•Intensive aquaculture can
produce yields that are
orders of magnitude
beyond natural
ecosystems
How to maximize energy flow to fish
Increased nutrient loading—fertilization + ammonia and anoxia tolerant species
Shortening the food chain—primary consumers (eg carps, tilapia or mullets)
Don’t rely on natural recruitment and managing the life cycle—stocking/hatcheries
Increasing consumption efficiency—small pens intensive feeding
Increased assimilation efficiency—feeding with easy to digest food pellets
Increased production efficiency—low activity species that don’t mind crowding,
, highly turbid water
Lepeophtheirus salmonis
Many aquaculture proponents
argue that aquaculture reduces
harvesting pressure on wild
fisheries.
Salmonid aquaculture not very trophically efficient,
food pellets made from by-catch of wild species
Major water quality issues—nutrient pollution
from cages, anti-fouling paint, antibiotics, habitat
destruction
Transmit diseases to wild salmonids—bacteria,
viruses, protozoans, fungi, “fish lice” –parasitic
copepods and other Crustacea
Genetic problems when domestic escapees
compete with or interbreed with wild fish
Argulus
Rivers support more fish biomass than lakes for the same TP Level? Why?
Fish community biomass kg ● ha-1
1000
Rivers
100
10
Lakes
1
1
10
100
Total Phosphorus µg ●
1000
L-1
Log B = 0.94+ 0.52 (± 0.09) Log TP -0.18 (± 0.05) L/R, RMS=0.27, R2=0.71
Zooplankton abundance in reservoirs depends on the physical regime.
0.70
Zooplankton, Dry weight (mg/L)
0.60
0.50
MRRR
StMR
Keho
0.40
0.30
CHIN
PC
0.20
McGR
0.10
WTTN
OMRD
0.00
50
100
150
Water residence time (days)
200
250
Summarizing concepts on Secondary production
•The organic matter produced by primary producers (NPP) is used by
a web of consumers
•NPP is used directly by primary consumers (herbivores and detritivores), which are in
turn consumed by carnivores.
•Measurement of 2o Production is done by estimating the rate of growth of individuals
and multiplying by the number of individuals per unit area in the cohort (age or size group).
•The efficiency of secondary production ranges from 5-20% (Avg 10%)
at each trophic level.
•Efficiency depends on several factors--palatability, digestibility, energy requirements
for feeding (activity costs)(eg homeotherms vs poikilotherms , other limiting factors
eg water, and nutrient quality of food.
•Trophic efficiency can be represented as the product of CE*AE*PE, each of which
is dependent on one or more of the above factors.
•The yields of many important fisheries depends on a combination of NPP, the
length ofthe food chain leading to the fish being harvested, and the efficiency
of each step.
•Many of the species that we harvest or very high in the food chain, so a great deal
of NPP is required to support them.
•Lakes have zonation structured by physical forces such as light, wind and waves.
•different zones in the lake had different types of plants and animals
•Zones in a river system are less
distinct
•But they are functionally very
important
The River Continuum Concept
Physical forces change gradually along a river
•Elevation ↓
•Slope ↓
•Temperature and nutrients ↑
•Drainage area and discharge ↑
