Collaborative Research: ORCC: Harnessing Adaptive Variation in Drought Resistance Strategies to Manage Populations Under Climate Change
合作研究:ORCC:利用抗旱策略的适应性变化来管理气候变化下的人口
基本信息
- 批准号:2222465
- 负责人:
- 金额:$ 95.26万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-11-01 至 2026-10-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Preserving biological diversity in the face of climate change is a major societal challenge, and land managers face daily decisions about how to do so as they strive to sustain natural resources. Climate change is increasing average temperatures and also changing how often and how intensely extreme events like severe droughts occur. Extreme events are particularly challenging for organisms with limited movement like plants, potentially causing enduring losses of diversity or even local extinctions. Management and conservation actions that take predicted future environments into account are necessary, but there is little consensus on what these actions should be and what biological principles should guide them. This challenge exists in part because studying what traits allow plants to withstand these extreme climate events is difficult; extreme droughts occur unpredictably, yet data or experimental resources must be obtained beforehand to assess the event’s impact. The proposed research will take advantage of a decade of collections of the common monkeyflower, Mimulus guttatus, made before, during, and after a severe, multi-year drought experienced in the 2010s in the Western US. Through studying what genetic variants and characteristics have helped adapt different populations to long-term differences in moisture among sites and also to this severe contemporary event, the proposed research will reveal strategies that may allow populations to remain resilient in future climates. These predictions will be tested in field studies. Through workshops with land managers, the project design will be informed by relevant stakeholders, and the results will subsequently inform their decisions.The proposed research will address this overarching question: what genetic and organismal adjustments to drought resistance strategies will promote local population resilience to changing climates? Annual populations of M. guttatus, are widespread but patchily distributed across a landscape over which the seasonal timing and severity of drought stress is highly variable. Although M. guttatus populations show multiple genetic and organismal signatures of adaptation to spatial variation in aridity, recent work has found they are becoming locally maladapted as climate change causes increasingly drastic disruptions to historical drought regimes. The project will intensively characterize how genetic variation acts through regulatory networks to adaptively tune organismal strategies to local conditions and ask whether the varied eco-evolutionary processes that unfolded during the 2010s Western US drought are explained by local variation in historical drought intensity, local standing genetic variation, or seed bank dynamics. Specifically, population genomic analyses and in-depth resurrection experiments will assess how genes and morphological, transcriptomic, and ecophysiological traits evolved during this severe drought event. How drought-associated alleles adaptively adjust these traits will be tested functionally by gene editing, and manipulative field experiments will evaluate how these genetic and organismal factors enhance fitness under current and predicted future drought regimes. All experiments will be structured around a common set of genotypes, and the resulting synergy will enable construction and validation of predictive frameworks for inclusion of genetic and organismal data into assisted gene flow practices as a means to promote population resilience to climate change and inform critical conservation decisions.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.
面对气候变化,保护生物多样性是一个重大的社会挑战,土地管理者在努力维持自然资源的同时,每天都面临着如何做到这一点的决定。气候变化正在提高平均气温,也改变了严重干旱等极端事件发生的频率和强度。极端事件对像植物这样活动有限的生物来说尤其具有挑战性,可能会导致生物多样性的持久损失,甚至局部灭绝。考虑到预测的未来环境的管理和保护行动是必要的,但对于这些行动应该是什么,以及应该以什么生物学原则来指导,几乎没有达成共识。这一挑战之所以存在,部分是因为研究哪些特性允许植物抵御这些极端气候事件是困难的;极端干旱的发生是不可预测的,但必须事先获得数据或实验资源,以评估事件的影响。这项拟议的研究将利用十年来收集的常见猴花Mimulus guttatus,这些收集是在美国西部经历了2010年代的严重、多年干旱之前、期间和之后进行的。通过研究哪些遗传变异和特征有助于不同种群适应不同地点之间的长期湿度差异,以及这一严重的当代事件,拟议的研究将揭示可能使种群在未来气候中保持弹性的策略。这些预测将在实地研究中得到验证。通过与土地管理人员的研讨会,相关利益攸关方将向项目设计提供信息,结果将随后为他们的决策提供信息。拟议的研究将解决这个首要问题:对抗旱战略进行哪些遗传和组织调整将促进当地人口对不断变化的气候的适应能力?美洲斑潜蝇一年生种群分布广泛,但在干旱胁迫的季节时间和严重程度高度可变的景观中分布零星。尽管古特塔斯根结线虫种群表现出适应干旱空间变化的多种遗传和组织特征,但最近的研究发现,随着气候变化对历史上的干旱制度造成越来越严重的破坏,它们正变得局部不适应。该项目将深入描述遗传变异如何通过调控网络发挥作用,根据当地条件自适应调整有机体的策略,并询问2010年代美国西部干旱期间展开的各种生态进化过程是否由历史干旱强度的局部变异、当地长期遗传变异或种子库动态解释。具体地说,种群基因组分析和深入的复活实验将评估基因以及形态、转录和生态生理特征在这次严重干旱事件中如何进化。干旱相关的等位基因如何自适应地调整这些特征将通过基因编辑进行功能测试,操纵性田间实验将评估这些遗传和组织因素如何增强在当前和预测的未来干旱制度下的适应性。所有实验都将围绕一组共同的基因类型构建,由此产生的协同效应将使预测框架的构建和验证成为可能,以将遗传和生物数据纳入辅助基因流动实践,作为促进种群对气候变化的适应能力并为关键的保护决策提供信息的一种手段。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。
项目成果
期刊论文数量(0)
专著数量(0)
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Daniel Runcie其他文献
Expanding genomic prediction in plant breeding: harnessing big data, machine learning, and advanced software
在植物育种中扩展基因组预测:利用大数据、机器学习和高级软件
- DOI:
10.1016/j.tplants.2024.12.009 - 发表时间:
2025-07-01 - 期刊:
- 影响因子:20.800
- 作者:
José Crossa;Johannes W.R. Martini;Paolo Vitale;Paulino Pérez-Rodríguez;Germano Costa-Neto;Roberto Fritsche-Neto;Daniel Runcie;Jaime Cuevas;Fernando Toledo;H. Li;Pasquale De Vita;Guillermo Gerard;Susanne Dreisigacker;Leonardo Crespo-Herrera;Carolina Saint Pierre;Alison Bentley;Morten Lillemo;Rodomiro Ortiz;Osval A. Montesinos-López;Abelardo Montesinos-López - 通讯作者:
Abelardo Montesinos-López
Machine learning algorithms translate big data into predictive breeding accuracy
机器学习算法将大数据转化为预测性育种准确性
- DOI:
10.1016/j.tplants.2024.09.011 - 发表时间:
2025-02-01 - 期刊:
- 影响因子:20.800
- 作者:
José Crossa;Osval A. Montesinos-Lopez;Germano Costa-Neto;Paolo Vitale;Johannes W.R. Martini;Daniel Runcie;Roberto Fritsche-Neto;Abelardo Montesinos-Lopez;Paulino Pérez-Rodríguez;Guillermo Gerard;Susanna Dreisigacker;Leonardo Crespo-Herrera;Carolina Saint Pierre;Morten Lillemo;Jaime Cuevas;Alison Bentley;Rodomiro Ortiz - 通讯作者:
Rodomiro Ortiz
MegaLMM improves genomic predictions in new environments using environmental covariates
MegaLMM 使用环境协变量改进新环境中的基因组预测
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Haixiao Hu;R. Rincent;Daniel Runcie - 通讯作者:
Daniel Runcie
Daniel Runcie的其他文献
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{{ truncateString('Daniel Runcie', 18)}}的其他基金
Collaborative Research: Mechanisms of Malleability and Resilience of Flowering Responses to Current and Future Variability in Seasonal Cues in a Geographically-widespread Species
合作研究:地理广泛物种开花响应当前和未来季节线索变化的可塑性和弹性机制
- 批准号:
1558090 - 财政年份:2016
- 资助金额:
$ 95.26万 - 项目类别:
Continuing Grant
NSF Postdoctoral Fellowship in Biology FY 2012
2012 财年 NSF 生物学博士后奖学金
- 批准号:
1202838 - 财政年份:2013
- 资助金额:
$ 95.26万 - 项目类别:
Fellowship Award
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Cell Research
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Research on the Rapid Growth Mechanism of KDP Crystal
- 批准号:10774081
- 批准年份:2007
- 资助金额:45.0 万元
- 项目类别:面上项目
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