MODULARIZACE VÝUKY EVOLUČNÍ A EKOLOGICKÉ BIOLOGIE CZ.1.07/2.2.00/15.0204 Spatial ecology - describes changes in spatial pattern over time processes - colonisation / immigration and local extinction / emigration local populations are subject to continuous colonisation and extinction wildlife populations are fragmented Metapopulation - a population consisting of many local populations (sub-populations) connected by migrating individuals with discrete breeding opportunities (not patchy populations) population density changes also in space for migratory animals (salmon) seasonal movement is the dominant cause of population change movement of individuals between patches can be density-dependent distribution of individuals have three basic models: most populations in nature are aggregated (clumped) Regular distribution described by hypothetical uniform distribution n .. is number of samples x .. is category of counts (0, 1, 2, 3, 4, ...) all categories have similar probability mean: variance: for regular distribution: n xP 1 )( = )1( 2 1 += nµ )1( 12 1 22 −= nσ 2 σµ > described by hypothetical Poisson distribution µ .. is expected value of individuals x .. is category of counts (0, 1, 2, 3, 4, ...) probability of x individuals at a given area usually decreases with x observed and expected frequencies are compared using χ2 statistics for random distribution: ! )( x e xP x µ µ − = Random distribution 2 σµ = described by hypothetical negative binomial distribution µ .. is expected value of individuals x .. is category of counts (0, 1, 2, 3, 4, ...) k .. degree of clumping, the smaller k (→0) the greater degree of clumping approximate value of k: for aggregated: Coefficient of dispersion (CD) CD < 1 … uniform distribution CD = 1 … random distribution CD > 1 … aggregated distribution xk kkx xk k xP       +− −+       −= − µ µµ )!1(! )!1( 1)( µσ µ − ≈ 2 2 k Aggregated distribution x s CD 2 = 2 σµ < • Geographic range - radius of space containing 95% of individuals • individual makes blind random walk • random walk of a population undergoes diffusion in space - radial distance moved in a random walk is proportional to - area occupied (radius2) is proportional to time Spread of muskart in Europe time Elton 1958 N t=0 t=1 t=2 t=3         − = DtDt N tN 4 exp 4 ),( 2 0 ρ π ρ Pure dispersal radius Dt4=ρ t D 4 2 ρ = • Difussion model - solved to 2dimensional Gaussian distribution - assuming all individuals are dispersers - range expanses linearly with time - no reproduction N0- initial density ρ .. radial distance from point of release (range) D - diffusion coefficient (distance2/time) 0 N t=0 t=1 t=2 t=3 Dispersal + population growth radius rDc 2= 0         −= Dt rt Dt N tN 4 exp 4 ),( 2 0 ρ π ρ • Skellam‘s model - Includes diffusion and exponential population growth r .. intrinsic rate of increase c - expansion rate [distance/time] Skellam 1951 Levins (1969) distinguished between dynamics of a single population and a set of local populations which interact via individuals moving among populations Hanski (1997) developed the theory - suggested core-satellite model the degree of isolation may vary depending on the distance among patches unlike growth models that focus on population size, metapopulation models concern persistence of a population - ignore fate of a single subpopulation and focus on fraction of sub-population sites occupied assumptions - sub-populations are identical in size, distance, resources, etc. - extinction and colonisation are independent of p - many patches are available - natality and mortality is ignored eppmp dt dp −−= )1( Levin‘s model p .. proportion of patches occupied m .. colonisation (immigration) rate - proportion of open sites colonised per unit time e .. extinction (emigration) rate - proportion of sites that become unoccupied per unit time Levin (1969) Time p 0.5 0.1 equilibrium is found for dp/dt = 0 - sub-populations will persist (p* > 0) only if colonisation is larger than extinction (m > e) - all patches can be occupied only if e = 0 - K ..is fraction of patches - defined by balance between m and e m e m em p −= − = 1* K