•Width of channel and floodplain ↑
•Mean velocity ↑
•Mean depth ↑
•Turbidity ↑
•Sediments, erosional, alluvial, to depositional
•Shading ↓
•Periphyton, macrophytes ↑, then ↓
•Phytoplankton and zooplankton ↑
•Coarse detritus input highest upstream
•Fine detritus accumulates downstream
•Benthic invertebrate community changes
shredders, grazers, collectors
•Fish community changes
•Cold water to warm water species
http://www.d.umn.edu/~seawww/depth/rivers/art/figure1_4.jpg
Allochthonous input—Detritus processing
•Dead plant biomass breaks down slowly
and their nutrients can remain tied up in as
organic detritus for long periods of time
•Primary production in many ecosystems
depends more on its recycling rate ie mainly
decomposition of plant detritus, than on
loading rates
•Aquatic plants break down more rapidly
than terrestrial plants, and woody plants are
very slow to decompose because they
contain lignin, which most bacteria and fungi
can’t digest.
Leaf processing
•Wetting and breadown of cuticle
•Leaching of soluble components (DOM)
•Colonization by bacteria and fungi
•Increase in protein content
•Colonization by invertebrates
•Enhances microbial action
•Breakdown into small fragments
Invertebrate detritiivores find
leaves much more to their
liking after they have been
colonized by bacteria and
fungi
Detritus processing in a stream
Shredders enhance
microbial action
(bacteria & fungi)
•convert CPOM to FPOM
•Food for microdetritivores
Processing of FPOM by microdetritivores
Shredders-macrodetritivores
collectors-microdetritivores
Filter-feeders, deposit-feeders
Litter bag experiments have been used to study decomposition of detritus
•Nutrient content of the
detritus, especially N
greatly increases
decomposition rate,
•as does increased
temperature
•and mesh size
100 %
Weight
remaining %
Larger invertebrates get
into the litter bags if the
mesh is coarse
0.5 mm mesh
2 mm mesh
10
20
days
30
The interplay between the autochothonous and the allochtonous food chain
Allochthonous input
Autochthonous input
The River Discontinuum: Dams and wiers
Stream Fragmentation, A wier blocking fish movement
a hanging culvert can block fish movement
http://www.cee.mtu.edu/~dwatkins/images/aqua3pics/hatchery-weir.jpg
http://www.nzfreshwater.org/thumbnails/culvert.jpg
Dams/Reservoirs interrupt the river continuum
•create entirely new habitats
Fisheries Management using a population model
dB
 rB  (b  m) B
dt
r is called the intrinsic rate of increase
b is the per capita birth rate, m is per capita death rate
Bt  B 0e ( b  m )t or B 0e rt
This is called exponentia l growth, time is continuous
Bt  B 0t , where   1  r ,
This is called geometric growth, time is discrete
when t steps become very small
1  r   e r
so discrete time approaches continuous time
Nt
ln
 (b  m)t
N0
Exponential
Time
b<m
b=m
b>m
Density dependent birth and death
Per capita
birth,death
When B  K
b=b0-b1B
m=m0+m1B
b0
Slope=b1
m0
Slope=m1
dB
0
dt
(b  m)
K is called the
carrying capacity
B
K
Biomass
Nt
ln
 rt
N0
Since b and m are equal when B  K
and
b  b0  b1B
m  m0  m1B
then
r0
K
m1  b1
dB
 rB  (b  m) B,
dt
dB
 (b0  b1B   m0  m1B ) B
dt
1 dB
 (r 0  b1  m1B)
B dt




