Biological Journal of the Linnean Society (2001), 73: 65-79. With 1 figure
doi: l0.1006/bij1.2001.0525, available online a t http;//www.idealibrary.com on
IDE h1@
Correlates of extinction risk of birds from two
Indonesian islands
MAFtTIN J. JONES1*, MA'ITHEW S. SULLIVAN1, STUAFtT J. MARSDEN2 and
MARK D. LINSLEY3
Departments of 'Biological Sciences and 2Environmental and Geographical Sciences,
Manchester Metropolitan University, Chester Street, Manchester M 1 5GD
3Elm Cottage, The Street, Chillesford, Woodbridge IP12 3PU
Received 22 March 2000; accepted for publication 14 February 2001
Size of distributional range, position in the range, body size and diet are some of the ecological traits that may
correlate with local abundance. Evolutionary phenomena such as taxon cycles, acting over much greater time
periods, may also influence abundance and promote species extinction. This paper assesses which of a wide range
of ecological and historic traits best predict the variation in abundance of tropical forest birds on Sumba and Buru
islands in Wallacea (Indonesia). In addition we seek to determine which traits predict species' ability to adapt t o
secondary or logged forest. The most important correlates of both abundance and ability t o transfer were those
related to the evolutionary history of the species within the Wallacean Archipelago and not the traits that were
more directly related to species ecology. These relationships are maintained when allowance is made for phylogenetic
relationships. Our interpretation of the results is that recent colonists t o an island are initially rare in the indigenous
forest habitat but concomitant with an adaptation to local conditions they gradually become more abundant and
taxonomically distinct from other populations of the same species. These results apparently contradict the taxon
cycle hypothesis but this may be a result of o u r focus on indigenous forest habitats rather than on a wider range
0 2001 The Linnean Society of London
dominated by anthropogenic ones.
ADDITIONAL KEYWORDS: taxon cycles - island birds - extinction - logging - species abundance.
INTRODUCTION
strategies which are proactive rather than the current
norm of reacting to imminent species extinction.
Variation in abundance within a group of species,
whether mainland or island taxa, has been related
to many factors. Some which have recently received
attention include the following:
Since 1600, 103 of the 116 known bird extinctions
have occurred on islands (Gaston & Blackburn, 1995).
Whether the proximate cause of species loss is
anthropogenic or a stochastic process, it is the
possession of characteristically small and geographically restricted populations which renders insular species particularly prone to extinction (Gilpin
& Soule, 1986; Mace & Kershaw, 1997; Pimm, Jones
& Diamond, 1988; Thiollay, 1997). However, even
within a single island community there is considerable variation in population size between species
(e.g. see Jones, Linsley & Marsden, 1995); understanding the causes of this variation may help u s
uncover the ultimate causes of the extinction process
itself and thus may help in the design of conservation
(1) Species with large geographical ranges tend to
have high local abundances; a possible explanation of both traits is that such species are
ecologically unspecialized and have a wide niche
(Brown, 1984) but there has recently been a
much wider debate on the subject (e.g. Gaston
& Lawton, 1990; Nee, Gregory & May, 1991a;
Lawton, 1993; Gaston, Blackburn & Lawton,
1997a; Holt et al., 1997).
(2) Species on the edge of their range tend to occur
at lower local abundances than the same species
in the middle of their range - perhaps because
species can exploit progressively fewer patches
towards the edge of their range (Hengeveld &
* Corresponding author. E-mail: m . j o n e s b u . a c . u k
0024-4066/01/050065 + 15 $35.00/0
65
0 2001 The Linnean Society of London
66 M. J. JONES ET AL.
Haeck, 1982; Brown, 1984; Lawton, 1993; Gaston,
Blackburn & Lawton, 199713, but see Blackburn
et al., 1999).
(3) Large-bodied species may occur at lower densities
(Blackburn & Lawton, 1994; Blackburn et al.,
1993; Cotgreave & Harvey, 1992; Gregor & Blackburn, 1995; Nee et al., 1991b).
(4) Species with certain individual traits such as
narrow frugivorous diets (Terborgh & Winter,
1980) lack of mobility (McKinney, 1997) and
sexual dimorphism (McLain, Moulton & Redfearn,
1995; Sorci, Moller & Clobert, 1998) may become
rare, perhaps because these traits are facets of
an increasing specialization and resistance t o
change.
An extra dimension for island taxa is that there
may be an evolutionary process, acting over a much
greater time period which relates t o abundance.
Wilson (1959, 1961) used the term ‘Taxon Cycle’ to
describe the initial expansion of a taxon within
an archipelago followed by differentiation into subspecies and eventually species on individual islands.
This differentiation was accompanied by an increasing risk of extinction of some of the island
populations. Ricklefs (1970) and Ricklefs and Cox
(1972, 1978) applied the same construct to birds and
suggested that interspecific competition was the
mechanism which drove the cycle.
Others have looked for evidence of taxon cycles,
some successfully (e.g. Greenslade, 1968; Rummel &
Roughgarden, 1985; Ricklefs & Bermingham, 1999)
and some unsuccessfully (e.g. Jones et al., 1987).
Glazier (1980) has also postulated the existence of
cycles in mainland taxa. In practice, the main
objections to the idea have centred on the mechanism
of inter-specific competition rather than the actual
concept of the taxon cycle (e.g. Pregill & Olsen, 1981)
These objections could be viewed as part of a more
general debate on the importance of inter-specific
competition in mediating species co-occurrence on
islands (see Whittaker, 1998, for review of the
arguments). Nevertheless, there has recently been a
renewed interest in the idea of taxon cycles (e.g.
Lawton, 1993; Chown, 1997) and mechanisms other
than inter-specific competition have been suggested
(Glazier, 1987; Chown, 1997 and Matsuda & Abrams,
1994). Most recently, Ricklefs & Bermingham (1999)
have used molecular techniques t o estimate taxon age
directly rather than by inference from distributional
patterns. They support the taxon cycle hypothesis
by showing that ecology and distribution are closely
related to taxon age. They also suggest that intrinsic
factors are responsible for the changes in abundance.
The factor they emphasize is the differential effects
of pathogens on colonists and residents rather than
inter-specific competition within the bird community.
Although the ultimate causes of extinction may be
part of a natural process, anthropogenic activities
are now a most important proximate contributor to
increased extinction and extinction risk on islands
(Caughey, 1994; Bibby, 1994; Whittaker, 1998). For
forest birds, logging is undoubtedly a significant
threat but although the effects of logging on mainlands have been reasonably well studied, (e.g. Johns,
1987; 1989; Lambert, 1992; Thiollay, 1992), logging
on islands has received practically no attention (one
exception being Marsden, 1998). This is unfortunate
as the effects on island species may be particularly
deleterious. Thiollay (1997) suggests that island
species have wider niches and can adapt better to
habitat change but it could also be argued that some
of the more specialized island species, perhaps with
low population densities, would be particularly vulnerable t o the effects of logging and habitat conversion.
This paper has two aims. The first is t o identify
which characteristics of island bird species are associated with low abundance and therefore increased
risk of extinction in a natural habitat - in this case
tropical forest. We do not directly test the taxon
cycle hypothesis because as Whittaker (1998) has
highlighted, the hypothesis itself has evolved with
each island and taxa studied so that it is not now
a “discrete and easily refutable hypothesis”. Rather,
we aim to establish whether historical factors (as
examined in taxon cycle studies) are better predictors
of species abundance than the ecological ones such
as distributional range size, body size and diet.
