GLobal Insect Threat-Response Synthesis (GLiTRS): a comprehensive and predictive assessment of the pattern and consequences of insect declines
GLobal Insect Threat-Response Synthesis (GLiTRS): a comprehensive and predictive assessment of the pattern and consequences of insect declines
批准号:
NE/V007548/1
负责人:
Nicholas Isaac
金额:
$115.02万
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:
未结题
起止时间:
2020 至 --
中文摘要
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英文摘要
With increasing recognition of the importance of insects, there are growing concerns that insect biodiversity has declined globally, with serious consequences for ecosystem function and services. Yet, gaps in knowledge limit progress in understanding the magnitude and direction of change. Information about insect trends is fragmented, and time-series data are restricted and unrepresentative, both taxonomically and spatially. Moreover, causal links between insect trends and anthropogenic pressures are not well-established. It is, therefore, difficult to evaluate stories about "insectageddon", to understand the ecosystem consequences, to devise mitigation strategies, or predict future trends. To address the shortfalls, we will bring together diverse sources of information, such as meta-analyses, correlative relationships and expert judgement. GLiTRS will collate these diverse lines of evidence on how insect biodiversity has changed in response to anthropogenic pressures, how responses vary according to functional traits, over space, and across biodiversity metrics (e.g. species abundance, occupancy, richness and biomass), and how insect trends drive further changes (e.g. mediated by interaction networks).We will integrate these lines of evidence into a Threat-Response model describing trends in insect biodiversity across the globe. The model will be represented in the form of a series of probabilistic statements (a Bayesian belief network) describing relationships between insect biodiversity and anthropogenic pressures. By challenging this "Threat-Response model" to predict trends for taxa and places where high-quality time series data exist, we will identify insect groups and regions for which indirect data sources are a) sufficient for predicting recent trends, b) inadequate, or c) too uncertain. Knowledge about the predictability of threat-response relationships will allow projections - with uncertainty estimates - of how insect biodiversity has changed globally, across all major taxa, functional groups and biomes.This global perspective on recent trends will provide the basis for an exploration of the consequences of insect decline for a range of ecosystem functions and services, as well as how biodiversity and ecosystem properties might be affected by plausible scenarios of future environmental change.GLiTRS is an ambitious and innovative research program: two features are particularly ground-breaking. First, the collation of multiple forms of evidence will permit a truly global perspective on insect declines that is unachievable using conventional approaches. Second, by validating "prior knowledge" (from evidence synthesis) with recent trends, we will assess the degree to which insect declines are predictable, and at what scales.
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DOI:
10.3897/neobiota.77.91402
发表时间:
2022-11-07
期刊:
NEOBIOTA
影响因子:
5.1
作者:
[Minnaar,Ingrid A., Hui,Cang, Clusella-Trullas,Susana]
通讯作者:
Clusella-Trullas,Susana
DOI:
10.1098/rspb.2023.0897
发表时间:
2023-06-14
期刊:
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
影响因子:
4.7
作者:
[Mancini, Francesca, Cooke, Rob, Woodcock, Ben A. A., Greenop, Arran, Johnson, Andrew C. C., Isaac, Nick J. B.]
通讯作者:
Isaac, Nick J. B.
DOI:
10.26786/1920-7603(2023)735
发表时间:
2023
期刊:
Journal of Pollination Ecology
影响因子:
--
作者:
[Greenop A]
通讯作者:
Greenop A
DOI:
10.1016/j.biocon.2022.109884
发表时间:
2023-01-07
期刊:
BIOLOGICAL CONSERVATION
影响因子:
5.9
作者:
[Cooke, Rob, Mancini, Francesca, Isaac, Nick J. B.]
通讯作者:
Isaac, Nick J. B.
DOI:
10.1111/ddi.13422
发表时间:
2021-10
期刊:
Diversity and Distributions
影响因子:
4.6
作者:
[Ashleigh M. Basel;J. Simaika;M. Samways;G. Midgley;S. MacFadyen;Cang Hui]
通讯作者:
Ashleigh M. Basel;J. Simaika;M. Samways;G. Midgley;S. MacFadyen;Cang Hui
共 8 条
Data integration for large scale ecological models
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批准号:NE/R005133/1
-
项目类别:Research Grant
-
资助金额:$4.09万
-
财政年份:2017
-
负责人:Nicholas Isaac
-
依托单位:
A unified approach to studying animal abundance: integrating evolution, ecology and scale dependency
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批准号:NE/D009448/2
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项目类别:Fellowship
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资助金额:$13.8万
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财政年份:2008
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负责人:Nicholas Isaac
-
依托单位:
A unified approach to studying animal abundance: integrating evolution, ecology and scale dependency
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批准号:NE/D009448/1
-
项目类别:Fellowship
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资助金额:$27.29万
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财政年份:2007
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负责人:Nicholas Isaac
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依托单位:
国内基金
海外基金
Insect Science
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批准号:30824805
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项目类别:专项基金项目
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资助金额:20.0万元
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批准年份:2008
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负责人:赵云鲜
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依托单位: