OPUS: CRS Synthesizing long-term data to forecast native understory plant community structure & dynamics with invasion--species interactions, abiotic change & physiology

世界上许多地方的森林都受到大量本地有蹄类食草动物（鹿、驼鹿、麋鹿）和非本地入侵植物的负面影响。本项目将在个体、种群和群落层面探讨过多的食草动物和入侵者对森林常见原生多年生野花的影响。该项目有三个目标：1。利用群落共存模型确定鹿群食草性、入侵性和周围植物邻域对单个野花种群持久性的相对影响和重要性。2. 评估人为压力源（鹿、入侵）如何相互作用，并预测在长期实验中不同情景下未来森林野花的组成。3. 分享野花数据库，并与艺术家/设计师合作，为学生提供设计培训。本科生将创建虚拟现实体验、应用程序或桌面游戏等产品。由于美国森林经常经历高鹿群和非本地植物的入侵，群落模型的结果将适用于基础科学家和土地管理者的大区域尺度；学生产品将促进公众对森林正在发生的变化有更广泛的了解。该项目将使用在美国国家科学基金会支持下收集的单个野花数据库和非生物数据，建立一个有凝聚力的群落模型，并通过长期的野外实验，使用四种生物和非生物相互作用的景观来预测群落共存。计划中的分析将使用在长期野外实验中收集的每种野花的生长、存活、开花和种子生产数据库，在近20年的时间里，白尾鹿和一种有毒植物入侵者的存在都受到了控制。这种方法是新颖的，它将建立一个机制的、基于过程的模型，利用长期实验处理的数据来评估林下群落的共存情况，而不是现象学或应用模拟。通过提供一个统一的框架来评估生物压力源、环境特征和物种种群动态之间的关键联系和相互作用，以预测未来的群落动态和组成，该模型将为先前的个体或成对相互作用研究增加价值。本科生将接受数据可视化训练，使用与森林下层植被群落建模相同的长期数据库。设计过程，“行动反映变化”，要求学生定义和探索他们试图可视化的具体内容之间的联系，并为目标受众完善他们的产品。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Forests in many parts of the world are negatively impacted by both high populations of native ungulates herbivores (deer, moose, elk) and non-native invasive plants. This project will explore overabundant herbivores’ and invaders’ impacts at the individual, population, and community levels for common native perennial wildflowers of forests. The project has three goals: 1. Determine the relative effect and importance of deer herbivory, invasion, and surrounding plant neighborhood on individual wildflower population’s persistence using a community coexistence model. 2. Evaluate how the anthropogenic stressors (deer, invasion) interact and forecast future forest wildflower composition under the different scenarios created in the long-term experiment. 3. Share the wildflower databases and collaborate with artists/designers on students’ training in design. Undergraduates will create products such as virtual reality experiences, apps, or board games. Since US forests often experience both high deer populations and invasion by non-native plants, the results of the community models will be applicable at wide regional scales for basic scientists and land managers; the student products will foster a broader public understanding of ongoing changes to our forests. The project will use individual wildflower databases and abiotic data collected with NSF support to build a cohesive community model and to project community coexistence using four biotic and abiotic interaction landscapes imposed by a long-term field experiment. The planned analyses will use growth, survival, flowering and seed production databases for each wildflower species collected in the long-term field experiment, in which the presence of both white-tailed deer and a noxious plant invader are manipulated for nearly two decades. This approach is novel, in that rather than being phenomenological or applying simulations, it will build a mechanistic, process-based model to assess understory community coexistence leveraging data from long-term experimental treatments. This modeling will add value to prior individual or pair-wise interaction studies by providing a unified framework to assess critical links and interactions between biotic stressors, environmental characteristics, and species’ population dynamics to forecast future community dynamics and composition. Undergraduate students will be trained in data visualization using the same long-term databases used in the community modeling of the forest understory. The design process, “Act Reflect Change”, requires students to define and explore connections between the specific content they attempt to visualize and refine their product for their target audiences.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.