Second, we aim to identify which of these traits
are correlated with the ability of species to cope
with habitat change, in this case the conversion of
primary or mature forest to secondary or logged
forest, and whether such ‘flexibility’is a major factor
in influencing extinction risk.
METHODS
STUDY SITES AND BIRD FAUNA
Data were collected on two Indonesian islands, Buru
in Maluku province (the Moluccan Islands) between
8 November and 18 December 1989 and Sumba in
Nusa Tengarra province (the Lesser Sunda Islands)
between 23 July and 23 September 1992. On Buru,
data collection was restricted to the North West of
the island between sea level and 800m. On Sumba
we visited six forest patches distributed along the
East-West axis of the island and ranging in altitude
between 20 and 1060m. Precise locations and other
details of the study sites can be found in Marsden
et al. (1997) and Jones et al. (1995). Bum still
supports montane and lowland evergreen rainforest,
CORRELATES OF EXTINCTION RISK
the latter dominated by Dipterocarpaceae (Monk, De
Fretes & Reksodiharjo-Lilley, 1997). The remaining
forest on Sumba is mainly deciduous with some
evergreen in river valleys; rain and elfin forest exist
above 800m although there is little land above this
elevation t o support it (Monk et al., 1997; Linsley,
Jones & Marsden, 1998).
Both islands are situated within Wallacea which
is a zone of transition between the Oriental and
Australo-Papuan avifaunas. There are just over 100
regularly breeding birds on each island. B m has
10 endemic species and a distinct high altitude
element its avifauna, Sumba has seven endemics
(White & Bruce, 1986; Jepson, 1993; Linsley et al.,
1998).
BIRD ABUNDANCE DATA
Birds were recorded using a point count method (see
Jones et al., 1995) at 352 census stations on Sumba
and 150 on Buru. The stations were between 250m
(dense forest) and 400m apart (more open forest)
along transect routes. The positions of the transects
were not randomly sited for safety and logistical
reasons. Every other station was positioned 50m at
right angles to the main route to reduce any edge
effects. Two experienced bird recorders spent 10min
at each station and produced a joint list of bird
contacts. Flying birds which were not seen to land
or take off were excluded. Sighted contacts were
allocated t o a height category; Canopy (>15m),
mid (5-15m), low (1-5m), ground (<lm). Distance
estimates were made t o each contact but only those
within 61m were used for analysis; choosing a
greater distance would have produced larger sample
sizes for some species but differing levels of conspicuousness would have distorted the abundance
indices of the bird species.
A number of species were excluded from the
subsequent analysis; birds of prey and swifts because
they were nearly always seen in flight and were not
assignable to a particular habitat type, migrants
because they were not a permanent element of the
island faunas and the nocturnal and/or crepuscular
species which would not have been sampled adequately by the methods used. Also excluded from
much of the analysis were species known t o be
present on one or other of the islands (Coates &
Bishop, 1997) but which were not recorded during
our censuses. It could be argued that they should
be included in the analysis with zero abundance but
there is difficulty in deciding whether such species
were not recorded because they are genuinely rare
(and therefore should be included) or because we did
not visit the areas or habitats they prefer. These
species are considered at the end of Results.
67
An index of abundance for each species in each
habitat was calculated by summing the number of
contacts and dividing by the number of stations in
that habitat.
HABITAT DATA
The following habitat variables were recorded at
each station; tree diameter at breast height, height
and distance to the central point of the 10 nearest
trees, percentage cover at canopy (>15m), mid
(5-15m), low (1-5m) and ground (<lm) levels,
whether the main point of inversion for each tree
was above or below half the tree height (arguably
the best way of identifying past disturbance in the
area as branching below half height indicates growth
under an open canopy). Basal area and density of
trees were calculated from the tree measurements.
Each census station was further assigned to one of
the following habitat types; primary forest, secondary
forest (but not previously subject to mechanical
logging) and selectively logged forest (Bum only).
Although we describe forest as ’primary’it is probable
that all forest on both islands has been subject to
at least some level of disturbance. Therefore, primary
describes areas with large, straight-boled trees, a
closed canopy and no obvious disturbance but such
areas may not be pristine forest.
The habitat characteristics measured at each census station were used in a Discriminant Function
Analysis to check if these subjective habitat classifications were supported by differences in the
habitat variables measured. Stations which were
identified by the DFA as having the wrong classification (i.e. less than a 50% probability) were
allocated to the habitat for which they had the
higher probability but only if they were contiguous
to an area of that habitat. For example, a station
which was in a large area of secondary forest but
which was classified by the DFA as primary (perhaps
an isolated remnant) retained its secondary classification. Similarly, a station classified by the DFA
as secondary but which was sited within a primary
forest area (perhaps because it was the site of a
past tree fall) was classed as primary.
On Sumba, areas of degraded secondary forest and
scrub were excluded t o leave two forest types, primary
and secondary and classification, both subjective and
through the DFA, was clear-cut. On Buru there were
three possible forest types, primary, secondary and
logged. A problem here was that the distinction
between primary and mature secondary was not clear;
the island has been subject t o shifting cultivation and
much of the forest which has not been mechanically
logged is a mosaic of primary forest and secondary
at different stages of recovery (pers. observ.). Therefore we designated a ‘mature’ forest category which
68
M. J . JONES ET AL.
comprised stations which were primary or mature
secondary. Areas of younger secondary forest and
scrub were excluded from the analysis. The logged
forest contained stations which were at the same
altitude as the mature forest and which we knew
from Forestry Department records were in forest
selectively logged between 5 and 12 years before our
visit.
SPECIES TRAITS
The traits chosen as potential correlates of species
abundance were as. follows: distinctiveness; number
of con-genors; number of islands; edge; speciedgenus
ratio; number of sub-species; size; dimorphism; group
size; diet; canopy occupancy; variation in height and
mobility. An explanation of these traits, how they were
derived or calculated and the rationale for choosing
them are detailed in Appendix 1.
ANALYSIS
Initially the values for each trait were regressed
against the log of the abundance of the bird species.
After checking for linearity, all of the traits were also
entered into a stepwise linear regression analysis with
log abundance as the dependent variable. A problem
with these analyses is that in a group of related species,
it may not be valid to treat the individual species as
independent. We therefore carried out a ‘comparative
analysis by independent contrasts’ (F’urvis & Rambaut,
1995)which extracts independent data points for analysis. The data points or contrasts are the differences
between the two values of a variable a t each evolutionary event in a phylogenetic tree of the species
found on each island (phylogenies followed Sibley &
Monroe, 1990). The contrasts for the abundance in
primary or mature forest were then regressed against
the contrasts for each of the species traits. A series of
pairwise regressions rather than multiple regressions
were used as some of the relationships were now nonlinear and not easily transformable.
The ability of species t o exploit anthropogenic habitats was tested as follows: the species abundances
in secondary (Sumba) or logged forest (Buru) were
regressed against those in primary forest or mature
forest respectively; it was presumed that species with
positive residuals were those that had adapted relatively well to the disturbed habitat (at least in comparison to the other species) and those with negative
residuals had not. The residuals were then used as
the dependent variables in bivariate and stepwise
multiple regressions with the species traits to see
which of those traits were related to the ability to
exploit these new habitats.
In analyses correcting for phylogenetic relationships,
developing a set of contrasts for the ability to transfer
between habitats was not straightforward since, because of the potential lack of independence, we could
not generate residuals from a regression analysis. Instead, the species abundances in each forest type were
ranked separately and the rank in secondary or logged
forest subtracted from the rank in primary forest. We
then examined whether a species had increased or
decreased relative to the other species in that community. Some of these differences were obviously negative so a constant was added (bringing the largest
negative value up to one) and the log of the difference
in ranks used t o generate the contrasts with the traits.
The effect of position within the range (the ‘edge’
variable in Appendix 1) could not be tested in the
above analyses because of its close correlation with
‘distinctiveness’- the highly distinct species are the
single island endemics which could only be classified
as on the edge of their range. The effect of position
was therefore examined using a sub-set of species
which occurred on more than four islands and the
abundances of edge versus non-edge species compared
with an F test.
RESULTS
Bird species recorded in our surveys are listed in
Appendix 2.
There were no significant relationships in any of the
analyses between species abundance and ‘number of
con-genors’, ‘species to genus ratio’ and ‘canopy occupancy’ so these three do not appear in any of the
tables or figures.
UNIVARIATE REGRESSIONS: COMPARISON OF
INDEPENDENT CONTRAST AND ORIGINAL DATA
The analyses of the independent contrasts are shown
in Tables 1 (Sumba) and 2 (Buru) where the results
are compared to the bivariate regressions using the
original data. A feature of calculating the contrasts is
that sample sizes are approximately halved. All of the
regressions using the original data were linear, i.e. in
no cases did non-linear models produce significant
relationships with higher ? values. Using the contrasts, a small number of the relationships emerge as
quadratic which, on examination of the plots, is caused
by the combination of the smaller sample size and
presence of outliers (contrasts produced when two
species are closely related but differing greatly in
abundance). Where quadratic models are quoted, linear models were also significant but with lower 4
values.
For Sumba (Table 1)‘distinctiveness’ is a significant
predictor of abundance in primary forest in both original and contrast data sets. ‘Number of sub-species’
4.52
7.35
2.52
1.64
0.47
3.89
0.71
0.00
2.14
0.03
CONTRASTS
0.040
0.004
0.127
0.213
0.501
0.060
0.409
1.ooo
0.157
0.875
0.037
0.099
0.004
0.192
0.890
0.900
0.460
0.552
0.011
0.289
4.60
2.84
9.06
1.75
0.02
0.02
0.56
0.36
6.93
1.15
Distinctiveness
No. of sub-species
Number of islands
Size
Dimorphism
Mobility
Height variation
Fruit in diet
Seeds in diet
Insects in diet
Distinctiveness
No. of sub-species
Number of islands
Size
Dimorphism
Mobility
Height variation
Fruit in diet
Seeds in diet
Insects in diet
P
F
Correlate
a t 0.05 level.
0.164
0.412
0.103
0.066
0.020
0.145
0.033
0.000
0.085
0.001
0.087
0.056
0.159
0.035
0.000
0.000
0.013
0.001
0.126
0.023
f
0.082
0.872
- 0.048
-0.536
-0.072
0.206
0.066
0.000
-0.229
0.038
0.110
0.054
- 0.020
-0.002
0.017
0.001
0.253
0.077
-0.424
0.129
bl
Primary forest
- 1.908
b2
0.805
0.049
0.835
0.891
0.664
0.046
0.011
0.259
0.112
0.202
0.571
0.053
0.546
0.112
0.200
0.886
0.966
0.550
0.652
0.874
0.33
3.94
0.37
2.62
1.70
0.02
0.01
0.36
0.21
0.03
0.06
3.47
0.04
0.02
0.19
3.56
7.83
1.34
2.73
1.72
P
0.003
0.240
0.002
0.001
0.008
0.245
0.272
0.055
0.106
0.070
0.007
0.076
0.008
0.052
0.039
0.000
0.000
0.008
0.004
0.001
?
-0.034
-0.160
0.004
-0.032
-0.152
0.308
-0.902
-0.496
- 0.327
0.742
-0.511
1.051
-0.074
0.034
0.076
0.013
0.285
1.223
- 1.301
0.325
bl
-- 0.687
0.729
b2
Transfer from primary to secondary forest
F
Original data
Table 1. Correlates of bird species abundance on Sumba: bivariate regressions. For original data, N = 50, for contrasts, N = 25. Bolding indicates significance
70
M. J. JONES ET AL.
Table 2. Correlates of bird species abundance on Buru: bivariate regressions. For original data, N = 42, for contrasts,
N = 24. Bolding indicates significance at 0.05 level.
Original data
Mature forest
Transfer from mature to logged forest
Correlate
F
P
f
bl
Distinctiveness
No. of sub-species
Number of islands
Size
Dimorphism
Mobility
Height variation
Fruit in diet
Seeds in diet
Insects in diet
11.44
1.17
5.21
0.90
0.06
0.27
0.35
0.00
4.20
0.33
0.002
0.287
0.028
0.349
0.804
0.610
0.557
0.965
0.047
0.567
0.218
0.028
0.113
0.021
0.002
0.007
0.009
0.000
0.093
0.008
0.150
0.026
-0.015
-0.001
-0.030
-0.002
-0.162
- 0.004
- 0.395
0.058
CONTRASTS
5.52
0.033
0.01
0.904
5.60
0.027
2.78
0.109
1.18 0.289
2.44
0.133
4.93 0.037
0.15
0.701
0.11
0.745
0.01
0.946
0.208
0.010
0.203
0.112
0.051
0.100
0.190
0.007
0.005
0.001
0.252
0.037
- 0.355
1.271
- 0.652
-0.453
- 0.796
0.470
-0.615
-0.120
Distinctiveness
No. of sub-species
Number of islands
Size
Dimorphism
Mobility
Height variation
Fruit in diet
Seeds in diet
Insects in diet
is significant using the contrasts and approaches significance in the original data; this variable is, however,
highly significant in the multiple regression analysis
of the original data (see below and Table 3). ‘Number
of islands’ is highly significant in the original data but
not in the contrasts. For the transfer from primary to
secondary forest, there is, as noted, a difference in
methodology but there is some similarity in the results
using original and contrast data in that ‘number of
sub-species’is just significant using contrasts and close
to significance using the original data. ‘Height variation’ is significant using the contrasts but not using
the original data.
The Buru analysis (Table 2) shows a strong similarity
between the results using the original and contrast
data. In both data sets, ‘distinctiveness’ and ‘number
of islands’ are significantly related to abundance in
mature forest and to the ability to transfer to logged
forest.
It is clear that rather similar trends emerge from
the regressions across species as those within taxa
(the independent contrasts analysis). For further analyses we concentrate on the original data set; this is
obviously the less conservative approach but there
is the significant advantage that we can investigate
P
4
bl
7.98
2.57
4.18
3.69
0.00
3.72
0.73
1.30
4.77
4.40
0.007
0.116
0.047
0.062
0.983
0.062
0.398
0.262
0.035
0.042
0.163
0.059
0.093
0.082
0.000
0.094
0.018
0.031
0.104
0.097
0.098
0.029
-0.010
-0.002
-0.002
-0.005
-0.176
-0.083
-0.315
0.151
9.91
6.43
20.82
8.93
1.62
0.04
1.55
0.03
0.01
0.00
0.001
0.007
(0.001
0.001
0.217
0.842
0.228
0.874
0.944
0.927
0.486
0.380
0.510
0.573
0.068
0.002
0.069
0.001
0.000
0.000
0.096
0.174
1.033
-0.037
-0.206
-0.069
-0.049
-0.011
-0.003
0.004
F
b2
1.258
1.042
multivariate relationships and dissect out the more
important of the predictors of bird abundance. In contrasts analysis it is only possible to include one noncontinuous variable in a multivariate investigation
and in this particular case the sample sizes would, in
any case, be too low. We could also not accommodate the
non-linear relationships present within the contrasts
data.
