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Lake Erie is a classic case of development, recovery from, and return to eutrophication, hypoxia, and harmful algal blooms. Forecast models are used annually to predict bloom intensity for the whole Western Lake Erie Basin, but do not necessarily reflect nearshore conditions or regional variations, which are important for local stakeholders. In this study we: 1) developed relationships between observed whole basin and nearshore bloom sizes, and 2) updated and extended a Bayesian seasonal bloom forecast model to provide new regional predictions. The western basin was subdivided into 5 km near-shore regions, and bloom start date, size, and intensity were quantified with MODIS-derived images of chlorophyll concentrations for July–October 2002–2016 for each subdivision and for the entire basin. While bloom severity within each subdivision is temporally and spatially unique, it increased over the study period in each subdivision. The models for the 5 km subdivisions explained between 83 and 95% of variability between regional sizes and whole bloom size for US subdivisions and 51% for the Canadian subdivision. By linking predictive basin-wide models to regional regression estimates, we are now able to better predict potential bloom impacts at scales and in specific areas that are vital to the economic well-being of the region and allow for better management responses.

Ecological forecasts are quantitative tools that can guide ecosystem management. The coemergence of extensive environmental monitoring and quantitative frameworks allows for widespread development and continued improvement of ecological forecasting systems. We use a relatively simple estuarine hypoxia model to demonstrate advances in addressing some of the most critical challenges and opportunities of contemporary ecological forecasting, including predictive accuracy, uncertainty characterization, and management relevance. We explore the impacts of different combinations of forecast metrics, drivers, and driver time windows on predictive performance. We also incorporate multiple sets of state‐variable observations from different sources and separately quantify model prediction error and measurement uncertainty through a flexible Bayesian hierarchical framework. Results illustrate the benefits of (1) adopting forecast metrics and drivers that strike an optimal balance between predictability and relevance to management, (2) incorporating multiple data sources in the calibration data set to separate and propagate different sources of uncertainty, and (3) using the model in scenario mode to probabilistically evaluate the effects of alternative management decisions on future ecosystem state. In the Chesapeake Bay, the subject of this case study, we find that average summer or total annual hypoxia metrics are more predictable than monthly metrics and that measurement error represents an important source of uncertainty. Application of the model in scenario mode suggests that absent watershed management actions over the past decades, long‐term average hypoxia would have increased by 7% compared to 1985. Conversely, the model projects that if management goals currently in place to restore the Bay are met, long‐term average hypoxia would eventually decrease by 32% with respect to the mid‐1980s.

A large region of low-dissolved-oxygen bottom waters (hypoxia) forms nearly every summer in the northern Gulf of Mexico because of nutrient inputs from the Mississippi River Basin and water column stratification. Policymakers developed goals to reduce the area of hypoxic extent because of its ecological, economic, and commercial fisheries impacts. However, the goals remain elusive after 30 y of research and monitoring and 15 y of goal-setting and assessment because there has been little change in river nitrogen concentrations. An intergovernmental Task Force recently extended to 2035 the deadline for achieving the goal of a 5,000-km2 5-y average hypoxic zone and set an interim load target of a 20% reduction of the spring nitrogen loading from the Mississippi River by 2025 as part of their adaptive management process. The Task Force has asked modelers to reassess the loading reduction required to achieve the 2035 goal and to determine the effect of the 20% interim load reduction. Here, we address both questions using a probabilistic ensemble of four substantially different hypoxia models. Our results indicate that, under typical weather conditions, a 59% reduction in Mississippi River nitrogen load is required to reduce hypoxic area to 5,000 km2 The interim goal of a 20% load reduction is expected to produce an 18% reduction in hypoxic area over the long term. However, due to substantial interannual variability, a 25% load reduction is required before there is 95% certainty of observing any hypoxic area reduction between consecutive 5-y assessment periods.

