Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S1: Overview of a number of community assembly studies that explicitly
address scaling. Main findings are summarized together with information on whether
organismic scales (orga.) or spatial (sp.) and environmental (env.) scales had been
varied and on whether diversity (D) was estimated based on functional (f) or
phylogenetic (p) information.
Orga.
Phylogenetic and
strata classes
Sp. and env.
Environmental extent
of communities
D
p
Main results
More clustering at larger scales due
to a shift in niche evolution
Phylogenetic
Spatial extent of
species pools
p
More clustering at larger scales
Phylogenetic and
size classes
Spatial extent of
communities
p
More overdispersion at finer scales
None
Spatial extent of
communities
p
Almost no scaling effect (slightly
clustered to random signal for
increasing scale) but different
patterns in different habitats
p
More overdispersion at finer scales
Phylogenetic
None
None
Spatial and
environmental extent
of communities
P
More clustering at larger scales
None
Spatial extent of
communities
p, f
More overdispersion at finer scales
Size classes
Spatial extent of
communities
f
Mixed
p
Overall clustering, stronger at larger
scale (and in temperate regions)
Ecologically informed species pools
None
Spatial extent of
communities
p
Mixed
None
Spatial extent of
species pools
p
None
Spatial extent of
communities
p
No effect (suggested that
environmental extent is more
important)
From overdispersion to clustering for
increasing scales
Phylogenetic
None
p
Mixed
None
Spatial extent and
environmental extent
of species pool
f
More clustering at larger
environmental scales; no additional
spatial scale effect
None
Environmental extent
of species pool
f
More clustering at larger scales
Environmental extent
of species pool
f
Trend towards less clustering at
smaller scales
Spatial extent of
communities and
species pools
p, f
No effect for “p”; mixed for “f”
Phylogenetic
None
Reference
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
References
Belmaker, J. & Jetz, W. (2013) Spatial Scaling of Functional Structure in Bird and
Mammal Assemblages. American Naturalist, 181, 464-478.
Carboni, M., Münkemüller, T., Gallien, L., Lavergne, S., Acosta, A. & Thuiller, W. (2013)
Darwin’s naturalization hypothesis: scale matters in coastal plant communities.
Ecography, 36, 560-568.
Cavender-Bares, J., Keen, A. & Miles, B. (2006) Phylogenetic structure of floridian plant
communities depends on taxonomic and spatial scale. Ecology, 87, S109-S122.
Chalmandrier, L., Münkemüller, T., Gallien, L., De Bello, F., Mazel, F., Lavergne, S. &
Thuiller, W. (accepted) A family of null models to distinguish between habitat
filtering and biotic interactions in functional diversity patterns. Journal of
Vegetation Science.
Harmon-Threatt, A. N. & Ackerly, D. D. (2013) Filtering across Spatial Scales: Phylogeny,
Biogeography and Community Structure in Bumble Bees. Plos One, 8.
Kembel, S. W. & Hubbell, S. P. (2006) The phylogenetic structure of a neotropical forest
tree community. Ecology, 87, S86-S99.
Kraft, N. J. B. & Ackerly, D. D. (2010) Functional trait and phylogenetic tests of
community assembly across spatial scales in an Amazonian forest. Ecological
Monographs, 80, 401-422.
Kraft, N. J. B., Valencia, R. & Ackerly, D. D. (2008) Functional traits and niche-based tree
community assembly in an amazonian forest. Science, 322, 580-582.
Lessard, J. P., Borregaard, M. K., Fordyce, J. A., Rahbek, C., Weiser, M. D., Dunn, R. R. &
Sanders, N. J. (2012) Strong influence of regional species pools on continent-wide
structuring of local communities. Proceedings of the Royal Society B-Biological
Sciences, 279, 266-274.
Murria, C., Bonada, N., Arnedo, M. A., Zamora-Munoz, C., Prat, N. & Vogler, A. P. (2012)
Phylogenetic and ecological structure of Mediterranean caddisfly communities at
various spatio-temporal scales. Journal of Biogeography, 39, 1621-1632.
Slingsby, J. A. & Verboom, G. A. (2006) Phylogenetic relatedness limits co-occurrence at
fine spatial scales: Evidence from the schoenoid sedges (Cyperaceae : Schoeneae)
of the Cape Floristic Region, South Africa. American Naturalist, 168, 14-27.
