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At least 703 records · Page 39

Incineration as a Method for Resource Recovery from Inedible Biomass in a Controlled Ecological Life Support System

Resource recovery from waste streams in a space habitat is essential to minimize the resupply burden and achieve self-sufficiency. In a Controlled Ecological Life Support System (CELSS) human wastes and inedible biomass will represent significant sources of secondary raw materials necessary for support of crop plant production (carbon, water, and inorganic plant nutrients). Incineration, pyrolysis, and water extraction have been investigated as candidate processes for recovery of these important resources from inedible biomass in a CELSS. During incineration CO2 is produced by oxidation of the organic components and this product can be directly utilized by plants. Water is concomitantly produced, requiring only a phase change for recovery. Recovery of inorganics is more difficult, requiring solubilization of the incinerator ash. The process of incineration followed by water solubilization of ash resulted in loss of 35% of the inorganics originally present in the biomass. Losses were attributed to volatilization (8%) and non-water-soluble ash (27%). All of the ash remaining following incineration could be solubilized with acid, with losses resulting from volatilization only. The recovery for individual elements varied. Elemental retention in the ash ranged from 100% of that present in the biomass for Ca, P, Mg, Na, and Si to 10% for Zn. The greatest water solubility was observed for potassium with recovery of approximately 77% of that present in the straw. Potassium represented 80% of the inorganic constituents in the wheat straw, and because of slightly greater solubility made up 86% of the water-soluble ash. Following incineration of inedible biomass from wheat, 65% of the inorganics originally present in the straw were recovered by water solubilization and 92% recovered by acid solubilization. Recovery of resources is more complex for pyrolysis and water extraction. Recovery of carbon, a resource of greater mass than the inorganic component of biomass, is more difficult following pyrolysis and water extraction of biomass. In both cases, additional processors would be required to provide products equivalent to those resulting from incineration alone. The carbon, water, and organic resources of inedible biomass are effectively separated and output in usable forms through incineration.

Bubenheim, David L.↗

Predicting measures of soil health using the microbiome and supervised machine learning

Soil health encompasses a range of biological, chemical, and physical soil properties that sustain the commercial and ecological value of agroecosystems. Monitoring soil health requires a comprehensive set of diagnostics that can be cost-prohibitive for routine analyses. The soil microbiome provides a rich source of information about soil properties, which can be assayed in a high-throughput, cost-effective way. We evaluated the accuracy of random forest (RF) and support vector machine (SVM) regression and classification models in predicting 12 measures of soil health, tillage status, and soil texture from 16S rRNA gene amplicon data with an operationally relevant sample set. We validated the efficacy of the best performing models against independent datasets and also tested best practices for processing microbiome data for use in machine learning. Soil health metrics could be predicted from microbiome data with the best models achieving a Kappa value of ~0.65, for categorical assessments, and a R2 value of ~0.8, for numerical scores. Biological health ratings were better predicted than chemical or physical ratings. Validation with independent datasets revealed that models had general predictive value for soil properties, including yield. The ecological profiles of several taxa important for model accuracy matched the observed relationships with soil health, including Pyrinomonadaceae, Nitrososphaeraceae, and Candidatus Udeaobacter. Models trained at the highest taxonomic resolution proved most accurate, with losses in accuracy resulting from rarefying, sparsity filtering, and aggregating at higher taxonomic ranks. Furthermore, our study provides the groundwork for developing scalable technology to use microbiome-based diagnostics for the assessment of soil health.

16S rRNA gene↗

Facet-dependent electron transfer induces distinct arsenic reallocations on hematite

The interfacial electron transfer (ET) between electron shuttling compounds and iron (Fe) oxyhydroxides plays a crucial role in the reductive dissolution of Fe minerals and the fate of surface-bound arsenic (As). However, the impact of exposed facets of highly crystalline hematite on reductive dissolution and As immobilization is poorly understood. In this study, we systematically investigated the interfacial processes of the electron shuttling compound cysteine (Cys) on various facets of hematite and the reallocations of surface-bound As(III) or As(V) on the respective surfaces. Our results demonstrate that the ET process between Cys and hematite generates Fe(II) and leads to reductive dissolution, with more Fe(II) generated on {001} facets of exposed hematite nanoplates (HNPs). Reductive dissolution of hematite leads to significantly enhanced As(V) reallocations on hematite. Nevertheless, upon the addition of Cys, a raipd release of As(III) can be halted by its prompt re-adsorption, leaving the extent of As(III) immobilization on hematite unchanged throughout the course of reductive dissolution. This is due to that Fe(II) can form new precipitates with As(V), a process that is facet-dependent and influenced by water chemistry. Electrochemical analysis reveals that HNPs exhibit higher conductivity and ET ability, which is beneficial for reductive dissolution and As reallocations on hematite. In conclusion, these findings highlight the facet-dependent reallocations of As(III) and As(V) facilitated by electron shuttling compounds and have implications for the biogeochemical processes of As in soil and subsurface environments.

54 ENVIRONMENTAL SCIENCES↗

Produced Water-Economic, Socio, Environmental Simulation Model (PW-ESEim) Model: Proof-of-Concept for Southeastern New Mexico

A proof-of-concept tool, the Produced Water-Economic, Socio, Environmental Simulation model (PW-ESESim), was developed to support ease of analysis. The tool was designed to facilitate head-to-head comparison of alternative produced water source, treatment, and reuse water management strategies. A graphical user interface (GUI) guides the user through the selection and design of alternative produced water treatment and reuse strategies and the associated health and safety risk and economic benefits. At the highest conceptual level, alternative water strategies include the selection of a source water (locally or regionally available produced water), treatment strategy (pre-treatment, physical, chemical, biological, desalination, and post-treatment processes) and product water purpose (e.g., irrigation, industrial processing, environmental). After selection of these details, the PW-ESESim output a number of key economic, societal, environmental, public/ecological health and safety metrics to support user decision-making; specific examples include, cost of treatment, improvements in freshwater availability, human and ecologic health impacts and growth in local jobs and the economy. Through the simulation of different produced water treatment and management strategies, tradeoffs are identified and used to inform fit-for-purpose produced water treatment and reuse management decisions. While the tool was initially designed using Southeastern New Mexico (Permian Basin) as a case study, the general design of the PW-ESESim model can be extended to support other oil and gas regions of the U.S.

54 ENVIRONMENTAL SCIENCES↗

High Resolution Imaging Spectrometer (HIRIS) - A major advance in imaging spectrometry

HIRIS, a facility instrument on the Earth Observing System Platform, will enable scientists to both identify and interpret changes, in the global environment, at a level of detail unavailable with previous instrumentation. This instrument will make localized measurements of biological, ecological, climatological, hydrological, and geological properties, and, with its finer wavelength sampling and full spectral coverage over the wavelength region of interest, will allow these properties to be identified and studied quantitatively from space. The data obtained will be downlinked from space, processed, catalogued, stored in active archives for easy access, and distributed to users.

Rockey, Donald E.↗

Design and test of an object-oriented GIS to map plant species in the Southern Rockies

Elevational and latitudinal shifts occur in the flora of the Rocky Mountains due to long term climate change. In order to specify which species are successfully migrating with these changes, and which are not, an object-oriented, image-based geographic information system (GIS) is being created to animate evolving ecological regimes of temperature and precipitation. Research at the Earth Data Analysis Center (EDAC) is developing a landscape model that includes the spatial, spectral and temporal domains. It is designed to visualize migratory changes in the Rocky Mountain flora, and to specify future community compositions. The object-oriented database will eventually tag each of the nearly 6000 species with a unique hue, intensity, and saturation value, so their movements can be individually traced. An associated GIS includes environmental parameters that control the distribution of each species in the landscape, and satellite imagery is used to help visualize the terrain. Polygons for the GIS are delineated as landform facets that are static in ecological time. The model manages these facets as a triangular irregular net (TIN), and their analysis assesses the gradual progression of species as they migrate through the TIN. Using an appropriate climate change model, the goal will be to stop the modeling process to assess both the rate and direction of species' change and to specify the changing community composition of each landscape facet.

