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The soil region influenced by plant roots, i.e., the rhizosphere, is one of the most complex biological habitats on Earth and significantly impacts global carbon flow and transformation. Understanding the structure and function of the rhizosphere is critically important for maintaining sustainable plant ecosystem services, designing engineered ecosystems for long-term soil carbon storage, and mitigating the effects of climate change. However, studying the biological and ecological processes and interactions in the rhizosphere requires advanced integrated technologies capable of decoding such a complex system at different scales. Here, we review how emerging approaches in sensing, imaging, and computational modeling can advance our understanding of the complex rhizosphere system. Particularly, we provide our perspectives and discuss future directions in developing in situ rhizosphere sensing technologies that could potentially correlate local-scale interactions to ecosystem scale impacts. We first review integrated multimodal imaging techniques for tracking inorganic elements and organic carbon flow at nano- to microscale in the rhizosphere, followed by a discussion on the use of synthetic soil and plant habitats that bridge laboratory-to-field studies on the rhizosphere processes. We then describe applications of genetically encoded biosensors in monitoring nutrient and chemical exchanges in the rhizosphere, and the novel nanotechnology-mediated delivery approaches for introducing biosensors into the root tissues. Next, we review the recent progress and express our vision on field-deployable sensing technologies such as planar optodes for quantifying the distribution of chemical and analyte gradients in the rhizosphere under field conditions. Moreover, we provide perspectives on the challenges of linking complex rhizosphere interactions to ecosystem sensing for detecting biological traits across scales, which arguably requires using the best-available model predictions including the model-experiment and image-based modeling approaches. Experimental platforms relevant to field conditions like SMART (Sensors at Mesoscales with Advanced Remote Telemetry) soils testbed, coupled with ecosystem sensing and predictive models, can be effective tools to explore coupled ecosystem behavior and responses to environmental perturbations. Finally, we envision that with the advent of novel high-resolution imaging capabilities at nano- to macroscale, and remote biosensing technologies, combined with advanced computational models, future studies will lead to detection and upscaling of rhizosphere processes toward ecosystem and global predictions.

Coastal wetlands are being lost at an alarming rate and thus wetland restoration is an important way to recruit coastal wetlands as an ally in our fight against climate change. To better understand and maximize the effectiveness of wetland restoration, it is important to evaluate the success of these restoration projects. In this study, we measured sediment accumulation and soil carbon density in North Campus Open Space, a recently restored wetland near the campus of UC Santa Barbara. The objectives of this study were to 1) assess rates of sediment accumulation since restoration, 2) evaluate spatial heterogeneity in sediment accumulation and soil carbon density, and 3) use this information to better understand the mechanisms that define the relationship between sediment accumulation and surface soil carbon storage to better predict carbon accumulation. Sediment accumulation rate averaged 2.16 mm/year, with a range of 0.4 mm/yr to 5.4 mm/yr. Sediment accumulation, surface soil carbon density, and subsurface carbon density all varied significantly by plot location. The spatial dynamics of vertical accretion were primarily driven by mineral rather than organic material, whereas surface soil carbon was primarily driven by aboveground plant biomass. Sediment accumulation was greatest downstream, whereas soil carbon accumulation was greatest upstream at the freshwater stream inputs. Some areas showed a negative relationship between sediment accumulation and soil carbon density, with high sediment accumulation associated with low surface soil carbon density. Although wetlands are touted to mitigate sea level rise and climate change through sediment accretion and carbon sequestration, these results suggest that sediment accumulation and carbon accumulation do not necessarily co-occur. The results imply that sediment accumulation alone cannot reliably predict carbon accumulation.

