Complex interactions of in-stream dissolved organic matter and nutrient spiralling unravelled by Bayesian regression analysis

Uptake and release patterns of dissolved organic matter (DOM) compounds and co-transported nutrients are entangled, and the current literature does not provide a consistent picture of the interactions between the retention processes of DOM fractions. We performed plateau addition experiments with five different complex DOM leachates in a small experimental stream impacted by diffuse agricultural pollution. The study used a wide range of DOM qualities by including leachates of cow dung, pig dung, corn leaves, leaves from trees, and whole nettle plants. We measured changes in nutrient and dissolved organic carbon (DOC) concentrations along the stream course and determined DOM fractions by fluorescence measurements and parallel factor (PARAFAC) decomposition. To assess the influences of hydrological transport processes, we used a 1D hydrodynamic model. We developed a non-linear Bayesian approach based on the nutrient spiralling concept, which we named the “interactions in nutrient spirals using Bayesian regression” (INSBIRE) approach. This approach can disentangle complex interactions of biotic and abiotic drivers of reactive solutes' uptake in multi-component DOM sources. It can show the variability of the uptake velocities and quantify their uncertainty distributions. Furthermore, previous knowledge of nutrient spiralling can be included in the model using prior probability distributions. We used INSBIRE to assess interactions of compound-specific DOM and nutrient spiralling metrics in our experiment. Bulk DOC uptake varied among sources, showing decreasing uptake velocities in the following order: corn > pig dung > leaves > nettles > cow dung. We found no correlations between bulk DOC uptake and the amounts of protein-like compounds or co-leached soluble reactive phosphorus (SRP). The fastest uptake was observed for SRP and the tryptophan-like component, while the other DOM components' uptake velocities more or less resembled that of the bulk DOC. Almost all DOM components showed a negative relationship between uptake and concentration, known as efficiency loss. Furthermore, we observed a few negative and (weak) positive interactions between the uptake and the concentration of different components, such as a decreased uptake of protein-like compounds at high concentrations of a high-molecular-weight humic-like compound. We also found an influence of the wetted width on the uptake of SRP and a microbially derived humic substance, which indicates the importance of the sediment–water interface for P and humic C cycling in the studied stream. Overall, we show that bulk DOC is a weak predictor of DOC uptake behaviour for complex DOM leachates. Individual DOM compound uptake, including co-leached nutrients, is controlled by both internal (quality-related) and external (environmental) factors within the same aquatic ecosystem. We conclude that the cycling of different C fractions and their mutual interaction with N and P uptake in streams is a complex, non-linear problem, which can only be assessed with advanced non-linear approaches, such as the presented INSBIRE approach.

Complex interactions of in-stream DOM and nutrient spiralling unravelled by Bayesian regression analysis

<p>The carbon cycle in aquatic environments is of high interest because of its effects on water quality and greenhouse gas production as well as its alteration through anthropogenic activities with unknown outcomes. Uptake and release of dissolved organic matter (DOM) compounds is depending on the molecular structure and is strongly linked to N and P dynamics. Current research has not fully revealed the complex patterns behind.</p><p>To investigate the interactions between DOM components, we performed ten plateau addition experiments with different, realistic, complex DOM leachates (cow dung, pig dung, corn, leaves and nettles) in a small stream. The DOM quality was determined by fluorescence measurements and parallel factor (PARAFAC) decomposition and the nutrient concentrations were measured at eleven consecutive points in the stream at plateau conditions. The hydrological transport processes were incorporated by using the results of a 1-D hydrodynamic model.</p><p>The nutrient spiralling concept and its application in nutrient dynamics is a valuable basis for the analysis of our data. However, we could not find a data analysis approach, that suited the nature of our questions and data. Based on previously observed nutrient uptake models, we extended the nutrient spiralling concept by additional non-linear terms to analyse interactions between different DOM components.</p><p>We developed the “Interactions in Nutrient Spirals using BayesIan REgression (INSBIRE)” approach to analyse DOM uptake and retention mechanism. This approach can disentangle complex and interacting biotic and abiotic drivers in nutrient uptake metrics, show their variability and quantify their error distribution. We successfully used INSBIRE to show DOM-compound-specific interactions and draw conclusions from the data of our experiment. The applicability of INSBIRE has still to be tested in other studies, but we see a high potential not only in DOM dynamics but any kind of solute dynamics where interactions are crucial.</p>

