Acta Chiropterologica, 1(1): 3-15, 1999 PL 1SSN 1508-1109 © Museum and Institute of Zoology PAS

The evolution of flight and echolocation in pre-bats: an evaluation of the energetics of reach hunting

JOHN R. SPEAKMAN

Department a/Zoology, University ofAberdeen, Aberdeen, AB24 217, Great Britain E-mail: J.Speakman@abdn.ac.uk

Theories of the evolution of echolocation and flight in bats can be divided into models in which echolocation evolved first, flight evolved first, or where both evolved in tandem. The echolocation frrst hypothesis, as well as some of the flight first theories, conunonly include a hypothetical phase where the pre-bat hunted by intercepting insects as they flew past a perch. I have called this behavior 'reach hunting'. In the current paper I have tried to reconstruct the likely energy gains that an animal could achieve when using this foraging strategy. The most favorable reconstruction suggests that it would take more than a day of continuous foraging to meet a reach hunters daily energy requirement, which probably explains why no extant animals hunt in this manner. This modelling suggests that the evolution of bats is unlikely to have included a period of reach hunting behaviour.

Key words: Chiroptera, evolution, flight, echolocation, aerial insects, reach hunting

INTRODUCTJON fossil forms (e.g., Archaeonycteris and Palaeochiropteryx - Habersetzer and

Currently, the earliest known bats date Storch, 1987). Aerodynamic reconstructions from the Eocene. Several specimens of a of the bats from Green River and the Messel single species (lcaronycteris index) have suggest that they were probably as capable of been recovered from the Green River forma­ powered flight as their modern day counter­tion in Wyoming, dated to 53 mya (Jepsen, parts (Padian, 1987; Habersetzer and Storch, 1966, 1970). Examination of these fossil bats 1987, 1989; Norberg, 1989). In addition to reveals enormous extension of the digits of the fully developed wing structure the early the forelimbs. In modern bats the extended fossil bats have a rotated hip joint similar to hand digits support the wing membrane, and that found in modern bats (Simmons and it seems most likely that in lcaronycteris they Geisler, 1998). This rotation of the limb may also served this function (see Padian, 1987, be related to the orientation of the legs during for an example reconstruction). The excep­ flight and attachment of the plagioptagium tional soft tissue preservation of fossil bats (Simmons, 1995). from the Messel pit in Germany, which are A less obvious anatomical trait of these approximately 3-4 million years younger early fossil bats is their enlarged cochleae than Icaronycteris, confirms the presence of relative to the size of their skulls, since this a fully formed wing membrane in similar can only be examined by radiographic analy­

1. R. Speakman4 f

sis. The extent of enlargement is less than that found in modem day insectivorous bats, but generally larger than modem megachiro­pterans (Habersetzer and Storch, 1989; Simmons and Geisler, 1998: fig. 29). This enlargement strongly suggests that the bats were not only capable of flying, but had also developed a sophisticated echolocation system (Novacek, 1985, 1991; Habersetzer and Storch, 1989, 1992). Two key traits that we associate with modern bats (flight and echolocation) are already present in the earliest fossil representatives of this taxon (Neuweiler, 1984).

As observed by Griffin (1958), the ab­sence of any direct fossil evidence means that we can only speculate on the process of the development of these traits. Such speculation is not easy. Indeed, Darwin (1859) in the "Origin of Species" considered that the difficulty explaining the evolution of bats from a quadrupedal ancestor posed a serious problem for the theory of evolution (see Difficulties with the Theory section). Never­theless several attempts have been made to reconstruct the process which may have led to evolution of the early fossil bats from a quadrupedal ancestral pre-bat.

There have been three major alternative scenarios [reviewed in Arita and Fenton (1997) and Simmons and Geisler (1998)). These can be called the echolocation first hypothesis, the flight first hypothesis and the tandem evolution hypothesis. All of the models can be considered 'monophyletic' hypotheses since they have generally been developed on the a priori premise that the order Chiroptera is monophyletic (although at various times in the history of the develop­ment of the ideas they have been modified to fit the diphyly hypothesis of bat origins ­Pettigrew et al., 1989).

The echolocation first hypothesis suggests that the pre-bats developed a fully advanced echolocation system before they started to fly. The situation is presumed to be reversed

in the flight first hypothesis, while the tan­ t dem development idea suggests that the capabilities were closely linked throughout their evolution with advances in both systems evolving in parallel. In the present paper I will consider some problems with the echo­

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location first model for the evolution of echolocation.

