Revisiting the relationship between phylogenetic diversity and productivity

重新审视系统发育多样性与生产力之间的关系

基本信息

  • 批准号:
    2022742
  • 负责人:
  • 金额:
    $ 44.93万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-10-01 至 2023-09-30
  • 项目状态:
    已结题

项目摘要

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.
物种多样性之间的关系(即,物种的数量)及其生产力(例如,一年中产生的生物量)已经在生态学中从理论的角度和通过在该领域进行的一些最大的实验进行了深入的研究。了解生物多样性和生产力之间的关系对于开发生物燃料等应用以及预测物种丧失的影响至关重要。该项目旨在利用现有的大量实验数据开发新的统计、数学和计算工具,用于预测未经测试的生态群落的生产力,并确定共同的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可以用来回答遥远的问题,例如抗生素组合对细菌生长的影响。该项目的目的是制定一个统计框架,以适应生物多样性-生态系统功能实验产生的数据,该框架符合广义Lotka-Volterra模型,该模型是研究得最好的种群动态模型之一。为了保持足够小的自由参数的数量,任何两个物种之间的相互作用被建模为它们共享的进化历史的函数。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,而不是目前实践中的汇总统计数据,来测试进化对生产力的影响。通过超越传统上用于模拟这些数据的线性回归方法,该项目将弥合种群动态理论和实验方法之间的差距。为了进一步将种群动态与系统发育信息联系起来,该项目将开发明确解释系统发育的模型,从而使研究能够调查共同进化历史对生态群落共存和稳定性的影响。该奖项反映了NSF的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Modelling ecological communities when composition is manipulated experimentally
通过实验控制组成时对生态群落进行建模
  • DOI:
    10.1111/2041-210x.14028
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    6.6
  • 作者:
    Skwara, Abigail;Lemos‐Costa, Paula;Miller, Zachary R.;Allesina, Stefano
  • 通讯作者:
    Allesina, Stefano
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Stefano Allesina其他文献

Beyond pairwise mechanisms of species coexistence in complex communities
超越复杂群落中物种共存的成对机制
  • DOI:
    10.1038/nature22898
  • 发表时间:
    2017-06-01
  • 期刊:
  • 影响因子:
    48.500
  • 作者:
    Jonathan M. Levine;Jordi Bascompte;Peter B. Adler;Stefano Allesina
  • 通讯作者:
    Stefano Allesina
Specialty Grand Challenge Article Grand Challenges in Population Dynamics the Multidimensionality of Population Dynamics the Spatial Dimension of Population Dynamics Theoretical Models and Empirical Studies Ecology and Evolution
专业大挑战文章 人口动态的重大挑战 人口动态的多维性 人口动态的空间维度 理论模型和实证研究 生态学与进化
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    D. Oro;Stefano Allesina
  • 通讯作者:
    Stefano Allesina
Network structure , predator-prey modules , and stability in large food webs : Electronic Supplementary Material ( ESM )
  • DOI:
  • 发表时间:
    2007
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Stefano Allesina
  • 通讯作者:
    Stefano Allesina

Stefano Allesina的其他文献

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{{ truncateString('Stefano Allesina', 18)}}的其他基金

CAREER: Scientific Computing for a New Generation of Ecologists
职业:新一代生态学家的科学计算
  • 批准号:
    1148867
  • 财政年份:
    2012
  • 资助金额:
    $ 44.93万
  • 项目类别:
    Standard Grant
EAGER: Accelerating the Pace of Discovery by Changing the Peer Review Algorithm
EAGER:通过改变同行评审算法加快发现步伐
  • 批准号:
    1042164
  • 财政年份:
    2010
  • 资助金额:
    $ 44.93万
  • 项目类别:
    Standard Grant

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