Sunday, September 12, 2010

Geographic Information System - Seeing Patterns

Audubon South Carolina uses geographic information system (GIS) software for a variety of purposes.  As we've previously noted: GIS software allows one to take a mountain of data and view it graphically in any desired combination. In this way, patterns and relationships can be more easily detected.

The first image shows a bird's-eye view of the boardwalk here at the Francis Beidler Forest. The nature center and the beginning of the boardwalk are at the upper left. Goodsen Lake is shown at the lower right. North is at the top of the image. The data layers shown include the boardwalk; the species (flora and fauna) sighted over the last few years; the buildings and shelters; the low boardwalk trail; and the property boundaries.  Other layers on file include the canoe trail; Project PROTHO data such as nest locations, banding locations, banded bird sightings, and territories; access gates; habitat restoration sites; breeding bird survey plots; etc. What makes GIS technology a powerful tool is the user's ability to view the data separately or in combination with other, sometimes seemingly unrelated, data.

The species data are shown as individual points in the image with each type (plant, mammal, bird, reptile, insect, fish, etc.) shown in a unique color. Though the separate dots are difficult to see in the image, the software allows the user to zoom in. It should be clear that the green dots are the most seen animals. Based on our organization's focus, one could guess correctly that the green dots represent birds.
Using the data shown in the image as an example, there are over 7200 species points in the data table. In August, if a nature photographer had only an hour before she had to depart for the airport and she desperately wanted to take a picture of an Eastern Cottonmouth (Agkistrodon piscivorus piscivorus), where on the boardwalk would she likely have success? Simply looking through the table for the data to answer that question would be difficult, extremely time-consuming and likely fruitless. However, by posing that query using the GIS software (month and cottonmouth), only the appropriate data points light up. In seconds, you could tell the photographer to go to the stretch between #8 and #10.
Anyone with the free ESRI ArcView Reader software can view and query GIS data.  Changes cannot be made to the data, but students can view data, develop questions, and query the data for answers.  Recently, we showed this GIS capability to a local high school environmental studies teacher and used our species data as an example of the free resources available from the Audubon Center at Francis Beidler Forest.  Even though the staff has over 100 years of combined service at the Francis Beidler Forest and tens of thousands of walks around the boardwalk, we learned something by looking at the example maps we produced.
The first image shows all the recorded Eastern Cottonmouth sightings along the boardwalk.  As shown above, the time of year will dictate where along the boardwalk the snakes can be seen, but throughout the year Eastern Cottonmouths can be seen at any location.
We were curious if the same applied for Brown Water Snakes (Nerodia taxispilota).  As you can see below, Brown Water Snakes have not been sighted along the backside of the boardwalk (along the swamp's edge) or back toward the nature center.
When we pulled back to include the canoe trail, which is along the main creek channel of the swamp and almost always full of water, there were an abundance of Brown Water Snake sightings and only four Eastern Cottonmouth sightings.

The distance between the east end of the boardwalk and the west end at the swamp's edge is not great.  The distance between the end of the canoe trail and the east end of the boardwalk is approximately 300 meters.  However, the habitat obviously has different characteristics and the two species of snakes have their preferences.
Looking at the data picture produced by GIS technology allows one to immediately see a pattern that could not be perceived by looking through a table of data.  It does tell us why the pattern exists, but is clearly shows its existence and inspires us to investigate.
We'll let you know when we discover the answer!
Images by Mark Musselman

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