Climate driven mismatches in fruit, pest and natural enemy phenology to mitigate crop damage
Climate driven mismatches in fruit, pest and natural enemy phenology to mitigate crop damage
批准号:
2106289
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
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
Climate influences timing of key events including crop flowering, seed set, and harvest, but also the peak abundance and occurrence crop pests and their natural enemies. Changing climate may alter the timing and duration of organisms' life-cycle events, leading to 'phenological mismatches' or prolonged activity cycles that have consequences for sustainable crop production.This PhD will explore the impacts of climate change on pest control, identified as a key industry need. UK pear orchards provide an ideal model system for this study because;1. Pears have one, dominant pest (pear sucker -Psylla pyri), which is resistant to most approved insecticides.2. Damage by pear sucker, caused by sap feeding and honeydew causing sooty mound and premature leaf drop, is a substantial source of economic loss in UK pear production, with yields below other European countries with similar climates.3. Pear sucker has a small number of key natural enemies (Anthocorid bug - Anthocoris nemoralis, European earwig - Forficula auricularia and ladybirds native 7-spot - Coccinella septempunctata, and invasive Harlequin - Harmonia axyridis).4. Ample pear orchards are available for the study including preexisting insect count for 18 sites.NIAB EMR have excellent existing data on pear pests and natural enemies including weekly year-round data for 7 years from 3 orchards, and data collected for 3 years from 15 orchards. They also hold the database for onset and duration of flowering of pear cultivars from1936 onwards. Climate predictions for the UK under a range of future scenarios are available from the Met office's UKCP18 projections.The aim of this PhD will be to utilize existing data to model tri-trophic interactions, collect field data to validate the models, identify production risks for pear growers under future climate conditions and explore options for reducing and mitigating identified risks.
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Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
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批准号:--
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项目类别:外国青年学者研究基金项目
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资助金额:--
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批准年份:2024
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负责人:江洋子
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依托单位:
基于Cache的远程计时攻击研究
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批准号:60772082
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项目类别:面上项目
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资助金额:28.0万元
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批准年份:2007
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负责人:王韬
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依托单位: