MSB-ECA: Phylogenetically-informed modeling of the regional context of community assembly

MSB-ECA：社区组装区域背景的系统发育模型

• 批准号: 1802605
• 负责人: Diane Alston
• 金额: $ 29.9万
• 依托单位: Utah State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1802605&HistoricalAwards=false
• 关键词: MSB; ECA; Phylogenetically; informed; modeling

Ecologists have made great progress using observations from projects such as the National Ecological Observatory Network (NEON) to understand how communities of species will adapt to environmental change. This project builds on this progress by examining communities of species within the context of their evolutionary history, asking whether close relatives respond similarly (or differently) to environmental change. This research will focus first on modelling the plants, mammals, and birds observed at NEON sites, using this information to predict regions where non-native species could invade and degrade the valuable ecosystem services that these communities provide. Building on these foundations, this project will statistically model and predict species? associations, giving insight into costly beetle pest outbreaks and ticks that can carry diseases. As part of this work, teaching materials will be developed to help under-represented groups develop data science skills and make use of the data publicly available from NEON. Additionally, the project will develop a data science class for the Native American STEM Mentorship Program at Utah State, focusing on the use and analysis of NEON data.Integrating the cross-scale drivers of the distribution of biodiversity requires an understanding of both ongoing ecology and historic evolution. Species? shared evolutionary history reflects the biogeographical history that shaped them, and can inform us of constraints on species? ecology in the present. This proposal will integrate local-scale ecological community assembly with macro-scale regional assembly and trait evolution. Evolution is the context within which ecological processes take place: there can be no macro-scale synthesis of ecology without addressing phylogenetic context. This will be achieved through three major research objectives: (1) develop and release new datasets of North American plants, birds, mammals, beetles, and ticks found at and around NEON sites; (2) extend previous analyses (Phylogenetic Generalized Linear Mixed Models; PGLMMs) of the evolution of species? environmental tolerances to test macro-evolutionary models of local-scale competition within the plants, bird, and mammals of the NEON sites; and (3) extend these models to incorporate cross-guild interactions, focusing on plant-beetle and mammal-tick associations.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.

生态学家利用国家生态观测网络（氖）等项目的观测结果，在了解物种群落如何适应环境变化方面取得了很大进展。该项目建立在这一进展的基础上，通过研究物种进化历史背景下的物种群落，询问近亲对环境变化的反应是否相似（或不同）。这项研究将首先侧重于对氖站点观察到的植物、哺乳动物和鸟类进行建模，利用这些信息来预测非本地物种可能入侵并降低这些社区提供的宝贵生态系统服务的区域。在这些基础上，该项目将统计建模和预测物种？协会，让深入了解昂贵的甲虫害虫爆发和蜱，可以携带疾病。作为这项工作的一部分，将开发教材，以帮助代表性不足的群体发展数据科学技能，并利用氖公开提供的数据。此外，该项目还将为犹他州的美国原住民STEM导师计划开发一个数据科学课程，重点是氖数据的使用和分析。整合生物多样性分布的跨尺度驱动因素需要了解持续的生态学和历史演变。物种？共同的进化历史反映了塑造它们的地理历史，并能告诉我们物种的限制？生态在当下该方案将局部尺度的生态群落组装与宏观尺度的区域组装和性状进化相结合。进化是生态过程发生的背景：如果不解决系统发育背景，就不可能有宏观尺度的生态学综合。这将通过三个主要的研究目标来实现：（1）开发和发布北美植物，鸟类，哺乳动物，甲虫和蜱在氖网站及其周围发现的新数据集;（2）扩展以前的分析（系统发育广义线性混合模型; PGLMOST）的物种进化？环境耐受性，以测试宏观进化模型的局部规模的竞争内的植物，鸟类和哺乳动物的氖网站;和（3）扩展这些模型，以纳入跨行业协会的相互作用，重点放在植物甲虫和哺乳动物蜱associations.This奖项反映了NSF的法定使命，并已被认为是值得支持的评估使用基金会的智力价值和更广泛的影响审查标准。

项目成果

Pronounced genetic separation among varieties of the Primula cusickiana species complex, a Great Basin endemic

大盆地特有报春花品种复合体之间存在明显的遗传分离

• DOI: 10.1101/2021.03.19.436082
• 发表时间: 2021
• 期刊: Systematic botany
• 影响因子: 1
• 作者: Koontz, A;Pearse, WD;Wolf, P
• 通讯作者: Wolf, P

Complexity is complicated and so too is comparing complexity metrics‐A response to Mikula et al. (2018)

复杂性很复杂，比较复杂性指标也很复杂——这是对 Mikula 等人的回应。

• DOI: 10.1111/evo.13636
• 发表时间: 2018
• 期刊: Evolution
• 影响因子: 3.3
• 作者: Pearse, William D.;Morales‐Castilla, Ignacio;James, Logan S.;Farrell, Maxwell;Boivin, Frédéric;Davies, T. Jonathan
• 通讯作者: Davies, T. Jonathan

Global conservation of phylogenetic diversity captures more than just functional diversity

• DOI: 10.1038/s41467-019-08600-8
• 发表时间: 2019-02-20
• 期刊: NATURE COMMUNICATIONS
• 影响因子: 16.6
• 作者: Owen, Nisha R.;Gumbs, Rikki;Faith, Daniel P.
• 通讯作者: Faith, Daniel P.

Global imprint of mycorrhizal fungi on whole-plant nutrient economics

• DOI: 10.1073/pnas.1906655116
• 发表时间: 2019-11-12
• 期刊: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• 影响因子: 11.1
• 作者: Averill, Colin;Bhatnagar, Jennifer M.;Kivlin, Stephanie N.
• 通讯作者: Kivlin, Stephanie N.

What we (don't) know about global plant diversity

• DOI: 10.1111/ecog.04481
• 发表时间: 2019-09-01
• 期刊: ECOGRAPHY
• 影响因子: 5.9
• 作者: Cornwell, William K.;Pearse, William D.;Zanne, Amy E.
• 通讯作者: Zanne, Amy E.