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Simulating UK plant biodiversity under climate change to aid landscape decision making

Simulating UK plant biodiversity under climate change to aid landscape decision making
模拟气候变化下的英国植物生物多样性以帮助景观决策
批准号:
NE/T010355/1
负责人:
Richard Reeve
金额:
$37.97万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --

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中文摘要
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英文摘要
Landscapes are composed of multiple habitats as well as the biodiversity that resides within them, and are a product of interactions between species present, climate, geography and human use. They provide many ecosystem services, such as provision of food and water, regulation of climate and carbon cycling, which are vital for a stable future for our society, economy, health and wellbeing. Plants form the basis of all terrestrial ecosystems and are fundamental to providing these ecosystem services. Landscape decisions should therefore be underpinned by tools that enable prediction of plant responses to global change and landscape management. However, current approaches to modelling plant species distributions are deficient for this purpose as they focus on individual, or a small number of, species; ignore interactions between species; or only model a small number of plant functional types.A systems approach will be used to address this significant gap in current real-world landscape decision support by developing tools to predict (including uncertainty quantification) current and future distribution of all ~1,800 UK plant species in a manner that accounts for competitive interactions between species. This will enable effective assessment of the impacts of landscape decisions and/or climate change, e.g. in specific locations or on important habitat types such as peatlands. Invasive non-natives are considered a growing threat to ecosystem services and through extension to ~200,000 plant species worldwide this tool also enables assessment of the impact of invasive non-native plant species on current and potential future UK landscapes. Pests and diseases also represent a significant challenge and tools developed by this project will be a valuable resource for managing landscapes for plant health, for example, by providing distributions of at-risk populations - i.e. the distribution of plant hosts for any disease or pest of interest. Future work could explore the potentially critical feedbacks between the dynamics of plant community distributions and the transmission of pests and diseases by coupling models of these processes.This project builds on an existing coarse spatial scale model for all plant biodiversity on Earth and an ongoing NERC-funded project developing a higher resolution version for UK plant species. The latter project makes use of the more detailed climate, land use and plant coverage records available for the UK. However, further refinements are needed to properly quantify structural and process uncertainty within this framework. Without such work predictions of the effect of climate change and land use decisions that emerge from these models could be misleading.Currently niche preferences are parameterised by observational data with no uncertainty assessment. In terms of structural uncertainty, it is critical to account for between-species heterogeneity better by establishing how each species grows and reproduces (its functional type). Building on existing digitisation expertise at the Natural History Museum we therefore propose to extract relevant functional type information from existing taxonomic descriptions to create a more extensive trait database for all UK native and non-native plant species. As well as being a valuable resource in its own right and extensible to all global plant records, this work will be used within the project to enhance the simulation model to capture the relative differences in growth, competition and dispersal between species. Comparison with the current model based on a limited number of functional types will highlight the role of structural complexity and the impact of non-linearities on model output. We will also develop tools to quantify uncertainty in these models using available plant species distribution data so that we can correctly capture the impact of planned and expected land use and climate change, and ultimately guide future landscape decision making.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1016/j.ssmph.2022.101192
发表时间: 2022-09
期刊: SSM-POPULATION HEALTH
影响因子: 4.7
作者: [McMonagle, Ciaran, Brown, Denise, Reeve, Richard, Mancy, Rebecca]
通讯作者: Mancy, Rebecca
FAIR data pipeline: provenance-driven data management for traceable scientific workflows.
公平数据管道:可追溯的科学工作流程的出处驱动的数据管理。
DOI: 10.1098/rsta.2021.0300
发表时间: 2022-10-03
期刊: PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
影响因子: 5
作者: [Mitchell, Sonia Natalie, Lahiff, Andrew, Cummings, Nathan, Hollocombe, Jonathan, Boskamp, Bram, Field, Ryan, Reddyhoff, Dennis, Zarebski, Kristian, Wilson, Antony, Viola, Bruno, Burke, Martin, Archibald, Blair, Bessell, Paul, Blackwell, Richard, Boden, Lisa A. A., Brett, Alys, Brett, Sam, Dundas, Ruth, Enright, Jessica, Gonzalez-Beltran, Alejandra N. N., Harris, Claire, Hinder, Ian, Hughes, Christopher David, Knight, Martin, Mano, Vino, McMonagle, Ciaran, Mellor, Dominic, Mohr, Sibylle, Marion, Glenn, Matthews, Louise, McKendrick, Iain J. J., Pooley, Christopher Mark, Porphyre, Thibaud, Reeves, Aaron, Townsend, Edward, Turner, Robert, Walton, Jeremy, Reeve, Richard]
通讯作者: Reeve, Richard
DOI: 10.1016/j.epidem.2022.100612
发表时间: 2022-09
期刊: EPIDEMICS
影响因子: 3.8
作者: [Shadbolt, Nigel, Brett, Alys, Chen, Min, Marion, Glenn, McKendrick, Iain J., Panovska-Griffiths, Jasmina, Pellis, Lorenzo, Reeve, Richard, Swallow, Ben]
通讯作者: Swallow, Ben
DOI: 10.1111/geb.13564
发表时间: 2022-07
期刊: Global Ecology and Biogeography
影响因子: 6.4
作者: [C. Harris;N. Brummitt;C. Cobbold;R. Reeve]
通讯作者: C. Harris;N. Brummitt;C. Cobbold;R. Reeve
Open Epidemiology for pandemic modelling: a transparent, traceable, reusable, open source pipeline for reproducible science
  • 批准号:
    ST/V006126/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $64.67万
  • 财政年份:
    2021
  • 负责人:
    Richard Reeve
  • 依托单位:
The interplay of land-use, climate and plant biodiversity on the UK stage
  • 批准号:
    NE/T004193/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $6.41万
  • 财政年份:
    2019
  • 负责人:
    Richard Reeve
  • 依托单位:
Mathematical Theory and Biological Applications of Diversity
  • 批准号:
    BB/P004202/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $12.82万
  • 财政年份:
    2016
  • 负责人:
    Richard Reeve
  • 依托单位:
Assessing the impact of foot-and-mouth vaccination programs
  • 批准号:
    BB/K021400/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $3.12万
  • 财政年份:
    2013
  • 负责人:
    Richard Reeve
  • 依托单位:
国内基金
海外基金
LncRNA-lincUK介导邻近基因UK组蛋白修 饰调控褐飞虱繁殖力的机制研究
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2025
  • 负责人:
    刘凯
  • 依托单位:
CREKA/rhPro-UK靶向载药微泡在腔内超声场下对静脉血栓的除栓作用及机理研究
EEID:US-UK-China: 新发禽流感病毒的演进与生态传播动力学的前瞻性研究
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  • 批准号:
    31970054
  • 项目类别:
    面上项目
  • 资助金额:
    62.0万元
  • 批准年份:
    2019
  • 负责人:
    瞿旭东
  • 依托单位: