Appendix S1 Plots of variables, residuals, autocorrelation and colour maps.
CONTENTS:
1) PREDICTORS OF SPECIES RICHNESS: SOURCES AND PATTERNS
Figure A Island size
Figure B Distance to continental Asia
Figure C Altitudinal gradient on islands
Figure D Average precipitation (dry years)
Figure E Seasonality
Figure F Large rain forest blocks
See main text (fig. 2) for Biogeographic regions
2) RESIDUALS OF GLM ANALYSIS
Figure H Correlation with latitude, longitude and species richness
3) SPATIAL AUTOCORRELATION OF DATA: MORAN’S I – CORRELOGRAM
Figure I Species richness (all and subsets)
Figure J Predictor variables
4) LOCATION OF DISTRIBUTION CENTRES
Figure K Distribution centres of widespread vs. restricted species
5) COLOUR MAPS OF ESTIMATED SPECIES RICHNESS
Figure L All Sphingidae
Figure M Subfamilies Macroglossinae and Sphinginae
Figure N Restricted and widespread species
REFERENCES
1) PREDICTORS OF SPECIES RICHNESS: PATTERNS AND SOURCES
140
120
100
80
60
Est. species richness
40
20
0
0.001
0.010
0.100
1.000
10.000
100.000
Island size [10.000km2]
Figure A Log-scaled island areas and estimated species richness of all Sphingidae on 114 islands. Island areas were
calculated from the world map in ArcView 3.2a (2000), using an extension of Hooge et al. (1999). Back to Content
140
120
100
80
60
Est. species richness
40
20
0
0
1000
2000
3000
4000
5000
6000
7000
8000
Distance to continental Asia [km]
Figure B Distance to continental Asia and estimated species richness of all Sphingidae on 114 islands. The closest
distances between islands and the coast of Southeast-Asia were calculated with a program by Hooge et al. (1999), using
a UTM (zone 50) projection of the world map in ArcView 3.2a (2000). Back to Content
140
120
100
80
60
Est. species richness
40
20
0
0
500
1000
1500
2000
2500
3000
3500
Elevational gradient [m]
Figure C Altitudinal gradient on islands and estimated species richness of all Sphingidae on 114 islands. Gradients were
measured as the highest altitude class (as evident from the graph) on the 3D-world map 2.0 (http://www.longgame.com/).
I.e., assignment to the class “1000” represents islands with mountains ≥1000m, but less than 2000m. Due to the
resolution of the map, exceedingly high peaks (e.g. Puncak Jaya >5000m in New Guinea) are not covered by data. Back to
Content
140
120
100
80
60
Est. species richness
40
20
0
0
1000
2000
3000
4000
5000
6000
Average rainfall in dry years [mm]
Figure D Average precipitation in dry years and estimated species richness of all Sphingidae on 114 islands. Precipitation
data were taken from a map on Asian climate available at http://www.esri.com/, using the highest rainfall-category within
an island. The alternatively available data for the relatively wet years did not result in a substantially different pattern. Back
to Content
90
80
70
60
50
40
30
Est. species richness
20
10
0
Semi-evergreen
Evergreen
Mean
Mean±SE
Mean±SD
Seasonality
Figure E Seasonality of 114 islands was assessed from a map of large-scale vegetation zones (available at
http://www.esri.com/), consisting largely of “evergreen forest” and “semi-evergreen forest” in our study region. Minor
vegetation types, such as ‘interzonals’ (e.g. river floodplains) or savannahs (in southern New Guinea) were ignored. The
