Stephens & Foraging - Behavior and Ecology - Chapter 7 pdf

7 Energy Storage and Expenditure Anders Brodin and Colin W. Clark 7.1 Prologue The snow creaks under our winter boots as we walk along the snow scooter track to our study site. The cold is overwhelming, and though we have been walking for an hour, we do not feel warm. The air is perfectly still, and the heavy snow on the branches of the surrounding conifers absorbs all sounds. When we arrive at the bait station, we spill some seeds onto the feeding tray and retire to the nearby trees. The seeds soon attract the attention of some willow tits. It is astonishing that these 10 g animals with their high-speed metabolism can survive in an environment where the temperature can remain below freezing for months. We know they need to eat three or four food items per minute throughout the short winter day to survive the long night. Surprising- ly, thewillowtits donot consume theseeds.Instead, theybeginferrying seeds fromthetray to hidingplacesnearby. They concealthemcarefully under flakes of bark, in broken branches, and in tufts of lichen. Evident- ly, willow tits can exploit the temporary abundance of seeds most effec- tively by hoarding them, deferring their consumption until later. so- phisticated energy management makes their survival in these extreme conditions possible. Their daily regimen combines use and maintenance of external (thousands of individually stored items) and internal (several 222 Anders Brodin and Colin W. Clark grams of fat) energy supplies, augmented when necessary with tactics such as hypothermia. 7.2 Introduction Organisms need energy to sustaintheirgrowthand metabolism. Most animals do not forage continuously and must store energy for periods when foraging is not possible. They also need to perform other activities that may not be compatible with foraging. Periods when energy expenditure exceeds energy intake may be short;forexample, between two meals or overnight.Theymay also be long, lasting through the winter or throughout extended periods of drought. Energy can be stored in the body as fat, carbohydrates, or sometimes as proteins, or in the environment as hoarded supplies. Many forms of energy storage are well known. Bears become very fat in autumn before they go into hibernation. Honeybees store large supplies of honey in the hive to be used as food during the winter. Many avian and mam- malian species hoard thousands of seeds and nuts in autumn and depend on these foods during the winter. Energy storage is also common in organisms such as plants and fungi. Many of our most common root vegetables, such as potatoes, rutabagas, and carrots, are good examples of plants that store energy for future growth and reproduction. Animals must actively regulate their energy expenditure. During hiberna- tion, most animals reduce expenditure by lowering their body temperature and thereby their metabolism. Many humans try to decrease their body fat energy stores and get slimmer; for example, by reducing food intake. Others instead try to increase their energy stores. Before a race, cross-country and marathon runners may actively deplete the glycogen reserves in the liver and muscles. The evening before the race, they gorge on carbohydrates, attempt- ing to enlarge those reserves and so increase their endurance (e.g., ˚ Astrand and Rodahl 1970). For animals that live in seasonally fluctuating environments, finely tuned management of the energy supply may be crucial for survival and reproduction. Indeed, without such adaptations, these organisms could not inhabit these environments. We begin this chapter by presenting examples of how animals store and regulate energy. Next, we adopt an economic perspective that focuses on the costs and benefits of energy storage. This leads to a brief overview of how be- havioral ecologists havemodeled energy storage. We devote thesecondhalf of the chapter to dynamic state variable modeling (Houston and McNamara 1999; Clark and Mangel 2000). From the simplest possible model, we pro- ceed through models of increasing complexity to illustrate the key factors Energy Storage and Expenditure 223 controlling energy storage. The text considers the problems of small passerine birds in a cold winter climate as a convenient model for problems of energy storage andregulation. We focuson evolutionaryaspects ofenergy regulation. Box 7.1 introduces neural and endocrine mechanisms of energy regulation. BOX 7.1 Neuroendocrine Mechanisms of Energy Regulation in Mammals Stephen C. Woods and Thomas W. Castonguay Myriad approaches have been