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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.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Study of the Microbial Diversity of a Newly Discovered East Antarctic Freshwater Lake, L27C, and of a Perennially Ice-Covered Lake Untersee

The microbial communities that reside within freshwater lakes of Schirmacher and Untersee Oases in East Antarctica must cope with extreme conditions that may include cold temperature, annual freeze-thaw cycles, exposure to UV radiation, especially during the austral summer months, low light beneath thick ice-cover, followed by seasonal darkness. The objective of this study was to assess the microbial biodiversity and distribution from samples taken from two freshwater lakes (L27C and Lake Untersee) that were collected during the Tawani 2008 International Antarctic Expedition that conducted research in this region of Antarctica. L27C is a small, previously unreported lake residing 2 km WNW of Maitri Station at Schirmacher Oasis. Biodiversity and distribution of microorganisms within the lake were studied using both culture-independent and culture-dependent methodologies based upon the analysis of eubacterial 16S rRNA gene sequences. Lake Untersee, a perennially ice-covered, ultra-oligotrophic, lake in the Otto-von-Gruber-Gebirge (Gruber Mountains) of central Dronning Maud Land was also sampled and the microbial diversity was analyzed by eubacterial 16S rRNA gene sequences derived from pure cultures. Direct culturing of water samples from each lake on separate R2A growth medium exhibited a variety of microorganisms including: Janthinobacterium, Hymenobacter, Sphingamonas, Subtercola, Deinococcus, Arthrobacter, Flavobacterium, Polaromonas, Rhodoferax and Duganella. The evaluation of samples from L27C through culture-independent methodology identified a rich microbial diversity consisting of six different phyla of bacteria. The culture-independent analysis also displayed the majority of bacteria (56%) belonged to the Class gamma-proteobacteria within the phylum Proteobacteria. Within the Class gamma-proteobacteria, Acinetobacter dominated (48%) the total microbial load. Overall, L27C exhibited 7 different phyla of bacteria and 20 different genera. Statistical analysis (Shannon-Weaver Diversity Index and Simpson Diversity Index) of the biodiversity of L27C displayed a moderately rich and diverse community. Investigations of the biodiversity and distribution of microorganisms in these lakes will help further our understanding of how the physical environment impact the structure and function within these microbially dominated ecosystems.

Huang, Jonathan P.↗
NASA NTRS2022

Using airborne and DESIS imaging spectroscopy to map plant diversity across the largest contiguous tract of tallgrass prairie on earth

Grassland ecosystems are under threat globally, primarily due to land-use and land-cover changes that have adversely affected their biodiversity. Given the negative ecological impacts of biodiversity loss in grasslands, there is an urgent need for developing an operational biodiversity monitoring system that functions in these ecosystems. In this paper, we assessed the capability of airborne and spaceborne imaging spectroscopy (also known as hyperspectral imaging) to capture plant α-diversity in a large naturally-assembled grassland while considering the impact of common management practices, specifically prescribed fire. We collected a robust in-situ plant diversity data set, including species composition and percent cover from 2500 sampling points with different burn ages, from recently-burned to transitional and pre-prescribed fire at the Joseph H. Williams Tallgrass Prairie Preserve in Oklahoma, USA. We expressed in-situ plant α-diversity using the first three Hill numbers, including species richness (number of observed species in a plant community), exponential Shannon entropy index (hereafter Shannon diversity; effective number of common species, where species are weighed proportional to their percent cover), and inverse Simpson concentration index (hereafter Simpson diversity; effective number of dominant species, where more weight is given to dominant species) at four different plot sizes, including 60 m × 60 m, 120 m × 120 m, 180 m × 180 m, and 240 m × 240 m. We collected full-range airborne hyperspectral data with fine spatial resolution (1 m) and visible and near-infrared spaceborne hyperspectral data from DESIS sensor with coarse spatial resolution (30 m), and used the spectral diversity hypothesis—i.e., that the variability in spectral data is largely driven by plant diversity—to estimate α-diversity remotely. In recently-burned plots and those at the transitional stage, both airborne and spaceborne data were capable of capturing Simpson diversity—a metric that calculates the effective number of dominant species by emphasizing abundant species and discounting rare species—but not species richness or Shannon diversity. Further, neither airborne nor spaceborne hyperspectral data sets were capable of capturing plant α-diversity of 60 m × 60 m or 120 m × 120 m plots. Based on these results, three main findings emerged: (1) management practices influence grassland biodiversity patterns that can be remotely detected, (2) both fine- and coarse-resolution remotely-sensed data can detect the effective number of dominant species (e.g., Simpson diversity), and (3) attention should be given to site-specific plant diversity field data collection to appropriately interpret remote sensing results. Findings of this study indicate the feasibility of estimating Simpson diversity in naturally-assembled grasslands using forthcoming spaceborne imagers such as National Aeronautics and Space Administration's Surface Biology and Geology mission.

