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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Adaptive Management Using Remote Sensing and Ecosystem Modeling in Response to Climate Variability and Invasive Aquatic Plants for the California Sacramento-San Joaquin Delta Water Resource

The California Sacramento-San Joaquin River Delta is the hub for California's water supply and supports important ecosystem services, agriculture, and communities in Northern to Southern California. Expansion of invasive aquatic plants in the Delta coupled with impacts of changing climate and long-term drought is detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California to develop science-based, adaptive-management strategies for invasive aquatic plant in the Sacramento-San Joaquin Delta. Specific mapping tools developed utilizing satellite and airborne platforms provide regular assessments of population dynamics on a landscape scale and support both strategic planning and operational decision making for resource managers. San Joaquin and Sacramento River watersheds water quality input to the Delta is modeled using the Soil-Water Assessment Tool (SWAT) and a modified SWAT tool has been customized to account for unique landscape and management of agricultural water supply and drainage within the Delta. Environmental response models for growth of invasive aquatic weeds are being parameterized and coupled with spatial distribution/biomass density mapping and water quality to study ecosystem response to climate and aquatic plant management practices. On the water validation and operational utilization of these tools by management agencies and how they are improving decision making, management effectiveness and efficiency will be discussed. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and water resource managers make science-informed decisions regarding management and outcomes.

Adaptive↗
NASA NTRS2009

Terrestrial Carbon Sinks in the Brazilian Amazon and Cerrado Region Predicted from MODIS Satellite Data and Ecosystem Modeling

A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2004. Net ecosystem production (NEP) flux for atmospheric CO2 in the region for these years was estimated. Consistently high carbon sink fluxes in terrestrial ecosystems on a yearly basis were found in the western portions of the states of Acre and Rondonia and the northern portions of the state of Par a. These areas were not significantly impacted by the 2002-2003 El Nino event in terms of net annual carbon gains. Areas of the region that show periodically high carbon source fluxes from terrestrial ecosystems to the atmosphere on yearly basis were found throughout the state of Maranhao and the southern portions of the state of Amazonas. As demonstrated though tower site comparisons, NEP modeled with monthly MODIS Enhanced Vegetation Index (EVI) inputs closely resembles the measured seasonal carbon fluxes at the LBA Tapajos tower site. Modeling results suggest that the capacity for use of MODIS Enhanced Vegetation Index (EVI) data to predict seasonal uptake rates of CO2 in Amazon forests and Cerrado woodlands is strong.

Potter, C.↗
NASA NTRS2000

Ecosystem Modeling of Biological Processes to Global Budgets

From an ecological perspective, the search for life on distant planets begins from several key assumptions. The first of these is that, viewed from a remote location in space, the signature of life on a distant planet will be the result of net gas exchange of organisms with their environment. On the basis of extensive biogeochemical measurements and biogenic trace gas fluxes in modem Earth environments, it is probable that certain groups of organisms both produce and consume the same trace gas(es) within a single bioprofile of Solid (porous) substrate or surface water. The net gas exchange rate with the atmosphere measured at the living surface is frequently the result of competing metabolic reactions, which may carried out by different functional groups of organisms located at dissimilar 'climatic' or chemical microsites within the same bioprofile. Biogenic gases produced at one (deep) level of a bioprofile may be consumed by another functional group of organisms located closer to the level of surface exchange with the atmosphere. A second key assumption is that the net biogenic fluxes of atmospheric gases on Earth can be used to infer relative abundance and functional composition of the major organisms on a distant planet. Examples of this principle include the presence of methanogenic microorganisms abundant today in freshwater ecosystems worldwide, which are major source of atmospheric methane and its seasonal variability in Earth's atmosphere. A third assumption is that scaling up biogenic gas fluxes from a single biological community to the planetary level requires flux measurements at the whole ecosystem level. This implies that measurements of biogenic gas exchange with the global atmosphere cannot be easily inferred from measurements of gas production rates of single organisms, which may have been isolated in some manner from the setting of their native ecosystem. Hence, the unit of biological organization used in modern Earth Science for scaling up to biosphere effects on atmospheric composition is the ecosystem level. These assumptions are the foundation for developing modern emission budgets for biogenic gases such as carbon dioxide, methane, carbon monoxide, isoprene, nitrous and nitric oxide, and ammonia. Such emission budgets commonly include information on seasonal flux patterns, typical diurnal profiles, and spatial resolution of at least one degree latitude/longitude for the globe. On the basis of these budgets, it is possible to compute 'base emission rates' for the major biogenic trace gases from both terrestrial and ocean sources, which may be useful benchmarks for defining the gas production rates of organisms, especially those from early Earth history, which are required to generate a detectable signal on a global atmosphere. This type of analysis is also the starting point for evaluation of the 'biological processes to global gas budget' extrapolation procedure described above for early Earth ecosystems.

