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At least one stomach-produced signal has the opposite effect. Ghrelin is a hormone secreted from gastric cells just prior to the onset of an anticipated meal, and its levels fall precipitously once eating is initiated. Exoge-nously administered ghrelin stimulates eating, even in individuals that have recently eaten (Cummings et al. 2001). Hence, ghrelin is unique among the signals that have been described that arise in the gastrointestinal tract and influence food intake, since all of the others act to reduce meal size (see table 7.1.1). An important and as yet unanswered question concerns the signals that elicit ghrelin secretion from the stomach. It is probable that the brain ultimately initiates ghrelin secretion from the stomach at times when eating is anticipated.

The second group of signals controlling food intake is related to the amount of stored energy in the body. The best known of these "adiposity" signals are the pancreatic hormone insulin and the fat cell hormone leptin. As depicted in figure 7.1.1, each is secreted into the blood in direct proportion to body fat, each enters the brain from the blood, and receptors for each are located in the arcuate nucleus of the hypothalamus in the brain. When either leptin or insulin is administered directly into the brain near the arcuate nucleus, individuals eat less food and lose weight in a dose-dependent manner. Likewise, if the activity of either leptin or insulin is reduced locally within the brain, individuals eat more and become quite obese (Schwartz et al. 2000; Woods et al. 1998). Hence, both leptin and insulin could hy-pothetically be used to treat human obesity, but only if they could be administered directly into the brain, since their systemic administration has proved relatively ineffective and elicits unwanted side effects.

The third category of signals controlling energy homeostasis includes neurotransmitters and other factors arising within the brain. These signals are generally partitioned into those with a net anabolic action and those with a net catabolic action. When their activity is stimulated in the brain, anabolic signals increase food intake, decrease energy expenditure, and increase body weight. In contrast, when the activity of catabolic signals is enhanced in the brain, anorexia and weight loss occur (fig. 7.1.2). While numerous neuropeptides and other neurotransmitters have been reported to alter food intake (see table 7.1.1), a few will serve as examples. Neuropeptide Y (NPY) is synthesized in neurons throughout the brain and peripheral nervous system. One of the more important sites of synthesis with regard to energy homeostasis is the arcuate nucleus of the hypothalamus, where NPY-synthesizing cells contain receptors for both leptin and insulin (see figs. 7.1.1 and 7.1.2). These NPY neurons in turn project to other regions of the hypothalamus, where they stimulate food intake and reduce energy expenditure; administering exogenous NPY near the hypothalamus results in robust eating (Schwartz et al. 2000; Woods et al. 1998).

A separate and distinct group of neurons in the arcuate nucleus also has receptors for both leptin and insulin, but these neurons synthesize a peptide called proopiomelanocorticotropin (POMC). POMC, in turn, can be processed to form any of a large number of active compounds. POMC neurons in the arcuate nucleus process the molecule into a-melanocyte-stimulating hormone (a-MSH), a potent catabolic signal (see fig. 7.1.2). Like NPY,

Adiposity Signals

Figure 7.1.2. Hypothalamic circuits that influence caloric homeostasis. The adiposity hormones, leptin and insulin, are transported through the blood-brain barrier and influence neurons in the arcuate nucleus (ARC). ARC neurons that synthesize and release NPY and AgRP are inhibited by the adiposity signals, whereas ARC neurons that synthesize and release a-MSH are stimulated by the adiposity signals. NPY/AgRP neurons are inhibitory to the PVN and stimulatory to the LHA, whereas a-MSH neurons are stimulatory to the PVN and inhibitory to the LHA. The PVN, in turn, has a net catabolic action, whereas the LHA has a net anabolic action.

Figure 7.1.2. Hypothalamic circuits that influence caloric homeostasis. The adiposity hormones, leptin and insulin, are transported through the blood-brain barrier and influence neurons in the arcuate nucleus (ARC). ARC neurons that synthesize and release NPY and AgRP are inhibited by the adiposity signals, whereas ARC neurons that synthesize and release a-MSH are stimulated by the adiposity signals. NPY/AgRP neurons are inhibitory to the PVN and stimulatory to the LHA, whereas a-MSH neurons are stimulatory to the PVN and inhibitory to the LHA. The PVN, in turn, has a net catabolic action, whereas the LHA has a net anabolic action.

a-MSH is released in other hypothalamic areas, where it elicits reduced food intake, increased energy expenditure, and loss of body weight. An important feature of this network is that a-MSH causes its catabolic actions by stimulating melanocortin (MC) receptors (specifically, MC3 and MC4 receptors). Activity of these same receptors can be reduced by a different neurotransmitter called agouti-related peptide (AgRP), which is also made in the arcuate nucleus; specifically, within the same neurons that synthesize NPY. Thus, arcuate POMC neurons, when stimulated by increased leptin and insulin (as occurs if one gains a little extra weight), release a-MSH at MC3 and MC4 receptors to reduce food intake and body weight. At thesame time, elevated leptin and insulin inhibit arcuate NPY/AgRP neurons. If insulin and leptin levels decrease (as occurs during fasting and weight loss), the POMC neurons are inhibited and the NPY/AgRP neurons are activated. The NPY stimulates food intake while the AgRP inhibits activity at the MC3 and MC4 receptors. This complex system therefore helps to keep body weight relatively constant over time, and the transmitters involved (NPY, AgRP, and a-MSH) are but three of a long list of transmitters that influence the system (Schwartz et al. 2000; Woods etal. 1998).

