Home > File Archive > Other

Other Files

 
Page 1 of 2  
Category Theme Resource  (click on title to view file details) Download
Research Data Data Submission Geographic variation in top-down and bottom-up control of a salt marsh food web, and oil spill impacts
Description - Understanding the relative strengths of top-down and bottom-up forces is an important key to predicting the structure of biological communities. The strength of these effects can be regulated in part by predator abundance and nutrient availability. In 2009, we hypothesized that the importance of these factors varies geographically between the southeastern Atlantic Coast and the Gulf Coast due to differences in tidal regime, and began to study this variation using a biogeographic, manipulative field experiment. Although our original purpose was to understand the structure of salt marsh arthropod food webs, BP's Deepwater Horizon spill in the Gulf Coast presented an opportunity to understand how stress from an oil spill might affect the variables that we were measuring. The fact that we had plots and transect sampling in place at multiple sites along the Gulf and East Coasts put us in a position to evaluate any impacts that might occur if oil hit some of the sites.

The study was conducted at 11 sites across the Gulf Coast, from Texas to Florida, and 11 sites along the Atlantic Coast, from Florida to Maine. At each site, experimental plots were sampled and a 100m transect was sampled near the plots within 5m of the high marsh boundary. Sampling was conducted in May 2009, August 2009, and August 2010. In 2010, four extra sites were added to the existing experimental sites because of known oil contamination, and another site was added as an extra control. Only the transect sampling was conducted at these sites. At this date we are making available the metadata and study locations in order to inform other research efforts related to the BP Deepwater Horizon Oil Spill. Data will be made available after samples are processed.
(contributed by Steve Pennings, 2010)
KML file
      MS Excel file
Forms Data Submission GCE data-only submission form for describing tabular data files to attach to data sets submitted online
Description - This Microsoft Excel spreadsheet template is provided for formatting and describing tabular data files for submission to the GCE Information Management Office for archiving in the GCE Data Catalog and LTER Data Portal. Note that data set documentation (metadata) must be provided separately online prior to submission of the data files (see https://gce-lter.marsci.uga.edu/private/app/add_dataset.asp to register the documentation).

For tabular data (e.g. spreadsheets, non-digital data sheets, simple comma or space-delimited logger files), the data values and column information should be entered or pasted into the "Tabular Data" worksheet unless prior arrangements are made with IM staff for parsing data from specialized formats (e.g. raw data logger files, real-time data telemetry or lab-specific storage formats). Specialized tabular or non-tabular data (e.g. GIS files, raster imagery, genomics data) can be described and uploaded directly from the View Submissions page (see below) after the metadata are submitted so use of this template is not required.

Completed templates and data files (if provided separately) should be uploaded to the GCE IM office using the "Add Files" links for the corresponding data set metadata on the Private GCE Web Site (https://gce-lter.marsci.uga.edu/private/app/view_submissions.asp).

