Macronutrients (carbon (C), nitrogen (N), and phosphorous (P)) are substances that all organisms require to survive, grow and reproduce. While C, N, and P are naturally present in all aquatic ecosystems, human activities have significantly increased their concentrations and changed their dynamics in rivers. This lead to widespread degradation of water quality. Meaningfully reversing those consequences requires understanding how anthropogenic activities have changed macronutrient dynamics. This approach is still hindered by the availability of long-term data which covers periods of pollution and recovery. In this thesis, I investigated long-term changes by collecting, combining, and interpolating time series of many different ecological variables. Particularly, I developed a conceptual model that linked a 65-year long time series of in-stream N concentrations in the Elbe to changed anthropogenic N sources, which I, in turn, explained with a characteristic succession of human needs. To understand the sources and the sinks of N in rivers, I developed a mass balance model that quantifies how much N has been retained by organisms in the Elbe over the last 42 years. Using an inverse Bayesian model approach, I estimated the daily importance of bacterial and algal activity over 36 of these 42 years. Apart from N, macronutrient ratios (C:N:P) are a crucial determinant of the integrity of aquatic ecosystems. To comprehend the effects of anthropogenic activities on C:N:P ratios, I analyzed C, N, and P data from 574 German catchments spanning a large gradient of agricultural and urban activities. Over the last 65 years, I discovered multiple regime shifts in the N dynamics of the Elbe. Before ∼ 1970, the Elbe experienced constant N concentrations across the seasons. Afterwards, a distinct seasonal pattern emerged with high concentrations during winter and low concentrations during summer. After the collapse of the German Democratic Republic in 1989, water quality in the Elbe improved drastically as many pollutant sources were removed. This manifested in declining annual mean N concentrations, but the summer and winter concentrations diverged further. I explain this with a changing ratio of agricultural and urban N sources, which affect the in-stream N concentrations differently across the seasons. Furthermore, improved water quality led to decreased bacterial and increased algal activity in the Elbe. Higher bacterial activity led to the higher N removal rates from the stream but also caused low oxygen concentrations in the Elbe and increased CO2 emissions. Across Germany, I found that most catchments, agricultural or not, are enriched with nitrogen compared to C and P. Especially the relatively low availability of C will reduce the capacity of rivers and adjacent ecosystems to remove the excessive N via biological processes. Overall, this thesis contributes to the understanding how anthropogenic activities change macronutrient availability in rivers over multiple decades and how riverine macronutrient cycling responds to different anthropogenic pressures. Nutrient management strategies usually do not consider seasonality and stoichiometry. This thesis suggests that those metrics have clear ecological implications and should be integrated into holistic macronutrient management strategies.:Summary 13
2 Introduction 16
2.1 The importance of macronutrients in aquatic ecosystems . . . . . . . . . 16
2.2 Anthropogenic impacts on macronutrient concentrations in rivers . . . . 18
2.3 Impacts of increased macronutrient concentrations on rivers and adjacent
ecosystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.4 Research questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.5 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3 Drivers of multi-decadal nitrate regime shifts in a large European
catchment 34
3.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.3 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.4 Data and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.4.1 The Elbe catchment . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.4.2 Time series data . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
3.4.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.5 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.5.1 Mean concentrations and seasonality metrics . . . . . . . . . . . . 45
3.5.2 The role of in-stream nitrate retention . . . . . . . . . . . . . . . 50
3.5.3 Limitations of this study . . . . . . . . . . . . . . . . . . . . . . . 50
3.5.4 Environmental implications . . . . . . . . . . . . . . . . . . . . . 50
3.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.7 Author contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.8 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
4 From iron curtain to green belt: Elbe River shift from heterotrophic
to autotrophic nitrogen retention over 35 years of passive restoration 62
