1 / 36

Mapping Soil-Vegetation-Landscape Relationships Wind River Range, Wyoming

Mapping Soil-Vegetation-Landscape Relationships Wind River Range, Wyoming. Brian McMullen M.S. Soil Science. Overview of Location and Project Objectives Maps and Analysis Future Work for Project. Introduction. Terrestrial Ecosystems Unit Inventory (TEUI)

leadbetter
Download Presentation

Mapping Soil-Vegetation-Landscape Relationships Wind River Range, Wyoming

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Mapping Soil-Vegetation-Landscape Relationships Wind River Range, Wyoming Brian McMullen M.S. Soil Science

  2. Overview of Location and Project • Objectives • Maps and Analysis • Future Work for Project

  3. Introduction • Terrestrial Ecosystems Unit Inventory (TEUI) • United States Forest Service (USFS) • “…management decisions based on scientific understanding of ecosystems on and surrounding National Forest lands” • Comprehensive survey • Soil • Vegetation • Parent Material

  4. Introduction Research Area • Wind River Range – Western WY • Shoshone National Forest, southern portion • Scant soils and vegetation data • Increased management pressures • Higher backcountry use and visitation • Fire ecology • Grazing impacts

  5. Project Overview • 2 field seasons, 253 ecological site descriptions • Wide range of data collected by 2 soil scientists and 2 botanists • Data is first compiled into an Excel Spreadsheet • Data management the most time consuming and ulcer inducing part of project

  6. Project Location Wind River Mountains Logan, UT Image from Google Earth

  7. Continental Divide Image from Google Earth

  8. Shoshone National Forest

  9. Objective 1- Creation of Geodatabase for Plot Data • Compilation of 2004 data completed • 2005 data is ~ 60% complete • 25 columns of data inputs x 253 plots = 6325 cells of data • Coffee consumption is up

  10. Spreadsheet Data

  11. Spreadsheet Data

  12. Spreadsheet Converted to Database File

  13. Database File Converted to Geodatabase, Shapefiles, and Feature Classes

  14. Initial Layers Added to Base Map • Trails • Roads • Water Features

  15. Lots O’ Data Layers

  16. Hard Lesson Learned

  17. What the Hell is Base Saturation? • Base saturation is the amount of the soils exchange sites (negatively charged sites on soil surface, or CEC [Cation Exchange Capacity]) occupied by basic cations • Base cations include Ca, Mg, K, and Na • Higher levels of exchangeable base cations = greater buffering capacity • Higher levels of exchangeable base cations = more fertile soil

  18. Mapping Base Saturation • Spatial variability of Base Saturation (measured by ammonium acetate method at USU Soil Genesis Lab) • Track influence of mafic dikes in Louis Lake area • Feedback between - soil parent material/landforms • soil properties • vegetation

  19. Base Saturation Data

  20. Mafic Dikes of the Louis Lake Pluton

  21. 1st Attempt at Depicting B.S. Trends

  22. Base Saturation Data Nearest Neighbor Algorithm ArcGIS Spatial Analyist

  23. Base Saturation Data Inverse Distance Weighting Algorithm ArcGIS Spatial Analyist

  24. Base Saturation Data Kriging Algorithm ArcGIS Spatial Analyist

  25. Inverse Distance Weighting pH

  26. Inverse Distance Base Saturation %

  27. Clay (%) Distribution by Natural Neighbor Algorithm

  28. Clay (%) Distribution by Inverse Distance Weighting Algorithm

  29. Sampling Points Overlain by Geology Coverage

  30. Moisture and Temperature Mapping • As time permits, I would like to look at and incorporate: • Snotel Data • PRISM Data • Soil Survey moisture and temperature data from the neighboring locales

  31. SNOTEL Locations in the Wind River Range

  32. Examining SNOTEL data and soil temperature moisture relationships will drive me to drink more than just coffee……

More Related