Optimal foraging when regulating intake of multiple nutrients

There is growing evidence that, rather than maximizing energy intake subject to constraints, many animals attempt to regulate intake of multiple nutrients independently. In the complex diets of animals such as herbivores, the consumption of nutritionally imbalanced foods is sometimes inevitable, forcing trade-offs between eating too much of nutrients present in the foods in relative excess against too little of those in deficit. Such situations are not adequately represented in existing formulations of foraging theory. Here we provide the necessary theory to fit this case, using an approach that combines state-space models of nutrition with Tilman's models of resource exploitation (Tilman 1982, Resource Competition and Community Structure, Princeton: Princeton University Press). Our approach was to construct a smooth fitness landscape over nutrient space, centred on a 'target' intake at which no fitness cost is incurred, and this leads to a natural classification of the simple possible fitness landscapes based on Taylor series approximations of landscape shape. We next examined how needs for multiple nutrients can be assessed experimentally using direct measures of animal performance as the common currency, so that the nutritional strategies of animals can be mapped on to the performance surface, including the position of regulated points of intake and points of nutrient balance when fed suboptimal foods. We surveyed published data and conducted an experiment to map out the performance landscape of a generalist leaf-feeding caterpillar, Spodoptera littoralis. (C) 2004 Tire Association for the Study of Animal Behaviour. Poblished by Elsevier Ltd. All rights reserved.

Using an individual-based model to select among alternative foraging strategies of woodpigeons: data support a memory-based model with a flocking mechanism

Population modelling is increasingly recognised as a useful tool for pesticide risk assessment. For vertebrates that may ingest pesticides with their food, such as woodpigeon (Columba palumbus), population models that simulate foraging behaviour explicitly can help predicting both exposure and population-level impact. Optimal foraging theory is often assumed to explain the individual-level decisions driving distributions of individuals in the field, but it may not adequately predict spatial and temporal characteristics of woodpigeon foraging because of the woodpigeons’ excellent memory, ability to fly long distances, and distinctive flocking behaviour. Here we present an individual-based model (IBM) of the woodpigeon. We used the model to predict distributions of foraging woodpigeons that use one of six alternative foraging strategies: optimal foraging, memory-based foraging and random foraging, each with or without flocking mechanisms. We used pattern-oriented modelling to determine which of the foraging strategies is best able to reproduce observed data patterns. Data used for model evaluation were gathered during a long-term woodpigeon study conducted between 1961 and 2004 and a radiotracking study conducted in 2003 and 2004, both in the UK, and are summarised here as three complex patterns: the distributions of foraging birds between vegetation types during the year, the number of fields visited daily by individuals, and the proportion of fields revisited by them on subsequent days. The model with a memory-based foraging strategy and a flocking mechanism was the only one to reproduce these three data patterns, and the optimal foraging model produced poor matches to all of them. The random foraging strategy reproduced two of the three patterns but was not able to guarantee population persistence. We conclude that with the memory-based foraging strategy including a flocking mechanism our model is realistic enough to estimate the potential exposure of woodpigeons to pesticides. We discuss how exposure can be linked to our model, and how the model could be used for risk assessment of pesticides, for example predicting exposure and effects in heterogeneous landscapes planted seasonally with a variety of crops, while accounting for differences in land use between landscapes.

Biased oviposition and biased survival together help resolve a fig-wasp conflict

We report evidence that helps resolve two competing explanations for stability in the mutualism between Ficus racemosa fig trees and the Ceratosolen fusciceps wasps that pollinate them. The wasps lay eggs in the tree's ovules, with each wasp larva developing at the expense of a fig seed. Upon maturity, the female wasps collect pollen and disperse to a new tree, continuing the cycle. Fig fitness is increased by producing both seeds and female wasps, whereas short-term wasp fitness increases only with more wasps, thereby resulting in a conflict of interests. We show experimentally that wasps exploit the inner layers of ovules first (the biased oviposition explanation), which is consistent with optimal-foraging theory. As oviposition increases, seeds in the middle layer are replaced on a one-to-one basis by pollinator offspring, which is also consistent with biased oviposition. Finally, in the outer layer of ovules, seeds disappear but are only partially replaced by pollinator offspring, which suggests high wasp mortality (the biased survival or ‘unbeatable seeds’ explanation). Our results therefore suggest that both biased oviposition and biased survival ensure seed production, thereby stabilizing the mutualism. We further argue that biased oviposition can maintain biased survival by selecting against wasp traits to overcome fig defenses. Finally, we report evidence suggesting that F. racemosa balances seed and wasp production at the level of the tree. Because figs are probably selected to allocate equally to male and female function, a 1:1 seed:wasp ratio suggests that fig trees are in control of the mutualism.