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Title: Evaluating shrub-associated spatial patterns of soil properties in a shrub-steppe ecosystem using multiple-variable geostatistics

Abstract

Geostatistics are often calculated for a single variable at a time, even though many natural phenomena are functions of several variables. The objective of this work was to demonstrate a nonparametric approach for assessing the spatial characteristics of multiple-variable phenomena. Specifically, we analyzed the spatial characteristics of resource islands in the soil under big sagebrush (Artemisia tridentala Nutt.), a dominant shrub in the intermountain western USA. For our example, we defined resource islands as a function of six soil variables representing concentrations of soil resources, populations of microorganisms, and soil microbial physiological variables. By collectively evaluating the indicator transformations of these individual variables, we created a new data set, termed a multiple-variable indicator transform or MVIT. Alternate MVITs were obtained by varying the selection criteria. Each MVIT was analyzed with variography to characterize spatial continuity, and with indicator kriging to predict the combined probability of their occurrence at unsampled locations in the landscape. Simple graphical analysis and variography demonstrated spatial dependence for all individual soil variables. Maps derived from ordinary kriging of MVITs suggested that the combined probabilities for encountering zones of above-median resources were greatest near big sagebrush. 51 refs., 5 figs., 1 tab.

Authors:
 [1];  [2]; ;  [3]
  1. Washington State Univ., Pullman, WA (United States)
  2. USDA-ARS, Pullman, WA (United States)
  3. Pacific Northwest Lab., Richland, WA (United States)
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
151254
Resource Type:
Journal Article
Journal Name:
Soil Science Society of America Journal
Additional Journal Information:
Journal Volume: 59; Journal Issue: 5; Other Information: PBD: Sep-Oct 1995
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; 55 BIOLOGY AND MEDICINE, BASIC STUDIES; 99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; SOILS; GEOCHEMISTRY; STATISTICS; USES; ECOSYSTEMS; PLANTS; BIOMASS; CALCULATION METHODS

Citation Formats

Halvorson, J J, Smith, J L, Washington State Univ., Pullman, WA, Bolton, H Jr, and Rossi, R E. Evaluating shrub-associated spatial patterns of soil properties in a shrub-steppe ecosystem using multiple-variable geostatistics. United States: N. p., 1995. Web. doi:10.2136/sssaj1995.03615995005900050038x.
Halvorson, J J, Smith, J L, Washington State Univ., Pullman, WA, Bolton, H Jr, & Rossi, R E. Evaluating shrub-associated spatial patterns of soil properties in a shrub-steppe ecosystem using multiple-variable geostatistics. United States. https://doi.org/10.2136/sssaj1995.03615995005900050038x
Halvorson, J J, Smith, J L, Washington State Univ., Pullman, WA, Bolton, H Jr, and Rossi, R E. 1995. "Evaluating shrub-associated spatial patterns of soil properties in a shrub-steppe ecosystem using multiple-variable geostatistics". United States. https://doi.org/10.2136/sssaj1995.03615995005900050038x.
@article{osti_151254,
title = {Evaluating shrub-associated spatial patterns of soil properties in a shrub-steppe ecosystem using multiple-variable geostatistics},
author = {Halvorson, J J and Smith, J L and Washington State Univ., Pullman, WA and Bolton, H Jr and Rossi, R E},
abstractNote = {Geostatistics are often calculated for a single variable at a time, even though many natural phenomena are functions of several variables. The objective of this work was to demonstrate a nonparametric approach for assessing the spatial characteristics of multiple-variable phenomena. Specifically, we analyzed the spatial characteristics of resource islands in the soil under big sagebrush (Artemisia tridentala Nutt.), a dominant shrub in the intermountain western USA. For our example, we defined resource islands as a function of six soil variables representing concentrations of soil resources, populations of microorganisms, and soil microbial physiological variables. By collectively evaluating the indicator transformations of these individual variables, we created a new data set, termed a multiple-variable indicator transform or MVIT. Alternate MVITs were obtained by varying the selection criteria. Each MVIT was analyzed with variography to characterize spatial continuity, and with indicator kriging to predict the combined probability of their occurrence at unsampled locations in the landscape. Simple graphical analysis and variography demonstrated spatial dependence for all individual soil variables. Maps derived from ordinary kriging of MVITs suggested that the combined probabilities for encountering zones of above-median resources were greatest near big sagebrush. 51 refs., 5 figs., 1 tab.},
doi = {10.2136/sssaj1995.03615995005900050038x},
url = {https://www.osti.gov/biblio/151254}, journal = {Soil Science Society of America Journal},
number = 5,
volume = 59,
place = {United States},
year = {Fri Sep 01 00:00:00 EDT 1995},
month = {Fri Sep 01 00:00:00 EDT 1995}
}