models performed similarly up to 65 km, but beyond this distance, uncorrected reflectivity became a stronger predictor than range-corrected reflectivity, suggesting range limitations to these corrections. Together, these findings further validate weather radar as an ornithological tool, but also highlight and quantify potential sampling biases. In my second chapter, I focused on using NEXRAD to study habitat transitions by migratory birds. During migration, birds regularly transition between terrestrial and aerial habitats. Yet, much of our understanding of migratory behavior is centered around either terrestrial habitat quality or atmospheric conditions separately, at relatively coarse temporal scales. I employed NEXRAD to study the dynamic drivers and relative importance of terrestrial, aerial, and sampling predictors as birds transition between the terrestrial and airspace boundary. I found that atmospheric conditions were consistently strong predictors of migration activity throughout the night, and across spring and fall seasons. Key sampling predictors, such as the time after local sunset, fluctuated throughout the night, with high importance shortly after sunset and diminishing importance in the middle of the night. Yet, terrestrial variables were not a strong predictor of nightly variation in migration activity. My results demonstrate that the importance of predictors of activity varies temporally, both within a single night and across seasons. These findings illuminate bird migration as a dynamic process, highlighting limitations and opportunities for employing weather surveillance radar to study transitions between terrestrial and aerial habitats. In my third chapter, I used NEXRAD to study migratory stopover in urban areas. Despite global expansion, the role of cities in macroecological processes remains understudied. Using radar estimates of migratory bird stopover across the U.S., I assessed urban landscapes' contributions to stopover and links to social demographics for 2,130 parks across 88 cities. Stopover hotspots disproportionately occurred on urban landscapes relative to land area, with nearly 50% of spring migration hotspots falling within Metropolitan Statistical Areas. The relationship between urbanization and stopover varied regionally, correlating negatively in eastern flyways and positively in western flyways. Finally, stopover was positively correlated with income but varied considerably, with many cities showing no effect or an effect in the opposite direction. This study highlights the significance of cities in a hemispheric-scale ecological process and demonstrate radar as tool for studying urban social-ecological interactions. Finally, in my fourth chapter, I investigated the effects of different light spectrums on birds in flight for the purpose of informing novel conservation management approaches. Artificial light at night (ALAN) has been shown to influence the behavior of migratory birds, yet how different light spectra modulate these effects is somewhat unclear. I conducted a field experiment across 31 nights at a remote site in northern Colorado using LED floodlights with white, red, amber, and blue lighting treatments during fall migration in 2023 and 2024. Using a vertically looking radar system, I quantified avian in-flight responses in migration traffic rate, flight height, and flight direction. I found that short wavelength, white light significantly reduced flight height, and this response was stronger than red, amber, or blue lights. Beyond providing insight into avian biology, my results could have implications for the conservation management of ALAN. Further, the ability to detect behavior changes from a small point source in a low-density migration system supports the notion that ALAN may be more pervasive than is often recognized. At its core, my dissertation is indicative of a broader shift in ecology and conservation science. Advances in remote sensing offer an opportunity to vastly expand the way we characterize social-ecological systems thereby diversifying the options we have for managing them. However, this "big data" approach must be validated and informed by local inference. My work emphasizes this point. As the integration of large datasets and machine learning become increasingly prominent in conservation biology, I urge the conservation community to explore their potential with creativity while remaining vigilant of the potential biases they may introduce.
Open Access
From genes to landscapes: direct and indirect interactions across ecological scales
(Colorado State University. Libraries, 2025) Folks, Christine, author; Ode, Paul, advisor; Smith, Melinda, committee member; Sloan, Dan, committee member; Bean, Dan, committee member
Interactions within and between species profoundly shape ecosystems, influencing community structure, ecosystem function, and evolutionary trajectories. This dissertation examines how direct and indirect interactions vary across spatial, temporal, and ecological scales using a multitrophic plant-herbivore network consisting of the invasive plant Russian knapweed (Rhaponticum repens), and its two biological control insects: the gall wasp Aulacidea acroptilonica and gall midge Jaapiella ivannikovi. I address three central questions: (I) What mechanisms drive plant-mediated interactions between insect herbivores? (II) Does R. repens ecotype selection influence its interactions with herbivores? and (III) How do climate variables and global change influence contemporary and future interactions between specialist plant-insect networks? To address these questions, I: (I) perform network analysis of plant-insect communities; (II) perform reciprocal transplants and phylogenetic analysis of R. repens populations; and (III) examine plant-insect-climate interactions across spatial and temporal scales. My findings emphasize the interconnectedness of ecological systems, revealing how plant-mediated effects drive indirect interactions between herbivores across ecological scales. Density-dependent interactions and gall community composition emerge as key drivers of herbivore performance, suggesting plant defense activation as the primary mechanism mediating asymmetric interactions between species. Rhaponticum repens exhibits evidence for rapid climate driven evolution in its invasive range resulting in dramatically increased resistance to herbivory. Climate modeling reveals complex responses to environmental change, including context-dependent herbivore facilitation under stress and unexpected species niche convergence under severe climate scenarios.
