Yellow Perch Keeping Fit and Dieting by benbenzhou

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									ZOO 511                                                               Bioenergetics
                                                                                  Updated Kornis 2010




NAME ________________________________________



Introduction: yellow perch
We will start by using the bioenergetics model to understand how water temperature,
diet, and body size influence yellow perch growth rates. Data for this simulation is based
on a yellow perch population in an average northern Wisconsin lake.

Directions: click on “Start”, then “All Programs”, then “Bioen 95”, then “Fish
Bioenergetics” (do not select “Perch”)

Find the BioEn file named “Yellowperch.” When it opens, it should be titled “Yellow Perch
Juvenile”

First, familiarize yourself with the User Input data – temperature, diet, and prey energy
density (a measure of food quality), and the observed growth information

The model was originally run using both beginning and end weights to estimate total
consumption, but for this exercise we‟ll use the total consumption as an input to model the
end weight. Click on the “setup” drop-down menu, then “simulation” and check the box “fit
to consumption”. You will then have to OK each input variable by clicking on “edit”, and
then “ok”.

Now estimate P, the proportion of maximum consumption, by clicking the P button. Then
run the model by clicking the R button. Write down the P and the end weight estimated
by the model. Next, graph the growth rates. Click on the graph icon to the right of the R
button. Note the key tools “”, “remove”, and “cumulative”. The arrow adds a variable,
remove removes one. The top variable on the list will plot on the x-axis. All ensuing
variables will go on the y-axes (both left and right if >2 response variables). We‟ll get to
cumulative in a bit. Plot „Day of year‟ on the x-axis and scroll down to select „specific
growth rate (g/g/day)‟ and hit OK.

Quick note: Day 1 corresponds roughly to May 1st based on the temperatures recorded.

1. What do you notice about the growth rate – is it constant? Why not? Where do peak
growth rates occur? How do peaks and troughs of the growth rates correspond with the
diet data? (hint: add “mean prey energy density” to the plot) How do you think that
temperature and diet interact to shape growth rates? Note the p-value and the end
weight.
ZOO 511                                                              Bioenergetics
                                                                                 Updated Kornis 2010




2. Now, let‟s doctor the data. First, pretend the lake is a bit further north, somewhere in
Ontario, and the average summer temperature is 6 cooler. Change the temperature file
so that each day is 6 cooler and then run the model as you did previously. Keep track of p
and the end weight, and then graph the growth rate. How did making the lake cooler
effect the growth of the perch? Did the pattern of growth change? How would you
interpret the changes in the p value and the end weight?




3. Now suppose this is a southern state‟s lake and the winter temperature is 6 warmer
than northern Wisconsin. Change the temperature file to make each day 6 warmer and
rerun the model. What happens to growth now? What do negative growth rates mean?
The pattern of growth is very different in this warmer scenario – do any of the data play a
role in this? (hint: you can look for patterns by adding other parameters to you plots and
seeing if changes in these parameters correlate visually with the growth pattern)




4. Compare the end weight for each scenario – in which temperature regime did the perch
grow best? What does this say about the consumption for the fish in the real system (i.e.
is it getting enough to eat to maximize growth?). Speculate on why a fish might not grow
optimally even if temperatures would allow good growth.
ZOO 511                                                               Bioenergetics
                                                                                  Updated Kornis 2010




5. Suppose these diet data derived from an older, hence larger, fish. How do you expect
the growth rate of the fish to differ if the fish mass is initially 5 g? Return to the
original data (real temperature data) and change the starting weight to 5 g (click the
“User input parameters” button to change start weight). Compare p, end weight and growth
rates to the modeling run in question 1.




Scenario #1: YOY bluegill survival

Peaceful, placid Lake Blue-plate is a popular spot for sport anglers who want to catch
bluegill, Lepomis macrochirus. You work for the Department of Natural Resources (DNR),
and you are in charge of managing the bluegill sport fishery in Lake Blue-plate. You have
found that one of the most important aspects of maintaining a healthy population of
bluegill is over winter survival of young-of-the-year (YOY) bluegill. The model
"bluegillYOY.run" describes the conditions for YOY bluegill growth in Lake Blue-plate from
May 1st (day 1) to November 1st (day 180).



1. Click the "diet proportions" tab and look at the YOY bluegill's diet. (The values are
proportions (they sum to 1 for each day); dipterans are larvae of flying insects such as
midges.) Describe, in words, how a larval bluegill's diet changes over the course of the
summer. This needn't take more than 2-3 short sentences.




2. Using the "User Input Parameters" tab, change the model so that bluegill grow from
0.25 g to 1.5 g between May and November. Past data show that over winter survival of
YOY bluegill in Lake Blue-plate is poor unless they reach a weight of 1.5 g by November 1st
(Note the model is “fit to end weight” not “fit to consumption”. What must the P-value and
total consumption (in grams) be for a bluegill to reach this size threshold?




3. Plot the cumulative consumption of detritus, zooplankton, and diptera by individual
through time. Add each variable, then highlight it and click the “cumulative” key in the
ZOO 511                                                               Bioenergetics
                                                                                  Updated Kornis 2010




plot window. This gives you the cumulative totals as opposed to values on a per day basis.
What are the approximate totals for each at the end of the simulation? (BE CAREFUL--
note the Y-axis labels!!!!)




4. Plot the specific growth rate (in joules per gram per day) of the bluegill through time.
What explains the slow growth at the beginning? Why do you think it changes on day 15?




Describe (or draw) the general shape of the plot.




What is the approximate peak growth rate, and approximately when does it occur?



5. Fix P at 0.8 for these questions:

What is the final weight (g) of the bluegill at normal temperatures? Will over winter
bluegill survival be good or poor?




In an unusually cold summer (decrease all temperatures 4°C), what is the final weight?
Will over winter bluegill survival be good or poor?




6. Again, plot the specific growth rate of the bluegill (in joules/gram/day). Describe the
plot (when it peaks, where, etc.); it should look different than the plot in #4.
ZOO 511                                                               Bioenergetics
                                                                                  Updated Kornis 2010




On about day 120, you should see a big drop in growth rate. What else about the bluegill's
energetics is changing on day 120? (Hint: look at your User Input data)




One day, you read that climatologists are predicting a summer that is much cooler than
normal. You expect that Lake Blue-plate will be 4°C below normal, as in the previous
simulation. As a manager, you must take steps to prevent high juvenile bluegill mortality.

   7. Using the bioenergetics model, figure out a way to get YOY bluegill to grow to 1.5 g
        by November 1st, despite the poor temperatures. Keep P fixed at 0.8. This will
        take a bit of experimenting with the User Input data. (Think carefully about what
        you can control in nature on a rather limited budget. Is it possible for some
        management decision to cause a switch in fish diets? Can you influence
        temperature? Prey energy content? Prey proportions?) Write a brief description
        of what management actions you would undertake to ensure YOY bluegill survival.
        (Use the back of this page if you need more room).
This is primarily a thought exercise…you may not necessarily be able to model the
management decision you make in Bioenergetics 3.0.
ZOO 511                                                               Bioenergetics
                                                                                   Updated Kornis 2010




Scenario #2 Create and answer a hypothesis using bioenergetics

You have had an opportunity to explore Bioenergetics and you now have a broad
understanding of inputs and outputs. It is now time to take your knowledge of fish diets,
foraging, functional morphology, fish behavior and your scientific curiosity to create a
scenario that you can answer with Bioenergetics 3.0.

Often times, before scientists step into the field to collect data or perform an
experiment they want or need to have an idea of the outcome, so scientists create a
model, such as a bioenergetics model, to indicate how the experiment will likely unfold.
This method of predicting your experimental result and showing whether or not your
experiment would even be valuable can be especially useful in grant writing or in project
proposals.

Brainstorm with your partner(s):
We have base bioenergetics files for juvenile yellow perch and YOY bluegill (both of which
you have already explored), as well as adult perch, cisco, and smallmouth bass. Pick a
species or pairs of species and develop a scenario in which you manipulate one or more
inputs to observe a change in an output that addresses a question.

In the perch case above we investigated the properties of temperature on the growth of a
population of perch. In the YOY bluegill scenario we investigated the impact of
temperature on over winter survival.

Scenarios could be based on competition, predation, match-mismatch with prey, global
warming, stocking, severe winters, drought, or any environmental perturbation. What are
you curious about?

Assignment: Scenario write up
Once you create and work through your scenario you and your partner need to write a
single spaced one-page write-up plus figure(s) and lit cited. The write-up should include the
following:
    - Title
    - Scenario introduction – a short paragraph setting up the scenario (I.e. what is the
        question or manipulation?)
    - Methods – a sentence or two saying you used Bioen 3.0 and what variables you
        manipulated
    - Results – include values in written text and references to your figure(s)
    - Discussion – relate it to the literature. You must have at least four citations or two
        per person. How do your results relate to the literature? Support? Refute?
    - Literature Cited – Use CJFAS format or the format we assigned in for your term
        papers

								
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