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What is a metapopulation? And why should I care?

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?

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  1. What is a metapopulation?And why should I care? Hugh Possingham and friends

  2. How to manage a metapopulationProblem 1 Michael Westphal (UC Berkeley), Drew Tyre (U Nebraska), Scott Field (UQ) Can we make metapopulation theory useful?

  3. 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)

  4. Hugh’s birthplace The Mount Lofty Ranges, South Australia

  5. 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)

  6. The Cleland Gully Metapopulation; basically isolated Figure shows options Where should we revegetate now, and in the future? Does it depend on the state of the metapopulation?

  7. Stochastic Patch Occupancy Model(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

  8. 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

  9. 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

  10. 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

  11. Management trajectories:1 – only largest patch occupied C5 E5 E5 E5 E5 E5 E5 E7 DN

  12. Management trajectories:2 – all patches occupied E5 E5 E2 E2 C5 C2 E5 E2 E5 DN E7 E5 E5 E5

  13. 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.

  14. Other issues • Computational problems • Problems, models and algorithms – what are they?

  15. 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

  16. Oryx problem Growth rate R = 0.85 Capacity = 50 Growth rate R = 1.3 Capacity = 20 ?? Zoo Population Wild Population

  17. 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

  18. 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

  19. Metapopulaton dynamics in a dynamic landscape • What do mussels, Leadbeater’s possum and annual herbs have in common? Empirical conversations over a long time

  20. Applied Theoretical Ecology Eradicate, Exploit, Conserve + Pure Ecological Theory Decision Theory =

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