SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Data from the fossil record are used to illustrate biodiversity in the past and estimate modern biodiversity and loss. This data is used to compare current rates of extinction with past extinction events. Paleontologists are encouraged to use this data to understand the course and consequences of current losses and to share this knowledge with researchers interested in conservation and ecology.
This review summarizes a decade of research in which we have used molecular methods, in conjunction with more traditional approaches, to study hot spring cyanobacterial mats as models for understanding principles of microbial community ecology. Molecular methods reveal that the composition of these communities is grossly oversimplified by microscopic and cultivation methods. For example, none of 31 unique 16S rRNA sequences detected in the Octopus Spring mat, Yellowstone National Park, matches that of any prokaryote previously cultivated from geothermal systems; 11 are contributed by genetically diverse cyanobacteria, even though a single cyanobacterial species was suspected based on morphologic and culture analysis. By studying the basis for the incongruity between culture and molecular samplings of community composition, we are beginning to cultivate isolates whose 16S rRNA sequences are readily detected. By placing the genetic diversity detected in context with the well-defined natural environmental gradients typical of hot spring mat systems, the relationship between gene and species diversity is clarified and ecological patterns of species occurrence emerge. By combining these ecological patterns with the evolutionary patterns inherently revealed by phylogenetic analysis of gene sequence data, we find that it may be possible to understand microbial biodiversity within these systems by using principles similar to those developed by evolutionary ecologists to understand biodiversity of larger species. We hope that such an approach guides microbial ecologists to a more realistic and predictive understanding of microbial species occurrence and responsiveness in both natural and disturbed habitats.
NASA’s DEVELOP program engages individuals and organizations in 10-week feasibility studies to apply NASA Earth observations (EO) to decision makers’ needs. Since 2018, DEVELOP conducted 21 projects in Central and South America, eight of those in collaboration with Sistema de la Integración Centroamericana (SICA) and its member state partner agencies. These projects addressed a diverse set of community needs across multiple themes, including 11 addressing issues related to biodiversity and ecosystem services that utilized a suite of EO to measure and monitor deforestation, habitat suitability, and land change impacts on watershed health in Peru, Costa Rica, Panama, Honduras, and Colombia. This poster introduces DEVELOP, its approach to capacity building, key partnerships, and project results highlighting the capabilities of EO for enhanced decision making in the area of ecosystem services and biodiversity.
There are many internal and external drivers of animal movement. For example, where might an animal go if it’s hungry, or how will it move if it’s really windy? The Internet of Animals project aims to combine animal telemetry data with earth observations to better support applied ecological management, architect a next-generation space-based animal tracking system and develop technology that can link to biodiversity and habitats via remote sensing. In this talk, Morgan Gilmour will provide an overview of movement ecology, remote sensing, and how earth observations with NASA’s assets can help inform biodiversity and conservation. Morgan is a Research Scientist at NASA Ames Research Center. Her research focuses on marine animal movement ecology. Some recent projects include investigating animal movement in relation to marine protected areas in the central Pacific and quantifying at-sea habitat use by albatrosses.
Given the speed at which humans are changing the climate, species with high degrees of endemism may not have time to avoid extinction through adaptation. We investigated through teleconnection analysis the origin of rainfall that determines the phylogenetic diversity of rainforest frogs and the effects of microclimate differences in shaping the morphological traits of isolated populations (which contribute to greater phylogenetic diversity and speciation). We also investigated through teleconnection analysis how deforestation in Amazonia can affect ecosystem services that are fundamental to maintaining the climate of the Atlantic rainforest biodiversity hotspot. Seasonal winds known as flying rivers carry water vapor from Amazonia to the Atlantic Forest, and the breaking of this ecosystem service could lead Atlantic Forest species to population decline and extinction in the short term. Our results suggest that the selection of morphological traits that shape Atlantic Forest frog diversity and their population dynamics are influenced by the Amazonian flying rivers. Our results also suggest that the increases of temperature anomalies in the Atlantic Ocean due to global warming and in the Amazon forest due to deforestation are already breaking this cycle and threaten the biodiversity of the Atlantic Forest hotspot.
Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will provide updates on NASA’s prototype open-source aquatic modeling platform, Spectral Water Inversion Processor and Emulator (SWIPE), which is a comprehensive, multi-faceted modeling platform for both forward and inverse modeling of diverse aquatic ecosystems from the benthos to top-of-atmosphere (TOA). SWIPE provides a cohesive application which leverages recent advancements in particle modeling, Big Data analytics, and machine learning to develop a high-fidelity synthetic training ground for sensitivity studies and algorithm development for multispectral or upcoming hyperspectral missions. Some of the prominent features of SWIPE to be discussed include: 1. Advanced hyperspectral modeling of globally diverse algal and non-algal particles using a novel two-layer coated sphere scattering model and radiative transfer modeling, 2. Massive, highly detailed synthetic spectral libraries of Analysis-Ready-Data (ARD) which include spectral libraries of particle microphysics, water biogeophysical and optical properties, as well as surface and TOA reflectances at 1 nm resolution, 3. An ensemble of pre-built analytic, machine learning, and deep learning inversion algorithms for various water quality and biodiversity related retrieval parameters and uncertainty quantification, 4. Sensor-agnostic water quality inversion at wide ranging spatial and spectral resolutions including a codebase for seamless application in the Google Earth Engine and NASA Earth Exchange (NEX) for planetary scale analysis. SWIPE will be a fully open-source platform based in python with comprehensive documentation, tutorials, and options for distributed computing on high performance computing clusters or on single, local machines. Further, we will discuss how we envision SWIPE contributing towards a global analysis of coastal and inland water quality dynamics.
Rice paddies are both major food-production systems and critical winter habitats for wildlife. In the Civilian Control Zone (CCZ) adjoining the Korean Demilitarized Zone (DMZ), post-harvest interventions such as supplementary grain feeding and straw retention are promoted through agronomic and conservation incentives. These measures differ in ecological scope: feeding provides direct, concentrated energetic subsidies, whereas straw management alters habitat structure and resource bases. We clarified whether these pathways function in complementary or substitutive ways to support resilient, long-term conservation strategies in rice agroecosystems. Using camera traps, we evaluated the effects of three straw treatments (chopped-straw, whole-straw, straw-removed) and supplemental feeding on winter bird and mammal communities across 48 rice fields in the CCZ. Our results demonstrate that feeding produced strong, localized increases in bird abundance and richness, driven mainly by cranes (Grus japonensis and Antigone vipio) and geese (Anser spp.), with limited effects on Shannon diversity or functional structure. Among non-feeding fields, chopped-straw paddies consistently supported higher richness and Shannon diversity than whole-straw or straw-removed fields, while centroid shifts in taxonomic and functional space were modest. Mammal abundance and diversity were largely insensitive to feeding or straw regimes, varying instead with road and forest distance and regional context. Supplemental feeding and straw retention are therefore not interchangeable tools: feeding concentrates a few avian guilds, whereas chopped-straw retention enhances baseline diversity across farmland. Collectively, our findings suggest integrating low-input straw retention with targeted feeding offers a more robust pathway for sustaining winter biodiversity in rice agroecosystems.
Abstract Seasonal and El Niño-Southern Oscillation (ENSO) warming result in similar ocean changes as predicted with climate change. Climate-driven environmental cycles have strong impacts on microbiome diversity, but impacts on microbiome function are poorly understood. Here we quantify changes in microbial genomic diversity and functioning over 11 years covering seasonal and ENSO cycles at a coastal site in the southern California Current. We observe seasonal oscillations between large-genome lineages during cold, nutrient rich conditions in winter and spring versus small-genome lineages, including Prochlorococcus and Pelagibacter , in summer and fall. Parallel interannual changes separate communities depending on ENSO condition. Biodiversity shifts translate into clear oscillations in microbiome functional potential. Ocean warming induced an ecosystem with less iron but more macronutrient stress genes, depressed organic carbon degradation potential and biomass, and elevated carbon-to-nutrient biomass ratios. The consistent microbial response observed across time-scales points towards large climate-driven changes in marine ecosystems and biogeochemical cycles.