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Beyond the park: exploring informal green spaces, the provision of ecosystem services, and socio-spatial equity in U.S. cities
(Colorado State University. Libraries, 2025) Nelson-Olivieri, Jasmine, author; Bombaci, Sara, advisor; Angeloni, Lisa, committee member; Horton, Kyle, committee member; Pejchar, Liba, committee member
With accelerating global urbanization and development, urban parks are increasingly recognized as essential for promoting ecological resilience, public health, and social equity while serving as critical habitat for wildlife. Parks provide a myriad of ecosystem services to community members, from reducing heat islands and flood risks to promoting exercise and recreation. However, urban parks are often inequitably distributed in terms of size, quality, and access. Due to these inequities, some researchers have explored other, more informal green spaces to fill the void. Informal green spaces are transient areas of spontaneous vegetation that form due to other land uses such as street and railroad verges, irrigation ditches, and vacant lots. While these spaces are often overlooked, they may provide substantial ecosystem services in areas that have traditionally lacked them due to reduced access to managed park space. However, few studies have explored the potential equity of access and the presence of these spaces. Further, few have explicitly compared the ecosystem service provisioning of informal green space to that of formal green spaces in our cities. This dissertation arose from a desire to understand how informal green spaces serve urban inhabitants, both relative to formal green spaces, and whether they might offer untapped potential to mitigate environmental injustices in urban environments. This dissertation explores the structure, function, and equity implications of informal green spaces within urban environments, positioning them as critical but often overlooked components of sustainable city planning. Across three empirical chapters, I examine how informal green spaces compare to formal green spaces in terms of spatial distribution, ecological characteristics, and socio-economic outcomes. In Chapter 1, I analyze and compare the landscape metrics of both informal and formal green spaces across ten U.S. cities, quantifying their quantity, shape, configuration, and fragmentation. I also explore the spatial equity of informal and formal green spaces across each city using the Gini coefficient, a metric designed to assess spatial inequities of a variable across a landscape. The findings reveal that informal green spaces often comprise a greater total area within census block groups across cities. Further, informal green spaces are more equitably distributed than formal green spaces, though they are also typically more fragmented. The multiple linear regression models predicting the equity of green space distribution through the Gini coefficient demonstrate that equity is strongly influenced by race and income, with Whiter and wealthier communities generally benefiting more. These results underscore the need to formally recognize and integrate IGS into urban green infrastructure planning to reduce long-standing spatial inequities. Chapter 2 focuses on Fort Collins, Colorado, to evaluate how vegetation structure within IGS and FGS influences ambient noise levels. Using remote sensing and GIS data, I find that although IGS tend to have taller canopies, they are also slightly louder on average. Surprisingly, canopy height alone does not predict noise attenuation; vegetation density and habitat type emerge as stronger predictors. Communities with higher social vulnerability experience greater noise exposure, highlighting inequities in green space quality and environmental protection. These findings call attention to the importance of vegetation structure in environmental justice and suggest new directions for designing green spaces as acoustic refuges in cities. Chapter 3 further investigates Fort Collins by examining the relationship between green space characteristics, socio-demographics, and urban heat island (UHI) effects. While IGS and FGS cover similar areas, IGS are significantly more fragmented. Gini coefficients confirm that IGS are more equitably distributed, particularly in lower-income neighborhoods. Median income consistently predicts both green space equity and UHI intensity, and spatial configuration metrics like edge density influence localized heat exposure. These findings demonstrate that IGS can serve as critical, if underutilized, assets in climate resilience strategies, especially for vulnerable communities facing disproportionate heat burdens. Collectively, these studies demonstrate that IGS play a meaningful role in mitigating environmental inequities related to access, noise, and urban heat. However, realizing their full potential will require intentional recognition, integration, and management in urban planning. The findings advocate for a multifaceted, equity-driven approach to urban greening that includes both formal and informal green spaces to build more resilient and inclusive cities.
Open Access
Interactive effects of chronic nitrogen addition and pulsed deluge events on community structure and function of the shortgrass steppe
(Colorado State University. Libraries, 2025) Linabury, Mary C., author; Smith, Melinda D., advisor; Blumenthal, Dana, committee member; Havrilla, Caroline, committee member; Nippert, Jesse, committee member
Global change is intensifying climate extremes, leading to more intense droughts and deluges (i.e., large rainfall events). Simultaneously, mass industrialization has led to the continuous alteration of resources such as atmospheric CO2 and reactive nitrogen. Patterns of perturbations can be evaluated through the "pulse-press" framework which describes resource alteration along a temporal continuum: from discrete, short-term "pulse" to chronic, long-term "press". The combination of chronic press and discrete pulse resource alterations is expected to cause large and potentially unexpected changes to ecosystem structure (i.e., diversity, community composition) and function (i.e., productivity). Pulse-press dynamics have been observed and explored in theory and models, but robust experimental evidence is lacking. Therefore, this dissertation experimentally evaluated pulse-press dynamics in two grassland ecosystems: a shortgrass steppe in northeastern Colorado and a tallgrass prairie in northeastern Kansas. The first chapter of this dissertation established how the two grassland ecosystems responded to five years of nitrogen press along a gradient of addition levels. Within the shortgrass steppe, I found that nitrogen addition did not affect productivity but caused community change. In contrast, production increased within the tallgrass site without changes in community composition. These divergent responses, likely mediated by site-level differences in aridity, demonstrate that structural and functional responses may decouple under nitrogen press. The second chapter examined the interaction of pulsed deluge timing and nitrogen press at the shortgrass steppe. An extreme deluge applied mid-late growing season in 2021 had no significant effect on structure or function, while an early-mid deluge in 2022 synergistically interacted with nitrogen addition resulting in large increases to production. This synergistic interaction was driven by an increase in a weedy forbaceous species and showed that nitrogen press and pulsed deluge events can generate unexpected effects on ecosystem function. The third and final chapter of this dissertation assessed the legacy effects of deluge pulse amid ongoing nitrogen press. We monitored post-deluge plots and found unexpected production legacies that were not predicted by the initial response to deluge but were influenced by growing season precipitation. Community composition changes persisted even during the dry 2024 growing season, when production legacies were no longer evident. These results demonstrate that effects of deluge pulse amid ongoing nitrogen press may generate lagged responses, independent from initial responses. Collectively, this work establishes that interacting pulse and press resource alterations can produce large, complex, and often unforeseen effects on the structure and function of grassland ecosystems.
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How the pendulum swings: conservation as a tool to both reinforce and disrupt colonial systems of oppression
(Colorado State University. Libraries, 2025) Layden, Tamara J., author; Bombaci, Sara, advisor; David-Chavez, Dominique, advisor; Pejchar, Liba, committee member; Correia, Joel, committee member
Elevating Indigenous leadership in conservation science is critical for social and ecological resilience and recovery. However, Indigenous conservation governance is frequently undermined by persistent colonial research standards. In response, calls to implement ethical guidelines that honor Indigenous rights are mounting. Despite this growing movement, most conservation studies continue to follow largely colonial, extractive models, presenting a widening gap between ethical guidelines and practical applications across diverse research contexts. To help bridge this gap and contribute to the development, application, and evaluation of ethics in conservation practice, my dissertation offers: 1) a primer of the histories and contemporary paradigms that continue to hinder justice in conservation research and practice, 2) ethical guidance and relational evaluation attuned to Indigenous and communal conservation contexts, and 3) a case study example of transdisciplinary approaches to wildlife conservation, grounded in relational accountability to Indigenous and communal rights-holders. My dissertation research draws from Indigenous and multicultural values and methodologies that aim to re-center relationships, with outcomes represented through research, story, and art. Through diverse modalities, this body of work seeks to provide an entry point for cultivating a deeper understanding of justice and decolonization in conservation while offering guidance, recommendations, and examples for researchers, scholars, community members, and institutions to reaffirm Indigenous rights and improve relations with Indigenous stewards, thereby strengthening collective conservation visions and futures.
