What is a metapopulation and why should i care
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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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What is a metapopulation and why should i care l.jpg

What is a metapopulation?And why should I care?

Hugh Possingham and friends


How to manage a metapopulation problem 1 l.jpg

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 l.jpg
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)


Slide4 l.jpg

Hugh’s birthplace metapopulation

The Mount Lofty Ranges, South Australia


Mlr southern emu wren l.jpg
MLR Southern Emu Wren metapopulation

  • 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)


Slide6 l.jpg

The Cleland Gully metapopulation

Metapopulation;

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 l.jpg
Stochastic Patch Occupancy Model metapopulation(Day and Possingham, 1995)

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

Intermediate states

Extinction process

(0,1,0,0,1,0)

(0,1,0,0,0,0)

(0,0,0,0,1,0)

Colonization process

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

Plus fire


The spom l.jpg
The SPOM metapopulation

  • 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 l.jpg
Decision theory steps metapopulation

  • 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


Slide10 l.jpg

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

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


Management trajectories 1 only largest patch occupied l.jpg
Management trajectories: metapopulation1 – only largest patch occupied

C5

E5

E5

E5

E5

E5

E5

E7

DN


Management trajectories 2 all patches occupied l.jpg
Management trajectories: metapopulation2 – all patches occupied

E5

E5

E2

E2

C5

C2

E5

E2

E5

DN

E7

E5

E5

E5


Take home message l.jpg
Take home message metapopulation

  • 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 l.jpg
Other issues metapopulation

  • Computational problems

  • Problems, models and algorithms – what are they?


Optimal translocation strategies problem 2 l.jpg

Optimal translocation strategies metapopulationProblem 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 l.jpg

Oryx problem metapopulation

Growth rate R = 0.85

Capacity = 50

Growth rate R = 1.3

Capacity = 20

??

Zoo Population

Wild Population


Result base parameters l.jpg

Result – base parameters metapopulation

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 l.jpg

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 l.jpg

Metapopulaton dynamics in a dynamic landscape “new” species we won’t know R in the zoo

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


Eradicate exploit conserve l.jpg

Applied “new” species we won’t know R in the zoo

Theoretical

Ecology

Eradicate, Exploit, Conserve

+

Pure Ecological Theory

Decision Theory

=