Morain, Stanley A.↗

Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

Uncertainties in input land cover estimates contribute to a significant bias in modeled above ground biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

High Resolution↗

Negative extreme events in gross primary productivity and their drivers in China during the past three decades

Climate extremes have remarkable impacts on ecosystems and are expected to increase with future global warming. However, only few studies have focused on the ecological extreme events and their drivers in China. In this study, we carried out an analysis of negative extreme events in gross primary productivity (GPP) in China and the sub-regions during 1982–2015, using monthly GPP simulated by 12 process-based models (TRENDYv6) and an observation-based model (Yao-GPP). Extremes were defined as the negative 5th percentile of GPP anomalies, which were further merged into individual extreme events using a three-dimensional contiguous algorithm. Spatio-temporal patterns of negative GPP anomalies were analyzed by taking the 1000 largest extreme events into consideration. Results showed that the effects of extreme events decreased annual GPP by 2.8% (i.e. 208 TgC/year) in TRENDY models and 2.3% (i.e. 151 TgC/year) in Yao-GPP. Hotspots of extreme GPP deficits were mainly observed in North China (−53 gC/sq.m year) in TRENDY models and Northeast China (−42 gC/sq.m year) in Yao-GPP. For China as a whole, attribution analyses suggested that extreme low precipitation was associated with 40%–50% of extreme negative GPP events. Most events in northern and western China could be explained by meteorological droughts (i.e. low precipitation) while GPP extreme events in southern China were more associated with temperature extremes, in particular with cold spells. GPP was revealed to be much more sensitive to heat/drought than to cold/wet extreme events. Combined with projected changes in climate extremes in China, GPP negative anomalies caused by drought events in northern China and by temperature extremes in southern China might be more prominent in the future.

Climate change↗

Integrated parameter and process learning for hydrologic and biogeochemical modules in Earth System Models

Focus area: Primary focal area #2; secondary focal area #3: Learning about parameters and processes of land surface hydrologic and biogeochemical models in Earth System models by integrating machine learning, physics, and big data. Science challenges: How do we maximally leverage big-data observations to improve hydrobiogeochemical process description and parameterization so that such modules more realistically capture hydrologic and vegetation responses and feedbacks under the future climate? For example, how can we leverage physics, limited observations of vegetation and streamflow to better estimate evapotranspiration, and, relatedly, net primary productivity, especially for drought areas? Vegetation plays a critical role in regional and global water cycles; however, existing vegetation models have failed to predict vegetation response to droughts (McDowell & Xu, 2017) , arctic greening (Keenan & Riley, 2018) , and critical transitions between forest and savanna (Hirota et al., 2011) . These studies suggest that when we build process-based models (PBM) parameterized from regional and global plant traits, we tend to poorly describe plant adaptation and local-scale competition processes. The models and their associated parameters assigned for different regions in the world are not capturing essential heterogeneity in vegetation responses at finer spatial scales. Many parameters of the land surface models control hydrology and vegetation dynamics at the same time. The heterogeneity in vegetation response is a function of (i) plant type, (ii) plant size, (iii) competition and succession, (iv) environmental controls, and (v) local variations due to the unique ecological community that are very difficult to describe (e.g., the size of gaps resulting from fire that facilitated the coexistence of pioneering species). In the demographic models, only factors (i) and (iv) were captured, and plant types were generally described only by leaf phenology and climate zones. With current demographic models, we generally consider more traits to define plant types (i) and calibrate these traits to consider factors (ii), (iii) and (iv); however, it is substantially challenging to scale to regional and global simulations due to trait variations across space (Ali et al., 2016). Moreover, it has been noted that hillslope processes, including ridge-to-valley flow and sunny vs. shady slopes are primary organizers of water, energy, and vegetation (Clark et al., 2015; Fan et al., 2019) . Although gradual improvements in the hydrologic model component in earth system models may reduce this error (at a remarkably slow pace), the long-term, gradual impact of hydrology on plant traits are not well captured. Recent work showed that the hydrologic controls exerted by groundwater and lateral flow are primary regulators of rooting depth (Fan et al., 2017) . Such hydrologic controls have seldom been reflected in vegetation model parameterizations.

