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At least 145 records · Page 8

Hypercapnic ventilatory response in humans before, during, and after 23 days of low level CO2 exposure

Alterations in ventilation and the chemoreceptor response to CO2 during 23 d of 1.2% inspired CO2 were studied in four male subjects. Resting ventilation (VE), tidal volume (VT), respiratory frequency (fR), inspired and end tidal O2 and CO2 and the hypercapnic ventilatory response (HCVR) measured by CO2 rebreathing were measured once before entering the chamber, on days 2, 5, 11, and 22 of CO2 exposure, and one day after. Resting VE slightly increased (5%) on day 2 of exposure and significantly increased (22%) by day 5 followed by a progressive decrease to pre-chamber levels by day 22 and on the first day of recovery. Tidal volume and fR were not statistically different. During the exposure PetCO2 was significantly elevated with day 2 having the largest increase (19.6%). PetCO2 returned to normal within 24 h post exposure. The HCVR was characterized by the slope (SHCVR), intercept at zero ventilation (B), and the ventilation at a PCO2 = 60 mmHg (VE60). The SHCVR decreased (14%) on day 2, but was not significant; the SHCVR on the other exposure days were also not different. The SHCVR on the first recovery day significantly increased (37%). The HCVR B was shifted to the right on day 2 by 5.2 mmHg, then progressively returned to the pre-exposure position. On recovery the B significantly shifted 6.9 mmHg to the right of pre-exposure B. The VE60 decreased by approximately 32% and 16% on day 2 and 5, respectively, then returned within pre-exposure range for the remainder of the exposure and during recovery. During the early phase and one day after the exposure the HCVR was right shifted. One day after exposure chemoreceptor sensitivity to elevated CO2 was increased but, the B was right shifted resulting in a reduced HCVR below PCO2 of 60 mmHg and a greater HCVR above 60 mmHg.

NASA Discipline Cardiopulmonary↗

Development of Urban Air Mobility (UAM) Vehicles for Ease of Operation

To date the air transportation system has been developed with the in-cremental introduction of new technology and with highly experienced air transport pilots and air traffic controllers overseeing flight operations. Thus, we currently have one of the safest commercial aviation systems in the world. General Aviation (GA) in the United States, however, has not always followed the same cautious and monitored approach to implementation; consequently, the GA safety record does not meet the high standards of commercial aviation. Recently, a new system known as Urban Air Mobility (UAM), is attracting considerable interest and investment from industry and government agencies. UAM refers to a system of passenger and small-cargo air transportation vehicles within an urban area with the goal of reducing the number of times we need to use our cars, thus improving urban traffic by moving people and cargo from crowded single pas-senger vehicles on our roads to personal and on-demand air vehicles. These UAM vehicles will be small and based on electric, Vertical-Take-Off-and-Landing (eV-TOL) systems. A significant component of UAM is offloading of flight-man-agement responsibilities from human pilots to newly-developed autonomy. Cur-rently, over 100 UAM vehicles are either in development or production. Most, if not all, have a goal of fully autonomous vehicle operations, but fully autonomous flying vehicles are not expected in the near future. Therefore, we are de-veloping concepts for UAM vehicles that will be easy to fly and/or manage by operators with minimal pilot training. In this paper we will discuss our human-automation teaming approach to develop an easy-to-operate VTOL aircraft, and some of the fly-by-wire technology needed to stabilize the vehicle so that a sim-ple ecological mental model of the flying task can be implemented. We will discuss the requirements for a stability augmentation system that must be developed to support our simple pilot input model, and also present design guidelines and requirements based on a pilot input and management model. Finally, our ap-proach to vehicle development will involve considerable operator testing and evaluation: improving pilot model, inceptors, displays and also work on a plan for how a UAM vehicle can be integrated with terminal area air traffic control airspace with minimal impact on controller workload.

