Group Size, Scaling of Work, and Metabolism in Ant Colonies

每克能量消耗随体型增加而降低的模式（称为代谢缩放）在所有动物群体中都存在，但其背后的机制仍不清楚。有趣的是，群居昆虫群体随着群体规模的增加，代谢降低的程度是相同的。这个项目将结合实验和数学模型来确定蚁群中能源使用和工作组织之间的关系。蚁群可以作为这个问题的一个范例，因为它们高度协调的社会是围绕维持群体生长和维护所需的工作组织起来的，类似于生物体中的代谢过程。了解代谢缩放的机制在生理、医学和农业方面具有潜在的应用价值。该项目中基于能源的模型和实验将远远超出社会性昆虫群体，包括为人类人口规模问题提供信息。该项目将把这项研究与数学和社会生物学联合指导计划联系起来，共同培养生物学和数学方面的本科生研究团队。学生将参加有关社会生物学原理和模拟建模的正式培训项目，然后作为跨学科团队参与合作研究。与亚利桑那州立大学研究和少数族裔项目的现有联系将用于招募代表性不足的学生加入该项目。此外，还将与亚利桑那州立大学的ask -a- biology外展项目合作开发用于在线K-12课程的群体规模、社会行为和新陈代谢等教学模块。该项目由综合有机体系统学部动物行为项目、数学科学部数学生物学项目和生物、数学和物理科学交叉领域的BIOMAPS项目共同资助。群体规模是社会性最基本的属性之一，对社会组织和适合度有重要影响。先前的研究发现，较大的收获蚁群（加利福尼亚Pogonomyrmex californicus）在任务表现和活动模式上表现出异速变化，包括工人专业化程度的提高。它们还会转移工作的分配，可能会远离更昂贵的任务。可能与此相结合的是，菌落也显示出一致的低代谢缩放模式，这与有机缩放模式相匹配。由于任务绩效与群体的生长和新陈代谢直接相关，这些结果导致了一个假设，即更大的群体通过工作组织的规模变化实现了能源使用的规模经济。为了检查蜂群大小如何影响工作组织，将在不同大小的实验室蜂群中测量跨任务的工人分布、个人任务专业化和工人活动水平。将同时测量群体代谢、产卵量和生长率，以将行为组织与群体代谢后果联系起来。此外，将评估蜂群人口统计数据，包括工蚁规模和年龄分布，以了解它们对新陈代谢变化的贡献。这些参数将被测量：(a)菌落大小不同，但年龄不变；(b)个体遗传学上随时间变化的菌落大小；(c)大小操纵菌落。实证研究将结合模拟、微分方程和优化模型，探讨任务组织和活动的组成部分如何相互作用，以产生群体代谢和生产力的比例变化。

The pattern of lower energy use per gram with increasing size (known as metabolic scaling) occurs across all animal groups, yet the mechanisms behind it are still not understood. Intriguingly, social insect colonies show the same level of reduced metabolism with increasing colony size. This project will combine experiments and mathematical models to determine the relationships between energy use and the organization of work in ant colonies. Ant colonies serve as an exemplar for this question, because their highly coordinated societies are organized around the work needed to sustain colony growth and maintenance, analogous to metabolic processes in organisms. Understanding the mechanisms underlying metabolic scaling has potential applications in physiology, medicine, and agriculture. The energy-based models and experiments in this project will be relevant well beyond social insect colonies, including informing human population scaling issues. The project will connect this research with a Mathematics and Social Biology Co-mentoring Program, to train research teams of undergraduates together in biology and mathematics. Students will participate in a formal training program on social biological principles and simulation modeling, and then participate as cross-disciplinary teams in collaborative research. Existing connections with research and minority programs at ASU will be used to recruit under-represented students into the program. Teaching modules on group size, social behavior, and metabolism for online K-12 use will also be developed in collaboration with ASU's Ask-a-Biologist outreach program. This project is co-funded by the Animal Behavior program in the Division of Integrative Organismal Systems, the Mathematical Biology program in the Division of Mathematical Sciences, and the BIOMAPS program for proposals at the interface of Biology, Math and the Physical Sciences.Group size is one of the most fundamental attributes of sociality, with important effects on social organization and fitness. Previous work has found that larger harvester ant colonies (Pogonomyrmex californicus) exhibit allometric changes in task performance and activity patterns, including increased worker specialization. They additionally shift the allocation of effort, possibly away from more expensive tasks. Potentially coupled with this, colonies also show a consistent pattern of hypometric metabolic scaling, which matches that of organismal scaling patterns. Because task performance is directly linked to colony growth and metabolism, these results lead to the hypothesis that larger colonies achieve economies of scale in energy use from scaling changes in the organization of work. To examine how colony size influences work organization, the distribution of workers across tasks, individual task specialization, and worker activity levels will be measured in laboratory colonies of varying size. Colony metabolism, brood production and growth rates will be measured simultaneously to link behavioral organization to colony metabolic consequences. Additionally, colony demographics, including worker size and age distributions, will be assessed for their contributions to variation in metabolism. These parameters will be measured for: (a) colonies that vary in size but not age; (b) colonies changing in size ontogenetically over time; (c) size-manipulated colonies. The empirical research will be combined with simulation, differential equation and optimization models to ask how components of task organization and activity might interact to generate scaling changes in colony metabolism and productivity.