Open Access
Enacting environmental justice: community-based water research and resistance in highland Ecuador
(Colorado State University. Libraries, 2025) Parham, Rose, author; Hausermann, Heidi, advisor; Farah, Andrea Baudoin, committee member; Correia, Joel E., committee member
In the highland parish of Pintag, Ecuador, community members face declining water quality and governance failures despite the country's progressive constitutional framework recognizing the Rights of Nature, the human right to water, and the principles of Buen Vivir. This thesis presents a community-based, interdisciplinary research project developed in collaboration with an Indigenous collective in Pintag, to investigate water quality conditions and governance dynamics in the region. Using a mixed-methods approach that combined water sampling, interviews, and participant observation, the research examines both biophysical indicators of water contamination and lived experiences of water access, management, and injustice. Findings reveal that gravel mining and institutional neglect contribute to sedimentation and microbial contamination in waterways. However, many of the most pressing issues stem not from extractive activity alone, but from deeper systemic problems: regulatory gaps, underfunded institutions, and top-down structures that marginalize Indigenous and rural communities, leading to injustices. Despite constitutional protections, state institutions often fail to meaningfully engage with or support local water governance efforts. Community members report persistent procedural and recognitional environmental injustices, including lack of consultation, inaccessible data, and devaluation of Indigenous knowledge and autonomy. In response, communities are reclaiming power over local water governance through grassroots organizing, alternative development models, and resistance to extractivist logics. This thesis contributes to environmental justice literature by highlighting how state failures produce uneven water governance outcomes, and how communities are building decolonial alternatives rooted in reciprocity and self-determination.
Open Access
Developing an open-source remote sensing framework for long-term wetland restoration monitoring
(Colorado State University. Libraries, 2025) Akin, Jackson, author; O'Connell, Jessica, advisor; Armitage, Anna, committee member; Koons, David, committee member
Wetland restorations can take decades to show measurable success, yet long-term monitoring remains uncommon. Field-based monitoring is often costly and labor-intensive, making remote sensing an appealing alternative. In this project, we developed an open-source, reproducible remote sensing workflow calibrated with field data from a wetland restoration site in Galveston, Texas. The restoration was initiated in 2004, with additional efforts in 2011, with goals to increase wetland habitat, buffer wave energy and slow the erosion of remaining natural marsh. Our objective was to build an automated monitoring framework to assess restoration trajectory over time using biophysical metrics including elevation, land cover, and aboveground biomass. We trained models using Sentinel-2 satellite imagery and digital elevation model (DEM) data to estimate these metrics. To enhance elevation estimates, we developed a correction model that reduced root mean squared error (RMSE) from 0.29-m to 0.12-m. Our land cover model achieved an overall testing accuracy of 90% for classifying water, vegetation, and bare soil, while the aboveground biomass model performed with an RMSE of 82.4 g m-2 (normalized RMSE of 14%). These models were applied in time series analyses to evaluate site-wide landscape level restoration progress. We found that restoration mounds of 20+ years old had lower elevations than reference sites, but were similar to mid-aged sites, suggesting they are relatively stable. Mounds also appeared to be buffering remaining natural areas from lateral marsh erosion. However, mounds created in 2004 showed increased rates of vegetation transitioning to water and should be monitored closely. By applying this scalable and cost-effective framework, managers can more readily detect emerging restoration challenges and make timely, data-driven decisions, such as planting more vegetation, implementing more erosion control structures or increasing mound elevation through thin layer soil placement. Through leveraging high-resolution and freely available Sentinel-2 imagery and elevation data, the models achieved high classification accuracy and effectively captured key trends in biophysical parameters such as elevation, land cover and AGB, offering insight into restoration trajectories over time. While expert interpretation is still necessary for management decisions, this framework offers a powerful tool for improving long-term restoration monitoring and adaptive management.
Open Access
Effects of genotype and acclimation on honeybee thermal responses
(Colorado State University. Libraries, 2025) Rylance, Elizabeth, author; Naug, Dhruba, advisor; Hoke, Kim, committee member; Hufbauer, Ruth, committee member
As global temperatures rise, animals are increasingly exposed to changing thermal environments that challenge their physiological and behavioral performance. Genetic variation and phenotypic plasticity are two key factors that influence how organisms respond to such environmental change. Understanding the capacity and limitations of these responses is essential for predicting species resilience under climate change. In this thesis, I investigate how thermal responses are shaped by 1) short-term thermal acclimation and 2) genotypic differences at a key metabolic enzyme locus in honeybees, a species of high ecological and agricultural importance. In the first chapter, I assessed the capacity for short-term acclimation to mitigate the effects of thermal stress. Bees were acclimated for 48 hours to either a cool (25°C) or warm (35°C) temperature and subsequently tested at both acclimation and non-acclimation temperatures. Metabolic rate showed evidence of compensatory acclimation, with warm-acclimated bees maintaining stable performance at high temperature. In contrast, activity and learning performance declined following heat exposure, with no evidence of a beneficial acclimation response. These results suggest that energetically demanding traits such as cognition and locomotion may have a more limited capacity for acclimation and higher vulnerability to sustained heat stress. In the second chapter, I examined how genetic variation in a key metabolic enzyme, malate dehydrogenase (MDH-1), influences thermal performance. Bees representing homozygous Slow (SS), homozygous Fast (FF), and heterozygous (SF) genotypes were assayed across four temperatures and three traits: metabolic rate, locomotor activity, and learning ability. Metabolic rate exhibited a strong genotype-by-temperature interaction; Fast bees consistently had the highest rates, Slow bees the lowest, and heterozygous bees had flexible, intermediate responses. Activity levels varied with both genotype and temperature, while learning performance was influenced by genotype but not temperature. Heterozygotes outperformed both homozygous types in the learning assay, suggesting a potential heterozygote advantage. These results highlight how functional diversity in a key metabolic enzyme can shape trait performance across thermal gradients, with broader implications for colony-level function and honeybee breeding practices. Together, these chapters show that both genetic variation and phenotypic plasticity influence how bees respond to thermal variation, but their effects vary across different performance traits. Genetic variation may support flexible trait expression across environments, whereas short-term acclimation alone may be insufficient to maintain performance in key behavioral traits under thermal stress. These findings emphasize the importance of integrative, trait-based approaches to evaluating thermal responses and have implications for understanding pollinator performance and adaptation in a warming world.