The current increase in global fire activity, driven by climate change, land use change, and fire suppression policies, warrants a better understanding of fire’s effects on soil microorganisms which drive major biogeochemical processes including carbon turnover and nutrient availability. Viruses of prokaryotes (bacteria and archaea), which are largely dsDNA viruses, apply pressure to microbial communities via infection and lysis and may also have distinct impacts on biogeochemical cycling apart from infection dynamics, making their own responses to fire (associated with host dynamics and/or based on their extracellular durability) important factors in understanding post-fire biogeochemistry. Incorporating soil viruses into the microbial community framework has begun to elucidate their roles in key soil processes and reveal similar and distinct responses to changing environmental conditions when compared to their host. Our ability to comprehensively interrogate dsDNA viral communities in soil has been possible with the development of size filtrated metagenomics, or viromics, which enriches samples in virus-like particles and enhances the ability to recover viruses through shotgun metagenomic sequencing. Using a viromics-based approach, the following three studies investigate soil viral communities in fire-affected systems with three different angles and scopes, in response to: (1) laboratory-based heating, (2) a field-based prescribed burn, and (3) a field-based wildfire. In the first study, research was focused on isolating and understanding the effects of heating in soil, which is one of the main direct impacts from fire and is also relevant in other practices, such as solarization. Prior to this work, little was known about the effects of high temperatures on soil viruses. In this study, three data types (DNase-treated viromes, non-DNase-treated viromes, and 16S rRNA gene amplicon sequencing) were leveraged to measure the responses of soil viral and prokaryotic communities to heating to 30ºC, 60ºC, or 90ºC, in comparison to field and control conditions. This experiment investigated: (1) the responses of dsDNA viral communities to heating of soils from two horizons (O and A) from the same forest soil profile, (2) the extent to which specific viral taxa could be identified as heat-sensitive or heat-tolerant across replicates and soil horizons, and (3) prokaryotic and virus-host dynamics in response to heating. Both viral and prokaryotic communities responded similarly to the treatment variables, and within both soil horizons, viral and prokaryotic communities clustered into three groups, based on beta-diversity patterns: the ambient community (field, control, and 30ºC samples), the 60ºC, and the 90ºC communities. As DNase-treated viromic DNA yields were below detection limits at 90ºC, it was inferred that most viral capsids were compromised after the 90ºC treatment, indicating a maximum temperature threshold between 60ºC and 90ºC for most viral particles in these soils. Groups of heat-tolerant and heat-sensitive vOTUs were also identified across both soil sources. Overall, it was determined that over 70% of viral populations, like their prokaryotic counterparts, could withstand temperatures as high as 60ºC, with shifts in relative abundance explaining most community compositional differences across heating treatments.In the second study, the response of viral communities to prescribed burning, a management strategy for maintaining forest health and mitigating devastating wildfires, was investigated. Soil viral community responses to a spring prescribed burn in a mixed conifer forest were assessed, as was the extent to which soil chemical properties and/or prokaryotic host communities could explain the observed patterns. With a before-after control-impact (BACI) design, two replicate soil samples were collected at each of two depths (0-3 cm and 3-6 cm) from four treatment (burn) plots and two control plots, at five timepoints (two before and three after the burn) over two months. From these 120 samples, 91 viromes were sequenced, and 198,402 viral ‘species’ (vOTUs) were recovered. Viral communities differed most significantly by location, regardless of treatment, and along with prokaryotic communities, exhibited a heterogenous response to fire. This response was correlated with soil chemical changes attributed to the burn, leading to the development of a chemistry-based burn severity index for this study. Low viromic DNA yields (a proxy for viral particle abundances) at high burn severity suggested loss of viral biomass. The relative abundances of Firmicutes, Actinobacteria, and the viruses predicted to infect them significantly increased along the burn severity gradient, suggesting survival of spore-formers and viral infection of these abundant taxa. In the third study, soil samples were collected over the course of one year after a wildfire in Mediterranean chaparral and woodland habitats in northern California. The principal goal of the study was to compare temporal responses within each habitat to unburned controls. Wildfire resulted in substantial shifts in viral community composition in both habitats. There were significant changes in the relative abundances of viruses predicted to infect bacteria from spore-forming phyla, which were at higher abundance in burned samples. Additionally, a substantial proportion of vOTUs in both burned habitats was also found in a burned Mediterranean forest, which may indicate some conserved traits in post-fire ecosystems. Overall, from the results of these three studies, there are significant shifts in viral community composition in response to fire and fire-related impacts (heating). Measuring responses to biologically relevant temperature changes helped to elucidate how the direct impacts of heating from a disturbance like fire might be immediately shifting communities based on temperature persistence thresholds of extracellular virions. The prescribed burn study in a forest ecosystem introduced the heterogeneity of fire as an ecosystem process and reinforced the importance of measuring burn severity, specifically based on soil chemical property changes. The burn severity index helped to reveal clear shifts in viral community composition, with evidence of decreased viral particle abundances, decreased viral richness, and changes in relative abundances of viruses that infected specific phyla, particularly host phyla that also changed in relative abundance in the prokaryotic communities. Lastly, under the least controlled fire scenario, our third study found a clear difference in viral and prokaryotic communities between soils affected by wildfire and unburned controls.