ECHOLOCATION FIRST HYPOTHESIS

The echolocation first hypothesis origi­nated in the 1960s and has been through several transformations as new data accumulated, and it has, at various times, been modified to fit the bat diphyly and bat monophyly theories. The following account is an attempt to synthesise previous ideas into a contemporary consensus. The echolocation first hypothesis starts from the assumption that the ancestral pre-bat was nocturnal, arboreal and insectivorous (Fenton, 1984; Hill and Smith, 1984; Fenton et al., 1995; Arita and Fenton, 1997). A good model for such an animal might be the mod­ern day tree shrews (Scandentia), might also be the closest archontan relative to the modern Volitania (Novacek, Miyamoto, 1996). The hypothetical pre-bat i presumed to have communicated by using broadband ultrasound calls (Sales and Pye, 1972; Fenton, 1984). It is presumed that this animal fed primarily by gleaning insect pre from the arboreal substrate. The prey have been located by olfactory, visual tactile means [for example, Simmons Geisler (1998) argued that vision was prob bly well advanced in these animals]. The fi phase in the process of evolution involve a period when the bat fed by cap ing aerial insects flying past its arbor perches. This would involve reaching 0

wards from the branches to snatch the p ing insects from the air (Jepsen, 1970). In current paper I have coined the term 're hunting' for this behaviour. Selection i

reach hunting indivic sion of the digits and This would extend t

animal could reach 11 of prey. Webbing lx improve the success, struction of such a illustrated in Fig. 1

arms and would thus represer

The next phase J

involve refinement 0:

the animal for echol Broadband l

targets appro some ranging inform become progressivel­

was producing' frequency-modulated track incoming target

\ ~

I

. Reconstruction of a

5

while the tan­sgests that the

inked throughout .ces in both systems

. the present paper I blems with the echo­'or the evolution of

iYPOTHESIS

rst hypothesis origi­td has been through s as new data has as, at various times, e bat diphyly and bat he following account se previous ideas into sus. The echolocation from the assumption .-bat was nocturnal, IroUS (Fenton, 1984; Fenton et al., 1995; 97). A good extant ial might be the mod­(Scandentia), which t archontan relative to a (Novacek, 1986; rypothetical pre-bat is omunicated by using calls (Sales and Pye, •is presumed that this r gleaning insect prey strate, The prey may

olfactory, visual or unple, Simmons and hat vision was proba­ese animals]. The first of evolution would

the bat fed by captur­ing past its arboreal . nvolve reaching out­es to snatch the pass­(Jepsen, 1970). In the oined the term 'reach .viour, Selection in a

Evolution of flight and echolocation in pre-bats

reach hunting individual would favour exten­sion of the digits and forearm (Jepsen, 1970). This would extend the area over which the animal could reach thus increasing the intake of prey. Webbing between the digits might improve the success at prey capture. A recon­struction of such a hypothetical pre-bat is illustrated in Fig. 1. The development of elongated arms and digits with webbing would thus represent a pre-adaptation for flight.

The next phase in development would involve refinement of the ultrasound calls of the animal for echolocation (Fenton et al., 1995). Broadband ultrasound calls made while targets approached would provide some ranging information, and these would become progressively refined until the ani­mal was producing broad high intensity frequency-modulated (PM) sweeping calls to track incoming targets. During this phase of

evolution I suggest the animal might have abandoned the tops of branches in favour of hanging inverted below them. This might have provided two advantages. First, the animal would have both hands free for prey capture, and second, the branch would not cause an ultrasound shadow obscuring ap­proaching insect prey.

Eventually the animal would be echo­locating on to approaching targets to track their approach and sweeping them into greatly enlarged hand and arm webbing. As the range of echolocation improved many insects would be tracked approaching, but would not come within reach. The animal might have started to jump outwards to intercept these 'close encounters'. The hand/arms would then be used to aerody­namic advantage to glide to another perch from which the process could be repeated. This would lead the animal to develop a

FIG. 1. Reconstruction of a hypothetical reach hunting pre-bat with elongated forearms and enlarged digits with webbing to facilitate reach distance and capture of insect prey

6 J. R. Speakman

perch-hunting strategy similar to that found in modern rhinolophid bats (Schnitzler et al., 1985; Neuweiler et al., 1987; Jones and Rayner, 1989) and many other groups (e.g., megadennatids, nycterids and some vesper­tilionids - Simmons and Geisler, 1998; Bogdanowicz et al., 1999).

The next stage in the process would be to extend the time spent in flight to intercept more than single insects prior to relanding. As the numbers of insects captured between

.landings increased, perch hunting would gradually evolve into aerial hawking, with the bat continuously in flight. The current fossil evidence is suggested to start some­where in these latter two phases. Simmons and Geisler (1998) have suggested that the earliest fossils (lcaronycteris and Archaeo­nycteris) were perch hunting forms based on their short wings and lack of uropata­gia/calcars, while later fossils were aerial hawkers. Norberg (1989) also stated that these species may have been perch hunters, although she clearly considered them capable of continuous flight, rather than being re­stricted to hunting from perches, as implied by Simmons and Geisler (1998). Norberg (1989: 205) for example states: 'There is nothing in the wing shape which indicates the ancient bats included here were poor fliers' . Others have suggested that they were all aerial hawking bats (Habersetzer and Storch, 1989) based on their wing loading and pre­dicted aerodynamic performance relative to modern aerial hawking bats.

Once aerial hawking had evolved as a foraging strategy the sophistication of flight performance would improve in some forms, allowing them to glean insects from surfaces while remaining themselves in flight. This would allow bats to take insects from sites where ground based gleaning animals would have no access, because of their body weights, such as from the corollas offlowers. This in turn might lead to the evolution of nectar feeding and fruit feeding. S. Vogel

(pers. comm.) has suggested that nectar feeding in the Old and New World bats may have evolved by different routes with a direct link between insectivory and nectarivory in the New World, but a link via frugivory in the Old World. In either case the advancing sophistication of flight behaviour would allow bats to make these dietary shifts. In some instances this may have been followed by the evolution of folivory (Kunz and Ingalls, 1994).

The final aspect of the theory is the grad­ual loss of echolocation capability and its replacement by sight as the dominant mode ofperception in some fruit and nectar feeding bats (the Old World megachiropterans). A parallel but not yet completed process may be currently occurring in the frugivorous and nectarivorous phyllostomids, The final twist in the story is the re-evolution of echoloca­tion using completely different sound pro­duction mechanisms among some of the megachiropterans (Rousettus spp. using tongue clicks and Eonycteris spelaea using wing clapping - Griffin et al., 1958; Rob­erts, 1975; Gould, 1988). Arguments sup­porting this pattern of sensory modality swapping were presented by 1. M. Hutcheon at 11th International Bat Research Confer­ence in 1998.

PROBLEMS WITH THE ECHOLOCATION FIRST

MODEL

I think that there are at least three majo flaws with the echolocation first model :D

the evolution of bats. Two of these argumen have been presented elsewhere. The thir argument will be developed in this pap First, it has been suggested (Jones, 19 Speakman, 1993) that the echolocation model, as presented above, is unreali because it ignores observations that sh there are significant energy costs associ with the production of echolocation voc tions for animals that are statio

(Speakman et al., 1989 disappear during fli: Racey, 1991) because pling of wing beat, res tion in bats that are fly Suthers et al., 1971; high costs for stationa would be insufficient t perch hunting, the dii location for flying a means that the balance is very likely to be WI

favour of echolocatior or in tandem with it, ra

The second problei significant problems, suggest megachiropt ability to echolocate. , loss of sensory capab: animal kingdom, for cave fish and reptiles and fossorial animals 1965), and these have sent analogies to the (Simmons and Ge Hutcheon, pers. com these analogies to th echolocation in ances questionable. Loss 0

fish and fossorial ar there is no light availa thus vision is a supe cost energy to maint vision in this situati fitness benefit comi retain their visual cap from the hypothesise capability in mezacl highly sophisticat:d a location) is suggestec y another equally sc ve system (vision).

cd that there are P of sensory r 3). This is bee,

ume (Martin, 19E

7Evolution of flight and echolocation in pre-bats

led that nectar .;World bats may

.routes with a direct y and nectarivory in

L link via frugivory in ier case the advancing iht behaviour would lese dietary shifts. In iy have been followed folivory (Kunz and

the theory is the grad­ion capability and its is the dominant mode ruit and nectar feeding megachiropterans). A impleted process may in the frugivorous and omids. The final twist .volution of echoloca­

different sound pro­among some of the ousettus spp. using iycteris spelaea using 'fin et al., 1958; Rob­188). Arguments sup­of sensory modality ted by J. M. Hutcheon 3at Research Confer­

~CHOLOCATION FIRST

'e at least three major cation first model for wo ofthese arguments elsewhere. The third eloped in this paper. gested (Jones, 1993; the echolocation first' above, is unrealistic servations that show iergy costs associated -cholocation vocalisa­that are stationary

(Speakman et al., 1989). However, such costs disappear during flight (Speakman and Racey, 1991) because of the observed cou­pling of wing beat, respiration and vocalisa­tion in bats that are flying (Schnitzler, 1968; Suthers et al., 1971; Kalko, 1994). While high costs for stationary echolocation alone would be insufficient to prevent evolution of perch hunting, the different costs of echo­location for flying and perching animals means that the balance of costs and benefits is very likely to be weighted much more in favour of echolocation evolving after flight, or in tandem with it, rather than preceding it.