applied to the study of how animals meet their energy requirements. A century ago, the predominant view was that events such as gastric distension and contractions determine food intake, with signalsfrom thestomachrelayedtothe brainover sensorycircuits such as the vagus nerve. One of the most influential theories of energy balance, the “glucostatic hypothesis” posited over 50 years ago by Jean Mayer (1955), proposed that individuals eat so as to maintain a privileged level of immediately availableandusable glucose.When thiscommodity decreased, either due to enhanced energy expenditure or to depleted energy stores, hunger occurred and eating was initiated; as a meal progressed, newly available glucose was able to reduce the hunger signal. While theories such as this were highly influential, subsequent research has found them to be simplistic and limited, and it is now recognized that an intricate and highly complex control system integrates signals related to metabolism, energy expenditure, body fat, and environmental factors to control food intake. Most contemporary research has concentrated on the question “How much dowe eat ina given meal,or in agiven period oftime?” Over50years ago, Adolph (1947) pointed out that when we eat energetically diluted foods, a greater bulk of food is consumed. Conversely, we eat smaller meals when food is energetically rich. This simple observation implies that we eat to obtain a predetermined number of calories of food energy. In fact, we humans adjust our caloric intake with remarkable precision, with our intake under free feeding conditions matching our energy expenditure with an error of less than 1% over long intervals (Woods et al. 2000). The Control of Meals Energy is derived from three macronutrients: proteins, fat, and carbohy- drates. The carbohydrate glucose and various fatty acids provide energy to most tissues. The brain is unique, requiring a steady stream of glucose from (Box 7.1 continued) the blood in order to function. This reliance of the brain on glucose form- ed the basis of theglucostatic theory, and other theories over theyearshave focused on available fat or protein as being key to energy regulation. The premise underlying all of these hypotheses is that the level of some impor- tant commodity (glucose, fatty acids, total available energy to the brain or some other organ) waxes and wanes during the day. When the value gets low, indicating that some supply has become depleted, a signal is generated to eat; when the value is restored (repleted), a signal is generated to stop eating (Langhans 1996). While the logic of these “depletion-repletion” theories has considerable appeal, the bulk of evidence suggests that energy flux into the brain and other tissues is remarkably constant and that small fluctuations cannot account for the onset or offset of meals. What, then, determines when a meal will begin, especially when an individual could, in theory, eat whenever it chooses? The best evidence, at least for omnivores such as humans and rats, suggests that eating occurs at times that are convenient given other constraints in the environment, or at times that have resulted in successful eating in the past. We eat at partic- ular times because of established patterns, or because someone has prepared food for us, or because we have a break in our busy schedules (Woods et al. 1998). If depletion of some critical supply of energy provided an impetus dictating that we put other behaviors on hold until the supply is replen- ished, daily activity patterns would be much different. Instead, animals enjoy the luxury of eating when it is convenient, and they regulate their energy needs via controls over how much is eaten once a meal is initiated. Signals that Influence Intake Armed with the tools of contemporary genetics, molecular biology, and neuroscience, scientists have discovered literally dozens of signals over the past 20 years that either stimulate or inhibit food intake (Schwartz et al. 2000; Woods et al. 1998). As depicted in figure 7.1.1, these signals fit into three broad categories. The first are signals generated during meals as the ingested food interacts with receptors in the mouth, the stomach, and the intestines. Most of these signals are relayed to the brain via peripheral nerves (especially the vagus nerve) and provide information as to the qual- ity and quantity of what is being consumed. These are collectively called “satiety” signals because as their effect accumulates during a meal, they ultimately lead to the sensation of fullness or satiety in humans, and their (Box 7.1 continued) administration reduces meal size in animals including humans. As an ex- ample, mechanoreceptors in the stomach respond to distension, and this information is integrated with chemical signals generated in response to the content of the meal. The best-known satiety signal is the intestinal peptide cholecystokinin (CCK). CCK is secreted in proportion to ingested fat and carbohydrates, and it elicits secretions from the pancreas and liver to facilitate digestion. CCK also stimulates receptors on vagus nerve fibers. Figure 7.1.1. Schematic diagram of the signals that control caloric homeostasis. Satiety signals arising in the periphery, such as gastric distension and CCK, are relayed to the nucleus of the solitary tract (NTS) in the hindbrain. Leptin and insulin, the two circulating adiposity signals, enter the brain and interact with receptors in the arcuate nucleus (ARC) of the hypothalamus and other brain areas. These adiposity signals inhibit ARC neurons that synthesize NPY and AgRP (NPY cells in the diagram) and stimulate neurons that synthesize proopiomelanocortin (POMC), the precursor of α-MSH. These ARC neurons in turn project to other hypothalamic areas, including the paraventricular nuclei (PVN) and the lateral hypothalamic area (LHA). Catabolic signals from the PVN and anabolic signals from the LHA are thought to interact with the satiety signals in the hindbrain to determine when meals will end. (From Schwartz et al. 2000.) If individuals are administered an antagonist to CCK receptors prior to eating, they eat a larger meal, implying that endogenous CCK normally helps to limit meal size. Analogously, if CCK is administered prior to a meal, less food is eaten (Smith and Gibbs 1998). CCK is but one example of peptides secreted by the stomach and intestine during meals that act as satiety signals (table 7.1.1). (Box 7.1 continued) Table 7.1.1 A partial list of signals known to influence food intake Signals arising from peripheral organs Catabolic (satiety signals) Anabolic Leptin Ghrelin Insulin Amylin Cholecystokinin (CCK) Bombesin family (gastrin-releasing peptide or GRP, neuromedin B, bombesin) Glucagon Enterostatin Apolipoprotein AIV Somatostatin Peptide YY (PYY) Glucagon-like peptide 1 (GLP-1) Signals that act within the hypothalamus Catabolic Anabolic Leptin Neuropeptide Y (NPY) Insulin Galanin Amylin Corticosterone Corticotropin-releasing hormone (CRH) Cortisol Urocortin Dopamine Urocortin II Melanocyte-concentrating hormone (MCH) Neurotensin Orexins Oxytocin Ghrelin Serotonin Agouti-related peptide (AgRP) Histamine Beacon Glucagon-like peptide 1 (GLP-1) Cannabinoids Glucagon-like peptide 2 (GLP-2) β-Endorphin Tumor necrosing factor-α (TNF-α) Dynorphin Interleukin-6 (IL-6) Norepinephrine Interleukin-1 (IL-1) Amino acids Peptide YY (PYY) α-Melanocyte-stimulating hormone (α-MSH) Cocaine-amphetamine related transcript (CART) Prolactin-releasing hormone (PRL-RL) (Box 7.1 continued) 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 anti- cipated meal, and itslevelsfall precipitously once eating is initiated.Exoge- nously administered ghrelinstimulates eating, eveninindividuals 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 propor- tion tobody fat, eachenters thebrain from theblood, andreceptors 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 arcu- ate nucleus, individuals eat less food and lose weight in a dose-dependent manner. Likewise,ifthe activityofeither leptin orinsulin is reducedlocally 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 aregenerally partitionedintothose withanet anabolicactionand thosewith anetcatabolicaction. Whentheiractivity isstimulatedin thebrain,anabolic signalsincreasefoodintake, decreaseenergyexpenditure, andincreasebody 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 (Box 7.1 continued) 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; administeringexogenous NPY nearthe 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 leptinand insulin, but these neuronssynthesizea peptide called proopiomelanocorticotropin (POMC). POMC, in turn, can be pro- cessed to form anyof a large number ofactivecompounds. POMC neurons in the arcuate nucleus process the molecule into α-melanocyte-stimulating hormone (α-MSH), a potent catabolic signal (see fig. 7.1.2). Like NPY, 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 α-MSH are stimulated by the adiposity signals. NPY/AgRP neurons are inhibitory to the PVN and stimulatory to the LHA, whereas α-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. α-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 α-MSH causes its catabolic ac- tions 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 α-MSH at MC3 and MC4 receptors to reduce food intake and (Box 7.1 continued) body weight. At thesame time, elevated leptin and insulin inhibit arcu- ate 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 α-MSH) are but three of a long list of transmitters that influence the system (Schwartz et al. 2000; Woods et al. 