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NASA NTRS1976

Public health applications of remote sensing of vector borne and parasitic diseases

Results of an investigation of the potential application of remote sensing to various fields of public health are presented. Specific topics discussed include: detection of snail habitats in connection with the epidemiology of schistosomiasis; the detection of certain Anopheles breeding sites, and location of transient human populations, both in connection with malaria eradication programs; and detection of overwintering population sites for the primary screwworm (Cochliomyia americana). Emphasis was placed on the determination of ground truth data on the biological, chemical, and physical characteristics of ground waters which would or would not support the growth of significant populations of mosquitoes.

Source record↗

NASA NTRSDate not supplied

Climate Anomalies Correlation with Population Trends of the Eastern Towhee in the Mid-Eastern U.S.

The species of sparrow identified by foraging under dense thickets, the Eastern Towhee (Pipilo erythrophthalmus) resides in the Eastern United States, some populations either permanently living in the southeastern US or migratory populations living in the North. The mostly migratory Eastern Towhee has been experiencing population changes since the 1980s in the Eastern Seaboard. This species is increasing during the winter and decreasing during the summer, which is their breeding season. The Christmas Bird Count shows that in the winter, the Eastern Towhee populations have been increasing in their northern wintering range by 0.2625% in Maryland, 0.056% in West Virginia, 0.133% in New Jersey, 0.049% in Virginia, and 0.224% in Delaware from 1984-2019. The Breeding Bird Survey Data shows that in the summer, the Eastern Towhee populations have been declining in the Eastern United States by -4.0635% in Maryland, -3.073% in West Virginia, -15.0722% in New Jersey, -3.9375% in Virginia, and -6.3735% in Delaware from 1984-2015. The average climate anomalies in June range from -0.108 to 0.3705 degrees Celsius while the average climate anomalies in January range from 0.1395 to 0.5014 degrees Celsius. The Eastern Towhee are moving northward towards their northern wintering range during the winter and we explore the hypothesis of northward range shift in association with climate change. Our research displays how the behavior patterns of species are varying due to this stressor and how to better conserve species like the Eastern Towhee.

Mahlet Mesfin↗

DOE OSTI2025

Scaffolded and annotated nuclear and organelle genomes of the North American brown alga Saccharina latissima

Increasing the genomic resources of emerging aquaculture crop targets can expedite breeding processes as seen in molecular breeding advances in agriculture. High quality annotated reference genomes are essential to implement this relatively new molecular breeding scheme and benefit research areas such as population genetics, gene discovery, and gene mechanics by providing a tool for standard comparison. The brown macroalga Saccharina latissima (sugar kelp) is an ecologically and economically important kelp that is found in both the northern Pacific and Atlantic Oceans. Cultivation of Saccharina latissima for human consumption has increased significantly this century in both North America and Europe, and its single blade morphology allows for dense seeding practices used in the cultivation of its Asian sister species, Saccharina japonica. While Saccharina latissima has potential as a human food crop, insufficient information from genetic resources has limited molecular breeding in sugar kelp aquaculture. We present scaffolded and annotated Saccharina latissima nuclear and organelle genomes from a female gametophyte collected from Black Ledge, Groton, Connecticut. This Saccharina latissima genome compares well with other published kelp genomes and contains 218 scaffolds with a scaffold N50 of 1.35 Mb, a GC content of 49.84%, and 25,012 predicted genes. We also validated this genome by comparing the synteny and completeness of this Saccharina latissima genome to other kelp genomes. Our team has successfully performed initial genomic selection trials with sugar kelp using a draft version of this genome. This Saccharina latissima genome expands the genetic toolkit for the economically and ecologically important sugar kelp and will be a fundamental resource for future foundational science, breeding, and conservation efforts.