UAM↗

Investigating effects of soil chemicals on density of small mammal bioindicators using spatial capture-recapture models

Monitoring the ecological impacts of environmental pollution and the effectiveness of remediation efforts requires identifying relationships between contaminants and the disruption of biological processes in populations, communities, or ecosystems. Wildlife are useful bioindicators, but traditional comparative experimental approaches rely on a staunch and typically unverifiable assumption that, in the absence of contaminants, reference and contaminated sites would support the same densities of bioindicators, thereby inferring direct causation from indirect data. We demonstrate the utility of spatial capture-recapture (SCR) models for overcoming these issues, testing if community density of common small mammal bioindicators was directly influenced by soil chemical concentrations. By modeling density as an inhomogeneous Poisson point process, we found evidence for an inverse spatial relationship between Peromyscus density and soil mercury concentrations, but not other chemicals, such as polychlorinated biphenyls, at a site formerly occupied by a nuclear reactor. Although the coefficient point estimate supported Peromyscus density being lower where mercury concentrations were higher (β = –0.44), the 95% confidence interval overlapped zero, suggesting no effect was also compatible with our data. Estimated density from the most parsimonious model (2.88 mice/ha; 95% CI = 1.63–5.08), which did not support a density-chemical relationship, was within the range of reported densities for Peromyscus that did not inhabit contaminated sites elsewhere. Environmental pollution remains a global threat to biodiversity and ecosystem and human health, and our study provides an illustrative example of the utility of SCR models for investigating the effects that chemicals may have on wildlife bioindicator populations and communities.

36 MATERIALS SCIENCE↗

A Conceptual Framework to Integrate Biodiversity, Ecosystem Function, and Ecosystem Service Models

Global biodiversity and ecosystem service models typically operate independently. Ecosystem service projections may therefore be overly optimistic because they do not always account for the role of biodiversity in maintaining ecological functions. We review models used in recent global model intercomparison projects and develop a novel model integration framework to more fully account for the role of biodiversity in ecosystem function, a key gap for linking biodiversity changes to ecosystem services. We propose two integration pathways. The first uses empirical data on biodiversity–ecosystem function relationships to bridge biodiversity and ecosystem function models and could currently be implemented globally for systems and taxa with sufficient data. We also propose a trait-based approach involving greater incorporation of biodiversity into ecosystem function models. Pursuing both approaches will provide greater insight into biodiversity and ecosystem services projections. Integrating biodiversity, ecosystem function, and ecosystem service modeling will enhance policy development to meet global sustainability goals.

biodiversity models↗

Western Montana Ecological Forecasting II: Enhancing Habitat Suitability Modeling of Mustelid Species and Contaminant Monitoring in Northern Montana Using NASA Earth Observations

Environmental contaminants in aquatic ecosystems threaten both human and ecosystem health. Western Montana’s rivers possess great economic and ecological value, yet the status of contaminants in these systems can be unclear. Contaminants such as brominated flame-retardants, heavy metals, and pharmaceuticals negatively affect ecosystem health by traveling through the food chain and bioaccumulating in apex predators. Exposure to these contaminants can result in neurological, endocrine, and reproductive impairments in wildlife and humans. American mink (Neovison vison) and North American river otter (Lontra canadensis) have a predominantly aquatic diet and serve as reliable indicator species of environmental health. Working Dogs for Conservation (WD4C) uses detection dogs to locate scat samples of these species which are assessed for contaminants by the Virginia Institute of Marine Science (VIMS). With Software for Assisted Habitat Modeling (SAHM), the team generated current (2013-2020) and projected (2021-2040) habitat suitability models for mink and otter utilizing NASA Earth observations from Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Global Precipitation Measurement Integrated Multi-Satellite Retrievals for GPM (GPM IMERG), Shuttle Radar Topography Mission (SRTM), and Soil Moisture Active Passive (SMAP). The habitat suitability maps’ study region encompassed Flathead National Forest and Blackfeet Indian Reservation. Additionally, the team created site accessibility and precipitation anomaly maps that display the viability of survey locations. The current habitat suitability models performed well (AUC-PR=0.88). The most important predictor variables for suitable habitat were distance to rivers, elevation, and land cover. These end products will further inform WD4C survey site selection and contaminant monitoring.

Chelsea Morton↗

Assessing Disparities of Dengue Virus Transmission Risk across the US-Mexican Border Using a Climate Driven Vector-Epidemiological Model

Dengue fever is a mosquito‐borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Although transmission regularly occurs along the border region in Mexico, dengue virus transmission in bordering Arizona has not occurred. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input and Daymet for temperature and supplemental precipitation input, we modeled dengue transmission along a US‐Mexico transect using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Model runs were performed for 5 cities in Sonora, Mexico and southern Arizona. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. For cities with reported dengue case data, the top model simulations that best reproduced dengue case numbers were retained and their parameter values were extracted for comparison. These parameter values were used to run simulations in areas where dengue virus transmission does not occur or where dengue fever case data was unavailable. Additional model runs were performed to reveal how changes in climate or parameter values could alter transmission risk along the transect. The relative influence of climate variability and model parameters on dengue virus transmission is assessed to help public health workers prepare location specific infection prevention strategies.

