mee312093-sup-0001-Sourcepackage.tar.gzapplication/tar.gz151Kecofolio R package. Tools to quantify metapopulation portfolio effects.

Table S1. Metapopulations used in the empirical PE analyses. ID column numbers correspond to ID numbers in the figures.

Table S2. Moth sites used from the Rothamsted Insect Survey database.

Table S3. Reef locations used from the AIMS LTMP Great Barrier Reef database.

Figure S1. Subpopulation time series.

Figure S2. Map of included metapopulations.

Figure S3. Calculation of the mean-variance PE using Taylor's power law.

Figure S4. Taylor's power law z values across metapopulations.

Figure S5. Intra- vs. inter-subpopulation mean-variance scaling relationship (Taylor's power law z-value).

Figure S6. PEs with the mean-variance PEs estimated from a quadratic model.

Figure S7. PEs with the mean-variance PEs estimated from a linear-quadratic averaged model.

Figure S8. PEs from linear detrended time series.

Figure S9. PEs from loess detrended time series.

Figure S10. Empirical ecological PEs (points) overlaid in theoretical PE parameter space (colour shading) with empirical PE values shown beside the points.

Figure S11. Predicted vs. observed mean-variance (a) and average-CV PEs (b). Predicted PEs correspond to the colour underlying the metapopulations displayed in Fig. 5; observed PEs to the values calculated directly from the empirical data and shown in Fig. 3.

Figure S12. Relationship between the drivers of the PE in empirical systems for moths (red), reef fishes (purple), and salmon (blue).

Figure S13. The PE used as an index of ecosystem change.

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