Can optimal energy allocation in bioenergetic models improve predictions?

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All organisms consume energy via food and use that energy for daily processes, including growth, reproduction, and body maintenance. Scientists commonly use energy budget models to describe and predict the flow of this energy through individual organisms. Existing model use unrealistic assumptions about the partitioning of energy to different processes, and as a result, they often make inaccurate predictions. This research will modify this standard modeling approach to incorporate optimal energy partitioning, assuming that organisms evolve to partition energy resources in a way that maximizes their future survival and reproduction. Predictions using this new way of modeling will then be compared to predictions from the standard modeling approach, and both will be used to predict how animals should allocate energy after an injury. The Asian shore crab, a species that has invaded rocky shores along the US east coast from North Carolina to Maine, will be used as a model organism to test the hypothesis that this new optimal modeling approach provides better predictions than the standard approach. Energy partitioning will be examined through field and laboratory studies in crabs that have lost one or more limbs. The research will also provide early scientific training to junior high and high school students from underrepresented backgrounds by involving students from an existing summer program in making predictions using the models, and then testing these predictions using data collected in the field.Existing bioenergetic models generally assume fixed energy allocation strategies, and consequently yield predictions that are often inaccurate. This research uses optimal energy allocation in a 4-step process to improve bioenergetic modeling, with a focus on studying energy allocation following nonlethal injury in the invasive Asian shore crab Hemigrapsus sanguineus. The first step is to develop a bioenergetics model that includes injury. The second step is to measure condition-dependent metabolic rates needed to complete the parameterization of the bioenergetics model. The third step uses the bioenergetic model within dynamic state variable modeling framework to identify the optimal energy allocation strategy of injured crabs as a function of crab age, body condition, injury status, reproductive status, and time of the year relative to the reproductive season. The fourth step is empirically testing model predictions to determine whether a model that includes an optimal energy allocation strategy performs better than a null model with a fixed energy allocation strategy. The proposed work will improve our understanding of the energetic responses to nonlethal injury, will provide a general theoretical framework for understanding when injury recovery should be prioritized, and will demonstrate a modeling strategy that can predict and clarify context-dependent tradeoffs in energy allocation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.