TOOLS AND BRAINS IN BIRDS
byLOUIS LEFEBVRE1) , NEKTARIA NICOLAKAKIS and DENIS BOIRE 2,3,4)(1 Department of Biology, McGill University and 2 Département des Sciences Biologiques,
Université de Montréal, Montréal, Québec, Canada)(Acc. 14-V-2002)

Summary
Tools are traditionally de ned as objects that are used as an extension of the body and held
directly in the hand or mouth. By these standards, a vulture breaking an egg by hitting itwith a stone uses a tool, but a gull dropping an egg on a rock does not. This distinction
between true and borderline (or proto-tool) cases has been criticized for its arbitrarinessand anthropocentrism. We show here that relative size of the neostriatum and whole brain
distinguish the true and borderline categories in birds using tools to obtain food or water.
From two sources, the specialized literature on tools and an innovation data base gatheredin the short note sections of 68 journals in 7 areas of the world, we collected 39 true (e.g.
use of probes, hammers, sponges, scoops) and 86 borderline (e.g. bait  shing, batteringand dropping on anvils, holding with wedges and skewers) cases of tool use in 104 species
from 15 parvorders. True tool users have a larger mean residual brain size (regressed against
body weight) than do users of borderline tools, con rming the distinction in the literature. In
multiple regressions, residual brain size and residual size of the neostriatum (one of the areasin the avian telencephalon thought to be equivalent to the mammalian neocortex) are the best
predictors of true tool use reports per taxon. Innovation rate is the best predictor of borderline
tool use distribution. Despite the strong concentration of true tool use cases in Corvida
and Passerida, independent constrasts suggest that common ancestry is not responsible forthe association between tool use and size of the neostriatum and whole brain. Our results
demonstrate that birds are more frequent tool users than usually thought and that the complex

1)

Corresponding authors’s e-mail address: louis.lefebvre@mcgill.ca

3) Current address: Ecole d’Optométrie, Université de Montréal.
4)

We are grateful to Simon Reader for comments on earlier versions and to Sarah
Timmermans for alerting us to the existence of Mlikovsky’s data. We also thank Simran
Kurir, Yutaka Nishioka and Johan Bolhuis for help with the German, Japanese and Dutchlanguage papers. This work was funded by an NSERC grant to LL and an FCAR fellowship
to NN.
© Koninklijke Brill NV, Leiden, 2002

Behaviour 139, 939-973
Also available online -940

LEFEBVRE, NICOLAKAKIS & BOIRE

cognitive processes involved in tool use may have repeatedly co-evolved with large brains inseveral orders of birds.

Introduction
When used by humans, hammers, sponges, pokers, anvils and vices are
all classi ed as tools. In other animals, however, only the  rst three areconsidered legitimate. This is because the de nition of ‘true’ tools in theliterature speci es that they must be detached from the substrate and directly
held by the animal in the hand or mouth (van Lawick Goodall, 1970; Beck,1980; McFarland, 1982). In this view, a vulture breaking an egg by hitting
it with a stone is using a tool, but a gull dropping an egg on a rock isnot. Several authors have criticised the arbitrariness (Hansell, 1987) andanthropocentrism (Shettleworth, 1998) of this distinction .
Studies of tool use in animals tend to focus on manipulative, largebrained species that are closely related to humans, e.g. primates (Fragaszy& Visalberghi, 1989; McGrew, 1992; Whiten et al., 1999). Birds, unlike
primates, lack both hands and close hominid parentage and are generally
thought to be poor tool users. A review from the 1960’s, for example,
concludes that the entire class (close to 10 000 species) features only one
documented case of true tool use, the insertion of twigs in crevices by the
woodpecker  nch of the Galapagos Islands (Thomson, 1964). The recent
description in Nature of leaf tool manufacture in New Caledonian crows(Hunt, 1996) is all the more noteworthy because of the apparent rarity ofsuch reports in birds.
In a series of review papers, Boswall (1977, 1978, 1983a, b) pointed
out that cases of tool use in birds may be more numerous that we think.
He classi ed the literature into two categories, ‘true’ and ‘bordeline’ cases.
Following the traditional de nition, borderline cases (called ‘proto-tools ’
by Parker & Gibson, 1977) involve the use of objects that are part of a
substrate, e.g. anvils on which prey are battered or dropped, wedges andthorns with which food is held, bait that is deposited on water to attract  sh.
True tools are detached from the substrate, e.g. hammers, probes, scoops,
sponges and levers held directly in the beak or foot. If true tool use iscognitively more demanding than is borderline tool use (Parker & Gibson,
1977; Hansell, 1987; Vauclair, 1997), relative size of key brain structures
could also distinguis h the two categories (Gibson, 1986).

TOOLS AND BRAINS IN BIRDS

941

In birds, there is large taxonomic variation in the relative size (regressedagainst body weight or divided by brainstem size) of neural structures
thought to underlie cognition. For example, the neostriatum /hyperstriatum
ventrale complex (Rehkämper & Zilles, 1991; Dubbeldam, 1989, 1991,
1998) is  ve and a half times larger in carrion crows than it is in quail(Rehkämper et al., 1991). Reader & Laland (2002; Reader, 1999; see also
Gibson, 1986) have shown that the taxonomic distributio n of tool use
cases is positively correlated with size of the neocortex and striatum inprimates. In this study, we look for similar neural correlates of tool use inbirds. Volumetric data on the neostriatum , hyperstriatum ventrale and othertelencephalic areas (see Fig. 1) are available for 32 avian species covering
17 parvorders (Boire, 1989; Rehkämper et al., 1991; Timmermans et al.,
2000; avian taxonomy according to Sibley & Monroe, 1990), while wholebrain size is available for 737 species from 35 parvorders (Mlikovsky, 1989a,b, c, 1990). We use both the 737 species data set on whole brains andthe 32 species data set on telencephalic areas to test the idea that neural
structure size is positively correlated with the taxonomic distribution of tool
use reports in birds and provides an independent criterion for distinguishin g
the true and borderline categories. For the 32 species data set, we compare
relative size of the neostriatum and hyperstriatum ventrale with that of twoother telencephalic structures that are thought to be less closely involved incognition, the wulst and the striatopallida l complex. Like the mammalian
neocortex, the neostriatum and hyperstriatum ventrale play a crucial rolein several kinds of learning (McCabe et al., 1982; Horn, 1990; Nottebohm
et al., 1990; MacPhail et al., 1993). In contrast, the wulst is a sensory
projection area for visual and somatosensory information (Karten et al.,
1973; Shimizu et al., 1995), while the striatopallida l complex is involvedin stereotyped, species-speci c responses (Reiner et al., 1984; Dubbeldam,
1998). Both the wulst and striatopallida l complex play some role in learned
behaviour (wulst: MacPhail, 1976; Shimizu & Hodos, 1989; Deng & Rogers,
1997, 2000; striatopallida l complex: Parent, 1986; Stewart et al., 1996;
Mezey et al., 1999), but they are less specialized in complex integration thanare the neostriatum and hyperstriatum ventrale. In a multiple regression, thesize of the wulst and striatopallida l complex should consequently be lessclosely correlated with the number of tool use reports than should size of theneostriatum and hyperstriatum ventrale.

942

LEFEBVRE, NICOLAKAKIS & BOIRE

Fig. 1. Coronal sections of the telencephalon of Alectoris chukar, illustrating the hyperstriatum ventrale (HV), the neostriatum (Neo), the archistriatum (Archi), the nucleus basalis(n Bas), the wulst (W), and the striatopallidal (Paleo) complex. Top: rostral section; bottom:
caudal section. Scale bars in upper left-hand corner represent 1 mm.

