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A history of whaling. 10 th 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

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a history of whaling
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.

slide3
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

slide5
Blue whale

Sei whale

Minke whale

Fin whale

slide6
1946

17 nations signed a license where the International Whaling Commission (IWC) set a maximum catch in the Antarctic.

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

populations iii harvest models

Populations III: Harvest Models

Clupea harengus

Odocoileus virginianus

Pinus sylvestris

Oncorhynchus tshawytscha

review
Review

r – intrinsic or per capita growth rate

dN/dt = r*N – exponential growth

Nt=N0*ert

(We’re keeping it discrete)

Bye bye fuzzy duckling!!

review1
Review

Logistic 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=0.25

K=100

review2
Review

Ceratotherium simum

Exponential

K=100

Logistic

slide12
Review

Environmental resistance

Exponential

K=100

Logistic

slide13
How do we use this information to create harvesting quotas?

Two types of mortality:

Additive – added mortality causes a reduction in survival

any hunting is added mortality

if 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

slide14
K

Inflection point

K/2

Logistic growth

r=0.25

K=100

slide15
K/2

K

MSY

MSY = Maximum Sustainable Yield

Logistic growth

r=0.25

K=100

slide16
?

?

h

K/2

K

MSY

Logistic growth

r=0.25

K=100

OSY – Optimal Sustainable Yield

problems with setting quotas
MSY?

Recruitment

K

K

K

N

Problems with setting quotas

Estimating 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

slide18
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)
slide19
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
E2

E1

EMSY

H=q*E*N

Yield = efficiency*Effort*Population

Fixed Effort harvest

E2 > E1 > EMSY

slide21
Logistic

Allee model

dN/dt

N

Hindsight always helps – the Allee effect

Low population density is prone to sudden extinction

Fewer mating opportunities; simply too few to be fit enough

slide22
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.
making a better model
Making a better model

Fish, 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
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