Integration of the Different Categories of Signals

An area of considerable research activity at present is determining how the various types of signals interact to control energy balance. The picture that is emerging is that most regulation occurs at the level of meal size. That is, there is flexibility with regard to when meals begin, since most evidence suggests that idiosyncratic factors based on convenience, environmental constraints, and experience are more influential than energy stores in determining meal onset (Woods 1991). However, once a meal starts and food enters the body, satiety signals are secreted, and as they accumulate, they eventually create a sufficient signal to terminate the meal (Smith and Gibbs 1998). Evidence suggests that the sensitivity of the brain to satiety signals is in turn regulated by adiposity signals. That is, when leptin and insulin are relatively elevated (as occurs ifone has recently gained weight), the response to signals such as CCK is enhanced. In this situation, meals are terminated sooner and less total food is consumed, leading to a loss of weight over time. Conversely, when leptin and insulin are decreased (as occurs ifone has lost weight), there is reduced sensitivity to satiety signals, and meals tend to be larger. Many other factors, of course, interact with this system. For example, seeing (or anticipating) a particularly palatable dessert can easily override the signals so that an even larger meal can be consumed.

It is important to remember that the biological controls summarized in this short review must be integrated with all other aspects of an individual's environment and lifestyle. Because of other constraints, the actual effect of satiety and adiposity signals is not always apparent when food intake is assessed on a meal-to-meal basis. Rather, energy balance (the equation of intake and expenditure in order to maintain a stable body weight) becomes evident in humans only when assessments are made over several-day intervals (de Castro 1988).

230 Anders Brodin and Colin W. Clark

(Box 7.1 continued)

Although most of the research on the signals that control food intake has used humans, rats, or mice as subjects, sufficient analogous experiments have been performed on diverse groups of mammals as well as on several species of birds and fish, and the results are quite consistent with the conclusions above. Another important point that has recently come to light is that the same intercellular as well as intracellular signals that control energy homeostasis in mammals have been found to have comparable functions in many invertebrates, including insects and roundworms, as well as in yeasts (see review in Porte et al. 2005). What differ are the sources of energy used by different organisms and the foraging methods used to obtain them.

7.3 Forms of Energy Storage and Regulation

Food Stored in the Gut

The digestible contents of the gut will eventually become available as energy and can be considered an energy store. The supply varies depending on how much and how recently an animal has eaten. During winter, food in the crop of the willow ptarmigan (or red grouse), Lagopus lagopus, weighs on average 15% of body mass, enough to sustain the grouse for 24 hours (Irving et al. 1967). Yellowhammers (Emberiza citrinella) fill their crops with wheat before going to roost in early winter (Evans 1969). The arctic redpoll (Carduelis hornemanni)has a larger crop than similar species of southern latitudes, presumably because extra stores are more important in a cold climate (White and West 1977). However, in most species of small birds, food stored in the crop is a minor energy reserve.

Fat and Carbohydrates

Animals cannot store food in the digestive tract for very long. Even a large animal will digest the contents of its crop or stomach relatively quickly, and its blood glucose level will soon fall unless the animal consumes more food. Glycogen lasts longer, but animals can store only limited amounts. In order to build up larger or longer-lasting energy supplies, animals must either gain body fat or hoard food outside the body.

Animals commonly store lipids as fat and carbohydrates as glycogen, while plants normally store lipids as oils and carbohydrates as starches. Some marine organisms store waxes (Pond 1981). In most animals, carbohydrates primarily

Energy Storage and Expenditure 231

Figure 7.1. A tardigrade with the body cavity around the gut and the gonad (here with five oocytes) filled with a large number of circular storage cells that contain fat and carbohydrates. These cells represent the system for both energy storage and circulation in tardigrades. The storage cells show a distinct pattern of buildup and utilization ofenergy stores (reflected by variation in the sizes ofthe cells) strongly connected with the cycle of egg maturation. (After a photo by K. I. Jonsson.)