DeWeese, Kelly↗

NASA NTRS1975

The Screwworm Eradication Data System (SEDS)

One of the objectives of the SEDS was to build a versatile, yet economical, interactive system on the existing digital PDP 11/45 computers used in the Skylab production processing system. Previous experience on various interactive systems gave some background in the best methods of handling image data, registering and correcting the data, and extracting useful information from the images. The screwworm was eliminated in many parts of the United States by air-dropping sterile screwworms in areas where screwworms breed. The reproduction of the screwworm can be more or less predicted based on weather conditions -- cold weather slows the breeding, warm weather fosters it, and some moisture appears to enhance breeding conditions which, in turn, improves the chances of screwworm population growth. To obtain temperature and moisture conditions from remote areas, the NOAA improved TIROS operational satellite was selected to give data from the very high resolution radiometer (VHRR). The VHRR is a two-channel scanning instrument sensitive to energy in the visible spectrum from 0.6 to 0.7 micrometers and the infrared spectrum from 10.5 to 12.5 micrometers.

Quinn, M. J.↗

DOE OSTI2026

Synthetic Biology of Plants and Microbes for Agriculture, Environment, and Future Applications

Agriculture is under pressure to provide food for a growing population and the feedstock required to drive the bioeconomy. Methods to breed and genetically modify plants are inadequate to keep pace. When engineering crops, traits are painstakingly introduced into plants one-at-a-time, combine unpredictably, and are continuously expressed. Synthetic biology is changing these paradigms with new genome construction tools, computer aided design (CAD), and artificial intelligence (AI). “Smart plants” contain circuits that respond to environmental change, alter morphology, or respond to threats. Further, the plant and associated microbes (fungi, bacteria, archaea) are now being viewed by genetic engineers as a holistic system. Historically, plant health has been enhanced by many natural and laboratory-evolved soil microbes marketed to enhance growth, provide nutrients, or confer pest/stress resistance. Synthetic biology has expanded the number of species that can be engineered, increased the complexity of engineered functions, controlled environmental release, and assembled stable consortia. New CAD tools will manage genetic engineering projects spanning multiple plant genomes (nucleus, chloroplast, mitochondrion) and the thousands of genomes of associated bacteria/fungi. Here, this review covers advanced genetic engineering techniques to drive the next agricultural revolution, as well as push plant engineering into new realms for manufacturing, infrastructure, sensing, and remediation.

Clauer, Phillip [Massachusetts Inst. of Technology↗

NASA NTRS2020

Genetic Algorithm for Optimization of Neural Networks for Bayesian Inference of Model Uncertainty

The objective of this work was to develop a genetic optimization algorithm that can design a neural network capable of producing uncertainty estimates along with predictions. This algorithm is necessary because the inclusion of uncertainty modeling in a neural network greatly complicates the network’s design space, making the development of a converging model extremely difficult and time consuming. The genetic algorithm presented in this work uses a number of value ranges for various configurable neural network parameters to create a randomly generated population of network architectures. The initially generated population is then evolved over the course of several generations, with the best performing models breeding to produce novel network configurations. Mutations are randomly applied to the network designs to facilitate the development of adaptations beneficial to the task being performed. An experiment was conducted to validate the proposed algorithm, in which the genetic optimizer was tasked with producing a neural network capable of predicting the sound pressure level (SPL) resulting from jet-surface interaction (JSI) noise. The data used for this task was generated at the NASA Glenn Research Center in the Aero-Acoustic Propulsion Laboratory. Starting with an initial population size of 35 randomly generated networks, and evolved over the course of 10 generations, the genetic algorithm produced a design able to predict SPL as a result of JSI noise within 0.272 dB, on average.