b
1

m
1
1 dB
r0




 r 0 1 
B  , since K 


m1  b1
B dt
r
0


1 dB
 B
 r 0 1  
B dt
 K
•per capita rate of
increase slows down
linearly as the biomass
increases and reaches 0
when the carrying
capacity (K) is reached.
1 dB
 B
 r 0 1  
B dt
 K
Is called the logistic equation
1 dB
B dt
per capita rate of increase
reaches an upper limit of
r0 as B approaches 0
r0
slope 
K
It becomes negative
when B>K
B
K
dB
 B
 r 0 B 1  
dt
 K
r0 2
 r0B  B
K
dB
dt
K/2
K
dB
When B  0,
0
dt
dB
When B  K ,
0
dt
K dB
When B  ,
?
2 dt
B
dB
 B
 r 0 B 1  
dt
 K
r0 2
 r0B  B
K
dB
dt
dB
When B  0,
0
dt
dB
When B  K ,
0
dt
K dB r 0 K
When B  ,

2 dt
4
r0K
4
K/2
K
B
What would happen to a population at K/2 subjected to a harvest rate of
dB
dt
r0K
4
C
K/2
r0K
4
K
B
is called the Maximum Sustainable Yield (MSY)
r0K
4
The logistic model
dB
 B
 r 0 B 1  
dt
 K
dB
dt
r0K
4
*
C
K/2
K
B
An operational example
1.2
1
A lake that hasn’t been fished
for 20 yr is opened for fishing
and annual creel surveys
show that CPUE is declining
rapidly
0.8
CPUE
Kg/hr
0.6
0.4
0.2
0
0
5
10
15
20
25
3000
2500
•After a 9-yr moratorium the
population has gradually
bounced back, and the fishery
is opened again with more
restrictive limits
2000
Catch
Kg/yr
•The estimated total catch
varies from year to year but
the trend rapidly becomes
apparent and the lake is
closed
1500
1000
500
0
0
5
10
15
Year
20
25
•After signs of tapering
off limits are tightened
even further.
1.2
1
How can such a population
be managed with the logistic
model?
We don’t know B, K or r0
0.8
CPUE
Kg/hr
0.6
0.4
0.2
0
0
5
10
15
20
25
3000
We can also assume that the
population is at K to start with
2500
2000
Catch
Kg/yr
We can assume that CPUE
is a linear function of
Biomass (eg B=q*CPUE
Where q is called the
“catchability” factor
1500
1000
500
0
0
5
10
15
Year
20
25
•The catch (C) in the first year was 1020 kg, at the rate of 1.0 kg/fisherman hr.
•The following year the CPUE went down to 0.9 kg/fisherman hr.
•Assuming that the population was at its K, and that the CPUE reflects the
biomass linearly, B=q *CPUE, then dB/dt at K will be 0, and the entire catch will
be subtracted from the biomass present.
•That is we assume that there will be no significant recruitment or growth
response to compensate for thinning within the first season
•The response to the first year’s thinning will be reflected in the next year’s
catch data
•assume the change in CPUE reflects the change in B,
(D CPUE)/CPUE = (D B)/B, 0.1/1=1000/K. Therefore K =10,000 kg
•And CPUE =q B, that is 1.0 kg/hr =q * 10,000 kg,
• so q =1kg/hr/10000 kg = 0.0001kg/hr/kg
•The next year the catch rises to 1050 kg, and the CPUE falls to 0.83 kg/hr.
This catch appears to be unsustainable at this B level, but how much would
have been sustainable?
•The next year the catch rises to 1050 kg, and the CPUE falls to 0.83 kg/hr.
•This catch appears to be unsustainable at this B level, but how much would have
been sustainable?
•Using the catchability estimate q we can translate the drop in CPUE and estimate
that the biomass dropped from 9000 to 8300 kg (a drop of 700), and reason that if a
catch of 1050 caused a drop of 700, then a catch of 350 would have been
sustainable at that level of biomass.
•We can then repeat this for every year, including the years where the fishery is
closed
•CPUE can still be estimated from catch and release fishing if the fishery is closed.
•In this way each year’s catch combined with the change that takes place in CPUE
the following year can allow you to estimate the sustainable catch for that year
3000
Actual catches in kg/yr
Estimates of
sustainable catch
2500
By comparing the catch
for each year to the
change in biomass
(estimated from change in
CPUE) we can estimate
the catch that would have
been sustainable each
year
2000
Catch
Kg/yr 1500
1000
500
0
0
5
10
15
20
25
For the first 10 yr catches
were unsustainably high
and the population
crashed,
1.2
1
0.8
CPUE
0.6
Kg/hr
After the new limits were
put in they tended to
oscillate around the
estimated catch.
0.4
0.2
0
0
5
10
15
20
25
Fit to the logistic curve from the lake time series
dB/dt
1200
MSY
1000
(r0K)/4=990
800
600
400
200
K/2 = 5000
0
-200
0
2000
4000
6000
Biomass
If (r0K)/4 = 990 kg/yr and K=10000 kg,
then r0=0.39 kg*kg-1yr-1
8000
10000
12000
Suppose we have a lake with a population of 10,000 kg of pike where fishing
has not been allowed for at least 20 years.
Fishing is then opened up for several years and the population is knocked back
to 5,000 kg. Assume that growth follows the logistic curve.
(a) What would the biomass be after 10 yr if r0 were 0.2 kg/kg/yr
(b) If after closure it recovers to 9,800 kg in 10 years. Find r0?
K
Bt 
1  e  r 0 ( t i )
since the population was not pushed back
past the inflection point ( K/ 2), we don' t
need to worry about i and let it  0.
10000