Swenson, N. G. & Enquist, B. J. (2009) Opposing assembly mechanisms in a Neotropical
dry forest: implications for phylogenetic and functional community ecology.
Ecology, 90, 2161-2170.
Swenson, N. G., Enquist, B. J., Pither, J., Thompson, J. & Zimmerman, J. K. (2006) The
problem and promise of scale dependency in community phylogenetics. Ecology,
87, 2418-2424.
Swenson, N. G., Enquist, B. J., Thompson, J. & Zimmerman, J. K. (2007) The influence of
spatial and size scale on phylogenetic relatedness in tropical forest communities.
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Villalobos, F., Rangel, T. F. & Diniz, J. a. F. (2013) Phylogenetic fields of species: crossspecies patterns of phylogenetic structure and geographical coexistence.
Proceedings of the Royal Society B-Biological Sciences, 280.
Wang, J. J., Soininen, J. & Shen, J. (2013) Habitat species pools for phylogenetic structure
in microbes. Environmental Microbiology Reports, 5, 464-467.
Willis, C. G., Halina, M., Lehman, C., Reich, P. B., Keen, A., Mccarthy, S. & Cavender-Bares, J.
(2010) Phylogenetic community structure in Minnesota oak savanna is
influenced by spatial extent and environmental variation. Ecography, 33, 565577.
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S2: Details for the method description.
Merging of two databases
To ensure consistency between the two merged databases (Alps Vegetation Database
and French National Alpine Botanical Conservatory database), we applied the following
set of four filters: 1- we kept only geo-referenced community plots with a precision
higher than 500 m. 2- we discarded community plots for which the sampling date was
prior to 1980 in order to keep contemporary data only. 3- we restricted the analyses to
community-plots for which an estimation of abundance-dominance was available in
order to use abundance-weighted diversity metrics. Within each community-plot,
species abundances were recorded using a cover scheme with six classes (1: less than
1%; 2: from 1 to 5%; 3: from 5 to 25%; 4: from 25 to 50%; 5: from 50 to 75%; 6: more
than 75%; Braun-Blanquet, 1946) and were converted to estimated abundances using
the mean percentage within a class (i.e. 0.5, 3, 15, 37.5, 62.5 and 87.5%). 4- we kept only
community plots with more than one species and for which the species that contributed
80% or more to the total abundance cover were represented in the phylogenetic tree
(see below). The outcome of such a filtering procedure led us to select a total of 18,919
community plots and 3,081 species belonging to 773 genera and 135 families.
Land cover type classification
Land cover classification for each of the selected community plot was extracted from the
Corine
Land
Cover
database
(CORINE
2006,
http://www.epa.ie/whatwedo/assessment/land/corine/) at a 250-m resolution.
CORINE is a European map of the environmental landscape based on interpretation of
satellite images. It provides comparable digital maps of land cover for most European
countries. Because CORINE was not available for Switzerland, a reclassification of the
Swiss land cover map at the same resolution was carried out to match the definition of
CORINE. To restrict the number of different land cover types and to have a classification
better adapted to the Alpine context (better delineation of sparsely-vegetated or bareground land cover types) we re-classified the CORINE land cover data (details in Table
2). The final classification for the entire Alps thus consisted of 145,683 homogenous and
continuous polygons representing 11 land cover types (Table 2).
Phylogeny
The genus-level phylogeny of the Alpine plants was constructed following the workflow
proposed by Roquet et al. . We downloaded from Genbank three conserved
chloroplastic regions (rbcL, matK and ndhF) plus eight regions for certain families or
orders (atpB, ITS, psbA-trnH, rpl16, rps4, rps4-trnS, rps16, trnL-F), which were aligned
separately by taxonomic clustering. All sequences were aligned with three methods ,
then the best alignment for each region was selected and depurated with TrimAl after
being visually checked. Phylogenetic inference by maximum-likelihood (ML) was
conducted with RAxML applying a supertree constraint at the family-level based on
Davies et al. and Moore et al. . The best ML tree was dated by penalized-likelihood using
r8s and 25 fossils for calibration extracted from Smith et al. and Bell et al. .