Genetic algorithm↗

NASA NTRS2000

Landsat TM as a Tool for Locating Habitat for Cerulean Warblers

I believe that I made significant strides in three areas between fall of 1997 and fall of 2000 when I concluded my participation in the JOVE program. First, I acquired skill in digital remote sensing. This was significant to me because it had been 20 years since I had done any work utilizing remote sensing. I used my new skills in two classroom settings (forest ecology and GIS). In addition, I will participate as an instructor of digital remote sensing in a workshop for secondary educators this coming spring. Second, I received funding from the Arkansas Game and Fish Commission and the U.S. Forest Service to supplement JOVE funds. Third, and most importantly, a students and I developed a technique using LandSAT TM for identifying habitat for cerulean warblers. We developed a habitat model using logistic regression to discriminate between pixels that had a high probability of representing good cerulean warbler habitat and pixels that had a low probability of representing cerulean warbler habitat. Using this model, we located five significant populations of cerulean warblers in the Ozark National Forest of Arkansas. These populations were unknown before the initiation of this research and further represent a significant proportion of the known cerulean warblers in Arkansas. Preliminary findings were presented at the Ornithological Societies of America meeting in August of 1999. I also presented findings at the Arkansas Game and Fish Commission Research Symposium held in June of 2000. Finally, one paper is in press: James, D. A., C.J. Kellner, J. Self, and J. Davis., 'Breeding season distribution of cerulean warblers in Arkansas in the 1990's'. In addition, one paper is under construction: 'Population fluctuation and habitat selection by cerulean warblers in upland forests of Arkansas,' and one paper is under consideration: 'LandSAT TM and Logistic regression for identification of cerulean warbler habitat in upland forests of Arkansas.'

Kellner, Chris↗

NASA NTRS2011

Relationships Between Seed Weight, Germination Potential and Biochemical Reserves of Maritime Pine in Morocco: Elements for Tree Seedlings Improvement

Selection of quality seeds in breeding programs can significantly improve seedling productivity. Germination and biochemical analyses on seeds from ten natural populations of maritime pine (Pinus pinaster Ait.) in Morocco reveals significant differences among populations in seed weight, germination characters and protein content in both dry seeds and megagametophytes. During germination, the mobilization of protein content in megagametophyte is significantly different among populations than sugar content. A strong positive correlation between the germination capacity and the protein content in both dry seeds and megagametophytes indicates that the best populations in term of germination capacity may also be the richest in protein content. The present study finds that seed weight is not a good indicator for quality seed selection, nor is it recommended to increase the degree of germinability. Our results suggest that the pine population in southern Morocco might have adapted to drought conditions as it is characterized by heavy seed weight and lower speed of protein content mobilization in megagametophyte compared to northern populations growing in temperate climate.

Wahid, Nadya↗

NASA NTRS2021

Population Viability Analysis (PVA) as a Platform for Predicting Outcomes of Management Options for the Florida Scrub-Jay in Brevard County

The Florida scrub-jay (FSJ) is a species in decline because of extinction debt caused by habitat fragmentation and degradation. Understanding and managing the species and its habitats is challenging due to the complex interactions among the social system, a dynamic mosaic of scrub habitat, and active management. To provide insights into the possible fates of the FSJ populations of mainland, cape, and island sections of Brevard County, we modeled the population dynamics using the Vortex population viability analysis (PVA) software. Vortex is an individual-based simulation that allowed us to include such factors as demographic rates dependent on habitat state, impact of helpers on breeding success, and helper to breeder transition probabilities responding to availability of nearby vacant optimal habitat and vacancies due to the death of breeders. Detailed modeling of the FSJ was possible only because a lot of data about the species and its habitats have been gathered over decades of intensive research. We followed a phased approach to constructing population models that incorporated the best available science and data to address a variety of conservation actions. The first phase focused on constructing a model that incorporates sociobiology and source-sink habitat dynamics. This model allowed us to address some of the most important questions about population size and habitat quality. Once the model framework was in place, we considered the real landscapes and actual local populations, rather than just generic representations of typical FSJ dynamics. After examining the viability of the metapopulations under current conditions, we explored the likely consequences of various management actions that might slow or reverse population declines.

Population Viability Analysis↗

DOE OSTI2024

Adaptive gene loss in the common bean pan-genome during range expansion and domestication

The common bean ( Phaseolus vulgaris L.) is a crucial legume crop and an ideal evolutionary model to study adaptive diversity in wild and domesticated populations. Here, we present a common bean pan-genome based on five high-quality genomes and whole-genome reads representing 339 genotypes. It reveals ~234 Mb of additional sequences containing 6,905 protein-coding genes missing from the reference, constituting 49% of all presence/absence variants (PAVs). More non-synonymous mutations are found in PAVs than core genes, probably reflecting the lower effective population size of PAVs and fitness advantages due to the purging effect of gene loss. Our results suggest pan-genome shrinkage occurred during wild range expansion. Selection signatures provide evidence that partial or complete gene loss was a key adaptive genetic change in common bean populations with major implications for plant adaptation. The pan-genome is a valuable resource for food legume research and breeding for climate change mitigation and sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2001