Figure 7.1. A tardigrade with the body cavity around the gut and the gonad (here with five oocytes) filled with a large number of circular storage cells that contain fat and carbohydrates. These cells represent the system for both energy storage and circulation in tardigrades. The storage cells show a distinct pattern of buildup and utilization ofenergy stores (reflected by variation in the sizes ofthe cells) strongly connected with the cycle of egg maturation. (After a photo by K. I. Jonsson.)

serve as fuel for short-term, high-intensity work, since they generate more energy per oxygen molecule than does fat. Fat, on the other hand, is better for long-term storage in the body. Being hydrophobic, it contains twice as much energy per unit weight as the hydrophilic carbohydrates (Weis-Fogh 1967). Animals can also metabolize proteins to produce energy, although these mainly serve other functions.

Many examples of energy storage come from studies on birds and mammals, but invertebrates also store energy. Tardigrades have special cells for storing fat and glycogen (fig. 7.1). These small animals use the energy in these cells for reproduction. The storage cells vary in both size and contents. When the tardigrade reproduces, the cells shrink or disappear and growing eggs take their place (Jonsson and Rebecchi 2002). Vetch aphids (Megoura viciae) store lipids in special fat cells and use this energy for reproductive investment (Brough and Dixon 1989). Benthic amphipods of several species (Pontoporeia spp. and some close relatives) accumulate lipids during the spring diatom bloom (Hill et al. 1992). Some amphipod species may store lipids in their bodies for as long as a year. Amphipods use these stores during periods of food scarcity, reproduction, and metamorphosis.

Insects that normally fly long distances use fat deposits as fuel, while those that normally only make flights of short duration use carbohydrates (Yuval et al. 1994). In the mosquito Anophelesfreeborni, male mating success depends on swarming ability (Yuval et al. 1994). Swarming occurs after sunset, and the males feed on nectar after swarming. Since the next swarming flight will not occur until the following evening, the mosquito must store energy, primarily in the form of glycogen, for the rest of the night and the following day. The mosquitoes also have body lipid stores, but they use these for resting metabolism and not for flight.

Animals also use carbohydrates as short-term fuel and fat as long-term fuel in many contexts other than flight. Wood frogs (Rana sylvatica), for example, breed explosively during a mating period that lasts only 3—5 days (Wells and Bevier 1997), fueled by large glycogen reserves in muscle tissue. The males do not feed during the breeding period, being preoccupied with calling and searching for females. Spring peepers (Pseudacris crucifer), on the other hand, have a prolonged mating period that may last up to 2 months. During this period, males call at extremely high rates—3,000 to 4,000 notes per hour. Males draw 90% of the energy used for calling from fat and only 10% from glycogen (Wells and Bevier 1997). Most hibernating animals rely on fat for their winter metabolism, though carbohydrates can also be important in this respect. In the common frog (Rana temporaria), glycogen forms 40%— 50% of the energy stores at the onset of hibernation and supplies 20%— 30% of the energy metabolized during the winter (Pasanen and Koskela 1974).

Two forms of avian fat regulation have attracted special interest from researchers: migratory fattening and fat regulation in wintering songbirds. Box 7.2 deals with migratory fattening, and we develop some specific models of winter fat regulation in this chapter. Some bird species require large fat reserves for reproduction. Northern populations of geese build up larger fat deposits for breeding than southern populations (Mainguy and Thomas 1985). In harsher northern environments, geese must rely on fat for both yolk production and the female's own metabolism. At more southerly latitudes, the earlier growth of vegetation can support the female's metabolism during incubation, but females must still rely on fat for yolk production.

BOX 7.2 Energy Stores in Migrating Birds

Ake Lindstrom

Humans imagine migrating birds as free and unfettered in long and spectacular flights, but the truth is a little more prosaic: most of a migrant's time is spent on the ground. As much as 90% of its total time, and 66% of its total energy, is spent on foraging and resting ("stopovers") before and between migratory flights (Hedenstrom and Alerstam 1997). Migration can therefore be seen largely as a foraging enterprise, now and then interrupted by flight.

The long flights of migrating birds would not be possible without the deposition of extensive fuel stores. Even swallows, masters of feeding while in flight, put on substantial fuel stores during migration (Pilastro and Magnani 1997), presumably because they and other migrants often cross large ecological barriers where foraging is not possible at all, such as oceans and deserts. Migrants on stopovers must work hard and consume much more food than usual to deposit the necessary fuel. Accordingly, foraging capacity and conditions during stopovers are crucial for successful migration. The constitution of avian fuel stores, the amount and rate of fuel deposition, and the rate of foraging and energy acquisition during fuel deposition are therefore of particular interest to researchers trying to understand bird migration.

What Kind of Fuel?

It has long been thought that birds use only fat as their fuel for migration. This makes sense, since fat is by far the most energy-dense fuel available. Although fat catabolism is indeed responsible for about 95% of the energy used for flight, some protein is also metabolized during flight. Therefore, it is appropriate to speak of "fuel" rather than "fat" deposition.

