K. R. Bestgen, K. A. Zelasko, and G. C. White. Monitoring ...

lack of convergence. Simulation run results were censored (not a full 1,000 simulations was
achieved because some failed to converge or abundance was estimated at greater than 10X the
simulated level) at some reasonable level of abundance relative to the simulation parameters and
often reduced bias relative to what is reported, but the main point here is that estimating
abundance when population size is small and p’s are low is not advisable because highly biased
estimates can result, sometimes negative but often positive. Increasing number of sampling
passes when population size is 1,000 when p = 0.05 is advisable because 3 sampling passes
resulted in potential average positive bias of nearly 20%. Relatively low average bias resulted
when p’s were 0.10 or greater under all population sizes with 3 or 4 sampling passes, or when p
= 0.05 or higher with population size of 2,500 or 5,000, especially when sampling pass number
was increased from 3 to 4. In general, increasing the number of sampling passes from 3 to 4
reduced bias by 50% or more, regardless of the level of p or population size.
Similar to reducing bias, increased precision of abundance estimates was obtained by
increasing probabilities of capture, increasing sampling passes from 3 to 4, and increasing
population size under consideration (Figure 13). The CV’s were high under all scenarios when p
= 0.02, and remained high when p = 0.05 and population size was 1,000 or 2,500. When
sampling yields p’s per pass of 0.10, estimates of abundance are relatively precise for all
population sizes ranging from 1,000 to 5,000, especially when 4 sampling passes were
employed. In general, addition of a fourth sampling pass was less effective than expected for
increasing precision, when compared to addition of a fourth pass for bias reduction.
The CV’s generated from simulation results are generally consistent with CV’s for
abundance estimates generated by field sampling. For example, CV’s of abundance estimates
(1,600 to 5,200) for razorback suckers in the lower Green River from 2006–2008 were 22 to 37%
with p’s of 0.01 to 0.07 using 3-pass sampling. Those are similar to CV’s for a simulated
population of 2,500 animals with p = 0.05 and three sampling passes, which averaged 29.6%.
Similarly, middle Green River abundance estimates for Colorado pikeminnow from 2000–2003
that ranged from 660 to 1,600 had CV’s of 9 to 18% with p’s of 0.04 to 0.13 using 3-pass
sampling. Those CV’s are similar to those for simulated populations where 3 sampling passes
were conducted with p = 0.10 and population size was 1,000 or 2,500 animals, and resulting
CV’s were 9 and 19% respectively.
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