In response to degraded water quality, federal policy makers in the US and Canada called for a 40% reduction in phosphorus (P) loads to Lake Erie, and state and provincial policy makers in the Great Lakes region set a load-reduction target for the year 2025. Here, we configured five separate SWAT (US Department of Agriculture's Soil and Water Assessment Tool) models to assess load reduction strategies for the agriculturally dominated Maumee River watershed, the largest P source contributing to toxic algal blooms in Lake Erie. Although several potential pathways may achieve the target loads, our results show that any successful pathway will require large-scale implementation of multiple practices. For example, one successful pathway involved targeting 50% of row cropland that has the highest P loss in the watershed with a combination of three practices: subsurface application of P fertilizers, planting cereal rye as a winter cover crop, and installing buffer strips. Achieving these levels of implementation will require local, state/provincial, and federal agencies to collaborate with the private sector to set shared implementation goals and to demand innovation and honest assessments of water quality-related programs, policies, and partnerships.

Cyanobacteria blooms are a major environmental issue worldwide. Our understanding of the biophysical processes driving cyanobacterial proliferation and the ability to develop predictive models that inform resource managers and policy makers rely upon the accurate characterization of bloom dynamics. Models quantifying relationships between bloom severity and environmental drivers are often calibrated to an individual set of bloom observations, and few studies have assessed whether differences among observing platforms could lead to contrasting results in terms of relevant bloom predictors and their estimated influence on bloom severity. The aim of this study was to assess the degree of coherence of different monitoring methods in (1) capturing short- and long-term cyanobacteria bloom dynamics and (2) identifying environmental drivers associated with bloom variability. Using western Lake Erie as a case study, we applied boosted regression tree (BRT) models to long-term time series of cyanobacteria bloom estimates from multiple in-situ and remote sensing approaches to quantify the relative influence of physico-chemical and meteorological drivers on bloom variability. Results of BRT models showed remarkable consistency with known ecological requirements of cyanobacteria (e.g., nutrient loading, water temperature, and tributary discharge). However, discrepancies in inter-annual and intra-seasonal bloom dynamics across monitoring approaches led to some inconsistencies in the relative importance, shape, and sign of the modeled relationships between select environmental drivers and bloom severity. This was especially true for variables characterized by high short-term variability, such as wind forcing. These discrepancies might have implications for our understanding of the role of different environmental drivers in regulating bloom dynamics, and subsequently for the development of models capable of informing management and decision making. Our results highlight the need to develop methods to integrate multiple data sources to better characterize bloom spatio-temporal variability and improve our ability to understand and predict cyanobacteria blooms.

A first synoptic and trans-domain overview of plankton dynamics was conducted across the aquatic sites belonging to the Italian Long-Term Ecological Research Network (LTER-Italy). Based on published studies, checked and complemented with unpublished information, we investigated phytoplankton and zooplankton annual dynamics and long-term changes across domains: from the large subalpine lakes to mountain lakes and artificial lakes, from lagoons to marine coastal ecosystems. This study permitted identifying common and unique environmental drivers and ecological functional processes controlling seasonal and long-term temporal course. The most relevant patterns of plankton seasonal succession were revealed, showing that the driving factors were nutrient availability, stratification regime, and freshwater inflow. Phytoplankton and mesozooplankton displayed a wide interannual variability at most sites. Unidirectional or linear long-term trends were rarely detected but all sites were impacted across the years by at least one, but in many case several major stressor(s): nutrient inputs, meteo-climatic variability at the local and regional scale, and direct human activities at specific sites. Different climatic and anthropic forcings frequently co-occurred, whereby the responses of plankton communities were the result of this environmental complexity. Overall, the LTER investigations are providing an unparalleled framework of knowledge to evaluate changes in the aquatic pelagic systems and management options.

Harmful algal blooms (HABs) have increased in frequency and magnitude in western Lake Erie and spring phosphorus (P) load was shown to be a key driver of bloom intensity. A recently developed Bayesian hierarchical model that predicts peak bloom size as a function of Maumee River phosphorus load suggested an apparent increased susceptibility of the lake to HABs. We applied that model to develop load–response curves to inform revision of Lake Erie phosphorus load targets under the 2012 Great Lakes Water Quality Agreement. In this application, the model was modified to estimate the fraction of the particulate P (PP) load that becomes bioavailable, and it was recalibrated with additional bloom observations. Although the uncertainty surrounding the estimate of the bioavailable PP fraction is large, inclusion in the model improves prediction of bloom variability compared to dissolved reactive P (DRP) alone. The ability to characterize model and measurement uncertainty through hierarchical modeling allowed us to show that inconsistencies in bloom measurement represent a considerable portion of the overall uncertainty associated with load–response curves. The updated calibration also lends support to the system's apparent enhanced susceptibility to blooms. The temporal trend estimated by the model results in an upward shift of the load–response curve over time such that a larger load reduction is required to achieve a target bloom size today compared to earlier years. More research is needed to further test the hypothesis of a shift in the lake's response to stressors over time and, if confirmed, to explore underlying mechanisms.

