Final Flashcards
Removal method
- only applicable where there is a noticeable decrease in population size as a result of harvesting.
- Each harvest event must have a drop in population size.
- Will not work if only a small number is removed..
- Trying to produce leslie plot – negative slope.
Required for removal method
*a known number of animals removed (=catch) from habitat by trapping (=effort) over a period of time (harvest period)
Catchability (removal method)
- rate at which the trap catch decreases
* Catchability = slope
Removal method will only work if…
a population has been exploited to the point where harvesting at each sample time requires greater & greater catching effort. i.e., the number of fish caught in a net declines after each successive fishing trip at a constant rate dictated by the slope.
How to estimate initial size (removal method)
Estimate the initial size (N) of an exploited population at the end of the harvest by extrapolating to the x-axis
Data required (catch effort method)
1) catch data and effort data.. Catch is the hull and effort is what is used to get hull in. Ex. Effort = hooks, traps or nets catch data is divided by effort data to determine catch per unit effort (CPUE).
2) Accumulated catch = summation of catch for each fishing event.
- Plot CPUE vs. Ki
- Calculate linear regression & extrapolate to the X-axis to determine N ̂… i.e., when CPUE = 0 it represents the exhaustion of the catch
Assumptions (catch effort method
1) The population is closed (i.e., N is constant).
2) Individuals have the same probability of being caught throughout the sampling period
3) An animal can be harvested to the point of near extermination. - need to remove a large population in order to get results
Leslie plot
- A linear plot of CPUE data should reveal a straight line, which indicates the population at zero.
- If the line is not straight then the basic assumptions of this catch-effort method are being violated.
- Check R2 value for fit.
- CPUE vs vertical catch
- Linearity is a very important assumption to be met
Krebbs recommendation (catch effort)
- The CPUE data be visually checked by plotting the same data in the form of a semilog regression = Ricker plot.
- This type of plot may straighten the line and make it possible to assume that the underlying assumptions are not being violated.
**look to see if the linearity is improved. If improved, indicates transformation is necessary and linearity isn’t met. If doesn’t change, then linearity is met (esp with high R^2)
Catch-recovery 10% graph
*Removal methods such as Catch-Effort have poor precision and a large potential for bias, a conservative catch-recovery approach is recommended = 10% rule
- K is carrying capacity and k/2 is where max sustainable yield occurs.
- Bc the fishery often gets a low k/2 – unsustainable. If continue this way, and the catch increases, may not have a recovery and may become endangered. Ex cod off nfl.
*Opposite of this is fishing around k is sustainable and 10% rule means that you removed 10% of k on a similar recovery catch scenario. Catch recovery fits into this scenario bc the catch is the harvest, which is the drawdown and recovery occurs, so the initial population is estimated after the fishery is over.
Problems with aerial sampling
*Relative density
- Counting error
- counting bias
- precision
Counting error and counting bias and low precision are chronic and produce measures of relative density.
Relative density
is a consistent under or over estimation of density (N̂)
Counting error
Observer undercounts some samples and over counts on others, the two cancel each other.
Counting bias
Most samplers tend to consistently undercount.
Bias increases as more demands are placed on the counter (i.e., when increasing numbers of organisms are encountered and/or must be counted quickly).
Precision (aerial sampling)
can be increased with optimal survey designs: stratification and high replication
