SUPPLEMENTARY MATERIAL

Transcription

1 SUPPLEMENTARY MATERIAL Hoset KS, Ruffino L, Tuomi M, Oksanen T, Oksanen L, Mäkynen A, Johansen B and Moe T. Changes in the spatial configuration and strength of trophic control across a productivity gradient during a massive rodent outbreak. Ecosystems Appendix A1. Study site and illustrations of vegetation damage Figure A1. Study site (on next page). The base map was constructed from a NDVI map of the study area where low NDVI values have white colour (i.e., water bodies shows as white features) and darker colour indicates higher NDVI-values. A) Geographic location of study area relative to Northern Europe etc. B) Map of study area with location of rodent trapping grids (only rodent trapping = light blue circles, rodent trapping + vegetation devastation + blueberry monitoring = red squares, rodent trapping + veg dev = dark blue squares, rodent trapping + blueberry monitoring = blue squares) and biomass/point frequency grids (yellow triangles) in the landscape. The core study area (solid lines) is divided into the three sub-areas Highland, Slope and Lowland and the extended study area is visualised with a dotted line. C) Map of the study area with location of all long-tailed skua nests observed in 2011 (blue-green diamonds) and 2012 (light yellow diamonds), location of the line transect for mammalian activity (blue line) including observations from 2011 (green circles) and 2012 and the defined mustelid activity areas (polygons with green colour).

2 21 22 Figure A1. Study site.

3 Figure A2. Examples of vegetation devastation. A) Shrub habitat, B) Shrub/Empetrum nigrum habitat, C) Close-up shrub habitat, D) Meadow habitat with predominantly moss destruction 26

4 A2 Effect of vole density on vegetation damage index and grazing impact on bilberry damage index Vegetation damage index To assess how grazing impact on vegetation was affected by vole abundance and spatial location of the grid, we ran generalised linear models assuming a quasi-binomial error structure where the vegetation damage index was entered as the response variable. The explanatory factors included subarea (Highland, Slope and Lowland), total vole abundance in autumn 2011 and their interaction. The dispersion parameter was estimated to be Model results are summarized in Table A1 and Figure A3. Bilberry shoots The effect of the spatial location of the grid and vole abundance on bilberry damage, we ran a generalised linear model assuming a quasi-binomial error structure where the proportion of impacted shoots weighted against the bilberry damage index was entered as the response variable. Subarea, total vole abundance in autumn 2011 and their interaction were entered as explanatory factors as in the model describing vegetation destruction. The dispersion parameter was estimated to be Model results are summarized in Table A1 and Figure A3.

5 47 48 Table A1. Model output describing the dependency of vegetation damage index and bilberry damage index on vole density and subarea. Statistics P-value Vegetation damage index Subarea F2,48 = < Vole density 2011 F1,48 = < Subarea:Vole density F2,48 = Bilberry damage index Subarea F2,48 = < Vole density 2011 F1,48 = < Subarea:Vole density F2,48 = Figure A3. A) Proportion of vegetation ± SE that showed more than 50% damage from rodent clipping increased with 2011 autumn vole abundance in the Lowland and Highland, but not in the Slope. B) Proportion of bilberry shoots ± SE that was impacted by rodent grazing in 2012 increased with increasing vole density in the Lowland and Highland, but not in the Slope. Grazing impact was on average higher in the Slope than Lowland and Highland. Points indicate observed values while lines represent regression lines for each subarea

6 60 A3 Rodent densities and intrinsic growth rates by genus Figure A4. A) Observed number of individuals per grid by rodent genus in different years and seasons from spring 2010 to spring B) Intrinsic growth rates ± CI by rodent genus in different years and seasons from spring 2010 to spring The horizontal dashed line represents zero growth rate. Lemmus = Lemmus lemmus, Microtus = Microtus agrestis (most numerous) and Microtus oeconomus, Myodes = Myodes rufocanus (most numerous) and Myodes rutilus