Lower ColumbiaCoho Adult Spatial StructureMonitoring Design
Spatial Design
Temporal Design
Response Design
Inference Design
Evaluation Thresholds
References
Spatial Design
The design is similar to that created for Oregon coast coho(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.
Inference is made for Independent Populations. Click here to see the current coho spawner assessment units monitored by.ODFW’s Oregon Adult SalmonidInventory and Sampling (OASIS) project (ODFW monitors only the portions in Oregon). 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 clickhere.
Analytical procedures to calculate metrics:
1) Peak count.
Peak count per mile in a given stream segment (Hi) was calculated as follows:
Hi= Pi/mi
where
Pi= peak count of live and dead adult fish in stream segment I observed on a single visit, and
mi= miles surveyed in stream segment i.
Only adult coho are counted, jacks are excluded. Also excluded are naturally spawning hatchery fish. Survey data were screened to avoid inclusion of sites when significant portions of the run were missed. Only data from sites that were visited throughout the spawnng season and where the interval between successive counts with acceptable visibility (bottoms of riffles were visible) did not exceed ten days were included.
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 (Ni) 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:
where
CuK = number of unmarked (naturally produced) adult coho carcasses in populationK, and
CmK= number of adipose fin-marked ( produced) adult coho carcasses in populationK.
The average total fish per mile (T) spawning in a given set of stream segments was calculated as follows:
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 (Ni) 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.
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:
where
Pi = peak count of live and dead fish in stream segment i, and
mj = miles surveyed in stream segment i.
Inference Design
A minimum density of 4 wild fish/ mile was selected as the threshold for occupancy on the basis of the spawner frequency distributions developed by Talabere and Jones (2001), and by work conducted by Sharr et al. (2000) that suggested that at densities less than this level, the probability of each spawner finding a mate within a section of stream may decline. We believe that this number represents a threshold were spawning is likely to occur. The probability of “finding” a mate is reasonably high because of the behavior of the fish as they move through the reaches and key into rare patches of holding and spawning habitat. The typical spawning stream reach is 1.6 km long and 6m wide and has about 150m2of spawning gravel and 8 deep pools with cover for holding habitat (ODFW Aquatic Inventory and Spawner Survey Project unpublished data). Within this small fraction of total stream area, there is a good probability of a male-female paring (87.5%) although this may be reduced in populations with unequal sex ratios. Approximately 250 sites/ESU were surveyed from 1989 to 1996 and approximately 475 sites/ESU were surveyed from 1997 to 2003. In recent years, about ten percent of the total spawning miles were sampled annually. This design assures comprehensive representation of spawning habitats within the range of available spawning habitat.
Evaluation Thresholds
Metric 1
Percent occupancy (%Occ) is defined as the proportion of successfully-surveyed sites that meet the occupancy threshold.
%Occ = SitesOcc/SitesTotal * 100
Where SitesOcc = Number of successfully-surveyed sites that meet the occupancy threshold
And SitesTotal = Total number of successfully surveyed sites.
Pass – The percentage of sites not occupied by spawning adults or rearing juvenile salmon or steelhead is < the threshold at least six times during a 12-year period and the overall average percentage of sites not occupied during that same time period is < than the threshold.
Fail – The percentage of sites not occupied by spawning adults or rearing juveniles is > the threshold less than six times during a 12-year period or the overall average percentage of sites not occupied during that same time period is > the threshold.
Occupancy thresholds for Oregon Lower Columbia River coho salmon and steelhead populations. Watershed size is from McElhany et al. (2006).
107 Coast stratum steelhead are not listed under ESA.
Metric 2
The second metric uses a statistic that describes the regularity of a spatial point pattern and compares the regularity of the pattern of occupied sites with the regularity of the pattern of the original group of sample sites. The statistic that will be used to describe the regularity of the point pattern is the SVB statistic (Stevens, 2006). To calculate the SVB statistic, a polygon will be drawn around each point that encompasses the area closer to that point than to any other. If the polygons are similar in size and shape, then the distribution is more regular. If the polygons differ in size and shape then the distribution is more clustered. One criterion that is sensitive to both variation in area and shape is the variation of the distance from a point to the boundary of its polygon. If we define a Side as a division between two polygons, a Boundary as a segment of the domain boundary, and a Vertex as the intersection between two Sides or a Side and a Boundary, then the SVB can be approximated by the mean square deviation (MSD) of the distance from a sample point to Sides, Vertices, and Boundaries, relative to a nominal value (such as the MSD for a hexagon with area = [domain area / number of samples]).
To test that occupancy occurs at random over the domain, a pattern of random presence/absence can by simulated a by assigning each of the survey points either 0 (indicating absence) or 1 (indicating presence). By repeating the process multiple times, each time calculating the regularity ratio, a distribution of the SVB statistic can be constructed.
Evaluation Thresholds
In order to pass this metric, the observed regularity ratio must not significantly differ from a random distribution more than six times in any 12-year period.
References
Beidler, W.M., and T.E. Nickelson. (1980). An evaluation of the Oregon Department of Fish andWildlife standard spawning survey system for coho salmon. Oregon Department of Fishand 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.
Sharr, S., C. Melcher, T. Nickelson, P. Lawson, R. Kope, and J. Coon. (2000). 2000 review of Amendment 13 to the Pacific Coast Salmon Plan. Pacific Fisheries Management Council. Portland, Oregon.
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, D.L. (2006). Spatial properties of design-based versus model-based approaches to environmental sampling. 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences.Edited by M. Caetano and M. Painho.pp. 119-125.
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.
Talabere, A. and K. K. Jones. (2001). Pacific Salmon Conservation: Designating Salmon Anchor Habitat Areas, A Process to Set Priorities for Watershed Protection and Restoration. Oregon Department of Fish and Wildlife. Conservation Biology Program. Corvallis, Oregon.
Willis, R.A. (1954). The length of time that silver salmon spent before death on spawninggrounds at Spring Creek, Wilson River in 1951-52. Fish Commission of OregonResearch Briefs5:27-31.