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

Lead Research Organisation: Lancaster University
Department Name: Lancaster Environment Centre

Abstract

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.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
NE/M009106/1 01/10/2015 31/03/2024
1946135 Studentship NE/M009106/1 02/10/2017 31/05/2022