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At least 271 records · Page 15

Estimating biogeochemical fluxes across sagebrush-steppe landscapes with Thematic Mapper imagery

Thematic Mapper (TM) satellite data were coupled to an ecosystem simulation model to simulate variation in nitrogen mineralization over time and space in a sagebrush steppe. This system of data inputs and calculations provides estimates of ecosystem properties including rates of biogeochemical processes over extensive and complex landscapes, and under changing management and climatic conditions. The landscape surface was divided into three sagebrush ecosystem types plus one other class consisting of nonsagebrush vegetation. This classification presented a complex mosaic of ecosystem types that shifted markedly in composition from one end of the 933-sq km study area to the other. Annual N-mineralization rates ranged from 5 to 25 kg N/ha among the three sagebrush types. The most active type comprised 42 percent of the entire area but contributed 60 percent to the nitrogen mineralization throughout the landscape.

Reiners, W. A.↗

Harvest and nitrogen effects on bioenergy feedstock quality of grass-legume mixtures on Conservation Reserve Program grasslands

Perennial grass mixtures established on Conservation Reserve Program (CRP) lands can be an important source of feedstock for bioenergy production. This study aimed to evaluate management practices for optimizing the quality of bioenergy feedstock and stand persistence of grass-legume mixtures under diverse environments. A 5-year field study (2008–2012) was conducted to assess the effects of two harvest timings (at anthesis vs after complete senescence) and three nitrogen (N) rates (0, 56, 112 kg N ha -1 ) on biomass chemical compositions (i.e., cell wall components, ash, volatiles, total carbon, and N contents) and the feedstock energy potential, examined by the theoretical ethanol yield (TEY) and the total TEY (i.e., the product of biomass yield and TEY, L ha -1 ), of cool-season mixtures in Georgia and Missouri and a warm-season mixture in Kansas. The canonical correlation analysis (CCA) was used to investigate the effect of vegetative species transitions on feedstock quality. Although environmental variations (mainly precipitation) greatly influenced the management effect on chemical compositions, the delayed harvest after senescence generally improved feedstock quality. In particular, the overall cell wall concentrations and TEY of the warm-season mixtures increased by approximately 7%. Additional N supplies improved the total TEY of both mixtures by ~1.6–4.2 L ha -1 per 1.0 kg N ha -1 input but likely lowered the feedstock quality, particularly for the cool-season mixture. The cell wall concentrations of cool-season mixture reduced by approximately 3%–6%. The CCA results indicated that the increased legume compositions (under low N input) likely enhanced lignin but reduced ash concentrations. This field research demonstrated that with proper management, grass-legume mixtures on CRP lands can provide high-quality feedstock for bioenergy productions.

09 BIOMASS FUELS↗

Interactive Biogenic Emissions and Drought Stress Effects on Atmospheric Composition in NASA GISS ModelE

Drought is a hydroclimatic extreme that causes perturbations to the terrestrial biosphere and acts as a stressor on vegetation, affecting emissions patterns. During severe drought, isoprene emissions are reduced. In this paper, we focus on capturing this reduction signal by implementing a new percentile isoprene drought stress (y d ) algorithm in NASA GISS ModelE based on the MEGAN3 (Model of Emissions of Gases and Aerosols from Nature Version 3) approach as a function of a photosynthetic parameter (V c,max ) and water stress (β). Four global transient simulations from 2003–2013 are used to demonstrate the effect without y d (Default_ModelE) and with online y d (DroughtStress_ModelE). DroughtStress_ModelE is evaluated against the observed isoprene measurements at the Missouri Ozarks AmeriFlux (MOFLUX) site during the 2012 severe drought where improvements in the correlation coefficient indicate it is a suitable drought stress parameterization to capture the reduction signal during severe drought. The application of y d globally leads to a decadal average reduction of ∼ 2.7 %, which is equivalent to ∼14.6 Tg yr -1 of isoprene. The changes have larger impacts in regions such as the southeastern US. DroughtStress_ModelE is validated using the satellite ΩHCHO column from the Ozone Monitoring Instrument (OMI) and surface O 3 observations across regions of the US to examine the effect of drought on atmospheric composition. It was found that the inclusion of isoprene drought stress reduced the overestimation of ΩHCHO in Default_ModelE during the 2007 and 2011 southeastern US droughts and led to improvements in simulated O 3 during drought periods. We conclude that isoprene drought stress should be tuned on a model-by-model basis because the variables used in the parameterization responses are relative to the land surface model hydrology scheme (LSM) and the effects of y d application could be larger than seen here due to ModelE not having large biases of isoprene during severe drought.