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Assessing statistical significance in community structure
Different randomization schemes (“null models” in the following) are necessary for
different species pools when the distribution of frequencies of occurrence and/or
abundances is not random in the phylogenetic tree of the species pool. We used the
abundance phylogenetic divergence index (APD) to decide whether species frequencies
of occurrences or abundances should be taken into account when simulating random
communities . For each species pool, we calculated the APD index on the basis of species
frequencies of occurrences to detect a phylogenetic signal of frequently vs. rarely
occurring species (APDO) and on the basis of mean local relative abundances (APDA) to
detect a phylogenetic signal of locally highly abundant vs. rare species (see Appendix
S3). If neither APDO nor APDA were significant we simply randomized all species of the
species pool in the phylogenetic tree . If APDO was significant we randomized species in
a constrained way so that only species with similar frequencies of occurrence were
permuted. If APDA was significant we only permuted species with similar mean local
relative abundances. If APDO and APDA were both significant we randomized only
species with similar summed relative abundances across the species pool. To constrain
the randomizations as detailed above, species were grouped into frequency-ofoccurrence classes, mean-local-relative-abundance classes or summed-relativeabundance classes and we applied randomizations within these classes. Class
boundaries were changed for each of the 999 repetitions of the null model to avoid that
similar species at different sides of borders between classes would always be in different
classes .
To test whether 999 repetitions were sufficient for stable results, we conducted a power
analysis by repeating the null model analysis for grassland community plots and the
largest scale choice and thus the largest species pool, 30 times. We found that αdiversity-percentiles varied little within community plots (see Appendix S3) and thus
concluded that potential differences between different species pools could be attributed
to the species pool characteristics and not to the inherent uncertainties in a single
randomization scheme.
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Carboni, M., Münkemüller, T., Gallien, L., Lavergne, S., Acosta, A. & Thuiller, W. (2013)
Darwin’s naturalization hypothesis: scale matters in coastal plant communities.
Ecography, 36, 560-568.
Cavender-Bares, J., Keen, A. & Miles, B. (2006) Phylogenetic structure of floridian plant
communities depends on taxonomic and spatial scale. Ecology, 87, S109-S122.
Chalmandrier, L., Münkemüller, T., Gallien, L., de Bello, F., Mazel, F., Lavergne, S. &
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Thuiller, W. (accepted) A family of null models to distinguish between habitat
filtering and biotic interactions in functional diversity patterns. Journal of
Vegetation Science,
Davies, T.J., Barraclough, T.G., Chase, M.W., Soltis, P.S., Soltis, D.E. & Savolainen, V. (2004)
Darwin's abominable mystery: Insights from a supertree of the angiosperms.
Proceedings of the National Academy of Sciences, 101, 1904–1909.
Edgar, R.C. (2004) MUSCLE: multiple sequence alignment with high accuracy and high
throughput. Nucleic Acids Res., 32, 1792–1797.
Hardy, O.J. (2008) Testing the spatial phylogenetic structure of local communities:
statistical performances of different null models and test statistics on a locally
neutral community. Journal of Ecology, 96, 914-926.
Harmon-Threatt, A.N. & Ackerly, D.D. (2013) Filtering across Spatial Scales: Phylogeny,
Biogeography and Community Structure in Bumble Bees. Plos One, 8
Katoh, K., Kuma, K., Toh, H. & Miyata, T. (2005) MAFFT version 5: improvement in
accuracy of multiple sequence alignment. Nucleic Acids Res., 33, 511–518.
Kembel, S.W. & Hubbell, S.P. (2006) The phylogenetic structure of a neotropical forest
tree community. Ecology, 87, S86-S99.
Kraft, N.J.B. & Ackerly, D.D. (2010) Functional trait and phylogenetic tests of community
assembly across spatial scales in an Amazonian forest. Ecological Monographs,
80, 401-422.
Kraft, N.J.B., Valencia, R. & Ackerly, D.D. (2008) Functional traits and niche-based tree
community assembly in an amazonian forest. Science, 322, 580-582.
Lassmann, T. & Sonnhammer, E.L. (2005) Kalign - an accurate and fast multiple
sequence alignment algorithm. BMC Bioinformatics, 6, 289-298.