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4.2 Data and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
4.2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
4.2.2 Study site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
4.2.3 Two-station mass balance . . . . . . . . . . . . . . . . . . . . . . 68
7
4.2.4 Metabolism estimations . . . . . . . . . . . . . . . . . . . . . . . 69
4.2.5 Channel geometry estimations . . . . . . . . . . . . . . . . . . . . 70
4.2.6 Data preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
4.3 Estimating the N demand of metabolic processes . . . . . . . . . . . . . . 70
4.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
4.4.1 DIN retention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
4.4.2 Dissolved oxygen saturation and metabolism . . . . . . . . . . . . 75
4.4.3 Linking metabolism and DIN retention . . . . . . . . . . . . . . . 79
4.4.4 Ecological implications . . . . . . . . . . . . . . . . . . . . . . . . 82
4.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
4.6 Author contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
4.7 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
5 Stoichiometry on the edge - Humans induce strong imbalances of
reactive C:N:P ratios in streams 92
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
5.2 Data and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.2.1 Data selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.2.2 Derivation and visualization of C:N:P ratios . . . . . . . . . . . . 97
5.2.3 Classification of catchment stoichiometry . . . . . . . . . . . . . . 98
5.3 Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
5.3.1 Spatial variability of median reactive C:N:P ratios . . . . . . . . . 99
5.3.2 Intra-annual variability of reactive C:N:P ratios . . . . . . . . . . 101
5.3.3 Implications for biogeochemical processing . . . . . . . . . . . . . 105
5.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
5.5 Author contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
5.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
6 Discussion 116
6.1 Generality of findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
6.2 Relevance for eutrophication . . . . . . . . . . . . . . . . . . . . . . . . . 119
6.2.1 Seasonality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
6.2.2 Stoichiometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
6.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
6.4 Future research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
6.5 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
8
7 Publication record 125
8 Acknowledgements 127
S Appendices 128
S.1 Supplementary material for the article: Drivers of multi-decadal nitrate
regime shifts in a large European catchment . . . . . . . . . . . . . . . . 128
S.1.1 Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
S.1.2 Analytical methods for nitrate measurement . . . . . . . . . . . . 133
S.1.3 Parameter estimation for the mixed source succession model (MSSM)133
S.1.4 The role of in-stream nitrate retention . . . . . . . . . . . . . . . 136
S.1.5 Parameter uncertainty of MSSM . . . . . . . . . . . . . . . . . . . 138
S.1.6 Sensitivity analysis of MSSM . . . . . . . . . . . . . . . . . . . . 138
S.1.7 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
S.2 Supplementary material for the Chapter: From iron curtain to green belt
- Elbe River shift from heterotrophic to autotrophic nitrogen retention
over 35 years of passive restoration . . . . . . . . . . . . . . . . . . . . . 144
S.2.1 Segment geometry estimation . . . . . . . . . . . . . . . . . . . . 144
S.2.2 Gaussian error propagation . . . . . . . . . . . . . . . . . . . . . 144
S.2.3 Interpolation of the hourly dissolved oxygen time series . . . . . . 145
S.2.4 Metabolism model implementation and validation . . . . . . . . . 146
S.2.5 Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
S.2.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
S.3 Supplementary material for the article: Stoichiometry on the edge - Humans
induce strong imbalances of reactive C:N:P ratios in streams . . . . 157
S.3.1 Data selection criteria . . . . . . . . . . . . . . . . . . . . . . . . 157
S.3.2 Converting C, N and P time series to C:N:P ratios . . . . . . . . 157
S.3.3 Calculation of the dist metric . . . . . . . . . . . . . . . . . . . . 158
S.3.4 Possible contributions of dissolved organic nitrogen (DON) and
phosphorus (DOP) . . . . . . . . . . . . . . . . . . . . . . . . . . 158
S.3.5 Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
S.3.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:92561 |
| Date | 01 August 2024 |
| Creators | Wachholz, Alexander |
| Contributors | Borchardt, Dietrich, Flörke, Martina, Krebs, Peter, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 10.1088/1748-9326/acc3b1, 10.1088/1748-9326/ac6f6a, 10.4211/hs.26e8238f0be14fa1a49641cd8a455e29 |
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