Contrasting Saltcedar Dynamics in Native and Non-Native Habitats through Integration of Remote Sensing and Population Modeling
Contrasting Saltcedar Dynamics in Native and Non-Native Habitats through Integration of Remote Sensing and Population Modeling
批准号:
1951657
负责人:
Chunyuan Diao
金额:
$35.5万
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
项目状态:
已结题
起止时间:
2020-06-15 至 2024-11-30
中文摘要
该项目从克服遥感和地面生态研究之间的空间尺度差异的角度处理盐柏入侵这一紧迫问题。该项目的总体目标是开发一个综合的遥感种群模型框架,以根据盐柏在本地和非本地栖息地的动态对比来研究入侵机制。通过揭示跨尺度盐柏入侵的潜在机制,该框架将有助于大规模河岸恢复实践。研究结果将广泛传播给保护机构,以帮助预测和应对入侵盐柏的威胁。协同的教育和研究活动将为从中学到研究生的学生提供学习和研究的机会。最后,外联活动将扩大传统上代表性不足的学生社区在STEM相关领域的参与。盐柏入侵仍然是一个严重的生态问题,对河岸地区产生负面影响,对社会、经济以及最终对人类健康和福祉产生广泛影响。发展对其空间扩展和扩散机制的全面了解,对于积极主动的生态系统管理至关重要。该项目的关键研究问题是:盐柏在其本地和非本地生境中对不同的水文气候因素的反应有什么不同的动态?为了回答这个问题,研究人员将开发一个集成的遥感人口模型多组件框架。综合框架将构成不同尺度的盐柏动态对比分析的基础,并有助于深入了解驱动盐柏在其本地和非本地生境中截然不同的动态的水文气候制度。这一多标量框架将可转移到其他类型的竞争植物物种,提高其广泛的实用性,并有助于更有效的土地管理实践。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。
英文摘要
This project addresses the pressing problem of saltcedar invasion from a perspective that overcomes the spatial scale disparities between remote sensing and ground-based ecological studies. The overarching goal of this project is to develop an integrated remotely sensed population modeling framework to investigate the invasion mechanism based on the contrast of saltcedar dynamics in its native and non-native habitats. Through shedding light on the underlying mechanisms of saltcedar invasion across scales, the framework will contribute to the large-scale riparian restoration practices. Research findings will be broadly disseminated to conservation agencies to help predict and address the threat of invasive saltcedar. The synergistic educational and research activities will offer learning and research opportunities to students from secondary to graduate levels. Lastly, outreach activities will broaden the participation of traditionally underrepresented student communities in STEM related fields.Saltcedar invasion remains a severe ecological problem, negatively impacting riparian areas, with broad implications on society, the economy, and, ultimately, human health and wellbeing. Developing a comprehensive understanding of its spatial expansion and spread mechanisms is essential for proactive ecosystem management. The key research question of the project is: what are the contrasting dynamics of saltcedar in response to varying hydroclimatic factors across its native and non-native habitats? To answer this question, the investigators will develop an integrated remotely sensed population modeling multi-component framework. The integrated framework will form the basis for a contrasting saltcedar dynamic analysis across scales, and foster insights into the hydroclimatic regimes driving the vastly disparate dynamics of saltcedar across its native and non-native habitats. This multi-scalar framework will be transferable to other types of competing vegetation species, enhancing its utility widely, and contributing to more effective land management practices.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.
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DOI:
10.1080/01431161.2022.2145584
发表时间:
2022-09
期刊:
International Journal of Remote Sensing
影响因子:
3.4
作者:
[Ying Lu;Le Wang]
通讯作者:
Ying Lu;Le Wang
DOI:
10.3390/rs13245005
发表时间:
2021-12
期刊:
Remote. Sens.
影响因子:
--
作者:
[Zijun Yang;C. Diao;Bo Li]
通讯作者:
Zijun Yang;C. Diao;Bo Li
DOI:
10.1080/01431161.2023.2195573
发表时间:
2023-03
期刊:
International Journal of Remote Sensing
影响因子:
3.4
作者:
[Rui-Dong Li;Le Wang;Ying Lu]
通讯作者:
Rui-Dong Li;Le Wang;Ying Lu
DOI:
10.1016/j.rse.2023.113790
发表时间:
2023-11
期刊:
Remote Sensing of Environment
影响因子:
13.5
作者:
[Yilun Zhao;C. Diao;Carol K. Augspurger;Zi-Ling Yang]
通讯作者:
Yilun Zhao;C. Diao;Carol K. Augspurger;Zi-Ling Yang
DOI:
10.1016/j.rse.2021.112584
发表时间:
2021-10
期刊:
Remote Sensing of Environment
影响因子:
13.5
作者:
[Ying Lu;Le Wang]
通讯作者:
Ying Lu;Le Wang
CAREER: Scalable Remote Sensing Computational Framework for Near-real-time Crop Characterization
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批准号:2048068
-
项目类别:Continuing Grant
-
资助金额:$50.97万
-
财政年份:2021
-
负责人:Chunyuan Diao
-
依托单位:
CRII: OAC: Real-time Computational Modeling of Crop Phenological Progress towards Scalable Satellite Precision Farming
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批准号:1849821
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项目类别:Standard Grant
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资助金额:$17.5万
-
财政年份:2019
-
负责人:Chunyuan Diao
-
依托单位: