Conference: Advances in Mathematical Ecology

会议：数学生态学进展

• 批准号: 2304988
• 负责人: Sabrina Streipert
• 金额: $ 2.18万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2304988&HistoricalAwards=false
• 关键词: Conference; Advances; Mathematical; Ecology

This award will support a workshop on June 2-3, 2023, at the University of Pittsburgh (https://www.mathematics.pitt.edu/eco23). The workshop will provide an opportunity for junior researchers, including graduate and undergraduate students, postdocs, early career faculty, as well as experienced mathematicians and biologists to learn innovative research practices on advances in mathematical ecology. Particularly, the workshop will be an interdisciplinary event that brings together researchers from Mathematics and Ecology to discuss the effects of ecological factors such as changes in environmental conditions on species adaptation, migration, and coexistence. These topics will be addressed via talks and poster presentations based on experimental data, modeling approaches, and theoretical and computational mathematics. As such, the workshop will promote connections across areas of mathematics and facilitate the exchange of ideas between mathematics and other areas such as ecology, natural resource management, evolutionary biology, and computer science. The workshop includes activities for broadening participation of the underrepresented groups and promoting equity and inclusion in the mathematical sciences. Specifically, participants are selected to promote equity and diversity across participants and include researchers and trainees from a diverse pool of career stages, both from local and nationwide institutions. With the speaker's consent, slides and recordings from conference talks will be posted on the conference webpage to achieve an even broader dissemination of results and impact. All participants will be encouraged to submit their work to the Journal of Biological Systems, an open-access platform, which agreed to feature a special issue dedicated to this workshop.The workshop “Advances in Mathematical Ecology” aims to increase the research activities and interdisciplinary collaborations between researchers from mathematics, ecology, natural resource management, evolutionary biology, and computer science. Although the mathematical analysis of ecological models often neglects environmental variability to aid in the attainment of analytical results, experimental data suggests that ecologically important traits can evolve rapidly in response to environmental changes/variability. This may affect species fitness, persistence, migration, and immune systems and highlights the need to incorporate environmental fluctuations into efforts to predict how species will respond to such environmental factors. Indeed, understanding how species respond to changing environments is fundamental for the sustainable management of species and their ecosystems. The workshop will highlight the impact of environmental changes as measured from experimental and analyzed data, techniques for the implementation of environmental fluctuations in ecological and eco-evolutionary models, and methods to study the effects thereof on how species evolve over time. The specific workshop topics will include: i) Methods of implementing environmental fluctuations in spatio-temporal ecological models with a comparison of seasonal forced model parameters and models including probabilistic parameters. ii) The potential and limitations of data-driven models in ecology, and their alignment with theoretical models. iii) Experimentally observed and model-predicted effects of environmental changes on the dispersal of species, on the interaction across species, and on how species respond to diseases. These topics involve links across the areas of Mathematical Modeling, Ecology, Evolution, Nonlinear Dynamical Systems, Stochastic Dynamics, Nonlinear Partial Differential Equations, Calculus of Variations, and Statistics.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.

该奖项将支持2023年6月2日至3日在匹兹堡大学(https://www.mathematics.pitt.edu/eco23).)举行的研讨会工作坊将为初级研究人员，包括研究生和本科生、博士后、早期职业教师以及经验丰富的数学家和生物学家提供机会，学习关于数学生态学进展的创新研究实践。特别是，研讨会将是一个跨学科的活动，聚集了来自数学和生态学的研究人员，讨论生态因素，如环境条件的变化对物种适应、迁徙和共存的影响。这些主题将通过基于实验数据、建模方法以及理论和计算数学的演讲和海报演示来解决。因此，工作坊将促进数学领域之间的联系，并促进数学与其他领域如生态学、自然资源管理、进化生物学和计算机科学之间的思想交流。讲习班包括扩大代表不足群体的参与和促进数学科学中的公平和包容性的活动。具体来说，选择参与者是为了促进参与者之间的公平和多样性，并包括来自不同职业阶段的研究人员和受训人员，包括来自地方和全国机构的人员。经发言者同意，会议发言的幻灯片和录音将张贴在会议网页上，以实现更广泛的成果和影响的传播。所有参与者将被鼓励将他们的工作提交到开放获取平台《生物系统杂志》上，该杂志同意为这个工作坊专门制作一期特刊。研讨会的目的是增加来自数学、生态学、自然资源管理、进化生物学和计算机科学的研究人员之间的研究活动和跨学科合作。虽然生态模型的数学分析经常忽略环境的变异性，以帮助获得分析结果，但实验数据表明，生态上重要的特征可以随着环境的变化/变异性而迅速进化。这可能会影响物种的适合性、持久性、迁徙和免疫系统，并突显出需要将环境波动纳入预测物种将如何对这些环境因素做出反应的努力中。事实上，了解物种如何对不断变化的环境做出反应，对于物种及其生态系统的可持续管理至关重要。讲习班将重点介绍根据实验和分析数据测量的环境变化的影响，在生态和生态进化模型中实施环境波动的技术，以及研究其对物种如何随时间进化的影响的方法。讲习班的具体专题将包括：1)通过比较季节性强迫模型参数和包括概率参数的模型，在时空生态模型中实施环境波动的方法。二)数据驱动模型在生态学中的潜力和局限性，以及它们与理论模型的一致性。3)通过实验观察和模型预测，环境变化对物种扩散、跨物种相互作用以及物种如何应对疾病的影响。这些主题涉及数学建模、生态学、进化论、非线性动力系统、随机动力学、非线性偏微分方程、变分微积分和统计学等领域的链接。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。