We use two data sources for estimating the number of tool use cases. First,
we review the specialized literature, starting from Boswall’s (1977, 1978,
1983a, b) comprehensive papers and incorporating cases published sincethen (e.g. Andersson, 1989; Marks & Hall, 1992; Hunt, 1996; Caffrey, 2000).
Secondly, we use feeding innovation data accumulated for several areasof the world (Lefebvre et al., 1997, 1998, 2001; Nicolakakis & Lefebvre,
2000; Timmermans et al., 2000). At present, this data base includes close

TOOLS AND BRAINS IN BIRDS

943

to 1800 cases of new, unusual or rare foraging techniques or food types
used by birds, found by exhaustively searching the short note section of 67
ornitholog y journals over an average of 30 years. Reader & Laland (2002;
Reader, 1999) have shown that the number of tool use reports is positively
correlated with innovation rate in primates. We look for a similar relationshipin birds. According to Wyles et al. (1983) and Wilson (1985), innovation ,social learning, brain size and cognitively-comple x behaviours like tool use
are all expected to co-vary in opportunisti c taxa that exploit a wide array of
rapidly-changin g environmental conditions.

Methods
Tool use cases
The specialized literature on tool use was  rst searched for all true and borderline cases
related to feeding and drinking, starting with the classic reviews of van Lawick Goodall(1970), Beck (1980) and Boswall (1977, 1978, 1983a, b). To these were added all cases
found in the literature after 1983, the year of Boswall’s last exhaustive review. These include
Andersson (1989), Hunt (1996) and the review by Switzer & Cristol (1999), as well as papers
from the bibliographies of innovation notes (e.g. Duyck & Duyck, 1984, found in Clayton and
Jollife, 1996) and articles listed under ‘tool-using’ in The Zoological Record. Other tool use
functions (e.g. grooming: Dubois, 1969; defence: Caffrey, 2001) are sometimes mentioned
in the literature, but we focused only on feeding and drinking because these are the only
behaviours covered by our other source, innovation reports.
Cases were classi ed in  ve categories, true tool use and four sub-categories of borderline
tool use (dropping prey on a hard substrate, battering on an anvil, baiting, holding preywith a wedge or skewer). We excluded all cases considered unreliable by Boswall, unlesslater reports concluded otherwise. For example, egg-breaking with stones in Hamirostra
melanosternon is listed in Wilson (1975), excluded by Boswall (1983a), but con rmed
by Debus (1991) and Pepper-Edwards & Notley (1991). Use of leaves for grasping nuts
in Probisciger aterrimus is also excluded by Boswall (1983a); this negative judgement iscon rmed by Bertagnolio (1994). Save for two exceptions, string-pulling was also excluded
because van Lawick Goodall (1970) and Boswall (1977) argue that the visual continuity
between the food and the string make the latter no different from a stem or branch. The two
exceptions we decided to include are the ice  shing cases described by Holmberg (cited by
Scott, 1974 and Boswall, 1977). In these cases, Boswall points out that there is no visualcontinuity between the line and the  sh hidden under the ice. The impact of our decision
is evaluated later in the results section by comparing inclusion and exclusion of the twocases. The effects of a second decision, inclusion or exclusion of cases from captivity, is also
evaluated in a similar way. A total of 71 cases of true or borderline tool use were found in thespecialized literature.
The second set of tool use cases was obtained by searching through the innovation database collected over the years in our laboratory. This data base currently contains 1796
innovations in 6 areas of the world (North America, western Europe, India, Australia, New944

LEFEBVRE, NICOLAKAKIS & BOIRE

Zealand, southern Africa), collected by exhaustively searching the short note sections of
67 ornithology journals over an average of 30 years (see Lefebvre et al., 1997, 1998 andNicolakakis & Lefebvre, 2000, for examples and details on the collection method). For
the purpose of this paper, a 68th journal was also searched, Noticias de Galapagos, which
covers a geographical zone outside the six included in our normal data base, but where
several tool using cases have been reported (e.g. Hundley, 1963; Curio & Kramer, 1964;
Millikan & Bowman, 1967). Innovations are de ned as the ingestion of a new food type or
the use of a new foraging technique, based on terms in the short note such as ‘ rst report’,‘unusual’, ‘unknown’, ‘rare’, ‘opportunistic’, ‘adaptable’, ‘strange’, ‘not noted before’, ‘notrecorded’, ‘not mentioned in the literature’. All measures taken up to now indicate that
innovation frequency is a valid and reliable operational estimate of feeding  exibility in birds.
Correlations between the taxonomic distribution of innovation rates obtained by different
readers (usually blind to the hypothesis) on the same sets of journals vary between 0.827
and 0.910 (p < 0:001; Lefebvre et al., 1998; Nicolakakis & Lefebvre, 2000). Intertaxon differences in innovation rate correlate with problem-solving differences found in
the literature (Timmermans et al., 2000) and in experimental tests conducted in the  eld
and in captivity (Webster & Lefebvre, 2001). Nine potential biases have been examined:
number of species per taxonomic group, avian population size, research effort per taxon,
interest by ornithologists, reporting bias, journal source, editorial style, juvenile developmentmode, phylogeny. Only the  rst of these variables, species number, needs to be included in
multiple regressions to express innovation rate as an unbiased index (Lefebvre et al., 1998,
2001; Nicolakakis & Lefebvre, 2000). The  ve tool use categories taken from the specialized
literature were used with the innovation data base. 61 cases of true or bordeline tool use
were found in the data base; seven of these also appeared in the specialized literature andwere eliminated. Among the dropping cases, we included breaking of booby eggs on rocks
by Geospiza dif cilis (Köster & Köster, 1983; Grant, 1986). In this case, the eggs are notdropped from the air, but thrown down by pushing, rolling, bracing and levering with the bill
and feet; substrate use is thus the same as in other dropping cases, even if the bird is not in ight when it drops the egg.
Once all tool use cases in the innovation data base had been identi ed, they were removed
from the data set in each geographic zone. For each zone, innovation frequency per taxon
was then regressed against its most important confound, species number, obtained fromstandard ornithology texts (India: Ali & Ripley, 1995; New Zealand: Falla et al., 1979;
Australia: Simpson & Day, 1996; North America: Scott, 1987; Europe: Hagemeijer & Blair,
1997; southern Africa: Sinclair & Hockey, 1996) and reclassi ed according to Sibley &Monroe (1990) if initially given in non-molecular taxonomy. Standardized residuals werethen determined for each zone where a taxonomic group was present and a weighted averageinnovation rate calculated by taking into account the number of innovation cases yieldedby each zone, similar to the procedure used by Timmermans et al. (2000). Sampling error
potentially caused by a small regional data set is minimized when each zone is weighted
by the number of cases it contributes to the total. A large avifaunal zone with extensive
literature coverage (e.g. western Europe: 701 innovations in 24 journals) is likely to yielda more reliable measure than is a smaller zone with fewer journals (e.g. New Zealand: 57
innovations in only one journal).