Morin, Cory↗

Tracking the environmental impacts of ecological engineering on coastal wetlands with numerical modeling and remote sensing

Coastal wetlands are the most valuable ecosystems on the earth but facing severe degradation and losses owing to climate change and anthropogenic activities. Many ecological engineering projects (EEP) have been conducted to mitigate the degradation of coastal wetlands. However, the geomorphological impacts of EEP on coastal wetlands have not been well documented. In this study, a method employed a process-based hydrodynamic model and remote sensing (RS) was developed to evaluate the impacts of EEP on the geomorphological change of a prototype Ramsar site. Results demonstrated that RS has great potential in improving the quality of bathymetry data for the numerical model with a decrease of RMSE from 0.52 m to 0.3 m. It also showed good capacity in trend detection of geomorphological change spatially. Results showed the Chongming Dongtan wetland experienced erosion with an annual rate of -0.035 m/yr from 2013 to 2016 after the implementation of EEP. The deposition rate changed significantly in the area within 200 m of the EEP. It is found that the EEP modified the composition of vegetation, sediment transportation, as well as substrate stability, affecting the geomorphological change of coastal wetlands. It is suggested that the EEP with moderate anthropogenic disturbance is a direct and effective way to recover the coastal habitats for waterbirds. However, the modification of the coastal wetland ecosystem by EEP will lead to the potential vulnerability to global climate change. Therefore, how to mitigate the advantages and disadvantages of the EEP is needed to be further studied to find a more sustainable way for coastal management.

geomorphological change, coastal wetlands, Ecologi↗

Functional-type modeling approach and data-driven parameterization of methane emissions in wetlands (Final Technical Science Report)

Our goals are to improve understanding and quantitative representation of the multiple processes that affect methane emissions at a high (patch level, vertically detailed) spatial resolution, and translate this understanding to improved modeling capability of coastal wetland fluxes using the E3SM Land Model (ELM v1) wetland CH4 biogeochemistry module. We propose an experimental approach to identify and parameterize uncertainties in ELM. Understanding of methane emissions can be improved along three conceptual axes: (i) horizontal (ecohydrological patch resolution), (ii) vertical (through the depth of the soil column), and (iii) process level (e.g., resolving microbial pathways, vegetation specific transport pathways). Along each of the three axes, we will characterize, quantify, and model, the key ecological, hydrological, and meteorological controls of methane (CH4) flux heterogeneity in four model coastal wetlands.

54 ENVIRONMENTAL SCIENCES↗

Object-oriented model-driven control

A monitoring and control subsystem architecture has been developed that capitalizes on the use of modeldriven monitoring and predictive control, knowledge-based data representation, and artificial reasoning in an operator support mode. We have developed an object-oriented model of a Controlled Ecological Life Support System (CELSS). The model based on the NASA Kennedy Space Center CELSS breadboard data, tracks carbon, hydrogen, and oxygen, carbodioxide, and water. It estimates and tracks resorce-related parameters such as mass, energy, and manpower measurements such as growing area required for balance. We are developing an interface with the breadboard systems that is compatible with artificial reasoning. Initial work is being done on use of expert systems and user interface development. This paper presents an approach to defining universally applicable CELSS monitor and control issues, and implementing appropriate monitor and control capability for a particular instance: the KSC CELSS Breadboard Facility.

Drysdale, A.↗

Ecological Quality Evolution and Its Driving Factors in Yunnan Karst Rocky Desertification Areas