drought stress effects↗

Monitoring Regional Forest Disturbances across the US with near Real Time MODIS NDVI Products Resident to the ForWarn Forest Threat Early Warning System

Forest threats across the US have become increasingly evident in recent years. Sometimes these have resulted in regionally evident disturbance progressions (e.g., from drought, bark beetle outbreaks, and wildfires) that can occur across multiyear durations and have resulted in extensive forest overstory mortality. In addition to stand replacement disturbances, other forests are subject to ephemeral, sometimes yearly defoliation from various insects and varying types and intensities of ephemeral damage from storms. Sometimes, after prolonged severe disturbance, signs of recovery in terms of Normalized Difference Vegetation Index (NDVI) can occur. The growing prominence and threat of forest disturbances in part have led to the formation and implementation of the 2003 Healthy Forest Restoration Act which mandated that national forest threat early warning system be developed and deployed. In response, the US Forest Service collaborated with NASA, DOE Oakridge National Laboratory, and the USGS Eros Data Center to build and roll-out the near real time ForWarn early warning system for monitoring regionally evident forest disturbances. Given the diversity of disturbance types, severities, and durations, ForWarn employs multiple historical baselines that are used with current NDVI to derive a suite of six forest change products that are refreshed every 8 days. ForWarn employs daily quarter kilometer MODIS NDVI data from the Aqua and Terra satellites, including MOD13 data for deriving historical baseline NDVIs and eMODIS 7 NDVI for compiling current NDVI. In doing so, the Time Series Product Tool and the Phenological Parameters Estimation Tool are used to temporally de-noise, fuse, and aggregate current and historical MODIS NDVIs into 24 day composites refreshed every 8 days with 46 dates of products per year. The 24 day compositing interval enables disturbances to be detected, while minimizing the frequency of residual atmospheric contamination. Forest change products are computed versus the previous 1, previous 3, and all previous years in the MODIS record for a given 24 day interval. Other "weekly" forest change products include one computed using an adaptive length compositing method for quicker detection of disturbances, two others that adjust for seasonal fluctuations in normal vegetation phenology (e.g., early versus late springs). This overall approach enables forest disturbance dynamics from a variety of regionally evident biotic and abiotic forest disturbances to be viewed and assessed through the calendar year. The change products are also being utilized for forest change trend analysis and for developing regional forest overstory mortality products. ForWarn's forest change products are used to alert forest health specialists about new forest disturbances. Such alerts are also typically based on available Landsat, aerial, and ground data as well as communications with forest health specialists and previous experience. ForWarn products have been used to detect and track many types of regional disturbances to multiple forest types, including defoliation from caterpillars and severe storms, as well as mortality from both biotic and abiotic agents (e.g., bark beetles, drought, fire, anthropogenic clearing). ForWarn offers products that could be combined with other geospatial data on forest biomass to assess forest disturbance carbon impacts within the conterminous US.

Spruce, Joseph P.↗

Effect of some detergents, humate, and composition of seedbed on crop of tomato plants in a hydroponic culture

It is established that single detergent doses distinctly stimulate vegetative development of plants in the initial stage when humates are available. When detergents are applied every four weeks in a hydroponic culture, in which the seedbed does not contain active humates, the crop is reduced by 50%. This adverse effect does not occur when the seedbed is a mixture of brown coal and peat.

