OUTLINE FOR THIS WEEK Lec 11 – 13

1. OUTLINE FOR THIS WEEK Lec 11 – 13 METAPOPULATIONS concept --> simple model Spatially realistic metapopulation models Design and Implementation Pluses/minuses The importance of the MATRIX CORRIDORS (as a conservation tool)

2. Classical metapopulations are…. P* unrealistic but add a different perspective to defining suitable or critical habitat conservation decisions regarding habitat patches Why?

3. Spatially realistic metapopulation models Assume occupancy results from extinction-colonisation dynamics extinction varies with patch area colonisation varies with isolation and neighbouring patch areas and can be modelled using patch occupancy models (eg IFMs) if the metapopulation is at equilibrium

4. Patch occupancy models Data requirements a presence/absence snaphot Patch areas (A), Interpatch distances (dij) Fit model Obtain estimates for how Areas and distances influence colonisation Area influences extinction Use relationships to predict whether occupied patch goes extinct unoccupied patch is colonised Predict forwards in time 1,2,3,4……1000 years

5. Incidence function models The positive Are simple Can represent discrete networks of populations in patches that vary within a spatially realistic landscape Allow rigorous mathematical analysis Require limited data

6. Incidence function models The limitations Data requirements to estimate parameters 1 sufficient patches - 30+ sufficient occupied or empty patches - 10+ Equilibrium - no strong trend in % occupied 3 Constant extinction and colonisation rates Q. Why?

7. Limitations Are metapopulations in equilibrium ? Patchy Non-eqm declining Classical HIGH<--- Fragmentation ---> LOW Baguette: common rare common

8. The Limitations are extinction and colonisation rates constant Pika Moilanen et al 1998 Field Vole - Crone et al 2001 Bodie, California Tvarrminne, Finland 4 years - 76 patches 5 yrs - 76 islands Parameters vary Parameters vary 2-100 fold Area effects differ between yrs NO BUT Using mean values captured dynamics of the systems

9. The Limitations Are metapopulations common? Hanski Many spp may be in extinction-recolonisation balance many butterflies forest insects on dead trees daphnia in rock pools frogs in ponds birds in fragmented woodlots - nuthatches small mammals on islands or in patchy habitat Harrison and Taylor 1993, Baguette 2004 Spp in extinction-recolonisation balance are rare

10. Examples of spp in extinction-recolonisation balance • Glanville fritillary on granite outcrops • Discrete breeding populations • All populations small with high risk extinction • Recolonization possible (patches < 4km apart) • Pool frog in ponds along Baltic coast • relatively frequent extinctions (pike predation) • movement between ponds rare • extinctions create vacant ponds which are recolonized Harrison and Taylor 1997

11. Critical appraisal - CONCLUSIONS Exclusive use of classic metapopulation model theory should be avoided Management of pop’ns using IFM should be preceded by examination of assumptions regarding population turnover and equilibrium state Classic metapopulation theory is not only framework to examine consequences of habitat loss and fragmentation From Baguette 2004 Basic and Applied Ecology 5: 213 on

12. METAPOPULATION BIOLOGY considers the size and isolation of patches in a uniform matrix How well does patch size and isolation explain occupancy patterns?

13. Prugh et al PNAS 2008 105: 20770-20775 How well does area and isolation explain occupancy? Data 785 terrestrial animals 1015 networks with 12,370 discrete patches

14. Prugh et al PNAS 2008 105: 20770-20775 How well do area and isolation explain occupancy? Explained deviance in occupancy Isol Area Area+ Area* Isol Isol Area and isolation explain, on average, 25% of the variation in patch occupancy

15. If extinction-recolonisation dynamics drives patch occupancy And recolonisation depends on movement “Dispersal is……… the glue that binds populations together Wiens 2001 What prevents or facilitates dispersal?

16. METAPOPULATION vs LANDSCAPE BIOLOGY ECOLOGY Patches in a matrix Patches in a variable landscape

17. Prugh et al PNAS 2008 105: 20770-20775 How does the matrix influence Patch-Occupancy Models? Open = Area Filled = Isolation The matrix influences the strength of area/isolation effects

18. How does the matrix influence the movement of individuals the occupancy of patches the growth of metapopulations

19. the matrix and movement of individuals experiments with forest birds Chucao tapaculo - endemic to Chile Understorey forest insectivore Primarily terrestrial - hops rather than flies

20. The matrix and movement Approach- testing the permeability of matrix Radiocollar individuals Release in unoccupied patches Patches - big enough to supply food too small to breed Monitor time to departure 14 13 14

21. the matrix and movement Likelihood of dispersal Movement pattern Birds were never seen in open habitat Open habitat constrains dispersal

22. Barriers in the matrix The problem with roads major cause of fragmentation Inhibit normal movement Promote linear paths

23. Barriers in the matrix The problem with roads Roads limit movement And are a major source of mortality And alter genetic structure

24. the matrix and patch occupancy Vizcacha

25. Patch occupancy in the Mountain Vizcacha APPROACH: Use presence/absence data and logistic regression to examine the role of Patch size Isolation - distance Patch quality - density & depth of crevices Barriers in the matrix - rivers Conclude - barriers, quality and isolation predict presence of viscachas Walker 2003 Landscape Ecol

26. the matrix and population growth in fragmented habitat

27. DATA available All territories mapped Reproduction and adult survival in fragments of varying size Dispersal and survival of juveniles in relation to “connectedness” well connected 4% individuals die during dispersal poorly connected 18% individuals die during dispersal Used data to simulate growth rates

28. Growth  = Sf + (Ny*Sy) Connected Sf Ny Sy Large 0.67 0.70 0.46 0.99 Med 0.67 0.89 0.46 1.08 Small 0.67 1.07 0.46 1.16 Neighbourhood 0.67 0.83 0.46 1.05 Fragmented Large 0.67 0.70 0.32 0.89 Med 0.67 0.89 0.32 0.95 Small 0.67 1.07 0.32 1.01 Neighbourhood 0.67 0.83 0.32 0.94 Q. What does this data tell you?

29. Summary Simple metapopulation models ignore the matrix Matrix habitat type and barriers in the matrix influence movement and occupancy Connectedness can influence metapopulation growth Next: how effective are corridors