Open Access
Non-target effects and soil persistence of indaziflam: implications for seed-based restoration of cheatgrass-invaded landscapes in the Colorado Front Range
(Colorado State University. Libraries, 2025) Myers, Lauren, author; Brown, Cynthia S., advisor; Havrilla, Caroline, advisor; Dayan, Franck E., committee member; Paschke, Mark, committee member
Invasive species threaten ecosystems around the world. In the grasslands and shrublands of western North America, invasive annual grasses, especially Bromus tectorum (cheatgrass or downy brome), pose ecological and economic threats through their inhibitory interactions with native species, exacerbation of wildfires through increased fine fuel loads, and poor forage and habitat quality. As a winter annual species, cheatgrass also possesses a phenological advantage that makes it especially difficult to eradicate. Indaziflam, a pre-emergent biocellulose inhibiting herbicide with residual soil activity, has established a new paradigm of control for cheatgrass and other invasive annual grasses. Indaziflam is highly effective in reducing the cover of cheatgrass for at least two to three years without harming established perennial grasses. However, the effects of indaziflam on non-target species are less clear. Given that indaziflam is used pre-emergence, it may inhibit the germination of non-target species as well, which is a concern for land managers, especially when practicing seed-based restoration. We conducted a greenhouse study to assess the dose-response relationship between indaziflam and native species commonly used for seed-based restoration in the Colorado Front Range, Colorado, USA. We also conducted a field study to assess the quantities of indaziflam residue in various soils in sites treated with indaziflam in the Colorado Front Range at varying points in the past. First, I will review the literature on indaziflam as it pertains to its mechanism of action, target impacts, and non-target impacts. Next, I will provide an overview of the greenhouse and field studies. Using the filter framework of community assembly, I argue that while B. tectorum acts as a biotic filter to native species establishment and its control is vital for restoration of invaded landscapes, indaziflam may also act as an unintentional abiotic filter to native species establishment.
Open Access
Ecological characteristics of stream reaches with and without low-tech process-based restoration in a wildfire-affected watershed
(Colorado State University. Libraries, 2025) Nichter, Kimberly Alyse, author; Preston, Dan, advisor; Fairchild, Matthew, committee member; Kanno, Yoichiro, committee member; Morrison, Ryan, committee member; Wohl, Ellen, committee member
Wildfires can alter community structure and ecosystem function of montane streams, leading to management challenges. Low-tech process-based restoration (LTPBR) may be a useful tool in post-wildfire catchments, but relatively few studies have examined how LTPBR may influence ecological responses following wildfire. This study compared abiotic and biotic characteristics of a stream reach that received LTPBR, untreated reaches without LTPBR, and a reach with relict beaver activity that had relatively intact berms. All sites had unconfined floodplains and were affected by wildfire four years prior to the surveys. The treatment reach received post-assist log structures two years prior to field surveys. Our objective was to characterize differences in sediment size, water temperature, benthic algae, fine and particulate organic matter, large wood, riparian vegetation, macroinvertebrate communities, and brook trout density and size structure. The relict beaver site had more shallow, lentic habitat, finer substrate, increased particulate organic matter, and greater temperature variability. The untreated reach had a deep, simpler channel, larger substrate, lower particulate organic matter, and more uniform temperatures. The treatment reach had a channel with depth and substrate sizes intermediate between the relict beaver and untreated reaches, higher chlorophyl-a, and moderate temperature variability. Benthic macroinvertebrate biomass and composition varied across habitat types; standing biomass was highest on wood and lotic hard substrates. When scaled to habitat area at the reach scale, macroinvertebrate biomass was highest at the relict beaver reach and comparable at the treatment and untreated reaches. Insect inputs to the stream and emergence showed temporal variation, but did not differ consistently between stream reaches. The treatment reach had slightly higher brook trout density than the other reaches although the most downstream untreated reach had slightly larger fish, particularly in spring. Our results highlight potential differences in stream function and community structure between wildfire-affected streams with and without LTPBR treatments. Continued research on ecological impacts of LTPBR in addition to geomorphic effects may provide valuable insight to success of LTPBR in post-fire watersheds.
Open Access
Where you live matters: extreme weather conditions amplify territory quality effects on island bird reproduction
(Colorado State University. Libraries, 2025) Horowitz, Hannah P., author; Neuwald, Jennifer L., advisor; Ghalambor, Cameron K., advisor; Mouton, James C., committee member; Sillett, T. Scott, committee member; Aubry, Lise M., committee member
Aspects of territory quality and environmental variation (e.g. rainfall, temperature) are key predictors of reproductive success in birds. However, the interaction between variation in territory quality and extreme weather events on reproduction has seldom been explored. The Island Scrub-jay (Aphelocoma insularis), a species endemic to Santa Cruz Island, California, is a highly territorial species where breeding pairs maintain year-round territories that vary in vegetation composition and structure. Using a 15-year dataset (2008-2023), we examined how physical metrics of territory quality and extreme weather conditions affect reproductive output. We found that high-quality territories are characterized by more chaparral/woodland habitat, while low-quality territories have a higher proportion of scrub habitat. In addition, during drought and abnormally hot years, pairs in lower-quality territories experienced significantly reduced reproductive output, often failing to fledge any young at all. Conversely, years of high rainfall and cooler temperatures had a uniformly positive effect, boosting reproductive output for all breeding individuals regardless of territory quality, likely due to increased resource availability. Our findings highlight the importance of how variance in territory quality interacts with drought and high temperatures to disproportionately reduce reproductive output within poor quality territories, but also how wet, cool years can buffer populations by facilitating reproductive success across all territories. As droughts and extreme heat are projected to become more frequent, severe, and prolonged under future climate change scenarios, the reproductive variance among breeding pairs risks skewing the effective population size and reducing the genetic diversity of this already vulnerable, range-restricted species. This study emphasizes the importance of quantifying variation in territory quality and protecting structurally diverse, high quality habitat types as they may play an outsized role in long-term persistence of territorial species amidst increasing climatic stress.