Complex interactions of in-stream DOM and nutrient spiralling unravelled by Bayesian regression analysis

Uptake and release patterns of dissolved organic matter (DOM) compounds and nutrients are entangled, and the current literature does not provide a consistent picture of the link between DOM composition, nutrient concentrations, and effects on their cycling. We performed two plateau addition experiments for each of five different, realistic, complex DOM leachates in a small stream, heavily enriched in nitrate but not phosphate or DOM due to diffuse agricultural pollution. By including cow and pig dung as well as corn, leaves and nettles leachates, the study used a wide range of different DOM qualities. We measured changes in nutrient concentrations and determined DOM fractions by fluorescence measurements and parallel factor (PARAFAC) decomposition. To assess influences from hydrological transport processes, we used a 1-D hydrodynamic model. We propose a non-linear Bayesian approach to the nutrient spiralling concept, the Interactions in Nutrient Spirals using BayesIan REgression (INSBIRE) approach. This approach can disentangle complex and interacting biotic and abiotic drivers in nutrient uptake metrics, show their variability and quantify their error distribution. Furthermore, previous knowledge on nutrient spiralling can be included in the model using prior probability distributions. We used INSBIRE to assess interactions of compound-specific DOM and nutrient spiralling metrics the data of our experiment. The uptake processes of different DOM fractions were linked to each other. We observed stimulating and dampening effects of DOM fractions on each other and the overall DOM uptake. We found saturation effects for dissolved organic carbon (concentration of C, DOC) uptake, as rising concentrations of a DOM fraction dampened its uptake. The degradation of a humic DOM component of terrestrial origin was stimulated by other DOM fractions, pointing to priming effects. We also found an influence of the wetted width on the uptake of soluble reactive phosphorus (SRP) and a microbially derived humic substance, which indicates the importance of the sediment-water interface for P and humic C cycling in the studied stream. Interestingly, we found no interactions between DOM uptake and nitrate or SRP concentrations, or any effect of the added DOM leachates on nitrate uptake, indicating that the increase in DOC concentrations and SRP concentrations were not sufficient to affect the relatively steady nitrate uptake during the experiments. Overall, we show that bulk DOC is a weak predictor of DOC uptake behaviour for complex DOM leachates and that individual DOM compound uptake, nitrate uptake and SRP uptake are controlled very differently within the same aquatic ecosystem. We also found effects of hydromorphology on the uptake of one humic fluorophore and SRP. We conclude that cycling of different C fractions, their interaction and interactions with N and P uptake in streams is a complex, non-linear problem, which can only be assessed with advanced non-linear approaches, such as we present with INSBIRE.

Modeling nutrient in-stream processes at the watershed scale using Nutrient Spiralling metrics

