tamivoreii rodcntj tamivoreii rodcntj
pacing: and similar oral olher
I I unguis« I I primates pacing: and similar oral olher ol her
Figure 6.2.1. Taxonomic distribution of abnormal behaviors across four mammalian orders (carnivores, 61 species; rodents, 15 species; ungulates, 26 species; primates, 19 species). (From Mason et al. 2006.)
1. Ungulates cannot completely abandon foraging, even when it is redundant.
On farms and in zoos, ungulates are typically fed in a way that requires minimal foraging: homogeneous hay, browse, or artificial food—milled, low-fiber mash or pellets—is placed in a manger under their noses. It thus does not need to be searched for, it neither demands nor allows diet selection, and it often needs little chewing. Consequently, captive ungulates eat their daily rations in a fraction of the time it would take naturally. For instance, horses on pasture may graze for 16 hours a day, yet in stables, horses commonly consume all their food within 2 hours (Kiley-Worthington 1983); similar contrasts apply to all provisioned ungulates (reviewed in Bergeron et al. 2006). Several authors have therefore hypothesized that abnormal oral behaviors represent foraging behaviors that ungulates are unable or unwilling to abandon, despite their now being unnecessary for ingestion (e.g., reviewed Rushen et al. 1993). Evidence consistent with this hypothesis includes the observation that stalled pigs bar-chew for lengths of time similar to those they would naturally spend in grass chewing, rooting, and stone chewing if kept outside (Dailey and McGlone 1997). If correct, this idea raises new questions about what ungulates are defending (a minimum time spent in foraging behavior? a minimum number of bites per day?) and functional questions as to why. It could simply be that selection has not favored complete flexibility in foraging time. As this chapter shows, foraging time does generally decrease if intake rate goes up, but investigators obtained these findings in naturalistic conditions that may not extrapolate to the extreme intake rates that occur in captive situations. Alternatively, defending a certain minimum level of daily foraging could bring functional benefits independent of nutrient gain, such as information gain, preventing excessive tooth growth, or maintaining gut flora and other aspects of digestive function.
As this chapter shows, ungulate foraging involves thousands ofdaily bites that do more than break down food: they stimulate saliva production (100 or more liters per day in cattle), which helps buffer gastrointestinal acidity. Processed diets, however, take less chewing per unit time (Abijaoude et al. 2000), much less total foraging time per day, and overall, involve far fewer mouth movements. Could these reductions impair gut health by reducing salivation? Processed, low-fiber diets certainly cause gastrointestinal acidity—and even ulceration—in cattle, horses, and pigs (Blood and Ra-dostits 1989; Hibbard et al. 1995; Sauvant et al. 1999; Nicol 2000). The second hypothesized explanation for abnormal oral behaviors is thus that they are attempts to generate saliva to buffer gut acidity. Thus, horses' crib biting can be reduced by antacids and by antibiotics that control the gut's lactate-producing bacteria (Johnson et al. 1998; Nicol et al. 2001). Some oral behaviors are linked with gut health: tooth grinding and crib biting are associated with gastritis and ulcers in horses (Rebhun et al. 1982; Nicol et al. 2001), but tongue rolling and similar behaviors in calves correlate negatively with stomach lesions (Wiepkema et al. 1987; Canalietal. 2001). This idea raises several unanswered questions: How do ungulates monitor the pH oftheir digestive tracts, and does this vary with foraging niche? Do some or all ungulates monitor saliva production levels? Do abnormal oral behaviors effectively generate saliva, and does this help alleviate abnormal gut pH? Ifso, are these learned or innate responses—or does this vary with dietary niche?
3. Captive ungulates are deficient in nutrients and so stay motivated to forage.
Naturally, diet selection is the principal means of modulating gastrointestinal acidity; for example, ruminants respond to acidosis with increased fiber intake (Keunen et al. 2002). Herbivores also have excellent abilities to detect specific nutrient deficits and respond to them behaviorally (see section 6.4 and box 6.1). Yet, in captivity, humans constrain the quantities ungulates eat and the diets they can select. The last explanation for abnormal oral behaviors is therefore that they represent state-dependent foraging attempts driven by dietary deficiency. For example, simple energy deficits play a major role in pigs' oral stereotypies (e.g., Appleby and Lawrence 1987; Terlouw et al. 1991), while deficits of copper, manganese, or cobalt can induce tongue rolling in cattle (Sambraus 1985). It is unclear at the mechanistic level why such behaviors are then sustained, but evolutionarily, it may be that it is adaptive to search for food until successful. In some instances, however, the abnormal behavior is a "pica" (the ingestion of nonfood items) that may actually redress deficits, as has been argued for dirt eating by free-living horses (Blood and Radostits 1989; McGreevy et al. 2001). Thus, in captive ungulates, horses' wood chewing may be an adaptive response to a lack of dietary fiber (Redbo et al. 1998), and the chewing of urine-soaked wood slats by sheep a way of gaining nitrogenous urea when deficient in protein (e.g., Whybrow et al. 1995). Protein deficiency could also explain wool chewing by sheep, since the soiled wool from other animals' rear ends is preferred (Sambraus 1985). In these instances, we do not know whether foragers identify the required nutrients via specific taste receptors, or the extent to which associative learning about physiological consequences reinforces the behavior.