 8,807
 0.2 (10)
1 e
K
1  e  r 0 ( t i )
Bt
1

c
 r 0 ( t i )
K 1 e
1  c 
 ln 
c 

r0 
t
1  0.98 
 ln 
0.98 

r0 
 0.4kg / kg / yr
10
Bt 
(c) What should be the maximum sustainable yield of this fishery?
(d) If the population were reduced to 2,000 kg, would a quota of 500 kg/yr be
sustainable?, 1000kg?
r0K
MSY 
4
0.4kg  kg 1 yr 1  10,000kg

4
 1,000kg / yr
dB
 B
 r 0 B 1  
dt
 K
 2,000kg 
 0.4kg  kg 1 yr 1  2,000kg 1 

10
,
000
kg


 800  0.8
 640kg / yr
Suppose we have a lake with a population of 10,000 kg of pike where fishing
has not been allowed for at least 20 years.
Fishing is then opened up for several years and the population is knocked back
to 5,000 kg. Assume that growth follows the logistic curve.
Over what range of biomass would a yield of 600 kg/yr be sustainable without
causing a reduction in biomass?
dB
 B
 r 0 B 1  
dt
 K
B 

 0.4 B 1 
  600kg / yr
10
,
000


 4000 B  0.4 B 2  6000000kg / yr
 0.4 B 2  4,000 B  6000000  0
 b  b 2  4ac

2a
 4000  4000 2  4( 0.4  6,000,000 

2  ( 0.4 
B  1837 and B  8162
1837  B  8162
Constant Quota fishing at levels approaching the MSY shortens the biomass
range the population will recover, and the likelihood of entering the danger zone
increases. Once the danger zone is entered fishing must stop or be severely
curtailed
dB
dt
Danger zone
Stable biomass range
r0K
4
Catch rate
K/2
r0K
4
K
Maximum Sustainable Yield (MSY)
B
The red zone is much bigger if the curve is strongly skewed right
Solutions that are being considered by fish managers
What if we consider a fishery based on constant effort rather than constant quota
The catch isn’t as great but the likelihood of entering the red zone is lower
dB
dt
Catch = qB
Slope=q
r0K
4
Stable range
K/2
C
K
B
Foodweb relationships between fish predators and prey
Bottom up
•Richer systems have higher productivity at all trophic levels
•Enrichment usually increases the biomass of the top trophic level in the web.
Top down
•Predators usually reduce the biomass of their prey
•And cause changes in the structure of prey communities
•Lake Michigan example
Bottom-up Fish biomass dependent on nutrient loading
Reductions in fish biomass usually accompany reductions in nutrient loading
•Intensive aquaculture can
produce yields that are
orders of magnitude
beyond natural
ecosystems
How to maximize energy flow to fish
Increased nutrient loading—fertilization + ammonia and anoxia tolerant species
Shortening the food chain—primary consumers (eg carps, tilapia or mullets)
Don’t rely on natural recruitment and managing the life cycle--stocking
Increasing consumption efficiency—small pens intensive feeding
Increased assimilation efficiency—feeding with easy to digest food pellets
Increased production efficiency—low activity species, highly turbid water
Original Lake Michigan Food web
Lake trout Trophic position 4-4.5
“Once upon a time”
Benthos& zooplankton
sedimentation
Phtoplankton
Offshore food chain
Benthic algae
Aquatic
macrophytes
&detritus
Inshore food chain
Changes in the Lake Michigan Food web during the 60’s
Top-down cascade
Lake trout Trophic position 4-4.5
Lamprey wipes out lake trout
Alewife invades and outcompetes other zooplanktivores; becomes very abundant
Mysis very abundant
Benthos& zooplankton
Large zooplankton decimated
sedimentation
Phtoplankton
Algal blooms
