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At least 163 records · Page 9

The 1990 forest ecosystem dynamics multisensor aircraft campaign

The overall objective of the Forest Ecosystem Dynamics (FED) research activity is to develop a better understanding of the dynamics of forest ecosystem evolution over a variety of temporal and spatial scales. Primary emphasis is being placed on assessing the ecosystem dynamics associated with the transition zone between northern hardwood forests in eastern North America and the predominantly coniferous forests of the more northerly boreal biome. The approach is to combine ground-based, airborne, and satellite observations with an integrated forest pattern and process model which is being developed to link together existing models of forest growth and development, soil processes, and radiative transfer.

Williams, Darrel L.

GLOBEC: Global Ocean Ecosystems Dynamics: A component of the US Global Change Research Program

GLOBEC (GLOBal ocean ECosystems dynamics) is a research initiative proposed by the oceanographic and fisheries communities to address the question of how changes in global environment are expected to affect the abundance and production of animals in the sea. The approach to this problem is to develop a fundamental understanding of the mechanisms that determine both the abundance of key marine animal populations and their variances in space and time. The assumption is that the physical environment is a major contributor to patterns of abundance and production of marine animals, in large part because the planktonic life stages typical of most marine animals are intrinsically at the mercy of the fluid motions of the medium in which they live. Consequently, the authors reason that a logical approach to predicting the potential impact of a globally changing environment is to understand how the physical environment, both directly and indirectly, contributes to animal abundance and its variability in marine ecosystems. The plans for this coordinated study of of the potential impact of global change on ocean ecosystems dynamics are discussed.

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A bottom-up evolution of terrestrial ecosystem modeling theory, and ideas toward global vegetation modeling

A primary purpose of this review is to convey lessons learned in the development of a forest ecosystem modeling approach, from it origins in 1973 as a single-tree water balance model to the current regional applications. The second intent is to use this accumulated experience to offer ideas of how terrestrial ecosystem modeling can be taken to the global scale: earth systems modeling. A logic is suggested where mechanistic ecosystem models are not themselves operated globally, but rather are used to 'calibrate' much simplified models, primarily driven by remote sensing, that could be implemented in a semiautomated way globally, and in principle could interface with atmospheric general circulation models (GCM's).

Running, Steven W.

Response of Earth's Ecosystem to Global Change

The Earth is in the midst of rapid and unprecedented change, much of it caused by the enormous reproductive and resource acquisition success of the human population. For the first time in Earth's history, the actions of one species-humans-are altering the atmospheric, climatic, biospheric, and edaphic processes on a scale that rivals natural processes. How will ecosystems, involving those manipulated and managed by humans largely for human use, respond to these changes? Clearly ecosystems have been adjusting to change throughout Earth's history and evolving in ways to adapt and to maintain self-organizing behavior. And in this process, the metabolic activity of the biosphere has altered the environmental conditions it experiences. I am going to confine this presentation to a few thoughts on the present state of terrestrial ecosystems and the urgency that changes in it is bringing to all of us.

Peterson, David L.

SIR-C/X-SAR: Imaging Radar Analyses for Forest Ecosystem Modeling

Progress, significant results and future plans are discussed relating to the following objectives: (1) Ecosystem characterization using SIR-C/X-SAR and AirSAR data; (2) Improving radar backscatter models for forest canopies; and (3) Using SAR measurements and models with forest ecosystem models to improve inferences of ecosystem attributes and processes.

Ranson, K. Jon

Ecosystems and the Biosphere as Complex Adaptive Systems

Ecosystems are prototypical examples of complex adaptive systems, in which patterns at higher levels emerge from localized interactions and selection processes acting at lower levels. An essential aspect of such systems is nonlinearity, leading to historical dependency and multiple possible outcomes of dynamics. Given this, it is essential to determine the degree to which system features are determined by environmental conditions, and the degree to which they are the result of self-organization. Furthermore, given the multiple levels at which dynamics become apparent and at which selection can act, central issues relate to how evolution shapes ecosystems properties, and whether ecosystems become buffered to changes (more resilient) over their ecological and evolutionary development or proceed to critical states and the edge of chaos.

Levin, Simon A.

Cryoconite and Ice-bubble Microbial Ecosystems in Antarctica

During the Antarctica 2000 Expedition samples of rocks and ice bubbles entrained in ice were collected from the blue ice fields near the Moulton Escarpment of the Thiel Mountains (85S, 94W) and the Morris Moraine of the Patriot Hills (80S, 8 1 W) Ellsworth Mountains of Antarctica. Investigation of the microbiota of these cryoconite and ice bubble ecosystems are now being conducted to help refine chemical and morphological biomarkers of potential significance to Astrobiology. The Antarctica 2000 Expedition will be discussed and the preliminary results of the studies of the ice bubble and cryoconite microbial ecosystems discussed. Recent ESEM images of the Antarctic microbiota will be presented a the relevance of ice ecosystems to Astrobiology will be discussed.