MULTIVARIATE ANALYSES: ABUNDANCE IN PRIMARY
OR MATURE FOREST
For Sumba (Table 3A) the most important predictor of
abundance of species in primary forest is the number
of sub-species of that species which occur within Wallacea as a whole. The fit of the model is improved by
seed eaters having low abundance and a weak trend
for larger species to be commoner. Just over 45% of
the variation in the abundance index is explained by
a combination of these three traits.
On Buru (Table 3B), ‘number of sub-species’is again
a highly significant predictor but ‘distinctiveness’ is
entered into the equation first - endemic species and
sub-species being more abundant than the widespread
ones. There is also a negative relationship between
CORRELATES OF EXTINCTION RISK
71
Table 3. Correlates of bird species abundance: stepwise multiple linear regression analysis using the original data.
Order of entry indicated by t values
(A) Sumba
Primary forest
Transfer from primary to secondary
forest
Correlate
t
No. of sub-species
Size
Seeds in diet
3.79
1.98
2.42
P
0.001
0.054
0.020
t
0.090
-0.002
-0.361
2.54
2.14
0.015
0.039
1.52
0.136
Mobility
Distinctiness
No. of sub-species
Insects in diet
Dimorphism
Mobility
Fruit in diet
P
b
b
0.133
0.005
-0.014
12 = 0.452, F3,39
= 9.66, P<O.OOl
12=0.126, F3,39=
3.01, P=0.042
Mature forest
Transfer from mature to logged forest
3.74
3.04
3.73
2.17
<0.001
0.005
<0.001
0.038
0.621
0.306
-0.541
-0.221
P<O.OOl
12~0.428,F4,zg=7.18,
insect eating and abundance. Inclusion of ‘mobility’
improves the fit of the model but it is not itself significantly related to abundance. Overall 43.8% of the
variation in abundance is explained.
MULTIVARIATE ANALYSES: TRANSFER TO
ANTHROPOGENIC HABITATS
The analysis of the ‘ability’ of species to exploit disturbed habitats is also shown in Table 3. The dependent
variables are the residuals of the regressions between
the abundances in secondary and primary forest
(Sumba) or logged and mature forest (Buru). On
Sumba, abundance in primary forest explains 71.5%
of the variation of that in secondary forest; only 12.6%
of the variation in the residuals can be attributed to
the species traits. There is a weak trend for larger
species and those with many sub-species t o be more
abundant in secondary forest than would be predicted
from their primary forest abundance. On Buru only
49.6% of the variation in abundance in logged forest
is explained by the mature forest abundance. The
species which best tolerate logged forest are the more
taxonomically distinct ones with higher numbers of
sub-speciesin Wallacea;they are also likely t o eat fruit
and be more vagile. The model explains 47.5% of the
variation in the residuals.
4.45
2.88
<0.001
0.007
0.574
0.367
3.07
3.03
0.005
0.005
- 0.445
0.437
%=0.475, F4,29=8.47, P<O.OOl
The slope of the original regression between secondary and primary forest abundances on Sumba is
0.913 and between logged and mature forest on Buru
is 0.649; the intercepts are very close to the origin
(-0.011 for Sumba and 0.025 for Buru). This suggests
that, for Buru at least, the commoner species are less
abundant in logged forest than their mature forest
abundances would predict.
INCLUSION OF UNRECORDED SPECIES
We now include in the analysis some of the species
which were not recorded during censussing but which
we believe are genuinely rare rather than occurring
in different areas/habitats. There was one species in
this category on Sumba and 12 on Buru (See Appendix
2). The Sumba species and seven of the Bum ones
were actually seen or heard in the study areas, but
not recorded at census stations. The other five species
were included because, with reference t o White &
Bruce (1986) and Coates & Bishop (1997), we suspect
that they should be present in the areas censused.
The inclusion of species with an abundance of zero
skews the distributions of species abundance (markedly so for Buru) so we now use bivariate correlations.
Also, as ‘number of sub-species’ and ‘distinctiveness’
are clearly the most important correlates of species
72
M. J. JONES ET AL.
3
Q
-d
1.8 A
1.6
1.4
1.2 r
F
T
2
4 0.4
0.2
-
1+2
3+4
5+6
7
1.6
1.4
1.2
- d l
c
1 0.8
a
a 0.6
8 0.4
4
0.2
0
1+2
Distinctiveness score
7
5+6
3+4
Distinctiveness score
e!
2
1.8
1.6
D
T
T
3
4
I
0.6
0.4
0.2
n
Number of sub-species in Wallacea
1+2
3+4
5+6
7+8
>8
Number of sub-species in Wallacea
Figure 1. The relationships between mean abundance in forest on Sumba and Buru and taxonomic distinctiveness
and number of sub-species in Wallacea. N values: (A) distinctiveness 15, 21, 10, 5 (Sumba); (B) 14, 20, 14, 6 (Buru);
(C) number of sub-species 27, 11, 8, 3, 2 (Sumba); (D) 30, 7, 6, 4, 7 (Buru). For Sumba, distinctiveness is significantly
related to log abundance (F,9=4.36, P=O.O42) but number of sub-speciesis not (F4y=3.06,P=O.O87). Spearman rank
correlations show that distinctiveness is significantly related to abundance (r,=0.486,N = 54, P<O.OOl), but number of
species is not (rs=0.242,N=54, P=0.075).
abundance, the impact of the unrecorded species is
examined just in relation to these two traits.
Figure 1shows the relationships between abundance
of birds and ‘distinctiveness’ and ‘number of sub-species’ with these extra species included as zeros. The
two islands show remarkably similar patterns. The
most distinct species (the endemics) are the commonest; abundance also tends to be highest for the
species which are represented by many sub-species
within Wallacea; on both islands however there is a
dip in abundance for species with 5 to 6 sub species.
The relationship between ‘distinctiveness’ and abundance is significant for both islands (Fig. 1). That between ‘number of sub-species’ and abundance only
approaches significance but does so on both islands (the
variability around the means is obviously increased by
the addition of species with zero abundance).
POSITION WITHIN THE SPECIES RANGE
The effect of position within the range on abundance
was analysed by dividing the bird species into two
groups, those on the edge of their range (scores 1 and
2 in Appendix 1) and those not on the edge (scores 3
and 4 in Appendix 1).On Bum there was no difference
between the two groups (Fl,30 =0.543, P=0.467, edge:
x=8.95, SD=2.45-32.64, non-edge: x=6.52, S D =
2.10-20.23) but on Sumba, species at the edge of their
range (x = 18.05, SD =5.72-56.98) were significantly
more abundant than those not a t the edge (%=5.511,
S D = 1.05-28.83, Fl,44=5.23, P=O.O27).
DISCUSSION
There has been considerablerecent debate on the importance of controlling for phylogenetic relationships in
cross-species analysis (Ackerly & Donoghue, 1995; Harvey, Read & Nee, 1995; Ricklefs, 1996; Starck, 1998;
Westoby, Leishman & Lord, 1995). Whilst there may be
a very strong theoretical case for doing so, controlling
for phylogeny poses a significant practical problem for
studies of island communities. Islands are depauperate
and the process of gaining statistical independence between species further reduces the sample sizes (by approximately 50% in this study). We accept that,
irrespective of the practical problems, the phylogeny of
the species should be addressed. Nevertheless, we feel
justified in concentrating our interpretations upon the
results derived from the original data. This is because
firstly, the analysis of the independent contrasts shows
the same trends as the analysis of the original data,
and secondly, although the possibility of type 1 error is
CORRELATES OF EXTINCTION RISK
increased, we only acknowledge the strongest relationships which are apparent from both islands.
