Modeling the Ecological Impact of Phosphorus in Catchments with Multiple Environmental Stressors

Diatoms as indicators in running waters: trends of studies on biological assessment and monitoring

Despite the biodiversity and ecosystem services provided by lotic ecosystems, they are strongly affected by anthropogenic activities. Therefore, biological monitoring and assessment strategies are crucial in helping maintain these ecosystems and developing mitigation policies. We provide a global overview of the use of benthic diatoms as bioindicators in lotic environments, by analyzing 764 articles published in the past 20 years. We analyzed the influence of substrate type on samplings, which species have been highlighted as indicators and for which type of impacts, which anthropogenic impacts have been most commonly evaluated, and which metrics have been commonly used in studies using diatoms to assess and monitor the quality of lotic environments. We found that the most studied anthropogenic impact is artificial eutrophication and that some species, especially Nitzschia palea, have been thoroughly mentioned as indicators of this impact. Indicator species related to other types of impact are less common, demonstrating the need for studies on this issue. Moreover, we verified that traditional taxonomic metrics, such as diversity and diatom indices, have been widely used. Some alternative metrics have been used recently, such as those based on teratological valves, lipid bodies, valve size, and DNA metabarcoding. The number of biomonitoring and assessment studies based on diatoms has increased considerably in the past 20 years. Nonetheless, the demand for natural resources and consequently the degradation of lotic ecosystems have accelerated significantly. Thus, the development of low-cost and time-efficient biological assessment and monitoring strategies is essential for evaluating the health of lotic environments.

Multiple in-stream stressors degrade biological assemblages in five U.S. regions

Biological assemblages in streams are affected by a wide variety of physical and chemical stressors associated with land-use development, yet the importance of combinations of different types of stressors is not well known. From 2013 to 2017, the U.S. Geological Survey completed multi-stressor/multi-assemblage stream ecological assessments in five regions of the United States (434 streams total). Diatom, invertebrate, and fish communities were enumerated, and five types of potential stressors were quantified: habitat disturbance, excess nutrients, high flows, basic water quality, and contaminants in water and sediment. Boosted regression tree (BRT) models for each biological assemblage and region generally included variables from all five stressor types and multiple stressors types in each model was the norm. Classification and regression tree (CART) models then were used to determine thresholds for each BRT model variable above which there appeared to be adverse effects (multi-metric index (MMI) models only). In every region and assemblage there was a significant inverse relation between the MMI and the number of stressors exerting potentially adverse effects. The number of elevated instream stressors often varied substantially for a given level of land-use development and the number of elevated stressors was a better predictor of biological condition than was development. Using the adverse effects-levels that were developed based on the BRT model results, 68% of the streams had two or more stressors with potentially adverse effects and 35% had four or more. Our results indicate that relatively small increases in the number of stressors of different types can have a large effect on a stream ecosystem.

What is the deal with the Green Deal: Will the new strategy help to improve European freshwater quality beyond the Water Framework Directive?

Agricultural land use covers almost half of the EU territory and reducing nutrient and pesticide losses to freshwaters is central to existing EU policy. However, the progress of improving freshwater quality and reducing eutrophication is slow and lags behind targets. The Green Deal is a key element of the EU plans to implement the United Nation's Sustainable Development Goals. Here, we discuss the opportunities that the Green Deal and associated strategies may provide for the achievement of the water quality goals of the Water Framework Directive in agricultural landscapes. We welcome Green Deal's aspirational stated goals. However, the reliance of mitigation of diffuse agricultural pollution on the reform of the Common Agricultural Policy represents grave risks for practical implementation and the achievement of the Green Deal objectives. We also argue that the new strategies should be targeted at tackling and understanding the sources of water quality problems along the full pollution continuum. To maximise the opportunities for tackling diffuse pollution from agricultural land use and achieving the delayed water quality targets, we stress that a range of targeted new instruments will be needed to close the gaps in the pollution continuum 'from source to impact'. These gaps include: (I) smart and standardised monitoring of the impacts of proposed eco-schemes and agri-environment-climate measures, (ii) active restoration of agricultural streams and ditches and their floodplains to reduce secondary pollution sources, (iii) options to draw down nutrient levels to or below the agronomic optimum that reduce legacy sources, (iv) integrating farm-scale and catchment-scale analysis of trade-offs in reducing different pollutants and their combined effects, and finally (v) accounting for emerging pressures to freshwater quality due to climate change. Incorporation of the pollution continuum framework into tackling diffuse agricultural pollution will ensure that the European water-related policy goals are achieved.