Using data from the Los Angeles Family and Neighborhood Study, US Census, and RefUSA, this dissertation examines the role of demographics, businesses, block aesthetics, and social relationships on perceptions of neighborhood boundaries among Los Angeles residents. Chapter one begins by contextualizing neighborhood spatial perceptions through the lens of community attachment and activity patterns theory. The second chapter examines the role of these dimensions on individual perceptions of neighborhood spatial scale, finding significant associations for key elements within them each. The third chapter shifts to block level analyses to examine whether factors in each of these dimensions predict differences in perceptions of neighborhood bounds among neighbors. Results do in fact indicate that certain factors are associated with greater consensus in these perceptions (e.g. social services and population density), while others tend to be associated with greater differences (e.g. participation in local or civic group). Given the importance of these findings, the next chapter is focused on enhancing research by incorporating these boundary perceptions into aggregate analyses. By capturing neighborhoods as residents see them, we may more accurately capture ‘neighborhood’ effects. Because of this, an aggregate measure informed by resident perceptions of neighborhood spatial scale is developed in chapter four. This unit is then tested against models aggregated to census block and .5 mile egohood boundaries. Results indicate that models incorporating neighborhood boundaries as residents define them tend to explain more variance in neighborhood cohesion than the other approaches. While there is little difference between approaches found in models focused on explaining the variance in standard deviations in neighborhood perceptions, these results seem to indicate that this is a useful approach that warrants further refinement. The final chapter outlines the overall project and connects findings back to prior research and theory. The project’s limitations are also discussed leading to avenues for future research. Suggestions are also provided for the usefulness of this approach to other fields that may benefit from analyses that seem tied to resident perceptions of neighborhood boundaries.

Future climate projections predict a global increase in precipitation variability as well as a trend towards aridity, which can influence how nitrogen (N) is cycled in terrestrial ecosystems. Increasingly arid conditions can alter N cycling by increasing soil inorganic N concentrations and making this N more susceptible to loss. Further, shifts in precipitation patterns in one season can establish effects on the N cycle that can “carry-over” into the following season, known as precipitation legacy effects. However, how current and historic precipitation patterns may alter soil N availability through changes in inorganic N supply—i.e., gross N mineralization and gross nitrification—is not well constrained. We measured the effects of altering precipitation variability on soil N cycling using an isotope pool dilution on soils from a Pinyon–Juniper dryland under a precipitation manipulation experiment. We found that wintertime drought, the most extreme drought we imposed, reduced gross N mineralization by ~2.5x and gross nitrification rates by ~9.5x compared to ambient conditions, establishing a legacy effect that reduced gross N mineralization by ~2x compared to ambient conditions the following summer. As we observed an increase in soil N concentrations (~6x greater than ambient conditions) simultaneous with lower gross rates of inorganic N supply under drought, our results imply that dry conditions must have reduced N immobilization rates below those of inorganic N supply to account for the increased N availability. Our measurements show that extreme drought can have negative consequences on inorganic N supply that persist even after the drought ends, suggesting these responses may become more common as drought is expected to increase in frequency and severity across the globe.

This work takes the first steps towards linking symbiotic associations of microbes to desert plants with global methane cycling. Drylands occupy 37.1% of the Earth’s terrestrial surface and are increasingly being converted into agricultural fields. Sustainable and productive use of arid land requires a better understanding of the functional traits of microbes inhabiting native arid environments. To improve our knowledge of native arid ecosystem functioning, we performed preliminary studies with soil samples collected from Anza-Borrego Desert State Park. The following discoveries were made: 1) Metagenomic data identified the methanotrophic bacteria Methylocaldum sp. as the predominant genus within the methanotrophic community in vegetated and unvegetated soil of the Anza-Borrego desert. 2) The consumption rate of atmospheric methane positively correlated with the presence of vegetation; 3) Genome annotations of methanotrophs from the rhizosphere of desert plants highlight several functions that can contribute to interactions with plants; 4) Methanotrophs have the potential to improve plant survival during drought stress. Based on these data we propose that in arid environments plants facilitate methane transport to the ground and cooperate with methane-consuming microbes to capture methane efficiently evolved in deeper soil layers and atmospheric methane (i.e. reverse chimney), which is then metabolized to provide supplemental resources for survival in water-limiting conditions. The results suggest that the plant-methanotroph associations represent an overlooked sink of atmospheric methane in dryland ecosystems. We show that supplementation with native Methylocaldum isolates from the Anza-Borrego Desert can potentially improve crop drought tolerance (e.g. Sorghum). Furthermore, this work provides essential evidence that targeted engineering of association between crops and methanotrophs in dryland soils can enhance atmospheric methane sink, ultimately influencing the global climate.

