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Presentations Posters The dynamic littoral fringe – Spatial and temporal patterns in community structureand productivity in North American coastal ecosystems
Abstract - This presentation will illustrate case studies of changes in littoral ecosystems on the Northern Gulf of Mexico and Southeastern Atlantic coasts, as captured with satellite and airborne imagery analysis. On the Georgia coast, 35 years of Landsat imagery revealed large scale (3 fold) inter-annual variation and a cumulative net loss of 16.5% in the aboveground biomass of the keystone salt marsh species, Spartina alterniflora. Spatial differences and temporal changes in 620 km2 (about 680,000 pixels of Spartina habitat) were linked to climate variables, river hydrology, and sea level dynamics. In the same area, riparian brackish and freshwater wetlands are sensitive indicators of changes in salinity patterns. On the Texas coast, Black Mangrove vegetation is replacing salt marsh communities, as shown in analysis of high resolution WorldView satellite imagery. This “tropicalization” is well underway, but also reveals instabilities due to occasional winter incursions of arctic air. Finally, at multiple sites, we’ve used airborne hyperspectral and HICO Space Station imagery to document patterns of phytoplankton chlorophyll (including HABs) and CDOM in estuarine, inshore, and shelf waters.
(contributed by John F. Schalles, 2018)
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    LIGHT AND TEMPERATURE CONTROL THE SEASONAL DISTRIBUTION OF THAUMARCHAEOTA IN THE SOUTH ATLANTIC BIGHT
Abstract - Previous work on the Georgia, USA coast revealed consistent mid-summer peaks in the abundance of Thaumarchaeota accompanied by spikes in nitrite concentration. We collected data on the distribution of Thaumarchaeota, ammonia-oxidizing Betaproteobacteria (AOB), nitrite-oxidizing Nitrospina, environmental variables and rates of ammonia oxidation during 6 cruises in the South Atlantic Bight from April to November 2014 to evaluate the areal extent and timing of the bloom. The abundance of Thaumarchaeota marker genes (16S rRNA and amoA) increased at inshore and nearshore stations starting in July and peaked in August at >107 copies L-1, a period when free Cu2+ concentrations (sub-fM) were well below those believed to limit Thaumarchaeota growth. The bloom did not extend onto the mid-shelf, where Thaumarchaeota genes ranged from 103 to 105 copies L-1. Clone libraries from samples collected at mid-shelf stations generated using Archaea 16S rRNA primers were dominated by sequences from Marine Group II and III Archaea, whereas libraries from inshore and nearshore stations were dominated by Thaumarchaeota. Thaumarchaeota were also abundant in oxygen-depleted waters at depth at the shelf-break. This population was phylogenetically-distinct from the inshore/nearshore population. Ammonia oxidation rates (AO) were highest at inshore stations and were at the limit of detection at mid-shelf stations. AO correlated significantly with ammonium concentration (r2=0.23) and Thaumarchaeota abundance (r2=0.14). Nitrite concentration correlated with AO (r2=0.74). Our analysis of environmental data suggests that Thaumarchaeota distributions in the SAB are controlled primarily by photoinhibition and secondarily by water temperature, while AO is controlled primarily by ammonium availability.
(contributed by James T. Hollibaugh, 2017)
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    Seawater Addition Long Term Experiment (SALTEx)
Abstract - SALTEx is a field experiment designed to simulate the effects of saltwater intrusion in a tidal freshwater marsh to help GCE scientists understand and predict changes resulting from chronic and acute salinization driven by sea level rise and climate variability.
