Presentation Abstract
As part of continuing work in Port Gamble, WA a diver-based eelgrass survey was completed to support the application for a Hydraulic Project Approval (HPA), as required by the Washington State Department of Fish and Wildlife (WDFW) for in-water work. The survey was completed following interim guidelines established by WDFW in 2008, although to fit the guidelines to the specific project some methods were modified and approved by WDFW. Collecting statistically robust data proved to be difficult, as shoot density in the eelgrass bed was highly variable. In some areas the variance was so high that power calculations estimated the sample number (n) to be higher than the available number of quadrats. In addition to issues with variance, data were not normally distributed so it is questionable whether parametric statistics should be used on this data. In areas where count data are highly variable and not normally distributed perhaps a more reasonable approach to data analysis is to use a non-parametric resampling method for analysis. This presentation will show the results of a survey completed along an existing wastewater treatment outfall pipe and a reference location, the results of power analysis for the survey, and statistical results comparing the sites using parametric and non-parametric statistics.
Session Title
The Role of Eelgrass Ecosystems in the Salish Sea
Conference Track
Habitat
Conference Name
Salish Sea Ecosystem Conference (2016 : Vancouver, B.C.)
Document Type
Event
Start Date
2016 12:00 AM
End Date
2016 12:00 AM
Location
2016SSEC
Type of Presentation
Poster
Genre/Form
conference proceedings; presentations (communicative events)
Contributing Repository
Digital content made available by University Archives, Heritage Resources, Western Libraries, Western Washington University.
Subjects – Topical (LCSH)
Zostera marina--Monitoring--Washington (State)--Gamble, Port (Bay)
Geographic Coverage
Salish Sea (B.C. and Wash.); Gamble, Port (Wash. : Bay)
Rights
This resource is displayed for educational purposes only and may be subject to U.S. and international copyright laws. For more information about rights or obtaining copies of this resource, please contact University Archives, Heritage Resources, Western Libraries, Western Washington University, Bellingham, WA 98225-9103, USA (360-650-7534; heritage.resources@wwu.edu) and refer to the collection name and identifier. Any materials cited must be attributed to the Salish Sea Ecosystem Conference Records, University Archives, Heritage Resources, Western Libraries, Western Washington University.
Type
Text
Language
English
Format
application/pdf
Included in
Fresh Water Studies Commons, Marine Biology Commons, Natural Resources and Conservation Commons
A Nonparametric Statistical Approach to Analyzing Eelgrass Density Data
2016SSEC
As part of continuing work in Port Gamble, WA a diver-based eelgrass survey was completed to support the application for a Hydraulic Project Approval (HPA), as required by the Washington State Department of Fish and Wildlife (WDFW) for in-water work. The survey was completed following interim guidelines established by WDFW in 2008, although to fit the guidelines to the specific project some methods were modified and approved by WDFW. Collecting statistically robust data proved to be difficult, as shoot density in the eelgrass bed was highly variable. In some areas the variance was so high that power calculations estimated the sample number (n) to be higher than the available number of quadrats. In addition to issues with variance, data were not normally distributed so it is questionable whether parametric statistics should be used on this data. In areas where count data are highly variable and not normally distributed perhaps a more reasonable approach to data analysis is to use a non-parametric resampling method for analysis. This presentation will show the results of a survey completed along an existing wastewater treatment outfall pipe and a reference location, the results of power analysis for the survey, and statistical results comparing the sites using parametric and non-parametric statistics.