The second problem is that there are also significant problems with the scenarios that suggest megachiropterans have lost the ability to echolocate. Although it is true that loss of sensory capability is common in the animal kingdom, for example among blind cave fish and reptiles (e.g., Halpern, 1973) and fossorial animals (e.g., Lund and Lund, 1965), and these have been claimed to repre­sent analogies to the loss of echolocation (Simmons and Geisler, 1998; J. M. Hutcheon, pers. comm.), the relevance of these analogies to the hypothetical loss of echolocation in ancestral Megachiroptera is questionable. Loss of vision in blind cave fish and fossorial animals occurs because there is no light available in their habitats and thus vision is a superfluous trait that must cost energy to maintain. Animals that lose vision in this situation therefore derive a fitness benefit compared to animals that retain their visual capability. This is different from the hypothesised loss of echolocation capability in megachiropterans where one highly sophisticated and useful system (echo­location) is suggested to have been replaced by another equally sophisticated but alterna­tive system (vision). I have previously sug­gested that there are difficulties with such a swap of sensory modalities (Speakman, 1993). This is because the limited brain volume (Martin, 1981) processing capacity

and/or metabolites that can be devoted to sensory systems, means that an intermediate animal possessing both an inferior echo­location and inferior visual system, compared to specialised alternatives, would always be out competed by animals with the specialised alternatives (Speakman, 1993). This makes it unlikely that if megachiropterans ever had the capability to echo locate that they would lose it to replace it with a complex visual system (Rayner, 1991). More probable that they never had the capability in the first place. This argument receives substantial support from the observed success of the megachiropteran groups that have evolved a rudimentary form of echolocation. A third argument against the echolocation first hy­pothesis, developed here, concerns the ener­getic feasibility of 'reach hunting' as a forag­ing strategy.

ENERGETICS OF REACH HUNTING

In the remainder of this paper I propose to evaluate the energy gains that a hypothetical 'reach hunting' animal might be expected to obtain by using this foraging strategy and how such gains might depend on the length­ening of the arms and digits and the inversion of posture. To evaluate the energy returns that reach hunting would provide it is neces­sary to quantify several key parameters. The first parameter is the distance that an animal can reach, which provides an estimate of the area surrounding the animal within which any passing insect would be vulnerable to capture. The second paramter is the likeli­hood of an insect flying into this area of vulnerability, which will depend on the density of insects and their activity (flight speeds and flight patterns). The third parame­ter is the probability that an insect will be detected and captured once it enters the zone of vulnerability. Finally, we must calculate the energy content of the prey that can be extracted by the animal in question. I will

8 1. R. Speakman

consider each of these parameters in tum and then synthesise this information to recon­struct the probable energy gains that an animal could obtain by employing this forag­ing strategy.

REACH D1STANCE AND AREA OF VULNERA­

BILlTY

A dorsal view of a model pre-bat, such as a tree shrew, reveals that the animal has two points of attachment to the arboreal habitat. These are located approximately below the pelvic and pectoral girdles (Fig. 2A). Assum­ing that the animal uses the forelimbs to capture its prey (Fig. 1), there are two ways to envisage the reach distance. In the first reconstruction the centre of the body remains over the forward point of attachment and the forelimb is extended to one side (Fig. 2B). However, the animal can extend the reach substantially by leaning outwards, so that the centre of the body lies to one side of the branch at the same time as extending the forelimb in the same direction (Fig. 2C).

Leaning and reaching gives the maximum area of vulnerability. This fact suggests two things. Selection will favour reducing the angle between the body and the forelimbs and thus will not only favour extension of the arms and digits to effect prey capture but will also promote selection of extended body length. In addition, adopting an inverted posture, and releasing both forelimbs from the perch, actually reduces rather than in­creases the area of vulnerability. The sugges­tion that an inverted posture might increase prey capture would only occur ifby releasing both limbs the increased probability of a successful capture offset the reduced volume of air in which passing insects would be vulnerable.

The maximum reach distance for a lean­ing and reaching animal is approximately equal to the length of one arm plus digits, plus the width of the body, plus the length of

the second arm minus the digits (which are utilised in holding on to the branch to form the second point of attachment). Using the tree shrew (Tupaia pieta) as a model, I mea­sured the lengths of the major limb bones and digits of a museum specimen (University of Aberdeen, Natural History Museum: unnum­bered display specimen). The measurements were: body width, 50 rnm; humerus, 25 mm; ulna/radius, 35 rnm; hand incl. digits, 15 mm. Applying the above formula gives an esti­mated maximum reach distance of 175 mm. It seems very unlikely that the animal could make such a reach in all directions (for exam­ple vertically upwards). However, I will make the generous assumption that this would in fact be possible, so the area of vulnerability for this model pre-bat animal describes a sphere of radius 175 mm and a volume of 0.024 m' (which is approximately equivalent to a square box with sides 28 em across).