The traits which describe the species’ niche in the
forests either do not figure at all in the results (canopy
occupancy, group size) or do so rarely and not in a
consistent way across all analyses (mobility, variation
in height and the diet variables). There are also no
consistent relationships between body size and abundance; there is some evidence that large species are
less abundant in primary forest on Sumba and more
abundant than expected in secondary forest but the
relationship (at least in the former case) is weak. Body
size is described as only a moderate (and negative)
predictor of abundance by Gregory & Blackburn (1995)
but there can also be positive relationships within
some tribes (Nee et al., 1991b).
One trait which is strongly related t o bird abundance, at least in some of the bivariate regressions, is
‘number of islands’ which is equivalent t o the range
size of each species. The relationship between range
size and local abundance was postulated by Hengeveld
& Haeck (1982) and Brown (1984)but the latter author
states that the relationship exists within groups of
closely related and ecologically similar species. The
Sumba and Bum avifaunas obviously do not conform
t o such homogeneous groupings so we might not expect
to find positive relationships. In fact we find the opposite, the species with the smallest ranges are the
most abundant. This relationship does not figure in
the multiple regression analyses as range size is closely
correlated with ‘distinctiveness’ and ‘number of subspecies’ which are the most important predictors of
local abundance.
The separate analysis using the distributional variable, ‘edge’ also proves contrary t o that predicted.
Brown (1984) suggested that species on the edge of
their ranges may exist at lower local abundances than
in the centre. There is no relationship here for Buru
but on Sumba, excluding endemic species and subspecies, species on the edge are more abundant than
those towards the centre of their range.
As we have been analysing small and disparate
groups of species it is perhaps not surprising that we
do not find clear relationships between abundance and
body size or position within the range or with some of
the ecological traits. This does however make the
strong and consistent relationships with the historical
variables in our study even more dramatic. As an
explanation of the relationship we hypothesize that
when a taxon colonizes Wallacea it may be poorly
adapted t o the indigenous habitats and therefore rare.
Successful adaptation to local conditions would be
concomitant with an increase in local abundance and
also with differentiation from other island and mainland populations. The peak of adaptation and abundance would coincide with a high level of differentiation
73
at the sub-species followed by the species level within
Wallacea. An alternative t o this hypothesis (as suggested by an anonymous referee) is that the species best
adapted t o forest habitats may disperse less between
islands and so differentiate at a faster rate. Distinctiveness might therefore be associated with a preadaptation to forest life rather than the evolution
of higher abundance following adaptation. We derive
some support for the former explanation from the fact
that there is no relationship in our data sets between
mobility and increasing distinctiveness (rs=0.239, N =
47, P=0.106 for Sumba and rs=0.123, N=41, P =
0.461 for Buru) which would perhaps be predicted by
the latter hypothesis.
An increase in taxonomic distinctiveness and subspeciation is presumably a result of the increasing age
of a taxon in an archipelago. This relationship may
not of course be a direct one as differentiation may not
proceed at a constant rate. For instance, Cronk (1997)
distinguishes relict endemics which are ancient taxa
whose continental forbears have become extinct, and
‘recent’endemics which are “products of adaptive radiation representing rapid punctuational events”.
Nevertheless, Ricklefs & Bermingham (1999) have
used molecular techniques to demonstrate that taxonomic distinctiveness of island birds is fairly closely
correlated with their time of arrival in an archipelago.
It is the historical variables which are also the best
predictors of the ability to cope with habitat change.
Taxonomically distinctive species (Buru) or those represented by many sub-species (Sumba), are the ones
which are successful at making the transition to disturbed forests (or at least they are not declining as
much as the others). These successful species are also
the species which were already most abundant in
primary or mature forest. The habitats being compared
are not of course dramatically different; we specifically
excluded scrub habitats on Sumba so the comparison
is between areas which both have appreciable forest
cover. On Bum, the logging was selective so the forest
structure was partially retained and had time for
further recovery. We would not expect the highly adapted forest species t o successfully exploit much more
degraded forest.
Apart from agreeing that underlying historical processes have a profound effect on species abundance, the
results of this study seem to be opposite t o those found
more generally in the taxon cycle literature where
increasing endemism is accompanied by a decrease
rather than an increase in abundance. There may not
actually be a contradiction here as previous work on
taxon cycles has examined distribution and abundance
across many different habitats and not just within
indigenous forest. For example, Ricklefs & Cox (1978)
sampled nine habitats, six of which were anthropogenic.
The early cycle (less distinct) species in Ricklefs and
74
M. J. JONES ET AL.
Cox’s study could therefore be very abundant overall,
but still be rare in indigenous forest which is dominated
by the later stage species. This interpretation is certainly consistent with some of the results (e.g. Fig. 7)
presented in Ricklefs & Bermingham (1999) and also
with the fact that many undifferentiated species which
are rare in forest on Sumba are common in scrub and
cultivated habitats (e.g. brown honeyeater and spotted
dove (Linsley et al., 1998)). Although this may resolve
the apparent conflict in results, such an interpretation
suggests that in taxon cycle studies, the elevated abundances for recent colonists and the low abundances for
endemics are purely the result of human influence. In
this case it is possible that taxon cycles are only apparent because many new habitats have been created
which are exploitable by generalist species and the
endemics only become rare because their habitats have
become restricted.
There is perhaps good evidence t o suggest that endemism and specialization promotes extinction vulnerability (McKinney, 1997)but perhaps this is only so
if habitat change is rapid and drastic. If we focus on
conditions and habitats unaffected by man, extinctions
might be much more frequent for the recent colonists
which occur at low abundance because they are not
well adapted to local conditions and the large areas of
anthropogenic habitat would not be available This
would support the general view of Simberloff (1998)
that endemic speciesbecome rare through loss of habitat
rather than some sort of inherent evolutionary weakness.
There are two reasons for exercising caution in the
interpretation of our results (apart from the problems
of data independence as discussed above). The first is
that the forests on Sumba are highly fragmented (and
may have been for a long time; Linsley et al., 1998)
and there is the possibility that some of the highly
specialized species have been lost, leaving the less specialized, more abundant ones which may be better able
to survive in fragments (Turner, 1996). The forests on
Buru are much more extensive but have been subject
to shifting cultivation, perhaps for a very long time, so
again there may have been some pre-selection of the
species in our study. The second reason is that although
we have found similar trends on two islands, the analyses are not completely independent. Of the species
included in the analysis, nine are common to Sumba
and Buru and, not surprisingly, their abundances are
weakly correlated between the islands r,=0.681, P =
0.043).
We conclude that measures of the age o r evolutionary
development of a taxon within an archipelago are much
better than individual or derived ecological traits at
predicting local abundance. Lawton (1993) wrote that
“evolutionaryhistory leaves a signal on distribution and
abundance detectable through the noise of contemporary ecological events”;in our study the signal is
more than detectable, it actually drowns out the ‘noise’
of individual species ecology. Further studies are needed
to show whether the same patterns are present in
indigenous habitats in other island groups and in other
taxa. There is also no reason why the same patterns
should not be evident on mainlands. Studies of the
effects of habitat change such as logging, should also
be re-examined t o see if taxon development is the best
predictor of survival in anthropogenic habitats.