data provide mainly a distinction between the perhumid islands and those with monsoon-seasonality in the northern parts
of the Philippines and the Lesser Sunda Islands. If different zones occurred within one island (e.g. West Java vs. Central
and East Java) we assigned the “evergreen” climate, as we know of species likely to be limited by drought, but not viceversa. Back to Content
120
100
80
60
40
Est. species richness
20
Mean
Mean±SE
Mean±SD
0
No rainforest
Rainforest
Figure F The presence or absence of large rain forest blocks was mainly assessed from maps in Monk et al. (1997) and
Stibig et al. (2002). Back to Content
2) RESIDUALS OF GLM ANALYSIS
r2
<0.001
p = 0.83
0
5 10 15 20 25
170
Longitude [o]
160
150
140
130
120
110
100
Residuals
30
20
10
0
-10
-20
-30
-40
r2 <0.001
p = 0.91
90
Latitude [o]
30
20
10
0
-10
-20
-30
-40
80
Residuals
Residuals
30
20
10
0
-10
-20
-30
-40
-15 -10 -5
r2 = 0.26, p <0.001
0
20
40
60
80
100
120
140
Est. species richness
Figure H Correlations of GLM residuals (for all Sphingidae) with latitude, longitude and sphingid species richness. There
is no obvious geographic pattern in residuals, but the model consistently overestimates species-poor islands, whereas it
underestimates species-rich islands. Back to Content
3) SPATIAL AUTOCORRELATION OF DATA: MORAN’S I – CORRELOGRAMS
1.0
0.5
1.0
All Sphingidae
0.5
1.0
Subf amily
Macroglossinae
1.0
Subf amily
Smerinthinae
0.5
0.5
0.0
0.0
0.0
0.0
-0.5
-0.5
-0.5
-0.5
-1.0
-1.0
500 1500 2500
1000 2000
-1.0
500 1500 2500
1000 2000
1.0
Moran's I
0.5
-1.0
500 1500 2500
1000 2000
1.0
Restricted
(lower 25%)
0.0
1.0
0.5
Medium-restricted
(25-50%)
0.0
-0.5
-0.5
-1.0
-1.0
500 1500 2500
1000 2000
500 1500 2500
1000 2000
1.0
Medium-widespread
(50-75%)
0.5
0.5
0.0
0.0
-0.5
-0.5
-1.0
500 1500 2500
1000 2000
Subf amily
Sphinginae
Widespread
(upper 25%)
-1.0
500 1500 2500
1000 2000
Distance [km]
500 1500 2500
1000 2000
p <0.05
Non-sign.
Figure I Correlograms of Moran’s I as a measure of spatial autocorrelation of sphingid species richness (complete and all
subsets). The smallest spatial scale of analysis, 500 km, is approximately four times the median of an island’s nearest
neighbour; the maximum scale of 2,500 km represents ca. 30% of the total longitudinal and >60% of the total latitudinal
extent of the study region. Moran’s I were calculated with Rookcase (Sawada 1999), using UTM coordinates of island
centres. Significance tests are Bonferroni-corrected. Back to Content
1.0
0.5
Biogeogr. region
0.0
1.0
1.0
0.5
0.5
0.0
-0.5
-0.5
-1.0
1.0
0.5
0.0
Distance to Asia
-1.0
500 1000 1500 2000 2500
-0.5
-1.0
500 1000 1500 2000 2500
1.0
Altitudinal range
0.5
500 1000 1500 2000 2500
1.0
Precipitation
0.5
0.0
0.0
0.0
-0.5
-0.5
-0.5
-1.0
-1.0
Moran's I
500 1000 1500 2000 2500
log(Island area)
Seasonality
-1.0
500 1000 1500 2000 2500
500 1000 1500 2000 2500
1.0
0.5
0.0
-0.5
Rainf orests
-1.0
500 1000 1500 2000 2500
Distance [km]
Figure J Correlograms of Moran’s I as a measure of spatial autocorrelation of interval-scaled predictor variables. The
smallest spatial scale of analysis, 500 km, is approximately four times the median of an island’s nearest neighbour; the
maximum scale of 2,500 km represents ca. 30% of the total longitudinal and >60% of the total latitudinal extent of the
study region. Moran’s I were calculated with Rookcase (Sawada 1999), using UTM coordinates of island centres.