Lessard, J.P., Borregaard, M.K., Fordyce, J.A., Rahbek, C., Weiser, M.D., Dunn, R.R. &
Sanders, N.J. (2012) Strong influence of regional species pools on continent-wide
structuring of local communities. Proceedings of the Royal Society B-Biological
Sciences, 279, 266-274.
Moore, M.J., Soltis, P.S., Bell, C.D., Burleigh, J.G. & Soltis, D.E. (2010) Phylogenetic analysis
of 83 plastid genes further resolves the early diversification of eudicots.
Proceedings of the National Academy of Sciences, 107, 4623-4628.
Murria, C., Bonada, N., Arnedo, M.A., Zamora-Munoz, C., Prat, N. & Vogler, A.P. (2012)
Phylogenetic and ecological structure of Mediterranean caddisfly communities at
various spatio-temporal scales. Journal of Biogeography, 39, 1621-1632.
Pavoine, S., Love, M.S. & Bonsall, M.B. (2009) Hierarchical partitioning of evolutionary
and ecological patterns in the organization of phylogenetically-structured species
assemblages: application to rockfish (genus: Sebastes) in the Southern California
Bight. Ecology Letters, 12, 898-908.
Roquet, C., Thuiller, W. & Lavergne, S. (2013) Building megaphylogenies for
macroecology: taking up the Challenge. Ecography, 36, 013–026.
Sanderson, M.J. (2003) r8s: inferring absolute rates of molecular evolution and
divergence times in the absence of a molecular clock. Bioinformatics, 19, 301-302.
Slingsby, J.A. & Verboom, G.A. (2006) Phylogenetic relatedness limits co-occurrence at
fine spatial scales: Evidence from the schoenoid sedges (Cyperaceae : Schoeneae)
of the Cape Floristic Region, South Africa. American Naturalist, 168, 14-27.
Smith, S.A., Beaulieu, J.M. & MJ., D. (2010) An uncorrelated relaxed-clock anaysis
suggests an earlier origin for flowering plants. Proceedings of the National
Academy of Sciences, 107, 5897-5902.
Stamatakis, A., Hoover, P. & Rougemont, J. (2008) A Rapid Bootstrap Algorithm for the
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RAxML Web-Servers. Systematic Biology, 75, 758–771.
Swenson, N.G. & Enquist, B.J. (2009) Opposing assembly mechanisms in a Neotropical
dry forest: implications for phylogenetic and functional community ecology.
Ecology, 90, 2161-2170.
Swenson, N.G., Enquist, B.J., Thompson, J. & Zimmerman, J.K. (2007) The influence of
spatial and size scale on phylogenetic relatedness in tropical forest communities.
Ecology, 88, 1770-1780.
Swenson, N.G., Enquist, B.J., Pither, J., Thompson, J. & Zimmerman, J.K. (2006) The
problem and promise of scale dependency in community phylogenetics. Ecology,
87, 2418-2424.
Villalobos, F., Rangel, T.F. & Diniz, J.A.F. (2013) Phylogenetic fields of species: crossspecies patterns of phylogenetic structure and geographical coexistence.
Proceedings of the Royal Society B-Biological Sciences, 280
Wang, J.J., Soininen, J. & Shen, J. (2013) Habitat species pools for phylogenetic structure
in microbes. Environmental Microbiology Reports, 5, 464-467.
Willis, C.G., Halina, M., Lehman, C., Reich, P.B., Keen, A., McCarthy, S. & Cavender-Bares, J.
(2010) Phylogenetic community structure in Minnesota oak savanna is
influenced by spatial extent and environmental variation. Ecography, 33, 565577.
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S3: Distribution of α-diversity-percentiles within grassland community plots
across 30 repetitions of the same scale choice, i.e. the largest spatial and environmental
extents and the broadest organismic scale (one species pool). Each boxplot shows the
distribution of α-diversity-percentiles across the 30 repetitions. Community plots are
ranked according to the median position of their observed α-diversity-percentiles.
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S4: Overview of species pool structures (resulting from the different scale
choices) with their number of species (no species), and the abundance phylogenetic
deviation both for occurrence frequency (APDO) and average abundance (APDA) (‘0’:
random, ‘-‘: clustered, p<0.025, ‘+’: over-dispersed, p<0.975).