Overall, these three interlinked hypotheses ask fundamental research questions about which aspects of herbivore foraging are inherently "hardwired" and difficult to modify, which respond facultatively to state and circumstance, and how these design features relate to dietary niche. We can also see that abnormal oral behaviors reflect deficiencies. These may be nutritional deficiencies or a mismatch between the feeding methods imposed in the captive situation and the foraging mode that the free-living animal prefers. Some abnormal oral behaviors almost certainly indicate gastrointestinal discomfort, even pain. Addressing the questions they raise is thus ethically important as well as scientifically interesting.
The opposite occurs in some insects, in which the presence of conspecifics may lower host plant attractiveness. Feeding by conspecifics may reduce plant quality or induce plant defenses (e.g., see Raupp and Sadof 1991). Insects seldom gain the antipredator benefits of group foraging (except in cases of predator satiation), but they do pay the costs ofintraspecific competition and perhaps increased conspicuousness.
Like other animals, herbivores may alter their diets in the presence ofpre-dators or parasites. For example, Cosgrove and Niezen (2000) have shown that sheep infected with gastrointestinal parasites shift toward diets that contain higher proportions of protein than uninfected animals. Even the risk of predation or parasitism can cause such dietary shifts. Hutchings et al. (1998, 1999, 2001; Hutchings, Gordon et al. 2000; Hutchings, Kyriazakis et al. 2000) have shown that sheep may forage less selectively in response to differences in intake rate ifmore selective foraging also means a higher exposure to parasitic worm larvae. Abrams and Schmitz (1999) modeled the results of Rothley et al. (1997), who showed that the presence of a spider caused grasshoppers to shift their foraging effort from high-quality grasses to low-quality forbs. Smith et al. (2001) showed a similar result for herbivorous crane flies. Kie (1999) provides an excellent review of this trade-off in ungulates.
Herbivores face many other trade-offs. For example, Torres and Bozinovic (1997a) demonstrated a diet selection—thermoregulation trade-off in the degu (Octodon degus), a generalist herbivorous rodent from central Chile. Degus preferred low-fiber diets to high-fiber diets at 20°C, but were indifferent at 38°C, preferring to minimize their thermoregulatory risk rather than maximize their digestible energy intake.
Herbage quality may change during the day, creating another environmental constraint. The relative qualities of two plant species may change from dawn, when water-soluble carbohydrate concentrations are low, to dusk, when they are higher after a day of photosynthesis (e.g., Ciavarella et al. 2000). Orr et al. (1997) have shown that the dry matter, water-soluble carbohydrate, and starch content of grass and clover increase differentially over the course of the day (0730—1930), and that sheep bite rate and chewing rate decline while bite mass increases, apparently in response to the changes in the plants. Plant quality may vary over longer time scales as well. There are strong seasonal variations in both herbage quality and, of course, quantity; for example, Luo and Fox (1994) have nicely demonstrated seasonal shifts in the diet of the eastern chestnut mouse (Pseudomys gracilicaudatus). Many plant secondary metabolite concentrations vary seasonally, requiring animals to track these changes (e.g., Dearing 1996). Provenza (1995b; see box 5.2) reviewed the use of individual memory of the postingestive consequences ofnutrients and toxins to track temporal variation in plant secondary metabolite concentrations generally, and Duncan and Gordon (1999) reviewed the effects of these conflicting demands of intake rate maximization and toxin intake minimization on diet choice in larger herbivores.
Spatial distribution of the vegetation clearly influences diet selection. Indeed, many workers believe that this is the key difference between "diet preference" (diet choice when unconstrained by the environment) and "diet selection" (diet choice under environmental constraints; for more discussion, see Newman et al. 1992; Parsons, Newman et al. 1994). Here we are thinking not only about differences in encounter rates with each plant species (these are adequately considered in even the simplest diet choice models), but also about differences in the total, vertical, and horizontal abundance and distribution of herbage mass. To a grazing mammal, what does it mean to "take a bite ofperennial ryegrass"? Ryegrass may be finely interspersed with other plant species, it may occur higher or lower in the grazed horizon, it may be younger or older than other available bites, it may include reproductive stems, and so on. Many researchers have addressed these issues. Harvey et al. (2000) showed that sheep traded off diet preference and pasture height in a complex manner (fig. 6.2). Edwards et al. (1996a) used an artificial pellet system to test the influence ofspatial variation on sheep diets while keeping total food availability constant (see also Dumont et al. 2000). They found that the proportion ofthe preferred cereal pellet in the diet declined when its horizontal distribution (equivalent to fractional cover) declined, but only when the vertical abundance of cereal was low. They concluded that diet selection experiments that ignore how the food alternatives are distributed horizontally and vertically could be misunderstood. Although my examples here have been oflarge vertebrates, invertebrates also show responses to the spatial distribution of host plants that simple encounter rate considerations cannot explain.
The environment presents constraints enough, but, as discussed in chapter 5, herbivores must also deal with an array of physiological and morphological constraints. The classic physiological constraint is nutritional, as exemplified by the sodium constraint for browsing moose (see also Forchhammer and Boomsma 1995); protein provides another example (e.g., Tolkamp and Kyr-iazakis 1997; Berteaux et al. 1998). Belovsky's (1978) now classic paper spawned a cottage industry of linear programming models of herbivore behavior (e.g., Nolet et al. 1995; Randolph and Cameron 2001). Linear programming is a mathematical technique for solving an optimization problem subject to linear constraints. While this approach remains popular today, it has not been without controversy in the study of herbivory (e.g., Hobbs 1990; OwenSmith 1993, 1996, 1997). Hirakawa (1997a) has modeled digestive constraints using a more sophisticated nonlinear programming approach. Hirakawa shows that when foraging time is long or food is abundant, the digestive
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