(1) Goal: The scientific objective to the proposed research is to develop a proto-type downscaled (<1 km) version of the root-zone soil moisture product called SoilMERGE or SMERGE. This objective is linked as root zone soil moisture is a critical climate variable that has a more direct influence on plant growth than precipitation. Therefore, the developed downscaled version of SMERGE can be used as input into biodiversity informatic techniques (i.e., maximum entropy modeling) Development of downscaled SMERGE will be facilitated by Department of Energy (DOE) resources specifically data from the DOE Atmospheric Radiation Measurement (ARM) facility and modeling platforms such as the Energy Exascale Earth System Model (E3SM).
Ecology, evolution, and biodiversity of microbiomes and viromes in extreme environments are key areas of research that explore how microbial communities adapt, survive, and thrive under harsh conditions. The studies published in our Research Topic advance our understanding of microbial and viral diversity, evolutionary processes, and the ecological roles of these communities, with implications for biotechnology, climate resilience, and even astrobiology.
Discussed here are the effects of anthropogenic global climate change on biodiversity. The focus is on human responses to the problem. Greenhouse warming-induced climate change may shift agricultural growing belts, reduce forests of the Northern Hemisphere and drive many species to extinction, among other effects. If these changes occur together with the mass extinctions already occurring, we may suffer a profound loss of biological diversity.
A remote sensing research agenda designed to expand the knowledge of the spatial distribution of species richness and its ecological determinants and to predict its response to global change is proposed. Emphasis is placed on current methods of mapping species richness of both plants and animals, hypotheses concerning the biophysical factors believed to determine patterns of species richness, and anthropogenic processes causing the accelerating rate of extinctions. It is concluded that biodiversity should be incorporated more prominently into the global change and earth system science paradigms.
The number of extant species of organisms is estimated to be from fewer than 3 to more than 30 x 10(6) (May, 1992). Molecular biology, comparative genetics and ultrastructural analyses provide new insights into evolutionary relationships between these species, including increasingly precise ideas of how species and higher taxa have evolved from common ancestors. Accumulation of random mutations and large macromolecular sequence change in all organisms since the Proterozoic Eon has been importantly supplemented by acquisition of inherited genomes ('symbiogenesis'). Karyotypic alterations (polyploidization and karyotypic fissioning) have been added to these other mechanisms of species origin in plants and animals during the Phanerozoic Eon. The new evolution concepts (coupled with current rapid rates of species extinction and ignorance of the extent of biodiversity) prompted this analysis of the field of systematic biology and its role in the reorganization of extant species into higher taxa. Two superkingdoms (= Domains: Prokaryotae and Eukaryotae) and five kingdoms (Monera = Procaryotae or Bacteria; Protoctista: algae, amoebae, ciliates, foraminifera, oomycetes, slime molds, etc.; Mychota: 'true' fungi; Plantae: one phylum (division) of bryophytes and nine phyla of tracheophytes; and Animalia) are recognized. Two subkingdoms comprise the monera: the great diverse lineages are Archaebacteria and Eubacteria. The criteria for classification using molecular, ultrastructural and genetic data for this scheme are mentioned. For the first time since the nineteenth century, logical, technical definitions for each group are given with their time of appearance as inferred from the fossil record in the primary scientific literature. This classification scheme, which most closely reflects the evolutionary history, molecular biology, genetics and ultrastructure of extant life, requires changes in social organization of biologists, many of whom as botanists and zoologists, still behave as if there were only two important kingdoms (plants and animals).
Based on geomorphic character and mapped geology, geologists have interpreted the landscape surrounding the Andes Mountains as becoming progressively younger to the East. These sedimentary materials filled the late Miocene swampland that formerly occupied central and western Amazonia. Apart from the ancient landscapes of the Guiana Highlands (top right, figure 1a), Zone Ac is the oldest, followed by Zone Aw, within which megafan Jw is older than megafan Je (figure 1a). DNA-based paleogeography of the trumpeters shows that younger clades diverge from parent lineages with increasing distance from the Andes chain. Thus, Psophia napensis diverges from the P. crepitans parent, and P. ochroptera diverges from P. napensis. The P. ochroptera population is confined solely to the Je megafan (figure 1a). The same trend is seen on the south side of the Amazon depression. Since the timing of the events seems to be of exactly the same order [post-Miocene for the land surfaces and trumpeter divergence within the last 3 million years (figure 1d)], it seems reasonable to think that the megafans provided the substrate on which new bird lineages could speciate. Such physical controls of evolution are becoming more important in the understanding of biodiversity.
