Paleotropics
Neotropics
Table S1. List of data sets used for assessing the magnitude of correlations for bat species
richness and species composition, respectively, between full data sets and species subsets with
different numbers of species deleted either at random, or according to their rarity in the
respective assemblage.
1
Country
Location1
Mexico
Mexico
Mexico
Costa Rica
Panama
Panama
Panama
Panama
Panama
Panama
Panama
Trinidad
Trinidad
French Guiana
Ecuador
Ecuador
Ecuador
Brazil
Brazil
Brazil
Bolivia
Vietnam
Ivory Coast
Ivory Coast
Ivory Coast
Ivory Coast
Madagascar
Yucatan
Yucatan
Chamelaa)
La Selva
Fort Sherman
BCNM
BCNM
BCNM
BCI
BCI
Soberanía
Victoria-Mayaro
Victoria-Mayaro
St. Eugène
Podocarpus
Tiputini
Tiputini
Una
Roncador b)
BDFFP
Yungas de La Paz
Kim Hy
Comoé c)
Comoé c)
Taï
Taï
Bemaraha a)
Sampling
method2
GN
AS
GN
GN
GN
GN
CN
AS
GN
CN
GN
GN
CN
GN
GN
GN
CN
GN
GN
GN
GN
GN
GN
CN
GN
CN
GN
Sobs3
20
17
22
36
36
29
34
20
36
35
38
34
24
36
27
49
26
19
21
40
22
22
35
39
18
21
8
No. of rare
species4
13
2
13
18
25
18
23
10
22
21
25
24
9
16
15
28
10
12
9
26
14
12
25
25
5
14
2
forest/habitat type other than tropical wet/moist forest: a) tropical dry forest, b) Cerrado, c) biome transition
(forest-savanna mosaic)
BCNM = Barro Colorado Nature Monument, BCI = Barro Colorado Island, BDFFP = Biological Dynamics of
Forest Fragments Project
2
sampling methods: GN = ground nets, CN = (sub)canopy nets, AS = acoustic sampling
3
Sobs: number of species observed
4
species representing < 1% of total relative abundance
Fig. S1. The magnitude of correlations across sites between the full dataset and subsets of
data for species richness SR (a), and for species composition as represented by the ordination
scores of the first axis of a detrended correspondence analysis DCA1 (b) and the Jaccard
index J (c). Results shown comprise datasets from 19 tropical localities based on ground-level
mist netting. Subsets were generated by deleting different numbers of species either at random
or based on species rarity. The bold line connects median correlations r(SUB x FULL) for 100
randomly chosen subsets at each of five species pool sizes; the broken lines indicate upper
and lower 95th percentile correlations. Open circles denote non-random subset correlations,
with species eliminated based on up to three abundance thresholds, whenever applicable
(relative abundance < 0.1% ( ), < 0.5% ( ), < 1% ( )).
Una − Brazil
Victoria−Mayaro − Trinidad
Yucatan − Mexico
Yungas − Bolivia
Sherman − Panama
Soberanía − Panama
St.Eugène − French Guiana
Taï − Ivory Coast
Tiputini − Ecuador
Comoé − Ivory Coast
Kim Hy − Vietnam
La Selva − Costa Rica
Podocarpus − Ecuador
Roncador − Brazil
BCI − Panama
BCNM − Panama
BDFFP − Brazil
Bemaraha − Madagascar
Chamela − Mexico
(a)
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
r(SRSUBxSRFULL)
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
10
20
30
40
10
20
30
40
10
20
30
Number of species
40
10
20
30
40
10
20
30
40
Una − Brazil
Victoria−Mayaro − Trinidad
Yucatan − Mexico
Yungas − Bolivia
Sherman − Panama
Soberanía − Panama
St. Eugène − French Guiana
Taï − Ivory Coast
Tiputini − Ecuador
Comoé − Ivory Coast
Kim Hy − Vietnam
La Selva − Costa Rica
Podocarpus − Ecuador
Roncador − Brazil
BCI − Panama
BCNM − Panama
BDFFP − Brazil
Bemaraha − Madagascar
Chamela − Mexico
(b)
1.0
0.8
0.6
0.4
0.2
0.0
1.0
r(DCA1SUBxDCA1FULL)
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
10
20
30
40
10
20
30
40
10
20
30
Number of species
40
10
20
30
40
10
20
30
40
Una − Brazil
Victoria−Mayaro − Trinidad
Yucatan − Mexico
Yungas − Bolivia
Sherman − Panama
Soberanía − Panama
St. Eugène − French Guiana
Taï − Ivory Coast
Tiputini − Ecuador
Comoé − Ivory Coast
Kim Hy − Vietnam
La Selva − Costa Rica
Podocarpus − Ecuador
Roncador − Brazil
BCI − Panama
BCNM − Panama
BDFFP − Brazil
Bemaraha − Madagascar
Chamela − Mexico
(c)
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
r(JSUBxJFULL)
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
10
20
30
40
10
20
30
40
10
20
30
Number of species
40
10
20
30
40
10
20
30
40
Fig. S2. The magnitude of correlations across sites between the full data set and subsets of
data for species richness SR (a), and for species composition as represented by the ordination
scores of the first axis of a detrended correspondence analysis DCA1 (b) and the Jaccard
index J (c). Results shown comprise 8 data sets based on canopy-level mist netting or acoustic
sampling (AS). Subsets were generated by deleting different numbers of species either at
random or based on species’ rarity. The bold line connects median correlations r(SUB x FULL)
for 100 randomly chosen subsets at each of five species pool sizes; the broken lines show
upper and lower 95th percentiles. Open circles denote non-random subset correlations, with
species eliminated based on up to three abundance thresholds, whenever applicable (relative
abundance < 0.1% ( ), < 0.5% ( ), < 1% ( )).
(a)
r(SRSUBxSRFULL)
1.0
0.8
0.6
0.4
0.2
0.0
Tiputini − Ecuador
Victoria−Mayaro − Trinidad
Comoé − Ivory Coast
Taï − Ivory Coast
BCI − Panama
BCNM − Panama
AS−BCNM − Panama
AS−Yucatan − Mexico
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
10
15
20
25
30
35
10
15
Number of species
20
25
30
35
(b)
r(DCA1SUBxDCA1FULL)
1.0
0.8
0.6
0.4
0.2
0.0
Tiputini − Ecuador
Victoria−Mayaro − Trinidad
Comoé − Ivory Coast
Taï − Ivory Coast
BCI − Panama
BCNM − Panama
AS−BCNM − Panama
AS−Yucatan − Mexico
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
10
15
20
25
30
35
10
15
Number of species
20
25
30
35
(c)
r(JSUBxJFULL)
1.0
0.8
0.6
0.4
0.2
0.0
Tiputini − Ecuador
Victoria−Mayaro − Trinidad
Comoé − Ivory Coast
Taï − Ivory Coast
BCI − Panama
BCNM − Panama
AS−BCNM − Panama
AS−Yucatan − Mexico
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
10
15
20
25
30
35
10
15
Number of species
20
25
30
35