About 30% of the total mass loss during a flight (and subsequent mass increase during a stopover) may be due to protein catabolism (Jenni and Jenni-Eiermann 1998). The protein fuel is "stored" as active tissue, mainly in muscles, liver, gut, and heart. Some level of protein catabolism may be physiologically necessary for the active animal, but the rapid cyclic metabolism of organs may mainly reflect adaptive rebuilding of the bird's body (Piersma and Lindstrom 1997). During flight, the birds have a large "flying machine" (muscles and heart), whereas digestive organs are small to avoid extra flight costs. During stopovers, the birds have a large "eating machine" (gut, intestines, liver), whereas heart and flight muscles are relatively small.

How Much Fuel?

The size of migratory fuel stores varies enormously between individuals and species, from very small (5%—10% above lean body mass) to huge (> 100% above lean body mass; Alerstam and Lindstrom 1990). That is, some birds more than double their mass before they take off for a migratory flight. Fuel stores for migration are regularly much larger than stores for winter survival, which rarely exceed 50% (Biebach 1996). Obviously, many birds do not store as much fuel in winter as they are physically capable of.

Numerous factors influence the amount of fuel stored by a migratory bird. The minimum is obviously set by the distance that needs to be covered, especially when migrants must cross ecological barriers (Alerstam and Lindstrom 1990). Stores may also be larger than the minimum set by distance, as a safety measure against potentially unfavorable arrival conditions (Gudmundsson et al. 1991). Other strategic decisions that influence the size of fuel stores relate to how much (or rather, how little) time and energy ideally should be spent on migration (Alerstam and Lindstrom 1990). If birds try to minimize time spent on migration, maximizing the speed of migration to reach the destination as soon as possible, then they should put on more fuel at a given site the faster the rate of fuel deposition (Lindstrom and Alerstam 1992). If minimizing energy expenditure is more important, they should put on relatively small stores, independently of fuel deposition rate (Danhardt and Lindstrom 2001). The risk of predation may also be an important factor to take into account. One way to minimize predation risk is to keep fuel stores small, reducing the negative effects of weight on maneuverability and takeoff ability (Kullberg et al. 1996).

The upper limit to the size of fuel stores is set by the capacity for takeoff and flight (Hedenstrom and Alerstam 1992). Some migrants have been reported as being so heavy that they could barely take off from the ground (Thompson 1974). At the other end of the spectrum, poor feeding conditions may almost preclude fuel deposition. The smallest fuel stores reported ( 10%) are found in irruptive species ("invasion species") such as tits, woodpeckers, and crossbills (Alerstam and Lindstrom 1990). This is not surprising, however, since these birds are on the move because of food shortage in the first place.

Rate of Fueling?

When time is short, which it may be for migrants that need to cover great distances during a short migration period, the fueling rate is crucial. The fueling rates reported for migratory birds are normally 0%—3% per gram of lean body mass per day. For example, a 100 g lean bird adding 3 grams per day has a fueling rate of 3%. For this bird, it takes 20 days to put on 60% fuel. The highest fueling rates known in wild birds are 10%—15% (Lindstrom 2003).

The maximum fueling rate is achieved when the food intake rate is maximized and the energy expenditure rate is minimized (the minimum possible energy expenditure rate is the basal metabolic rate, BMR). Maximum fueling rates are negatively correlated with body mass, being 10%—15% in small birds (less than 50 g) and 1%—2% in large birds such as geese (more than 1 kg). The explanation for this important relationship is as follows. The maximum energy intake rates of animals are about 5—6 times BMR, independently of body mass (Kirkwood 1983). BMR scales allometrically (the energy turnover rate per gram decreases with increasing body mass), so fueling rates are lower in larger birds. As a result, a small songbird with a fueling rate of 10% can reach a given proportional fuel load—for example, 50%—in 5 days, whereas a large goose with a rate of 2% will need 25 days to reach the same fuel load. On average, the relative amount of fuel needed to cover a given distance is independent of body size (for example, a 40% fuel load is needed to cover 2,000 km). Therefore, fueling rates largely determine the speed ofmigration. Large birds may thus be limited in how far they have time to migrate within a given migration season.

The actual rate offueling in a migrant is most often determined by food abundance. However, some migrants experience unlimited food supplies, such as spilled seeds on fields and invertebrate eggs and larvae on beaches. In these birds, it is mainly the capacity of the digestive system that limits fueling rates (Lindstrom 2003). In addition, the amount of time per day that feeding is possible is important (Kvist and Lindstrom 2000). For diurnal feeders, it is therefore advantageous to migrate when days are long (for example, at high latitudes in summer).

Migratory birds in captivity display many traits that they would in the wild; for example, they consume large amounts of food whenever possible. Such studies have shown that migratory birds have among the highest energy intake rate capacities measured in any homeothermic animal (Kvist and Lindstrom 2003). Intake rates of up to 10 times BMR have been measured. A contributing factor is certainly the capacity to rapidly enlarge the digestive organs during fueling. Natural selection has obviously favored traits that make large energy turnover rates possible during migration.