Transparency drops
Offshore food chain
Benthic algae
Aquatic
macrophytes
&detritus
Inshore food chain
Test of the top-down cascade theory: introduce pacific salmon
Alewife declines
Benthos& zooplankton
Large zooplankton recover Benthic algae
sedimentation
Aquatic
Algal blooms stop macrophytes
Phtoplankton Transparency increases
&detritus
Offshore food chain
Inshore food chain
Zebra mussel invading a compartmentalized food web
Prior to the
zebra mussel
invasion, the
rich nutrient
regime
allowed the
phytoplankton
to shade out
the littoral
zone
vegetation
A
H1
A2
H3
H2
As water
clears
light
reaches the
bottom and
plants
& benthic
algae
grow
F1
F2
P1
P2
Light is a key physical factor—determines the boundaries within which
photosynthesis (primary production) can take place
Rooted plants cannot grow at depths beyond the light limit.
In offshore regions where the bottom is below the photic zone suspended
phytoplankton are the main photosynthetic organisms
Photic zone
Light limit
Phytoplankton compete for light with littoral vegetation (macrophytes, epiphytic,
and benthic algae) and enrichment by nutrients usually leads to a reduction in
the extent of the littoral zone community.
Managing access to renewable resources—eg groundwater and
fisheries
Cost-benefit curve for a fishery
Tangent
Total Costs
Benefits
& costs
of
fishing
effort, $
Benefits
0
Eeff
Emsy
Ec
Fishing effort (units)
This analysis involves three assumptions that simplify it without
sacrificing too much realism
1.)The Benefits depend on the amount of fish caught times a price
assumed to be constant.
2.)The Cost of each additional unit of fishing effort is constant.
3.)The fish catch per unit of effort is directly proportional to the size
of the fish population.
(Thus the benefit curve looks like the reverse of the fish renewability
curve, and the cost function is a straight line)
"Too many people, in too many boats, chasing too few fish".
The problem of open-access fisheries
•in a fishery the most efficient allocation of effort (maximum net
benefit) requires an effort level well below that required to obtain the
MSY.
•This effort level would be both ecologically sustainable and
economically efficient
•Many owner-operated fisheries, both recreational and commercial do
seem to operate in this manner.
•Most open-access fisheries do not operate efficiently and often not
sustainably either.
•Most suffer from over-capitalization (too much effort), leading to
stock collapse, and socio-economic hardship
What can be done about the overcapitalization problem in openaccess fisheries?
1.)Aquaculture or ranching of wild fish
good for shellfish, salmon, catfish, trout,
doesn't work for tuna, cod, percids
takes up a lot of space, and causes significant
environmental damage
2.)Raising the costs, use less efficient gear or methods
3.)Taxes on fishing permits
4.)Individual Transferable Quotas (ITQs)
5.)Small-scale co-operatives and sea-tenure system
6.)Eliminate government subsidies
(c) If this population at K were fished at the rate of 4000 kg/yr at what biomass
level would it level off at?
At K, dB/dt would be 0, but it would gradually increase as the fishing
pressure reduced B
dB
 B
 r 0 B 1    4000kg / yr
dt
 K


B
0.4kg  kg yr  B 1 
 4000kg / yr

 10,000kg 
1
1

0.4 B 2 
 0.4 B 
  4000kg / yr
10,000kg 