(contributed by Dontrece Smith, 2016)
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    GCE Data Toolbox for MATLAB – a software framework for automating environmental data processing, quality control and documentation
Abstract - Environmental scientists are under increasing pressure from funding agencies and journal publishers to release quality-controlled data in a timely manner, as well as to produce comprehensive metadata for submitting data to long-term archives (e.g. DataONE, Dryad and BCO-DMO). At the same time, the volume of digital data that researchers collect and manage is increasing rapidly due to advances in high frequency electronic data collection from flux towers, instrumented moorings and sensor networks. However, few pre-built software tools are available to meet these data management needs, and those tools that do exist typically focus on part of the data management lifecycle or one class of data.The GCE Data Toolbox has proven to be both a generalized and effective software solution for environmental data management in the Long Term Ecological Research Network (LTER). This open source MATLAB software library, developed by the Georgia Coastal Ecosystems LTER program, integrates metadata capture, creation and management with data processing, quality control and analysis to support the entire data lifecycle. Raw data can be imported directly from common data logger formats (e.g. SeaBird, Campbell Scientific, YSI, Hobo), as well as delimited text files, MATLAB files and relational database queries. Basic metadata are derived from the data source itself (e.g. parsed from file headers) and by value inspection, and then augmented using editable metadata templates containing boilerplate documentation, attribute descriptors, code definitions and quality control rules. Data and metadata content, quality control rules and qualifier flags are then managed together in a robust data structure that supports database functionality and ensures data validity throughout processing. A growing suite of metadata-aware editing, quality control, analysis and synthesis tools are provided with the software to support managing data using graphical forms and command-line functions, as well as developing automated workflows for unattended processing. Finalized data and structured metadata can be exported in a wide variety of text and MATLAB formats or uploaded to a relational database for long-term archiving and distribution.The GCE Data Toolbox can be used as a complete, light-weight solution for environmental data and metadata management, but it can also be used in conjunction with other cyber infrastructure to provide a more comprehensive solution. For example, newly acquired data can be retrieved from a Data Turbine or Campbell LoggerNet Database server for quality control and processing, then transformed to CUAHSI Observations Data Model format and uploaded to a HydroServer for distribution through the CUAHSI Hydrologic Information System. The GCE Data Toolbox can also be leveraged in analytical workflows developed using Kepler or other systems that support MATLAB integration or tool chaining. This software can therefore be leveraged in many ways to help researchers manage, analyze and distribute the data they collect.
(contributed by Wade M. Sheldon, 2013)
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    GCE Data Toolbox and Metabase: A sensor-to-synthesis software pipeline for LTER data management
Abstract - LTER sites use a wide range of software to acquire, process, quality control and archive data. A separate set of tools is then typically used to produce and manage metadata content and generate EML-described data packages for the LTER NIS. This separation of data and metadata processing is inefficient, risks loss of information, and often delays data release. Software developed at the GCE LTER site - the GCE Data Toolbox for MATLAB - streamlines this process by coupling metadata creation to data processing and quality control. This software also interfaces with the Metabase, a sophisticated Metadata Management System (MMS) that supports data warehousing and automatic distribution of EML-described, version-controlled data through the NIS. Used together, these systems constitute an integrated and highly automated pipeline for producing EML-described data packages for archival and synthesis efforts. This poster describes how this software is used to automate and streamline data management at the GCE and CWT LTER sites, and opportunities for use at other sites.
(contributed by Wade M. Sheldon, 2012)
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    GCE Data Toolbox: Metadata-driven Software for Data Acquisition, Quality Control and Synthesis
Abstract - The effort required to process, document, and quality control raw data from sensors is often a limiting step in bringing environmental data online. Similarly, the effort required to find, download and refactor data collected by others can prove limiting in large-scale synthesis efforts. However, the GCE Data Toolbox (MATLAB-based software developed at GCE-LTER) has proven effective in overcoming both of these barriers. This software can automate processing of data collected by a wide variety of data logger systems, from initial acquisition through quality control and distribution of documented data sets and plots. It is equally adept at harvesting and integrating existing data from national monitoring programs and environmental databases (e.g. LTER ClimDB/HydroDB, USGS NWIS, NOAA NCDC, NOAA NERR). This poster provides a brief overview of the toolbox, which is freely available for use by other LTER sites.
(contributed by Wade M. Sheldon, 2011)
PDF file
    GCE Data Toolbox: Metadata-driven Software for Data Acquisition, Quality Control and Synthesis
Abstract - The effort required to process, document, and quality control raw data from sensors is often a limiting step in bringing environmental data online. Similarly, the effort required to find, download and refactor data collected by others can prove limiting in large-scale synthesis efforts. However, the GCE Data Toolbox (MATLAB-based software developed at the Georgia Coastal Ecosystems LTER) has proven effective in overcoming both of these barriers. This software can automate processing of data collected by a wide variety of data logger systems, from initial acquisition through quality control and distribution of documented data sets and plots. It is equally adept at harvesting and integrating existing data from national monitoring programs and environmental databases (e.g. LTER ClimDB/HydroDB, USGS NWIS, NOAA NCDC, NOAA NERR). This poster provides a brief overview of this software, which is freely available under an open source license.