Hoover, Richard B.

Modern Microbial Ecosystems are a Key to Understanding Our Biosphere's Early Evolution and its Contributions To The Atmosphere and Rock Record

The survival of our early biosphere depended upon efficient coordination anion- diverse microbial populations. Microbial mats exhibit a 3.46-billion-year fossil record, thus they are the oldest known ecosystems. Photosynthetic microbial mats were key because, today, sunlight powers more than 99 percent of global primary productivity. Thus photosynthetic ecosystems have affected the atmosphere profoundly and have created the most pervasive, easily-detected fossils. Photosynthetic biospheres elsewhere will be most detectible via telescopes or spacecraft. As a part of the Astrobiology Institute, our Ames Microbial Ecosystems group examines the roles played by ecological processes in the early evolution of our biosphere, as recorded in geologic fossils and in the macromolecules of living cells: (1) We are defining the microbial mat microenvironment, which was an important milieu for early evolution. (2) We are comparing mats in contrasting environments to discern strategies of adaptation and diversification, traits that were key for long-term survival. (3) We have selected sites that mimic key environmental attributes of early Earth and thereby focus upon evolutionary adaptations to long-term changes in the global environment. (4) Our studies of gas exchange contribute to better estimates of biogenic gases in Earth's early atmosphere. This group therefore directly addresses the question: How have the Earth and its biosphere influenced each other over time Our studies strengthen the systematics for interpreting the microbial fossil record and thereby enhance astrobiological studies of martian samples. Our models of biogenic gas emissions will enhance models of atmospheres that might be detected on inhabited extrasolar planets. This work therefore also addresses the question: How can other biospheres be recogniZed" Our choice of field sites helps us explore Earth's evolving early environment. For example, modern mats that occupy thermal springs and certain freshwater environments experience conditions such as low O2 and sulfate and high inorganic carbon and sulfide levels that resemble those of ancient marine environments. Later in history, both biologically-induced carbonate precipitation and the trapping and binding of suspended grains of carbonate became a dominant mechanism for carbonate deposition. Modern marine carbonate platforms and alkaline offer good examples of microbiologically-induced calcification. Both marine platforms and solar salterns illustrate microbially-driven trapping and binding. We are also exploring the effects of water composition upon the exchange of biogenic gases with the atmosphere.

DesMarais, David J.

BIOME: An Ecosystem Remote Sensor Based on Imaging Interferometry

Until recent times, optical remote sensing of ecosystem properties from space has been limited to broad band multispectral scanners such as Landsat and AVHRR. While these sensor data can be used to derive important information about ecosystem parameters, they are very limited for measuring key biogeochemical cycling parameters such as the chemical content of plant canopies. Such parameters, for example the lignin and nitrogen contents, are potentially amenable to measurements by very high spectral resolution instruments using a spectroscopic approach. Airborne sensors based on grating imaging spectrometers gave the first promise of such potential but the recent decision not to deploy the space version has left the community without many alternatives. In the past few years, advancements in high performance deep well digital sensor arrays coupled with a patented design for a two-beam interferometer has produced an entirely new design for acquiring imaging spectroscopic data at the signal to noise levels necessary for quantitatively estimating chemical composition (1000:1 at 2 microns). This design has been assembled as a laboratory instrument and the principles demonstrated for acquiring remote scenes. An airborne instrument is in production and spaceborne sensors being proposed. The instrument is extremely promising because of its low cost, lower power requirements, very low weight, simplicity (no moving parts), and high performance. For these reasons, we have called it the first instrument optimized for ecosystem studies as part of a Biological Imaging and Observation Mission to Earth (BIOME).

Peterson, David L.

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.

Seasonal Variation and Ecosystem Dependence of Emission Factors for Selected Trace Gases and PM2.5 for Southern African Savanna Fires

In this paper we present the first early dry season (early June-early August) emission factor measurements for carbon dioxide (CO2), carbon monoxide (CO), methane (Ca), nonmethane hydrocarbons (NMHC), and particulates with a diameter less than 2.5 microns (pM2.5) for southern African grassland and woodland fires. Seasonal emission factors for grassland fires correlate linearly with the proportion of green grass, used as a surrogate for the fuel moisture content, and are higher for products of incomplete combustion in the early part of the dry season compared with later in the dry season. Models of emission factors for NMHC and PM(sub 2.5) versus modified combustion efficiency (MCE) are statistically different in grassland compared with woodland ecosystems. We compare predictions based on the integration of emissions factors from this study, from the southern African Fire-Atmosphere Research Initiative 1992 (SAFARI-92), and from SAFARI-2000 with those based on the smaller set of ecosystem-specific emission factors to estimate the effects of using regional-average rather than ecosystem-specific emission factors. We also test the validity of using the SAFARI-92 models for emission factors versus MCE to predict the early dry season emission factors measured in this study. The comparison indicates that the largest discrepancies occur at the low end (0.907) and high end (0.972) of MCE values measured in this study. Finally, we combine our models of MCE versus proportion of green grass for grassland fires with emission factors versus MCE for selected oxygenated volatile organic compounds measured in the SAFARI-2000 campaign to derive the first seasonal emission factors for these compounds. The results of this study demonstrate that seasonal variations in savanna fire emissions are important and should be considered in modeling emissions at regional to continental scales.