Open Access
A method to quantify and depict uncertainty in wildlife habitat suitability models using Bayesian inference and expert opinion
(Colorado State University. Libraries, 2005) O'Brien, Lee E., author; Wiens, John, advisor; Theobald, Dave, advisor; Flather, Curtis, committee member
Knowing the distribution of wildlife habitats across the landscape is an important component in biological conservation planning. Many conservation planning projects use wildlife habitat suitability models as the basis for predicting the distribution of habitat for terrestrial species. The predictions are typically binary GIS maps depicting the distribution of suitable versus unsuitable habitat, without indication of how strong the evidence is for these predictions across the area. There are many sources of uncertainty in these models as each data layer, with its own level of uncertainty, is incorporated into the models. Habitat suitability models are often knowledge-based and do not quantify their inherent uncertainty. Or, if the models are empirically-based, there are usually insufficient data to derive habitat distribution predictions and to test the predictions to determine the level of uncertainty associated with them. To make evident the uncertainty inherent in knowledge-based habitat suitability models, Bayesian inference procedures were used to combine expert opinions about the strength of wildlife habitat relationships with prior model parameters to create probability maps that depict the state of knowledge about the distribution of suitable habitat for terrestrial wildlife species. The Bayesian method has several advantages. One is that probability in a Bayesian framework is a direct representation of uncertainty. Thus models produced using this method are easy to understand and interpret. This method can be used on any species, regardless of the amount of empirical data available. Modeling species with deficient habitat relationship data produces appropriate results showing high levels of uncertainty. Bayesian methods allow the combination of empirical and knowledge-based evidence, so that all sources of information about species habitat may be incorporated. Bayesian models may also be updated, so that models can be improved as new information arises. The models can also incorporate landscape context and depict the associated uncertainty. With binary models, a priori decisions are made to include or reject specific habitat conditions. This tends to either over or under predict suitable habitat by including or rejecting borderline conditions. The portrayal of the results (habitat is suitable: yes or no) also implies a certainty that is unwarranted. With the Bayesian method, all possible habitat conditions are retained in the models, revealing areas of potentially suitable habitat that may have been omitted by binary models, and the certainty of the predictions is forthrightly depicted. The models derived by this method produce simple, honest, spatial depictions of what is known about the distribution of suitable wildlife habitat that can be used to support more informed decisions in species conservation planning and management.
Embargo
Big data analysis and coupled human-natural systems modeling to examine the influence of socioeconomic and environmental factors on protected areas
(Colorado State University. Libraries, 2025) Zarria-Samanamud, Melody Rocio, author; Boone, Randall, advisor; Bowser, Gillian, advisor; Havrilla, Caroline, committee member; Jones, Kelly, committee member; Klein, Julia, committee member; Young, Kenneth, committee member
This dissertation aims to deepen our understanding of how human and environmental factors affect protected areas through a social-ecological systems approach. This dissertation comprises two topics. The first consists of determining the level of landscape changes in protected areas and identifying the anthropogenic and environmental factors associated with these changes. The other topic explores the potential impacts of climate change and land management on ecosystems, agropastoral families' livelihoods, and livestock grazing behavior in the Peruvian Andes. I used a social-ecological systems analytical approach to have an interdisciplinary perspective on how the biophysical and socioeconomic contexts of protected areas impact their conservation effectiveness and influence the pressures they face. My analyses used innovative analytical approaches, including big data analysis and agent-based modeling, to offer new insights into these critical issues. In Chapter 2, I quantified changes in the landscape of protected areas worldwide and identified the critical anthropogenic and biophysical factors associated with these changes. I estimated landscape metrics for about 11,000 protected areas for 2000 and 2020 using open-source spatial data and performed random forest analyses. Changes in the landscape of protected areas and their associated socioeconomic and environmental factors differed by region and cover classes. In general, landscape changes were mainly influenced by anthropogenic factors, such as the level of human development, agricultural expansion, population density, and the protected area's regulation level. The main biophysical factors critical in explaining landscape changes were slope and precipitation. In Chapter 3, I examined the ecological impacts of climate change in a mountain landscape in the Andes of Peru. I parametrized an ecosystem-process model (L-Range) to Andean environmental conditions to capture ecosystem responses to climate change. Climate change impacts on Andean ecosystems vary by cover class, topographic position, and climate scenario. Shrublands and woodlands will become more productive, whereas wetlands are projected to experience a decline in primary production. However, under the most extreme climate scenario, all cover classes will undergo a reduction in primary production. In Chapter 4, I explored the potential economic and ecological impacts of various land management scenarios in a valley of Huascaran National Park in the Andes of Peru used as grazing lands by a local community. I built the Agent-based model of laNd management Dynamics and Ecosystem Services (ANDES) that represents livestock grazing behavior, grazing management, and household economies. I coupled the ANDES/L-Range models to deepen my understanding of how new management scenarios and future climate conditions would impact ecosystems and families' economies. Families' incomes were reduced under the scenarios involving a reduction in livestock population. The biomass availability was markedly higher only under the scenarios that involved livestock population reduction and the implementation of new rotational grazing schemes. These findings reveal that not only livestock numbers should be adjusted but also livestock distribution. In Chapter 5, I analyzed how different grazing management schemes impact livestock forage consumption, grazing behavior, and body condition of cattle and sheep. I analyzed information derived from the Livestock Grazing Behavior sub-model of ANDES. Livestock responses to grazing management varied by species. Forage consumption and body condition were the highest under the scenarios that implied livestock population reduction. Moreover, livestock mortality was the lowest under these scenarios. In general, the below-optimal performance of livestock across all management scenarios suggests adjusting stocking rate and grazing frequency. The key insights derived from Chapters 3, 4, and 5 are as follows. The Andean ecosystems' response to climate change will exhibit considerable variability. While a reduction in primary production is anticipated across most cover classes, except for woodlands, the impacts of climate change will also be influenced by the ecosystem's landscape setting. Livestock management practices, particularly those that involve reducing livestock numbers, will result in better animal body condition. The implementation of regulatory policies, such as reducing livestock populations and limiting park land access, will have significant economic repercussions on families, especially middle-aged and elderly individuals, whose income primarily relies on livestock production. My study provides critical information for the sustainable management and conservation of protected areas and can serve as the basis for designing integrative policies that balance conservation and sustainable development. The development of conservation and sustainability policies must address the factors impacting protected areas and their surroundings. To achieve this, these policies should incorporate diverse perspectives and foster engagement with local communities.