54 ENVIRONMENTAL SCIENCES↗

Effects of dissolved cations, dissolved organic carbon, and exposure concentrations on per- and polyfluoroalkyl substances bioaccumulation in freshwater algae

Per- and polyfluoroalkyl substances (PFAS) have attracted global attention because of their persistence, toxicity, bioaccumulation potential, and associated adverse effects. As important primary producers, freshwater algae constitute the base of the food web in freshwater aquatic ecosystems. However, the effects of key environmental factors on PFAS uptake and bioaccumulation in freshwater algae have not been thoroughly studied. In this study, three bioaccumulation experiments were conducted to evaluate the influence of dissolved cations, dissolved organic carbon, and exposure concentrations on PFAS bioaccumulation in algae. Among the 14 studied PFAS, seven long-chain PFAS tended to bioaccumulate in algae. Elevated divalent cations (Ca 2+ and Mg 2+ ) and dissolved organic carbon did not significantly change the algal bioconcentration factors (BCFs) of PFAS, suggesting complexity of the interactions among PFAS, environmental factors, and biotic activities. Additionally, increasing exposure concentrations (0.5, 1, 5, and 10 μg/L of each PFAS) increased PFAS concentrations in algae but decreased the BCF values. This indicated that attention should be paid to the application of BCFs in future studies, including ecological risk assessment. Moreover, fluorotelomer sulfonic acids (FTSs) were incompletely recovered, suggesting that biotransformation occurred. Further studies should be conducted to evaluate whether algae play a role in FTSs biotransformation and to determine the mechanisms. In conclusion, studying the impacts of key environmental factors on PFAS bioaccumulation in algae is crucial for understanding the bioaccumulation processes that occur at the lowest trophic level and that eventually affect the dynamics of entire aquatic ecosystems.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Landscape fragmentation overturns classical metapopulation thinking

Habitat loss and isolation caused by landscape fragmentation represent a growing threat to global biodiversity. Existing theory suggests that the process will lead to a decline in metapopulation viability. However, since most metapopulation models are restricted to simple networks of discrete habitat patches, the effects of real landscape fragmentation, particularly in stochastic environments, are not well understood. To close this major gap in ecological theory, we developed a spatially explicit, individual-based model applicable to realistic landscape structures, bridging metapopulation ecology and landscape ecology. This model reproduced classical metapopulation dynamics under conventional model assumptions, but on fragmented landscapes, it uncovered general dynamics that are in stark contradiction to the prevailing views in the ecological and conservation literature. Notably, fragmentation can give rise to a series of dualities: a) positive and negative responses to environmental noise, b) relative slowdown and acceleration in density decline, and c) synchronization and desynchronization of local population dynamics. Furthermore, counter to common intuition, species that interact locally (“residents”) were often more resilient to fragmentation than long-ranging “migrants.” This set of findings signals a need to fundamentally reconsider our approach to ecosystem management in a noisy and fragmented world.

54 ENVIRONMENTAL SCIENCES↗

The Breadboard Project - A functioning CELSS plant growth system

The primary objective of the Breadboard Project for the next 3-4 years is to develop, integrate and operate a Controlled Ecological Life Support System (CELSS) at a one-person scale. The focus of this project over the past two years has been the development of the plant growth facility, the first module of the CELSS. The other major modules, food preparation, biomass processing, and resource recovery, have been researched at the laboratory scale during the past two years and facilities are currently under construction to scale-up these modules to an operational state. This paper will outline the design requirements for the Biomass Production Chamber (BPC), the plant growth facility for the project, and the control and monitoring subsystems which operate the chamber and will present results from both engineering and biological tests of the facility. Three production evaluations of wheat, conducted in the BPC during the past year, will be described and the data generated from these tests discussed.