TOOLS AND BRAINS IN BIRDS

945

Neuroanatomical data
Data on whole brains were taken from Mlikovsky (1989a, b, c, 1990). These data include cranial volumes (with appropriate corrections to estimate actual brain mass) measured by the author on museum specimens for 615 species (Mlikovsky, 1989a), as well as fresh-weight dataon 151 species taken from previously published sources (e.g. Crile & Quiring, 1940; Portmann, 1947; Armstrong & Bergeron, 1985). We  rst checked all secondary data included in
Mlikovsky’s tables against the previously published source and averaged sets of species listed
as separate by Mlikovsky but now considered monospeci c by Sibley & Monroe (1990). We
then took standard body weights from the CRC Handbook (Dunning, 1993) and regressed
log brain size against log body weight for all species. From the residuals of this regression,
we looked for outliers that could potentially indicate an unreliable source; any species whose
residual brain size was more than 2 standard deviations away from the mean of its family
was eliminated. We reran the regression of log brain size against log body weight for the 737
remaining species and used the residuals of this regression as our  nal data. Mean residuals
were calculated for each parvorder, following the procedure used in previous papers on innovations and neural structure size (Lefebvre et al., 1997, 1998, 2001; Nikolakakis & Lefebvre,
2000; Timmermans et al., 2000). In the analyses below, the species level residual is usedwhenever a tool using species is included in Mlikovsky’s data base (61 of the 125 cases oftool use). When it is not, the mean residual of the closest available taxonomic level (genus:
21 cases; family: 36 cases; parvorder: 1 case; suborder: 6 cases) is used as an estimate. Mean
residual at the parvorder/suborder level predicts 73% of the variance at the species level, whilemeans at the genus and family level respectively predict 91% and 82% of the species levelvariance. Mlikovsky’s data base includes the 32 species featured in Boire (1989) and Rehkämper et al. (1991); the correlation between the brain sizes measured in the two data sources is0.998 (N D 32, p < 0:001), indicating that Mlikovsky’s measurements are reliable.
Volumetric data for the four telencephalic areas (Fig. 1) were taken from Boire (1989;
28 species) and Rehkämper et al. (1991; 4 species). Rehkämper et al. (1991) cover 6
species, but two of these, Coturnix coturnix and Phasianus colchicus, are also included in
Boire (1989); for these cases, we used the mean of the data reported in the two sources.
Of the four telencephalic areas used in the analysis, only the hyperstriatum ventrale isanatomically de ned in identical terms in Boire (1989) and Rehkämper et al. (1991).
For the other three structures, areas are lumped or split in different ways and must be
regrouped at a level where they are are identical. The neostriatum of Rehkämper et al. (1991)
includes the archistriatum, neostriatum and nucleus basalis prosencephali of Boire (1989).
The striatopallidal complex comprises the paleostriatum in Rehkämper et al. (1991) andthe basal telencephalon, paleostriatum augmentatum and paleostriatum primitivum in Boire(1989). The wulst is measured as a single structure in Boire (1989), whereas it corresponds
to the sum of the hyperstriatum accessorium (incorporating the hyperstriatum intercalatus
superior) and hyperstriatum dorsale in Rehkämper et al. (1991). As was done for the wholebrain, volume of each of the four structures was regressed (after log transformation) against
the body weight of the subjects given in Boire (1989) and Rehkämper et al. (1991); average
residual deviations were then calculated for each of the 17 parvorders present in the sample.
Regressions, phylogeny and independent contrasts
All regressions were conducted on Systat (Wilkinson, 1995). Depending on the analysis, thedependent variable was the taxonomic distribution of either true or borderline tool use reports.

946

LEFEBVRE, NICOLAKAKIS & BOIRE

The number of reports was log transformed before analysis to normalize its distribution,
since the data include very large numbers (true tool use in Corvida represents 40% of thesample) and very small ones (several parvorders with zero cases). Depending on the analysis,
the independent variables were (1) mean residual brain size per taxon; (2) mean residual
size per taxon of each of the four telencephalic areas; (3) innovation rate (calculated as aweighted average per taxon for the 6 zones of the world, excluding tool use cases); (4) numberof species per taxon (log transformed), an obvious confounding variable of the number oftool use reports (a parvorder like Passerida, which has 3556 species according to Sibley &Monroe, 1990, is likely to yield more reports than the parvorder Odontophorida, which has
only six species); and (5) juvenile development mode, a known confounding variable of avian
brain size (Bennett & Harvey, 1985; nidicolous, altricial birds have larger brains as adults thando nidifugous, precocial ones).
Three estimates of tool use were used in the multiple regressions. The  rst one used
all cases found (39 true tools, 86 borderline), tabulated them at the level of the parvorderand entered them in the regressions as independent cases. The second estimate eliminatedpotential pseudoreplication and phyletic confounds caused by genera with many tool use
reports. Some genera include several species that use one or more techniques. For example,
there are 10 cases of borderline tool use in Larus (dropping and baiting),  ve in Pitta (allbattering) and 11 in Corvus (dropping and battering). These multiple entries could bias theresults by arti cially creating many data points with similar relative brain size values. We
eliminated the 48 cases where more than one species and/or more than one technique arereported in a genus and redid the regressions on these genus-level data. The third estimate
was based on independent contrasts, not frequencies per taxon. If Passerida and Corvida bothhave large brains and a high number of tool use reports, the association between these traits
could be caused by the relatively recent divergence of the two parvorders; a similar phyletic
confound is less likely to be the case for Corvida and Psittaciformes, which are very distantly
related (see phyletic trees in Figs. 3 to 6). We used the CAIC computer program written
by Purvis & Rambaut (1995), a technique that factors out common ancestry by estimating
trait values at ancestral nodes, averaging empirical values for related extant taxa weighted byphyletic distance. The phyletic branch lengths entered in the CAIC regressions are taken from
Sibley & Ahlquist (1990) and are based on DNA hybridization distances. Multiple regressions(forced through the origin) are then conducted on the contrasts, not the actual parvorders usedin our  rst two estimates.

Results
Tool use distributio n
A total of 125 cases were found in the two data sources, after removal of
the 7 overlapping reports. Despite the low degree of overlap, the two data
sources provide similar taxonomic distribution s of total tool use reports:
the correlation between the two sources is 0.806 (p < 0:001, N D
35 taxonomic groups). The 125 cases are listed in Table 1 by tool use
category and taxonomic group. Several trends are immediately obvious in