Controlling Malaria and Other Diseases Using Remote Sensing

Remote sensing offers the vantage of monitoring a vast area of the Earth continuously. Once developed and launched, a satellite gives years of service in collecting data from the land, the oceans, and the atmosphere. Since the 1980s, attempts have been made to relate disease occurrence with remotely sensed environmental and geophysical parameters, using data from Landsat, SPOT, AVHRR, and other satellites. With higher spatial resolution, the recent satellite sensors provide a new outlook for disease control. At sub-meter to I 10m resolution, surface types associated with disease carriers can be identified more accurately. The Ikonos panchromatic sensor with I m resolution, and the Advanced Land Imager with 1 Om resolution on the newly launched Earth Observing-1, both have displayed remarkable mapping capabilities. In addition, an entire array of geophysical parameters can now be measured or inferred from various satellites. Airborne remote sensing, with less concerns on instrument weight, size, and power consumption, also offers a low-cost alternative for regional applications. NASA/GSFC began to collaborate with the Mahidol University on malaria and filariasis control using remote sensing in late 2000. The objectives are: (1) To map the breeding sites for the major vector species; (2) To identify the potential sites for larvicide and insecticide applications; (3) To explore the linkage of vector population and transmission intensity to environmental variables; (4) To monitor the impact of climate change and human activities on vector population and transmission; and (5) To develop a predictive model for disease distribution. Field studies are being conducted in several provinces in Thailand. Data analyses will soon begin. Malaria data in South Korea are being used as surrogates for developing classification techniques. GIS has been shown to be invaluable in making the voluminous remote sensing data more readily understandable. It will be used throughout this study to clearly demonstrate the spatial relationship between the disease intensities, geophysical variables, and socioeconomic parameters. Asides from malaria and filariasis, application of remote sensing to the control of other diseases have been vigorously pursued by NASA's Environment and Health Initiative. The current program includes projects on Rift Valley fever, St. Louis encephalitis, dengue fever, ebola, African dust and diseases, meningitis, asthma, bartonellosis, cholera, and urban health concerns. Results from these projects indicate that remote sensing will play an increasingly important role in disease control in the future.

Kiang, Richard K.↗

DOE OSTI2025

Optimizing genomic prediction for complex traits via investigating multiple factors in switchgrass

Genomic prediction has accelerated breeding processes and provided mechanistic insights into the genetic bases of complex traits. To further optimize genomic prediction, we assess the impact of genome assemblies, genotyping approaches, variant types, allelic complexities, polyploidy levels, and population structures on the prediction of 20 complex traits in switchgrass (Panicum virgatum L.), a perennial biofuel feedstock. Surprisingly, short read-based genome assembly performs comparably to or even better than long read-based assembly. Due to higher gene coverage, exome capture and multi-allelic variants outperform genotyping-by-sequencing and bi-allelic variants, respectively. Tetraploid models show higher prediction accuracy than octoploid models for most traits, likely due to the greater genetic distances among tetraploids. Depending on the trait in question, different types of variants need to be integrated for optimal predictions. Furthermore, our study provides insights into the factors influencing genomic prediction outcomes, guiding best practices for future studies and for improving agronomic traits in switchgrass and other species through selective breeding.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Rapid quantification of whole seed fatty acid amount, composition, and shape phenotypes from diverse oilseed species with large differences in seed size