More information about GCE data submission is available at http://gce-lter.marsci.uga.edu/public/im/data_submission.htm. An overview and training presentation (Adobe Acrobat PDF file) and example tabular data file (Zip Archive) are also available for reference.
(contributed by Wade Sheldon, 2019)
PDF file
      MS Excel file
      Zip archive
    GCE data and metadata submission form for tabular and non-tabular data files (legacy version)
Description - Note: This form has been deprecated as of October 2018. Please used the new GCE Data Submission web forms (https://gce-lter.marsci.uga.edu/private/app/add_dataset.asp) to enter or revise data set documentation (metadata), and use the updated Excel data submission template (http://gce-lter.marsci.uga.edu/public/app/resource_details.asp?id=852) to prepare your data file(s) for archiving.

~~~~~~~~~~

This Microsoft Excel spreadsheet template is provided for submitting metadata (documentation) for both tabular and non-tabular data sets to the GCE Information Management Office for archiving in the GCE Data Catalog and LTER Data Portal. More information about GCE data submission is available at http://gce-lter.marsci.uga.edu/public/im/data_submission.htm.

For tabular data (e.g. spreadsheets, logger files), the data values and column information can be included in the "Tabular Data" worksheet along with the documentation metadata, or provided separately if prior arrangements are made with IM staff for parsing data from specialized formats (e.g. raw data logger files, real-time data telemetry or lab-specific storage formats).

For non-tabular data (e.g. GIS files, raster imagery, genomics data), the data file(s) can be described in the template and then uploaded separately, or download links can be provided in the "Non-Tabular Data" worksheet.

Completed templates and data files (if provided separately) should be uploaded to the GCE IM office using the "Submit Data" form on the Private GCE Web Site (https://gce-lter.marsci.uga.edu/private/app/upload_data.asp).

Note that a GCE Data Submission Training presentation and Zip archive of sample submissions are also available for downloading (see http://gce-lter.marsci.uga.edu/public/app/resource_details.asp?id=535).
(contributed by Wade Sheldon, 2017)
MS Excel file
    Georgia Coastal Ecosystems LTER Controlled Keyword Vocabulary version 1.2 (June 2015)
Description - This spreadsheet contains the GCE-LTER controlled keyword vocabulary, with keywords categorized by type and mapped to the LTER Controlled Vocabulary terms.
(contributed by Wade Sheldon, 2015)
MS Excel file
  Oceanographic Cruises GCE quarterly oceanographic monitoring cruise log template
Description - (none)
(contributed by Wade Sheldon, 2005)
MS Excel file
  Research Planning Sapelo Island Research Annual Report Form
Description - As part of the research application and approval process, annual reports to research sponsors are required each year until the project is concluded, all research equipment has been removed, and the site has recovered from disturbance. Please use this form to complete these reports for attachment to your original research request. See the Sapelo Research Requests page for more information about requirements (link: http://gce-lter.marsci.uga.edu/public/site/research_requests.htm).
(contributed by Dorset Hurley, 2011)
MS Word file
      Rich text file
Logistics Geographic Coordinates Georgia Rivers LMER CTD profiling site coordinates
Description - (none)
(contributed by Wade Sheldon, 2007)
MS Excel file
Proposals GCE3 Proposal Planning GCE-III Project Summary
Description - (none)
(contributed by Merryl Alber, 2012)
PDF file
Software ArcGIS extension Animal Space Use for ArcGIS v.1
Description - Animal Space Use for ArcGIS v.1 is an ESRI ArcGIS extension designed to process output files generated from the Animal Space Use stand alone software. The zip folder contains a .pdf user manual as well as an .exe file with ESRI .mxd and .mxt documents and Microsoft Excel .xla and .xlam files.

Please refer to the user manual for further instructions.
(contributed by John Carpenter, 2009)
Zip archive
  GIS Scripts GCE ArcGIS Python Scripts
Description - Eight Python scripts (version 2.5) were developed to dynamically generate ESRI shapefiles. The scripts use input data from a database or csv file, and the output is saved as a zipfile. Each script has two variants: 1) a prompt interface, which allows the user to pass in variables from the command line, and 2) hard coded variables, which allows the script to be utilized in an integrated information system. The scripts are organized into two main categories. The first category receives input data from a database. Six scripts receive input data from a database, and are further categorized according to their output. These are: 1) One point shapefile that contains one or more points, 2) One polygon shapefile that contains two or more polygons, and 3) One polygon shapefile that contains one polygon per shapefile. The SQL and ArcGIS attribute table fields are dynamically generated based on variables that are either passed in or hard coded in the script. The other main category, a total of two scripts, receives input data from a csv file. For every csv file in a directory, one point shapefile is generated for every row in the csv file. The ArcGIS attribute field names are dynamically generated based on the first row in the csv file. The code is thoroughly commented.
(contributed by Travis Douce, 2010)
Zip archive
  MATLAB Toolbox GCE Data Toolbox for MATLAB - Public Version 3.93
Description - The GCE Data Toolbox is a MATLAB software library that supports metadata-based analysis, visualization, transformation and management of ecological data sets. The toolbox is based on the GCE Data Structure, a specification for storing tabular data along with comprehensive metadata and quality control information. Metadata fields are queried by toolbox programs for all operations, allowing data values to be managed and analyzed appropriately based on the type of information they represent. This semantic processing approach supports highly automated and intelligent data analysis and ensures data set validity throughout all processing steps. Data structure size is only limited by available computer memory, and large data sets (e.g. >1 million records) can effectively be managed and analyzed using standard desktop computer hardware.

See the GCE Data Toolbox web page (http://gce-lter.marsci.uga.edu/public/im/tools/data_toolbox.htm) for more information.
(contributed by Wade Sheldon, 2015)
Zip archive
18 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.