TOOLS AND BRAINS IN BIRDS

947

this table. The cases are widely distributed amongst 104 species in 15
parvorders. Nineteen species use more than one technique, seven of themin the genus Corvus. The common crow Corvus brachyrhyncho s is the
species showing the most techniques; it uses stone hammers to open acorns,
sharpens a piece of wood to probe a hole, drops palm fruits and nuts onasphalt roads (but may not systematically use cars to break the food open,
Cristol et al., 1997, contra Maple, 1974 and Grobecker & Pietsch, 1978;see however Caffrey, 2001), batters  sh on hard sand (also scaling it on
the sand by scraping), and, in captivity, uses a scoop to carry water todry food. Several tool use categories are concentrated in particular taxa.
Twenty-eight of the 39 cases of true tool use occur in two Passeriforme
parvorders, Passerida and Corvida (suborder Passeri). All four cases of tool
use in Psittaciformes involve captive birds. Holding food with a wedge ora skewer is reported in Corvida and Piciformes. Dropping food to break
it open on a hard surface is equally distributed among three parvorders,
Charadriida, Accipitrida and Corvida. There are no tool use reports in large,
well-studied taxa like Phasianida, Anseriformes, Columbiformes, Falconida,
Apodiformes and Podicipedida, nor in smaller, poorly-studie d groups likeColiiformes, Galbuliformes, Trogoniformes, Phaethontida and Pteroclides(see phyletic trees in Figs. 4 and 6).
The relationship between brain size and each of the tool use categories is
illustrated in Fig. 2. Brain sizes are directly available for the species involvedin 61 cases. In the 64 others, the species are assigned the mean residual brain
size of its genus (N D 21/, family (N D 36/, parvorder (N D 1/ or suborder(N D 6, all Tyranni). As can be seen in Fig. 2, dropping, baiting and battering
on an anvil are used by birds with a wide range of brain sizes. Several of these(e.g. gulls, herons, anhingas, roadrunners) have negative brain size residuals.
In contrast, true tool use is overwhelmingly shown by birds with positive
residuals. The two notable outliers are a captive oystercatcher that uses sticks
to dislodge invertebrates in a zoo (residual brain size ¡0:598; Olney, in
Boswall, 1978) and the bristle-thighe d curlew, who throws coral stones at
albatross eggs on Paci c islands (Marks & Hall, 1992). It is noteworthy that
this species, Numenius tahitiensis , is the one with the largest brain in its
parvorder, Scolopacida (residual D ¡0:236; parvorder mean D ¡0:757,
N D 20).
On average, true tool users have a larger residual brain size than doborderline tool users; the mean for the  rst category (1.060, SEM D 0.130,

Ceryle rudis
Dacelo novaeguineae
Halcyon smyrnensis
Geococcyx californianus
Podargus strigoides

Eulabeornis castaneoventris
Numenius tahitiensis
Buteo jamaicensis
Gypaetus barbatus
Anhinga anhinga
Threskiornis molucca
Xenicus gilviventris

Coraciiformes

Ralli
Scolopacida
Accipitrida

SulidaCiconiida
Tyranni

Pitta erythrogaster

Ceryle rudis
Eurypya helias
Larus fuscus
Milvus migrans
Ardeola ralloides
Butorides striatus

Coraciiformes
Grui
Charadriida
Accipitrida
Ciconiida

Cuculiformes
Caprimulgi

Species

Taxon

Batter on anvil
Batter crab on rocks
Batter rat and bone
Batter frog on branchBatter reptiles on rocks
Batter feathers off
prey against dead bough
Batter shells on anvils
Batter crabs on rocks
Slam snake on rock in  ight
Batter bones on rocks
Batter  sh on branchBatter mussels on anvils
Batter grasshopperon corrugated iron
Batter hard-shelled prey

Technique
Bait  sh
Bait with bread
Bait with maggots
Bait with bread; captive
Bait with bread
Bait with insects
Bait with bread,
insects, twigs, feathers

McDonald 1974

Woinarski et al. 1998
Marks & Hall 1992
Ellis & Brunson 1993
Fleming 1955
Wellenstein & Wiegmann 1986
Vestjens 1973
Sibson 1974

Cooper 1981
Roberts 1961
Tehsin 1989
Meinzer 1993
Wheeler 1943

Root, in Boswall 1983aAlders, in Boswall 1977
Sinclair 1984
Roberts 1982
Crous 1994
Higuchi 1986; Keenan 1981;
Foxall & Drury 1987;
Wood 1986; English 1987;

Reference

0.771*¡0:577*
0.236
0.843
0.860
¡1:342¡0:0210.771*

0.161
0.790
0.193
¡0:2460.716

0.161¡0:0660.155
0.325¡0:761¡0:308Brain size

T ABLE 1. Borderline and true tool techniques used by different species, classi ed by taxon. Brain size given as
residual deviation from log-log regression against body weight

948
LEFEBVRE, NICOLAKAKIS & BOIRE

Passerida

CorvidaTaxon

Corcorax melanorhamphos
Ailuroedus dentirostris
Daphoenositta chrysoptera
Falcunculus frontatus
Ficedula hypoleuca
Myiophonus caeruleus
Oenanthe leucura
Oenanthe oenanthe
Saxicola rubetra
Saxicola torquata
Saxicoloides fulicata
Turdus iliacus
Turdus pelios
Turdus philomelos
Anthus petrosus
Passer domesticus

Colluricincla harmonica

Corvus brachyrhynchos

Species
Pitta guajana
Pitta moluccensis
Pitta sordida
Pitta versicolor
Lanius collaris

T ABLE 1. (Continued)
TechniqueBatter hard-shelled prey
Batter hard-shelled prey
Batter hard-shelled prey
Batter hard-shelled prey
Batter grasshopper on
post then skewer on thorn
Batter  sh on sand,wipe on sand (to scale?)
Batter mouse on stump,
wren and robin on rockBatter mussels
Batter snails on stones
Bash insects on branchBash insects on branchBatter snails
Batter shells on rocks
Batter lizard on stone
Batter caterpillars
Batter caterpillars
Batter snails
Batter frog and gecko
Batter snails
Batter snails on rocks
Batter snails on rocks
Batter snails
Batter wings
off damsel ies

1.554*
1.313*
1.554*
1.554*¡0:045*¡0:045*¡0:045*¡0:045*¡0:234¡0:234*¡0:045*
0.364
0.379
0.088
¡0:846*0.402

1.554*

Tilt 1962; Reilly 1966
Hobbs 1971
Marshall 1954
Noske 1985
Noske 1985
Page 1978
Smythies, in Boswall 1978
Heselden et al. 1996
King 1978
King 1978
Fisher 1979
Sivasubramanian 1991
Richards 1977
Walsh & Walsh, in Boswall 1983b
Boswall 1977
Tutt 1990
Hammond 1997

2.121

Brain size
0.771*
0.771*
0.771*
0.771*
0.318

Phillips 1978

Reference
Chasen 1939
Robinson 1927
Robinson 1927
Hindwood 1966
Gore 1981

TOOLS AND BRAINS IN BIRDS

949

Corvus albicollis

Accipitrida

CorvidaCariama cristata
Numenius tahitiensis
Catharacta skua
Larus argentatus
Larus canus
Larus delawarensis
Larus dominicanus
Larus glaucescens
Larus marinus

Pycnonotus cafer
Acridotheres fuscus

Species
Ploceus philippinus

Larus melanocephalus
Larus occidentalis
Larus paci cus
Aquila chrysaetos
Gypaetus barbatus
Haliaeetus leucocephalus
Neophron percnopterus
Pandion haliaetus

Grui
Scolopacida
Charadrida

Taxon

Drop on substrate
Drop eggs on stones
Drop eggs
Drop penguin eggs
Drop rabbits on rocks
Drop molluscs
Drop molluscs
Drop egg on water
Drop molluscs
Drop crabs on hard sand;drop rat
Drop molluscs
Drop molluscs
Drop mussels on road
Drop tortoises
Drop bones and tortoise
Drop tortoises
Drop tortoise and lizards
Drop conches on
concrete- lled drums
Drop tortoises

TechniqueBatter frogs
on electrical wire
Batter gecko on wall
Batter mouse

T ABLE 1. (Continued)

Uys 1966

Kooij & van Zon 1964
Marks & Hall 1992
Sladen, in Boswall 1977
Young 1987
Cristol & Switzer 1999
Cristol & Switzer 1999
Moon 1992
Cristol & Switzer 1999
Cramp & Simmons 1983
Harber & Johns 1947
Cristol & Switzer 1999
Cristol & Switzer 1999
Wheeler 1946
Leshem 1985
Boswall 1977
Bindner 1968
Leshem 1985
Leshem 1985

