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All you can eat

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Defining prey fields & mechanistic limits to food consumption in larval fish IBMs: ... (Blaxter 1962, Pedersen 1984), Pacific hake (Sumida & Moser 1980) Pinfish ... – PowerPoint PPT presentation

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Title: All you can eat


1
All you can eat?
Center for Marine and Atmospheric Research -
University of Hamburg -
Super Size Me!
Defining prey fields mechanistic limits to food
consumption in larval fish IBMs An example for
sprat (Sprattus sprattus) in the North Sea. Ute
Daewel Myron A. Peck, Miriam Dickmann, Wilfried
Kühn, Mike St. John, Corinna Schrum
2
Outline
3
Introduction
  • Spatial and temporal variability in fish vital
    rates depend on
  • abiotic factors (e.g., temperature, advective
    velocity, turbulence, light level)
  • biotic factors (e.g., prey size and
    availability)

Prey field generation Observed-Modelled
4
Development of Mechanistic IBM Foraging and
Growth Subroutines
FEEDING LARVAE
Light?
F(prey type,prey density)
5
Observed prey fields
Video plankton recorder
Advantages Size- species-resolved prey fields
information about patchiness Disadvantages s
napshot in time and space
6
Model-generated prey fields
Ecosystem model ECOSMO (Schrum et al. 2005) 1.
April 31. September 1990
7
Prey fields
Zooplankton biomass mgC/m³ ? ind./m³
Prey length range 150-1000 µm ? Increment 10 µm
8
Sensitivity analysis (Variability of prey size
distribution)
9
Spatial variability (monthly mean 1993)
10
Part 2
  • Spatial and temporal variability in fish vital
    rates depend on
  • abiotic factors (e.g., temperature, advective
    velocity, turbulence, light level)
  • biotic factors (e.g., prey size and
    availability)

Strategies to handle overfeeding in complex
IBMs
11
Results from IBM Sensitivity analysis
(Individual Parameter Pertubation)
Parameters tested
a angle of visual acuity CS capture
success HT handling time ss swimming speed
Cmax maximum consumption
Rs standard metabolism k activity
multiplier SDA specific dynamic action ae
assimilation efficiency
12
Limit to prevent over-feeding within models
Approach 1 GCmax Maximum Consumption
(Cmax) Werner et al. 1996, Letcher et al. 1996,
Daewel et al. Submitted Maximum Growth
(Gmax) Hinrichsen et al. 2002 Fiksen and
Folkford 1999
Approach 2 GER Gut Content Evacuation Lough
et al. 2005
Approach 3 AE Assimilation Efficiency Reglero
2003
13
Approach 1 GCmax - Non-mechanistic limit to
prevent over-feeding
14
Approach 1 GCmax - Cmax from bioenergetic
balance with known growth rates
CmaxA GR (RR RSDA RA)
G estimates (from field otoliths)
15
Approach 2 GER - Mechanistic limitation I gut
evacuation rate
16
Approach 3 AE - Mechanistic limitation
(assimilation efficiency)
Assimilation efficiency F (larval length,
relative ingestion, temperature)
17
Results (simulated consumption and growth)
T15C Zoopl. Biomass100 mgC/m³
104
103
102
100
Food consumption rate (mg d-1)
10
1.0
0.1
4
6
8
10
12
14
16
18
20
22
larval length (mm)
18
Prey patchiness
Growth at 15 mm SL
GCmax
GER
AE
19
Prey patchiness
  • Thin layer of zooplankton
  • depth changes with time

Holiday et al. thin layers program
20
Prey patchiness
  • Super Tool Components
  • Remoted operated vehicle (ROV)
  • Sensors for measuring
  • conductivity, temperature, pressure
  • flourescence
  • light
  • turbidity
  • oxygen
  • current
  • primary production
  • Most importantly for furthering IBM modeling,
    camera system for resolution of
  • Zooplankton species distributions
  • patchiness
  • Species interactions

21
Conclusions and Recommendations
  • Summary
  • Part 1
  • Foraging and growth IBM subroutines (larval
    sprat, T, prey)
  • VPR prey fields ? resolving patchiness, species
    and size distribution
  • NPZD-derived prey fields ? continuous, long-term,
    large spatial scales
  • Model sensitivity I ? size spectrum, small prey
    thresholds
  • Part 2
  • Comparison of 3 approaches employed to
    prevent over-feeding
  • Assimilation efficiency method ? patchy
    prey environments

Recommendations IBMs with complex foraging
subroutines should strive to incorporate
realistic prey fields (e.g., VPR - OPC - ROV)
that resolve prey patchiness.
These IBMs should also employ physiologically-bas
ed limits to energy assimilation.
Using NPZD model estimates to generate prey
fields has the advantage of incorporating
climate-driven changes in prey abundance and
distribution.
Other (stage-based) prey field model approaches
are also being advanced.
22
Thank you!
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