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Power Efficiency Guide

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a Equations based on body mass M in kg.

b Glossophagine basal metabolic rate is 1.15 times the average basal metabolic rate for bats (Arends et al. 1995). c W = J s"i.

d G. c. - Glossophaga commissarisi.

Notes:

a Equations based on body mass M in kg.

b Glossophagine basal metabolic rate is 1.15 times the average basal metabolic rate for bats (Arends et al. 1995). c W = J s"i.

d G. c. - Glossophaga commissarisi.

1987, 1994). However, the average DEE of glossophagines is 60% to 70% higher than the average for other eutherian mammals of their size class, as determined on the basis of DEE estimates with the doubly-labeled water method (Nagy 1994). The DEEs for glossophagines are among the highest yet measured for mammals, and they coincide with the range typical for birds. Put differently, daily energy turnover in a glossophagine is roughly two-thirds of the total caloric content of its body - twice the value typical for a similar-sized terrestrial mammal (assuming 22 kj g-1 dry body mass; Masman et al. 1986).

Considering vertebrate nectarivores in general, nectar-feeding ptero-podid bats (Syconycteris australis; Geiser & Coburn 1999) and 6-15 g sun-birds (Nectarinidae; Peaker 1990) have DEEs similar to glossophagines. Only hummingbird DEEs appear on average, to be about 30% higher (cf. Tiebout & Nagy 1991; Lopez Calleja et al. 1997).

Our DEE measurements based on 11 glossophagine species provide a basis for inferring ecological requirements. A later section addresses how this food energy must be distributed spatially within the habitat in order to meet the energy costs of foraging.

The energy cost of flight

Horizontal forward flight Flight is the major energetic cost for a foraging bat. The net energy gained from a flower visit by a glossophagine bat is therefore the difference between the energy content of the imbibed nectar sugar and the flight cost of commuting from the previous flower, plus the hovering expenditures during feeding. The cost of horizontal forward flight in small bats has so far been measured by indirect metabolic energy balance methods: the total energy turnover of an animal is ascertained over periods of both flight and rest. Flight cost is determined by subtracting the estimated cost entailed during the non-flight period from the total energy turnover (Speakman & Racey 1991; Winter & von Helversen 1998). Flight costs for small bats, at their lower speeds, are approximately 2o%-25% lower than most estimates for birds (Table 8.1; cf. Winter & von Helversen 1998).

Through the course of a night, bats gain mass by feeding. Mass increases by about 5% during the first hour of foraging and by another 3% to 5% during the rest of the night (Winter 1998a), leading to a roughly proportional increase in flight cost. Forward flight cost as given by the equation in Table 8.1 is based on mean night-time body masses.

Flight speeds

The cost of flight for a given distance is a function of flight power (W or J s-1) and flight speed (m s-1). Commuting flight speeds have been measured in the field for several species of glossophagine bats (Sahley et al. 1993; Winter 1999). In addition, general scaling factors predicting flight speed from body mass can be derived from aerodynamic models (Norberg & Rayner 1987). According to presently available data, commuting flight speeds of glossophagines scale with body mass M as V [ms-i] = 20 M[kg]0-23 (Winter 1999). When neighboring flowers are close to each other, acceleration and deceleration phases with reduced speeds constitute a significant portion ofa flight interval. To determine acceleration and deceleration, we studied Glossophaga commissarisi (8.5 g) feeding at the bromeliad Vriesea gladioliflora in Costa Rica. The presence of a bat hovering and feeding at flowers was detected with photoelectric sensors at the flowers and timed by a computer (Winter 1999). The equation for flight acceleration derived from these data (see Table 8.1) can be used to estimate flight times between close flowers, and multiplication of these estimates by forward flight cost (Table 8.1) approximates the flight cost over short distances.

Fig. 8.2. Movements of the wings during hovering flight of Glossophaga soricina (at a flower of Vrieseagladioliflora). The wings need room to move in front of the body (c) and above it (a). The sequence (d)-(f) shows the supination of the "distal wing triangle" (wing tip reversal) during the backstroke of the wing, which generates lift. (From von Helversen 1993.)

Fig. 8.2. Movements of the wings during hovering flight of Glossophaga soricina (at a flower of Vrieseagladioliflora). The wings need room to move in front of the body (c) and above it (a). The sequence (d)-(f) shows the supination of the "distal wing triangle" (wing tip reversal) during the backstroke of the wing, which generates lift. (From von Helversen 1993.)

Hovering flight

By hovering, glossophagine bats remain airborne while imbibing the nectar solution (Fig. 8.2). This hovering involves a kinematic feature of wing movement - the "tip reversal" - that may be unique among bats. During the wing's backstroke, the morphological underside of the hand-wing is turned upwards (supinated), thus forming a distal wing triangle that generates lift during a short phase of the wing's backstroke (von Helversen 1986).

To determine the energetic cost of hovering flight, we trained glos-sophagine bats to visit an artificial feeder that also served as a respirome-try mask. When a bat inserted its head into the mask to feed, respiratory gases were withdrawn for oxygen and carbon dioxide analysis to estimate metabolic rates. Contrary to the expectations (from a previous quasi-steady aerodynamic analysis of hovering flight in glossophagines; Norberg et al. 1993), the metabolic cost of hovering flight turned out to be only slightly higher than the cost of horizontal forward flight (between 10% and 30%, depending on body mass, see Table 8.1; b; Winter 1998&; Voigt & Winter 1999). Although the small difference seems surprising, hummingbirds show a similar pattern (cf. Ellington 1991). It is interesting to compare the glossophagines' solution to hovering flight with that of other hovering nectar-feeders, sphingid moths and hummingbirds. Among these, glossophagines have the lowest mass-specific cost of hovering flight. At a power of 1.1 W, a glossophagine bat can support a body mass of 7 g, a hummingbird one of 4 g, and a sphingid moth a mass of3 g (Fig. 8.1). These differences in hovering energetics are partially explained by the effect of relative wing area (Voigt & Winter 1999).