Bharos 1999
Johnsingh 1979

Reference
George 1973

1.780

¡0:198*¡0:198*¡0:198*
0.164
0.860
0.403
0.264
0.810

¡0:013*
0.236¡0:198*¡1:1790.142¡0:198*¡0:098¡0:198*¡0:2870.455*
0.496*

Brain size
¡0:347*950
LEFEBVRE, NICOLAKAKIS & BOIRE

Corvida

Piciformes

Passerida

Taxon

Melanerpes lewis
Melanerpes carolinensis
Picoides villosus
Picoides pubescens
Sphyrapicus varius
Cracticus spp
Cracticus torquatus

Dendrocopos major
Dendrocopos syriacus

Hold with wedge or skewer
Wedge in enlarged hole
Crack in wall as
wedge and anvil
Wedge in enlarged hole
Wedge seed in crevice
Wedge seed in crevice
Knothole as vice
Wedge seeds in barkThorns to impale prey
Wedge in forks andcrevices; skewer on branch

Drop shells on roads,
place nuts at traf c lights
Drop mussels
Drop horse chestnuts
Drop nuts
Drop ‘egg’ on soil
Drop gerbil
Push, lever, bill braceeggs down on rocks

Corvus corone

Corvus frugilegus
Corvus monedula
Corvus moneduloides
Corvus rhipidurus
Corvus splendens
Geospiza dif cilis

Drop shells
Drop bones

Corvus caurinus
Corvus corax

T ABLE 1. (Continued)
Technique
Drop nuts on freeway

Species
Corvus brachyrhynchos

1.435
1.352*
1.189*
1.189*
2.215*
2.215*
1.427*
1.554*
1.554*
Law 1929
Erlwein 1996
Erlwein 1996
Davis 1995
Labedz 1980
Boswall 1977
Sedgwick 1947

1.554
1.278
1.694*
1.694*
1.694*
0.230*

1.530

1.694*
1.973

Brain size
2.121

Sielmann, in Boswall 1977
Gorman 1998

Reference
Grobecker & Pietsch 1978;
Maple 1974; Cristol et al. 1997
Zach 1978, 1979
Lorenz, in van Lawick
Goodall 1970
Conder & Everett 1979
Nihei 1995
Priestley 1947
Gibson 1992
Hunt 1996
Andersson 1989
Fitzwater 1967
Köster & Köster 1983;
Grant 1986

TOOLS AND BRAINS IN BIRDS

951

Amazona ochrocephala
Cacatua galerita

Psittaciformes

Neophron percnopterus

Accipitrida

Ciconia ciconia

Leptoptilos crumeniferus
Colluricincla harmonica

Ciconiida

CorvidaHamirostra melanosternon

Numenius tahitiensis
Haematopus ostralegus

Scolopacida
Charadriida

Psittacus erithacus
Anodorhynchus hyacinthinus

Melanerpes uropygialis

Sitta carolinensis

Species
Pica pica
Lanius spp
Thryothorus ludovicianus

Piciformes

Passerida

Taxon

True tools
Gouges bark chips tobring honey to young
Bell to scoop seed, captive
Bottle top to scoop
water, captive
Pipe to bail water, captive
Leaf to steady nutcracking;captive
Throw stones at eggs
Stick to dislodge
invertebrates; captive
Stones to hammer
ostrich eggs, smash lizard
Throw stones at eggs;
captive
Wring moss in beak togive chicks water
Stick to get prey in hole
Twigs for probing

Technique
Wedge nuts in crevice
Thorns to impale prey
Wedge sun ower seeds
between bricks
Knotholes as vice

T ABLE 1. (Continued)

0.287
1.393
1.554*

Marshall 1982
Mitchell, in Boswall 1977

0.543*

0.264

van Lawick Goodall 1970
Iankov 1983
Debus 1991; PepperEdwards & Nottley 1991
Rekasi 1980

0.236
¡0:5981.606*
2.913
Smith 1971
Bertagnolio 1994
Marks & Hall 1992
Olney, in Boswall 1978

1.900
1.310

1.189*

0.929*

Brain size
1.916
0.381
0.187*

Murphy, in Boswall 1983aLongthorp, in Boswall 1983aAntevs 1948

Davis 1995

Reference
Rolando & Zunino 1992
Boswall 1977
Haney 1982

952
LEFEBVRE, NICOLAKAKIS & BOIRE

Passerida

Taxon

Falcunculus frontatus
Camarhynchus heliobates
Camarhynchus pallidus
Camarhynchus pallidus
Certhidea olivacea

Cyanocorax yncas
Daphoenositta chrysoptera

Corvus rhipidurus
Corvus splendens
Cyanocitta cristataCorvus moneduloides

Corvus corone

Corvus corax

Corvus brachyrhynchos
Corvus caurinus

Corvus brachyrhynchos
Corvus brachyrhynchos

Species
Corcorax melanorhamphos

T ABLE 1. (Continued)
Technique
Empty shells to hammer
open closed mussels
Stone to smash acorn
Cup to carry water todry mash, captive
Sharpen wood to probe
Stick to pry peanut
from bamboo, captive
Pull  shing lines toget  sh under ice
Pull  shing lines toget  sh under ice
Twigs, leaves asprobes, hooks
Hammer ‘egg’ with rock
Leaf to get ants from hole
Tear paper, use as
rake and sponge, captive
Twig under bark
Use and carry twigs toopen wood-borer grub
Twigs for probing
Twigs for probing
Wood chips scrapers
Twig probes and levers
Twig probes

2.121
1.694*
1.973

1.694*
1.694*
1.694*
1.621
1.181
1.554*
1.554*
0.230*
0.230*
0.230*
0.230*

Caffrey 2000
Jewett, in Boswall 1983a
Holmberg, in Boswall 1977;
Scott 1974
Holmberg, in Boswall 1977;
Scott 1974
Orenstein 1972; Hunt 1996
Andersson 1989
Rajan & Balasubramanian 1989
Jones & Kamil 1973
Gayou 1982
Green 1972
Richards, in Boswall 1977
Curio & Kramer 1964
Greenhood & Norton 1999
Millikan & Bowman 1967
Hundley 1963

1.530

2.121
2.121

Brain size
1.554*

Duvall, in Boswall 1978
Beck 1980

Reference
Hobbs 1971

TOOLS AND BRAINS IN BIRDS

953

Sitta pusilla
Sitta carolinensis

Parus caeruleus
Parus gambeli
Parus major
Parus palustris

Turdus merula

Bradornis microrhynchus

SpeciesEuphagus cyanocephalus

T ABLE 1. (Continued)
Technique
Dunked prey as sponge
to bring nestlings water
Grass stem in holeto  sh for termites
Twig broom to search
for food in snow
Twig to push nuts
Splinter in crack
Pine needles in crevices
Sponge up food powder,
wrap to store; captive
Bark scale levers
Bark lever

0.929*
0.929*
Morse 1968; Pranty 1995
Mitchell 1993

¡0:110Priddey 1977

0.510
0.680*
0.626
0.430¡0:045*

McNaughton, in Boswall 1983b

Coombes, in Boswall 1977
Gaddis, in Boswall 1983b
Duyck & Duyck 1984
Clayton & Jollife 1996

Brain size
0.230*

Reference
Koenig 1985

* Data unavailable for this species; value is mean residual for the genus, family or suborder.

