Recruitment

      Lecture Outline

    Recruitment

    Surplus production

    Yield-per-recruit models

      Assignments

    Pp. 375 – 401 and 666-669 In Inland Fisheries Management

Recruitment

1)      The addition of new individuals at a particular stage in their life history to a population

a)      Typically when fish first become vulnerable to sampling gear

2)      Recruitment necessary to sustain

a)      Reproductive population

b)      Fishery

3)      Influenced by density dependent processes

a)      Low densities

b)      High densities

4)      Fishes vary greatly in recruitment potential

a)      Elasmobranchs

b)      Lake Sturgeon

c)      Striped bass

5)      Influenced by density independent processes

6)      Predictive models

a)      Ricker Model – recruitment should peak at some mid-level of stock abundance and will decline at high stock abundance due to DD mortality rates

b)      Beverton-Hold model – Recruitment should increase with increasing stock size, but at a constantly smaller rate

7)      Effects of harvest

a)      Growth overfishing – Fishing mortality among young, small fish is too high

b)      Recruitment overfishing – Fishing mortality among adult fish is too high

 

Surplus production

1)      Surplus production – biomass that can be removed by fishing and be fully replaced by reproduction and growth the following year

2)      Assumes fish produce more offspring than are necessary to replenish a stock

Yield-per-recruit Models

1)      Yield or harvested biomass is determined by the intensity of fishing mortality at each given age and the survival and growth that occurs between consecutive ages

2)      Predict the yield/recruit (Y/R) based on:

a)      Age at first harvest

b)      Rate of fishing mortality

Effectiveness of Modeling

1)      Many assumptions are not met

2)      Data may lack precision

3)      Difficulty of calculating certain parameters

4)      Models are still helpful in developing hypotheses and management scenarios in the absence of other information