Some female pinnipeds fast during lactation so that they can remain with their pups. Female gray seals (Halichoerus grypus) lactate for 16 days. Their milk contains 60% fat, and the pups gain an average of 2.8 kg per day, most of it as body fat (Boness and Bowen 1996). This weight gain allows the pup to stay on the ice until it has molted and is ready to go to sea. During her fast, the mother uses fat in the blubber layer and loses almost 40% of her body mass (Iverson et al. 1993).

Food Hoarding

Some species accumulate external food reserves, typically called hoards or caches, that they can use as substitutes for or supplements to energy reserves stored in the body. In honeybees (Apis mellifera), queen and workers survive the winter by eating honey that they stored in autumn. To make sure that there is enough food for the hive, workers usually kill the drones, which the hive no longer needs, but if honey stores are large, the workers may allow the drones to live (Ohtani and Fukuda 1977). Under cold conditions, the bees form a cluster so that a dense mantle ofworkers insulates the brood (Michener 1974; Seeley 1985). To save energy, the bees actively reduce the oxygen level in the hive, thereby reducing their metabolic rate. In cold weather, the hive may be nearly dormant, with an oxygen level of only 7.5% in the core (van Nerum and Buelens 1997). The bees can also increase the hive's temperature by active heat production, such as movements of the flight muscles (Michener 1974; Seeley 1985).

European moles (Talpa europeae) store earthworms in underground "fortresses" (Funmilayo 1979). The mole decapitates the worm and pushes its front end into the earth wall. Without a front end, the worm cannot move, and it stays alive and fresh until it is eaten, often after several months. A single mole may store over a kilogram of worms in this way, which serves as an important energy reserve (Skoczen 1961).

Beavers (Castor fiber and C. canadensis) stay in their lodges most of the winter. During this time, they exploit caches ofpreferred foods, such as twigs and branches of aspen (Populus spp.), birch (Betula spp.), and hazel (Corylus spp.). They stick the branches vertically into the bottom mud or stock them under floating rafts that they construct of less palatable trees (Doucet et al. 1994). The rafts and the upper ends of the vertical branches will freeze into the ice, and the palatable underwater parts will then become a safe underwater supply of winter food (Vander Wall 1990).

Male northwestern crows (Corvus caurinus) store mussels found at low tide. The stores ensure that the crows can eat mussels even when the high tide makes them unavailable. Males feed incubating females stored mussels, which makes it possible for females to stay on their eggs (James and Verbeek 1984). The South Island robin (Petroica a. australis) stores earthworms during the early morning when they are most available. Robins eat the stored worms later the same day (Powlesland 1980).

Regulation of Energy Expenditure

An alternative to increasing the amount of stored energy is to reduce energy expenditure. Since energy stores will last longer if an animal reduces its metabolic rate, strategies such as hibernation, torpor, and hypothermia are closely connected to energy storage. We will discuss such strategies that mainly aim to reduce energy expenditure in this chapter. Aestivation, or summer torpor, is a functionally equivalent way to escape drought or high temperatures.

In temperate and boreal regions, ectotherms and many small endotherms hibernate by entering a state of torpor. Their body temperatures may be close to zero and their heart rates reduced to only a few strokes per minute. Endotherms that hibernate are typically small, insectivorous mammals, such as bats and hedgehogs. Some birds, such as hummingbirds and nightjars, also use torpor to save energy. Large mammals such as bears and badgers "hibernate" with body temperatures only a few degrees below normal (Hissa 1997). The basis for this difference between small and large mammals is largely allometric. Larger animals have more heat-producing mass in relation to cooling surface, and hence can have lower metabolic rates, than small ones. Hibernation at a high body temperature requires large energy reserves, but has other benefits. A hibernating bear can flee or defend itself almost immediately if startled. In addition, pregnant females can give birth and lactate in the protected den, which would be impossible under torpor.

7.4 The Economy of Energy Reserves

Benefits of Energy Reserves

The previous section gave a sampling of the forms of energy storage. Energy storage allows animals to perform activities, such as sleeping or breeding, that are not compatible with foraging, to inhabit areas with temporarily harsh conditions, to survive periods of food shortage, and so on. Though the most obvious benefit of storing fat in the body is the energy that becomes available when it is metabolized, there are other possible benefits, such as insulation, protection, support, and social and sexual signals (Witter and Cuthill 1993). Furthermore, energy stores can provide an insurance benefit, even if the animal rarely has to metabolize them (Brodin and Clark 1997).