Knott, W. M.↗

Male mating season range expansion results from an increase in scale of daily movements for a polygynous–promiscuous bird

Abstract Males of species with promiscuous mating systems are commonly observed to use larger ranges during the mating season relative to non‐mating seasons, which is often attributed to a change in movements related to reproductive activities. However, few studies link seasonal range sizes to variation in daily space use patterns to provide insight into the behavioral mechanisms underlying mating season range expansion. We studied 20 GPS‐tagged male wild turkeys ( Meleagris gallopavo ), a large upland gamebird, during the mating and summer non‐mating seasons to test the hypothesis that larger mating season ranges resulted from male wild turkeys expanding the scale of daily movement activities to locate and court females. We delineated mating and non‐mating seasons based on intensity of gobbling, a vocalization tied to courtship behavior, recorded by autonomous recording units distributed across the study area. Mating season ranges were significantly larger than non‐mating season ranges. Daily ranges were larger in the mating season, as were distances between roost sites used on consecutive nights. Variance in daily range size was greater in the mating season, but low temporal autocorrelation suggested considerable daily variability in both seasons. We found no evidence that male wild turkeys changed how they distributed daily movements within seasonal ranges, or differences in habitat use, suggesting larger mating season ranges result from male wild turkeys increasing the scale of their daily movements, rather than a systematic shift to a nomadic movement strategy. Likely, the distribution of females is more dynamic and ephemeral compared to other resources, prompting males to traverse larger daily ranges during the mating season to locate and court females. Our work illustrates the utility of using daily movement to understand the behavioral process underlying larger space use patterns.

59 BASIC BIOLOGICAL SCIENCES↗

Hyperspectral Remote Sensing and Ecological Modeling Research and Education at Mid America Remote Sensing Center (MARC): Field and Laboratory Enhancement

The purpose of this project was to establish a new hyperspectral remote sensing laboratory at the Mid-America Remote sensing Center (MARC), dedicated to in situ and laboratory measurements of environmental samples and to the manipulation, analysis, and storage of remotely sensed data for environmental monitoring and research in ecological modeling using hyperspectral remote sensing at MARC, one of three research facilities of the Center of Reservoir Research at Murray State University (MSU), a Kentucky Commonwealth Center of Excellence. The equipment purchased, a FieldSpec FR portable spectroradiometer and peripherals, and ENVI hyperspectral data processing software, allowed MARC to provide hands-on experience, education, and training for the students of the Department of Geosciences in quantitative remote sensing using hyperspectral data, Geographic Information System (GIS), digital image processing (DIP), computer, geological and geophysical mapping; to provide field support to the researchers and students collecting in situ and laboratory measurements of environmental data; to create a spectral library of the cover types and to establish a World Wide Web server to provide the spectral library to other academic, state and Federal institutions. Much of the research will soon be published in scientific journals. A World Wide Web page has been created at the web site of MARC. Results of this project are grouped in two categories, education and research accomplishments. The Principal Investigator (PI) modified remote sensing and DIP courses to introduce students to ii situ field spectra and laboratory remote sensing studies for environmental monitoring in the region by using the new equipment in the courses. The PI collected in situ measurements using the spectroradiometer for the ER-2 mission to Puerto Rico project for the Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS). Currently MARC is mapping water quality in Kentucky Lake and vegetation in the Land-Between-the Lakes (LBL) using Landsat-TM data. A Landsat-TM scene of the same day was obtained to relate ground measurements to the satellite data. A spectral library has been created for overstory species in LBL. Some of the methods, such as NPDF and IDFD techniques for spectral unmixing and reduction of effects of shadows in classifications- comparison of hyperspectral classification techniques, and spectral nonlinear and linear unmixing techniques, are being tested using the laboratory.