LIKELIHOOD OF AN INSECT ENTERING THE

AREA OF VULNERABILITY

Imagine a cube measuring 1 m on each side. Inside this cube, in the middle, is an­other cube measuring 28 em on each side. There is a single insect flying around at random inside the big cube. How long would it take before the insect would pass through the smaller cube? The solution to this prob­lem would be the answer to the likelihood of· an insect entering the area of vulnerability, at a density of I insect/nr', If we could answer this question the general solution would be applicable to all insect densities and the encounter rate of our hypothetical pre-bat with prey could be evaluated from knowl­edge of its prey density.

Unfortunately, a simple mathematical solution to the problem is not tractable. In general we might expect the answer to be a distribution approximating something like a Poisson distribution. But deriving parameters

A: Hypothetical Arboreal Predator

B: Reach

rear,

c: Lean and Reach

FIG. 2. Schematic view: (A) girdle; (B) of a hypothetical ' branch; (C) of a 'lean and re"

9 Evolution of flight and echolocation in pre-bats

.rigits (which are ne branch to form

chment). Using the a) as a model, I mea­

~ major limb bones and pecimen (University of story Museum: unnurn­en). The measurements mm; humerus, 2S rnm:

iand incl. digits, 15 mrn. formula gives an esti­.h distance of 175 mm. y that the animal could t11 directions (for exam­.ds). However, I will

assumption that this .ssible, so the area of model pre-bat animal

. radius 175 nun and a vhich is approximately ~ box with sides 28 cm

NSECT ENTERING THE

_ITY

easuring 1 m 'On each , in the middle, is an­28 cm on each side.

sect flying around at cube. How long would ct would pass through solution to this prob­

.er to the likelihood of· rea of vulnerability, at 13• If we could answer ral solution would be .ct densities and the hypothetical pre-bat

raluated from knowl­

f· simple mathematical n is not tractable. In ct the answer to be a ting something like a It deriving parameters

A: Hypothetical Arboreal front anchor point Dorsal viewPredator

rear anchor point

••- ••-...-»-.-.-------------------.-~ area of vulnerability

B: Reach //__-/ "'."\~~'lnsects

I "

rfront anchor point

\, .. \ "." " <,

.. ~ -c-, ...

rear anchor point

-...-.......--­

~~;~~n and _///-­

//

! ... ..

\ (

)\ ... :' \ j'/\\. rear anchor point-~l.

,//' .. -," -._-­

--.._~----

reach distance ..../

\

~ --_...--..- -_..----------...-

FIG. 2. Schematic view: (A) from above of an arboreal mammal showing locations of the pelvic and pectoral girdle; (B) of a hypothetical 'reach' to one side, retaining the centre of the pectoral girdle over the centre of the branch; (C) of a 'lean and reach'. By displacing the pectoral girdle away from the centre of the branch the total

length of the reach is greatly extended

• •

10 J. R. Speakman

of such a solution depends on several un­ involved an equal probability of moving to 400.,------ ­

knowns such as the directionality ofthe flight each of the nine alternatives (rule A: 350 •

path. To derive a solution to the insect in two equiprobable movement). The second move­ 300

cubes problem I used a computer simulation. ment rule (B) was weighted against diagonal •~ 250

(The simulation was written in BASIC and movements. Thus each of the four corner t:: ~ 200 •

copies are available from the author on re­ alternatives had a probability of 0, and the 0"£ 150

quest). In the simulation an insect is moving remaining five alternatives were equiprob­100 •

around a cube with sides measuring 1 m. The able. The third movement rule (C) was 50 •large cube is subdivided into small cubes weighted against directly forward movement •0.1...------ ­

measuring 1 em on each side. The insect or remaining stationary. Both these possibili­ a 2000 4000 SI

moves between the 1ern cubes in single steps ties were given a probability of 0, and the taking one time unit to travel one step. One remaining 8 alternatives were equiprobable.

350 ;------- ­way to imagine this scenario is to imagine In all cases, the program iterated move­that wherever it is the insect is in the centre ments until the insect entered a cube of given 300 • of a virtual Rubik cube. The virtual Rubik dimensions located centrally in the larger •250

cube consists of 26 1-cm cubes surrounding cube. The number of 1ern steps before enter­ u >.