Regenerative agricultural practices strive to produce food that have lower economic, environmental, and social impacts defined by the processes used (i.e. using cover crops, reducing tillage) or by proposed outcomes (i.e. improving soil health, improving biodiversity). In almond orchards the regeneration of ecosystem health and productivity can be achieved through practices including recycling of almond hull and shell resources as soil amendments, reducing dust production during harvest, and minimizing synthetic fertilizer inputs. The current and set standards of conventional almond production poses a unique challenge when proposing regenerative agriculture goals. To facilitate almond harvest and simplify irrigation and fertigation practices, almond orchards are typically managed with the orchard floor bare, and trees are grown in rows with irrigation and fertilization localized exclusively to the 3.6 meter (12-ft) wide soil strip below the tree canopy. The alleyways are often left unirrigated and bare to facilitate almond harvest. These conventional practices reduce soil health, whereas with the advent of off-ground harvesting, opportunities exist to incorporate cover crops (CC) and the use of organic matter amendments (OMA) including almond hulls and shells (AHS) to maintain a more permanent mulch layer to protect the soil. This thesis examined the changes in soil physical, chemical, and biological properties from the use of AHS and a CC mix of 60% oats, 35% spring peas, and 5% yellow mustard in a randomized complete block design field trial. Nutrient cycling and OMA decomposition dynamics was analyzed one and two years after practice adoption. Effects on soil aggregate stability, particulate organic matter (POM), mineral associated organic matter (MAOM), microbial biomass, and soil moisture in amended trees harvested using on-ground and off-ground harvest machines were determined. Results showed increased C and N in microaggregate and macroaggregate soil organic matter fractions, increased saprophytes and arbuscular mycorrhizal fungi, and improved soil moisture in amended soils. Exchangeable potassium (XK) and soil organic matter (SOM) increased in the amended on and off-ground harvest treatments and was highly correlated with microbial communities measured. We found that after 3 years of AHS OMA and catch-frame harvest, MAOM and soil aggregate stability increased due to this undisturbed forest litter layer which may allow more microbial processes to contribute to more MAOM over time. Cover crop biomass was highest in oats but peas contributed the highest soil N. 192 days after AHS application, an average of 38% of the AHS material decomposed and 90 days after the CC were seeded, an average of 69% of the CC material decomposed.

Effective cover crop termination by roller crimping remains a challenge in organic no-till vegetable systems. In addition, slow decomposition of surface residues can delay planting and lead to competition for soil resources. Application of microbial inoculants to promote residue decomposition could potentially address these constraints. Two field studies were conducted in Davis, California to evaluate the effect of microbial tea treatments on the rate of cover crop surface residue decomposition, labile carbon and inorganic N pools, and sweet potato yield under different environmental conditions. To assess fall termination of a summer cover crop, four treatments were applied to sorghum sudangrass following roller crimping: thermophilic compost tea, vermicompost tea, a commercially available microbial inoculant (EM-1), and a roller crimped control. To assess spring termination of a winter cover crop, four treatments were applied to a multispecies cover crop mix (bell beans, peas, vetch, wheat) following roller crimping: vermicompost tea, EM-1, a roller crimped control, and a tilled treatment. Litter bags were used to measure residue decomposition and soil samples were obtained from 0-10 cm to determine inorganic N and POXC concentrations. In contrast to our hypothesis, we found no effect of the microbial tea treatments on the rate of residue decomposition in either study. Decomposition following roller crimping was much greater in the spring than the fall (41.6 vs 16.4%), likely due to the presence of legumes in the winter cover crop mix and higher soil surface moisture due to increased rainfall throughout the litter bag retrieval period in the spring. The microbial tea treatments had no effect on soil ammonium-N, nitrate-N, or POXC concentrations. However, soil ammonium-N and nitrate-N concentrations significantly increased by 39 and 51% in the tilled vs. roller crimped treatments, respectively (ammonium-N: 1.2 mg N kg-1 and 0.73 mg N kg-1; nitrate-N: 5.5 mg N kg-1 and 2.7 mg N kg-1). Meanwhile, POXC increased significantly over time in the fall termination study, but decreased over time in the spring termination study. There were no significant differences in sweet potato yield between the roller crimped treatments and the tilled treatment, indicating the presence of surface residues combined with the difference in soil N levels had no effect on sweet potato yield.