Long-term food hoarding provides a good example of how active energy regulation allows animals to inhabit temporarily harsh environments. Nutcrackers (Nucifraga spp.) spend most of the autumn hoarding food (Swan-berg 1951; Tomback 1977; Vander Wall 1988), and they depend on this stored food during the winter. Hoarding makes their regular food source—pine seeds or hazelnuts—available during a predictable time of food shortage—the winter. When pine or hazelnut crops fail, nutcrackers turn up in large numbers in areas far from their breeding grounds (Vander Wall 1990). These massive emigrations illustrate the nutcrackers' dependence on stored food.

Family groups of acorn woodpeckers (Melanerpes formicivorus) maintain granaries of acorns consisting of specially excavated holes in tree trunks or telephone poles. They use the stored acorns during brief periods of food shortage, but not as a regular winter food source (Koenig and Mumme 1987). So, for acorn woodpeckers, food hoarding seems to be a hedge against unpredictable periods of low food availability. In contrast, nutcrackers need stored food to survive the predictable onslaught ofwinter.

These two benefits of food hoarding frequently act at the same time. The willow tit (Parus montanus) is a small boreal parid. Like nutcrackers, they store a large proportion of their winter food during autumn. An individual may store 40,000 to 70,000 items in one autumn (Haftorn 1959; Pravosudov 1985; Brodin 1994c). Other, less well-known parid species may store even more (Pravosudov 1985). Willow tits probably do not remember the specific locations of all these caches (Brodin and Kunz 1997). Instead, they place their caches in locations where they will forage during the winter (Brodin 1994b). These stores increase the hoarder's general winter food level (Brodin and Clark 1997) and, as in nutcrackers, they constitute a regular source of winter food (Haftorn 1956; Nakamura and Wako 1988; Brodin 1994c).

Besides this massive hoarding in autumn, willow tits also store smaller numbers of seeds if there is surplus food during the winter (Haftorn 1956; Pravosudov 1985; Brodin 1994c). Over shorter time periods, tits can remember the precise locations of seeds they have stored (e.g., Sherry et al. 1981). Tits can retrieve these remembered seeds more quickly than the larger store of unremem-bered seeds. They are too few to be a substantial energy source, but provide insurance against unpredictable conditions. Such small caches that are retained in memory may allow willow tits to maintain lower fat reserves than nonhoard-ing species, avoiding fat levels that would be costly to carry (Brodin 2000).

The importance of energy storage as a bet-hedging strategy increases as the environment becomes less predictable. Avian ecologists assume that ground foragers experience more variation in winter than tree-foraging species. Rogers (1987) compared fat reserves in species of similar size and physiology foraging in different habitats. He found that tree foragers carried smaller fat reserves than similar-sized species foraging on the ground.

Small birds in boreal regions are fatter in winter than the rest of the year (Lehikoinen 1987; Haftorn 1992). They also have a larger daily amplitude of mass gain and loss in winter, which depends on the fact that winter nights

Figure 7.2. Winter fattening in small birds. The figure shows a hypothetical example with a sudden onset ofwinter (dashed vertical line) when temperatures fall below zero and the environment becomes covered with snow. Since nights in winterare longerand colderthan in autumn, the amplitude ofthe daily weight gain and loss is larger, but minimum reserves are larger as well. This phenomenon was labeled winter fattening by Lehikoinen (1987).

Figure 7.2. Winter fattening in small birds. The figure shows a hypothetical example with a sudden onset ofwinter (dashed vertical line) when temperatures fall below zero and the environment becomes covered with snow. Since nights in winterare longerand colderthan in autumn, the amplitude ofthe daily weight gain and loss is larger, but minimum reserves are larger as well. This phenomenon was labeled winter fattening by Lehikoinen (1987).

are longer and colder than summer nights (fig. 7.2). Their reserves at dawn are higher in winter than in summer, meaning that the birds maintain a larger buffer against poor feeding conditions in winter, a phenomenon called winter fattening (Lehikoinen 1987). Winter fattening occurs both in the field (Rogers and Rogers 1990) and in the laboratory. Great tits (Parus major) increased their fat reserves in response to stochastic variation (Bednekoff et al. 1994; Bednekoff and Krebs 1995). Thus, stored energy serves both as a regular energy source and as a bet-hedging strategy.

Costs of Storing Energy

Acquiring and maintaining energy stores can be costly in several ways. In humans and domestic animals, excessive fat deposits can increase mortality, mainly through increased strain on the heart and vascular system (Pond 1981). An energy-storing animal spends time and energy foraging that it could have allocated to other behaviors. Furthermore, foraging may entail exposure to predators that the animal would not otherwise have experienced (see chap. 13).

Behavioral ecologists have extensively studied the costs of storing body fat in birds, both theoretically and empirically. Pravosudov and Grubb (1997) have reviewed energy regulation in wintering birds. Witter and Cuthill (1993) have reviewed the costs of carrying fat in birds, noting especially that mass-dependent costs may be important. Small birds should carry the smallest

Figure 7.3. Angle of ascent in relation to fat load (as a percentage of fat-free body mass) in a warbler, the blackcap. To make these measurements, birds foraging in a cage were startled by an attacking artificial predator. (After Kullberg et al. 1996.)

reserves possible to escape an attacking predator, but they should carry the largest reserves possible to avoid starvation. This means that they face a tradeoff between starvation and predation that may not be evident in nonflying organisms. In section 7.6 we explore this trade-off in detail.