Taxon

954
LEFEBVRE, NICOLAKAKIS & BOIRE

TOOLS AND BRAINS IN BIRDS

Fig. 2.

955

Residual brain size for the species using true tools and the four sub-categories ofborderline tools. The dotted line represents the mean residual for all birds.

N D 39/ is signi cantly different from the mean for the second category(0.581, SEM D 0.090, N D 86; F1;123 D 8:99, p D 0:003/. The difference inresidual brain size between true and borderline tool users is robust; it remains
signi cant when we restrict the analysis to one case per genus, eliminating
49 reports (p D 0:017/, and when we exclude the 11 cases from captivity(p D 0:035/, the two line pulling reports (p D 0:005/, or the 64 cases
where a species’ brain size was estimated from the mean of its genus, family,
parvorder or suborder (p D 0:009/.
True tools and telencephalic areas
The difference between true and borderline tool use is also evident in thetaxonomic distribution of reports. Overall, the distributio n of borderline tool
reports is most consistentl y correlated with innovation rate, while neural
structure size is the best correlate of true tool use reports (Tables 2 and 3).
Species number per taxon (an obvious confounding variable of the number oftool use reports) also remains in most of the  nal multiple regression models.
Tables 2 and 3  rst present the individual correlation .r, then p) of eachindependant variable with true or borderline tool use, then the p value for956

LEFEBVRE, NICOLAKAKIS & BOIRE

that variable at the end of the multiple regressions. As predicted, size ofthe neostriatum and hyperstriatum ventrale is more strongly correlated withtrue tool use than is size of the striatopallida l complex and wulst (Table 2).
In the multiple regressions, the neostriatum is the only structure that remains
along with species number. The four telencephalic areas are highly correlatedwith each other (r of residual neostriatum size with that of hyperstriatum
ventrale: 0.989; with wulst: 0.798; with striatopallida l complex: 0.962; allp < 0:001, N D 17/. The one with the highest correlation with true tool use,
the neostriatum , thus accounts for the common variance of the four areas in
the multiple regression, causing all others to drop out. Innovation rate also
drops out of the  nal model despite a strong individual correlation with true
tool use before the multiple regression. This is because innovation rate iscorrelated with size of the telencephalic areas; its share of the variance intrue tool use reports is accounted for by the stronger effect of neostriatum
size. Note that innovation rate is even more highly correlated with size ofthe hyperstriatum ventrale (individual correlation D 0.653; p after multiple
regression D 0.006) than it is with size of the neostriatum (individual
correlation D 0.611; p after multiple regression D ns); if we omit tool
use from the multiple regression and put innovation rate as the dependent
variable, then the hyperstriatum ventrale is the only structure that remains inthe  nal model (r 2 D 0:385, F1;14 D 10:39, p D 0:006/.
Identical conclusions apply whether we include all reports or keep only
one per genus (Table 2). Independent contrasts also yield similar results toregressions on phyletically-uncorrecte d taxa (Table 2), despite an obvious
concentration of cases in Corvida and Passerida (Fig. 3). Juvenile development mode is non-signi cant in all analyses here and below, both in the individual correlations and multiple regression models. Figure 3 illustrates thetaxonomic distributio n of true tool use residuals (regressed against species
number), as well as residual size of the neostriatum (regressed against bodyweight) for the 17 parvorders (phyletic tree proportional to DNA hybridizations distances in Sibley & Ahlquist, 1990).
True tools and whole brains
The results on telencephalic areas are con rmed at the level of the wholebrain for three of the four estimates of true tool use distribution . Relative
brain size is (with species number) the only variable that remains in the

957

TOOLS AND BRAINS IN BIRDST ABLE 2. Association between true and borderline tool use frequency andrelative size of the four telencephalic areas, species number per taxon andinnovation rate (see text for details)
True tools
individual
correlations
Total frequency/taxon
Neostriatum 0.803
HV
0.790
Pallidal
0.756
Wulst
0.658
Species0.694
Innovation
0.728

Borderline toolspp in multiple
regression<0.001<0.001
0.001
0.006
0.003
0.001

0.001
ns
ns
ns
0.020
ns

individual pcorrelations
0.598
0.581
0.536
0.455
0.589
0.656

0.014
0.018
0.032
0.076
0.016
0.006

p in multiple
regression
ns
ns
ns
ns
ns
0.006

r 2 D 0:739, F2;14 D 23:70, p < 0:001 r 2 D 0:389, F1;14 D 10:55, p D 0:006
Without multiple entries/genus
Neostriatum 0.815 <0.001
HV
0.811 <0.001
Pallidal
0.794 <0.001
Wulst
0.634
0.008
Species
0.690
0.003
Innovation
0.730
0.001

0.001
ns
ns
ns
0.013
ns

0.614
0.596
0.522
0.585
0.622
0.624

0.011
0.015
0.038
0.017
0.010
0.010

ns
ns
ns
ns
ns
0.010

r 2 D 0:751, F2;14 D 25:11, p < 0:001 r 2 D 0:346, F1;14 D 8:94, p D 0:010
Independent contrasts
Neostriatum 0.745
HV
0.729
Pallidal
0.708
Wulst
0.544
Species
0.576
Innovation
0.526

0.001
0.002
0.003
0.036
0.025
0.044

0.002
ns
ns
ns
0.031
ns

0.493
0.457
0.418
0.324
0.444
0.567

0.062
0.087
0.121
0.239
0.097
0.027

ns
ns
ns
ns
ns
0.022

r 2 D 0:670, F2;13 D 14:72, p < 0:001 r 2 D 0:322, F1;14 D 6:64, p D 0:022

 nal multiple regression model for phyletically-uncorrecte d frequencies, forthe data set that eliminates multiple entries per genus and for one of thetwo regressions on independent contrasts. Two versions of the independent
contrasts are needed here, because the contrast produced by CAIC at thenode where suborders Tyranni and Passeri meet is an outlier that skews the
distributio n of true tool use cases, causing it to signi cantly differ fromnormality (p < 0:05/. The problem is caused by the very large difference

958

LEFEBVRE, NICOLAKAKIS & BOIRE

T ABLE 3. Association between true and borderline tool use frequency andmean residual brain size, species number per taxon and innovation rate (seetext for details)
True tools
individual
correlationsp

Total frequency/taxon
Brain size
0.493
0.004
Species
0.597<0.001
Innovation
0.467
0.006

Borderline tools

p in multiple
regression

individual
correlations

pp in multiple
regression

0.034
0.002
ns

0.456
0.653
0.510

0.008
<0.001
0.002

ns
0.001
0.037

r 2 D 0:413, F2;32 D 12:94, p < 0:001
Without multiple entries/genus
Brain size
0.516
0.002
Species
0.602<0.001
Innovation
0.466
0.006

0.021
0.002
ns

r 2 D 0:434, F2;32 D 14:04, p < 0:001
Independent contrasts
Brain size
0.389
Species
0.415
Innovation
0.422