Rocky desertification is a key element affecting regional ecological quality. Rocky desertification in Southwest China directly affects the ecological security of the Yangtze River and Pearl River basins and also restricts regional economic and social development. In order to clarify the evolution laws and key influencing factors of ecological quality in Yunnan karst rocky desertification areas, a quantitative analysis based on the remote sensing-based ecological index (RSEI) model was conducted to explore the overall evolution characteristics and change laws of ecological quality in Yunnan karst rocky desertification areas in the past 30 years. The correlation between RSEI, rock outcrop rate (Fr), and driving factors was determined by redundancy analysis. The results showed the following: (1) RSEI in Yunnan karst rocky desertification areas generally showed a decreasing trend, with a fluctuation in the mid-term, followed by a tendency to recover. It fell into three stages: decline, trough, and recovery, with fitting coefficients of -0.121, -0.057, and 0.157, respectively. In contrast, Fr showed an opposite tendency, illustrating the inverse relationship between RSEI and Fr, and the rate of sequential succession was much faster than that of the reverse succession under human measures of intervention. (2) The mean value of RSEI of Yunnan karst rocky desertification areas was generally lower than that of the total Yunnan Province land areas and Yunnan non-karst rocky desertification areas, but the mean value of Fr was generally more than that of both the above-mentioned areas. In addition, the RSEI and Fr of Yunnan karst rocky desertification areas both showed lower stability values than those of both the above-mentioned areas. This generally suggested a low ecological quality and a high degree of desertification under a low stability in Yunnan karst rocky desertification areas. (3) The correlation of RSEI and Fr with driving factors followed the order of topographic factors, soil factors > water factors > anthropogenic factors. Anthropogenic factors were the driving force changing the state of rocky desertification, geological factors such as topography and soil to a larger extent determined the original macroscopic ecological relationship of rocky desertification, and water factors lay between the above two. The findings of this research will provide theoretical support and a basis for the improvement of ecological quality and comprehensive control of karst rocky desertification in Yunnan Province.

54 ENVIRONMENTAL SCIENCES↗

Foundational Human-Autonomy Teaming Research and Development in Scalable Remotely Operated Advanced Air Mobility Operations: Research Model and Initial Work

To achieve the scalability envisioned for many Advanced Air Mobility (AAM) applications, uncrewed aerial system (UAS) concepts are being pursued with the goal of enabling fewer human operators to manage more increasingly autonomous vehicles. NASA’s Transformational Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) subproject has identified human-autonomy teaming (HAT) as a critical area of research required to support these operations. Under T3-RAM, the HAT Foundational Research Activity has been tasked with providing basic research to identify HAT and human-automation interaction (HAI) principles that can be used to achieve scalable multi-vehicle UAS operations. This paper first outlines a research model to produce ecologically relevant basic research, then contextualizes completed and planned research and development activities within this model. Proposed research threads are presented, along with their practical and theoretical implications.

Human-Autonomy Teaming↗

Assessing mechanisms for microbial taxa and community dynamics using process models

Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer–resource model with a neutral model in stochastic differential equations. Using time-series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer–resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗

Southern Bhutan Ecological Forecasting II: Utilizing NASA Earth Observations to Model Land Cover Change and Elephant Wildlife Corridors in Southern Bhutan

The diverse landscapes of Bhutan host a rich biodiversity of animal and plant species. Asian elephants (Elephas maximus) are a flagship keystone wildlife species whose conservation is essential for the functioning of Bhutan’s forest ecosystems. Despite this, increasing habitat loss and human-elephant conflict continue to be detrimental to the survival of Asian elephants. The lack of information on Bhutan’s elephants and land use and land cover (LULC) trends present major challenges for Bhutan in modeling locations with suitable habitat and biological corridors for elephants. The DEVELOP Southern Bhutan Ecological Forecasting II team at NASA Goddard Space Flight Center partnered with the Bhutan Foundation, Bhutan Tiger Center, and Bhutan Ecological Society to help address this problem. The team mapped LULC in Bhutan for 2010 and 2015 by utilizing NASA Earth observations, including Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) to acquire information on historical LULC patterns and view apparent land cover change. The team used the Linkage Pathways Tool of the Linkage Mapper Toolbox in ArcMap to derive biological corridor maps from habitat suitability model outputs of the previous term and known locations of protected areas in Bhutan. The corridor maps were used to view and assess corridor suitability and connectivity between protected parks. Project results are being provided to partners to help make informed decisions on the placement and conservation of elephant movement corridors.