Cetin, Haluk↗

Models of Small-Scale Patchiness

Patchiness is perhaps the most salient characteristic of plankton populations in the ocean. The scale of this heterogeneity spans many orders of magnitude in its spatial extent, ranging from planetary down to microscale. It has been argued that patchiness plays a fundamental role in the functioning of marine ecosystems, insofar as the mean conditions may not reflect the environment to which organisms are adapted. Understanding the nature of this patchiness is thus one of the major challenges of oceanographic ecology. The patchiness problem is fundamentally one of physical-biological-chemical interactions. This interconnection arises from three basic sources: (1) ocean currents continually redistribute dissolved and suspended constituents by advection; (2) space-time fluctuations in the flows themselves impact biological and chemical processes, and (3) organisms are capable of directed motion through the water. This tripartite linkage poses a difficult challenge to understanding oceanic ecosystems: differentiation between the three sources of variability requires accurate assessment of property distributions in space and time, in addition to detailed knowledge of organismal repertoires and the processes by which ambient conditions control the rates of biological and chemical reactions. Various methods of observing the ocean tend to lie parallel to the axes of the space/time domain in which these physical-biological-chemical interactions take place. Given that a purely observational approach to the patchiness problem is not tractable with finite resources, the coupling of models with observations offers an alternative which provides a context for synthesis of sparse data with articulations of fundamental principles assumed to govern functionality of the system. In a sense, models can be used to fill the gaps in the space/time domain, yielding a framework for exploring the controls on spatially and temporally intermittent processes. The following discussion highlights only a few of the multitude of models which have yielded insight into the dynamics of plankton patchiness. In addition, this particular collection of examples is intended to furnish some exposure to the diversity of modeling approaches which can be brought to bear on the problem. These approaches range from abstract theoretical models intended to elucidate specific processes, to complex numerical formulations which can be used to actually simulate observed distributions in detail.

McGillicuddy, D. J.↗

Antarctic Astrobiology

Stars may be cold and dry today but there is compelling evidence that earlier in its history Mars did have liquid water. This evidence comes from the images taken from orbital spacecraft. The dry valleys of Antarctica comprise the largest ice-free region on that continent. The valleys are a cold desert environment with mean annual temperatures of -20 C. The lakes in the dry valleys of Antarctica provide an example of the physical processes that can maintain large bodies of liquid water under mean annual temperatures well below freezing. Biologically these lakes are also important analogs because of the plankton and benthic communities of microorganisms that thrive there. Life could have existed in lakes on Mars an ecological similar conditions.

McKay, Christopher P.↗

Waste management in space: a NASA symposium. Special issue

This special issue contains papers from the NASA Symposium on Waste Processing for Advanced Life Support, which was held at NASA Ames Research Center on September 11-13, 1990. Specialists in waste management from academia, government, and industry convened to exchange ideas and advise NASA in developing effective methods for waste management in a Controlled Ecological Life Support System (CELSS). Innovative and well-established methods were presented to assist in developing and managing wastes in closed systems for future long-duration space missions, especially missions to Mars.

NASA Center ARC↗

A bioreactor system for the nitrogen loop in a Controlled Ecological Life Support System

As space missions become longer in duration, the need to recycle waste into useful compounds rises dramatically. This problem can be addressed by the development of Controlled Ecological Life Support Systems (CELSS) (i.e., Engineered Closed/Controlled Eco-Systems (ECCES)), consisting of human and plant modules. One of the waste streams leaving the human module is urine. In addition to the reclamation of water from urine, recovery of the nitrogen is important because it is an essential nutrient for the plant module. A 3-step biological process for the recycling of nitrogenous waste (urea) is proposed. A packed-bed bioreactor system for this purpose was modeled, and the issues of reaction step segregation, reactor type and volume, support particle size, and pressure drop were addressed. Based on minimization of volume, a bioreactor system consisting of a plug flow immobilized urease reactor, a completely mixed flow immobilized cell reactor to convert ammonia to nitrite, and a plug flow immobilized cell reactor to produce nitrate from nitrite is recommended. It is apparent that this 3-step bioprocess meets the requirements for space applications.

NASA Discipline Number 61-10↗