Stable isotopes as indicators of nitrate attenuation across landscapes

Abstract

Mitigating the cascade of environmental damage caused by the movement of excess reactive nitrogen (N) from land to sea is currently limited by difficulties in precisely and accurately measuring N fluxes due to variable rates of attenuation (denitrification) during transport. This thesis develops the use of the natural abundance isotopic composition of nitrate (δ15N and δ18O of NO₃-) to integrate the spatialtemporal variability inherent to denitrification, creating an empirical framework for evaluating attenuation during land to water NO₃- transfers. This technique is based on the knowledge that denitrifiers kinetically discriminate against 'heavy' forms of both N and oxygen (O), creating a parallel enrichment in isotopes of both species as the reaction progresses. This discrimination can be quantitatively related to NO₃- attenuation by isotopic enrichment factors (εdenit). However, while these principles are understood, use of NO₃- isotopes to quantify denitrification fluxes in non-marine environments has been limited by, 1) poor understanding of εdenit variability, and, 2) difficulty in distinguishing the extent of mixing of isotopically distinct sources from the imprint of denitrification. Through a combination of critical literature analysis, mathematical modelling, mesocosm to field scale experiments, and empirical studies on two river systems over distance and time, these short comings are parametrised and a template for future NO₃- isotope based attenuation measurements outlined. Published εdenit values (n = 169) are collated in the literature analysis presented in Chapter 2. By evaluating these values in the context of known controllers on the denitrification process, it is found that the magnitude of εdenit, for both δ15N and δ18O, is controlled by, 1) biology, 2) mode of transport through the denitrifying zone (diffusion v. advection), and, 3) nitrification (spatial-temporal distance between nitrification and denitrification). Based on the outcomes of this synthesis, the impact of the three factors identified as controlling εdenit are quantified in the context of freshwater systems by combining simple mathematical modelling and lab incubation studies (comparison of natural variation in biological versus physical expression). Biologically-defined εdenit, measured in sediments collected from four sites along a temperate stream and from three tropical submerged paddy fields, varied from -3‰ to -28‰ depending on the site’s antecedent carbon content. Following diffusive transport to aerobic surface water, εdenit was found to become more homogeneous, but also lower, with the strength of the effect controlled primarily by diffusive distance and the rate of denitrification in the sediments. I conclude that, given the variability in fractionation dynamics at all levels, applying a range of εdenit from -2‰ to -10‰ provides more accurate measurements of attenuation than attempting to establish a site-specific value. Applying this understanding of denitrification's fractionation dynamics, four field studies were conducted to measure denitrification/ NO₃- attenuation across diverse terrestrial → freshwater systems. The development of NO₃- isotopic signatures (i.e., the impact of nitrification, biological N fixation, and ammonia volatilisation on the isotopic 'imprint' of denitrification) were evaluated within two key agricultural regions: New Zealand grazed pastures (Chapter 4) and Philippine lowland submerged rice production (Chapter 5). By measuring the isotopic composition of soil ammonium, NO₃- and volatilised ammonia following the bovine urine deposition, it was determined that the isotopic composition of NO₃ - leached from grazed pastures is defined by the balance between nitrification and denitrification, not ammonia volatilisation. Consequently, NO₃- created within pasture systems was predicted to range from +10‰ (δ15N)and -0.9‰ (δ18O) for non-fertilised fields (N limited) to -3‰ (δ15N) and +2‰ (δ18O) for grazed fertilised fields (N saturated). Denitrification was also the dominant determinant of NO₃- signatures in the Philippine rice paddy. Using a site-specific εdenit for the paddy, N inputs versus attenuation were able to be calculated, revealing that >50% of available N in the top 10 cm of soil was denitrified during land preparation, and >80% of available N by two weeks post-transplanting. Intriguingly, this denitrification was driven by rapid NO₃- production via nitrification of newly mineralised N during land preparation activities. Building on the relevant range of εdenit established in Chapters 2 and 3, as well as the soil-zone confirmation that denitrification was the primary determinant of NO₃- isotopic composition, two long-term longitudinal river studies were conducted to assess attenuation during transport. In Chapter 6, impact and recovery dynamics in an urban stream were assessed over six months along a longitudinal impact gradient using measurements of NO₃- dual isotopes, biological populations, and stream chemistry. Within 10 days of the catastrophic Christchurch earthquake, dissolved oxygen in the lowest reaches was <1 mg l⁻¹, in-stream denitrification accelerated (attenuating 40-80% of sewage N), microbial biofilm communities changed, and several benthic invertebrate taxa disappeared. To test the strength of this method for tackling the diffuse, chronic N loading of streams in agricultural regions, two years of longitudinal measurements of NO₃- isotopes were collected. Attenuation was negatively correlated with NO₃- concentration, and was highly dependent on rainfall: 93% of calculated attenuation (20 kg NO₃--N ha⁻¹ y⁻¹) occurred within 48 h of rainfall. The results of these studies demonstrate the power of intense measurements of NO₃- stable isotope for distinguishing temporal and spatial trends in NO₃ - loss pathways, and potentially allow for improved catchment-scale management of agricultural intensification. Overall this work now provides a more cohesive understanding for expanding the use of NO₃- isotopes measurements to generate accurate understandings of the controls on N losses. This information is becoming increasingly important to predict ecosystem response to future changes, such the increasing agricultural intensity needed to meet global food demand, which is occurring synergistically with unpredictable global climate change.