Guminka, A. Z.↗

Multidecadal shifts in forest plant diversity and community composition across glacial landforms in northern lower Michigan, USA

Understanding how plant community assemblage is affected by spatial and temporal patterns is crucial to understanding forest ecosystem responses to disturbance, including future climate change. In this article, we tracked how diversity and composition are distributed through space and time in a midsuccessional mixed hardwood forest in northern lower Michigan, United States. This region’s geographically and abiotically distinct glacial landforms influence both the spatial and temporal dynamics of its forest communities. Vegetation sampling plots (n = 87) were established at the University of Michigan Biological Station in 1990 and resampled in 2015. Vegetation in the overstory, sapling, and groundcover layers was censused. Abiotic variables, including elevation, pH, and soil nutrients, were measured in a subset of plots (n = 40). There were strong differences in diversity and community composition among glacial landforms, with the moraine having a 31% greater species richness in the groundcover layer compared with those of the other glacial landforms. Surprisingly, plant communities across all three vegetation layers showed little change over the 25-year period, and we found no evidence of differences in successional rates among glacial landforms. Our findings indicate that glacial landforms have a large influence on the production and maintenance of local plant diversity and community composition in this area and suggest that successional dynamics may manifest themselves over much longer time periods in these northern biomes.

Forestry↗

Acoustic space occupancy: Combining ecoacoustics and lidar to model biodiversity variation and detection bias across heterogeneous landscapes

There is global interest in quantifying changing biodiversity in human-modified landscapes. Ecoacoustics may offer a promising pathway for supporting multi-taxa monitoring, but its scalability has been hampered by the sonic complexity of biodiverse ecosystems and the imperfect detectability of animal-generated sounds. The acoustic signature of a habitat, or soundscape, contains information about multiple taxa and may circumvent species identification, but robust statistical technology for characterizing community-level attributes is lacking. Here, we present the Acoustic Space Occupancy Model, a flexible hierarchical framework designed to account for detection artifacts from acoustic surveys in order to model biologically relevant variation in acoustic space use among community assemblages. We illustrate its utility in a biologically and structurally diverse Amazon frontier forest landscape, a valuable test case for modeling biodiversity variation and acoustic attenuation from vegetation density. We use complementary airborne lidar data to capture aspects of 3D forest structure hypothesized to influence community composition and acoustic signal detection. Our novel analytic framework permitted us to model both the assembly and detectability of soundscapes using lidar-derived estimates of forest structure. Our empirical predictions were consistent with physical models of frequency-dependent attenuation, and we estimated that the probability of observing animal activity in the frequency channel most vulnerable to acoustic attenuation varied by over 60%, depending on vegetation density. There were also large differences in the biotic use of acoustic space predicted for intact and degraded forest habitats, with notable differences in the soundscape channels predominantly occupied by insects. This study advances the utility of ecoacoustics by providing a robust modeling framework for addressing detection bias from remote audio surveys while preserving the rich dimensionality of soundscape data, which may be critical for inferring biological patterns pertinent to multiple taxonomic groups in the tropics. Our methodology paves the way for greater integration of remotely sensed observations with high-throughput biodiversity data to help bring routine, multi-taxa monitoring to scale in dynamic and diverse landscapes.

Airborne lidar↗

Continental land cover classification using meteorological satellite data

The use of the National Oceanic and Atmospheric Administration's advanced very high resolution radiometer satellite data for classifying land cover and monitoring of vegetation dynamics over an extremely large area is demonstrated for the continent of Africa. Data from 17 imaging periods of 21 consecutive days each were composited by a technique sensitive to the in situ green-leaf biomass to provide cloud-free imagery for the whole continent. Virtually cloud-free images were obtainable even for equatorial areas. Seasonal variation in the density and extent of green leaf vegetation corresponded to the patterns of rainfall associated with the inter-tropical convergence zone. Regional variations, such as the 1982 drought in east Africa, were also observed. Integration of the weekly satellite data with respect to time produced a remotely sensed assessment of biological activity based upon density and duration of green-leaf biomass. Two of the 21-day composited data sets were used to produce a general land cover classification. The resultant land cover distributions correspond well to those of existing maps.

Tucker, C. J.↗

Utilization of LANDSAT imagery for mapping vegetation on the millionth scale

A series of test sites were examined to determine if the information content of the LANDSAT imagery that may be obtained of these sites is sufficient to permit their mapping according to the vegetation classification system recently published by Unesco. These sites include examples from the humid tropics, arid and semi-arid subtropics and temperature zones: Western Highlands of Papua New Guinea, Mindoro Island in the Philippines, Great Smoky Mountains of the southeastern United States, East Tennessee Valley, interior of Western Australia, northeastern Uganda, and south-central Kansas. The results of the experiment were presented in the form of vegetation maps and annotated images which serve to illustrate the detectability of various formations. It was concluded that, for the test sites examined, the formations of the Unesco vegetation classification can be satisfactorily distinguished on LANDSAT MSS images, especially when used as color composites and judiciously chosen as to season.

