Results

1. Extinction risk as a consequence of variation in time and spaceFridaLögdberg and Uno Wennergren Introduction and Aim Environmental variation is an importantfactor for population dynamics, as well as its temporal structure. Autocorrelatednoisewilldecrease the magnitude of population fluctuationscompared to a non-atucorrelatedenvironmentalnoise. This has impacts on extinction risk, but is only valid for a non-structuredsingle-species population. Howwillautocorrelatedenvironmentalnoiseaffect population dynamics in a spatial setting? Conclusions wwåpitåp Results Method Local population dynamicsfollowed the Rickerequation, changing from over- to under compensatinggrowth with parameter b, and with environmentalnoiseaffecting K: EnvironmentalnoiseMass-actionmixing process, and landscape implicit. 2. Landscape implicitMass-actionmixing process, and landscape implicit. 3. Landscape explicitDispersal is distancedependent. Contact Frida Lögdberg SpatiotemporalBiologyIFM, Theory and Modelling Linköping University SE-581 83 Linköping, Sweden Email: friwa@ifm.liu.se

2. Extinction risk as a consequence of variation in time and spaceFridaLögdberg, Tom Lindström and Uno Wennergren CONCLUSIONS 1. Overcompensatory dynamics - Yes. Extinction risks decrease with colour. Undercompensatory dynamics – No. Extinction risk at max in medium colour. 2. Yes, the qualitative effect of colour is preserved regardless of synchrony and aggregation. Yet:a. Synchrony has large effect on extinction risks b. Aggregation level of landscape also effect extinction risk AIM The importance of the spatial dimension when population dynamics is affected by coloured environmental noise. A B C D INTRODUCTION Coloured noise on single population - decrease the magnitude of population fluctuations.Is this also true for extinction risk? In a spatial setting noise can be correlated both in time and across space; synchronized environmental variation.Are effects of coloured noise preserved despite synchrony? Regardless of aggregation? E F Figure 1. Left: overcompensating density regulation. Right: under-compensating density regulation. Extinction risk (A-B), mean of population density (C-D) and population variance (E-F) as a function of environmental noise colour (γ). The curves show different degrees of synchrony (ρ) of environmentalnoise. Growth rate, r=1.5, number of subpopulations=10, mean K=100, and dispersal=0.1 (mass-action mixing). Analyzing empirical landscapes with spectral method. Empirical data from treeinventories on oldoaks from the Swedish County of Östergötland. Measure of landscape aggregation: continuity=1.02 and contrast=4.7 (compare with middle group of figures in Fig. 2). Figure 2. Landscape is generated with different patch-aggregation; continuity 0,1 and 2 (from left to right), and contrast 2 (upper row) and 5 (lower row). Extinction risk as a function of environmental noise colour (γ).The curves show different degrees of synchrony (ρ) of environmentalnoise. Growth rate, r=1.5, number of subpopulations=500, mean K=100, and distance dependent dispersal=0.1 METHOD Local population Ricker equation Over/under compensatory Parameter b Environmental noise Affecting K Environmental noise New method: 1/|f|γ-noise generated by a spectral synthesis (FFT) in two dimensions (time and space). Noise colour (γ) and synchrony (ρ) between patches can be set with accuracy yet controlling for variance. • Landscape, implicit • Initial analysis with implicit spatial dimension • Dispersala mass-action mixing process • All patches equally connected. • Landscape, explicit • New method: Replicates of landscapes with specifiedaggregation were generated with a spectral method (FFT). The continuous landscape was transformed to a point pattern. Continuity; a measure of spatial autocorrelation. • Contrast; a measure of patch-density dispersion. • Dispersal was distance dependent with “fatter • tail”-shape of displacement kernel. Contact Frida Lögdberg SpatiotemporalBiologyIFM, Theory and Modelling Linköping University SE-581 83 Linköping, Sweden Email: friwa@ifm.liu.se