:;; 200a central l-cm cube. In a given time unit the ing the central box (which mimics the area of ::J •0"insect in the middle of the Rubik cube can vulnerability) was recorded and the program E 150

move to any of the immediately adjacent 26 iterated 1,000 times to generate a distribution -100

l-crn cubes (or stay where it is) - making a of interception distances. The results of three total of 27 movement possibilities. Once it simulations using different movement rules 50

• oJ.-..-~-_--has moved it is then considered to be the are shown in Fig. 3A-C. In these simulations, a 2000 4000central point of another virtual Rubik cube the central cube had dimensions of 20 em on

with a further 27 movement options open to each side. The pattern of distances in all it, and so on. The insect can enter the large these cases was remarkably similar. How­ 350 r------­1m cube at any point on its surface and can ever, the actual means differed by about 25%

300 •

also exit at any point. If it exits then another between the shortest and longest. The short­•insect immediately enters the 1m cube some­ est interception on average for an intercep­ 250

~ t:: 200where else completely at random. In other tion cube of this size occurred with the Q)

::Jwords there are no edge effects for the large equiprobable movement rule (A) and was go 150 • ~ •cube. 1,676 steps (16.76 m). On average, at a

100

I used three different movement rules to density of 1 insect/m ' each insect would fly •describe the insect flight behaviour. In all 16.76 m within the 1 m cube before flying 50

0'-1-----­three cases I made the a priori assumption into the area of vulnerability. It is necessary a 2000 4000

that the insect would fly forwards with much to know the flight speeds of insects to con­em steps before ent

greater probability than backwards. The vert this into a time. probability of entering one of the 9 1-cm Johnson (1962) reported flight speeds for FIG. 3. Distributions of t: cubes in front of the insect was set at 0.75, insects of different sizes, and found that the thetical fly inside a 1 m

entering a zone of vulneand for moving into the 9 cubes behind was majority of small insects « 1.5 ern body the cube measuring 20

set at O. Thus the animal had a probability of length), which dominate the aerial insect three different movement 0.25 of staying in one of the 9 cubes at the fauna (see below), fly at speeds of around text for ill~

centre of its direction of travel. Having de­ 1 mls. Larger insects such as moths and fmed whether the insect would move for­ dragonflies can fly much faster than this, but movement rule that ~

wards or not, I then used several alternative are very rare components of the aerial insect distance suggests thar rules defining to which of the 9 cubes the community. Using a mean flight speed of sect/nr' one insect WOl

insect would move. The simplest of these 1 m/s, in our hypothetical example, the vulnerability about e

• •

• • • • •

• •

l' moving to .es (rule A:

c second move­. against diagonal

If the four comer ility of 0, and the es were equiprob­ent rule (C) was 'orward movement oth these possibili­ility of 0, and the rere equiprobable. am iterated move­red a cube of given 'ally in the larger steps before enter­mimics the area of ~d and the program erate a distribution I'he results of three It movement rules l these simulations, nsions of 20 em on if distances in all bly similar. How­ered by about 25% longest. The short­?e for an intercep­occurred with the rule (A) and was On average, at a :h insect would fly cube before flying lity. It is necessary , of insects to con­

ed flight speeds for and found that the .s «1.5 em body : the aerial insect

speeds of around ich as moths and faster than this, but of the aerial insect an flight speed of ical example, the

Evolution of flight and echolocation in pre-bats 11

400 ,---------------,

350 A• 300

•~ 250 l: ~ 200 • C'£ 150

100 • 50

350 r----------------,

300

250 >. CJ

; 200 :I C' ~ 150

100

50

• B

•

•

• • • • • ••

2000 4000 6000 8000 10000 12000

350.,...---------------,

300 • C 250

>. • CJ t: 200 Q)

:I C' 150 e....

100

50

a 2000 4000 6000 8000 10000 12000

em steps before enters area of vulnerability

FIG. 3. Distributions of the distances that a hypo­thetical fly inside a I m cubed box covers before entering a zone of vulnerability in the centre of the cube measuring 20 em'. Simulations under three different movement rules are illustrated (see

text for more details)

movement rule that generates the shortest distance suggests that at a density of 1 in­sect/nr' one insect would fly into the area of vulnerability about every 17 seconds. To

evaluate how realistic the computer simula­tions were, I constructed a cube with sides of 20 em using plastic drinking straws and placed it at a height of 1.5 m on a warm sunny afternoon near Aberdeen and observed for 20 minutes the numbers of insects that flew through it. I estimated by eye that around the immediate vicinity of the box the aerial insect density was around 1.5 insects/nr'. On average, I recorded 4.2 insects passing through the box each minute - while the computer simulation at a density of 1.5 insects/nr' predicts (17/1.5) an insect every 11.2 seconds or 5.2 per minute. Given the arbitrary nature of the flight rules used in the model, and probable inaccuracies in the evaluation of insect density by eye, I am struck by the similarity of these values and therefore feel the computer simulation af­fords a reasonable approximation (perhaps slightly generous) of the likely interception rates that hypothetical reach hunting animals might have with P9tejJt!a!.prey.J,Jsing hypothetical cUcpe witb s~i:ies Qt28'YJ;l:r(see above) to simulate a tree-shrew like animal~

and using the equiprobable moveqientJ3,l.le, the average time to interception at a density of 1 insect/nr' and a flight speed of 1 m/s was 10 seconds.