Open Access
Landscape conservation design from the perspective of the obligate species: example for the sagebrush steppe biome
(Colorado State University. Libraries, 2025) O'Brien, Lee E., author; Hufbauer, Ruth, advisor; Steel, Zachary, advisor; Gavin, Michael, committee member; Morisette, Jeffrey, committee member
Conservation strategies in use today are not keeping up with the speed and scale of threats to the natural world. They are not effectively curbing the current wave of species extinctions. There is a critical need to conserve and manage whole landscapes, preserving their ecological integrity, to head off species imperilment. Habitat loss and fragmentation are significant causes of species imperilment, and both habitat amount and contiguity (inverse of fragmentation) must be addressed for effective conservation planning. This study is focused on identifying the location, configuration, and contiguity of environmental and abiotic factors required to sustain the populations of species that are reliant on a particular landscape for some portion of their life histories. I used the sagebrush steppe biome in the western United States to demonstrate how this can be done. Several major issues have heretofore inhibited identifying habitats able to sustain the populations of a wide array of taxa: 1) insufficient data for many species; 2) bias issues with using publicly collected "big data"; 3) inadequate computing capacity for large-extent high-resolution habitat models, and; 4) no explicit way for habitat models to include species-specific habitat connectivity, important for population viability. Some of these issues can be addressed now because of the increasing availability of species location data, increased computational capacities, and better optimization algorithms, and some I propose ways to address. Surmounting these impediments allowed me to identify the fundamental habitats most likely to sustain populations of native species, and use these models as inputs in a systematic conservation planning procedure to identify areas of the sagebrush steppe biome most likely to support the persistence of the obligate taxa using the least amount of land. I compared this approach to using an umbrella species to protect habitats of sympatric species, assessing whether protecting habitats for sage-grouse species, greater sage-grouse (Centrocercus urophasianus) and Gunnison sage-grouse (C. minimus), would protect the other taxa reliant upon the sagebrush steppe landscape. I found that using sage-grouse habitat as an umbrella left many sympatric species with inadequate habitat protection. Determining whether sufficient habitat of sympatric species is protected requires knowing the habitat requirements of these taxa. If the habitat requirements of these taxa are determined, as done in this study, each species' required habitat can be included in a conservation plan, instead of relying on the assumption that conserving an umbrella species' habitat will provide sympatric species protection adequate to secure their persistence. The approach developed here has additional advantages. Namely, as new information becomes available, the fundamental habitat models for species can be updated and included in the conservation plans. Also, the amount of species fundamental habitat required or supplemental goals (e.g., including core sagebrush, threats, or sage-grouse protection areas) can be easily added to the optimization routine to produce new optimal multi-species habitat configurations. This gives conservation planners the means to explore explicit effects and tradeoffs of pursuing different conservation objectives, while assuring the resulting plans can support the persistence of the obligate taxa of a biome.
Embargo
Ominous mouse: tracing zoonotic disease risk in the South Caucasus
(Colorado State University. Libraries, 2025) Gilbertson, Kendra E., author; Webb, Colleen, advisor; Kosoy, Michael, committee member; Sofaer, Helen, committee member; Kading, Rebekah, committee member
Most emerging infectious diseases that affect humans originate in animal species. In order to accurately predict disease risk, we must understand the spatial distribution of the various environmental, ecological, and host factors that allow pathogens to spillover into human populations. The most foundational of these requirements is the presence of one or more host species that allow the pathogen to persist in a given location. We accomplished this by using a Bayesian Additive Regression Trees (BART) model to predict the distributions of 15 medically-relevant small mammals species across the South Caucasus while also exploring different methodological strategies. Our flexible machine learning approach allowed us to create predictions that had high ecological accuracy and strong discrimination ability crucial for discerning the likelihood of species presence. We also found that models trained on random background points were well suited for our goal of maximizing discrimination ability without sacrificing biological realism. We recommend the consideration of this approach to those using species distributions to predict disease risk. Next we incorporated these predictions as predictive layers in a risk prediction model of tularemia in order to understand the spatial risk and ecological drivers of this complex pathogen. We found that tularemia was primarily a rural disease in humans, partially a result of the increased contact between humans and animals in agricultural settings. While we observed different distributions between clinical manifestations of tularemia, the causes of these diverging patterns warrant further inquiry. We extended our examination of zoonotic risk to include six additional pathogens. To paint a picture of overall disease risk in the South Caucasus, we combined the predicted distributions of all diseases to create a disease richness map. This is of public health import as it identified areas of elevated transmission risk across pathogens. We also found that zoonoses in the South Caucasus typically occur in rural areas, and those with occupational exposures were at the most risk. These areas are more likely to support higher diversity of host and vector species, allowing for circulation of pathogens in the environment and greater contact rates between humans and disease-carrying animals. Our research adds to a broader understanding of zoonotic risk and its ecological factors in the South Caucasus and we provided methodological recommendations relevant to the field of disease ecology.
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Lodgepole pine resilience in Troublesome times: the influence of stand-level characteristics on regeneration following bark beetle mortality and wildfire
(Colorado State University. Libraries, 2025) Horn, Mattie, author; Rocca, Monique, advisor; Stevens-Rumann, Camille, committee member; Rhoades, Charles C., committee member
Climate-driven increases in disturbance activity from bark beetle outbreaks and wildfire have prompted concerns for potential declines in tree regeneration. In forests of the Southern Rocky Mountains, widespread tree mortality from bark beetles over the last few decades has resulted in forest conditions that may drive alternate patterns of recovery following subsequent wildfire. As such, the extreme fire season of 2020 presents a unique opportunity to examine the patterns of forest recovery following two disturbances that are unprecedented in their severity and extent. In this study, I collected field data on lodgepole pine seedling recruitment following the East Troublesome fire, which burned through beetle-killed lodgepole pine stands (11-19 years post outbreak), to 1) assess the potential for natural forest recovery and 2) determine the primary stand-level factors that influence the abundance of post-fire lodgepole pine seedlings. In the summer of 2022, I sampled 116 plots across gradients of beetle severity, fire severity, and stand age in Rocky Mountain National Park, Colorado. In each plot, I measured variables capturing fire effects, forest structure, topography, and post-fire regeneration. General linear mixed models were used to determine the relative influence of fire effects, seed source, stand characteristics, and topography on post-fire lodgepole pine seedling density. I found that 97% of the study area had lodgepole pine seedlings established at 2 years post-fire, and 70% of the study area had seedling densities exceeding 370 t ha -1, however, seedling densities were highly variable across the landscape. The abundance of lodgepole pine seedlings at the plot-level was strongly associated with the density of cone-bearing trees, elevation, and tree consumption. These results highlight the mechanisms by which pre-fire forest structure and canopy consumption alter post-fire seed availability to influence post-fire lodgepole pine recruitment. My findings help inform predictions of future forest trajectories following sequential disturbance by bark beetle outbreaks and wildfire and underscore the need for tailored forest management approaches that consider both the legacy of bark beetle outbreaks as well as the variable nature of fire effects.