Williams, D. L.↗

Significance of vegetation in interpreting thermal radiation from a terrestrial surface

The regions between crop rows are modeled as infinitely long diffuse cavities. Geometrical view factors are calculated, accounting for reflected radiation emanating internal to the cavity and from the background sky. A 'cavity' emissivity dependent on local geometry is defined to allow for correcting apparent temperatures to true temperatures. The total emissivity appropriate for correcting aircraft thermal data is then calculated by averaging all emissivity components to account for soil, crop, and background. It is shown that even for the lowest crop and vegetation emissivities, if the crop height-to-spacing ratio is greater than unity, the composite emissivity is greatly increased, giving rise to a decreased error in remotely sensed temperature data.

Sutherland, R. A.↗

Organic matter in eolian dusts over the Atlantic Ocean

The elemental and mineralogical composition and the microfossil and detritus content of particulate fallout from the lower troposphere over the Atlantic Ocean have been extensively documented in earlier work, and it was possible to ascribe terrigenous source areas to such fallout. A brief review of the organic geochemistry of eolian dusts is also presented here. The lipids of eolian dusts sampled from the air mass over the eastern Atlantic from about 35 deg N to 30 deg S were analyzed here. These lipids consisted mainly of normal alkanes, carboxylic acids and alcohols. The n-alkanes were found to range from n-C23 to n-C35 with high CPI values and maximizing at n-C27 in the North Atlantic, at n-C29 in the equatorial Atlantic and at n-C31 in the South Atlantic. The n-fatty acids had mostly bimodal distributions, ranging from n-C12 to n-C30 (high CPI), with maxima at n-C16 and in the northern samples at n-C24 and in the southern samples at n-C26. The n-alcohols ranged from n-C12 to n-C32, with high CPI values and maxima mainly at n-C28. The compositions of these lipids indicated that their terrigenous sources were comprised mainly of higher plant vegetation and desiccated lacustrine mud flats on the African continent.

Simoneit, B. R. T.↗

Combined use of remote sensing and seismic observations to infer geologically recent crustal deformation, active faulting, and stress fields

Characteristic traits for earthquakes associated with strike-slip motion in Central California and the Salton Sea area, as revealed in ground based studies and LANDSAT imagery, were compared. The mapped lineaments are found to be oriented in several dominant directions. One direction is the same as the trend of the San Andreas fault. The other directions differ from area to area and may reflect the stresses of earlier geologic processes. The pattern of lineament orientations is significantly LANDSAT MSS data, SEASAT synthetic aperture radar data, and magnetic field data from the South Mountain area west of Gettysburg, Pennsylvania were registered to match each other in spatial position and merged. Pattern recognition techniques were applied to the composite data set to determine its utility in recognizing different rock types and structures in vegetated terrain around South Mountain. With the use of a texture algorithm to enhance geologic features, a classification of the entire area was made. A test of the correlation between SAR tone and texture, LANDSAT tone and texture, and magnetic field data revealed no tone or texture measures linking any two of the original data sets.

Alexander, S. S.↗

Detecting biotic and hydrogeochemical processes in large peat basins with Landsat TM imagery

A survey was made of three large peat basins in boreal North America with Landsat TM imagery and field sampling. False-color composites composed of Bands 2, 3, and 4 are particularly effective in discriminating the major vegetation types and the important hydrogeochemical processes in these peatlands. This imagery indicates that the discharge of alkaline groundwater provides one of the most important regional and local controls on peatland development.

