Robust Mathematical Models of Ecotoxicological Dynamics Subject to Stoichiometric Constraints

准确评估污染物的风险需要了解复杂的生态相互作用、元素循环以及自然压力源（如资源限制和污染物压力源）的相互作用。生态毒理学模型的发展极大地促进了我们对污染物如何影响生物和通过水生食物网循环的理解。然而，目前的模型没有考虑污染物压力源和元素约束的动态相互作用，如营养/光的可用性和食品质量。研究人员将结合考虑饮食营养价值和毒物负荷的数学模型设计并进行实验室实验。研究结果将产生知识并增进对环境和全球变化的理解。该项目将阐明营养物和化学污染物的循环，并最终改进毒理学风险评估方案，这将有利于环境管理人员和决策者。这些模型的用户友好版本将在该项目的网页上分发。研究生将接受数学和生态毒理学领域的跨学科培训，以获得对科学问题的广泛理解，这是跨学科有效沟通所必需的。调查人员和研究生将参与由德克萨斯理工大学STEM外展、研究和教育中心组织的K-12外展活动。生态化学计量学理论强调多种化学元素的平衡和生物体内基本元素的相对丰度，从而形成生态动态。研究人员将开发和分析在生态化学计量学框架下构建的一系列经验可检验和稳健的种群动态数学模型。在模型开发的同时，研究人员将整合来自文献和本研究中设计的新实验的数据，以便参数化、测试和改进模型。动力系统理论和工具将用于解释和分析模型，包括分析，计算和数值，以及分岔分析。模型和实验的综合将导致一个强大的理论框架的发展，适用于改善生态毒理学中的风险评估应用，其中包括化学计量限制对并发生态和毒理学过程的影响。

Accurately assessing the risks of contaminants requires knowledge of complex ecological interactions, elemental cycling, and the interactive effects of natural stressors, such as resource limitations and contaminant stressors. The development of ecotoxicological models have contributed significantly to our understanding of how contaminants impact organisms and cycle through aquatic food webs. However current models do not incorporate dynamical interactive effects of contaminant stressors and elemental constraints, such as nutrient/light availability and food quality. Investigators will design and conduct laboratory experiments in conjunction with mathematical models that account for both nutritional value of diet and toxicant load. The results will generate knowledge and enhance understandings of the environment and global change. The project will shed light on nutrient and chemical contaminant cycling and ultimately improve toxicological risk assessment protocols, which will be beneficial to environmental managers and policy decision makers. User-friendly versions of the models will be disseminated on the project's webpage. Graduate students will receive interdisciplinary training in the fields of mathematics and ecotoxicology to gain a broad understanding of scientific problems, necessary to communicate effectively across disciplines. Investigators and graduate students will be involved in K-12 outreach initiatives organized by the STEM Center for Outreach, Research, and Education at Texas Tech University.The theory of ecological stoichiometry emphasizes the balance of multiple chemical elements and the relative abundance of essential elements in organisms that shape ecological dynamics. Investigators will develop and analyze a series of empirically testable and robust mathematical models of population dynamics structured under the framework of ecological stoichiometry. In parallel to model development, investigators will integrate data from the literature and from new experiments designed in this research, in order to parameterize, test, and improve the models. Dynamical systems theory and tools will be used to interpret and analyze the models including analytical, computational and numerical, as well as bifurcation analysis. The synthesis of the models and experiments will result in the development of a robust theoretical framework appropriate for improved risk assessment applications in ecotoxicology that incorporate the effects of stoichiometric constraints on concurrent ecological and toxicological processes.