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The large scale understanding of natural organic matter: processes and application

Research output: ThesisDoctoral Thesis

  • Jess Adams
Publication date2017
Number of pages228
Awarding Institution
  • Quinton, John, Supervisor
  • Tipping, E., Supervisor, External person
Award date13/12/2017
  • Lancaster University
<mark>Original language</mark>English


Natural biogeochemical cycles of the macronutrient elements carbon (C), nitrogen
(N) and phosphorus (P) have been transformed by food and fuel production,
through atmospheric pollution and climate change. Further, land disturbance has
led to considerable losses of nutrients from terrestrial ecosystems. This
investigation aims to explore and address several barriers to understanding natural
organic matter cycling across terrestrial and aquatic ecosystems.
Soil organic matter (SOM) turnover models are often constrained by C and N,
while data on organic P is lacking. Twenty UK soils were used to provide the first
investigation of organic P in density fractionated SOM pools. Organic matter in the
mineral fraction was considerably more enriched in oP. Stoichiometric ratios
agreed with a new classification model, which provides important constraints for
models of nutrient cycles.
Radiocarbon (14C) measurements of aquatic OM indicates sources and turnover on
different timescales. Here, the first analysis of particulate O14C in UK rivers
suggested topsoil was the major source. Significantly depleted material was found
in a catchment with historical mining activity. Global, temporal analysis of
dissolved O14C enabled quantification of different OM sources, and highlighted the
importance of assessing the data against the changing atmospheric 14C signal. New
dissolved O14C data for rural, arable and urban catchments were more depleted
than the global averages.
In industry, there is a growing need to manage aquatic nutrient enrichment through
rapid and reliable monitoring. A model of UV absorbance was tested against
freshwaters that were biased towards eutrophic conditions. The results
demonstrated the weak absorbing components of algal DOM, and new variable
model parameters were introduced, which quantified the contribution of algal
DOM. This could have implications on model predictions of DOC concentration,
and a generally applicable spectroscopic model is questionable.
This investigation considerably expands the dataset available for modelling large
scale biogeochemical cycles, highlights the importance of an integrated approach,
and considers the implications involved with applied modelled predictions of
aquatic DOC.