Open Access
Neighborhood income, landscape, and local factors relate to differences in pollinator biodiversity in Denver city parks
(Colorado State University. Libraries, 2025) Bailey, Nicole Isabel, author; Mola, John, advisor; Hufbauer, Ruth, committee member; Bombaci, Sara, committee member
Urbanization is a growing influence on pollinator species worldwide, benefiting some species while threatening others. Urban areas have high cover of impervious surfaces, inconsistent access to floral resources, and competition from non-native honeybees. Urban areas can also be impacted by a "luxury effect", where greater biodiversity is found in more affluent areas. Despite these threats, city parks could be a crucial refuge for pollinator biodiversity. In this study, we investigated how pollinator species richness and community composition differed across Denver city parks depending on landscape-level factors, (neighborhood income and land cover surrounding a park), and local factors, (floral traits and honeybee abundance). After visiting 25 city parks three times during the summer of 2023, we found that income did not strongly relate to wild bee species richness or community composition, but floral species richness and origin did. We found that lower-income parks had a higher proportion of non-native weedy plants and lower wild bee species richness than parks with primarily native plantings. Wild bee communities differed in parks with high compared to low honeybee abundances, with more bumble bees observed in higher honeybee parks. Increased cover of impervious surfaces and income negatively related to butterfly species richness, but butterfly communities remained similar across parks. These findings suggest that managers can implement diverse native plantings in parks to support biodiverse pollinator communities regardless of neighborhood income level.
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Changes in functional structure of aquatic insect communities across environmental gradients in mountain streams
(Colorado State University. Libraries, 2024) Gutierrez, Carolina, author; Poff, N. LeRoy, advisor; Ghalambor, Cameron, advisor; Neuwald, Jennifer, committee member; Webb, Colleen, committee member
This study investigates the functional diversity of aquatic insect communities across environmental gradients within Rocky Mountain headwater streams, aiming to better understand how elevation, water temperature, and canopy cover shape the structure and dynamics of these communities. Functional diversity (FD) is defined here as the range, distribution, and relative abundance of organismal traits, which together provide deeper insight into ecosystem functionality than species diversity alone. FD was quantified through three primary metrics: functional richness (FRic), functional evenness (FEve), and functional divergence (FDiv), each capturing distinct aspects of how species contribute to ecosystem functioning. This multidimensional approach enables a nuanced examination of how aquatic insect communities respond to various environmental stressors and spatial constraints, particularly as altitudinal changes present unique challenges in terms of temperature variability and resource availability. Field data were collected from twenty-four stream sites distributed across elevation bands ranging from 1,500 to 3,500 meters. Sites were replicated in three different drainage systems to account for regional variation, with insect specimens collected and assessed for twenty functional traits. These traits included parameters such as voltinism (number of life cycles per year), adult lifespan, emergence synchronization, and dispersal ability, all of which are critical in determining an insect's role in the ecosystem. Canopy cover and water temperature were also measured to evaluate how localized microclimates and light availability influenced community composition. Results revealed a significant decline in functional richness with increasing elevation, with the steepest reductions observed in streams with sparse canopy cover. Functional richness was highest in areas where canopy cover ranged between 65-78%, and water temperature was between 8°C and 15°C, suggesting that moderate canopy cover and specific thermal conditions support more functionally diverse communities. Functional evenness and divergence, while showing less pronounced patterns, indicated that the most extreme trait values are critical for resilience in these systems, particularly under fluctuating environmental conditions. Trophic interactions further illustrate the importance of specific functional groups, such as predators, grazers, and filterers, in shaping community structure. The analysis of beta diversity demonstrated substantial turnover in functional traits across elevation gradients, emphasizing the heterogeneity of insect communities within low-order, high-altitude streams and reinforcing the role of environmental filtering in community assembly. These findings highlight the vulnerability of headwater stream ecosystems to environmental changes and underscore the importance of functional diversity metrics in ecological monitoring and conservation efforts. Overall, this study contributes to our understanding of how functional environmental gradients structure diversity and provides a foundation for comparative studies on functional diversity in tropical versus temperate mountain stream ecosystems, particularly in the context of global biodiversity conservation.
Open Access
Investigating the adaptive genetic landscape of global crop species
(Colorado State University. Libraries, 2024) Hein, Kirsten Marie, author; McKay, John, advisor; Morris, Geoffrey, committee member; Ross-Ibarra, Jeffrey, committee member; Schipanski, Meagan, committee member
Improving environmental adaptation in crops is essential for sustaining food security in the face of global climate change. Recent advances in high-throughput genomic sequencing and phenotyping technologies have enabled researchers to identify and validate the genetic factors shaping adaptation. In this dissertation, I investigated the genetic basis of environmental adaptation in global cereal crops, focusing on the staple crop, maize (Zea mays L.), and the orphan crop, tef (Eragrostis tef Zucc.). In Chapter 2, I employed a landscape genomics approach to identify the genetic and environmental drivers of adaptation in a georeferenced collection of Ethiopian tef. In Chapter 3, I utilized both forward and reverse genetic approaches to evaluate the precision of phenotype-genotype mapping across multiple phenotyping methods for quantifying root system architecture in field-excavated maize. In Chapter 4, I applied a functional genetics approach to characterize a novel gene model in maize predicted to regulate root system development and nitrogen capture under field conditions. Collectively, this work provides valuable insights into the complex relationships between phenotype, genotype, and environment, contributing to our understanding of adaptation in two distinct and vital crop systems.