The environmental impact of cattle includes enteric and manure management derived greenhouse gas (GHG) emissions and reactive nitrogen (Nr) production. In the United States, beef and dairy cattle are responsible for 27.4% and 5.2% of total methane (CH4) emissions through enteric fermentation and manure management, respectively (EPA, 2024). Concurrently, beef and dairy cattle manure management accounts for 8.4% of total GHG emissions from agriculture, while agricultural soil management (including manure fertilizer application) accounts for 49% of total agricultural GHG emissions (EPA, 2024). Feed additives are a well-studied technique with potential to reduce enteric GHG emissions. With respect to additives, containing plant secondary metabolites (PSM), or constituent molecules derived from PSM, it remains an open question as to whether these molecules retain bioactivity throughout the gastrointestinal tract. If so, these feed additives could then continue affecting GHG and Nr production in manure. Additionally, improved diet formulation can aid in increasing digestibility, delivering more nutrients to the animal and less in manure (feces and urine). In Chapter 2 of the present dissertation, the objective was to determine the effect of plant secondary metabolite-based feed additives on fecal chemistry, and how these chemical properties would lead to differences in GHG emissions and Nr when feces were amended to different soils and at different water content levels. This was achieved by recovering feces from a live-animal trial where 24 Angus and crossbred Angus steers were divided as a randomized incomplete block design to determine the effects of the feed additive treatments Agolin (AG) or Mootral (MT) as compared to cattle on an un-supplemented diet (UN) as controls. The AG treatment was fed at 1 g/day dry matter (DM) and MT was fed at 23.5 g/day DM. Fresh fecal samples were collected from all animals per pen after cattle had been on treatment for 4 weeks, and were amended to two different soil types: sandy loam and clay, at two different water holding capacity (WHC) levels: 50% and 90%, in a completely randomized factorial design laboratory incubation. Soil-only control (CON) samples were prepared alongside feces-amended samples. The GHGs and Nr were recorded for 30 days. The AG (-73.2 mg kg-1) versus MT (-60.5 mg kg-1) treatment had lower cumulative mineralized N (Nmin) in the clay, 90% WHC category ( p < 0.01). The AG (98.2 mg kg-1) versus MT (144.5 mg kg-1) treatment had lower carbon dioxide (CO2) emissions in the clay, 90% WHC category (p < 0.01), and higher CO2 emissions in the sandy loam, 90% WHC category (p < 0.01). Cumulative nitrous oxide (N2O) emissions were not different among feces-amended soils and soil-only controls and were only affected by soil type, with clay having higher emissions than sandy loam (p = 0.01). Cumulative CH4 emissions were only affected by the three-way interaction of treatment x soil type x WHC. We conclude that the C and N dynamics as influenced by AG and MT inclusion in the diet are transient and highly dependent on soil characteristics. Chapter 3 of the present dissertation entails a similarly designed laboratory incubation with a focus on how crude protein content in the diet affects GHGs and Nr in feces-amended soils. Three levels dietary crude protein were achieved by mixing corn dried distillers grains with solubles (DDGS) into diets at the University of California, Davis feedlot which were fed to three groups of cattle randomized to each treatment diet. Levels of DDGS inclusion in treatment diets were: deficient (DEF; 19.63% DM), balanced (BAL; 27.28% DM), and excess (EXS; 28.82% DM). Feces were collected from Angus steers on each treatment and amended to a sandy clay loam and a clay loam at 50% and 90% WHC. In a 32-day incubation experiment, EXS (961 µg kg-1) had greater cumulative N2O than DEF (686 µg kg-1) and BAL (392 µg kg-1) at 90% WHC in both the sandy clay loam and clay loam (p < 0.01). BAL also had lower N2O than DEF in the clay loam at 90% WHC (p < 0.01). The soil type and WHC variables impacted emissions, leading to increased variability among treatments. Reduced DDGS in the diet provided sufficient dietary N for animal performance while minimizing excreta N emissions. In Chapter 4 of the present dissertation, a feed additive blend of quebracho and chestnut extracts along with a carrier from cereals rich in saponins was fed to dairy cattle at 0.15% DM for 64 days. A group of 24 multiparous dairy cows were blocked by parity, dry matter intake, baseline CH4, and days in milk, and randomized to receive the quebracho treatment (BPX) or an un-supplemented diet (CON). In this study, fecal chemistry and fecal microbiota were analyzed over the course of the animal trial by collecting samples from each animal on days 0-, 16-, 32-, and 64 of the study. Using 16S rRNA gene amplicon sequencing, a total of 1,538 amplicon sequence variants were identified. Phylogenetic diversity of microbiota exhibited a treatment  day effect (p < 0.01). Fecal C and N exhibited a corresponding treatment  day effect (p < 0.01); however, differences were only seen between BPX and CON on day 16, indicating a potential transient effect of the feed additive, where the microbiota and N partitioning returned to baseline after a slight perturbation. Differences in fecal chemical properties were also observed, with BPX having greater levels of indole-3-lactate than CON (p = 0.01). This corroborates known effects of tannins on microbial protein degradation. Greenhouse gas emissions were also measured for feces in a 14-day laboratory incubation, no differences were observed between BPX and CON for N2O (p = 0.45), CH4 (p = 0.69), or CO2 (p = 0.97). While feed additives like those tested here, have been implemented successfully, our results suggest that the microbiota can tolerate low doses of a tannin-based product, leading to no long-term changes. Higher doses may be more efficacious, but cost prohibitive. Our results stand alongside a paucity of currently published results investigating the effects of a PSM-based feed additive on feces amended to soil. Further research on the biotransformation of the active ingredients in the gastrointestinal tract, and minimum inhibitory concentrations toward microbes in manure and soil is needed to best align dosing with animal health and performance and intended effects on manure and soil chemistry.