Lower stratum
All data
Grassland
All
polygons
Focal
polygon
Bare-rock
All
polygons
Focal
polygon
Sparsely
vegetated
All
polygons
Focal
polygon
All strata
All
species
Only
herbaceous
Only
Asteraceae
All
species
Only
herbaceous
Only
Asteraceae
no species
APDO
APDA
no species
3043
+
0
2540
2584
+
0
2155
427
0
0
362
3081
+
+
2567
2585
+
0
2155
427
0
0
362
APDO
APDA
0
0
0
0
0
0
0
+
0
0
0
0
no species
695
601
88
707
601
88
APDO
APDA
no species
0
0
1168
0
0
986
0
0
175
0
0
1195
0
0
986
0
0
175
APDO
APDA
0
-
0
-
0
0
0
0
0
-
0
0
no species
257
216
38
257
216
38
APDO
APDA
no species
0
0
1604
0
0
1336
0
0
233
0
0
1651
0
0
1336
0
0
233
APDO
APDA
0
-
0
-
0
0
0
0
0
-
0
0
no species
268
231
38
270
231
38
APDO
APDA
0
-
0
-
0
0
0
0
0
-
0
0
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S5: Regression and partial regression analyses to explain the influence of
scale choices: (a) all scale choices (accordingly 18 species pools) and (b) removing the
organismic scale choices that only include Asteraceae species (no family-only scale
choices to show remaining effects after removing the most influential scale choice, 12
species pools remain). Organismic scale reduction includes phylogenetic constraints
(phylogeny), growth form constraints (growth form) and vegetation stratum constraints
(veg. stratum). Environmental and spatial scale reductions include a decrease in
environmental extent (focus on one land cover type) and a decrease in spatial extent
(space). In a first step, we calculated observed-diversity-residuals (Qc,α_res: residuals of
the regression of observed alpha diversity, Qc,α, against community ID, IDcom) and
percentile-residuals (perc-res.: residuals of the regression of α-diversity-percentiles
against community plot ID, IDcom). In a second step, we regressed community
delimitation and scales on the gamma diversity in the regional species pool (Qc, γ) and on
the observed-diversity-residuals. In a final step, we studied the influence of all variables
on percentile-residuals.
(a) All scale choices
Resp.
variable
Qc,α
perc
perc_res.
perc_res.
Qc,γ
Qc,γ
Qc,α_res
perc_res.
perc_res.
perc_res.
perc_res.
Explanatory variables
IDcom
IDcom
(phylogeny + growth
form + veg. stratum)^2
space + land cover
(phylogeny + growth
form + veg. stratum)^2
space + land cover
(phylogeny + growth
form + veg. stratum)^2
Qc,γ
Qc,α_res
(Qc,γ + Qc,α_res)^2
(space + land cover +
phylogeny + growth
form + veg. stratum +
Qc,γ + Qc,α_res)^2
Grassland
df
Res.
SE
5066
0.9
5066
0.24
Adj.
R2
0.1
0.53
Bare-rock
df
Res.
SE
1355
0.69
1355
0.19
Adj.
R2
0.24
0.56
Sp. vegetated
df
Res.
SE
3446
0.47
3446
0.19
Adj.
R2
0.19
0.47
5364
5367
0.23
0.23
0.02
0.02
1446
1449
0.16
0.18
0.29
0.02
3666
3669
0.17
0.18
0.14
0.05
5364
5367
0.31
2.05
0.98
0
1446
1449
0.23
1.68
0.98
0.01
3666
3669
0.36
1.85
0.96
0.01
5364
5368
5368
5366
0.53
0.23
0.21
0.19
0.63
0
0.15
0.35
1446
1450
1450
1448
0.41
0.16
0.14
0.14
0.61
0.27
0.41
0.41
3666
3670
3670
3668
0.31
0.17
0.16
0.16
0.54
0.12
0.24
0.24
5345
0.18
0.41
1427
0.14
0.44
3647
0.15
0.33
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
(b) No family-only scale choice
Resp.
variable
Qc,α
perc
perc_res.
perc_res.
