Dataset Information

Evolving nutritional strategies in the presence of competition: a geometric agent-based model.

ABSTRACT: Access to nutrients is a key factor governing development, reproduction and ultimately fitness. Within social groups, contest-competition can fundamentally affect nutrient access, potentially leading to reproductive asymmetry among individuals. Previously, agent-based models have been combined with the Geometric Framework of nutrition to provide insight into how nutrition and social interactions affect one another. Here, we expand this modelling approach by incorporating evolutionary algorithms to explore how contest-competition over nutrient acquisition might affect the evolution of animal nutritional strategies. Specifically, we model tolerance of nutrient excesses and deficits when ingesting nutritionally imbalanced foods, which we term 'nutritional latitude'; a higher degree of nutritional latitude constitutes a higher tolerance of nutritional excess and deficit. Our results indicate that a transition between two alternative strategies occurs at moderate to high levels of competition. When competition is low, individuals display a low level of nutritional latitude and regularly switch foods in search of an optimum. When food is scarce and contest-competition is intense, high nutritional latitude appears optimal, and individuals continue to consume an imbalanced food for longer periods before attempting to switch to an alternative. However, the relative balance of nutrients within available foods also strongly influences at what levels of competition, if any, transitions between these two strategies occur. Our models imply that competition combined with reproductive skew in social groups can play a role in the evolution of diet breadth. We discuss how the integration of agent-based, nutritional and evolutionary modelling may be applied in future studies to further understand the evolution of nutritional strategies across social and ecological contexts.

SUBMITTER: Senior AM

PROVIDER: S-EPMC4376532 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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Evolving nutritional strategies in the presence of competition: a geometric agent-based model.

Senior Alistair M AM Charleston Michael A MA Lihoreau Mathieu M Buhl Camille C Raubenheimer David D Simpson Stephen J SJ

PLoS computational biology 20150327 3

Access to nutrients is a key factor governing development, reproduction and ultimately fitness. Within social groups, contest-competition can fundamentally affect nutrient access, potentially leading to reproductive asymmetry among individuals. Previously, agent-based models have been combined with the Geometric Framework of nutrition to provide insight into how nutrition and social interactions affect one another. Here, we expand this modelling approach by incorporating evolutionary algorithms ...[more]

PMID: 25815976

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Project description:Competitive bodybuilders employ a combination of resistance training, cardiovascular exercise, calorie reduction, supplementation regimes and peaking strategies in order to lose fat mass and maintain fat free mass. Although recommendations exist for contest preparation, applied research is limited and data on the contest preparation regimes of bodybuilders are restricted to case studies or small cohorts. Moreover, the influence of different nutritional strategies on competitive outcome is unknown.Fifty-one competitors (35 male and 16 female) volunteered to take part in this project. The British Natural Bodybuilding Federation (BNBF) runs an annual national competition for high level bodybuilders; competitors must qualify by winning at a qualifying events or may be invited at the judge's discretion. Competitors are subject to stringent drug testing and have to undergo a polygraph test. Study of this cohort provides an opportunity to examine the dietary practices of high level natural bodybuilders. We report the results of a cross-sectional study of bodybuilders competing at the BNBF finals. Volunteers completed a 34-item questionnaire assessing diet at three time points. At each time point participants recorded food intake over a 24-h period in grams and/or portions. Competitors were categorised according to contest placing. A "placed" competitor finished in the top 5, and a "Non-placed" (DNP) competitor finished outside the top 5. Nutrient analysis was performed using Nutritics software. Repeated measures ANOVA and effect sizes (Cohen's d) were used to test if nutrient intake changed over time and if placing was associated with intake.Mean preparation time for a competitor was 22?±?9 weeks. Nutrient intake of bodybuilders reflected a high-protein, high-carbohydrate, low-fat diet. Total carbohydrate, protein and fat intakes decreased over time in both male and female cohorts (P <?0.05). Placed male competitors had a greater carbohydrate intake at the start of contest preparation (5.1 vs 3.7 g/kg BW) than DNP competitors (d =?1.02, 95% CI [0.22, 1.80]).Greater carbohydrate intake in the placed competitors could theoretically have contributed towards greater maintenance of muscle mass during competition preparation compared to DNP competitors. These findings require corroboration, but will likely be of interest to bodybuilders and coaches.