My PhD research celebrates nearly two centuries of theoretical advancements in soil-water interactions, specifically focusing on soil infiltration. Over time, mathematical models and experimental techniques have enriched our understanding of infiltration processes, contributing to improved water management, soil conservation, and environmental practices. Despite the proliferation of models enhancing our understanding of soil-water interactions, the diversity of available options poses challenges in model selection and data analysis. To address these challenges, I first conducted a detailed literature review tracing the theoretical and historical evolution of infiltration models. This review categorized 138 models based on their conceptual and empirical foundations, covering a wide spectrum of applications to guide researchers in selecting appropriate models and challenge existing theories to advance infiltration modeling. Building on this review, I addressed the uncertainty in extracting soil hydraulic properties, such as saturated hydraulic conductivity (Ks) and sorptivity (S) from experimental infiltration data to evaluate the physical meaning of these estimated properties across various infiltration models. As such, I performed a metadata analysis using a global database of 5,023 cumulative infiltration curves to assess the variability in (Ks) and (S) parameters across various one- and three-dimensional models and extraction techniques. My analysis revealed insights into the robustness of current practices applied in soil water parameter estimation. Another key finding from my literature review on infiltration modeling is the significant gap in theoretical frameworks studying the impact of soil structure on infiltration. To this end, I conducted a meta-analysis systematic review to establish correlations between infiltration rates and soil structural properties, emphasizing the need for integrated approaches. As we advance, leveraging large databases and advanced analytics can enhance our understanding of soil-water interactions and address real-world challenges. My research calls for continued scientific rigor and curiosity to uncover new relationships of dominant processes in soil science.

This dissertation is a three-part interconnected geographic study of fine scale soil moisture using monitoring, modeling, and remote sensing in coastal northern California. Although the focus is on hydrology and soil moisture, soil moisture naturally lends itself to be a unifying theme in physical geography connecting hydrology, agriculture, ecology, climate, wildfire, remote sensing, and humans through management actions. The objective of the three chapters is to advance the characterization and process understanding of soil-plant-water dynamics spatially and temporally and to provide high resolution soil moisture data that can be used by decision makers to improve situational awareness and planning through streamflow forecasting, landslide detection, drought warning and fire danger.In Chapter 1, monitoring data was collected in the context of a paired watershed study and soil and tree moisture probes were used to examine soil water-tree-ecosystem dynamics in Sonoma County, California. The results of this study showed: 1) there were noticeable effects on soil moisture and evapotranspiration from mechanical tree thinning and prescribed burns compared to an untreated watershed, 2) soil moisture decreased at the surface and increased in the root zone post-treatment, relative to an untreated watershed, 3) evapotranspiration decreased by 90 mm in the post treatment year for the treated watershed, 4) soil and tree moisture in situ sensors can be used as a surrogate for discrete and time consuming Live Fuel Moisture (LFM) measurements, and 5) soil moisture thresholds can be used to help identify wildfire danger and drought conditions. Improving real-time wildfire danger and drought conditions using existing or low-cost in situ sensors can improve situational awareness and planning.In Chapter 2, a novel L-band Unoccupied Aerial System (UAS) was used to map surface (0-10 cm depth) soil moisture at a high resolution in a complex, natural landscape. L-band UAS was used to map soil moisture at 5-50 meters resolution in a 3,200-acre mixed grassland-forested landscape in Sonoma County, California. The L-band dielectric constant model produced soil moisture maps with an unbiased root mean squared error (ubRMSE) of 0.07 m3/m3. A random forest machine learning model was also applied and produced surface soil moisture maps at 10-m and 30-m using optical UAS and thermal infrared (TIR) satellite data with accuracy levels of 0.020 m3/m3 and 0.017 m3/m3 ubRMSE, respectively. Improved fine-scale soil moisture maps developed using UAS-based systems may be used to help reduce fire risk and improve hydrologic models, streamflow forecasting, and early detection of landslides.In Chapter 3, high