0.028
0.018
0.016

ns
ns
0.014

r 2 D 0:178, F1;31 D 6:73, p D 0:014

r 2 D 0:472, F2;30 D 15:30, p < 0:001
0.454
0.650
0.533

0.008
<0.001
0.001

ns
0.001
0.022

r 2 D 0:483, F2;30 D 15:97, p < 0:001
0.373
0.575
0.433

0.035
0.001
0.013

ns
<0.001ns

r 2 D 0:331, F1;31 D 15:31, p < 0:001

in true tool use cases between Passeri (Passerida plus Corvida, 28 cases)
and Tyranni (no reported cases), given the small genetic distance between
the suborders (Fig. 4). We therefore ran mutiple regressions with the outlier
and without it. When the Tyranni-Passeri node is omitted, brain size isthe only variable (with species number) that remains in the  nal model;
note that exclusion of this node does not eliminate the 28 Passeri cases,
but simply contrasts them with other taxa at higher nodes in the phyletictree. When the outlier is included, brain size is signi cantly correlated withtrue tool use distributio n in individual correlations, but drops out of themultiple regression because of the higher contributio n of innovation rate.
Innovation rate is correlated with relative brain size (r D 0:499, p D 0:003,
N D 32/, which is why it accounts for the common variance with true tool
use distributio n in the  nal step of the regression. Figure 4 illustrates residual
true tool use per taxon (regressed against species number) and residual size

TOOLS AND BRAINS IN BIRDS

959

Fig. 3. (A) Phyletic tree of the 17 taxa for which telencephalic areas are available; branch
lengths are proportional to DNA hybridisation distances given in Sibley & Ahlquist (1990).
(B) Residual true tool use reports per taxon. (C) Residual size of the neostriatum.

of the whole brain (regressed against body weight) for the 35 parvorders(phyletic tree proportional to DNA hybridizations distances in Sibley &Ahlquist, 1990).
Borderline tools
In  ve of the six analyses conducted on borderline tools (Tables 2 and 3),
frequency per taxon is more strongly associated with innovation rate than it iswith size of the whole brain or of speci c telencephalic areas. At the level of
the whole brain, innovation rate is the only variable remaining (with species
number) in the  nal multiple regression model on phyletically-uncorrecte dfrequencies and on data that eliminate multiple entries per genus. In the
independent contrasts, the effect of innovation rate falls just short (0.087) of
the 0.05 level of signi cance. Contrary to the case seen above for true tools,
the contrast between Tyranni and Passeri does not yield an extreme value inthis analysis (Fig. 5). At the level of the four telencephalic areas, relative sizeof the neostriatum and hyperstriatum ventrale is signi cantly correlated withborderline tool use per taxon in the individual correlations, but drops out for
two of the three mutiple regressions due to a stronger effect of innovation
rate (illustrated in Fig. 6). Relative size of the neostriatum remains in the nal model only for independent contrasts (Table 2).

960

LEFEBVRE, NICOLAKAKIS & BOIRE

Fig. 4. (A) Phyletic tree of the 35 taxa for which whole brain data are available; branch
lengths are proportional to DNA hybridisation given in Sibley & Ahlquist (1990). (B) Residual true tool use reports per taxon. (C) Residual brain size.

Discussion
Two conclusions can be drawn from our results. First, tool use in birds ismuch more common than is often thought. Contrary to Thomson’s (1964)
statement, we found over 120 cases in 104 species, with 39 cases in thetrue tool category. A search through the innovation data base, an often
disregarded, low impact factor section of the literature, allowed us to double
the data set obtained from specialized reviews, yielding taxonomic trends
that were highly correlated with those of the specialised literature. Secondly,
three lines of evidence show that true tool users differ from borderline toolusers in the size of key neural structures: true tool users show a larger average
brain size, as well as a positive relationship between frequency of cases
per taxon and both size of the whole brain and size of the neostriatum. In
contrast, innovation rate is the best predictor of borderline tool use per taxon
in most of our regressions.

TOOLS AND BRAINS IN BIRDS

961

Fig. 5. (A) Phyletic tree of the 35 taxa for which whole brain data are available; branch
lengths are proportional to DNA hybridisation given in Sibley & Ahlquist (1990). (B) Residual borderline tool use reports per taxon. (C) Weighted innovation rate.

Our data con rm the distinction between true and borderline tool use emphasized by van Lawick Goodall (1970), Parker & Gibson (1977), Beck(1980), Boswall (1977, 1978, 1983a, b) and McFarland (1982). Compared
to borderline cases, true tool use probably involves a more sophisticate d integration of the potential uses of an object (Hansell, 1987), as well as theintricate movements needed for its manipulation . This integration should be
favoured by larger brain areas involved in tool use control. Our results support Parker & Gibson’s (1977) and Vauclair’s (1997) suggestions that borderline and true tool use categories represent different degrees of cognitive
ability, perhaps associated with differences in Piagetian sensorimotor stages(see Parker & Gibson, 1977). Whether a species is capable of using a given
degree may depend on the relative size of its neostriatum , but even species
capable of true tool use may  rst try simpler techniques. This is illustrated
by Andersson’s (1989) description of ‘egg’-breaking attempts by a fan-tailed
crow in Kenya. Because the ‘egg’ (a ping-pong ball mistakenly treated as anegg) could not be broken, the crow used a sequence of increasingly com-

962

LEFEBVRE, NICOLAKAKIS & BOIRE

Fig. 6. (A) Phyletic tree of the 17 taxa for which telencephalic areas are available; branch
lengths are proportional to DNA hybridisation distances given in Sibley & Ahlquist (1990).
(B) Residual borderline tool use reports per taxon. (C) Weighted innovation rate.

plex techniques: it  rst simply pecked at the shell with its beak, then  ew
up with the ‘egg’ and dropped it, then attempted to hammer the shell withan oversize stone, switching at last to a stone of manageable size to increase
hammering ef ciency. In a similar vein, some individuals and population sin a normally tool-using species may not utilise tools as a result of local
ecological conditions or lack of learning. Tebbich et al. (2001) report thatwoodpecker  nches do not use tools in habitats and seasons where gleaning
for insects yields higher payoffs. Tebbich et al. also show that some wildcaught individual s never use twig tools despite extensive exposure to social
and trial-and-error learning possibilities .
In the fan-tailed crow example, and in several others, the co-existenceof true and borderline techniques in the same species suggests that true
tool use may have evolved from simpler borderline tools, but the data offer
only ambiguous support for this idea. On the positive side, 16 of the 39
true tool use cases occur in taxa where borderline cases are reported in
the same species or genus. This is particularly evident in the seven Corvus
species that use both true tools and dropping, as well as in the genus
Turdus (use of a broom in T. merula, battering on anvils in three other
Turdus spp) and Melanerpes (use of a sponge in M. uropygialis, holding
in a wedge in M. lewis and M. carolinensis). In six species (Numenius