Glaser, Paul H.↗

An Assessment of the Surface Longwave Direct Radiative Effect of Airborne Dust in Zhangye China During the Asian Monsoon Year Field Experiment (2008)

Tiny suspensions of solid particles or liquid droplets, called aerosols, hover in earth's atmosphere and can be found over just about anywhere including oceans, deserts, vegetated areas, and other global regions. Aerosols come in a variety of sizes, shapes, and compositions which depend on such factors as their origin and how long they have been in the atmosphere (i.e., their residence time). Some of the more common types of aerosols include mineral dust and sea salt which get lifted from the desert and ocean surfaces, respectively by mechanical forces such as strong winds. Depending on their size, aerosols will either fall out gravitationally, as in the case of larger particles, or will remain resident in the atmosphere where they can undergo further change through interactions with other aerosols and cloud particles. Not only do aerosols affect air quality where they pose a health risk, they can also perturb the distribution of radiation in the earth-atmosphere system which can inevitably lead to changes in our climate. One aerosol that has been in the forefront of many recent studies, particularly those examining its radiative effects, is mineral dust. The large spatial coverage of desert source regions and the fact that dust can radiatively interact with such a large part of the electromagnetic spectrum due to its range in particle size, makes it an important aerosol to study. Dust can directly scatter and absorb solar and infrared radiation which can subsequently alter the amount of radiation that would otherwise be present in the absence of dust at any level of the atmosphere like the surface. This is known as radiative forcing. At the surface dust can block incoming solar energy, however at infrared wavelengths, dust acts to partially compensate the solar losses. Evaluating the solar radiative effect of dust aerosols is relatively straightforward due in part to the relatively large signal-to-noise ratio in the measurements. At infrared wavelengths, on the other hand, the effect is rather difficult to ascertain since the measured dust signal level is on the same order as the instrumental uncertainties. Although the radiative impact of dust is much smaller in the infrared, it can still have a noticeable influence on the distribution of energy in the Earth-atmosphere system. This is mainly attributed to the strong light-absorptive properties commonly found in many earth minerals.

Hansell, Richard A.↗

Building a Bilingual Google Earth Engine Dashboard to Increase Accessibility to Long-term Time Series Remote Sensing Data for Monitoring Saline System Changes in Chile’s Atacama Desert

Saline systems, consisting of salt flats, ponds, and marshes, provide vital water resources to wildlife and communities in northern Chile’s Atacama Desert, one of the driest regions in the world. Mining is extensive in the Atacama, which contains 30% of the world’s lithium reserves and is abundant in potassium and boron. The groundwater that feeds into salt marshes and ponds is extracted in large volumes for mining operations, limiting the availability of water for ecosystems. However, identifying long-term and large-scale environmental impacts from local lithium mining on the saline systems is limited by region inaccessibility and terrain variability. Open access satellite imagery and cloud computing technology has made studying Atacama saline systems feasible and allowed for collaboration across different agencies and countries. The NASA DEVELOP Program partnered with Chile’s la Universidad de La Serena and Servicio Nacional de Geología y Minería (SERNAGEOMIN) to create the Saline Analysis Tool (SalT) in Google Earth Engine (GEE). SalT is used to analyze the extent and distribution of remote saline systems in the Atacama from 1986 to the present day. The tool filters Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) data from GEE’s data catalog and creates a single composite image per year for analysis. Additional output analyses include land cover classification, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) raster images that can be displayed on the map interface or exported. The tool can also generate time-lapse videos and charts displaying NDVI, NDWI, and land cover over time. A key feature of the tool is the use of a bilingual graphical user interface to make analysis accessible and customizable to different users’ needs—SalT provides options to select an analysis area, analysis time period, and outputs to display or export. The tool also incorporates new Earth observations as they are added to GEE’s catalog. The ability to easily visualize and analyze long-term remote sensing imagery will enable SERNAGEOMIN and la Universidad de la Serena to continually monitor changes in these saline systems and inform future land management policy.

NASA DEVELOP↗

Verification Testing and Veg-05 Tomato Crop Production on the International Space Station