resolution root zone soil moisture, live fuel moisture, and fire danger maps were developed using machine learning, water balance, and regression models that connected the results from Chapter 1 and Chapter 2. Root zone soil moisture maps were developed using a random forest model that resulted in R2 values from 0.71 to 0.80. LFM maps were made using relationships developed in Chapter 1 and modeled soil moisture anomalies with an R2 of 0.82 compared against LFM data. The soil moisture anomaly and LFM results were applied to produce retrospective maps of fire danger that indicated predominantly medium to high fire danger during two historical fire ignition dates. An accumulated soil moisture anomaly (aSMA) showed interannual and long-term patterns and characterized an above-normal aSMA that switched to a below-normal aSMA right before the large wildfires that occurred between 2015-2020. Chapter 1 showed that root zone soil moisture was a better predictor of LFM than surface soil moisture and in Chapter 3, root zone soil moisture anomalies were shown to be an accurate predictor for LFM maps that can be useful to assess wildfire danger conditions at a high temporal and spatial scale. High resolution fire danger and LFM maps can be used to improve awareness of landscape conditions and early drought warning for decision makers.

Soils contain diverse and dynamic communities of microbes that interact with, and influence, microbiota in and on plants, animals, and humans. These exchanges, such as between soil and human microbiota, are part of a vast, integrated microbial ecosystem that underpins much of terrestrial life on Earth. This dissertation addresses relationships between soil microbiota and human microbiota, and their connections with human health. I approached these investigations by collecting and compiling a range of data spanning soil microbiota, child gut microbiota, health and disease factors, household characteristics, and biophysical landscape characteristics among 144 households across three rural counties in western Kenya. Using these data I first investigated the variation in gut microbial communities between children living in different rural environments, including agriculture, rural settlements, and uncultivated forest and shrubland landscapes. Although we did not find differences in child gut microbial diversity between children from these different landscapes, we found (1) significant differences in abundances of specific gut microbial taxa that are associated with health and disease, and (2) landscape-level differences in the taxa that discriminate children with a recent diarrheal episode from those without. These findings are initial evidence of a potential landscape association with the child gut microbiota, with implications for understanding childhood diarrheal disease burden. Next I investigated the relationship between the child gut microbial community and the soil microbiota in children’s households using a microbial source tracking approach. I found that the proportion of the gut microbiota attributed to soils (S2F proportion) varied among households, and in some was greater than a third, indicating a significant relationship between soil and gut microbiota at the household level. Furthermore I observed that S2F proportions were notably higher in households where I collected data later in the region’s seasonal rainy-dry cycle. Using three complementary regression modeling approaches, I examined potential correlates of S2F proportion from among the household and landscape biophysical data. I found stronger associations among soil and climate characteristics than among household and social factors, and soil pH and seasonal precipitation had the greatest association with S2F proportion. These results demonstrate the potential involvement of seasonal climate and soil properties in the relationship between the child gut microbiota and soil microbiota. Finally, I evaluated the capability of the soil and fecal microbiota to predict child and household characteristics using a series of machine-learning based classifier models. Utilizing only the fecal microbial data, the classifier successfully identified household-level landscape classes. With soil microbial data, the model successfully classified households by their landscape classes, soil classes, drinking water source, and season of sampling. A relatively small number of soil taxa were more important in the model’s performance, including taxa commonly found in the human gut. These findings indicate that a seasonal change in soil microbiota may influence the composition of the child gut microbiota in rural households. Altogether, this research presents novel evidence that household- and landscape-level exposures, including to soil microbiota, are strongly associated with the human gut microbial community, and that these associations hold potential implications for health and disease.