Probability maps of anthropogenic impacts affecting ecological status in European rivers

Understanding how anthropogenic pressures affect river ecological status is pivotal to designing effective management strategies. Knowledge on river aquatic habitats status in Europe has increased tremendously since the introduction of the European Union Water Framework Directive, yet heterogeneities in mandatory monitoring and reporting still limit identification of patterns at continental scale. Concurrently, several model and data-based indicators of anthropogenic pressures to freshwater that cover the continent consistently have been developed. The objective of this work was to create European maps of the probability of occurrence of river conditions, namely failure to achieve good ecological status, or to be affected by specific pervasive impacts. To this end, we applied logistic regression methods to model the river conditions as functions of continental-scale water pressure indicators. The prediction capacity of the models varied with river condition: the probability to fail achieving good ecological status, and occurrence of nutrient and organic pollution were rather well predicted; conversely, chemical (other than nutrient and organic) pollution and alteration of habitats due to hydrological or morphological changes were poorly predicted. The most important indicators explaining river conditions were the shares of agricultural and artificial land, mean annual net abstractions, share of pollution loads from point sources, and the share of upstream river length uninterrupted by barriers. The probability of failing to achieve good ecological status was estimated to be high (>60%) for 36% of the considered river network of about 1.6 M km. Occurrence of impact of nutrient pollution was estimated high (>60%) in 26% of river length and that of organic pollution 20%. The maps are built upon information reported at country level pursuant EU legal obligations, as well as indicators generated from European scale models and data: both sources are affected by epistemic uncertainty. In particular, reported information depend on data collection scoping and schemes, as well as national knowledge and interpretation of river system pressures. In turn, water pressure indicators are affected by heterogeneous biases due to incomplete or incorrect inputs and uncertainty of models adopted. Lack of effective reach- and site-scale indicators may hamper detection of locally relevant impacts, for example in explaining alteration of habitats due to morphological changes. The probability maps provide a continental snapshot of current river conditions, and offer an alternative source of information on river aquatic habitats, which may help filling in knowledge gaps. Foremost, the analysis demonstrates the need for developing more effective continental-scale indicators for hydromorphological alterations and chemical pollution.

A Bayesian network to simulate macroinvertebrate responses to multiple stressors in lowland streams

Aquatic ecosystems are affected by multiple environmental stressors across spatial and temporal scales. Yet the nature of stressor interactions and stressor-response relationships is still poorly understood. This hampers the selection of appropriate restoration measures. Hence, there is a need to understand how ecosystems respond to multiple stressors and to unravel the combined effects of the individual stressors on the ecological status of waterbodies. Models may be used to relate responses of ecosystems to environmental changes as well as to restoration measures and thus provide valuable tools for water management. Therefore, we aimed to develop and test a Bayesian Network (BN) for simulating the responses of stream macroinvertebrates to multiple stressors. Although the predictive performance may be further improved, the developed model was shown to be suitable for scenario analyses. For the selected lowland streams, an increase in macroinvertebrate-based ecological quality (EQR) was predicted for scenarios where the streams were relieved from single and multiple stressors. Especially a combination of measures increasing flow velocity and enhancing the cover of coarse particulate organic matter showed a significant increase in EQR compared to current conditions. The use of BNs was shown to be a promising avenue for scenario analyses in stream restoration management. BNs have the capacity for clear visual communication of model dependencies and the uncertainty associated with input data and results and allow the combination of multiple types of knowledge about stressor-effect relations. Still, to make predictions more robust, a deeper understanding of stressor interactions is required to parametrize model relations. Also, sufficient training data should be available for the water type of interest. Yet, the application of BNs may now already help to unravel the contribution of individual stressors to the combined effect on the ecological quality of water bodies, which in turn may aid the selection of appropriate restoration measures that lead to the desired improvements in macroinvertebrate-based ecological quality.

Modeling Water Quality in Watersheds: From Here to the Next Generation

In this synthesis, we assess present research and anticipate future development needs in modeling water quality in watersheds. We first discuss areas of potential improvement in the representation of freshwater systems pertaining to water quality, including representation of environmental interfaces, in-stream water quality and process interactions, soil health and land management, and (peri-)urban areas. In addition, we provide insights into the contemporary challenges in the practices of watershed water quality modeling, including quality control of monitoring data, model parameterization and calibration, uncertainty management, scale mismatches, and provisioning of modeling tools. Finally, we make three recommendations to provide a path forward for improving watershed water quality modeling science, infrastructure, and practices. These include building stronger collaborations between experimentalists and modelers, bridging gaps between modelers and stakeholders, and cultivating and applying procedural knowledge to better govern and support water quality modeling processes within organizations.

Phosphorus mirabilis: Illuminating the Past and Future of Phosphorus Stewardship

After its discovery in 1669, phosphorus (P) was named ("the miraculous bearer of light"), arising from the chemoluminescence when white P is exposed to the atmosphere. The metaphoric association between P and light resonates through history: from the discovery of P at the start of the Enlightenment period to the vital role of P in photosynthetic capture of light in crop and food production through to new technologies, which seek to capitalize on the interactions between novel ultrathin P allotropes and light, including photocatalysis, solar energy production, and storage. In this introduction to the special section "Celebrating the 350th Anniversary of Discovering Phosphorus-For Better or Worse," which brings together 22 paper contributions, we shine a spotlight on the historical and emerging challenges and opportunities in research and understanding of the agricultural, environmental, and societal significance of this vital element. We highlight the role of P in water quality impairment and the variable successes of P mitigation measures. We reflect on the need to improve P use efficiency and on the kaleidoscope of challenges facing efficient use of P. We discuss the requirement to focus on place-based solutions for developing effective and lasting P management. Finally, we consider how cross-disciplinary collaborations in P stewardship offer a guiding light for the future, and we explore the glimmers of hope for reconnecting our broken P cycle and the bright new horizons needed to ensure future food, water, and bioresource security for growing global populations.