Revisiting the relationship between phylogenetic diversity and productivity

生态群落的物种多样性(即物种数量)与其生产力(如一年产生的生物量)之间的关系在生态学中得到了深入的研究，无论是从理论的角度还是通过在该领域进行的一些最大的实验都是如此。了解生物多样性和生产力是如何联系在一起的，对于生物燃料的开发以及预测物种丧失的影响是至关重要的。该项目旨在利用现有的大量实验数据来开发新的统计、数学和计算工具，这些工具可用于预测未经测试的生态群落的生产力，并确定共同进化历史对生态系统功能的贡献。重要的是，为研究生态群落而开发的同样的数学机器也可以用来回答遥远的问题，比如抗生素组合对细菌生长的影响。除了这项工作外，还出版了软件包、课堂讲稿和教材，以促进社区采用和推广新开发的工具。该项目旨在开发一个统计框架，以适应生物多样性-生态系统功能实验产生的数据，该框架与广义Lotka-Volterra模型一致，该模型是研究最多的种群动态模型之一。为了使自由参数的数量足够少，任何两个物种之间的相互作用都被建模为它们共同的进化历史的函数。反过来，这使得有可能通过包括连接生态群落所有成员的进化树的整个结构，而不是像目前做法那样的汇总统计，来测试系统发育对生产力的影响。通过超越传统上用于对这些数据建模的线性回归方法，该项目将弥合种群动力学理论和实验方法之间的差距。为了进一步将种群动力学与系统发育信息联系起来，该项目将开发具有明确系统发生学解释的模型，使研究能够调查共同进化历史对生态群落共存和稳定的影响。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。

The relationship between species diversity (i.e., the number of species) of an ecological community and its productivity (e.g., the amount of biomass produced in a year) has been studied intensively in ecology, both from a theoretical point of view, and through some of the largest experiments ever conducted in the field. Understanding how biodiversity and productivity are related is essential for applications, such as the development of biofuels, as well as to predict the effects of species loss. The project aims to leverage the large amount of experimental data available to develop new statistical, mathematical and computational tools that can be used to predict the productivity of untested ecological communities, and to determine the contribution of shared evolutionary history to the functioning of ecosystems. Importantly, the same mathematical machinery developed for the study of ecological communities can be used to answer distant questions, such as the effect of combinations of antibiotics on the growth of bacteria. The work is complemented by the publication of software packages, lecture notes and teaching material, to facilitate community adoption and extension of the newly developed tools.The project aims to develop a statistical framework to fit data stemming from Biodiversity-Ecosystem Functioning experiments that is consistent with the Generalized Lotka-Volterra model, one of the best-studied models for population dynamics. To keep the number of free parameters sufficiently small, interactions between any two species are modeled as a function of their shared evolutionary history. In turn, this makes it possible to test the effects of phylogeny on productivity, by including the whole structure of the evolutionary tree connecting all members of an ecological community, rather than summary statistics as in current practice. By moving beyond the linear regression approaches traditionally used to model these data, the project will bridge the gap between theory of population dynamics and experimental approaches. To further connect population dynamics with phylogenetic information, the project will develop models with explicit accounting for phylogeny, allowing research to investigate the effects of shared evolutionary history on the coexistence and stability of ecological communities.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.