Qc,γ
Qc,γ
Qc,α_res
perc_res.
perc_res.
perc_res.
perc_res.
Explanatory variables
IDcom
IDcom
(growth form + veg.
stratum)^2
space + land cover
(growth form + veg.
stratum)^2
space + land cover
(growth form + veg.
stratum)^2
Qc,γ
Qc,α_res
(Qc,γ + Qc,α_res)^2
(space + land cover +
growth form + veg.
stratum + Qc,γ +
Qc,α_res)^2
Grassland
df
Res.
SE
3344
0.12
3344
0.14
Adj.
R2
0.75
0.87
Bare-rock
df
Res.
SE
1049
0.02
1049
0.08
Adj.
R2
0.97
0.91
Sp. vegetated
df
Res.
SE
2486
0.03
2486
0.11
Adj.
R2
0.9
0.79
3644
3645
0.12
0.12
0.09
0.11
1142
1143
0.08
0.07
0
0.14
2708
2709
0.1
0.09
0.04
0.26
3644
3645
0.06
0.07
0.55
0.39
1142
1143
0.07
0.04
0.13
0.71
2708
2709
0.07
0.04
0.21
0.71
3644
3646
3646
3644
0.1
0.13
0.11
0.1
0.28
0
0.32
0.35
1142
1144
1144
1142
0.02
0.07
0.07
0.07
0.13
0.09
0.01
0.11
2708
2710
2710
2708
0.03
0.09
0.09
0.07
0.3
0.18
0.23
0.51
3630
0.1
0.46
1128
0.07
0.19
2694
0.06
0.62
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S6: Distribution of α-diversity-percentiles within bare-rock community plots
across (a) all scale choices and accordingly 18 species pools and (b) removing the
organismic scale choices that only include Asteraceae species (no family-only scale
choices to show remaining effects after removing the most influential scale, 12 species
pools remain). Each boxplot shows the distribution of α-diversity-percentiles across the
tested scale choices. Outliers are not plotted. Community plots are ranked according to
the median position of their observed α-diversity-percentiles. In (a) 2% (15%) of
community plots show a median of α-diversity-percentiles above 0.95 (below 0.05); in
(b) 3% (15%) of community plots show a median of α-diversity-percentiles above 0.95
(below 0.05).
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S7: Distribution of α-diversity-percentiles within sparsely vegetated
community plots across (a) all scale choices and accordingly 18 species pools and (b)
removing the organismic scale choices that only include Asteraceae species (no familyonly scale choices to show remaining effects after removing the most influential scale, 12
species pools remain). Each boxplot shows the distribution of α-diversity-percentiles
across the tested scale choices. Outliers are not plotted. Community plots are ranked
according to the median position of their observed α-diversity-percentiles. In (a) 1%
(10%) of community plots show a median of α-diversity-percentiles above 0.95 (below
0.05); in (b) 1% (11%) of community plots show a median of α-diversity-percentiles
above 0.95 (below 0.05).
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S8: Distribution of α-diversity-percentiles within scale choices across barerock community plots. Each dot in a violin plot represents one of the focal community
plots; black dots identify community plots with significant high or low α-diversitypercentiles, small numbers below (and above) the violin plots give the percentage of
community plots with significant patterns of clustering (or over-dispersion). The width
of each violin plot refers to the density of data points. The colored dots help to visualize
the magnitude of change. Each color identifies one community across different scale
choices. Organismic scale constraints on the x-axis include phylogenetic constraints (all
vs. only Asteraceae family), growth form constraints (all vs. herbaceous species only) and
vegetation stratum constraints (all vs. only lowest stratum). Environmental and spatial
extent constraints on the y-axis include reduced environmental extent (all bare-rock
polygons) and reduced spatial extent (focal bare-rock polygon).
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S9: Distribution of α-diversity-percentiles within scale choices across
sparsely vegetated community plots. Each dot in a violin plot represents one of the focal
community plots; black dots identify community plots with significant high or low αdiversity-percentiles, small numbers below (and above) the violin plots give the
percentage of community plots with significant patterns of clustering (or overdispersion). The width of each violin plot refers to the density of data points. The
colored dots help to visualize the magnitude of change. Each color identifies one
community across different scale choices. Organismic scale constraints on the x-axis
include phylogenetic constraints (all vs. only Asteraceae family), growth form constraints
(all vs. herbaceous species only) and vegetation stratum constraints (all vs. only lowest
stratum). Environmental and spatial extent constraints on the y-axis include reduced
environmental extent (all sparsely vegetated polygons) and reduced spatial extent (focal
sparsely vegetated polygon).