Production of fresh, nutritious, and tasty produce for astronauts during spaceflight may provide health-promoting, bioavailable nutrients and enhance the dietary experience as we move into longer-duration missions. Growing and caring for plants may also reduce the psychological stresses associated with spaceflight and enhance connections to Earth. Requirements to consistently grow a diversity of crops under spaceflight environmental conditions remain poorly defined. The VEG-05 experiment is part of a series of experiments with pick-and-eat salad crops to better define best practices for crop production and handling in space. VEG-05 and predecessor experiments VEG-04A and VEG-04B, use the Veggie vegetable production facilities on the International Space Station to grow salad crops under different spectral compositions. In VEG-04A and B, mizuna mustard was cultivated with two different red: blue light treatments, and in VEG-05 we are cultivating ‘Red Robin’ dwarf cherry tomatoes under the same light spectra. Light can impact the growth habit, yield, nutritional composition, microbial levels, and even flavor attributes within crops, and our team will assess these characteristics for this crop during VEG-05. Prior to launch and installation on ISS in late 2022, both a science verification test (SVT), and an experiment verification test (EVT) were conducted at Kennedy Space Center in ISS Environment Simulator Chambers. Science verification testing, and a previous fertilizer test, grew plants in both plant pillows and PONDS (Passive Orbital Nutrient Delivery System) units and tested two different fertilizer treatments in both sets of hardware, with each test under only one of the light conditions. Because of challenges validating the PONDS hardware on ISS, and with good crop production in plant pillows, the EVT moved forward using only plant pillows with the highest fertilizer composition tested during SVT, and two Veggie units were utilized. One Veggie had light settings consisting of equal levels of red: blue light (150 µmol/m2/s for each color) plus green light (30 µmol/m2/s) while the second Veggie had a 90:10 ratio of red: blue light (270 µmol/m2/s red and 30 µmol/m2/s blue) plus green, so each unit provided 330 µmol/m2/s of photosynthetically active radiation to the tomato crops on average. Our original plan, based on prior ground testing, was to grow the crop for 104 days and harvest at 80, 90 and 104 days after initiation. For SVT, under the equal red: blue light treatment, fruit ripening in plant pillows was delayed and fruit were not ripe by day 80, so actual harvest days were days 90, 97, and 104. For EVT we saw fruit ripening earlier, especially in the high red treatment, and so we harvested at days 83, 90, and 99 days after initiation. In SVT we had mostly daily watering, and this led to excess water in plant pillows, which leaked out. This excess water also caused fungus to grow on one leaf and a couple of plant stems. To reduce this excess moisture, we throttled back the watering for EVT, and used the root mat reservoir more frequently. This led to watering only every other day, reducing crew time needed for plant care, however, two wilting events occurred during this EVT, at days 51 and 75. Plants recovered from these wilting events, but these events may have influenced the rate of fruit ripening and flower formation. Regardless, more than 10 fruit were produced from each plant on average, with the high red treatment producing slightly heavier fruit. Microbial testing from fruit during SVT indicated that fruit were safe for consumption with microbial levels below detection limits. VEG-05 flight and ground operations are expected to run between December 2022 and March 2023. This research was co-funded by the Human Research Program and Space Biology (MTL#1075) in the ILSRA 2015 NRA call.

Gioia D. Massa↗

Application of a computerized environmental information system to master and sector planning

A computerized composite mapping system developed as an aid in the land use decision making process is described. Emphasis is placed on consideration of the environment in urban planning. The presence of alluvium, shallow bedrock, surface water, and vegetation growth are among the environmental factors considered. An analysis of the Shady Grove Sector planning is presented as an example of the use of computerized composite mapping for long range planning.

Stewart, J. C.↗

Distinct assembly mechanisms underlie similar biogeographical patterns of rare and abundant bacteria in Tibetan Plateau grassland soils

Rare biosphere represents the majority of Earth's biodiversity and performs vital ecological functions, yet little is known about its biogeographical patterns and community assembly processes in terrestrial ecosystems. Herein, we investigated the community composition and phylogeny of rare (relative abundance <0.1%) and abundant (>1%) bacteria in dryland grassland soils on the Tibetan Plateau. Results revealed similar biogeographical patterns of rare and abundant bacteria at both compositional and phylogenetic levels, but rare subcommunity was more heavily influenced by stochasticity (72%) than the abundant (57%). The compositional variation of rare bacteria was less explained by environmental factors (41%) than that of the abundant (80%), while the phylogeny of rare bacteria (36%) was more explained than that of the abundant (29%). The phylogeny of rare bacteria was equally explained by local factors (soil and vegetation) and geospatial distance (11.5% and 11.9% respectively), while that of the abundant was more explained by geospatial distance (22.1%) than local factors (11.3%). Furthermore, a substantially tighter connection between the community phylogeny and composition was observed in rare (R(2) = 0.65) than in abundant bacteria (R(2) = 0.08). Our study provides novel insights into the assembly processes and biographical patterns of rare and abundant bacteria in dryland soils.

Ji, Mukan↗