Trait-shift induced interaction modification: How individual variation affects ecosystem stability

同一物种的个体生物可以在与环境和其他物种相互作用的重要特征上表现出实质性的差异。在一个物种内，这些可变特征的分布可以随着时间的推移而改变。例如，行为特征可以随着环境变化或物种相互作用而迅速改变。物种内部性状分布的动态变化可以改变物种间的相互作用模式，最终影响生态系统的稳定性。然而，这种影响的普遍性和重要性尚未得到系统的评估。本研究项目旨在通过理论与实证相结合的方法来填补这一空白。将开发一个数学框架，对不同类型的相互作用修改进行分类，并确定可能破坏生态系统稳定的条件。此外，将对实证研究进行全面调查，以评估上述各种类型的相互作用修改的证据水平，并为评估过去和未来的案例研究提供标准。该项目将培养数学与生态学交叉领域的年轻研究人员，以解决下一代面临的重要环境和生态问题。此外，将设计教育工具包和项目，以促进重要生态概念的教学，并吸引K-12学校中代表性不足的群体。种内性状变异越来越被认为是决定生态和进化动态的重要因素。尽管一些研究已经研究了遗传性状的变异如何影响生态进化动力学，但由表型可塑性、发育差异或物种相互作用引起的非遗传变异却很少得到考虑。传统上，生态系统被研究为具有固定相互作用强度的动态系统，但如果特征分布在短时间尺度内发生变化，这些相互作用强度将不再是恒定的。这种“性状转移诱导的相互作用修饰”（TSIIM）可以导致物种之间的高阶相互作用，导致物种灭绝或共存，否则是意想不到的。本项目将通过推广传统的动力系统来纳入种内性状变异，并将这些系统分类为不同的网络基序，为研究TSIIM建立一个理论框架。对大型生态系统的影响将使用由新基序增强的无序系统方法进行研究。利用实证研究对这些基序进行荟萃分析，将有助于深入了解TSIIM产生高阶相互作用的机制，从而促进对此类现象及其后果的实验研究。该项目由数学科学部的数学生物学项目和生物科学理事会环境生物学司的人口与社区生态集群共同资助。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。

Individual organisms of the same species can exhibit substantial variation in traits that are important for their interaction with the environment and other species. The distribution of such variable traits within a species can shift over time. For example, behavioral traits can change quickly in response to environmental change or species interactions. The dynamic shift of trait distribution within a species can modify the interaction patterns among species and ultimately affect the stability of ecosystems. However, the prevalence and significance of such effects have not been evaluated systematically. This research project aims to fill in the gap by integrating theoretical and empirical approaches. A mathematical framework will be developed to classify different types of interaction modification and identify conditions that would destabilize ecosystems. Additionally, a comprehensive survey of empirical studies will be conducted to assess the level of evidence for the various types of interaction modification identified above and provide criteria for evaluating past and future case studies. This project will train young researchers in the interdisciplinary area between mathematics and ecology to address important environmental and ecological problems facing the next generation. In addition, educational kits and programs will be designed to promote teaching of important ecological concepts and engage underrepresented groups in K-12 schools. Intraspecific trait variation has been increasingly recognized as an important factor in determining ecological and evolutionary dynamics. Although some work has examined how the variation of heritable traits affects eco-evolutionary dynamics, non-heritable variation caused by phenotypic plasticity, developmental differences, or species interactions has received less consideration. Ecosystems have traditionally been studied as dynamical systems with fixed interaction strengths, but these interaction strengths will no longer be constant if the trait distributions can shift within short timescales. Such “trait-shift induced interaction modification” (TSIIM) can lead to higher-order interactions among species, causing species extinction or coexistence that are otherwise unexpected. This project will develop a theoretical framework for studying TSIIM by generalizing traditional dynamical systems to incorporate intraspecific trait variation and categorizing these systems into different network motifs. The effect on large ecosystems will be studied using a disordered systems approach augmented by the new motifs. Meta-analysis of these motifs using empirical studies will provide insight on the mechanisms by which higher-order interactions arise from TSIIM, prompting experimental searches for such phenomena and their consequences.This project is jointly funded by the Mathematical Biology Program at the Division of Mathematical Sciences and the Population and Community Ecology Cluster in the Division of Environmental Biology at the Directorate for Biological Sciences.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.