Two questions remain. What was the density of aerial insects in the late Creta­ceous/early Tertiary when these animals were evolving, and second, to what extent is den­sity reduced inside the canopy of a tree adj­acent toa branch, when compared with the density measured in free field sites? In the absence of any information I have made the assumption that modem day insect densities matched those in the period when the hypo­thetical reach hunting pre-bat was alive. Johnson (1952) has reviewed estimates of aerial insect density. The maximum densities occur in locust and aphid swarms when between 11 and 14 individuals/rrr' have been reported. Generally, however, maximal den­sities average between 1 and 3 per nr', and

12

l

J. R. Speakman

these are sustained for relatively short peri­ods. We might imagine that for short periods the pre-bats could intercept insects at rates of 1 insect every 10 seconds. However over much longer periods average insect densities are considerably lower. Rydell (1989) esti­mated aerial insect densities in the early evening in southern Sweden were 0.15 to 0.30 insects/rrr' and Johnson (1950) reported slimmer densities in the temperate zone average 0.15 per nr' over the entire diel cycle. Densities of aerial insects in the tem­perate zone during summer generally exceed those in the tropics (Johnson, 1962). Since bats are believed to have evolved in sub­tropical and tropical habitats the assumption based on aerial insects from the temperate zone is probably generous.

Insect densities are generally measured at free-field sites and not within the canopies of trees. To evaluate the difference in insect density between a free-field site and within a tree canopy I made observations of the num­bers of insects flying through a 20 em' straw box located inside a tree (adjacent to a branch), at the same site and immediately after the free field observations detailed above. The average number of insects within the tree was only 16% of the average num­bers passing through the same box at the free-field site. Using a generous average insect density over 24 h of 0.2 insects/rrr' and a reduction from free-field to inside the canopy of 84% yields an interception rate with insects for the hypothetical animal based on the tree-shrew (with a 0.0224 nr' intercep­tion area) of one insect intercepted every 312.5 seconds.

To evaluate the energy intake of the animal it is necessary to make some assump­tions about the probability that the animal would detect these prey, the probability that once detected they would be captured, their energy content, and the digestive efficiency of the animal once it had eaten them. Since we are presumed to be dealing with an ani­

mal that has not developed a specialised sensory system for tracking incoming insects and is relying on vision, I have assumed that the animal only detects larger insects with wings measuring greater than 1 em across (see Brigham and Barclay, 1995, for biased size selection towards larger insects by night foraging Caprimulgiformes, which are con­strained by light levels). Insects over 1 ern long are actually a relatively rare component of the aerial fauna, which tends to be domi­nated by very small insects. Speakman et al. (In press) found that insects with wings greater than I em comprise only 4.2% of the total aerial insects in Norway during the summer. This is not an exceptional figure. Johnson (1962) quotes various values be­tween 2 and 5% for similar sized insects from various sites around the world. I will assume that the same size distribution of insects pertained in the late Cretaceous. This is a reasonable assumption given the similarity of modern insects to those trapped in amber from this time period (Ross, 1997). Moreover the rates at which insects were trapped in amber relative to the trapping rates of mod­ern sticky traps suggests the assumed density of ancient insects is also not unrealistic.

I will make the generous assumptions that if any insect of this size entered the zone of vulnerability, the success rate of capture was 100%, and once ingested the digestive effi­ciency was also 100%. The average mass of insects with wings measuring greater than 1 em is assumed to be 100 mg (based on my own unpublished observations of insects collected around Aberdeen) and they are assumed to have an energy content of25 kJ/g (Kunz, 1988). Each insect therefore was assumed to contain 2,500 J of available energy. Using these values, the interception rates with insects in the appropriate size class would be one insect every 7,440 seconds, giving the animal an energy ingestion rate of 0.34 Watts. Given this energy intake rate, how long would the hypothetical reach hunt­

ing animal need to fe: daily energy require based on Tupaia picta. imately 160 g. The da predicted for a marnn approximately 150kJ/ Consequently, with aJ 0.34 Watts it would average a predicted hunt foraging to take requirement.

It should be remem is based on several v tions: the interceptic equiprobable movem slightly generous inti with reality, the captu cally high (100%), it the digestive efficiem assumed aerial insect 24h was 30% higher t value for present day j least generous assurm mals only detect insec ing more than 1 em assumption however r ence to the calculatic contents of much s dominate the fauna is mass of modern insee ing less than 1 em in (Speakman and Rae animal would need tl small insects to mate single large insect. B detects all aerial insec daily energy requirerr approximately 20%.