Composts are increasingly used as soil amendments to enhance soil health and agricultural sustainability. However, their effects on nitrogen (N) availability, and therefore their fertilizer potential, greenhouse gas (GHG) emissions, carbon (C) sequestration, and crop water use efficiency (WUE) are unclear. We conducted a three-year field experiment in sub-surface drip-irrigated tomatoes to investigate the effects of co-compost (FW; food waste and green waste) and green waste compost (GW) on yield and fertilizer N use, as co-composts are gaining research interest as a means of diverting organic waste from landfills and increasing the nutrient value of GW compost. Three FW and GW compost rates (0, 9 t ha-1, or 18 t ha-1) and four fertilizer N levels (0%, 70%, 85% and 100% of recommended rate) were examined, and treatment combinations were chosen to replace a certain fertilizer N input with compost N. 15N-labeled fertilizer was used to determine fertilizer N crop use efficiency (true NUE), while apparent NUE was determined by comparing crop N uptake between treatments and no compost controls. In years two and three, FW and GW sustained and/or increased yield compared to no compost when low fertilizer rates were applied (0% N and 70% N), with lower apparent and true NUE observed in the compost treatments compared to no compost when 70% N and 85% N was supplied. These results suggest that compost served as an N source or primed the mineralization of soil N, potentially replacing fertilizer N crop uptake. Fertilizer N remaining in topsoil post-harvest was greatest for FW compared to GW and controls, while no difference in nitrate leaching potential was found among treatments, except in year two FW had the lowest nitrate leaching potential. These findings did not consistently produce statistically significant effects but show the potential role of compost in immobilizing fertilizer N and priming soil N mineralization. Within the same field experiment, we also evaluated the effects of FW and GW compost on GHG fluxes and cumulative emissions, soil C content, and nematode populations and diversity as a potential biological mechanism for C sequestration. FW and GW composts had no significant effects on the fluxes or annual cumulative emissions of N2O or CH4, likely because emissions under sub-surface drip irrigation were already low and the considerable variation in low fluxes obscured the detection of significant changes. The application of compost significantly increased soil respiration (carbon dioxide (CO2) emissions). The level of fertilizer N played a significant role in regulating N2O and CH4 emissions, as these fluxes decreased with lower levels of fertilizer N. Soil C content increased with the addition of FW and GW composts compared to the no-compost controls in the 0-15 cm soil layer. This increase was not observed in deeper soil layers of 15-30, 30-60, or 60-90 cm. FW and GW compost treatments reduced δ13C values in the topsoil, indicating that the newly added soil C was derived from the compost. Furthermore, compost application increased the presence of certain individual genera of bacterial- and fungal-feeding nematodes compared to the no-compost controls, offering insights into potential biological mechanisms for C decomposition and sequestration. However, no significant treatment effects were observed on individual genera of nematodes. These findings indicate that although compost may not directly lead to reductions of GHG, it holds potential for mitigating climate change by sequestering C in agricultural soils.We also conducted a one-year field experiment in two, surface drip-irrigated, super-high density olive orchards (in Woodland and Stockton, California, hereafter named the MR and ST sites, respectively) to investigate the effects of compost and fertilizer N management on yield and intrinsic WUE (iWUE; the ratio between net CO2 fixation and stomatal conductance). The olive industry in California is rapidly growing, and there is a need for irrigation and N management guidelines to be updated, taking climate change impacts on the state’s diverse microclimates and increased tree density into consideration. At each field site in our trial, two GW compost rates (0 or 9 t ha-1) and three fertilizer N rates (84, 112, or 140 kg N ha-1 at the MR site, and 28, 42, or 56 kg N ha-1 at the ST site) representing a low, medium, and high fertilizer rate were applied. During the growing season, monthly leaf sampling and concurrent soil sampling were conducted for analyzing δ13C, iWUE, and δ18O, which are proxies for plant water status, and soil gravimetric water content (GWC), NH4+, and NO3-. Compost increased yield compared to no-compost controls at the lowest fertilizer N level at the ST site, while no treatment effects on yield were observed at the MR site. Compared to no-compost controls, compost tended to increase olive δ13C and iWUE at lower fertilizer N levels, indicating increased stomatal closure and plant water stress. In contrast, compost decreased δ13C and iWUE at the highest fertilizer N level, indicating that additional N decreased compost-induced plant water stress. These treatment effects on δ13C and iWUE were more significant at the MR site than the ST site, and the overall iWUE was lower at the ST site than the MR site, indicating less plant water stress in the ST site, likely due to higher precipitation, older tree age, and thus larger root zones for water uptake masking treatment effects. The result of compost increasing iWUE, suggesting that the compost increased water stress for olive trees, was unexpected because compost typically improves soil water-holding capacity for crop uptake. However, in our study, soil GWC results contradicted these typical compost effects on soil water, as there was generally a lack of significant treatment effects on GWC at both field sites. There were also no consistent compost or fertilizer N effects on olive δ18O, an indicator for transpiration, and little to no treatment effects on soil NH4+ or NO3−. Soil NH4+ and NO3− did not show significant correlation with plant iWUE or δ18O, whereas soil GWC was positively correlated with iWUE at the MR site. Our results suggest olive iWUE was regulated more by soil water content than plant-available N content.