Christopher, Potter S.↗
NASA NTRS1995

Evaluating the Type and State of Alaska Taiga Forests with Imaging Radar for Use in Ecosystem Models

Changes in the seasonal CO2 flux of the boreal forests may result from increased atmospheric CO2 concentrations and associated global warming patterns. To monitor this potential change, a combination of information derived from remote sensing data, including forest type and growing season length, and ecophysiological models which predict the CO2 flux and its seasonal amplitude based on meteorological data, are required. In this paper we address the use of synthetic aperture radar (SAR) to map fores type and monitor canopy and soil freeze/thaw, which define the growing season for conifers, and leaf on/off, which defines the growing season for deciduous species. Aircraft SAR (AIRSAR) data collected in March 1988 during a freeze/thaw event are used to generate species maps and to determine the sensitivity of SAR to canopy freeze/thaw transitions. These data are also used to validate a microwave scattering model which is then used to determine the sensitivity of SAR to leaf on/off transitions and soil freeze/thaw. Finally, a CO2 flux algorithm is presented which utilizes SAR data and an ecophysiological model to estimate CO2 flux. CO2 flux maps are generated, from which areal estimates of CO2 flux are derived.

Alaska↗
NASA NTRS2013

Three Decades of Global Methane Sources and Sinks

Methane is an important greenhouse gas, responsible for about 20 of the warming induced by long-lived greenhouse gases since pre-industrial times. By reacting with hydroxyl radicals, methane reduces the oxidizing capacity of the atmosphere and generates ozone in the troposphere. Although most sources and sinks of methane have been identified, their relative contributions to atmospheric methane levels are highly uncertain. As such, the factors responsible for the observed stabilization of atmospheric methane levels in the early 2000s, and the renewed rise after 2006, remain unclear. Here, we construct decadal budgets for methane sources and sinks between 1980 and 2010, using a combination of atmospheric measurements and results from chemical transport models, ecosystem models, climate chemistry models and inventories of anthropogenic emissions. The resultant budgets suggest that data-driven approaches and ecosystem models overestimate total natural emissions. We build three contrasting emission scenarios which differ in fossil fuel and microbial emissions to explain the decadal variability in atmospheric methane levels detected, here and in previous studies, since 1985. Although uncertainties in emission trends do not allow definitive conclusions to be drawn, we show that the observed stabilization of methane levels between 1999 and 2006 can potentially be explained by decreasing-to-stable fossil fuel emissions, combined with stable-to-increasing microbial emissions. We show that a rise in natural wetland emissions and fossil fuel emissions probably accounts for the renewed increase in global methane levels after 2006, although the relative contribution of these two sources remains uncertain.

periodic variations↗
NASA NTRS2022

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↗
NASA NTRS1997

An Ecosystem Simulation Model for Methane Production and Emission from Wetlands

Previous experimental studies suggest that methane emission from wetland is influenced by multiple interactive pathways of gas production and transport through soil and sediment layers to the atmosphere. The objective of this study is to evaluate a new simulation model of methane production and emission in wetland soils that was developed initially to help identify key processes that regulate methanogenesis and net flux of CH4 to the air, but which is designed ultimately for regional simulation using remotely sensed inputs for land cover characteristics. The foundation for these computer simulations is based on a well-documented model (CASA) of ecosystem production and carbon cycling in the terrestrial blaspheme. Modifications to represent flooded wetland soils and anaerobic decomposition include three new sub-models for: (1) layered soil temperature and water table depth (WTD) as a function of daily climate drivers, (2) CH4 production within the anoxic soil layer as a function of WTD and CO2 production under poorly drained conditions, and (3) CH4 gaseous transport pathways (molecular diffusion, ebullition, and plant vascular transport) as a function of WTD and ecosystem type. The model was applied and tested using climate and ecological data to characterize tundra wetland sites near Fairbanks, Alaska studied previously by Whalen and Reeburgh. Comparison of model predictions to measurements of soil temperature and thaw depth, water-table depth, and CH4 emissions over a two year period suggest that inter-site differences in soil physical conditions and methane fluxes could be reproduced accurately for selected periods. Day-to-day comparison of predicted emissions to measured CH4 flux rates reveals good agreement during the early part of the thaw season, but the model tends to underestimate production of CH4 during the months of July and August in both test years. Important seasonal effects, including that of falling WTD during these periods, are apparently overlooked in the model formulation. Nevertheless, reasonably close agreement was achieved between the model's mean daily and seasonal estimates of CH4 flux and observed emission rates for northern wetland ecosystems. Several features of the model are identified as crucial to more accurate prediction of wetland methane emission, including the capacity to incorporate influences of localized topographic and hydrologic features on site-specific soil temperature and WTD dynamics, and mechanistic simulation of methane emission transport pathways from within the soil profile.