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S10: Interactive effect of -diversity-residuals and phylogenetic constraints
(organismic scale choices that only include Asteraceae species) on percentile-residuals
in grassland communities.
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S11: Visual presentation of the regression and partial regression analyses for
bare-rock community plots with arrows representing the effect of explanatory variables
on response variables and numbers representing adjusted R2 values of the respective
models (cf. Appendix S8 for more details): (a) includes all scale choices (accordingly 18
species pools) and (b) includes all scale choices besides the choices that only include
Asteraceae species (no family-only scale choices to show remaining effects after
removing the most influential scale choice, 12 species pools remain). Organismic scale
constraints include phylogenetic constraints (all vs. only Asteraceae family), growth form
constraints (all vs. herbaceous species only) and vegetation stratum constraints (all vs.
only lowest stratum). Environmental and spatial constraints include land cover types
and spatial extent (cf. Table 1 for more detail). In a first step, we studied the influence of
scale choices on the species pool diversity (Qc, γ) and on the -diversity-residuals
(resid(Qc,α~ IDcom), i.e. residuals of the regression of observed -diversity, Qc,α, against
community plot identity, IDcom). In a second step, we studied the influence of all
variables on percentile-residuals (resid(perc ~ IDcom), i.e. residuals of the regression of
α-diversity-percentiles against IDcom).
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S12: Visual presentation of the regression and partial regression analyses for
sparsely vegetated community plots with arrows representing the effect of explanatory
variables on response variables and numbers representing adjusted R2 values of the
respective models (see Appendix S8 for more details): (a) includes all scale choices
(accordingly 18 species pools) and (b) includes all scale choices besides the choices that
only include Asteraceae species (no family-only scale choices to show remaining effects
after removing the most influential scale choice, 12 species pools remain). Organismic
scale constraints include phylogenetic constraints (all vs. only Asteraceae family),
growth form constraints (all vs. herbaceous species only) and vegetation stratum
constraints (all vs. only lowest stratum). Environmental and spatial constraints include
land cover types and spatial extent (cf. Table 1 for more detail). In a first step, we
studied the influence of scale choices on the species pool diversity (Qc, γ) and on the diversity-residuals (resid(Qc,α~ IDcom), i.e. residuals of the regression of observed diversity, Qc,α, against community plot identity, IDcom). In a second step, we studied the
influence of all variables on percentile-residuals (resid(perc ~ IDcom), i.e. residuals of the
regression of α-diversity-percentiles against IDcom).
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S13: Spearman rank correlations between the median of all α-diversitypercentiles for a community plot (without the focal scale choices) and the α-diversitypercentiles under focal scale choices for bare-rock communities.
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S14: Spearman rank correlations between the median of all α-diversitypercentiles for a community plot (without the focal scale choices) and the α-diversitypercentiles under focal scale choices for sparsely vegetated communities.
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S15: The greatest range of α-diversity-percentiles for each community plot
across all scale choices (open circles), removing the scale choices that only include
Asteraceae species (no family-only scale choices, filled triangles) and for the scale
choices that include only Asteraceae species (family-only designs, filled squares) plotted
against the minimum number of species observed (note that species number may
decrease with the reduction of organismic scales) and the difference in number of
species (when comparing the two sampling designs that led to the highest and lowest αdiversity-percentiles). These plots show that the influence of scale choices on αdiversity-percentiles is not mainly driven by species richness in the community plots.
Münkemüller, T., et al. - Scale decisions can reverse conclusions on community assembly processes.
Appendix S16: The greatest range in α-diversity-percentiles for each community plot
(within the three focal polygons) across all scale choices plotted in space. The size of
points relates to the greatest difference in α-diversity-percentiles. These graphics show
that the uncertainty in α-diversity-percentiles is not mainly driven by the location of
community plots.