Significance tests are Bonferroni-corrected. Back to Content
4) LOCATION OF DISTRIBUTION CENTRES
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Restricted
Widespread
Wallace's line
Weber's line
1000
2000
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3000
4000 Kilometers
Figure K Location of distribution centres for widespread and restricted range size quartiles of Malesian species (map in
geographic projection). Distribution centres were estimated as means of latitudinal and longitudinal extremes (this is far
easier than calculating centroids for fragmented ranges, whereas a kernel-approach on original data would be heavily
biased by the popularity of sampling sites). Distribution centres of widespread species are clearly more west than those of
restricted species (see main text for statistical testing). Back to Content
5) COLOUR MAPS OF ESTIMATED SPECIES RICHNESS
Sphingidae - species richness
141-160
128-140
110-127
92-109
74-91
57-73
39-56
21-38
3-20
Figure L Species richness of all Sphingidae species in Southeast Asia. Patterns were derived from overlaying
distribution estimates of all species (see Beck & Kitching 2004 for details). Note that patterns within islands (e.g. higher
species richness in the mountainous regions of Borneo and New Guinea) are ignored in the analysis, where always
island totals were used. Back to Content
MACROGLOSSINAE
Estimated species richness
72-88
54-71
36-53
18-35
2-17
N
W
E
S
0
1000
2000
3000
4000 Kilometers
Malaita.shp
Leyte.shp
Leti.shp
Lembata.shp
Lavongai.shp
Larat.shp
Kulambangra.shp
Komodo.shp
Kelang.shp
Kai.shp
Jolo.shp
Java.shp
Isa bel.shp
Timor.shp
Ticao.shp
Tawitawi.shp
Tanimbar.shp
Sumbawa.shp
Sumba.shp
Sumatra.shp
SMERINTHINAE
Estimated species richness
30-34
22-29
15-21
7-14
1-6
N
W
E
S
0
1000
2000
3000
4000 Kilometers
Ferguson.shp
Dyau l.shp
Duma ran.shp
Dinagat.shp
Damp ier.shp
Dammer.shp
Choiseul.shp
Cebu.shp
Catanduanes.shp
Calayan.shp
Calamian.shp
C de mindanao.shp
C de luzon.shp
Buton.shp
Buru.shp
Figure M Estimated species richness for the subfamilies Macroglossinae and Smerinthinae. Data for the Sphinginae is
not shown as this subfamily is to poor in species to exhibit conclusive patterns. Back to Content
Simeuloe.shp
Sibuyan.shp
Shortland.shp
Sermatta.shp
RESTRICTED SPECIES
Estimated species richness
20
8-9
6-7
4-5
2-3
0-1
N
W
E
S
0
1000
2000
3000
4000 Kilometers
Leyte.shp
Leti.shp
Lembata.shp
Lavongai.shp
Larat.shp
Kulambangra.shp
Komodo.shp
Kelang.shp
Kai.shp
Burias.shp
Bougainville.shp
Borneo.shp
WIDESPREAD SPECIES
Estimated species richness
57-70
43-56
29-42
15-28
1-14
N
W
E
S
0
1000
2000
3000
4000 Kilometers
Figure N Estimated species richness for restricted and widespread species, defined as lower and upper quartile of
species’ global distribution rank (see main text for details). Back to Content
REFERENCES
ArcView GIS 3.2a (2000) Computer program and manual. Environmental Systems Research Institute (ESRI), Redlands
(California). http://www.esri.com.
Beck, J. & Kitching, I.J. (2004) The Sphingidae of Southeast-Asia, incl. New guinea and the Solomon Islands.
http://www.sphingidae-sea.biozentrum.uni-wuerzburg.de
Hall, R. (1998) The plate tectonics of Cenozoic SE Asia and the distribution of land and sea. Biogeography and geological
evolution of South East Asia (ed. by R. Hall & J.D. Holloway), pp 99-131. Backhuys, Leiden.
Holloway, J.D. (1987) Lepidoptera patterns involving Sulawesi: what do they indicate of past geography? Biogeographical
evolution of the Malay archipelago (ed. by T.C. Whitmore), pp 103-118. Clarendon Press, Oxford.
Holloway, J.D. (2003) Biological images of geological history: through a glass darkly or brightly face to face? Journal of
Biogeography, 30, 165-179.
Hooge, P. N,. Eichenlaub, W. & Solomon, E. (1999) The animal movement program. USGS, Alaska Biological Science
Center.
Monk, K.A., de Frete, Y., Reksodiharjo-Lilley, G. (1997) The ecology of Nusa Tenggara and Maluku. The Ecology of
Indonesia series V. Periplus Editions Ltd., Hong Kong.
Sawada, M. (1999) Rookcase: an Excel 97/2000 Visual Basic (VB) Add-In for exploring global and local spatial
autocorrelation. Bulletin of the Ecological Society of America, 80, 231-234.
Stibig, H. J., Beuchle, R. & Janvier, P. (2002) Forest cover maps of insular Southeast-Asia 1:5500000 derived from
SPOT-VEGETATION satellite images. TREES Publication Series D: Thematic outputs No. 3. European
Commission Joint Research Centre.
van Welzen, P.C., Turner, H. & Hovenkamp, P. (2005) Historical biogeography of Southeast-Asia and the West Pacific, or
the generality of unrooted area networks as historical biogeographic hypotheses. Journal of Biogeography, 30,
181-192.
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