ACKNOWLEDGEMENTS
For their financial support we should like t o thank the
British Ecological Society, British Petroleum (through
their support for the BirdLifflFI Conservation Expedition Awards) and Environmental Management Development in Indonesia. Hugh Lloyd helped t o collect
the data and we are also grateful to the following for
their help in the field and/or for their general support
of the project; Paul Andrew, Bas van Balen, Mike
Baltzer, Dr Will Banham, Dr Leo Banilodu, David
Bishop, Donald Bruning, Dr Frans Umbu Datta, Dr
Deddy Darnaedi (LIPI), Jonathan Eames; Dr Alan
Fielding, Richard Grimmettt, Dr Keith Hamer, Emma
Harrison, Bas van Helvoort, Derek Holmes, Dr Jane
Hill, Dr Mike Hounsome, Carol and Tim Inskipp, Paul
Jepson, Deddy Juhaeni, Abdul Khair, Hiroshi
Kobayashi, Lesley Lace, Dr Frank Lambert, Alison
McKnight, Yus Rusila Noor, Alex Ora, Wahyu Raharjaningtrah, Robert Umbu Rihi, Tony Saka, Fred
Smiet, Dr Cathy Turtle, Dr Soetikno Wirjoatmodjo
(LIPI), Effendy Sumardja (PHPA), Roland Wirth and
Max Zieren. Professor Rory Putman kindly provided
very useful discussions and comments on the manuscript.
REFERENCES
Ackerly DD, Donoghue MJ. 1995. Phylogeny and ecology
reconsidered. Journal of Ecology 83 730-733.
Blackburn TM, Brown VK, Doube BM, Greenwood JJD,
Lawton JH, Stork NE. 1993. The relationship between
body size and abundance in natural animal assemblages.
Journal of Animal Ecology 62: 519-528.
Blackburn TM, Lawton JH. 1994. Population abundance
and body size in animal assemblages. Philosophical Transactions of the Royal Society London, Series B 343 33-39.
Blackburn TM, Gaston K J , Quinn RM, Arnold H, Gregory RD. 1999. Do local abundances of British birds change
with proximity to range edge? Journal of Biogeography 2 6
493-505.
Bibby CJ. 1994. Recent past and future extinctions in birds.
Philosophical Transactions of the Royal Society, Series B
344: 3540.
CORRELATES OF EXTINCTION RISK
~
75
~
Brown JH.1984. On the relationship between abundance
and distribution of species. The American Naturalist 124:
255-279.
Caughley G. 1994. Directions in conservation biology.
Journal of Animal Ecology 6 3 215-244.
Chown SL. 1997. Speciation and rarity: separating cause
from consequence. In: Kunin WE, Gaston KJ, eds. The
Biology of Rarity. London: Chapman & Hall.
Coates BJ, Bishop KD. 1997. A Guide to the Birds of
Wallacea. Australia: Dove Publications, Alderley.
Cotgreave P, Harvey PH. 1992. Relationships between
body size, abundance and phylogeny in bird communities.
Funct iona 1 Ecology 6 248-256.
Cronk QCB. 1997. Islands: stability, diversity, conservation.
Biodiversity and Conservation 6 477493.
Gaston KJ, Blackburn TM. 1995. Birds, body size and the
threat of extinction. Philosophical Transactions of the Royal
Society, London. Series B 347: 205-212.
Gaston KJ, Blackburn TM, Lawton JH. 1997a. Interspecific abundance-range size relationships: an appraisal of mechanisms. Journal of Animal Ecology 66:
579-601.
Gaston KJ, Blackburn TM, Lawton JH. 1997b. Interspecific abundance-range size relationships: range position and phylogeny. Ecography 20: 390-399.
Gaston KJ, Lawton JH.1990. Effects of scale and habitat
on the relationship between regional distribution and local
abundance. Oikos 58 329-335.
Gilpin ME, Soul6 ME. 1986. Minimum viable populations:
processes of species extinction. In: Soule ME, ed. Conservation Biology: the Science of Scarcity and Diversity.
New York: Sinauer.
Glazier DS. 1980. Ecological shifts and the evolution of
geographically restricted species of North American Peromyscus (mice). Journal of Biogeography 7:63-83.
Glazier DS 1987. Toward a predictive theory of speciation:
the ecology of isolate selection. Journal of Theoretical Biology 126: 32S333.
Gotelli NJ, Graves GR. 1990. Body size and persistence of
avian species on land-bridge islands. Journal of Biogeography 17: 315-325.
Greenslade PJM. 1968. Island patterns in the Solomon
Islands bird fauna. Evolution 22: 751-761.
Gregory RD, Blackburn TM. 1995. Abundance and body
size in British birds: reconciling regional and ecological
densities. Oikos 7 2 151-154.
Harvey PH, Read AF',Nee S. 1995. Why ecologists need
to be phylogenetically challenged. Journal of Ecology 8 3
535-536.
Hengeveld R, Haeck J. 1982.The distribution of abundance.
I. Measurements. Journal of Biogeography 9 303-316.
Holt RD, Lawton JH,Gaston KJ, Blackburn TM. 1997.
On the relationship between range size and local abundance: back to basics. Oikos 78 183-190.
Jepson P. 1993. Recent ornithological observations from
Buru. Kukila 6 85-109.
Johns AD. 1987. The use of primary and selectively logged
rainforest by Malaysian hornbills (Bucerotidae) and im-
plications for their conservation. Biological Conservation
4 0 179-190.
Johns AD. 1989. Recovery of a peninsular Malaysian rainforest avifauna following selective timber extraction: the
first twelve years. Forktail 4: 89-105.
Jones MJ, Linsley MD, Marsden SJ. 1995. Population
sizes, status and habitat associations of the restrictedrange bird species of Sumba, Indonesia. Bird Conservation
International 5: 21-52.
Jones MJ, Lace LA, Hounsome MV, Hamer K. 1987. The
butterflies and birds of Madeira and La Gomera: taxon
cycles and human influence. Biological Journal of the Linnean Society 31: 95-111.
Karr JR.1982. Avian extinction on Barro Colorado Island,
Panama: a reassessment. American Naturalist 119 220239.
Lambert FR 1992. The consequences of selective logging
for Bornean lowland forest birds. Philosophical Transactions of the Royal Society of London 335 443-457.
Lawton J. 1993. Range, population abundance and conservation. Trends in Ecology and Evolution 8 409413.
Linsley MD, Jones MJ, Marsden SJ. 1998. A review of
the Sumba avifauna. Kukila 10 60-90.
Mace GM, Kershaw M. 1997. Extinction risk and rarity on
an ecological timescale. In: Kunin WE, Gaston KJ, eds.
The Biology of Rarity. London: Chapman & Hall, 130-149.
Marsden SJ. 1998. Changes in bird abundance following
selective logging on Seram, Indonesia. Conservation Biology 1 2 605-611.
Marsden SJ, Jones MJ, Linsley MD, Mead C, Hounsome
MV. 1997. The conservation status of the restricted-range
lowland birds of Buru, Indonesia. Bird Conservation Znternational 7: 213-233.
Matsuda H, Abrams PA. 1994. Runaway evolution to selfextinction under asymmetrical competition. Evolution 48:
1764-1772.
McKinney ML. 1997. Extinction vulnerability and selectivity: combining ecological and paleontological views.
