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What is a metapopulation? And why should I care?. Hugh Possingham and friends. How to manage a metapopulation Problem 1. Michael Westphal ( UC Berkeley), Drew Tyre (U Nebraska), Scott Field (UQ) Can we make metapopulation theory useful?.

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how to manage a metapopulation problem 1

How to manage a metapopulationProblem 1

Michael Westphal (UC Berkeley),

Drew Tyre (U Nebraska), Scott Field (UQ)

Can we make metapopulation theory useful?

specifically how to reconstruct habitat for a small metapopulation
Specifically: how to reconstruct habitat for a small metapopulation
  • Part of general problem of optimal landscape design – the dynamics of how to reconstruct landscapes
  • Minimising the extinction probability of one part of the Mount Lofty Ranges Emu-wren population.
  • Metapopulation dynamics based on Stochastoc Patch Occupancy Model (SPOM) of Day and Possingham (1995)
  • Optimisation using Stochastic Dynamic Programming (SDP) see Possingham (1996)

Hugh’s birthplace

The Mount Lofty Ranges, South Australia

mlr southern emu wren
MLR Southern Emu Wren
  • Small passerine (Australian malurid)
  • Very weak flyer
  • Restricted to swamps/fens
  • Listed as Critically Endangered subspecies
  • About 450 left; hard to see or hear
  • Has a recovery team (flagship)

The Cleland Gully


basically isolated

Figure shows options

Where should we revegetate now, and in the future? Does it depend on the state of the metapopulation?

stochastic patch occupancy model day and possingham 1995
Stochastic Patch Occupancy Model(Day and Possingham, 1995)

State at time, t, (0,1,0,0,1,0)

Intermediate states

Extinction process




Colonization process

State at time, t+1, (0,1,1,0,1,0)

Plus fire

the spom
  • A lot of “population” states, 2n, where n is the number of patches. The transition matrix is 2n by 2n in size (128 by 128 in this case).
  • A “chain binomial” model; SPOM has recolonisation and local extinction where functional forms and parameterization follow Moilanen and Hanski
  • Overall transition matrix, a combination of extinction and recolonization, depends on the “landscape state”, a consequence of past restoration activities
decision theory steps
Decision theory steps
  • Set objective (minimize extinction prob)
  • Define state variables (population and landscape states) and control variables (options for restoration)
  • Describe state dynamics – the SPOM
  • Set constraints (one action per 5 years)
  • Solve: in this case SDP

Control options (one per 5 years, about 1ha reveg)

E5: largest patch bigger, can do 6 times

E2: most connected patch bigger, 6 times

C5: connect largest patch

C2: connect patches1,2,3

E7: make new patch

DN: do nothing

take home message
Take home message
  • Metapopulation state matters
  • Actions justifiable but no clear sweeping generalisation, no simple rule of thumb!
  • Previous work has assumed that landscape and population dynamics are uncoupled. This paper represents the first spatially explicit optimal landscape design for a threatened species.
other issues
Other issues
  • Computational problems
  • Problems, models and algorithms – what are they?
optimal translocation strategies problem 2

Optimal translocation strategiesProblem 2

Brigitte Tenhumberg, Drew Tyre (U Nebraska), Katriona Shea (Penn State)

Consider the Arabian Oryx Oryx leucoryx – if we know how many are in the wild, and in a zoo, and we know birth and death rates in the zoo and the wild, how many should we translocate to or from the wild to maximise persistence of the wild population

oryx problem

Oryx problem

Growth rate R = 0.85

Capacity = 50

Growth rate R = 1.3

Capacity = 20


Zoo Population

Wild Population

result base parameters

Result – base parameters

R = release, mainly when population in zoo is near capacity

C = capture, mainly when zoo population small, capture entire wild population when this would roughly fill the zoo

if zoo growth rate changes results change but for a new species we won t know r in the zoo

If zoo growth rate changes, results change – but for a “new” species we won’t know R in the zoo

Enter – active adaptive management,

Management with a plan for learning

metapopulaton dynamics in a dynamic landscape

Metapopulaton dynamics in a dynamic landscape

  • What do mussels, Leadbeater’s possum and annual herbs have in common? Empirical conversations over a long time
eradicate exploit conserve




Eradicate, Exploit, Conserve


Pure Ecological Theory

Decision Theory