(contributed by Wade M. Sheldon, 2011)
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    Varation in marsh benthic invertebrate presence and abundance related to altered Spartina alterniflora density
Abstract - (none)
(contributed by Caroline R. McFarlin, 2010)
MS PowerPoint
    GCE Software Tools for Data Mining, Analysis and Synthesis
Abstract - The GCE-LTER project and partner organizations (SINERR, UGAMI, USGS) collect extensive environmental monitoring data around Sapelo Island on the SE Georgia Coast. In order to put these observations into a broader spatial and temporal context, it is also important to compare these data with other environmental monitoring observations. Long-term, spatially-extensive climate and hydrologic databases maintained by the LTER Network (ClimDB/HydroDB), USGS (National Water Information System) and NOAA (National Weather Service) are valuable resources for broad-scale comparisons (fig.1). For example, the LTER Network’s ClimDB/HydroDB database contains approximately 7 million daily records for 281 monitoring stations at 39 LTER and USFS sites, providing critical support for LTER cross-site comparisons. USGS and NOAA collect long-term climate and hydrologic data from a vast array of locations across North America (~8000 real-time USGS monitoring stations and ~12,000 active NWS COOP weather stations), supporting truly large-scale regional analyses.
(contributed by Wade M. Sheldon, 2009)
MS PowerPoint
    The Effects of Climate Signals on Freshwater Delivery to Coastal Georgia, U.S.A.
Abstract - Freshwater delivery is an important factor determining salinity in the LTER Georgia Coastal Ecosystem (GCE) site. Variability in freshwater delivery was examined in relation to various climate indices: the Southern Oscillation Index (SOI), the North Atlantic Oscillation (NAO) and the Bermuda High Index (BHI). Monthly standardized anomalies of river discharge and climate indices were compared with multi-decadal time series of Altamaha watershed precipitation at 7-13 stations using empirical orthogonal function (EOF) analysis to describe the precipitation patterns. The first EOF mode (65% of the variance) was spatially uniform with temporal variability at the monthly scale. The second mode (11% of the variance) showed a spatial gradient along the long axis of the watershed (NW-SE) whereas the third mode (6% of the variance) showed an onshore-offshore pattern with higher variability during June-September. There were no consistent relationships between NAO and precipitation. The SOI shows correlations with discharge and weak correlations with modes 1 and 2 of the precipitation. The BHI is correlated with May-January discharge with a 0-1 month lag, and is also strongly correlated with EOF mode 1 of precipitation. The occurrence of tropical storms in theregion is also strongly related to the BHI, but not the SOI.
(contributed by Joan E. Sheldon, 2009)
MS PowerPoint
    Dynamic, Rule-based Quality Control Framework for Real-time Sensor Data
Abstract - Quality control is a critical component of environmental data management, particularly for data collected by autonomous sensors. Performing quality analysis on high volume, real-time data from sensor networks, flux towers and instrumented platforms is a major challenge, though, and can become a limiting factor in managing these data. Software developed at the Georgia Coastal Ecosystems LTER Site (GCE Data Toolbox for MATLAB) has proven very effective for quality control of both real-time and legacy data, as well as interactive analysis during post processing and synthesis. This poster describes the dynamic, rule-based quality control framework provided by this software and illustrates how it can be used for both automated and interactive quality management of sensor data.
(contributed by Wade M. Sheldon, 2009)
PDF file
    Seasonal effects of the Southern Oscillation and Bermuda High on freshwater delivery to the central Georgia coast
Abstract - Freshwater delivery to the central Georgia coast is alternately correlated with the Bermuda High Index (BHI) and the El Niño/Southern Oscillation Index (SOI), but only in a limited way with the North Atlantic Oscillation Index (NAOI). The BHI describes the east-west position of the southern pole of the NAO, which influences southeastern U.S.A. weather more than the north-south NAO. Three-month standardized anomalies of Altamaha River discharge and precipitation at two stations in its watershed and one on the coast were compared with each other and the three climate indices. In winter, precipitation is correlated more with winter SOI than with other climate indices, but precipitation is only weakly correlated with the previous winter’s SOI during other seasons. In spring, the BHI develops a strong correlation with coastal precipitation. This influence weakens somewhat during summer and fall but spreads to the Altamaha watershed. Fall precipitation is correlated with the spring ! NAOI as well as the fall BHI. At times, climate signals explain as much as 29% of the variability in local data. Evaluating the relative strengths of these climate signals will aid in estimating the potential effects of climate changes in eastern Georgia.