Behavioral ecologists have focused on both mass-dependent predation risk and mass-dependent metabolic expenditure. Houston and McNamara (1993) have also suggested that body mass may reduce foraging ability, especially for birds that forage on the wing. Mass-dependent predation risk seems obvious; physical laws tell us that increasing fat loads must affect a bird's acceleration and takeoff angle. Kullberg et al. (1996) have shown this empirically using blackcaps (Sylvia atricapilla) (fig. 7.3). They measured takeoff angles and velocity during premigratory fattening, when fat loads were as large as 30%—60% of the lean body mass. It is less clear, however, whether smaller fat loads also affect takeoff ability. In boreal regions, wintering passerines gain about 10% of lean body mass in the course of every winter day and metabolize this store during the night when they cannot forage. Empirical evidence suggests that body mass fluctuations of this magnitude have little or no effect (Kullberg 1998a; Kullberg et al. 1998; Veasy et al. 1998; van der Veen and Lindstrom 2000; but see Metcalfe and Ure 1995). Either we cannot detect the effects of these small increases, or birds somehow compensate for the extra mass. Although we have no firm evidence, birds might compensate by increasing flight muscle tissue, and hence flight power, in parallel with fat. Lindstrom et al. (2000) have demonstrated a rapid buildup of wing muscles in parallel with fat reserves in migrating knots (Calidris canutus), so wintering passerines might do this as well. Small birds may be able to compensate for small or moderate fat loads, but probably not for large fat loads (fig. 7.4).

Changing environmental conditions may require that animals make major adjustments to their energy reserves. In autumn, migrating or hibernating animals require large fat reserves. Animals that spend the winter at northern latitudes build up larger minimum reserves in winter than they carry in summer and autumn. Houston et al. (1997) and Cuthill and Houston (1997) labeled the costs of such seasonal transitions "acquisition costs," whereas they called costs emanating from the daily regulation of reserves "maintenance costs." If we consider the daily fluctuations in figure 7.2, it is clear that fat is acquired and lost on a daily as well as a seasonal basis. This means that "maintenance costs" may also result from the acquisition of fat. The main difference is that acquisition costs result from increasing the average level of reserves, rather than just compensating for daily fluctuations.

Hoarding food externally also incurs costs. Hoarding will be wasted effort if precipitation, temperature, or microorganisms cause stores to spoil. Honeybees invest considerable time and work in converting stored nectar into a more durable form, honey. They produce an enzyme that converts simple sugars into more concentrated forms that have antibacterial effects (e.g., VanderWall 1990).

An important ecological consideration is that competitors can steal hoarded supplies. To reduce theft, hoarders can defend larders or scatter caches widely. Typical larder hoarders are small burrowing mammals such as various rodents (Rodentia), pygmy possums (Burramysparvus), shrews (Soricidae), and pikas (Ochontidae) (Vander Wall 1990). Larder hoarders can easily retrieve stored

Figure 7.4. The effect of body fat mass on predation risk as suggested by Brodin in a theoretical model. The x-axis shows fat as a percentage of lean body mass. At low levels of fat, a bird can compensate for the extra mass carried by increasing its flight muscle tissue. (After Brodin 2001.)

items, while scatter hoarders face a more challenging retrieval problem. But the consolidation that makes retrieval from a larder so simple also means that the whole supply can be lost if a larger competitor finds the larder. In eastern chipmunks (Tamias striatus), only individuals that can defend a burrow store food in larders. Newly emerged juveniles scatter-hoard until they become older and stronger (Clarke and Kramer 1994).

Scatter hoarders do not risk losing all their stored items if a competitor discovers a cache, but they need some mechanism for retrieval oftheir concealed and scattered caches, which can also be costly. The most accurate way to retrieve cached items is probably to remember their exact locations. However, if thousands of caches are stored for several months, this may require special adaptations of spatial memory. Implementation of memories may require repair of neurons and synapses, redundancy or backup in the form of extra brain tissue, and so on. Dukas (1999) discusses the potential costs of memory.

As mentioned earlier, animals can reduce energy expenditures instead of building up energy stores, but this strategy also incurs costs. In winter, small birds at northern latitudes frequently use nocturnal hypothermia to save energy (e.g., Haftorn 1972; Reinertsen 1996). Small passerines use their high metabolic rate to achieve body temperatures of up to 42°C. A 10°C reduction in nighttime body temperature can save a considerable amount of energy. Hypothermia, however, might also be risky. At dawn, it may take 15 minutes to regain a normal body temperature, and the bird might be vulnerable to predation during this warm-up period. We know little, however, about the possible costs of nocturnal hypothermia (see section 7.7).

