Author
TUGEL, ARLENE - NRCS | |
Herrick, Jeffrey - Jeff | |
Wills, Skye | |
REMMENGA, MARTA - NEW MEXICO STATE UNIV | |
BIGGAM, PETE - USDI - NPS | |
HIPPLE, KARL - NATIONAL SOIL SURVEY CTR |
Submitted to: Geological Society of America Meeting
Publication Type: Abstract Only Publication Acceptance Date: 9/15/2008 Publication Date: 10/5/2008 Citation: Tugel, A.J., Herrick, J.E., Wills, S.A., Remmenga, M., Biggam, P., Hipple, K. 2008. Soil survey and resource inventory guide for dynamic soil properties and soil change [abstract]. Geological Society of America Meeting, 2008 Joint Meeting, October 5-9, 2008, Houston, Texas. 756-2. CDROM. Interpretive Summary: Technical Abstract: Data and information about how soils change are needed by producers, land managers, and decision makers in order to plan for long-term productivity, interpret indicators used in monitoring and assessments, and manage human impacts on soil. In order to meet these needs, the National Cooperative Soil Survey is now including data collection procedures to characterize dynamic soil properties. The new procedures are based on simple conceptual models of management effects on soil, integrated soil and vegetation (where present) data collection, and replicate sampling at multiple scales. A cooperative effort to develop sampling guidelines was initiated in 2004. NRCS, working with the Agricultural Research Service Jornada Experimental Range, National Park Service, Forest Service, and Bureau of Land Management has developed the “Soil Survey and Resource Inventory Guide for Dynamic Soil Properties and Soil Change”. Data collection will be organized within projects to document land use or management effects on extensive, ecologically or economically important, or benchmark soils. Comparison study projects, which are designed to characterize dynamic soil properties for one or more land cover types or management systems, include the following six steps: 1) Project Planning, 2) Sampling Design, 3) Sampling Requirements, 4) Field Work, 5) Data Preparation, and 6) Data Analysis and Interpretation. These steps are described in this poster. |