Seed oils are widely used in the food, biofuel, and industrial feedstock industries, with their utility and value determined by total oil content and fatty acid composition. Current high throughput seed oil analysis methods either lack accuracy in total fatty acid profiling or require extensive labor for lipid extraction prior to derivatization to fatty acid methyl esters (FAME) and quantification by gas chromatography (GC). Alternatively, direct whole seed FAME production methods have been developed for the very small seeds in the model species Arabidopsis thaliana but these have generally not been adapted to larger seeds of most oilseed crops. High-throughput direct whole seed FAME production methods were optimized for seeds up to 5 mg each utilizing acid-catalyzed esterification. For the oilseed species Camelina sativa, Thlaspi avernse (pennycress), Cuphea viscosissima, and Brassica napus (var. Canola), the total seed fatty acid content and composition from direct seed esterification to FAME matched that of lipid extract derivatization demonstrating the accuracy of the methods. In combination with seed phenotyping using GridFree, this approach enabled the development of a rapid pipeline for simultaneous seed weight, count, size/shape phenotyping, and oil analysis. For the larger and tougher seeds produced by Limnanthes alba (Meadowfoam) and Cannabis sativa L. (hemp) the whole seed acid-based method proved insufficient, and prior laborious homogenization of seeds was required. Therefore, a rapid one-tube bead homogenization and base catalyzed-esterification method was developed. Base-derived fatty acid esterification cannot derivatize free fatty acids leading to slightly lower total seed fatty acid than acid-catalyzed methods, however the seed oil content and fatty acid composition that is valuable for screening large numbers of samples in research populations was accurately measured. New rapid whole seed fatty acid esterification and phenotyping protocols were developed to accurately assess oilseed lipid content. These methods are particularly valuable in oilseed research, breeding, and engineering applications where efficient analysis of large numbers of samples and accurate oil fatty acid profiling is essential. While having been developed for current and emerging oilseed crops, these methods also provide a foundation from which protocols might be established for new and emerging crop species.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

An overview of switchgrass phenotypes variability across diverse populations and their implications for conversion to fuels

There have been substantial changes to the human lifestyle over the past two centuries, which are reflected in the amount of fuel we consume to power our day-to-day needs. The way we use these resources has indeed manifested in an overdependence on non-renewable energy sources, such as coal and petroleum, for generating electricity and powering our transportation needs. There is a pressing need to explore alternative ways of fueling our current lifestyle without impacting the environment. Biofuels have long been touted as a sustainable solution for use as drop-in fuels in aviation and maritime applications. Still, they have yet to establish themselves as a competitive commercial alternative, necessitating further research and development. Lignocellulosic biomass is an underutilized resource that is widely accessible for the commercial processing of renewable biofuels. Bioenergy crops, such as switchgrass (Panicum virgatum L.), which can be cultivated on marginal lands with minimal competition for agricultural land, are an ideal and promising candidate for bulk-scale biofuel synthesis. Over the past 30 years, significant progress has been made in breeding and genetically modifying these grasses to enhance their drought resilience and subsequent yields. However, discrepancies in biomass composition can lead to irregular feedstocks for downstream operations, which in turn affect overall production targets for biofuels. Here, this review examines the variability in switchgrass (P. virgatum L.) biomass phenotypes across diverse populations and plant components, and their implications for biofuel conversion. The study highlights significant variations in biomass yield, composition, and cell wall chemistry both between switchgrass genotypes and within individual cultivars. Key findings include differences in cellulose, hemicellulose, and lignin content between leaves and stems, which affect biomass digestibility and ethanol yield. The review also discusses the impact of lignin chemistry, particularly the syringyl/guaicyl (S/G) ratio, on the efficiency of biomass saccharification. Furthermore, it explores how these variations respond differently to various pretreatment techniques, affecting overall biofuel production. We conclude that understanding and quantifying this variability is crucial for optimizing switchgrass as a feedstock for commercial biofuel production, thereby potentially addressing the pressing need for sustainable energy sources in sectors such as aviation.

Kousika, Rohit [Univ. of Tennessee, Knoxville, TN ↗

DOE OSTI2026

Constitutive and inducible oleoresin defenses share genetic architectures and mechanisms in Pinus taeda