Korontzi, S.

Using Remotely Sensed Data and Watershed and Hydrodynamic Models to Evaluate the Effects of Land Cover Land Use Change on Aquatic Ecosystems in Mobile Bay, AL

Alabama coastal systems have been subjected to increasing pressure from a variety of activities including urban and rural development, shoreline modifications, industrial activities, and dredging of shipping and navigation channels. The impacts on coastal ecosystems are often observed through the use of indicator species. One such indicator species for aquatic ecosystem health is submerged aquatic vegetation (SAV). Watershed and hydrodynamic modeling has been performed to evaluate the impact of land cover land use (LCLU) change in the two counties surrounding Mobile Bay (Mobile and Baldwin) on SAV stressors and controlling factors (temperature, salinity, and sediment) in the Mobile Bay estuary. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for LCLU scenarios in 1948, 1992, 2001, and 2030. Remotely sensed Landsat-derived National Land Cover Data (NLCD) were used in the 1992 and 2001 simulations after having been reclassified to a common classification scheme. The Prescott Spatial Growth Model was used to project the 2030 LCLU scenario based on current trends. The LSPC model simulations provided output on changes in flow, temperature, and sediment for 22 discharge points into the estuary. These results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment on a grid throughout Mobile Bay and adjacent estuaries. The changes in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on SAV habitat suitability. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of temperature, salinity, and sediment due to LCLU driven flow changes with the restoration potential of SAVs. Data products and results are being integrated into NOAA s EcoWatch and Gulf of Mexico Data Atlas online systems for dissemination to coastal resource managers and stakeholders.

Al-Hamdan, Mohammad Z.

Using Remotely Sensed Data and Watershed and Hydrodynamic Models to Evaluate the Effects of Land Cover Land Use Change on Aquatic Ecosystems in Mobile Bay, AL

Alabama coastal systems have been subjected to increasing pressure from a variety of activities including urban and rural development, shoreline modifications, industrial activities, and dredging of shipping and navigation channels. The impacts on coastal ecosystems are often observed through the use of indicator species. One such indicator species for aquatic ecosystem health is submerged aquatic vegetation (SAV). Watershed and hydrodynamic modeling has been performed to evaluate the impact of land cover land use (LCLU) change in the two counties surrounding Mobile Bay (Mobile and Baldwin) on SAV stressors and controlling factors (temperature, salinity, and sediment) in the Mobile Bay estuary. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for LCLU scenarios in 1948, 1992, 2001, and 2030. Remotely sensed Landsat-derived National Land Cover Data (NLCD) were used in the 1992 and 2001 simulations after having been reclassified to a common classification scheme. The Prescott Spatial Growth Model was used to project the 2030 LCLU scenario based on current trends. The LSPC model simulations provided output on changes in flow, temperature, and sediment for 22 discharge points into the estuary. These results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment on a grid throughout Mobile Bay and adjacent estuaries. The changes in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on SAV habitat suitability. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of temperature, salinity, and sediment due to LCLU driven flow changes with the restoration potential of SAVs. Data products and results are being integrated into NOAA s EcoWatch and Gulf of Mexico Data Atlas online systems for dissemination to coastal resource managers and stakeholders. Objective 1: Develop and utilize Land Use scenarios for Mobile and Baldwin Counties, AL as input to models to predict the affects on water properties (temperature,salinity,)for Mobile Bay through 2030. Objective 2: Evaluate the impact of land use change on seagrasses and SAV in Mobile Bay. Hypothesis: Urbanization will significantly increase surface flows and impact salinity and temperature variables that effect seagrasses and SAVs.