Annual Review of Ecology and Systematics 2 8 495-516.
McLain DK, Moulton MP, Redfearn TP. 1995. Sexual
selection and the risk of extinction of introduced birds on
oceanic islands. Oikos 7 4 27-34.
Monk KA, De Fretes Y, Reksodiharjo-Lilley G. 1997. The
Ecology of Nusa Tenggara and Maluku. Oxford: Oxford
University Press.
Nee S, Gregory FtD, May RM. 1991a. Core and satellite
species: theory and artifacts. Oikos 62: 83-87.
Nee S, Read AF', Greenwood JJD, Harvey PH. 1991b.
The relationship between abundance and body size in
British birds. Nature 351: 312-313.
Pimm SL, Jones H, Diamond J. 1988. On the risk of
extinction. The American Naturalist 1 3 2 757-785.
Pregill GK, Olson SL. 1981. Zoogeography of West Indian
vertebrates in relation to Pleistocene climatic cycles. Annual Review of Ecology and Systematics 12: 75-98.
Purvis A, Rambaut A. 1995. Comparative analysis by independent contrasts (CAIC): an Apple Macintosh application for analysing comparative data. Computer
Applications i n Biosciences 11: 247-251.
76
M. J. JONES ET AL.
Ricklefs RE. 1970. Stage of taxon cycle and distribution of
birds on Jamaica, Greater Antilles. Evolution 24: 475477.
Ricklefs RE.1996. Phylogeny and ecology. Tree 11: 229-230.
Ricklefs RE,Bermingham E. 1999. Taxon cycles in the
Lesser Antillean avifauna. Ostrich 7 0 49-59.
Ricklefs RE, Cox GW. 1972. Taxon cycles in the West Indian
avifauna. The American Naturalist 106: 195-219.
Ricklefs RE, Cox GW. 1978. Stage of taxon cycle, habitat
distribution and population density in the avifauna of the
West Indies. The American Naturalist 112: 875-895.
Rummel JD, Roughgarden J. 1985. A theory of faunal
buildup for competition communities. Evolution 3 9 10091033.
Sibley CG, Monroe Jr BL. 1990.Distribution and taxonomy
of birds of the world. Yale: Yale University Press.
Simberloff D. 1998. Habitat fragmentation and population
extinction of birds. Ibis 137: S105-Slll.
Sorci G, Moller AP, Clobert J. 1998. Plumage dichromatism of birds predicts introduction success in New Zealand.
Journal of Animal Ecology 67: 263-269.
Starck MJ. 1998. Non-independence of data in biological
comparisons. A critical appraisal of current concepts, assumptions and solutions. Theory in Biosciences 117: 109138.
Terborgh J , Winter B. 1980. Some causes of extinction. In:
Soule M, Wilcox B, eds. Conservation Biology: an Euolutionary-Ecological Perspective. New York Sinauer, 119133.
Thiollay J-M. 1992. Influence of selective logging on bird
species diversity in a Guianian rain forest. Conservation
Biology 6 47-63.
Thiollay J-M. 1997. Distribution and abundance patterns
of bird community and raptor populations in the Andaman
archipelago. Ecography 2 0 67-82.
'hrner IM. 1996. Species loss in fragments of tropical forest:
a review of the evidence. Journal of Applied Ecology 3 3
200-209.
Westoby M, Leishman MR, Lord JM. 1995. On misinterpreting the 'phylogenetic correction'. Journal of Ecology 8 3 531-534.
White CMN, Bruce MD. 1986. TheBirds of Wallacea. B.O. U
Checklist No. 7. London: British Ornithologists' Union.
Wilson EO. 1959. Adaptive shift and dispersal in a tropical
ant fauna. Evolution 13: 122-144.
Wilson EO. 1961. The nature of the taxon cycle in the
Melanesian ant fauna. American Naturalist 9 5 169-193.
Whittaker F&J. 1998. Island Biogeography. Oxford: Oxford
University Press.
APPENDIX 1
Definitions and derivations of potential correlates and rationale for their choice.
Name of derivation
DISTINCTIVENESS'
Taxonomic distinctiveness ranked according t o the following
criteria: 1= taxon on Sumba or Bum not distinct from the form
occurring in Indonesia and extra-limitally; 2 = non-endemic subspecies found on >5 islands, species extralimital; 3 = nonendemic sub-species found on >5 islands, species endemic to
Indonesia or non-endemic sub-species found on <5 islands,
species extralimital; 4=endemic sub-species, species extralimital to Indonesia or non-endemic sub-species but found on >5
islands, species endemic to Wallacea or non-endemic sub-species
found on <5 islands, species endemic to Indonesia; 5 = nonendemic sub-species but found on <5 islands; species endemic to
Wallacea or endemic sub-species; species restricted to Indonesia;
6 =endemic sub-species; species endemic to Wallacea; 7 =
endemic species.
OF CONGENORS'
NUMBER
Number of other species from the same genus from that island.
OF ISLANDS'
NUMBER
Number of islands occupied within Wallacea.
Rationale
This measure is similar to the taxon cycle ranks used
by Ricklefs & Cox (1978) but based more on distinction
of the Sumba and Bum taxa from forms present within
the rest of the species range rather than on their
distribution patterns per se.
The presence of congenors on the same island might
lead to competitive pressure, narrower niches and
lower abundance of at least some of the putative
competitors (Thiollay, 1997).
The number of islands on which the Sumba or Buru
taxon occurs provides an estimate of the range size of
the species which, following Brown (1984) may be a
correlate of local abundance.
CORRELATES OF EXTINCTION RISK
77
APPENDIX l-continued
Name of derivation
EDGE'
1=the island is on the very edge of the range; 2 =near to the
edge (at most three islands between it and the edge of the
species range; 3 =the island is in the middle of the Wallacean
range of the species; 4 =middle of the whole range of the species
(i.e. it is found in the Australasian and the Oriental regions.
RATIO'
SPECIEVGENUS
Ratio within Wallacea.
OF SUB-SPECIES'
NUMBER
Number of sub-species within Wallacea.
Rationale
Following Brown (1984), species on the edges of their
range may occur at lower densities than those in the
middle.
A high species to genus ratio would suggest a successful expansion within Wallacea which might in turn be
related to local abundance and ability to cope with
change.
A measure of the historical development of a species
within Wallacea, a species with a low number of sub.
species has either recently arrived and remains
undifferentiated or has become highly differentiated
and the sub-species have in effect disappeared and
become single island endemics.
SIZE^
Wing length (mm).
DIMORPHISM3
1=sexes identical, 2 = slight sexual dimorphism, 3 =marked
sexual dimorphism.
SEEDS, INSECTS IN DIET
FRUIT,
0 =absent from diet; 1=present but not dominant; 2 =dominant.
OCCUPANC~~
CANOPY
Percentage of total number of sighted contacts that were in the
sub-canopy or canopy (as opposed t o ground, low and mid levels).
VARIATION
IN HEIGH?
Variance of the mean height of contacts across all levels canopy, sub-canopy, mid, low and ground.
MOBILITY4
Percentage of total number of contacts which were flying and not
seen to take off or land.
Perhaps only a moderate predictor of abundance
(Gregor & Blackburn, 1995) but larger species might be
expected to occur at lower densities.
It has been suggested that among introduced species,
sexually dimorphic ones are less adaptable and more
likely to become extinct than monomorphic ones
(McLain et al., 1995; Sorci et al., 1998).
Different diets may relate to local abundance and ability
to cope with habitat change, e.g. frugivory may be associated with lower abundance (Terborg & Winter, 1980).