Potter, C. S.↗
NASA NTRS1997

Regional Application of an Ecosystem Production Model for Studies of Biogeochemistry in the...

The degree to which primary production, soil carbon, and trace gas fluxes in tropical forests of the Amazon are limited by moisture availability and other environmental factors was examined using an ecosystem modeling application for the country of Brazil. A regional geographic information system (GIS) serves as the data source of climate drivers, satellite images, land cover, and soil properties for input to the NASA Ames-CASA (Carnegie-Ames-Stanford Approach) model over a 8-km grid resolution. Simulation results supports the hypothesis that net primary production (NPP) is limited by cloud interception of solar radiation over the humid northwestern portion of the region. Peak annual rates for NPP of nearly 1.4 kg C m-2yr -1are localized in the seasonally dry eastern Amazon in areas that we assume are primarily deep-rooted evergreen forest cover. Regional effects of forest conversion on NPP and soil carbon content are indicated in the model results, especially in seasonally dry areas. Comparison of model flux predictions along selected eco-climatic transects reveal moisture, soil, and land use controls on gradients of ecosystem production and soil trace gas emissions (CO2, N2O, and NO). These results are used to formulate a series of research hypotheses for testing in the next phase of regional modeling, which includes recalibration of the light-use efficiency term in CASA using field measurements of NPP, and refinements of vegetation index and soil property (texture and potential rooting depth) maps for the region.

Potter, C. S.↗
NASA NTRS2012

Modeling the Ecosystem Services Provided by Trees in Urban Ecosystems: Using Biome-BGC to Improve i-Tree Eco

As the world becomes increasingly urban, the need to quantify the effect of trees in urban environments on energy usage, air pollution, local climate and nutrient run-off has increased. By identifying, quantifying and valuing the ecological activity that provides services in urban areas, stronger policies and improved quality of life for urban residents can be obtained. Here we focus on two radically different models that can be used to characterize urban forests. The i-Tree Eco model (formerly UFORE model) quantifies ecosystem services (e.g., air pollution removal, carbon storage) and values derived from urban trees based on field measurements of trees and local ancillary data sets. Biome-BGC (Biome BioGeoChemistry) is used to simulate the fluxes and storage of carbon, water, and nitrogen in natural environments. This paper compares i-Tree Eco's methods to those of Biome-BGC, which estimates the fluxes and storage of energy, carbon, water and nitrogen for vegetation and soil components of the ecosystem. We describe the two models and their differences in the way they calculate similar properties, with a focus on carbon and nitrogen. Finally, we discuss the implications of further integration of these two communities for land managers such as those in Maryland.

Brown, Molly E.↗
NASA NTRS1980

Simulation modeling of estuarine ecosystems

A simulation model has been developed of Galveston Bay, Texas ecosystem. Secondary productivity measured by harvestable species (such as shrimp and fish) is evaluated in terms of man-related and controllable factors, such as quantity and quality of inlet fresh-water and pollutants. This simulation model used information from an existing physical parameters model as well as pertinent biological measurements obtained by conventional sampling techniques. Predicted results from the model compared favorably with those from comparable investigations. In addition, this paper will discuss remotely sensed and conventional measurements in the framework of prospective models that may be used to study estuarine processes and ecosystem productivity.