TOOLS AND BRAINS IN BIRDS

963

tahitiensis, Neophron percnopterus, Corcorax melanorhamphos, Corvus
brachyrhynchos, C. moneduloides, C. rhipidurus), similar prey are handledwith a proto tool (batter or drop on an anvil) and a true tool (hammer,
probe). On the negative side, true tool use shows no borderline equivalents
in Paridae, Psittaciformes, Charadriidae or Ciconiidae; gulls also have notrue tool alternative to their frequent use of dropping. Overall, the data thus
provide poor evidence that proto tool users are preadapted for the use of true
tools.
As predicted, the two telencephalic areas thought to be avian equivalentsof the mammalian neocortex come out as the strongest predictors of thetaxonomic distributio n in tool use reports (Table 2). This does not mean thatthe wulst and striatopallida l complex play no role in tool use, but that thehigh correlation between the four telencephalic areas leads to the eliminationof those that contribute less in the multiple regression. Contrary to feeding
innovations (Timmermans et al., 2000; this study), the neostriatum comes out
slightly ahead of the hyperstriatum ventrale and is thus the only remaining
telencephalic predictor in the  nal multiple regression models. This result
is not due to the fact that we measured innovation rate on a larger sample
here (6 geographical areas, 1796 innovation reports) than did Timmermans
et al. (1030 reports; only 5 of the 6 geographical areas covered, to the
exclusion of southern Africa). In our sample, the hyperstriatum ventrale isstill the best telencephalic predictor of innovation rate both with and withoutphyletic corrections. Caution should be exercised because the data set fortools is much smaller than the one for innovations . If, however, the difference
between tool use and innovation rate is not due to sample size, this may
mean that the intricate control of movement present in tool use but not inmost feeding innovation s (often simply the ingestion of a new food) could be
most strongly associated with a different telencephalic structure (Fig. 1). The
hyperstriatum ventrale consists of higher order, multimodal processing areas.
The neostriatum features tertiary areas of this type, but also includes primary
projection  elds from both somatosensory (nucleus basalis) and visual(ectostriatum ) pathways, as well as secondary areas that receive input fromthese primary termination  elds (Rehkamper et al., 1985). The neostriatum
thus has the necessary features for both the cognitive and sensory-motor
aspects of tool use. True tool use in particular requires a subtle coordinationof visual and somatosensory information. Probes, for instance, are held in
the beak and must be moved in very precise ways inside crevices to force out

964

LEFEBVRE, NICOLAKAKIS & BOIRE

insects, using both tactile and visual feedback. Ascending visual pathways
to the forebrain terminate in the ectostriatum, located in the core of theneostriatum, and in the wulst. Sensory representation for the bill is locatedin the nucleus basalis prosencephali, included here in the neostriatum . The
nucleus basalis is particularly large in tactile feeders like the Scolopacida(Boire, 1989). It is striking that a species from this small-brained, noninnovative parvorder, the bristle-thighe d curlew, has evolved three types oftool use, stone throwing, egg dropping and food slamming on rocks (Marks& Hall, 1992). N. tahitiensis has the largest brain in its parvorder. As pointed
out by Marks & Hall (1992), the specialised somatosensory receptors on its
bill may, in an island context where birds are often more opportunisti c thanon continents, favour  exibility in the use of this food handling organ.
In Fig. 2, one borderline category, holding food with a wedge or skewer,
is associated with the same range of brain sizes as is true tool use. Wedging is seen in large-brained woodpeckers (Piciformes), while skewering isa specialized technique used by two types of Corvida, shrikes (genus Lanius) and butcherbirds (genus Cracticus). Such concentrations of particulartechniques in particular genera are seen for other types of tools. The genus
Pitta, for example, includes several species that batter prey on anvils, as does
the genus Turdus. Dropping prey on a hard surface is seen in several Larus
and Corvus species (see Cristol & Switzer, 1999 for a detailed discussion of
dropping). Several species of Galapagos  nches use twig probes for removing insects from crevices. Common ancestry is an obvious explanation forthe concentration of particular techniques in particular genera. This concentration could be caused by independent selection for each technique in eachgenus or by a general set of cognitive processes present in all tool-using taxa,
which only takes a particular form when exploitatio n of a particular food typeis required. In the latter view, the cognitive basis for hammering with a stone
and poking with a twig is similar, i.e. changing the function of an object andmanipulating it to reach hidden food. Differences between the techniques
would be driven instead by the particular defence mechanisms of the prey(hiding in a shell vs hiding in acrevice). The two possibilities , independent
selection for each technique vs common cognitive basis shaped by particularfood handling constraints, cannot be distinguishe d for the moment, but are
in any case not mutually exclusive.
Despite the fact that some techniques are prevalent in particular taxa, mostof our evidence suggests that phyletic confounds are not responsible for the

TOOLS AND BRAINS IN BIRDS

965

overall trends in the data. In all cases, eliminating multiple entries per genus
yielded identical results to the analyses conducted on the full data set. For
telencephalic areas, the regressions on independent contrasts and phyleticallyuncorrected taxa both point to the neostriatum as the best predictor of true
tool use reports. It is only at the level of the whole brain that common
ancestry poses a statistical problem at the node that joins suborders Passeri
and Tyranni (Fig. 4). The contrast produced by CAIC at the Passeriforme
node is so large that it leads to a violation of the normality asssumption of
linear regressions. Eliminating the outlier solves the statistical problem, but
obscures the fact that the two Passeriforme suborders differ sharply in thenumber of true tool use cases. Conversely, keeping the outlier accounts for
the Passeri-Tyranni difference, but may cause the results of the regression
to be statistically meaningless. Since both solutions pose problems, we haveincluded the two versions in our results.
In agreement with Boswall (1977, 1978, 1983a, b), our study suggeststhat tool use in birds is more common than is often assumed. Over 120 cases
were found in birds, but this is still much smaller than the 607 cases collectedby Reader & Laland (2002; Reader, 1999) in the order Primates. The
current avian total may underestimate actual frequencies because biologists
do not expect as many cases in birds as they do in primates. Primates(apes in particular) could still be more frequent tool users than are birds,
however, be it for reasons of cognition, dexterity or dietary specialisation
on embedded foods (Gibson, 1986; Parker, 1996). The important point isthat the association between larger telencephalic structures and tool use in
several groups of birds provides independent support for the joint evolutionof these traits in widely divergent taxa. Comparing primates to humans is
instructive, but raises the possibility of a phyletic confound, since the highest
number of tool use reports occurs in Pan, the genus most closely related to
Homo (Reader & Laland, 2002; van Lawick Goodall, 1970; Whiten et al.,
1999; McGrew, 1992). In their study, Reader & Laland (2002) were careful
to exclude common ancestry through the use of independent contrasts, but
our results on birds further strengthen the case for independent evolution in
two ways: not only are birds as a whole very distantly related to primates,
but in addition, most large-brained, tool using groups of birds are distantly
related to each other. As is evident in Figs. 4 and 6, Passeri, Accipitrida,
Charadriida, Psittaciformes, Coraciiformes and Piciformes, six groups that

966

LEFEBVRE, NICOLAKAKIS & BOIRE

show positive residuals, come from widely-divergen t branches of the avian
phyletic tree.
Caution must be exercised in interpreting anecdotal observations (seethe open peer commentary that follows Whiten & Byrne, 1988). In somecases, detailed work (Hunt, 1996) has con rmed a single chance observation(Orenstein, 1972). In other cases, however, initial claims have not been
supported. The dropping of nuts (Maple, 1974) and palm fruit (Grobecker& Pietsch, 1978) on roads by C. brachyrhynchos, for example, has beenvalidated by experimental work (Cristol & Switzer, 1999), but the suggestionthat vehicles are used as nut-crackers in these cases has not (Cristol et al.,
1997; Shettleworth, 1998; see however Caffrey, 2001 and similar work by
Nihei, 1995 on C. corone). Captivity can also introduce some biases (e.g.
training effects; Powell & Kelly, 1977), althought close proximity between
humans and captive animals may make detection of tool using ability easierthan it is in the  eld. Beyond these cautionary remarks, however, it is stillreasonable to assume that complex cognitive processes are often operatingwhen a vertebrate uses a tool. Parallel  ndings on primates (Reader &Laland, 2002) and widely-divergent groups of birds (this study) suggestthat these cognitive processes may have independently co-evolved with large
brains a number of times, allowing several species to pro t from otherwise
inaccessible food (Parker & Gibson, 1977; Gibson, 1986).

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