Hovering duration The cost-benefit analysis of foraging requires knowledge of hovering durations during feeding. Infrared photoelectric devices installed at flowers both in the field and in the laboratory have shown that glossophagines normally hover for less than one second, more typically 0.3-0.6 s (Fleming et al. 1996; M. Tschapka & O. von Helversen, unpublished data). Hovering thus constitutes only a small fraction of the foraging time budget. The dominant factor in the flight energy budget of a glossopha-gine bat is the expenditure for commuting and moving between flowers in horizontal forward flight. Selection pressure to reduce the cost of forward flight may therefore account for the relatively high wing loading of glossophagines as compared to other bats and for their relatively short wings, which are shorter than predicted for optimal hovering (Norberg & Rayner 1987).

Minimum nectar energy densities

A nectar-feeding specialist can subsist in a habitat only if the spatial density of nectar energy (kj per foraging distance between neighboring flowers) is sufficient for balancing its energy budget. The energy relations summarized in Table 8.1 provide a basis from which minimum food energy levels can be estimated. Estimating resource densities is always difficult, but is easier for nectar-feeding bats than for most animals: (1) the caloric content of nectar can be quantified, so that energy gains during foraging are accessible to measurement; (2) the time and energy costs during foraging can now be calculated with some precision; and (3) particular plants are visited repeatedly over weeks to months, so spatial memory for flower location should enable bats to efficiently relocate flowers.

Individual Glossophaga commissarisi visiting Vriesea gladioliflora (Bromeliaceae) were tagged with transponders (PIT-tags) so that they could be identified automatically while hovering at flowers that had transponder readers installed in front of them (O. von Helversen & M. Tschapka, unpublished data). This study revealed that: (1) single flowers were visited by several bats (often two to three); (2) the feeding range of individual bats included about 40-50 Vriesea bromeliads; (3) individual bats visited single flowers from a few times up to about 30 times during a night; and (4) each time an individual bat consumed roughly 30 ^l of 16% sugar (wt/wt) nectar (Tschapka 1998; Y. Winter & O. von Helversen, unpublished data).

Individual plants of many bat-pollinated species flower over several months and, in addition, secrete nectar throughout much of each night. The "food-resource space" for a glossophagine bat in a rainforest will therefore often be an area with predictable locations of renewable food sources. By repeatedly visiting known locations, a bat can spend most of its foraging time commuting, with only a little time spent searching. The food-energy density of the habitat from a bat's point of view is thus a function of (1) the mean distance between neighboring flowers along the foraging route and (2) the mean caloric value of nectar obtainable during a flower visit.

The resource space that can be profitably exploited by a glossophagine bat is delimited by several boundaries. First, the overall sum of energy gains from foraging must be sufficient to meet the energetic requirements during the non-foraging time period (Ex).

i=i where Efl is the nectar energy obtained from flower visit i, Pf and Ph are the energy costs of horizontal forward and hovering flight per unit time, f is the commuting time between two flowers, t^ is hovering duration, and Ex is the energy cost ofliving for the rest of a day when not foraging, such as resting metabolic rate (including thermoregulation during daytime and foraging pauses during the night), food search, and social interactions. The sum of these energy expenditures constitutes the DEE.

DEE is constrained by the capacity for food processing, by renal clearance capacity, and by further internal factors that limit energy turnover (Weiner 1992; Winter 1998a). Total foraging time Tf is calculated according to n

Foraging time is constrained by the length of the night minus the cumulative duration of digestive periods and times needed for other activities.

With these equations, for a given DEE and flight time budget we can compute the maximum number of flowers that can potentially be visited by a bat and their minimum nectar energy content requirement. The number of flower visits during a night Nfl multiplied by the mean nectar energy Efl available from a flower visit must at least equal the daily energy expenditure DEE:

The number of flowers a bat can visit during a night depends on the mean distance between flowers Sff, the flight speed of the bat, the mean duration of a hover-feeding visit th, and the total duration of nightly flight Tf. The maximum number of flower visits thus equals the total duration of nightly flight divided by the mean time needed to approach and exploit a single flower:

Flight duration between neighboring flowers tff is a function of the flight speed V and the mean distance between flowers Sff. If this distance is large, then the mean flight speed V approaches commuting flight speed during foraging, which for glossophagines scales with body mass M (in kg) as Vf = 20 M0-23 (Table 8.1; Winter 1999). Flight duration tff for the distance Sff then simply becomes tff = Sf/Vf. Often, however, the distance between neighboring flowers will be shorter so that acceleration and deceleration must be taken into account. Here, we approximate this by assuming a constant delay of one second for a flower visit at a cost equal to forward flight. Thus tff (in seconds) is taken to equal (Sff/ Vf) +1.

Bats will not detect every flower available in their foraging areas, and they cannot be expected to establish the minimum-length route (the traveling-salesman problem) to visit their flowers. Consequently, the mean distance between plants along a bat's foraging route will be larger than the minimum theoretically obtainable within the habitat Sff, which we model by a factor effs (<1) for the search efficiency of a bat. The minimum nectar energy to be obtained from an average flower visit Efl then becomes

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