This is a review of an article presented to Dr. Yang's GIS for Environmental Modeling class at Florida State University in the spring of 2008.
Sheppard, James K., Lawler, Ivan R., Marsh, Helene. (2007). Seagrass as Pasture for Seacows: Landscape-Level Dugong Habitat Evaluation. Estuarine Coastal & Shelf Science, 71(1-2):117-132.
The dugong is a cousin to the West Indian manatee, which feeds on specific types of seagrasses in area around northern Australia, Indonesia, and along similar latitudes along coastal areas of the Indian Ocean. This study uses GIS to determine which specific types of seagrasses are preferred by grazing dugongs in waters off of Queensland, Australia. GIS is used to observe remotely sensed near infrared spectroscopy to quantify the composition and configuration of seagrass communities.
Dugongs are tagged with GPS tracking devices, and their locations are tracked using the Animal Movement Analyst Extendsion in ArcView. After three months of tracking, a study area is developed from the many line features created by the movement of the animals to estimate the extent of popular grazing locations in Hervey Bay. Several field methods are used to capture samples of seagrasses at various locations throughout the study area – ranging from intertidal treks in shallow water to sample plant species by hand, to using submarine video equipment to analyze the plant structure from a boat. Both methods use GPS to derive latitude and longitude data and to record other information. Further, a steel sediment grab is used to sample benthic composition and sediment nutrients.
The information is loaded into a GIS where bathymetry, seagrass cover, and nutrient profiles are created from the GIS point data that was captured. Each of these layers are interpolated into a raster surface using the Kriging method, as it yields the most precise output for the data captured. Nutrient analysis is conducted with Near Infrared Reflectance Spectroscopy (NRIS) due to its ability to identify the composition of organic samples very efficiently.
The analysis sampled five seagrasses, ranging in levels of nitrogen, starch, and fiber. The dugongs convert nitrogen into protein, and use starch for energy. Fiber is a tertiary element in the seagrasses that is difficult for the dugongs to digest, therefore it is mainly avoided in large amounts. The analysis in this study confirms these findings from past research.
Remote sensing in this study is limited in evaluating biomass and species at low densities. More valid results are easier to obtain when higher concentrations of any particular species exist over a larger area, though patches can be discovered and accounted for when sampling. This aligns well with the general structure of seagrass meadows. Further, remote sensing is limited to shallow water, or where seagrass stalks reach to shallow depths of water were the electromagnetic wave can penetrate and return to the capturing device. Water quickly absorbs much of the beam emitted from sensing devices. In addition, turbid water is another limiting factor to using remote sensing in open, flowing water.
Overall, this is a very interesting article that touches on several powerful uses of GIS and remote sensing technology. The biological analysis addressed seems to get moderately complex, however the conclusions are clearly represented and are easily interpreted in context with the spatial component of this research.
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