Operational Plan for the Restoration of Diadromous Fishes to the ...

designs (GRTS), where samples are regularly distributed in space with known
inclusion probabilities. Such samples are compatible with standard statistical
methods (e.g. parametric and non-parametric methods), but statistical methods that
take advantage of inclusion probability may also be used, such as those in the R
package psurvey.analysis. We used the Penobscot Basin USGS NHD High GIS
data as our sampling frame, and developed sampling designs in R. These designs
can be readily edited to accommodate alternative sampling needs. Further,
although we focused only on the Penobscot for this exercise, we will create a statewide
sampling design that integrates the Penobscot sampling plan. This will allow
the same level of statistically rigorous sampling within the Penobscot basin, but also
allow the Penobscot data and all other data within the state-wide sampling plan to be
integrated. A final sampling plan for the Penobscot should be integrated into a
larger DPS-wide plan, and development of the plan should follow the steps outlined
later in this document.
For juvenile survey, we recommend a mix of full population estimates and relative
abundance estimates performed by electrofishing. Furthermore, additional panels
could be constructed to formally include CPUE and snorkel samples.
For redd surveys we recommend developing several index “reaches’ that are
surveyed every year, preferably multiple times per year to ensure the most accurate
counts possible, and a multi-panel GRTS design to provide greater spatial coverage.
Process
The final sampling plan should follow the process outlined in Figure 1. The plan will
be constructed to address the various sampling needs to meet the objectives
defined in the sample design process.
Figure 1. Flowchart of sampling design development
source: http://www.epa.gov/nheerl/arm/designpages/designprocoverview5.htm
PRFP Page 191