One of the fundamental problems of using large-scale biogeochemical models is the uncertainty involved in aggregating the components of fine-scale deterministic models in watershed applications, and in extrapolating the results of field-scale measurements to larger spatial scales. Although spatial or temporal lumping may reduce the problem, information obtained during fine-scale research may not apply to lumped categories. Thus, the use of knowledge gained through fine-scale studies to predict coarse-scale phenomena is not straightforward. In this study, we used the nutrient uptake metrics defined in the Nutrient Spiralling concept to formulate the equations governing total phosphorus in-stream fate in a deterministic, watershed-scale biogeochemical model. Once the model was calibrated, fitted phosphorus retention metrics where put in context of global patterns of phosphorus retention variability. For this purpose, we calculated power regressions between phosphorus retention metrics, streamflow, and phosphorus concentration in water using published data from 66 streams worldwide, including both pristine and nutrient enriched streams. Performance of the calibrated model confirmed that the Nutrient Spiralling formulation is a convenient simplification of the biogeochemical transformations involved in total phosphorus in-stream fate. Thus, this approach may be helpful even for customary deterministic applications working at short time steps. The calibrated phosphorus retention metrics were comparable to field estimates from the study watershed, and showed high coherence with global patterns of retention metrics from streams of the world. In this sense, the fitted phosphorus retention metrics were similar to field values measured in other nutrient enriched streams. Analysis of the bibliographical data supports the view that nutrient enriched streams have lower phosphorus retention efficiency than pristine streams, and that this efficiency loss is maintained in a wide discharge range. This implies that both small and larger streams may be impacted by human activities in terms of nutrient retention capacity, suggesting that larger rivers located in human populated areas can exert considerable influence on phosphorus exports from watersheds. The role of biological activity in this efficiency loss showed by nutrient enriched streams remained uncertain, because the phosphorus mass transfer coefficient did not show consistent relationships with streamflow and phosphorus concentration in water. The heterogeneity of the compiled data and the possible role of additional inorganic processes on phosphorus in-stream dynamics may explain this. We suggest that more research on phosphorus dynamics at the reach scale is needed, specially in large, human impacted watercourses.

Modeling nutrient in-stream processes at the watershed scale using Nutrient Spiralling metrics

One of the fundamental problems of using large-scale biogeochemical models is the uncertainty involved in aggregating the components of fine-scale deterministic models in watershed applications, and in extrapolating the results of field-scale measurements to larger spatial scales. Although spatial or temporal lumping may reduce the problem, information obtained during fine-scale research may not apply to lumped categories. Thus, the use of knowledge gained through fine-scale studies to predict coarse-scale phenomena is not straightforward. In this study, we used the nutrient uptake metrics defined in the Nutrient Spiralling concept to formulate the equations governing total phosphorus in-stream fate in a watershed-scale biogeochemical model. The rationale of this approach relies on the fact that the working unit for the nutrient in-stream processes of most watershed-scale models is the reach, the same unit used in field research based on the Nutrient Spiralling concept. Automatic calibration of the model using data from the study watershed confirmed that the Nutrient Spiralling formulation is a convenient simplification of the biogeochemical transformations involved in total phosphorus in-stream fate. Following calibration, the model was used as a heuristic tool in two ways. First, we compared the Nutrient Spiralling metrics obtained during calibration with results obtained during field-based research in the study watershed. The simulated and measured metrics were similar, suggesting that information collected at the reach scale during research based on the Nutrient Spiralling concept can be directly incorporated into models, without the problems associated with upscaling results from fine-scale studies. Second, we used results from our model to examine some patterns observed in several reports on Nutrient Spiralling metrics measured in impaired streams. Although these two exercises involve circular reasoning and, consequently, cannot validate any hypothesis, this is a powerful example of how models can work as heuristic tools to compare hypotheses and stimulate research in ecology.

Improvements to the Diurnal Upstream–Downstream Dissolved Oxygen Change Technique for Determining Whole-Stream Metabolism in Small Streams

Whole-stream metabolism in a first-order stream was measured using upstream–downstream changes in dissolved oxygen (DO) concentration measured at 1-min intervals over a 40-h period. The measured change in DO was corrected for reaeration flux using a reaeration coefficient determined from injections of conservative and volatile tracers. The whole-stream metabolism measurement was compared in the spring with in situ chamber measurements performed a few days later in the same stream reach. Chamber measurements of community respiration extrapolated to a 24-h period (CR24) were about one third the whole-stream measurements, while gross primary production (GPP) measured at midday in the chambers was roughly 20% less than the whole-stream estimate. Whole-stream GPP was higher during the spring just prior to forest canopy closure than in summer or autumn. Community respiration exceeded whole-stream GPP on all dates and was greatest during the summer. Our results suggest that this whole-stream approach provides a measure of total stream metabolism that is relevant to other stream ecosystem processes measured on reach scales, such as nutrient spiralling.