In data-limited or data-medium situations where long-term, comprehensive catch data does not exist, per-recruit models can be used to determine estimates of optimal fishing mortality. By focusing on yield-per-recruit or spawning stock biomass per recruit, managers can maintain a stock’s population by preserving its reproductive capability. Calculations of lifetime egg production (LEP), also known as egg production per recruit, can be used as reference points for harvest targets. As fishing pressure increases, the stock’s age structure changes, which reduces LEP and the equilibrium egg production (the level of egg production needed to balance fishery mortality). Eventually equilibrium egg production reaches zero and the population collapses. Unfortunately this point is often unknown due to lack of data, larval source-sink dynamics, and environmental variability.
Fractional change in lifetime egg production (FLEP) can be used as an alternative to more data-intensive per-recruit models such as spawning stock biomass per recruit. Length-frequency data from an unfished (or early exploited) population and the current population, along with information on growth and maturity, are used to determine a limit reference point that represents the persistence of a population. The fractional change is calculated as the ratio of LEP between the unfished and current populations. While FLEP analyses help calculate optimal fishing mortality, this method only indicates population trends and correlations, forcing managers to make assumptions about the target stock.
Inputs:
- Length-frequency data from an unfished (or early exploited) population and the current population. Need two samples of the size structure - one in the past and one with current fishing pressure
- Growth and maturity information including: length-egg production relationship; fraction of individuals in the (unexploited or early) fishery that are mature; abundance at length; maturity schedule (mass/fecundity relationship, a & b estimates)
Input Sensitivities:
- Catch data is representative of historic and current fishing influence on size distribution
- Estimation of early LEP as a pseudo-baseline for the fractional LEP calculation places a strong dependence on that first estimate
- Biases/ lack of precision/ accuracy in the estimation of the baseline LEP level will influence the other LEP estimates
- Biases in LEP estimation can be present due to incorrectly specified von Bertalanffy parameters, transient dynamics, and high levels of recruitment variability
Outputs:
- Lifetime Egg Production (LEP)
- Fractional change in Lifetime Egg Production (FLEP) (historic to current)
Assumptions:
- Users must extrapolate optimal harvest levels from population trends and correlations
- Equilibrium in size structure
- Constant annual recruitment