metapopulation assumptions
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Assumptions of Assumptions of metapopulationsmetapopulations

OutlineOutline
Basic metapopulation assumptions
Factors that affects local population dynamics
Model assumptions
advantages and disadvantages

Basic Metapopulation Basic Metapopulation AssumptionsAssumptions
Space is discrete, and it is possible to distinguish between the matrix and habitat patches
Habitat patch units are large and permanent enough to allow for persistence of local populations for at least a few generations

More basic assumptionsMore basic assumptions
Habitat patches are of equal size and are equally isolated
Migration has no real effect on dynamics
2 ways to think of migration

Density DependenceDensity Dependence
Per capita growth rate depends on past and/or present population densities
not all populations are strongly affected all the time
Morris and Doak, 2002

ExtinctionExtinction
Risk of extinction increases with decreasing population size
Allee Effect-Reduced per capita growth rate at low population density
Habitat fragmentation- reduces patch area
can be easily modeled

MigrationMigration
Need a sufficiently high rate of migration for metapopulations to persist as a result of recolonizations
If migration rate is too high, may accelerate metapopulation extinction
Rescue Effect/Propagule Rain

ColonizationColonization
Habitat Fragmentation- reduces level of patch connectivity
can be easily modeled

Spatially Implicit (Levins) Spatially Implicit (Levins) ModelModel
Assume:
infinite, discrete habitat patches with no variation
stochastic, asynchronous local dynamics
local dynamics be ignored
all patches are equally connected via migration
patches are empty or occupied
Hanski and Gilpin 1997

Levins ModelLevins Model
dP/dt= cP(1-P)-ePEquilibrium when Phat= 1-e/c
Highlights that recolonization must occur at at a high enough rate to compensate for extinctions

Advantages and Advantages and Disadvantages of the basic Disadvantages of the basic
Levins modelLevins model+ Easy mathematically and conceptually
- Can only answer a limited number of questions because it
ignores so many variables (generally can only be used for metapopulations close to a steady state)

Spatially Explicit ModelsSpatially Explicit Models
Assume:
many patches (arranged as cells in a lattice)
patches may be occupied or empty
no variation in patch size and quality
migration is distance dependent Hanski, 1999 Fig. 5.3A

Spatially Explicit ModelSpatially Explicit Model
Probability that a cell will become occupied= γ(y-x)
Where gamma is the rate of emigration and y-x is the distance between x and y

Advantages and Advantages and DisadvantagesDisadvantages
+ Local behavior is same from patch to patch, so dynamics can
be easily modeled.
- Can not simply describe the state of the metapopulation by the
fraction of patches occupied (need to use a vector- much more complicated)

Spatially Realistic ModelSpatially Realistic Modelfinite number of relatively small patches in comparison with the total landscape
randomly scattered patches
assume real patch attributes (area, location, etc)
patch area and isolation affect extinction and recolonization
occupied patches inflict colonization pressure on all empty patches
declines with distance
Hanski, 1999 Fig. 5.3

Spatially Realistic ModelSpatially Realistic Model
dpi/dt= Ci(t)[1-pi]-eipi
(dpi/dt= rate of change in patch i)pi= probability that patch i is occupied
Ci(t)= colonization rate in patch i, taking connectivity between all patches into account
ei= extinction rate in patch i , which is a function of the area of patch i

Advantages and Advantages and DisadvantagesDisadvantages
+ More realistic; can make quantitative predictions about
dynamics
- More complicated; A lot of data has to be assumed; Starts to
move away from the metapopulation concept

Works citedWorks citedDriscoll, D. 2007. How to find a metapopulation. Can. J. Zool., 85: 1031-1048.
Hanski, I. 1999. Metapopulation ecology. New York: Oxford University Press.
Hanski, I and Gaggiotti, O (Eds.). 2004. Ecology, genetics, and evolution of metapopulations. New York: Elsevier Academic Press.
Hanski, I and Gilpin, M (Eds.). 1997. Metapopulation biology: Ecology, genetics, and evolution. New York: Academic Press.
Hanski, I and Gilpin, M, 1991. Metapopulation dynamics: brief history and conceptual domain. Biological Journal of the Linnean Society, 42: 3-16.
Morris, W and Doak, D. 2002. Quantitative Conservation Biology. Sunderland: Sinauer Associates, Inc.
Nie, L and Mei, D. 2007. Fluctuation-enhanced stability of a metapopulation. Physics Letters A, 371: 111-117.