Comparing critical source areas for the sediment and nutrients of calibrated and uncalibrated models in a plateau watershed in southwest China.

Controlling non-point source pollution is often difficult and costly. Therefore, focusing on areas that contribute the most, so-called critical source areas (CSAs), can have economic and ecological benefits. CSAs are often determined using a modelling approach, yet it has proved difficult to calibrate the models in regions with limited data availability. Since identifying CSAs is based on the relative contributions of sub-basins to the total load, it has been suggested that uncalibrated models could be used to identify CSAs to overcome data scarcity issues. Here, we use the SWAT model to study the extent to which an uncalibrated model can be applied to determine CSAs. We classify and rank sub-basins to identify CSAs for sediment, total nitrogen (TN), and total phosphorus (TP) in the Fengyu River Watershed (China) with and without model calibration. The results show high similarity (81%-93%) between the identified sediment and TP CSA number and locations before and after calibration both on the yearly and seasonal scale. For TN alone, the results show moderate similarity on the yearly scale (73%). This may be because, in our study area, TN is determined more by groundwater flow after calibration than by surface water flow. We conclude that CSA identification with the uncalibrated model for TP is always good because its CSA number and locations changed least, and for sediment, it is generally satisfactory. The use of the uncalibrated model for TN is acceptable, as its CSA locations did not change after calibration; however, the TN CSA number changed by over 60% compared to the figures before calibration on both yearly and seasonal scales. Therefore, we advise using an uncalibrated model to identify CSAs for TN only if water yield composition changes are expected to be limited. This study shows that CSAs can be identified based on relative loading estimates with uncalibrated models in data-deficient regions.

Mowing Submerged Macrophytes in Shallow Lakes with Alternative Stable States: Battling the Good Guys?

Submerged macrophytes play an important role in maintaining good water quality in shallow lakes. Yet extensive stands easily interfere with various services provided by these lakes, and harvesting is increasingly applied as a management measure. Because shallow lakes may possess alternative stable states over a wide range of environmental conditions, designing a successful mowing strategy is challenging, given the important role of macrophytes in stabilizing the clear water state. In this study, the integrated ecosystem model PCLake is used to explore the consequences of mowing, in terms of reducing nuisance and ecosystem stability, for a wide range of external nutrient loadings, mowing intensities and timings. Elodea is used as a model species. Additionally, we use PCLake to estimate how much phosphorus is removed with the harvested biomass, and evaluate the long-term effect of harvesting. Our model indicates that mowing can temporarily reduce nuisance caused by submerged plants in the first weeks after cutting, particularly when external nutrient loading is fairly low. The risk of instigating a regime shift can be tempered by mowing halfway the growing season when the resilience of the system is highest, as our model showed. Up to half of the phosphorus entering the system can potentially be removed along with the harvested biomass. As a result, prolonged mowing can prevent an oligo-to mesotrophic lake from becoming eutrophic to a certain extent, as our model shows that the critical nutrient loading, where the lake shifts to the turbid phytoplankton-dominated state, can be slightly increased.

Competition for light and nutrients in layered communities of aquatic plants.

Dominance of free-floating plants poses a threat to biodiversity in many freshwater ecosystems. Here we propose a theoretical framework to understand this dominance, by modeling the competition for light and nutrients in a layered community of floating and submerged plants. The model shows that at high supply of light and nutrients, floating plants always dominate due to their primacy for light, even when submerged plants have lower minimal resource requirements. The model also shows that floating-plant dominance cannot be an alternative stable state in light-limited environments but only in nutrient-limited environments, depending on the plants' resource consumption traits. Compared to unlayered communities, the asymmetry in competition for light-coincident with symmetry in competition for nutrients-leads to fundamentally different results: competition outcomes can no longer be predicted from species traits such as minimal resource requirements ([Formula: see text] rule) and resource consumption. Also, the same two species can, depending on the environment, coexist or be alternative stable states. When applied to two common plant species in temperate regions, both the model and field data suggest that floating-plant dominance is unlikely to be an alternative stable state.

Predicting microbial nitrogen pathways from basic principles.

Nitrogen compounds are transformed by a complicated network of competing geochemical processes or microbial pathways, each performed by a different ecological guild of microorganisms. Complete experimental unravelling of this network requires a prohibitive experimental effort. Here we present a simple model that predicts relative rates of hypothetical nitrogen pathways, based only on the stoichiometry and energy yield of the performed redox reaction, assuming competition for resources between alternative pathways. Simulating competing pathways in hypothetical freshwater and marine sediment situations, we surprisingly found that much of the variation observed in nature can simply be predicted from these basic principles. Investigating discrepancies between observations and predictions led to two important biochemical factors that may create barriers for the viability of pathways: enzymatic costs for long pathways and high ammonium activation energy. We hypothesize that some discrepancies can be explained by non-equilibrium dynamics. The model predicted a pathway that has not been discovered in nature yet: the dismutation of nitrite to the level of nitrate and dinitrogen gas.

Spatially explicit fate modelling of nanomaterials in natural waters.

Site specific exposure assessments for engineered nanoparticles (ENPs) require spatially explicit fate models, which however are not yet available. Here we present an ENP fate model (NanoDUFLOW) that links ENP specific process descriptions to a spatially explicit hydrological model. The link enables the realistic modelling of feedbacks between local flow conditions and ENP fate processes, such as homo- and heteroaggregation, resuspension and sedimentation. Spatially explicit simulations using five size classes of ENPs and five size classes of natural solids showed how ENP sediment contamination 'hot spots' and ENP speciation can be predicted as a function of place and time. For the catchment modelled, neglect of spatial heterogeneity caused relatively small differences in ENP retention. However, simplification of the number of size classes to one average class, resulted in up to 3.3 times lower values of retention compared to scenarios that used detailed size distributions. Local concentrations in sediment were underestimated up to 20 fold upon simplification of spatial heterogeneity or particle size distribution. We conclude that spatial heterogeneity should not be neglected when assessing the risks of ENPs.

Warming can boost denitrification disproportionately due to altered oxygen dynamics.

BACKGROUND: Global warming and the alteration of the global nitrogen cycle are major anthropogenic threats to the environment. Denitrification, the biological conversion of nitrate to gaseous nitrogen, removes a substantial fraction of the nitrogen from aquatic ecosystems, and can therefore help to reduce eutrophication effects. However, potential responses of denitrification to warming are poorly understood. Although several studies have reported increased denitrification rates with rising temperature, the impact of temperature on denitrification seems to vary widely between systems. METHODOLOGY/PRINCIPAL FINDINGS: We explored the effects of warming on denitrification rates using microcosm experiments, field measurements and a simple model approach. Our results suggest that a three degree temperature rise will double denitrification rates. By performing experiments at fixed oxygen concentrations as well as with oxygen concentrations varying freely with temperature, we demonstrate that this strong temperature dependence of denitrification can be explained by a systematic decrease of oxygen concentrations with rising temperature. Warming decreases oxygen concentrations due to reduced solubility, and more importantly, because respiration rates rise more steeply with temperature than photosynthesis. CONCLUSIONS/SIGNIFICANCE: Our results show that denitrification rates in aquatic ecosystems are strongly temperature dependent, and that this is amplified by the temperature dependencies of photosynthesis and respiration. Our results illustrate the broader phenomenon that coupling of temperature dependent reactions may in some situations strongly alter overall effects of temperature on ecological processes.