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 thatidiosyncratic factors basedon convenience, environ- mental 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 if one 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 if one has lost weight), there is reduced sensitivity to satiety signals, and meals tendto be larger.Many other factors,ofcourse, interact withthis system. Forexample,seeing (or anticipating)a particularly palatabledessert 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 mustbe integrated with all other aspectsof 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 con- clusions above. Another important point that has recently come to light is that the sameintercellularas well as intracellularsignals 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 andhow recentlyananimal haseaten. Duringwinter,food inthe 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 (Emberizacitrinella) fill their crops withwheatbeforegoing to roost inearly winter (Evans1969).The arcticredpoll(Carduelishornemanni)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 asfat 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 [...]... 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. .. 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 (Hedenstr¨ m and Alerstam 19 97) Migrao tion can therefore be seen largely as a foraging enterprise, now and then... (Box 7. 2 continued) while in flight, put on substantial fuel stores during migration (Pilastro and Magnani 19 97) , 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... 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 (19 87) 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... 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... theoretically and empirically Pravosudov and Grubb (19 97) have reviewed energy regulation in wintering birds Witter and Cuthill (1993) have reviewed the costs of carrying fat in birds, noting especially that massdependent costs may be important Small birds should carry the smallest 239 240 Anders Brodin and Colin W Clark Figure 7. 3 Angle of ascent in relation to fat load (as a percentage of fat-free body... (Swanberg 1951; Tomback 1 977 ; Vander Wall 1988), and they depend on this stored 2 37 238 Anders Brodin and Colin W Clark 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... optimal (i.e., fitness-maximizing) time- and state-dependent behavioral strategies In the simplest cases, such models treat individual fitness Figure 7. 7 In a model by Brodin et al., animals of different rank experienced a period of food surplus (e.g., autumn) followed by a period of food scarcity (e.g., winter) The figure shows the ratio between optimal hoarding by a dominant animal, hD∗ , and optimal hoarding... McNamara and Houston and their co-workers have used dynamic state variable models to study various aspects of avian fat regulation during winter (McNamara and Houston 1990; Houston and McNamara 1993; Bednekoff and Houston 1994a, 1994b; McNamara et al 1994; Houston et al 19 97) These models have considered (1) optimal winter fat regulation strategies; (2) the sensitivity of overwinter survival, and of... Storage and Expenditure iteration would then be to calculate fitness for the penultimate day of winter, D − 1, when equation (7. 16A) would become F (x, D − 1) = max S(x,ε)E [F (x , D)] 0≤ε≤1 (7. 16B) On the right-hand side we have F(x , D), which is either 1 or 0 [eq (7. 15)], depending on the value of x We can calculate x from equation (7. 10), which gives the change in fat reserves over the day, and equation . Beacon Glucagon-like peptide 1 (GLP-1) Cannabinoids Glucagon-like peptide 2 (GLP-2) β-Endorphin Tumor necrosing factor-α (TNF-α) Dynorphin Interleukin-6 (IL-6) Norepinephrine Interleukin-1 (IL-1) Amino. acids Peptide YY (PYY) α-Melanocyte-stimulating hormone (α-MSH) Cocaine-amphetamine related transcript (CART) Prolactin-releasing hormone (PRL-RL) (Box 7. 1 continued) At least one stomach-produced signal. of its total time, and 66% of its total energy, is spent on foraging and resting (“stopovers”) before and between migratory flights (Hedenstr ¨ om and Alerstam 19 97) . Migra- tion can therefore