Ocean color remote sensing has provided the scientific community with unprecedented global coverage of chlorophyll a, an indicator of phytoplankton biomass. Together, satellite-derived chlorophyll a and knowledge of Phytoplankton Functional Types (PFTs) will improve our limited understanding of marine ecosystem responses to physiochemical climate drivers involved in carbon cycle dynamics and linkages. Using cruise data from the Gulf of Maine and the Middle Atlantic Bight (N 269 pairs of HPLC and phytoplankton absorption samples), two modeling approaches were utilized to predict phytoplankton absorption and pigments. Algorithm I predicts the chlorophyll-specific absorption coefficient (a*(sub ph) (m(exp 2) mg chl a(exp - 1)) using inputs of temperature, light, and chlorophyll a. Modeled r(exp 2) values (400700 nm) ranged from 0.79 to 0.99 when compared to in situ observations with approximately 25 percent lower r(exp 2) values in the UV region. Algorithm II-a utilizes matrix inversion analysis to predict a(sub ph)(m(exp -1), 400700 nm) and r(exp 2) values ranged from 0.89 to 0.99. The prediction of phytoplankton pigments with Algorithm II-b produced r(exp 2) values that ranged from 0.40 to 0.93. When used in combination, Algorithm I, and Algorithm II-a are able to use satellite products of SST, PAR, and chlorophyll a (Algorithm I) to predict pigment concentrations and ratios to describe the phytoplankton community. The results of this study demonstrate that the spatial variation in modeled pigment ratios differ significantly from the 10-year SeaWiFS average chlorophyll a data set. Contiguous observations of chlorophyll a and phytoplankton biodiversity will elucidate ecosystem responses with unprecedented complexity.
Hyperspectral remote sensing has the potential to continuously scale plant function and plant diversity information from landscape to global extents. Numerous studies have indicated that VSWIR (400-2500 nm) reflectance properties of vegetation capture evolutionarily conserved biochemical, structural, and other functional attributes of plant species. Spectral properties conserved in plants provide the opportunity to both 1) aggregate species into lineages with improved classification accuracy and 2) link those lineages directly to plant traits. Full realization of this goal will enable parameterization of Land Surface Models (LSMs) with remotely sensed information, e.g., canopy nitrogen, and better representations of biodiversity and functional diversity in biogeographic studies. In this study, we use hyperspectral AVIRIS data from the 2013 HyspIRI campaign over the Southern Sierra Nevada, California flight box to investigate the potential for incorporating evolutionary thinking into landcover classification. We link the airborne hyperspectral data with vegetation plot data from roughly 1372 surveys and a phylogeny representing 1361 species. We aggregate species into lineages ranging from species level groups down to similar number of Plant Functional Types as often used in LSMs. We assessed the ability of Random Forest and Partial Least Squares Discriminant Analysis to discriminate across these different phylogenetic scales and determine the optimal number of lineages to classify. Although there are some temporal and spatial differences in our training data, our best approaches achieved moderate classification accuracy (Kappa > 0.65). Given an optimal number of lineages, we explored approaches to improve classifications including machine learning and unmixing approaches. This work suggests that lineage-based methods may be a promising way to leverage the huge amounts of data that will come from high resolution and high return interval hyperspectral data planned for the Surface Biology and Geology mission with sparsely sampled existing ground-based ecological data.
Explore the source record for details and available documents.
Remote sensing is defined as making observations of an event or phenomena without physically sampling it. Typically this is done with instruments and sensors mounted on anything from poles extended over a cornfield,to airplanes,to satellites orbiting the Earth The sensors have characteristics that allow them to detect and record information regarding the emission and reflectance of electromagnetic energy from a surface or object. That information can then be represented visually on a screen or paper map or used in data analysis to inform decision-making.