The oleoresin defense system of loblolly pine (Pinus taeda) protects trees from insects and pathogens and is an important source of renewable biofuels and chemicals, but the genetic basis of oleoresin production is poorly understood. We characterized the genetic architecture of oleoresin flow, resin canal number, stem wood terpene content, and monoterpene composition in two clonal populations of P. taeda. We used quantitative genetic analyses, genome-wide association studies (GWASs), multiplex network learning, and gene expression profiling to elucidate shared gene networks underlying defense traits and to identify high-quality candidates for breeding and engineering loblolly pine. Genetic analyses revealed polygenic inheritance and trait-to-trait correlations provide strong evidence for shared genes regulating constitutive and induced oleoresin flow. We identified 236 single nucleotide polymorphisms associated with oleoresin flow, resin canal number, and terpene composition and highlight candidate genes likely involved in terpene biosynthesis, cambial meristem reprogramming, and pathogen perception and immune signaling. Fourteen GWAS candidates were methyl jasmonate-responsive in tissues where resin canals initiate and terpene production occurs. Integrating quantitative genetics, GWAS, gene expression, and multiplex network analyses enabled the prioritization of high-quality candidate genes. This work advances the development of more resilient loblolly pine optimized for ecological performance, renewable chemical, and biofuel production.

genome-wide association study↗

DOE OSTI2026

Ecological connectivity and habitat loss shape patterns of genetic diversity in a threatened salamander

Context The maintenance of genetic diversity is essential for preserving adaptive potential in populations, yet it is increasingly threatened by landscape alteration. The field of landscape genetics offers a framework for assessing how patch-level landscape conditions, modeled at multiple scales, influence genetic diversity. Objectives We sought to assess how local environmental features and connectivity influence genetic diversity across 74 four-toed salamander (Hemidactylium scutatum) breeding wetlands in the southeastern United States. Methods Using next-generation sequencing data and hierarchical Bayesian models, we examined genome-wide heterozygosity in relation to local landscape features and ecological connectivity. We also assessed the scale of effect of landscape features and tested for temporal lag effects. Results Genetic diversity was lower in wetlands with higher levels of historic deforestation and lower connectivity. An interaction between deforestation and connectivity indicated that deforestation had stronger negative effects in isolated wetlands but weaker effects in well-connected wetlands. Accounting for scale of effect and temporal lags was critical for detecting these relationships. Conclusions Our analyses highlight the importance of assessing the spatial scale (scale of effect) and temporal lag of landscape features to detect key drivers of genetic diversity. In line with population genetic theory, our results indicate that the genetic consequences of habitat loss do not affect populations uniformly and are most severe in isolated populations where gene flow cannot buffer against loss of diversity. Altogether, we highlight the importance of considering the interaction of habitat loss and connectivity in conservation genetic management.

Hemidactylium scutatum↗

NASA NTRS2022

Winter Severity Affects Occupancy of Spring- and Summer-Breeding Anurans Across the Eastern United States

Climate change is an increasingly important driver of biodiversity loss. The ectothermic nature of amphibians may make them particularly sensitive to changes in temperature and precipitation regimes, adding to declines from other threats. While active season environmental conditions can influence growth and survival, effects of variation in winter conditions on population dynamics are less well-studied. Given that extreme winter temperatures can influence amphibian survival and fitness, we expected that increased winter severity—as measured by variability in winter temperatures and snow cover—would be associated with decreased occupancy, and that populations that experience more severe winters would have the largest sensitivities and show the greatest declines.

climate↗

NASA NTRS1997

Radar Monitoring of Wetlands for Malaria Control

Malaria is perhaps the most serious human disease problem. It inflicts millions worldwide and is on the rise in many countries where it was once under control. This rise is in part due to the high costs, both economic and environmental, of current control programs. The search for more cost-effective means to combat malaria has focussed attention on new technologies, one of which is remote sensing. Remote sensing has become an important tool in the effort to control a variety of diseases worldwide and malaria is perhaps one of the most promising. This study is part of the malaria control effort in the Central American country of Belize, which has experienced a resurgence of malaria in the last two decades. The proposed project is a feasibility study of the use of Radarsat (and other similar radar systems) to monitor seasonal changes in the breeding sites of the anopheline mosquito, which is responsible for malaria transmission. We propose that spatial and temporal changes in anopheline mosquito production can be predicted by sensing where and when their breeding sites are flooded. Timely knowledge of anopheline mosquito production is a key factor in control efforts. Such knowledge can be used by local control agencies to direct their limited resources to selected areas and time periods when the human population is at greatest risk. Radar is a key sensor in this application because frequent cloud cover during the peak periods of malaria transmission precludes the use of optical sensors.

Pope, Kevin O.↗