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Soil macronutrient cycles beneath our feet: predicting how soil carbon and nitrogen manipulation regulates phosphorus cycling for environmental benefi

Soil macronutrient cycles beneath our feet: predicting how soil carbon and nitrogen manipulation regulates phosphorus cycling for environmental benefi
我们脚下的土壤常量养分循环:预测土壤碳和氮的操纵如何调节磷循环以实现环境效益
批准号:
1946135
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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:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --

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中文摘要
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英文摘要
Managing soil phosphorus is a major global issue, both with requirements for maximising P uptake into crops (ie minimising fertiliser resource input needs) and for reducing losses to waters. Both issues are united by controls of P turnover in soils, in turn influenced by coupled C, N and P cycles. These are often studied spatially, but without understanding temporally how we can manipulate these interacting cycles over time through management. Tackling this truly requires integrated biogeochemical knowledge and problem solving, necessitating training scientists capable of upscaling combined knowledge of soil, chemistry, biology and landscape processes into management advice. Recent BBSRC-funded work from the supervisors has shown controls of soil sorption, C and P status properties on soil solid-phase P forms and availability, spatially. The PhD research training opportunity here is to answer how these soil C, N, P processes can be beneficially manipulated to improve P efficiencies with respect to greater P availability and uptake of crop available P forms, yet minimising these forms from leaching.Microbial C, N and P cycling (and timescales of response to change) differ across soil types. The impacts of changing cycles on soil-solution P speciation couples P research needs with important agronomic management and societal goals of improving soil quality (e.g. increasing organic matter status of farmed soils). This studentship provides a training platform for the student to develop new knowledge, then a conceptual model leading to predictive ability, using manipulations and soil sensors, to understand timescales of improved soil P functions associated with microbial and soil organic matter quality changes. Specifically the PhD training will address the challenges of upscaling soil observations (including novel in-situ sensor data) to improve spatio-temporal prediction.
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