This function uses the output from
make_anglers to conduct
a bus-route or traditional access point creel survey of the population of anglers
make_anglers and provide clerk-observed counts of anglers and their effort.
The dataframe returned from
The start time of the clerk.
the end time of the clerk.
the wait time of the clerk.
The sampling probability of the survey. The default is
The mean catch rate for the fishery.
Arguments to be passed to other functions.
Total effort is the sum of the trip lengths from
The total number of anglers is equal to the
nrow() of the
Catch rates are assigned to anglers based upon the Gamma distribution
with a mean of
will be 0.5 (one-half hour). If a value is passed to
end_time - start_time.
start_time=NULL, then a
start_time is generated from the
uniform distribution between
11.5 hours into the fishing day.
end_time = start_time+wait_time
Incomplete trip effort is observed two ways: 1) by counting anglers
that were at the site for the entire time that the surveyor was at the site
and 2) counting anglers that arrived after the surveyor arrived at the site
but remained at the site after the surveyor left. These anglers are counted
and their effort calculated based upon surveyor
Completed trip effort is observed two ways: 1) by interviewing anglers
that left while the surveyor was at the site. The surveyor can determine
effort and catch. 2) by interviewing anglers that both arrived and departed
while the surveyor was on site. When
wait_time is short, these cases are
are rare; however, when
wait_time is long (e.g., all day), then these
cases are much more likely.
Trip lengths of observed trips (both incomplete and complete) are
scaled by the
sampling_prob value. The
sampling_prob is used to estimate
effort and catch.
Steven H. Ranney
Pollock, K. H., C. M. Jones, and T. L. Brown. 1994. Angler survey methods and their applications in fisheries management. American Fisheries Society, Special Publication 25, Bethesda, Maryland.
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library(dplyr) set.seed(256) start_time = .001 #start of fishing day end_time = 12 #end of fishing day mean_catch_rate = 0.1 #this will cause VERY few fish to be caught! make_anglers(100) %>% get_total_values(start_time = start_time, end_time = end_time, mean_catch_rate = mean_catch_rate) start_time = .001 #start of fishing day end_time = 6 #halfway through the fishing day sampling_prob = .5 #this needs to be .5 because we are sampling only 50% of the fishing day mean_catch_rate = 0.1 #this will cause VERY few fish to be caught! make_anglers(100) %>% get_total_values(start_time = start_time, end_time = end_time, sampling_prob = sampling_prob, mean_catch_rate = mean_catch_rate)
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