A key factor in t] sumed density of ir animals might be a1 attracted to certain lot or exuding sap, becau prey density might m. startegy. Although thi for the evolution of n

Evolution of flight and echolocation in pre-bats 13

, a specialised .ncoming insects

.iave assumed that larger insects with

er than 1 ern across lay, 1995, for biased arger insects by night mes, which are con­.). Insects over 1 em ively rare component ch tends to be domi­ects. Speakman et al. insects with wings

rise only 4.2% of the Norway during the

1 exceptional figure. ; various values be­lar sized insects from world. I will assume

stribution of insects 'retaceous. This is a ~iven the similarity of se trapped in amber ass, 1997). Moreover .cts were trapped in apping rates of mod­; the assumed density J not unrealistic. .ous assumptions that ~ entered the zone of ss rate of capture was ed the digestive effi­The average mass of asuring greater than 00 mg (based on my ervations of insects deen) and they are 'gy content of25 kJ/g nsect therefore was ,500 J of available lues, the interception, appropriate size class very 7,440 seconds, ergy ingestion rate of

energy intake rate, iothetical reach hunt­

ing animal need to feed each day to meet its daily energy requirements'? The model is based on Tupaia picta, which weighs approx­imately 160 g. The daily energy requirement predicted for a mammal of this body size is approximately 150 kJ/day (Speakman, 1997). Consequently, with an energy intake rate of 0.34 Watts it would take this animal on average a predicted 122.5 hours of reach­hunt foraging to take in a single days food requirement.

It should be remembered that this estimate is based on several very generous assump­tions: the interception rate, based on the equiprobable movement rule may predict slightly generous intercept rates compared with reality, the capture success is unrealisti­cally high (100%), it was also assumed that the digestive efficiency was 100%, and the assumed aerial insect density averaged over 24h was 30% higher than the literature cited value for present day insect populations. The least generous assumption was that the ani­mals only detect insects with wings measur­ing more than 1 em across. Relaxing this assumption however makes very little differ­ence to the calculation because the energy contents of much smaller insects which dominate the fauna is very low. The average mass of modem insects with wings measur­ing less than 1 em in length averages 1 mg (Speakman and Racey, 1989). Thus the animal would need to take in 100 of these small insects to match the intake of only a single large insect. By assuming the animal detects all aerial insects the time to meet the daily energy requirement is reduced by only approximately 20%.

A key factor in this analysis is the as­sumed density of insects. Reach hunting animals might be able to exploit insects attracted to certain locations such as flowers or exuding sap, because the locally elevated prey density might make it a more profitable startegy. Although this is a potential scenario for the evolution of reach hunting it is not a

probable precursor to the evolution of flight and echolocation. This is because animals exploiting such a resource would not need to develop sophisticated echolocation to track the flight paths of the insects or need to leap out and catch them, because the insects would always predictably come to the attrac­tant, where they might be captured.

CONCLUSIONS

The inevitable conclusion of this model­ling is that reach hunting is not a viable foraging strategy. Animals may have in the past, and may still, occasionally and opportu­nistically snatch insects from the air when stationary on the ground or a perch (Courts, 1997). The contribution of these insects to the total energy budget however is likely to have been (and be) trivial. Given that elon­gated limbs and webbed elongated digits (as envisaged in Fig. 1) would probably have reduced the efficiency of other activities, such as locomotion, it seems very improbable that natural selection would favour develop­ment of such traits.

I suggest that this conclusion is consistent with the fact that currently there are no known vertebrates that employ reach hunting as a foraging strategy (either with or without the aid of echolocation). The only animals, which employ similar tactics to intercept flying insects, are web spiders. Web spiders are only capable of doing this because the web is a massive trapping surface relative to the animals own body size. Only by having trap, which extends 20-50x greater than its limb length, can a spider trap sufficient insects to meet its energy requirements. As reach hunting is not a viable foraging strat­egy, and because it forms a major stage in the hypothetical scenario for pre-adaptation of the limbs of pre-bats for flight, this paper provides further evidence that the 'echo­location first' route is less realistic than the flight first and tandem evolution scenarios for the evolution of bats.

14 J. R. Speakman

ACKNOWLEDGEMENTS

The arguments in this paper were originally presented at a symposium on evolution of flight and echolocation at the 11th International Bat Research Conference in Brazil in August 1998. I am grateful to Nancy Simmons and Eli Kalko for inviting me to take part in the symposium and to Jader Marinho-Filho for financial assistance to attend it. Jens Rydell and Nancy Simmons made valuable comments on the original

paper.

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Received 10 March 1999, accepted 23 April 1999