Hamed Gholizadeh↗
NASA NTRSDate not supplied

Exploring the Integration of Earth Observations to Support Community Management of a Protected Area in Guatemala

Central America faces increasing challenges of deforestation and habitat fragmentation with complex drivers. Protected areas are one response to these challenges, forming a continuous forest stand subject to national conservation systems and laws. As part of a novel shared-management model, both the community of Santa María Tzejá and the Protected Areas Council of Guatemala (CONAP in Spanish) co-manage Cerro Cantil, a protected area in the Ixcán department of northwestern Guatemala covering approximately 314 ha. The SERVIR program, a joint initiative between NASA and USAID, in partnership with leaders from Santa María Tzejá, began a pilot project to explore how the integration of satellite remote sensing can support forest and biodiversity monitoring and contribute to the community’s reporting requirements. To assess Cerro Cantil’s potential role to protect endemic species between three larger protected areas, we model least cost corridors between Cerro Cantil and Laguna Lachuá, Visi Cabá, and Montes Azules for Alouatta pigra (Black Howler Monkey). Additionally, we evaluate the potential contribution of a forestry-conservation incentives program (PROBOSQUE) to stem fragmentation and support biodiversity by assessing the forest area overlapping both the modeled corridors and plots belonging to families enrolled in PROBOSQUE. Results contribute to community understanding of the value of Cerro Cantil to protect local biodiversity as well as the interaction of a forestry incentive program and protected area designation.

Biodiversity↗
NASA NTRS1996

Calibrating the Ordovician Radiation of marine life: implications for Phanerozoic diversity trends

It has long been suspected that trends in global marine biodiversity calibrated for the Phanerozoic may be affected by sampling problems. However, this possibility has not been evaluated definitively, and raw diversity trends are generally accepted at face value in macroevolutionary investigations. Here, we analyze a global-scale sample of fossil occurrences that allows us to determine directly the effects of sample size on the calibration of what is generally thought to be among the most significant global biodiversity increases in the history of life: the Ordovician Radiation. Utilizing a composite database that includes trilobites, brachiopods, and three classes of molluscs, we conduct rarefaction analyses to demonstrate that the diversification trajectory for the Radiation was considerably different than suggested by raw diversity time-series. Our analyses suggest that a substantial portion of the increase recognized in raw diversity depictions for the last three Ordovician epochs (the Llandeilian, Caradocian, and Ashgillian) is a consequence of increased sample size of the preserved and catalogued fossil record. We also use biometric data for a global sample of Ordovician trilobites, along with methods of measuring morphological diversity that are not biased by sample size, to show that morphological diversification in this major clade had leveled off by the Llanvirnian. The discordance between raw diversity depictions and more robust taxonomic and morphological diversity metrics suggests that sampling effects may strongly influence our perception of biodiversity trends throughout the Phanerozoic.

Non-NASA Center↗
NASA NTRS2019

Improved assessment of mangrove forests in Sundarbans East Wildlife Sanctuary using WorldView 2 and TanDEM-X high resolution imagery

Recent developments of remote sensing techniques which can capture both the structure and function of the ecosystem provide a more representative view of the landscape. These unique Earth observations were used to help improve traditional forestry surveys by providing species-specific land cover classes for mangrove forests in the Sundarbans East Wildlife Sanctuary. By combining optical data from WorldView2 (WV2; 2 m pixel) and a canopy height model derived using radar data from TanDEM-X (TDX; 12 m pixel), we identified nine mangrove and five non-mangrove classes by following an Iterative Self-Organizing Data Analysis Algorithm. Three dominant mangrove species accounted for nearly 50% of the sanctuary. Heritieria fomes disproportionately covered the largest area at 43%, overturning previous field-based estimates of Excoecaria agallocha dominance. E. agallocha and Sonneratia apetala, covered 3% and 1.47% of the sanctuary, respectively. Four mixed species classes were also identified with clear vegetation zonation patterns that trended toward species homogeneity with increasing distance from shore. The overall land cover accuracy (WV2: 89.33%; WV2-TDX: 89.89%), the Kappa Coefficient (WV2:0.88; WV2-TDX: 0.89) and change statistics between WV2 and WV2-TDX landcover classifications indicate that the WV2 imagery can separate mangrove community types without structural data. The combination of the land cover classifications and the canopy height model indicated that H. fomes were not only the most dominant forest but also, on average, the tallest (12.3 m) among the other eight mangrove types. Our large-scale mapping with high resolution optical and radar platforms can capture subtle changes in mangrove vegetation and canopy structural gradients more accurately and be used to monitor biodiversity changes and Aichi Biodiversity Targets and Indicators, which would contribute to biodiversity policy updating.

Md Mizanur Rahman↗
NASA NTRS2022

Colorado Eastern Plains Agriculture: Rangeland Monitoring to Inform Grazing Management in Eastern Colorado

Adaptive management on cattle ranches requires rangeland managers to decide the location and duration of the cattle grazing activity across different pastures. Biodiversity, forage availability, and cattle health are all affected by rangeland management. Virtual fencing is a tool that rangeland managers can use to potentially increase biodiversity and improve ranching operations. NASA DEVELOP and Colorado State University (CSU) collaborated with the Nature Conservancy (TNC), and Red Top Ranch to demonstrate the efficacy of virtual fencing. We sought to identify annual and monthly biomass patterns on the ranch through the creation of monthly max biomass productivity maps. We utilized a dataset from the Agricultural Research Service (ARS) to calculate biomass on the ranch. To validate our remotely-sensed results, we compared model-predicted biomass values to field-collected biomass clipping data and an additional biomass dataset from the Rangeland Analysis Platform (RAP). We used satellite imagery from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 –OLI-2, and Sentinel-2 MultiSpectral Instrument (MSI) for 2021 and 2022. We found that there was heterogeneity in biomass across the ranch, with higher biomass on the western side. The highest peak of biomass was in the summer months, with a smaller peak in mid-September. The ARS biomass dataset had a significant relationship with RAP for 2021. ARS biomass did not have a significant relationship with the biomass field data collected in 2022. The results of our study are aimed to support rotation management, ranch production, biodiversity, and conservation management.

cattle↗