Thinley Yidzin Wangden↗

Advancing representations of equity and justice in climate mitigation futures

THIS PAPER WAS PRIMARILY COMPLETED PRIOR TO THE AUTHOR JOINING PNNL AND NO DOE FUNDING WAS USED FOR THIS PAPER. In this work, we review how equity and justice issues in global climate mitigation scenarios are addressed within Integrated Assessment Models (IAMs) and propose a new research agenda to strengthen their integration in model development and application. We begin by examining prominent concerns at the science-policy interface. We introduce a typology of equity and justice limitations in climate mitigation scenarios, distinguishing among structural, methodological, and epistemological biases that shape what integrated assessment models can reveal at policy-relevant scales. Reflecting on these concerns, we propose a research agenda that describes new avenues of work and draws together distinct emerging initiatives. This agenda is based on the feasibility and depth of required interventions, from incremental improvements to structural reforms and alternative participatory approaches. Drawing on reflexive insights from integrated assessment practitioners, it addresses the operational challenges of translating justice concepts into metrics, including risks of reductionism, tokenism, and narrow definitions. Underlying this research agenda is a recognition that modeling communities must engage more critically with implicit assumptions in model design and use that have equity and justice implications. Achieving equitable climate futures will require transformative actions that integrate diverse justice concerns, advance sustainable development goals, and confront systemic inequities across both human and ecological dimensions. Although models will never capture all these aspects, they can be significantly enhanced to support more informed discussion and practical application. Our contribution proposes a way forward to achieving this goal.

Pachauri, Shonali↗

An Ensemble Investigation of the Causes for Regional Air-Quality Model Critical Load Exceedances Prediction Variability in European and North American Domains Using Diagnostics From Phase 4 of the Air Quality Model Evaluation International Initiative

We summarize tentative findings from multi air quality model ensembles for the years 2009 and 2010 in Europe (EU), and 2010 and 2016 in North America (NA), under AQMEII-4. The model predictions of sulphur and nitrogen deposition were used to estimate exceedances of critical loads for acidification and eutrophication, to show the extent to which the ensemble members agree in the magnitude and the trend of ecologically meaningful impacts. Model exceedance variability was analyzed using AQMEII-4 diagnostics. Evaluation against concentration and wet deposition observations, coupled with these diagnostics, identified specific process representations as the causes for variability between model predictions and for reduced model performance. All models predicted reductions in ecosystem acidification impacts in North America between the years 2010 and 2016, in accord with SO2 emissions reduction legislation which started in 2010 (SO2 SIP) However, all models in EU and NA domains had net negative biases for wet deposition of sulphur and nitrogen relative to observations. The wet S deposition average mean bias for the NA ensemble was -0.17 eq ha-1 d-1, and for the EU ensemble -1.15 eq ha-1 d-1. The NA daily wet deposition average mean bias for NH4+ was -0.37 eq ha-1d-1; EU -1.19 eq ha-1 d-1. The daily NA wet NO3- deposition average mean bias was -0.24 eq ha-1d-1; EU -0.69 eq ha-1 d-1. The members of the ensemble diverged (factor of 10) in their North American predictions for Ndep and consequently their eutrophication exceedances. The models with the highest eutrophication predictions also predicted the highest levels of gas-phase ammonia dry deposition (standard deviation of ammonia dry deposition flux across ensemble members was larger than the ensemble average). These models also had negative biases of predicted ammonia concentrations; average mean biases of -0.63 (satellite NH3) and -0.85 ppbv (surface NH3) compared to ensemble averages of -0.30 and -0.34 ppbv. Diagnostics showed that these differences resulted from the manner in which bidirectional ammonia fluxes were parameterized within these models. The second largest source of NA eutrophication prediction variability were models with positive biases in particulate ammonium and nitrate concentrations, and higher particle nitrogen deposition levels ( particle ammonium concentration bias +0.35 ug m-3; ensemble bias +0.15 ug m-3). We believe two factors may have led to these latter overestimates: higher levels of fine mode particle nitrate formation compared to other models (due to the use of an inorganic heterogeneous chemistry algorithm which did not take base cation chemistry into account), and updates to particle dry deposition velocities carried out in the absence of concurrent updates to wet scavenging algorithms. The relative importance of dry gas, dry particulate, and wet deposition towards total sulphur and nitrogen deposition totals differed between EU and North American domains, though all models had negative biases in wet deposition as noted above. Parallel and subsequent work suggests that multiphase hydrometeor scavenging may improve model wet deposition performance. An increased research focus is recommended for four model processes: multiphase hydrometeor scavenging, ammonia bidirectional fluxes, base cation chemistry and emissions, and particle dry deposition.

regional air-quality model↗