Project description:BackgroundTo prepare for competition, bodybuilders employ strategies based around: energy restriction, resistance training, cardiovascular exercise, isometric "posing", and supplementation. Cohorts of professional (PRO) natural bodybuilders offer insights into how these strategies are implemented by elite competitors, and are undocumented in the scientific literature.MethodsForty-seven competitors (33 male (8 PRO, 25 amateur (AMA), 14 female (5 PRO, 9 AMA) participated in the study. All PROs were eligible to compete with the Drug Free Athletes Coalition (DFAC), and all AMAs were recruited from the British Natural Bodybuilding Federation (BNBF). Competitors in these organisations are subject to a polygraph and are drug tested in accordance with the World Anti-Doping Agency. We report the results of a cross-sectional study of drug free bodybuilders competing at BNBF qualifying events, and the DFAC and World Natural Bodybuilding Federation finals. Participants completed a 34-item questionnaire assessing dietary intake at three time points (start, middle and end) of competition preparation. Participants recorded their food intake over a 24-h period in grams and/or portions. Dietary intakes of PRO and AMA competitors were then compared. Repeated measures ANOVA was used to test if nutrient intake changed over time, and for associations with division.ResultsMale PROs reported significantly (p < 0.05) more bodybuilding experience than AMAs (PRO: 12.3 +/- 9.2, AMA: 2.4 +/- 1.4 yrs). Male PROs lost less body mass per week (PRO: 0.5 +/- 0.1, AMA: 0.7 +/- 0.2%, p < 0.05), and reported more weeks dieting (PRO: 28.1 +/- 8.1, AMA: 21.0 +/- 9.4 wks, P = 0.06). Significant differences (p < 0.05) of carbohydrate and energy were also recorded, as well as a difference (p = 0.03) in the estimated energy deficit (EED), between male PRO (2.0 +/- 5.5 kcal) and AMA (- 3.4 +/- 5.5 kcal) competitors.ConclusionsLonger diets and slower weight loss utilized by PROs likely contributed towards a lower EED compared to the AMAs. Slower weight loss may constitute an effective strategy for maintaining energy availability and muscle mass during an energy deficit. These findings require corroboration, but will interest bodybuilders and coaches.

Project description:A large literature has accumulated suggesting that human and animal decision making is driven by at least two systems, and that important functions of these systems can be captured by reinforcement learning algorithms. The "model-free" system caches and uses stimulus-value or stimulus-response associations, and the "model-based" system implements more flexible planning using a model of the world. However, it is not clear how the two systems interact during deliberation and how a single decision emerges from this process, especially when they disagree. Most previous work has assumed that while the systems operate in parallel, they do so independently, and they combine linearly to influence decisions. Using an integrated reinforcement learning/drift-diffusion model, we tested the hypothesis that the two systems interact in a non-linear fashion similar to other situations with cognitive conflict. We differentiated two forms of conflict: action conflict, a binary state representing whether the systems disagreed on the best action, and value conflict, a continuous measure of the extent to which the two systems disagreed on the difference in value between the available options. We found that decisions with greater value conflict were characterized by reduced model-based control and increased caution both with and without action conflict. Action conflict itself (the binary state) acted in the opposite direction, although its effects were less prominent. We also found that between-system conflict was highly correlated with within-system conflict, and although it is less clear a priori why the latter might influence the strength of each system above its standard linear contribution, we could not rule it out. Our work highlights the importance of non-linear conflict effects, and provides new constraints for more detailed process models of decision making. It also presents new avenues to explore with relation to disorders of compulsivity, where an imbalance between systems has been implicated.

Dataset Information

Evolving nutritional strategies in the presence of competition: a geometric agent-based model.

Publications

Evolving nutritional strategies in the presence of competition: a geometric agent-based model.

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