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Increasing Reality

Increasing Reality. Modeling Improvements Linking migration and local extinction Accounting for habitat destruction Conceptual Improvements Continuous rather than categorical population structure Linking to landscape ecology Empirical studies. Modeling Improvements (Hess 1996).

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Increasing Reality

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  1. Increasing Reality • Modeling Improvements • Linking migration and local extinction • Accounting for habitat destruction • Conceptual Improvements • Continuous rather than categorical population structure • Linking to landscape ecology • Empirical studies

  2. Modeling Improvements (Hess 1996) • Assumption 1: colonization and extinction are assumed independent by Levins, but are both likely linked to connectivity • Corridors could bring immigrants as well as pathogens, predators, etc that increases extinction • Modeling this adjustment shows that metapopulation extinction increases if negative effects of connectivity increase faster than positive effects

  3. Fixing Assumption 1 • r(c) is recolonization rate as function of connectivity • Substitute r for c in original formula so c can indicate function of connectivity • x(c) is local extinction rate as function of connectivity Now, r(c) > x(c) for nonzero equilibrium (metapopulation not going extinct)

  4. Focus Now Shifts to Effects of Connectivity on Extinction and Colonization The relationship of extinction and colonization with connectivity is key to understanding if the metapopulation will survive or go extinct.

  5. Assumption 2 • Simple model assumes that a patch is immediately available for recolonization after deme goes extinct there, but often extinction occurs because habitat is destroyed and recolonization cannot occur until patch regenerates.

  6. Fixing Assumption 2 • Proportion of patches available for recolonization is not 1-p, but h-p, where h is fraction of total patches that are suitable (regenerated) • Local extinction is now a function of normal stochastic events (demographic and environmental) PLUS patch destruction (where d = extinction rate due to patch destruction)

  7. Focus Now Shifts to Relative Importance of Stochastic Events vs Habitat Loss to Extinction Removing risk of extinction to habitat destruction is critical, but eliminating stochastic events that cause extinction does little Note, in Levin’s terminology, m=c and x=e.

  8. Multi-species response to habitat Destruction • Liu et al. 2007 • Model metapopulation dynamics of a plant community looking at how instantaneous versus constant habitat destruction affects colonization and extinction of patches and competitive interactions among an assemblage of species Which means that the proportion of habitat occupied by species I is a function of colonization, mortality, competitive effects of other species, and a direction reduction in abundance due to habitat destruction

  9. Survival is affected by competitive ability (dominants go extinct because of poor colonization ability) and is initially greater in response to continuous destruction (top), but in long term complete extinction is predicted in response to continuous • Intermediately competitive species (6, 7, 8, 9) end up surviving instantaneous disturbance) • Metapopulation dynamics determine community composition (Liu et al. 2007)

  10. Fine-tuning How We Conceptualize Population Structure (Thomas and Kunin 1999) • Continuous function of Immigration (I), Emigration (E), Birth (B), and Death (D), rather than categories • Process, not pattern is what is important

  11. Populations are Not Fixed on Compensation Axis • Depends on balance of internal (B, D) vs. external (E, I) processes • Density dependence and stochastic variation in B, D, E, or I can affect position through time • May depend on location relative to other demes (central areas more likely to be sources, fringe areas more likely to be sinks, but this changes as central areas become fringe areas due to deme extinctions; Stacey et al. 1997) • Investigation of the change in processes through time or with respect to density would be fruitful investigation

  12. Plotting Metapopulations to View Processes

  13. A Butterfly (Hesperia comma) Example Result is a “Process-oriented” fingerprint of population structure. Two Study sites: Surrey has many small patches, close together with lots of E, I and some importing and some exporting populations. East Sussex has a few large patches with low E and I.

  14. Getting Real • Thinking about metapopulations in actual landscapes (Wiens 1997) • distances are not Euclidean • Patch permeability and edge effects may affect travel and hence functional distance between patches)

  15. Need to understand and quantify individual movements and how individuals in a population vary in their within- and between-patch movements

  16. When Can We Ignore Aspects of the Landscape? • The pattern of the landscape may be relatively unimportant until habitat loss exceeds the “percolation threshold” • Percolation thresholds vary with vagility of organism (Wiens 1997; Fig. 4) and as they are approached, the landscape perspective is more important to metapopulation modeling • Landscape view is less needed when: • Abundant and widespread suitable habitat • Less isolated patches • Transition probabilities among patches are relatively equal and high regardless of patch type • Habitat pattern is ephemeral

  17. What Can We Learn from Empirical Studies? • Metapopulations with “Strong Rescue Effects” are more common than thought (Stacey et al. 1997) • “Strong rescue effects” occur when dispersal prevents local extinctions (as opposed to rescuing occupancy of a patch after extinction) • Butterflies, small mammals (pikas, voles, prairie dogs, mice, chipmunks, rats, squirrels), amphibians (red-spotted newts, natterjack toads, pool frogs) • Individual demes can vary from being source in one year to sink in the next due to stochastic or landscape-mediated changes in survival and reproduction

  18. Modeling Isolates Importance of Rescue (Stacey et al. 1997)

  19. Modeling also Indicates the Detriments of Spatial Autocorrelation Do not want to have all demes function as sinks in the same year Implications for reserve design?

