The Marginal Value Theorem (MVT) is the dominant paradigm in predicting patch use and numerous tests support its qualitative predictions. Quantitative tests under complex foraging situations could be expected to be more variable in their support because the MVT assumes behavior maximizes only net energy-intake rate. However across a survey of 26 studies, foragers rather consistently ''erred'' in staying too long in patches. Such a consistent direction to the errors suggests that the simplifying assumptions of the MVT introduce a systematic bias rather than just imprecision. Therefore, I simulated patch use as a statedependent response to physiological state, travel cost, predation risk, prey densities, and fitness currencies other than net-rate maximization (e.g., maximizing survival, reproductive investment, or mating opportunities). State-dependent behavior consistently results in longer patch residence times than predicted by the MVT or another foraging model, the minimize /g rule, and these rules fail to closely approximate the best behavioral strategy over a wide range of conditions. Because patch residence times increase with state-dependent behavior, this also predicts mass regulation below maximum energy capacities without direct mass-specific costs. Finally, qualitative behavioral predictions from the MVT about giving-up densities in patches and the effects of travel costs are often inconsistent with state-dependent behavior. Thus in order to accurately predict patch exploitation patterns, the model highlights the need to: (1) consider predator behavior (sit-and-wait versus actively foraging); (2) identify activities that can occur simultaneously to foraging (i.e., mate search or parental care); and (3) specify the range of nutritional states likely in foraging animals. Future predictive models of patch use should explicitly consider these parameters. Key words: marginal value theorem, predation risk, foraging, patch use, stochastic dynamic programming, state-dependent behavior. [Behav Ecol 12:71-83 (2001)] O ptimal foraging theory is an important tool for increasing our understanding of animal behavior. One optimality model that has been particularly widely used is the Marginal Value Theorem (MVT), which predicts the behavior of foraging animals collecting energy within patches. Patch depletion will eventually force the animal to move. If the animal's goal is to maximize net rate of energy intake, it should leave a patch when its foraging rate drops to the overall average intake for the entire habitat (Charnov, 1976). The MVT further predicts that if an animal encounters a series of patches of varying quality, it should bias its foraging efforts such that eventually all patches are depleted to an equal prey density. The prey density at which a forager leaves a patch is known as the giving-up density, or GUD, and therefore optimal foraging should result in all exploited patches having similar GUDs.The MVT has been extensively applied and tested. Many studies have shown good qualitative support for M...
Although theories of parental investment and sex ratio generally assume that a single resource limits reproduction, many organisms invest two or more qualitatively different types of resources in the production of offspring. We examine the consequences of multifaceted parental investment for offspring provisioning and sex allocation, building our argument around a study of the nest-building Hymenoptera (wasps, bees, and ants). We review empirical studies that demonstrate that lifetime reproductive success may be constrained not only by resources used to provision offspring but also by the supply of mature oocytes or, in some cases, by the availability of space within nest sites or the time required to defend nests. Under multifaceted parental investment, the factor limiting parental fitness determines the currency of the optimization problem; parents are predicted to adjust reproductive behavior to maximize fitness returns per unit of the limiting resource. We develop simple models that predict that a greater availability of resources used for provisions will lead to an increase in the amount provisioned per offspring and an increase in the numerical or biomass proportion of females produced. These predictions explain widely observed patterns of variation in offspring provisioning and sex allocation in the nest-building Hymenoptera.
Many studies have shown that predation risk affects foraging behavior, but quantitative predictions are rare because of the lack of a common currency for energy intake and mortality. This problem is soluble in ants. We gave 12 Lasius pallitarsis colonies the choice between foraging in two patches that differed both in food quality and in associated mortality risk. We independently measured the growth that colonies could achieve on the diets offered in those patches. With no risk at either patch, colonies always preferred the higher food quality patch. When mortality risk (a large Formica subnuda ant) was associated with the trail to the higher food quality patch, the use of that patch depended on the magnitude of the growth differential between feeding in risky or safe patches: the greater the benefit of feeding in the risky patch, the greater was its relative usage. Colonies valued risky patches equally to safe patches at the point where forager mortality rates were approximately offset by colony growth gain. This ability to reduce mortality risk while foraging may be a factor that favors insect sociality, in general.
A major evolutionary question is how reproductive sharing arises in cooperatively breeding species despite the inherent reproductive conflicts in social groups. Reproductive skew theory offers one potential solution: each group member gains or is allotted inclusive fitness equal to or exceeding their expectation from reproducing on their own. Unfortunately, a multitude of skew models with conflicting predictions has led to confusion in both testing and evaluating skew theory. The confusion arises partly because one set of models (the 'transactional' type) answer the ultimate evolutionary question of what ranges of reproductive skew can yield fitness-enhancing solutions for all group members. The second set of models ('compromise') give an evolutionarily proximate, game-theoretic evolutionarily stable state (ESS) solution that determines reproductive shares based on relative competitive abilities. However, several predictions arising from compromise models require a linear payoff to increased competition and do not hold with non-linear payoffs. Given that for most species it may be very difficult or impossible to determine the true relationship between effort devoted to competition and reproductive share gained, compromise models are much less predictive than previously appreciated. Almost all skew models make one quantitative prediction (e.g. realized skew must fall within ranges predicted by transactional models), and two qualitative predictions (e.g. variation in relatedness or competitive ability across groups affects skew). A thorough review of the data finds that these three predictions are relatively rarely supported. As a general rule, therefore, the evolution of cooperative breeding appears not to be dependent on the ability of group members to monitor relatedness or competitive ability in order to adjust their behaviour dynamically to gain reproductive share. Although reproductive skew theory fails to predict within-group dynamics consistently, it does better at predicting quantitative differences in skew across populations or species. This suggests that kin selection can play a significant role in the evolution of sociality. To advance our understanding of reproductive skew will require focusing on a broader array of factors, such as the frequency of mistaken identity, delayed fitness payoffs, and selection pressures arising from across-group competition. We furthermore suggest a novel approach to investigate the sharing of reproduction that focuses on the underlying genetics of skew. A quantitative genetics approach allows the partitioning of variance in reproductive share itself or that of traits closely associated with skew into genetic and non-genetic sources. Thus, we can determine the heritability of reproductive share and infer whether it actually is the focus of natural selection. We view the 'animal model' as the most promising empirical method where the genetics of reproductive share can be directly analyzed in wild populations. In the quest to assess whether skew theory can provide a framewor...
Recent evolutionary models of reproductive partitioning within animal societies (known as`optimal skew',`concessions' or`transactional' models) predict that a dominant individual will often yield some fraction of the group's reproduction to a subordinate as an incentive to stay in the group and help rear the dominant's o¡spring. These models quantitatively predict how the magnitude of the subordinate's`staying incentive' will vary with the genetic relatedness between dominant and subordinate, the overall expected group output and the subordinate's expected output if it breeds solitarily. We report that these predictions accord remarkably well with the observed reproductive partitioning between conesting dominant and subordinate queens in the social paper wasp Polistes fuscatus. In particular, the theory correctly predicts that (i) the dominant's share of reproduction, i.e. the skew, increases as the colony cycle progresses and (ii) the skew is positively associated both with the colony's productivity and with the relatedness between dominant and subordinate. Moreover, aggression between foundresses positively correlated with the skew, as predicted by transactional but not alternative tug-of-war models of societal evolution. Thus, our results provide the strongest quantitative support yet for a unifying model of social evolution.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2023 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.