Detailed Research Information

Detailed project information for
Study Plan Number 02103

Branch : Aquatic Ecology Branch

Study Plan Number : 02103

Study Title : GIS-Based Adaptive Sampling for Early-Detection Monitoring of Invasive Species in National Parks: Incorporating Habitat Models and Incidental Reports into Sample Selection

Starting Date : 07/01/2005

Completion Date : 03/31/2009

Principal Investigator(s) : Smith, Dave R.; Young, John A.; & van manen, Frank

Primary PI : Smith, Dave R.

Telephone Number : (304) 724-4467

Email Address : drsmith@usgs.gov

SIS Number :

Primary Program Element :

Second Program Element :

Status : Active

Abstract : BACKGROUND
We propose to develop and evaluate a GIS-based adaptive sampling design for early-detection of invasive species in National Parks by using rare plant species as a surrogate. Rare plants are an appropriate surrogate to address early detection of invasive species because in both instances the species are relatively difficult to find and population abundance is difficult to estimate precisely. Data on plant distributions in Shenandoah National Park, along with fully developed habitat models and GIS coverages, will provide a reliable basis for the simulation study (Young et al. 2003). Various adaptive and conventional sampling designs will be constructed that make use of predictions from habitat models and incidental reports. Performance of the designs in terms of ability to identify hot spots, estimator precision, and yield of rare individuals and species will be compared to a baseline design (e.g., conventional simple random sampling) to identify designs with the greatest efficiency and yield. After establishing through the simulation study that a GIS-based adaptive sampling design is effective for early-detection monitoring, we propose additional ‘out-year’ phases of work including field trials focusing on particular invasive species and implementation of a monitoring program.
OBJECTIVES
1) Develop a GIS-based adaptive sampling design that incorporates information on habitat value and incidental reports for early-detection monitoring of invasive species.

2) Evaluate the performance of GIS-based adaptive sampling designs relative to other adaptive and conventional sampling designs by using rare plant species as a surrogate.

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Branch :	Aquatic Ecology Branch
Study Plan Number :	02103
Study Title :	GIS-Based Adaptive Sampling for Early-Detection Monitoring of Invasive Species in National Parks: Incorporating Habitat Models and Incidental Reports into Sample Selection
Starting Date :	07/01/2005
Completion Date :	03/31/2009
Principal Investigator(s) :	Smith, Dave R.; Young, John A.; & van manen, Frank
Primary PI :	Smith, Dave R.
Telephone Number :	(304) 724-4467
Email Address :	drsmith@usgs.gov
SIS Number :
Primary Program Element :
Second Program Element :
Status :	Active
Abstract :	BACKGROUND We propose to develop and evaluate a GIS-based adaptive sampling design for early-detection of invasive species in National Parks by using rare plant species as a surrogate. Rare plants are an appropriate surrogate to address early detection of invasive species because in both instances the species are relatively difficult to find and population abundance is difficult to estimate precisely. Data on plant distributions in Shenandoah National Park, along with fully developed habitat models and GIS coverages, will provide a reliable basis for the simulation study (Young et al. 2003). Various adaptive and conventional sampling designs will be constructed that make use of predictions from habitat models and incidental reports. Performance of the designs in terms of ability to identify hot spots, estimator precision, and yield of rare individuals and species will be compared to a baseline design (e.g., conventional simple random sampling) to identify designs with the greatest efficiency and yield. After establishing through the simulation study that a GIS-based adaptive sampling design is effective for early-detection monitoring, we propose additional ‘out-year’ phases of work including field trials focusing on particular invasive species and implementation of a monitoring program. OBJECTIVES 1) Develop a GIS-based adaptive sampling design that incorporates information on habitat value and incidental reports for early-detection monitoring of invasive species. 2) Evaluate the performance of GIS-based adaptive sampling designs relative to other adaptive and conventional sampling designs by using rare plant species as a surrogate.
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U.S. Department of the Interior \|\| U.S. Geological Survey 11700 Leetown Road, Kearneysville, WV 25430, USA URL: http://www.lsc.usgs.gov Maintainer: lsc_webmaster@usgs.gov Last Modified: October 21, 2002 dwn Privacy Policy and Disclaimers \|\| FOIA \|\| Accessibility