of such interactions involves diet: eating and being eaten. Understanding the drivers of food and diet selection is thus fundamentally important in ecology, but it is also potentially very complex. To begin with, animals need, and foods contain many nutrients and other components such as indigestible fiber and toxins, and their requirements and tolerances for each vary – for example with age, health, reproductive state, and activity levels. Further, nutrients do not act independently but interact in complex ways, such that the levels in the diet of some influence the effects of others, and therefore their ratios (i.e. balance) can be as, or more important than the individual amounts and concentrations in the diet. Such interactions can involve several nutrients. For example, calcium balance is influenced by dietary phosphorus, vitamin D, and some carbohydrates, such as lactose [17]. To further complicate things, for almost all species, very few, if any, foods contain all the required nutrients in the right ratios to satisfy nutrient requirements and even if they did, no food (with the exception perhaps of mammalian milk) changes its composition to oblige the changing nutrient needs of its consumer. Animals therefore need to combine several, often many, different foods in their diets in the right proportions to satisfy their complex and dynamic nutrient needs. And these are just a few of the complexities that nutrition entails.
In the 1990s, there were three dominant frameworks for understanding the role of diet in ecology, all of which were founded on highly simplified models of nutrition [18]. Two of these, Optimal Foraging Theory and Classical Nutritional Ecology, assumed that animals in the wild are disproportionately influenced by a single dietary component, energy, and protein, respectively, without regard for nuances such as those discussed above. The third framework, ecological stoichiometry, does emphasize the importance of dietary ratios, but makes the simplifying assumption that all nutrients can be represented by chemical elements – principally carbon, nitrogen, and phosphorus. By avoiding the complexities of nutrition, these frameworks enabled diet to be integrated into ecological theory and, in this respect, have made important contributions. However, there was no telling what had been lost to ecological theory by omitting essential features of nutrition not captured by these simplified frameworks. At the other end of the complexity spectrum, the applied and mechanistic nutritional sciences were amassing substantial detail about the chemistry and physiology of nutrition, with little attempt to integrate this detail into theory or draw on theory to synthesize and apply the information [13].
Against this background, the question arose what is “enough but not too much” nutritional complexity for ecological models? The most direct way to answer this is through discovering how animals themselves deal with the complexity of nutrition. There are, in theory, benefits from regulating the dietary intake of all nutrients with great precision, but there are also constraints and costs [19]. For example, the computational machinery required to solve such a high‐dimensional optimization problem is immense, and brains cannot be dedicated to nutrition alone. Even if they could perform the required integration beyond a certain level of dietary perfectionism, the gains from foraging will run into diminishing returns, and time would be better spent on other activities, such as predator avoidance, mating, and sheltering. On the other hand, animals that are too cavalier in their nutritional regulation will be driven to extinction. For these reasons, we might expect animal nutrition to achieve a balance between complexity and simplicity, and identifying that balance will inform the appropriate level of nutritional complexity to incorporate into ecological models.
Laboratory studies of animals
A strategic research approach for addressing this question is to start simple and see how well the animal’s feeding responses can be understood, predicted, and manipulated within the rarefied experimental environment. This was initially done in studies with insects, using synthetic foods formulated to differ systematically in specific nutritional dimensions while holding all others constant. An analytical framework called Nutritional Geometry was invented to disentangle the individual and interactive roles of the different nutrients in dietary regulation [1,2,13,20] (Fig. 6.1).
An important question that could be solved using Nutritional Geometry is whether energy really does drive animal foraging as assumed in Optimal Foraging Theory, whether protein does, as assumed by Classical Nutritional Ecology, or whether the situation is more complex than this, and if so, how [21]. In the early experiments, the nutritional dimensions varied were dietary energy density (the ratio of macronutrients to indigestible fiber) and the ratio of the macronutrients themselves (specifically, the protein:carbohydrate ratio, because fat is not an energetic macronutrient for the herbivorous insects in the studies). Results showed that neither energy nor protein alone could explain insect foraging – in all cases, the insects distinguished the different sources of energy (protein and carbohydrate) and spread their feeding across available foods in ways that provided specific amounts and ratios of the two nutrients. When the combinations of foods provided were changed, the insects maintained the same nutritional intake by changing the relative amounts of the new foods that were eaten [22]. In one study, cockroaches were manipulated into one of three nutritional states through providing access to a single food with high, low or intermediate protein:carbohydrate ratio and thereafter allowed to mix an intake from all three foods [23] (Fig. 6.2a). The three groups initially selected very different combinations of the available foods, favoring the food that provided the nutrient of which they were previously deprived. Remarkably, when the three groups converged on a common cumulative nutrient intake (i.e. had redressed their respective nutritional imbalances), they subsequently selected similar food combinations to maintain the balance of macronutrients on which they had converged.
Figure 6.1 Basic concepts in the Nutritional Geometry framework. (a) Dietary balance. The “intake target” represents the amount and balance of nutrients that are targeted by the animal’s regulatory systems, in this case, protein vs. fat and carbohydrate combined (non‐protein energy, NPE). Foods are represented as lines, called “nutritional rails,” which originate at the origin and project into the graph at an angle determined by the ratio of the nutrients that each contains. As the animal eats, it ingests the nutrients in the same proportion as the food it is eating, and its nutritional state thus changes along the same trajectory as the rail for that food (shown by dashed arrows). The animal can therefore reach its intake target either by selecting food that has the same ratio of nutrients as the intake target (i.e. a nutritionally balanced food) (food 1) or by switching (s1 and s2) between foods that are imbalanced but nutritionally complementary (foods 2 and 3). (b) When confined to a single nutritionally imbalanced food (i.e. with a rail that doesn’t intersect the intake target), the animal is confronted by a trade‐off between over‐ingesting one nutrient and under‐ingesting the other. By feeding to the green point, it meets its target for NPE but suffers a shortage of protein of magnitude green P‐. The converse is true if the animal feeds to the blue point – it would meet its protein target but ingest an excess of NPE (blue NPE+). At the red point, it would meet its target for neither nutrient but ingest a moderate excess of NPE and moderate deficit of P. (c) Experimental protocol for testing how the animal resolves the trade‐off between over‐ and under‐ingesting nutrients when confined to imbalanced foods. Experimental groups are each assigned one of several foods differing in the ratio of the nutrients, and the shape of the resulting array of intake points reveals the regulatory strategy. Three possibilities are illustrated: the blue symbols represent prioritization of protein (i.e. feeding to the target coordinate for protein regardless of whether this involves over‐ or under‐eating NPE), the green symbols represent NPE prioritization, and the red symbols represent an intermediate response in which the regulatory systems assign an equal weighting to excesses and deficits of the two nutrients. Many other configurations are possible.
