Journal of Biogeography
SUPPORTING INFORMATI ON
Spatial extent of biotic interactions affects species distribution and
abundance in river networks: the freshwater pearl mussel and its hosts
Sabela Lois, David E. Cowley, Adolfo Outeiro,
Eduardo San Miguel, Rafaela Amaro and Paz Ondina
APPENDIX S1 Data description.
Distribution and abundance data
Distribution and abundance data of Margaritifera margaritifera were obtained from
sampling surveys conducted during 2008–2011 in the study area. Sampling methods
and abundance estimates were described in Lois et al. (2014).
Biotic and abiotic predictor variables
Climate data were obtained for a model of 200 m resolution with annual and monthly
records from 2285 meteorological stations spanning 50 years (Ninyerola et al., 2005).
Six climate variables considered relevant for M. margaritifera were selected (average
annual temperature, average summer temperature, minimum and maximum summer
temperature, average annual precipitation and average summer precipitation). The
months of July, August and September were considered summer and this coincides with
typically lower river discharge in the study area. Data layers were resampled to a pixel
size of 40 m × 40 m using the nearest-neighbour approach in ARCMAP.
Categories in the surface geology map that may have relevance in characterizing
the river systems of Galicia and in the ecology of freshwater pearl mussel were classified into three main categories: granitic rocks, metamorphic rocks and detrital deposits
(Quaternary/Tertiary sedimentary deposits). These data were converted from vector
format into raster layers of categorical values of zero or one.
Elevation and slope were extracted from the digital elevation model (DEM) at a
resolution of 40 m × 40 m. A polygon feature that represented the areas with forest
cover was extracted and reclassified to a categorical feature (0 or 1), and converted to a
raster format.
Information on host fish for M. margaritifera – Salmo salar (Atlantic salmon),
Salmo trutta (resident trout) and its migratory ecotype (migratory trout) – included
1063 sampling points (1993–2003) across the majority of Galician streams (Beier et al.,
2007). We designed five host-fish predictor layers using the following information in
this dataset: density of each of the three host fishes (individuals m−2), and biomass of
salmonids (g m−2 yr−1). Vector point values of host-fish densities in each river were
converted to a range of 40 m × 40 m raster pixel values using kernel density estimation
implemented with ARCMAP using HAWTH’S ANALYSIS TOOLS to assign density values to
various pixels.
Journal of Biogeography
Supporting Information
Each raster layer described above was converted to the same resolution and
extent using ARCMAP 9.3 (ESRI, Redlands, CA, USA, 2009), the SPATIAL ANALYST extension
and the digital model of the land at a resolution of 40 m × 40 m as the basis for raster
layers extent.
Data for analysis of species distribution
The gridded space for conducting the analyses of species distribution was a cell size of
40 m × 40 m. To visualize, the logistic output of probability of presence was masked by
all river network boundaries in the study area.
SSN objects for analysis of mussel abundance
A spatial stream network (SSN) object was created to analyse the geostatistical mixed
models on stream networks. The SSN object contains the topological relationships, the
data regarding spatial weights and the covariates for the observed sites (Peterson & Ver
Hoef, 2014). The SSN object must be built before data can be analysed with the SSN package (Ver Hoef et al., 2014) in R (R Development Core Team, 2010). We created an SSN
object that contains the 20 stream networks of the study area by using STARS (Peterson
& Ver Hoef, 2014) geoprocessing toolsets. Watershed area was used to calculate spatial
weights. Covariate values for the abiotic and biotic predictors variables described above
were extracted for each river pixel of non-zero mussel abundance. For a detailed description of how to create an SSN object, see Peterson & Ver Hoef (2014).
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S. Lois et al.
Biotic interactions in river networks
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