Collaborative Proposal: Linking process to pattern through an experimental network approach to identify the behavioral mechanisms of reproductive isolation

合作提案：通过实验网络方法将过程与模式联系起来，以确定生殖隔离的行为机制

• 批准号: 1856229
• 负责人: Kayleigh Keller
• 金额: $ 18.33万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1856229&HistoricalAwards=false
• 关键词: Collaborative; Proposal; Linking; process; pattern

Animals frequently interact with members of their own and closely related species in non-random ways that have profound implications for evolution within and between populations, including the buildup or breakdown of genetic differences. Closely related subspecies often come into contact and interbreed, or, hybridize. This research will experimentally study how social interactions (networks), morphological traits, genomic ancestry, and migratory behavior explain the amount of interbreeding in two contact zones each consisting of two pairs of barn swallow subspecies that differ in degree of hybridization. The integration of observation and experiments in the wild with genomic analyses will allow for a direct test of how individual behaviors impact hybridization. The research uses miniaturized proximity loggers and network analytical methods to measure the frequency of interactions between individual swallows. Data collection will be accomplished through extensive student training and international collaboration. The use, visualization, and interpretation of social networks will be broadly disseminated through 1) conference presentations, workshops, and publications, 2) integrated into courses, 3) public release of code for new network analysis methods and 4) online dynamic interactive visualizations of research data with exercises and assessment tools. This work represents a highly novel and integrative approach to understanding how closely related populations evolve into different species, with important implications for biodiversity and conservation studies.Assortative behaviors (non-random social interactions) are thought to represent critical barriers to gene flow among recently diverged animal taxa. However, direct measurement of assortative behavior in nature is rarely possible. This research leverages the barn swallow (Hirundo rustica) subspecies complex to experimentally examine the contribution of assortative behavior to reproductive isolation in two hybrid zones between subspecies pairs that differ in evolutionary history. The following will be collected from each hybrid zone: 1) close-range social interactions from proximity tags to construct social networks, 2) fine-scale genomic information to measure individual ancestry, 3) wintering locations, migratory routes and timing of arrival data from geolocators and stable isotopes, 4) measures of morphological variation, and 5) data for molecular paternity analyses to construct fertilization networks based on within- and extra-pair matings as a direct measure of hybridization between subspecies. The construction of fertilization networks will enable analyses about the degree to which hybridization is mediated by social interactions, subspecific ancestry, migratory behavior, or morphology. These features are likely correlated with one another and their combined and relative importance in reproductive isolation will be analyzed using matrix regression methods. After collecting correlative data from each hybrid zone, experimental manipulations of phenotype and timing of breeding will be conducted to test for causal relationships between these traits and fertilizations, providing an extremely rare opportunity to experimentally test and manipulate predictors of hybridization. These comparisons offer the previously intractable opportunity to experimentally analyze how individual-level variation predicts reproductive decisions and the degree to which populations hybridize.This award was co-funded by Behavioral Systems in the Division of Integrative Organismal Systems and Evolutionary Processes in the Division of Environmental Biology.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.

动物经常以非随机的方式与它们自己的成员和密切相关的物种相互作用，这对种群内部和种群之间的进化产生深远的影响，包括遗传差异的积累或崩溃。 密切相关的亚种经常接触并杂交，或者杂交。这项研究将通过实验研究社会互动（网络）、形态特征、基因组祖先和迁徙行为如何解释两个接触区中的杂交量，每个接触区由两对杂交程度不同的家燕亚种组成。将野外观察和实验与基因组分析相结合，将可以直接测试个体行为如何影响杂交。该研究使用小型化接近记录仪和网络分析方法来测量个体燕子之间相互作用的频率。数据收集将通过广泛的学生培训和国际合作来完成。社交网络的使用、可视化和解释将通过以下方式广泛传播：1) 会议演示、研讨会和出版物，2) 融入课程，3) 公开发布新网络分析方法的代码，以及 4) 在线动态交互式可视化使用练习和评估工具研究数据。 这项工作代表了一种高度新颖和综合的方法，用于理解密切相关的种群如何进化成不同的物种，对生物多样性和保护研究具有重要意义。选型行为（非随机的社会互动）被认为代表了最近分化的基因流动的关键障碍动物类群。然而，直接测量自然界的选型行为几乎是不可能的。这项研究利用家燕（Hirundo rustica）亚种复合体，通过实验研究了进化史不同的亚种对之间的两个杂交区中选型行为对生殖隔离的贡献。将从每个混合区收集以下信息：1）通过接近标签构建社交网络的近距离社交互动，2）用于测量个体血统的精细基因组信息，3）越冬地点、迁徙路线和到达时间数据地理定位器和稳定同位素，4）形态变异的测量，以及 5）分子亲子关系分析的数据，以构建基于配对内和配对外交配的受精网络，作为杂交之间杂交的直接测量亚种。受精网络的构建将能够分析社会互动、亚种祖先、迁徙行为或形态介导杂交的程度。这些特征可能彼此相关，并且将使用矩阵回归方法分析它们在生殖隔离中的组合和相对重要性。在收集每个杂交区的相关数据后，将进行表型和育种时间的实验操作，以测试这些性状与受精之间的因果关系，为实验测试和操作杂交预测因子提供了极其难得的机会。这些比较提供了以前难以处理的机会，可以通过实验分析个体水平的变异如何预测生殖决策以及种群杂交的程度。该奖项由环境部门综合有机系统部门的行为系统和进化过程部门共同资助生物学。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

Using Networks to Connect Individual-Level Reproductive Behavior to Population Patterns

使用网络将个体层面的生殖行为与种群模式联系起来

• DOI: 10.1016/j.tree.2019.03.009
• 发表时间: 2019-06
• 期刊: Trends in Ecology & Evolution
• 影响因子: 16.8
• 作者: Safran, Rebecca J.;Levin, Iris I.;Fosdick, Bailey K.;McDermott, Molly T.;Semenov, Georgy А.;Hund, Amanda K.;Scordato, Elizabeth S.C.;Turbek, Sheela P.
• 通讯作者: Turbek, Sheela P.

Inference for Network Regression Models with Community Structure

具有社区结构的网络回归模型的推理

• 发表时间: 2021-01
• 期刊: PMLR
• 作者: Pan, Mengjie;McCormick, Tyler H.;Fosdick, Bailey K.
• 通讯作者: Fosdick, Bailey K.

Regression of exchangeable relational arrays

可交换关系数组的回归

• DOI: 10.1093/biomet/asac031
• 发表时间: 2022-01
• 期刊: Biometrika
• 影响因子: 2.7
• 作者: Marrs, F W;Fosdick, B K;Mccormick, T H
• 通讯作者: Mccormick, T H

Non-Uniform Sampling of Fixed Margin Binary Matrices

固定边距二元矩阵的非均匀采样

• DOI: 10.1145/3412815.3416887
• 发表时间: 2020-10
• 期刊: FODS '20: Proceedings of the 2020 ACM-IMS on Foundations of Data Science Conference
• 作者: Fout, Ale;Fosdick, Bailey K.;Hitt, Matthew P.
• 通讯作者: Hitt, Matthew P.