7.5 Modeling Energy Storage

Optimization models can help us understand the selective forces that have shaped energy storage and expenditure strategies. Such models have become standard in evolutionary and behavioral ecology (Stephens and Krebs 1986; Mangel and Clark 1988; Bulmer 1994; Houston and McNamara 1999) and range from simple analytic to complex computer models. While analytic models may be appropriate for studying foraging efficiency, they seldom provide sufficient detail for studies of the acquisition, storage, and use of energy supplies.

As a rule, we cannot measure the fitness consequences of stored energy directly. Instead, we must use some measurable currency that, we assume, is ultimately linked to fitness. Foraging models typically use currencies based on averages, such as the average net rate of energy gain (rate maximization) or the average time required to obtain the necessary daily food intake (time minimization). Models of energy storage have used the net rate of energy gain (e.g., Lucas and Walter 1991; Tamura et al. 1999), the ratio of energy gained to energy spent (Wolf and Schmid-Hempel 1990; Waite and Ydenberg 1994a, 1994b), or survival rate (Lucas and Walter 1991). We will use the probability of survival to the end of winter as the fitness currency in the dynamic models in this chapter. In cases in which winter mortality is high, it is reasonable to assume that winter survival is directly related to Darwinian fitness. In other cases, ending the winter with adequate reserves for future activities may also be important; for example, in models that include breeding events.

As section 7.4 shows, collecting food to store is costly. We can model these costs in various ways, depending on the currency and the aim of the model. Sometimes it may be convenient to see these costs as a probability of death, while at other times it may be more convenient to see them as energy losses. We will give two specific examples here.

In a model that aimed to investigate the potential effects of dominance rank on optimal food hoarding effort, Brodin et al. (2001) assumed that the cost of food hoarding consisted of an increase in predation risk while foraging. In this model, hoarding in autumn increased winter survival by making more winter food available at the same time as it reduced present survival in autumn by a probability of death, Pd. If predation risk is proportional to the amount of food stored, h (or more generally, foraging effort), this probability can be expressed as

(modified from Schoener 1971). Here k is a scaling constant. The probability ofsurvival then becomes

which can be multiplied by some fitness measure.

In some cases, it might be better to model costs as energy losses. In a field experiment on hoarding gray jays (Perisoreus canadensis), Waite and Ydenberg (1994b) used the time and energy spent hoarding as costs. The net rate of storing, Yh, is

where g h is the average energetic gain from one cache, pR the probability of recovering it, ce the energetic cost of transporting and storing it, cT the energetic cost of waiting for food at the feeder (a time cost controlled by the

Figure 7.5. A hypothetical graph of a migratory bird's daily food availability (solid curve) in relation to its average energy requirements (dashed line) over a year. During some periods food availability exceeds energy requirements, while food availability falls below energy requirements on other occasions.

Figure 7.5. A hypothetical graph of a migratory bird's daily food availability (solid curve) in relation to its average energy requirements (dashed line) over a year. During some periods food availability exceeds energy requirements, while food availability falls below energy requirements on other occasions.

experimenters), % the time needed to store one cache, and tw the manipulated waiting time.

A Graphical Paradigm

A graph (fig. 7.5) of an animal's daily food availability and energy requirements over a year shows periods ofpositive energy balance (food availability exceeds energy requirements) interspersed with periods of negative balance (food availability falls below energy requirements). Prolonged periods of positive energy balance might coincide with breeding episodes, whereas periods of negative energy balance would place emphasis on survival. This chapter focuses on periods of potential negative energy balance. Such periods must follow periods ofpositive energy balance because animals need to build energy reserves for use during subsequent periods ofnegative energy balance.

This graphical paradigm oversimplifies the problems of energy storage and retrieval in several respects. For example, a simple graph of the type in figure 7.5 cannot indicate uncertainty. In reality, the supply of and demand for energy resources may fluctuate randomly (though with predictable, seasonally dependent patterns) on both long-term and short-term time scales. Exceptionally high food availability during a period of positive energy balance may result in above average reproductive success. Conversely, low food availability during the normally productive season may limit reproduction and lead to increased risk of mortality. Under such circumstances, parents may sacrifice current reproduction to enhance survival.

ESS Models

In an influential paper, Andersson and Krebs (1978) showed the necessity of a recovery advantage for hoarders over nonhoarding conspecifics for hoarding to constitute an evolutionary stable strategy (ESS). In a group of foragers of size n, it is necessary that fH(nh) > FNH(nH). (7.4)

FH is the fitness ofa hoarder in a group with nH hoarders, and FNH is the fitness of nonhoarders in the same group. For hoarding to be an ESS, the probability that the hoarder will find its own cache, pH, must exceed the probability that a scrounger will find the cache, pS, by

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