Johnson, R. W.↗
NASA NTRS1999

Physical Control of Biological Productivity Off the Coast of Peru During the 1997-1998 El Nino

Satellite observations and an ecosystem model are used to understand the variability in the planktonic ecosystem off Peru for the period January 1996 to May 1998. The objective of this study is to quantify the changes in the ecosystem components, carbon pathways, and available food for small pelagic fish that occur associated with the change in physical forcing due to El Nino. Two periods are distinguished based on the observed sea level anomaly: a La Nina (LaN) period (1996) in which sea level was below normal and El Nino (EN), the average conditions for December 1997, in which the sea level was anomalously high. There are three phytoplankton size classes (pico-, nano-, and net-phytoplankton) which compete for nutrients and are eaten by three zooplankton size classes. The ecosystem model is forced by alongshore wind speed measured by the NASA Scatterometer (NSCAT) and the European Remote-sensing Satellites (ERS-1 and ERS-2). Larger, slower growing organisms are more sensitive to physical disturbance than smaller organisms (Carr, 1998]. In the present simulation as well, the primary effect of the El Nino (reduced nutrient supply, and increased temperature) is to reduce the biomass of large cells (netphytoplankton) and consequently of the zooplankton that rely on large cells as food source. EN conditions are accompanied by a rearrangement of carbon pathways: comparable uptake goes into reduced biomass accumulation, increased losses to respiration, reduced carbon export, and much reduced carbon available to fish. The star indicates the remotely sensed biomass (assuming a constant carbon to chlorophyll ratio of 60) as measured by the Ocean Color and Temperature Sensor (Nov.-Dec. 1996) and the Sea-viewing Wide Field-of-view Sensor (Dec. 1997). The model, which assumes no light limitation, overestimates total phytoplankton biomass. Additional Information is contained in the original.

Carr, Mary-Elena↗
NASA NTRS1998

A Simulation of Biological Prosesses in the Equatorial Pacific Warm Pool at 165 deg E

A nine-year simulation (1984-1992) of biological processes in the equatorial Pacific Warm Pool is presented. A modified version of the 4-component (phytoplankton, zooplankton, nitrate and ammonium) ecosystem model by McClain et al. (1996) is used. Modifications include use of a spectral model for computation of PAR and inclusion of fecal pellet remineralization and ammonium nitrification. The physical parameters (horizontal and vertical velocities and temperature) required by the ecosystem model were derived from an improved version of the Gent and Cane (1990) ocean general circulation model (Murtugudde and Busalacchi, 1997). Surface downwelling spectral irradiance was estimated using the clear-sky models of Frouin et al. (1989) and Gregg and Carder (1990) and cloud cover information from the International Satellite Cloud Climatology Project (ISCCP). The simulations indicate considerable variability on interannual time scales in all four ecosystem components. In particular, surface chlorophyll concentrations varied by an order of magnitude with maximum values exceeding 0.30 mg/cu m in 1988, 1989, and 1990, and pronounced minimums during 1987 and 1992. The deep chlorophyll maximum ranged between 75 and 125 meters with values occasionally exceeding 0.40 mg/cu m. With the exception of the last half of 1988, surface nitrate was always near depletion. Ammonium exhibited a subsurface maximum just below the DCM with concentrations as high as 0.5 mg-atN/cu m . Total integrated annual primary production varied between 40 and 250 gC/sq m/yr with an annual average of 140 gC/sq m/yr. Finally, the model is used to estimate the mean irradiance at the base of the mixed layer, i.e., the penetration irradiance, which was 18 Watts/sq m over the nine year period. The average mixed layer depth was 42 m.

McClain, Charles R.↗
NASA NTRS2022

Effect of Assimilating SMAP Soil Moisture on CO2 and CH4 Fluxes through Direct Insertion in a Land Surface Model

Soil moisture impacts the biosphere–atmosphere exchange of CO2 and CH4 and plays an important role in the terrestrial carbon cycle. A better representation of soil moisture would improve coupled carbon–water dynamics in terrestrial ecosystem models and could potentially improve model estimates of large-scale carbon fluxes and climate feedbacks. Here, we investigate using soil moisture observations from the Soil Moisture Active Passive (SMAP) satellite mission to inform simulated carbon fluxes in the global terrestrial ecosystem model LPJ-wsl. Results suggest that the direct insertion of SMAP reduces the bias in simulated soil moisture at in situ measurement sites by 40%, with a greater improvement at temperate sites. A wavelet analysis between the model and measurements from 26 FLUXNET sites suggests that the assimilated run modestly reduces the bias of simulated carbon fluxes for boreal and subtropical sites at 1–2-month time scales. At regional scales, SMAP soil moisture can improve the estimated responses of CO2 and CH4 fluxes to extreme events such as the 2018 European drought and the 2019 rainfall event in the Sudd (Southern Sudan) wetlands. The simulated improvements to land–surface carbon fluxes using the direct insertion of SMAP are shown across a variety of timescales, which suggests the potential of SMAP soil moisture in improving the model representation of carbon–water coupling.

SMAP↗