Coast Coho Adult Abundance Monitoring Design
Spatial Design
Temporal Design
Response Design
Inference Design
Evaluation Thresholds
References
Spatial Design
The design is described in detail in Stevens (2002). A GIS coverage of streams was used as a frame for
the population. The coverage was based on USGS 1:25,000 topographic maps, modified by ODFW to
correspond to the target population of streams for each population. The goal was to provide annual
estimates for each of the assessment units with a 95% confidence interval of +30%. To do this, a
minimum of 30 sites or 30% (whichever comes first) of the available spawning habitat for coho salmon
was sampled in each of the assessment units.
Independent populations are the most fine-scale unit at which inference is made, with inference also
made for Strata and the ESU. Click here to see the current coho spawner assessment units monitored
by.ODFW’s Oregon Adult Salmonid Inventory and Sampling (OASIS) project. Generalized Random
Tessellation Stratified designs (GRTS) achieve a spatially-balanced random point distribution (Stevens,
1997; Stevens & Olsen, 1999; Stevens & Olsen, 2003; Stevens and Olsen, 2004) and this approach was
used.
Temporal Design
A rotating panel design was used to accommodate the need for repeat visits while continuing to expand
the scope of the sample every year. Sets of panels are visited on different cycles. The design consists of
40 panels, with one panel defining sites visited every year, 3 panels defining sites visited on a 3-year
cycle, 9 panels defining sites visited on a 9-year cycle, and 27 panels defining sites visited on a 27-year
cycle. An equal number of sites were allotted to each panel. The three-year cycle parallels the coho life
cycle.
Response Design
Spawning ground surveys are conducted from October through January. Visits at a site are conducted at
least once every 10 days throughout the course of the spawning survey season. Surveyors either walk
upstream or boat downstream, depending of the size of the stream being surveyed. On average, sample
sites are roughly 1 mile long. The exact length of samples sites is determined by proximity to landmarks
(such as bridge crossings and tributary junctions).The surveyors count redds, live and dead fish (by
species), and sample carcasses for gender, length (mm MEPS), scales, fin clips and tags. For a full
description of the field methods used to conduct the spawning surveys click here.
Analytical procedures to calculate metrics:
1) Area-Under-the-Curve estimates of site abundance.
Coho salmon can be found spawning in Oregon coastal streams over a period of three or more months.
Because it is too costly and impractical to conduct counts every day of the number of adult coho
spawning at all randomly selected spawning survey sites during this extended time period, it is necessary
to employ statistical techniques to expand periodic counts (i.e. those conducted once every 10 day or
less throughout the spawning season) to an estimate of the total number of coho spawning at the site.
The observed numbers of live fish are plotted over time. An additional point with a value of zero is added
seven days before or after the first and last observations to close the curve. An integral is used to
calculate the area under the curve to estimate fish days. This statistic is then divided by an estimate of
the average length of time coho spend on the spawning grounds to estimate the number of fish.
An average spawning life (D) of 11.3 days was used for coho salmon spawning in survey streams (Willis
1952, Beidler and Nickelson 1980, and Perrin and Irvine 1990). Survey data were screened to avoid
making spawning density estimates for stream segments where few data points were available or
significant portions of the run were missed. These qualification criteria pertained to: (1) the duration of
the spawnng season over which counts needed to be made, (2) the number of counts that needed to be
conducted for each survey and (3) the number of times that the interval between successive counts could
exceed ten days. Additionally, water visibility had to be acceptable (bottoms of riffles were visible) over
the majority of the survey area. AUC estimates were not made for surveys that did not meet these
criteria. If the first or last count in the index area was greater than zero, a count of zero was assumed to
occur seven days before or after the actual count.
2) The percentage of spawning fish that are of natural origin.
During visits to the site surveyors examine carcasses to determine whether they are hatchery-origin fish
(adipose fin has been clipped) or if they are natural origin fish. Surveyors also attempt to see marks on
live fish and record these as well. If there are insufficient numbers of carcass examinations, live fish
observations are added in. The number of marked and unmarked fish is totaled by population to
calculate the proportion of total spawning fish that is made up of natural-origin fish.
The adult peak count per mile (Hi) and total number of adult coho salmon per mile (N i) in a given stream
segment are adjusted to eliminate the contribution of hatchery fish using the following equations:
Hi = (Hi)( PSk)
and
Ni = (Ni)( PSk)
where
PSk = estimated proportion of total adult coho salmon spawners in population k that originated from
natural production.
Values of PSk were estimated from fin-mark recoveries. Adipose fin-marking occurred for all adult coho
production at coastal facilities, thus the ratio of naturally produced coho could be calculated by dividing
the number of unmarked coho carcasses by the total number of coho carcasses encountered. Fin-mark
ratios were calculated for each population, and data were pooled within each Stratum. Only recoveries
on random surveys were used. Values were calculated as follows:
PS K  CuK CuK  CmK 
where
CuK = number of unmarked (naturally produced) adult coho carcasses in population K, and
CmK = number of adipose fin-marked ( produced) adult coho carcasses in population K.
The average total fish per mile (T) spawning in a given set of stream segments was calculated
as follows:
n
T   Ni n
i 1
where
n = number of stream segments surveyed, and
Ni = estimated total number of spawning fish per mile in stream segment i (see below).
The estimated spawning density (total fish per mile) for a given stream segment (N i) was calculated as
follows:
Ni = (Oi)/(mi)
Where
Oi = The total number of adult coho salmon spawning in a given stream segment (Oi) throughout the
course of the spawning season and
mj = miles of accessible coho salmon spawning habitat in reach segment j.
 a