  20. Long-distance Rescue from Dispersal may also be Important for Birds • Naturally fragmented populations of Ptarmigan • Lot of turnover in breeders, especially females (Martin et al. 2000)

  21. Recruitment was from Outside of Area Studied • Recruitment most conspicuous in females • More than 50% of females new each year, most of those from outside study area

  22. More is Not Necessarily Better Intermediate spp survive at median = 60% of regions, sedentary at 95%, mobile at 100% • Dispersal and population persistence in butterflies (Thomas 2000) • Apparent disruptive selection • Small populations and high colonization of intermediate dispersers not as good as larger populations (despite lower colonization) of poor dispersers • Large populations and high colonization by most mobile species

  23. Sinks Matter • Greater Reed Warblers (Netherlands) live in metapopulations with sinks and sources (Foppen et al. 2000) • Growth of sources increases with number of, and connectivity to, sinks

  24. Beyond Sources and Sinks: The Sponge (Marzluff et al. 2001) • Crow demographics suggest that populations in urban areas have lambda=1, yet populations continue to grow • Perhaps urban areas “soak up” non-breeders from wildland and suburban sources to fuel growth

  25. Projections indicate local breeding population not responsible for growth Projected growth

  26. Do suburban and exurban fledglings become young urban crows? • Method: radiotracking dispersing juveniles

  27. 56 crows radiotagged as fledglings at 8 sites: urban, suburban, fringe, and exurban

  28. Benefits of Moving to the City Of known-fate crows, 38% of urban and 68% of other crows died

  29. 45% of crows dispersing from suburbs and exurbs became more urban and 36% showed no change

  30. One non-disperser tried city life and came back home as a helper

  31. Is dispersal enough to explain the gap? • Five of 43 (12%) suburban and exurban crows moved to more-urban areas during dispersal • Sufficient to replace crows emigrating and add to population? Standardized Crow Count

  32. Is dispersal enough to explain the gap? Effect of adding 12.3% to local production explains some - but not all - of the gap between predicted and observed population growth More precise modeling of contribution of suburban and exurban areas worthwhile Standardized Crow Count

  33. Sociality and Metapopulations(Marzluff and Balda 1989) Sex-ratio based dispersal leads to metapopulations of Pinyon Jay flocks

  34. Metapopulations of Metapopulations? Small networks near large, persistent networks • Butterflies in Britian (Wilson et al. 2002) • Very long-distance dispersal is critical to persistence (longer than empirically-recorded max dispersal distances • Connectivity within patch networks and proximity to networks to other networks discriminated occupied from unoccupied networks

  35. A Word of Caution • Seduction of reduced risk of extinction in metapopulations relative to single, panmictic populations can be taken too far • Creation of small populations of captive Puerto Rican Parrots with human-mediated dispersal among the demes was recommended • But increased risk of disease spread with exchange of individuals among demes, and • Reduced mating success in small groups • Makes this recommendation unsound (Wilson et al. 1994)

  36. References • Wilson, R. J., Ellis, S., Baker, J. S., Lineham, M. E., Whitehead, R. W., and C. D. Thomas. 2002. Large-scale patterns of distribution and persistence at the range margins of a butterfly. Ecology 83:3357-3368. • Wiens, JA. 1997. Metapopulation dynamics and landscape ecology. Pp. 43-62. In: (Hanski, IA and ME Gilpin, eds.) Metapopulation biology: ecology, genetics, and evolution. Academic Press. San Diego. • Stacey, PB, Johnson, VA, and ML Taper. 1997. Migration within metapopulations: the impact upon local population dynamics. Pp. 267-291. In: (Hanski, IA and ME Gilpin, eds.) Metapopulation biology: ecology, genetics, and evolution. Academic Press. San Diego. • Wison, MH, Kepler, CB, Snyder, NFR, Derrickson, SR, Dein, FJ, Wiley, JW, Wunderle, JM Jr., Lugo, AE, Graham, DL, and WD Toone. 1994. Puerto Rican parrots and potential limitations of the metapopulation approach to species conservation. Conservation Biology 8:114-123. • Foppen, RPD, Chardon, JP, and W. Liefveld. 2000. Understanding the role of sink patches in source-sink metapopulations:reed warbler in an agricultural landscape. Conservation Biology 14:1881-1892. • Martin, K, Stacey, PB, and CE Braun. 2000. Recruitment, dispersal, and demographic rescue in spatially-structured white-tailed ptarmigan populations. Condor 102:503-516. • Thomas, CD. 2000. Dispersal and extinction in fragmented landscapes. Proceedings of the Royal Society (London) 267:139-145. • Thomas, CD and WE Kunin. 1999. The spatial structure of populations. J. Animal Ecology 68:647-657. • Hess, GR. 1996. Linking extinction to connectivity and habitat destruction in metapopulation models. American Naturalist 148:226-236. • Marzluff, J. M., K. J. McGowan, R. E. Donnelly, and R. L. Knight. 2001. Causes and consequences of expanding American Crow populations. Pages 331-363. In: Marzluff, Bowman, and Donnelly Eds., Avian conservation and ecology in an urbanizing world, Kluwer, Norwell, MA. • Marzluff, J. M. and R. P. Balda. 1989. Social, demographic, and evolutionary consequences of dispersal in a group-living bird, the pinyon jay. Ecology 70:316-328. • Liu, H. Y., Z. S. Lin, and T. Wen. 2007. Responses of metapopulation dynamics to two different kinds of habitat destruction caused by human activities. Plant Ecology 188:53-65.

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