Graduate Thesis Or Dissertation
 

Development of a legend and key for ecological resource analysis in the 15-mile administrative unit, Malheur County, Oregon

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/k643b377s

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  • The project of which this research was a part is designed to provide an improved system of ecological resource analysis. Specific objectives of this study were: (1) classification of plant communities on the fringes of the sagebrush steppes and the salt desert of southeastern Oregon, (2) development of symbolic and descriptive legends for the classification units, and (3) preparation of a dichotomous key to the legend. Major landform stratification was done on an aerial photo mosaic to aid the selection of sampling areas. Sampling was done by ocular survey of entire stands with the aid of pretyped aerial photography. Society tables were used for a phytosociological synthesis of the data. Fifty-six important plant communities were identified and characterized. The synthesized data were used in preparation of a descriptive legend and the dichotomous key. This narrative legend includes a brief description of each community and a summary of its associated environmental characteristics. A symbolic legend was devised to identify each of these communities. The legend identifiers consist of a hierarchically arranged, three-digit, non-connotative symbol. A field test was made indicating that the legend and key could be accurately used in the project area. In the test, 97 percent of the keyed determinations and legend units fit the newly examined stands with negligible difference between two observers. The legend and key are designed for use with aerial photo interpretation to provide a resource analysis of increased accuracy at reasonable cost. Suggestions for expansion and adaptation of the legend to other areas are presented.
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  • File scanned at 300 ppi (Monochrome, 256 Grayscale) using Capture Perfect 3.0.82 on a Canon DR-9080C in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
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