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Explore a structured decision analysis model to determine the ideal stocking level for salmon and trout in Lake Michigan. Analyze past data, predator-prey dynamics, and possible outcomes to guide future management decisions effectively.
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Searching for a good stocking policy for Lake Michigan salmonines Michael L. Jones and Iyob Tsehaye Quantitative Fisheries Center, Fisheries and Wildlife Michigan State University Lake Michigan Decision Analysis - 2012
Decision Analysis Structured, formal method for comparing alternative management actions Main components: Specify objectives Identify management options Assess knowledge and account for uncertainties Use model to forecast possible outcomes • Consider the possible consequences of a decision, rather than just predicting the most likely consequence Lake Michigan Decision Analysis - 2012
The Big Question How many salmon and trout should we stock into Lake Michigan each year? • more stocking leads to greater harvest, and thus benefits - unless… • too much stocking leads to poor feeding conditions and increased mortality, but • too little stocking may lead to negative effects of alewife on other species Lake Michigan Decision Analysis - 2012
How many salmon and trout are out there? • How much do they eat? • How capable are the prey fish of meeting this demand? • What happens to salmon and trout feeding (and survival) when prey numbers are low? What we need to know… Lake Michigan Decision Analysis - 2012
Our approach • Analyze the past • Salmonine abundance • Salmonine consumption • Prey fish production • Supply vs demand • Forecast the future • Simulation model • Data we used • Stocking and harvest • Growth and diet data • Prey fish survey data Lake Michigan Decision Analysis - 2012
What does the past tell us? Lake Michigan Decision Analysis - 2012
How many salmon and trout are out there? • Total salmonine numbers have remained relatively stable since 1990 • Reduced Chinook stocking has been offset by increased wild fish production • More recently, improved survival of older Chinook salmon has also offset reduced stocking Lake Michigan Decision Analysis - 2012
Age-3 Chinook numbers How many salmon and trout are out there? Salmonine abundance Lake Michigan Decision Analysis - 2012
How much do they eat? • Total consumption has remained fairly stable for last decade • Chinook salmon have accounted for more than half of total demand consistently since 1980 • Large alewife accounted for more than 40% of total prey consumed since 1980, except in the late 1980s when small alewife dominated Lake Michigan Decision Analysis - 2012
Consumption by all species of salmon and trout How much do they eat? Consumption by predator type 1 KT = 2.2 million lbs Consumption by prey type Lake Michigan Decision Analysis - 2012
How capable are the prey fish of meeting this demand? • Predation rates on alewife have ranged from 25%-45% per year from the mid-1980’s to present • Predation mortality peaked in mid-1980’s and has approached peak levels again recently • Alewife (and rainbow smelt) recruitment is variable and not strongly related to adult abundance Lake Michigan Decision Analysis - 2012
How capable are the prey fish of meeting this demand? Index of total predation mortality on alewife Lake Michigan Decision Analysis - 2012
How capable are the prey fish of meeting this demand? Stock and recruitment
What happens to salmon and trout feeding when prey numbers are low? • Chinook salmon consumption has declined when alewife abundance declined • Similar, but weaker pattern for lake trout Lake Michigan Decision Analysis - 2012
What happens to salmon and trout feeding when prey numbers are low? Lake Michigan Decision Analysis - 2012
What can we say about the future? Lake Michigan Decision Analysis - 2012
Policy simulation model Accounts for uncertainties: key uncertainties concern prey recruitment (supply) and predator feeding (demand) Management Decisions LMDA Prediction of Outcome Lake Michigan Decision Analysis - 2012 What we Know
Multiple possible futures Alternative relationships that are consistent with the data
Model results • The model forecasts possible future changes in fish populations and harvest, given a stocking policy • There are many possible futures, so we need to look at the range of possible (likely) outcomes • This range tells us what we think is most likely, but also what might happen • Mainly we’re interested in how likely it is that bad things will happen • Here’s how it works… Lake Michigan Decision Analysis - 2012
Generating results: First simulation Average biomass = 243 kT Lake Michigan Decision Analysis - 2012
Generating results First simulation: average alewife biomass = 243 kt Lake Michigan Decision Analysis - 2012
Generating results: Second simulation Average biomass = 52 kT Lake Michigan Decision Analysis - 2012
Generating results Second simulation: average alewife biomass = 52 kt Lake Michigan Decision Analysis - 2012
Generating results … and so on (e.g., results after 15 simulations) Lake Michigan Decision Analysis - 2012
An example result: Status quo policy In 26 of 100 cases alewife biomass was less than 100 kt: BAD In 45 of 100 cases alewife biomass was between 100 and 500 kt: OK Lake Michigan Decision Analysis - 2012