Intuitively, canopy species may be expected to suffer
more from forest disturbance, although Karr (1982) and
Gotelli & Graves (1990 suggest that it is species
restricted to one strata and especially lower strata
which are particularly extinction-prone.
Species which occupy a range of forest strata may have
wider niches, be more locally abundant and better
equipped to cope with habitat change.
Limited mobility may be a trait which promotes
extinction vulnerability (McKinney, 1997).
Based on information from White & Bruce (1986).
'Data on body mass were only available for a small fraction of the bird species and data required t o estimate body mass were unavailable for
many others. Wing length was used as an approximate measure of body size. Some lengths were taken from mist-netted birds in the field, some
from published data and others from museum specimens.
Dimorphism was assessed subjectively by a colleague who was present for the fieldwork and so knew the fauna well but was a t that time unaware
of the planned analysis. If sexes only differed very slightly in size or eye colour or depth of colour of the plumage, they were regarded as
monomorphic.
'These variables were calculated from the field data. I t was obviously not possible to derive them for the species not seen in the fieldwork. All
contacts irrespective of distance were used to derive them.
78
M. J. JONES ET AL.
APPENDIX 2
Bird species used i n the analysis. *Species recorded at the s t u d y sites but not d u r i n g formal censusing. #Species
n o t recorded d u r i n g fieldwork b u t which, w i t h reference t o White & Bruce (1986) and Coates & Bishop (1997), are
t h o u g h t t o b e present i n t h e s t u d y areas.
Megapodius reinwardt
Gallus varius
Treron teysmannii
Ptilonopus dohertyi
Ptilonopus melanospila
Ducula aenea
Columba uitiensis
Macmpygia ruficeps
Streptopelia chinensis
Chalcophaps indica
Trichoglossus haematodus
Cacatua sulphurea
Eclectus mratus
Geoffmyus geoffmyi
Tanygnathus megalorynchos
C aomant i s sepulcralis
Centmpus bengalensis
Halcyon australasia
Halcyon chloris
Rhyticems everetti
Pitta elegans
Coracina personata
Coracina dohertyi
Zoothera dohertyi
Rhinomyias oscillans
Orange-footed Scrubfowl
Green Junglefowl
Sumba Green Pigeon
Red-naped Fruit-dove
Black-naped Fruit-dove
Green Imperial Pigeon
Metallic Pigeon
Little Cuckoo Dove
Spotted Dove
Emerald Dove
Rainbow Lorikeet
Yellow-crested Cockatoo
Eclectus Parrot
Red-cheeked Parrot
Great-billed Parrot
Rusty-breasted Cuckoo
Lesser Coucal
Cinnamon-banded Kingfisher
Collared Kingfisher
Sumba Hornbill
Elegant Pitta
Wallacean Cuckoo-shrike
Sumba Cicadabird
Chestnut-backed Thrush
Russet-backed JungleFlycatcher
Rhipidura rufifmns
Pachycep ha la pectora 1is
Parus major
Dicaeum agile
Dicaeum sanguinolentum
Anthreptes malacensis
Muscicapa &uurica*
Ficedula harteri
Culicicapa ceylonensis
Terpsiphone paradisi
Monarcha triuirgatus
Myiagra ruficollis
Nectarinia buettikoferi
Zostemps wallacei
Zostemps citrinellus
Lichmera indistincta
Myzomela erythmcephala
Philemon buceroides
aeniopygia guttata
Lonchura molucca
Lonchura punculata
Aplonis minor
Oriolus chinensis
Dicrurus densus
Artamus leucorhynchus
Corvus macmrhyncos
Rufous Fantail
Common Golden Whistler
Great Tit
Thick-billed Flowerpecker
Blood-breasted Flowerpecker
Brown-throated Sunbird
Asian Brown Flycatcher
Sumba Flycatcher
Grey-headed Flycatcher
Asian Paradise Flycatcher
Spectacled Monarch
Broad-billed Flycatcher
Apricot-breasted Sunbird
Yellow-spectacled White-eye
Ashy-bellied White-eye
Brown Honeyeater
Red-headed Myzomela
Helmeted Friarbird
Zebra Finch
Black-faced Munia
Scaly-breasted Munia
Short-tailed Starling
Black-naped Oriole
Wallacean Drongo
White-breasted Wood-swallow
Large-billed Crow
Pompadour Green Pigeon
Superb Fruit Pigeon
White-bibbed Fruit-dove
Claret-breasted Fruit-dove
White-eyed Imperial Pigeon
Pied Imperial Pigeon
Long-tailed Mountain-pigeon
Metallic Pigeon
Slender-billed Cuckoo Dove
Great Cuckoo Dove
Emerald Dove
Moluccan Red Lory
Rainbow Lorikeet
Blue-fronted Lorikeet
Red-breasted Pigmy Parrot
Eclectus Parrot
Red-cheeked Parrot
Buru Racquet-tail
Great-billed Parrot
Moluccan King Parrot
Rusty-breasted Cuckoo
Coracina ceramensis
Ixos affini
Zoothera dumasi#
Cisticola exilis
Orthotomus cuculatus
Ficedula buruensis
Monarcha loricatus
Monarcha pileatus
Myiagra galeata
Rhipidura rufiuentris
Rhipidura superflua
Pachycephala pectoralis
Pachycephala griseonata
Dicaeum erthmthorar
Nectarinia aspasia
Nectarinia jugularis
Zostemps buruensis
Dicrurus bracteatus
Coruus enca#
Myzomela sanguinolenta
Philemon moluccensis
Pale Cicadabird
Golden Bulbul
Moluccan Thrush
Golden-headed Cisticola
Mountain Tailorbird
Cinnamon-chested Flycatcher
Black-tipped Monarch
White-naped Monarch
Dark-grey Flycatcher
Northern Fantail
Tawny-backed Fantail
Golden Whistler
Drab Whistler
Flame-breasted Flowerpecker
Black Sunbird
Olive-backed Sunbird
Buru Yellow White-eye
Spangled Drongo
Slender-billed Crow
Scarlet Honeyeater
Black-faced Friarbird
Buru
Tremn pompadora*
Ptilinopus superbus'
Ptilinopus riuoli
Ptilinopus viridis
Ducula perspicillata
Ducula bicolor
Gymnophaps mada
Columba uitensis*
Macmpygia amboinensis
Reinwardtoenu reinwardtii
Chalcophaps indica
Eos bornea
Trichoglossus haenaatodus
Charmosyna toropei*
Micmpsitta bruijnii*
Eclectus mratus
Geoffmyus geoffmyi
Prioniturus mada
Tanygnathus megalorynchos
Alisterus am boinensis
Cacomantis sepulcralis
CORRELATES OF EXTINCTION RISK
APPENDIX 2-continued
Bum
Chrysococcyx minutillus*
Eudynamys scolopacea
Scythmps novaehoElandiae#
Centropus bengalensis
Hem iprocne mys t acea
Tanysiptera galatea#
Halcyon chloris
Ceyx lepidus#
Pitta erythrogaster
Coarcina fortis
Little Bronze Cuckoo
Aplonis mysolensis
Asian Koel
Aplonis metallica*
Channel-billed Cuckoo
Lesser Coucal
Moustached Tree-swift
Common Paradise Kingfisher
Collared Kingfisher
Variable Dwarf Kingfisher
Red-bellied F’itta
Bum Cuckoo-shrike
Moluccan Starling
Metallic Starling
79