Conservation

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Conservation
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Elongated Elephant
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Bulte, Van Kooten

• CITES
• Bans TRADE in endangered species
• Reduces Demand
• Should be good for elephants, etc
• (Same argument for Viagra saving Rhinos)

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Poaching

• Poaching model is the fishing model, but adds
  enforcement.
  
• P price
• E effort (poaching
• B enforcement effort
• X stock
• F fine (punishment)

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• kExp is revenue as in fishing
• C(B) E is cost of poaching and increases in B,
  enforcement. Costs of evading getting caught.
  
• T E (zkEx p) expected value of punishment
• TE is likelihood of getting cauth
• Last element is the fine where z is a parameter
• Notice that this term has two Es which drives
  everything

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Zero Profits for Long Run

• 0 kExP C(B) E TE (zkEx p)
• Zero long run profits
• Gives E(P, B, )
• Point is that poaching increases in price and
  decreases in enforcement.
  
• h kEx is harvest

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Look at the Table

• CITES goes Along with
• DECREASED enforcement
• Reminiscent of Kip Viscusis idea of a taste for
  danger. (Gov makes you wear seatbelts, so you
  drive faster to get in your danger quota.)

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Social Planner Problem

• 1 Elephant 4.7 cows in terms of forage
• D(x) is foregone forage
• W(B) costs of enforcement
• R(x) are the existence values and tourism values
• zTh is the value of the govt seized ivory
• Q is total sold ivory including legal harvest and
  illegal
  

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maximand

• At each time
• P(Q) Q R zTh cE D(x) w(B)
• S.t. dx/dt G(x) h y
• Assumes CITES, only a local market

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With trade

• Here P(Q) is world price
• Big question is how much local price is below
  world price, even after otpimization.
  
• Now problem is linear in y, so get most rapid
  approach

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Model is really

• Most efficient way to harvest animals
• Poach or cull
• Right number of animals
• Since CITES doesnt prohibit govt from culling,
  it just reduces price.

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Bulte and KC

• Program this up with Zambia values and they get

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Payoff Slide
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So

• Elephants are on their way DOWN, Cites or no.
• CITES doesnt do that much.
• Underlying reasonstrong local market, possibly
  driven by smuggling.
  

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San Joaquin Kit Fox
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ESA

• Endangered Species Act
• Listing
• Take
• Includes annoying
• Applies to private land too
• Habitat Conservation Plans
• Can include a whole county
• E.g. each acre of toad habitat you take you have
  to buy 5 acres and preserve them elsewhere

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• The ESA was not thought to be radical when it was
  passed. Barely any debate.
  
• Court action and interaction with NEPA made it a
  very powerful tool
  
• The HCP element allowed negotiation and it is now
  just another part of doing business

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ESA

• See Gardner Shogren
• Most listed animals arent going to recover
• There is far too little money allocated to
  recovery plans to make progress
  
• Total value of the animals would need to be
  improbably high for it to be right for Congress
  to allocate that much money

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Who gets listed?

• Amy Ando sets up model where listing depends on
  things like fur
  
• And also depends on pressure group activity
• She records whether there was comment for or
  against a listing. That is her measure of
  pressure.

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• Payoff to a group depends on the other groups
  actions. The more pressure the other group
  applies, the more beneficial it is for the group
  to apply pressure.
• Defines a game where the Nash non coop soln is of
  the form P(i) a bP(j) for the two groups i
  and j.
  

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• comes down to lobby is a function of furriness
  and other groups action.
  
• finds that other groups action doesnt matter
• but furriness does.

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Bollworm
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Pests

• Pests are un elephants.
• They are small
• We want them dead but
• We dont want to kill ourselves and everything
  else killing them

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Pest Control

• Cotton, veggies are a big users of pest control
• Obvious problem is that pest control materials
  can
  
• Run off and kill good things
• Bio accumulate and kill bigger animals
• Like ddt and birds
• Some materials cause cancer, reproductive harm
  and so on.
  
• FERPA regulates these things
• Sunding, Zilberman, Siebert worked on costs of
  regulation in CA

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Cotton

• Livingston, Fackler
• Two pests, boll wevil and budworm
• Two controls BT cotton and pyrethroids
• Also a refugia
• Place where we dont use control/controls
• Problem Bugs become immune to controls.

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Biology

• Assume single gene for resistance
• x,X alleles for resistance/suspectibility for BT
• y,Y for pyrethroids
• x(t,i) proportion of allele in growing season t
  and generation i. Multiple generations per
  season
  
• g is probability of xy etc

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• Since each plant has two (is diploid) alleles
  there are 9 genotype frequencies.
  
• See paper for a list and their probabilities.
• Each plant is two choices from the four possible
  xy combos with their frequencies g.
  
• This makes a 9 vector of frequencies for a
  generation

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• Pests spend some time in refugia and some in
  cotton.
  
• first generation, 95 of pests in non selective
  environment
  
• then 98 of budworms in cotton
• and so on.

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• Different survival rates in refugia vs in
  sprayed/Bt cotton.
  
• So at end of generation, different percent of
  alleles in population.
  
• Bigger refugia, higher percent of suspectibles
  maintained.

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Problem

• Max money
• subject to allele dynamics
• choose refugia size, how much to spray
• findings use less sprayed refugia and less
  refugia all together.