a history of whaling 10 th century – records of whaling 1400-1700 atlantic arctic fishery –...
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A history of whaling 10th Century – records of whaling
1400-1700 Atlantic Arctic fishery – targeting the right whale
1600-1900 the Pacific fishery – more right whales
1800-1970s Sperm whale fishery
Quantity of oil in a sperm whale made it an attractive target
Innovation: Possible to make margarine of almost 100 percent whale oil.
Sperm Whale (Physeter macrocephalus)
1712 – Americans hunt sperm whale
1860 – Norwegians introduce steam-powered boats and explosive harpoons Factory ships and newer technologies
more species, more oceans, more countries
Blue whale Sei whale
Minke whale Fin whale
1949-1960 – IWC sets annual “fixed” quotas for all whaling
1972 - the United Nations called for a cessation of whaling and the United States Congress passed an Endangered Species Act
1987 - whale sanctuaries were declared in the 1970s and ’80s, and a general moratorium on commercial whaling, adopted by the IWC in 1982, took effect in 1987
1946 17 nations signed a license where the International Whaling Commission (IWC) set a maximum catch in the Antarctic.
Populations III: Harvest ModelsOdocoileus virginianus
Oncorhynchus tshawytscha
Pinus sylvestris
Clupea harengus
Reviewr – intrinsic or per capita growth rate
dN/dt = r*N – exponential growth
Nt=N0*ert
(We’re keeping it discrete)
Bye bye fuzzy duckling!!
Rabbits in Australia – invasive species can grow exponentially at first
ReviewLogistic growth – S-shaped or sigmoid curve
K – carrying capacity
Modify with “unused” component of K
(K-N)/K = (1-N/K) – used interchangeably
dN/dt = r*N*(1-N/K)
Logistic growth r=0.25K=100
Exponential
Logistic
K=100
Review
Ceratotherium simum
Exponential
Logistic
K=100
Review
Environmental resistance
Two types of mortality:
Additive – added mortality causes a reduction in survival any hunting is added mortalityif we want to control a population of invasives
Compensatory – added mortality does not affect survival, up to a threshold
harvesting/ hunting is mortality “that would have happened anyway” e.g. starvation, predation, disease
We assume that a “compensatory” decrease in non-harvest mortality occurs – perhaps due to extra food availability
How do we use this information to create harvesting quotas?
K
K/2
Inflection point
Logistic growth r=0.25K=100
0
1
2
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7
0 10 20 30 40 50 60 70 80 90 100
Population size N
Rec
uitm
ent
KK/2
MSY
MSY = Maximum Sustainable Yield
Logistic growth r=0.25K=100
0
1
2
3
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0 10 20 30 40 50 60 70 80 90 100
Population size N
Rec
uitm
ent
KK/2
MSY
Logistic growth r=0.25K=100 OSY – Optimal Sustainable Yield
? ?
h
Problems with setting quotasEstimating numbers is not easy
hard to obtain reliable MSY
You can’t just stop people that easily noncompliance is a huge issue
K varies with environment = MSY changes
N
Rec
ruit
men
t
K K K
MSY?
Factors that affect K
• Density-independent factors – Weather (storms, cold, drought)– Density-independent diseases (DDT poisoning)
• Density-dependent factors– Food – Space (territories, denning sites, nest cavities)– Density-dependent epizootics (rabies, SARS)
Trophic effects on K – remove large fish, remove fish waste, removes fertilizer, removes smaller fish, up the food chain, less fish to catch
Fixed Effort harvest
0
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0 10 20 30 40 50 60 70 80 90 100
Population size N
Rec
uit
men
t o
r H
arve
stin
g r
ate,
h
EMSY
E1E2
E2 > E1 > EMSY
H=q*E*NYield = efficiency*Effort*Population
Hindsight always helps – the Allee effectLow population density is prone to sudden extinction Fewer mating opportunities; simply too few to be fit enough
Allee model
N
Logistic
dN/dt
Peruvian anchoveta (Engraulis ringens)
• 1960-1972 – world’s largest fishery
• MSY estimated at 10 million tonnes/year
• Expanded fishing fleet plus El Niño events meant collapse
• 20,000 people relied on it, so politically harmful to close
• Repeated collapses – 1973, 1986 – still not recovered.
Peruvian Anchoveta Global capture estimate (tonnes)source: FAO
0
2000000
4000000
6000000
8000000
10000000
12000000
14000000
1950 1953 1956 1959 1962 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001
Making a better modelFish, deer, trees are not all one size or age
– We prefer adult or mature organisms
– Life-history events – reproduction, growth occur at different times
– Next Lecture: life-tables and age-structure