   C hi t hi  
h 1

Oi   


D




where
a = number of periods,
Chi = mean count in period h,
thi = number of days in period h, and
D = average spawning life (days) of coho salmon in survey segments.
Peak count per mile in a given stream segment (Hi) was calculated as follows:
H i  Pi / mi
where
Pi = peak count of live and dead fish in stream segment i, and
mj = miles surveyed in stream segment i.
Inference Design
The recommended estimator is the Horvitz-Thompson or π-estimator. Briefly, the estimator weights the
observation collected at si by the reciprocal of the inclusion density function π(si). Annual status estimates
are obtained from all sites visited in that year. The design selects points on streams. Suppose point si
falls on a stream segment with length li. The observation collected represents an aggregate over the
entire length of the segment. Thus, if the observation is spawner count, then the entire segment is
examined for spawners, and all spawners in the segment are counted. Let yi be the aggregated
observation. Then an estimator of the total number of spawners over the entire stream network is
where n is the number of samples. Moreover, within an assessment unit, π(s) is constant, so, letting
, the estimator becomes
.
Refer to epa.gov/nheerl/arm for R scripts (spsurvey library; function CDF.compute) to calculate
population abundance estimates and confidence intervals.
The proportion of natural-origin fish found on the spawning grounds calculated by population is multiplied
by the total estimate to determine the estimate of natural-origin (wild) fish.
There are occasions where estimates from non-statistical designs for isolated regions are added to this
probability estimate. For example, in the Lakes stratum the estimate is made by expanding from a
convenience sample. Where this occurs it is not possible to calculate confidence intervals for the nonstatistical design. Likewise, when the non-statistical estimate is added to statistical estimates to obtain
an estimate for the entire ESU, the confidence for the ESU estimate is unknown since the confidence is
unknown for portions of the estimate.
Evaluation Thresholds
In order to pass this criterion, the observed spawner abundance must be > the marine survival-specific
escapement target (see table below) at least six times in any 12-year period.
Escapement goals under different marine survival conditions (average survival rate in parentheses) for
independent populations comprising the Oregon Coast coho ESU.
References
Beidler, W.M., and T.E. Nickelson. (1980). An evaluation of the Oregon Department of Fish and Wildlife standard
spawning survey system for coho salmon. Oregon Department of Fish and Wildlife, Information Reports
(Fish) 80-9, Portland.
Perrin, C.J., and J.R. Irvine. (1990). A review of survey life estimates as they apply to the area-under-the-curve
method for estimating the spawning escapement of pacific salmon. Canadian Technical Report of
Fisheries and Aquatic Sciences 1733.
Stevens, D.L., Jr. (1997). .Variable density grid-based sampling designs for continuous spatial populations’.
Environmetrics 8: 167-195.
Stevens, D.L. (2002). Sampling design and statistical analysis methods for integrated biological and physical
monitoring of Oregon streams. OPSW-ODFW-2002-07, Oregon Department of Fish and Wildlife,
Portland, Oregon.
Stevens, Jr., D. L. and A. R. Olsen. (1999). .Spatially Restricted Surveys Over Time for Aquatic Resources.
Journal of Agricultural, Biological, and Environmental Statistics 4:415-428.
Stevens, Jr., D. L. and A. R. Olsen. (2004). .Spatially Balanced Sampling of Natural Resources. Journal of the
American Statistical Association 99:262-278.
Stevens, Jr. D.L., and N.S. Urquhart. (2000). Response Designs and Support Regions in Sampling Continuous
Domains. Environmetrics 11:13-41.
Stevens, Jr., D.L., and A. R. Olsen. (2003). .Variance Estimation for Spatially Balanced Samples of Environmental
Resources. Environmetrics 14:593-610.
Willis, R.A. (1954). The length of time that silver salmon spent before death on spawning grounds at Spring Creek,
Wilson River in 1951-52. Fish Commission of Oregon Research Briefs 5:27-31.