Open Access
Crop domestication impacts on rhizosphere interactions and nitrogen acquisition
(Colorado State University. Libraries, 2024) Hwang, Siwook, author; Fonte, Steven J., advisor; Machmuller, Megan B., committee member; Crews, Timothy E., committee member; Wrighton, Kelly C., committee member; Boot, Claudia M., committee member
Synthetic nitrogen (N) fertilizer is an essential pillar of modern industrial agriculture. Production and application of synthetic N fertilizer, however, are two of the most expensive, energy intensive, and environmentally deleterious processes in agriculture. Therefore, alternative means of providing N in an agroecosystem are of great interest in sustainable agriculture. While many solutions – from cover cropping to intercropping – have been suggested over time it remains unclear if the modern high-yielding crops can thrive in these alternative N conditions. Decades of breeding under high synthetic N input as well as the inherently annual nature of these modern cereal crops may prevent them from fully taking advantage of these alternative N sources. In this dissertation, I explored the impact of domestication on crop rhizosphere interactions and N acquisition, in both retrospective and prospective terms. First, I investigated how modern maize (Zea mays subsp. mays), and its wild relative Teosinte (Zea mays subsp. parviglumis) differed in their ability to adapt to, and take up, cover crop residue N and synthetic N inputs. We designed a 13C (carbon)/15N dual isotope labeling experiment in which we compared the C allocation patterns of modern maize and teosinte in response to synthetic (urea) and organic (cover crop residue) forms of N. Teosinte responded to organic N by increasing its biomass root-to-shoot (R:S) ratio by 50% compared to synthetic N, while modern maize maintained the same biomass R:S ratios in both N treatments. Recent photosynthate R:S ratio (measured using 13C-CO2, 7 weeks after establishment) was greater in organic N than in synthetic N treatments for both modern maize and teosinte (91% and 37%; respectively). Label-derived dissolved organic C (DOC), representing recent rhizodeposits, was 2.5 times greater in the organic N treatments for both genotypes. Modern maize took up a similar amount of organic N as teosinte using different C allocation strategies. Our findings suggest that intensive breeding under high N input conditions has not affected this modern maize hybrid's access to organic N sources while improving its ability to take up synthetic N. Next, I shifted my focus to the novel perennial grains Kernza and perennial wheat. Kernza® is a domesticated intermediate wheatgrass (IWG, Thinopyrum intermedium). Perennial wheat is a hybrid between Kernza/IWG and modern annual durum wheat (Triticum turgidum subsp. durum). Kernza, in addition to being a perennial, may still possess beneficial belowground traits that may have been lost in modern cereals through millennia of aboveground-focused plant breeding. If so, such traits may be passed down to perennial wheat. To characterize root architecture, exudate profiles, and microbial communities of Kernza and perennial wheat in relation to annual wheat, I conducted a greenhouse experiment. We grew three genotypes/species (Kernza, perennial wheat, annual wheat) and collected their root exudates after 8 weeks of growth. The exudates were analyzed via LC-MS/MS for their chemical composition. We extracted DNA from rhizosphere soils and sequenced them for 16S and ITS profiles. Lastly, we scanned the roots to analyze root distribution across different diameter classes. We found that perennial wheat invested more heavily into very fine (< 250 µm) roots compared to annual wheat and Kernza. Perennial wheat also exuded at a greater rate of exudates per amount of root biomass. We suspect that the greater proportion of very fine roots in perennial wheat led to greater surface area and greater specific exudation rate, and that this may be related to hybrid vigor. We did not find evidence of a genotype effect on root exudate or microbial community composition. However, root exudates (overall metabolite profiles) significantly correlated with root architecture (distribution of root volume over different diameter classes) and the microbial community composition. These interactions represent a potential pathway through which plants can exert influence over the rhizosphere microbial community. Overall, these results emphasize the importance of root architecture in mediating belowground interactions. Understanding rhizosphere dynamics and the response to domestication and hybridization can guide further development of robust perennial cereal crops. In a third experiment, I studied how Kernza, perennial wheat, and annual responded to cereal-legume intercropping (biculture) in the field. To do so, we planted each of the three genotypes in monoculture or in biculture with alfalfa (Medicago sativa). We sampled their rhizosphere over two growing seasons and extracted soil DNA to construct rhizosphere 16S and ITS profiles. We hypothesized that 1) rhizosphere microbial community composition of annual wheat and Kernza will be most dissimilar from each other with perennial wheat intermediate, and 2) microbial community composition will shift in biculture, with the greatest change in Kernza and the smallest in annual wheat. We found that the rhizosphere 16S profiles differed significantly from the other two genotypes but the 16S profile of perennial wheat did not differ from that of annual wheat. Perennial wheat seemingly inherited microbial recruitment traits of its annual parent more so than its perennial parent's. Interestingly, inclusion of legumes led to the convergence, rather than divergence, of 16S profiles among genotypes. We postulate that the competitive pressure of alfalfa may have led to this convergence of 16S profiles across genotypes. The fungal community did not show evidence of genotype effect. However, the fungal community composition changed over two years in monoculture but not in biculture. This result implies that fungal community may become distinct over time if it is influenced by only one genotype (i.e., monoculture) rather than two (i.e., biculture). In conclusion, we found evidence of genotype-driven microbial community assembly that changed with legume's competitive pressure. The inheritability of microbial assembly was present but skewed towards the annual parent. Our study demonstrates the importance of including rhizosphere interactions in our evaluation of novel cereal crops in and out of cereal-legume biculture. In a final study, I investigated how rhizosphere microbial ecology of these three genotypes (Kernza, annual wheat, and perennial wheat) could be linked to their ability to acquire N from neighboring alfalfa plants. We designed a greenhouse study in which we planted all three cereals in monoculture or in biculture with alfalfa and used 15N leaf feeding technique to track the movement of N from alfalfa to cereals. In addition, we also extracted DNA from the soil and sequenced it for 16S rRNA profiles. Arbuscular mycorrhizal fungi (AMF) infection rate was also measured on all cereals and legumes. We hypothesized that: 1) annual wheat would produce the greatest biomass but Kernza would have highest proportion of legume derived N in its biomass, 2) all microbial communities will shift in biculture, with the greatest change in Kernza and the smallest in annual wheat, and 3) Kernza would have the highest rate of infection from AMF, especially in biculture. Surprisingly, we found no evidence of genotype or cropping system (monoculture or biculture) effect on either proportion or absolute amount of N derived from legume. We did find, however, that DOC concentration was higher in cereal rhizosphere grown in biculture than in monoculture, suggesting greater belowground investment in exudates when the grasses are grown with a legume. Despite this trend, annual wheat had much lower microbial biomass carbon (MBC) level in its rhizosphere compared to the perennials, in biculture. We contended that this may be due to substrate suitability of annual wheat's rhizodeposit. We also found that AMF infection rate was in fact the lowest in Kernza. Lastly, we found that 16S profiles of all three cereals shifted towards that of alfalfa in biculture. This trend might suggest microbial spillover, wherein rhizosphere microbial community of one genotype colonizes that of a neighboring plant, from alfalfa rhizosphere. Overall, we demonstrated that quantifying the N transfer in the rhizosphere can provide important insight into how these genotypes may be inducing changes in soil biogeochemistry in response to neighboring legumes. In summation, this dissertation provides links between crop genotype, root exudate chemistry and rate, microbial community assembly, and their biogeochemical consequences, in alternative N environments. Deepened understanding of how complex rhizosphere interactions may affect internal N cycling could be leveraged to further optimize these unique systems such as perennial cereal-legume biculture. In doing so, we will be one step closer to a more sustainable future, that is less reliant on synthetic N fertilizers.

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