Al-Hamdan, Mohammad

Using Remotely Sensed Data and Hydrologic Models to Evaluate the Effects of Climate Change on Shallow Aquatic Ecosystems in the Mobile Bay, AL Estuary

Coastal systems in the northern Gulf of Mexico, including the Mobile Bay, AL estuary, are subject to increasing pressure from a variety of activities including climate change. Climate changes have a direct effect on the discharge of rivers that drain into Mobile Bay and adjacent coastal water bodies. The outflows change water quality (temperature, salinity, and sediment concentrations) in the shallow aquatic areas and affect ecosystem functioning. Mobile Bay is a vital ecosystem that provides habitat for many species of fauna and flora. Historically, submerged aquatic vegetation (SAV) and seagrasses were found in this area of the northern Gulf of Mexico; however the extent of vegetation has significantly decreased over the last 60 years. The objectives of this research are to determine: how climate changes affect runoff and water quality in the estuary and how these changes will affect habitat suitability for SAV and seagrasses. Our approach is to use watershed and hydrodynamic modeling to evaluate the impact of climate change on shallow water aquatic ecosystems in Mobile Bay and adjacent coastal areas. Remotely sensed Landsat data were used for current land cover land use (LCLU) model input and the data provided by Intergovernmental Panel on Climate Change (IPCC) of the future changes in temperature, precipitation, and sea level rise were used to create the climate scenarios for the 2025 and 2050 model simulations. Project results are being shared with Gulf coast stakeholders through the Gulf of Mexico Data Atlas to benefit coastal policy and climate change adaptation strategies.

Estes, M. G.

Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

Meng, Ran

Pre-Aerosol, Clouds, and Ocean Ecosystem (PACE) Mission Science Definition Team Report: PACE Technical Report Series - Volume 2

We live in an era in which increasing climate variability is having measurable impact on marine ecosystems within our own lifespans. At the same time, an ever-growing human population requires increased access to and use of marine resources. To understand and be better prepared to respond to these challenges, we must expand our capabilities to investigate and monitor ecological and bio geo chemical processes in the oceans. In response to this imperative, the National Aeronautics and Space Administration (NASA) conceived the Pre-Aerosol, Clouds, and ocean Ecosystem (PACE) mission to provide new information for understanding the living ocean and for improving forecasts of Earth System variability. The PACE mission will achieve these objectives by making global ocean color measurements that are essential for understanding the carbon cycle and its inter-relationship with climate change, and by expanding our understanding about ocean ecology and biogeochemistry. PACE measurements will also extend ocean climate data records collected since the 1990s to document changes in the function of aquatic ecosystems as they respond to human activities and natural processes over short and long periods of time. These measurements are pivotal for differentiating natural variability from anthropogenic climate change effects and for understanding the interactions between these processes and various human uses of the ocean. PACE ocean science goals and measurement capabilities greatly exceed those of our heritage ocean color sensors, and are needed to address the many outstanding science questions developed by the oceanographic community over the past 40 years.

Cetinic, Ivona

Building a Data Ecosystem: A New Data Stewardship Paradigm for the Multi-Mission Algorithm and Analysis Platform (MAAP)

New adaptive approaches to Earth observation data stewardship need to be adopted in order to allow for higher data volumes, heterogeneous data and constantly evolving technologies. The data ecosystem approach to stewardship offers a viable solution to this need by placing an emphasis on the relationships between data, technologies and people. In this paper, we present the Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform’s (MAAP) creation of a data ecosystem to support global aboveground terrestrial carbon dynamics research. We present the components needed to support the MAAP data ecosystem along with two data stewardship workflows used in the MAAP and the development of extended metadata for MAAP.

Bugbee, Kaylin

Multimodel Analysis of Future Land Use and Climate Change Impacts on Ecosystem Functioning

Land use and climate changes both affect terrestrial ecosystems. Here, we used three combinations of Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP1xRCP26, SSP3xRCP60, and SSP5xRCP85) as input to three dynamic global vegetation models to assess the impacts and associated uncertainty on several ecosystem functions: terrestrial carbon storage and fluxes, evapotranspiration, surface albedo, and runoff. We also performed sensitivity simulations in which we kept either land use or climate (including atmospheric CO2) constant from year 2015 on to calculate the isolated land use versus climate effects. By the 2080–2099 period, carbon storage increases by up to 87 ± 47 Gt (SSP1xRCP26) compared to present day, with large spatial variance across scenarios and models. Most of the carbon uptake is attributed to drivers beyond future land use and climate change, particularly the lagged effects of historic environmental changes. Future climate change typically increases carbon stocks in vegetation but not soils, while future land use change causes carbon losses, even for net agricultural abandonment (SSP1xRCP26). Evapotranspiration changes are highly variable across scenarios, and models do not agree on the magnitude or even sign of change of the individual effects. A calculated decrease in January and July surface albedo (up to −0.021 ± 0.007 and −0.004 ± 0.004 for SSP5xRCP85) and increase in runoff (+67 ± 6 mm/year) is largely driven by climate change. Overall, our results show that future land use and climate change will both have substantial impacts on ecosystem functioning. However, future changes can often not be fully explained by these two drivers and legacy effects have to be considered.

Krause, A.