(contributed by Joan E. Sheldon, 2008)
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    Detecting climate signals in river discharge and precipitation data for the central Georgia coast
Abstract - Identifying the effects of global change requires identifying global-scale signals in local data. We are seeking evidence of climate signals such as the Southern Oscillation Index (SOI) and the North Atlantic Oscillation Index (NAOI) in long-term data for the Georgia coast. The NAOI leads the SOI by 1 month and the two are very weakly correlated, so these two signals could explain different patterns in local data. Monthly standardized anomalies of Altamaha River discharge and Georgia coastal precipitation were constructed by normalizing, deseasonalizing, and detrending those data. Climate indices were also transformed if necessary, and all series were prewhitened prior to cross-correlation analyses to determine the most appropriate lags between series. Altamaha discharge and coastal precipitation are weakly negatively correlated, suggesting that coastal and inland precipitation patterns are different. However, climate signals explain very little of the variability in the local data (R2 < 0.02). This analysis will be extended to other datasets for coastal Georgia.
(contributed by Joan E. Sheldon, 2007)
MS PowerPoint
    Software tools for automated synthesis of LTER, USGS and NOAA climate and hydrologic data
Abstract - A prerequisite for any study of altered ecosystems and ecosystem services is to understand historic conditions. For many studies this requires in-depth analysis of trends in past climatic conditions, often using data collected over large geographic regions. Long-term, spatially-extensive climate and hydrologic databases maintained by the LTER Network (ClimDB/HydroDB), USGS (National Water Information System) and NOAA (National Climatic Data Center) are valuable resources for such synthesis projects, but differences in data formats, attribute names and measurement units complicate integrating data from these databases and comparing results with local data. Conventional software used for data analysis, such as spreadsheets and statistical packages, provide few options for mitigating these semantic and syntactic differences; however, metadata-based analytical software developed by the Georgia Coastal Ecosystems LTER project - the GCE Data Toolbox - can significantly simplify this task. This toolbox, written using the platform-independent MATLAB programming language, contains easy-to-use graphical dialogs for retrieving data from any station in ClimDB/HydroDB and the USGS NWIS over the Internet as well as importing NOAA NCDC data downloaded manually. Column names, units and quality-control flags are automatically standardized as data are imported based on editable metadata templates and unit conversion tables provided with the software. After importing, data sets can be sub-sampled by removing unneeded columns and filtering records, or re-sampled by statistical aggregation and binning. Multiple data sets can then be integrated using metadata-based unions and relational joins to create synthetic data sets for analysis. Use of these tools, alone or as part of a larger data analysis workflow, could significantly enhance studies of long-term climate trends for evaluation of ecosystem alteration.
(contributed by Wade M. Sheldon, 2006)
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    Hyperspectral imaging of wetlands and estuarine waters of National Estuarine Research Reserves in the Southeastern and Mid-Atlantic Regions of the United States
Abstract - We’ve organized and participated in seven hyperspectral flyover campaigns at six NOAA National Estuarine Research Reserves (NERRs) since October, 2002. A University of Nebraska aircraft with an AISA sensor (Specim Imaging, Ltd) was flown at each site. Each flyover included coincident field survey work. Across all sites, we collected imagery and field survey data for marsh vegetation classifications and phytoplankton chlorophyll estimations in local estuarine and near-shore open water habitats. Our presentation addresses product development and will review issues of close-range spectral libraries and algorithms, atmospheric corrections, identification of algal blooms, and classification accuracies.
(contributed by John F. Schalles, 2006)
MS PowerPoint
26 Records
LTER
NSF

This material is based upon work supported by the National Science Foundation under grants OCE-9982133, OCE-0620959, OCE-1237140 and OCE-1832178. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.