In response to water quality changes in the Great Lakes since implementing the 1978 Amendment to the Great Lakes Water Quality Agreement, the US and Canada renegotiated the agreement in 2012, requiring the governments to review and revise phosphorus (P) load targets, starting with Lake Erie. In response, the governments supported a multi-model team to evaluate the existing objectives and P load targets for Lake Erie and provide the information needed to update those targets. Herein, we describe the process and resulting advice provided to the binational process. The collective modeling effort concluded that avoiding severe Western Basin (WB) cyanobacteria blooms requires: 1) focusing on reducing total P loading from the Maumee River, with an emphasis on high-flow events during March–July, 2) focusing on dissolved reactive P load alone will not be sufficient because there is significant bioavailable P in the particulate phosphorus portion of the load, and 3) loading from the Detroit River is not a driver of cyanobacteria blooms. Reducing Central Basin (CB) hypoxia requires a CB + WB load reduction greater than what is needed to reach the WB cyanobacteria biomass goal. Achieving Cladophora thresholds will be challenging without site-specific load reductions, and more research is needed.

The variability in water quality and zooplankton community structure during downstream transport was investigated in the Po river (Italy) using for the first time a Lagrangian sampling approach. Two surveys were conducted, one in spring under relatively high discharge levels, and one at low flows in summer. Twelve stations along a 332-km stretch of the river's lowland reach and four major tributaries were sampled. A hydrodynamic modelling system was used to determine water transport time along the river, with a satisfying fit between simulated and observed discharge values. No clear downstream trend in phosphorus and nitrogen concentrations was found. Conversely, a marked longitudinal decrease in dissolved silica supports the hypothesis of increasing downstream silica limitation during the phytoplankton growing season. In spring, at low residence time, no apparent plankton growth was observed during downstream transport. In summer, higher temperatures and lower turbulence and turbidity associated with longer residence time stimulated algal growth and in-stream reproduction of fast-growing rotifer taxa, with the gradual downstream development of a truly potamal assemblage and the increase of the ratio of euplanktonic to littoral/epibenthic rotifer taxa. Crustacean zooplankton density was generally low. The importance of biotic interactions within the zooplankton in driving community abundance and composition appeared to increase in the downstream direction, paralleled by a decrease in the influence of physical forcing. Tributary influence was especially evident where severe anthropogenic alterations of river hydrology and trophic status resulted in enhanced plankton growth, ultimately affecting zooplankton structure in the main river. Copyright © 2016 John Wiley & Sons, Ltd.

Extreme climatic events, such as heatwaves and droughts, are occurring more frequently in many regions of the world. Lakes may be especially vulnerable to climatic perturbations, which can trigger sudden ecosystem changes through alterations in the hydrologic regime. However, the nature of lake response to climatic extremes, and associated long-term ecosystem-level implications are difficult to predict, due to the paucity of time series allowing exploration of ecosystem behavior before, during, and after extreme events. We investigated the impacts of the 2003 European heatwave on a small, stratifying lake by analyzing available limnological data between 1986 and 2012. In summer 2003, a shift from an unvegetated to a macrophyte-dominated regime occurred, due to the rapid spread of a benthic charophyte. We explored candidate mechanisms driving the shift by comparing empirical observations with the outcome of a model on lake alternative states parameterized for our study lake. Our results support the hypothesis that enhanced light availability due to a heatwave-induced decrease in water level drove the switch in dominant primary producers. The spread of the charophyte was associated with strong depletion of inorganic nutrients and suppression of the typical summer phytoplankton peak. These bottom-up interactions triggered cascading effects at higher trophic levels, inducing a decline in herbivorous zooplankters with high food requirements and in predatory taxa. Some of the changes in the lake food web persist through the available time series. If incidence of heatwaves increases, as projected across temperate regions, our findings suggest that abrupt and long-lasting ecosystem-level reorganizations may occur in small, stratifying lakes.

Introduction of alien species is one of the major threats to aquatic biota and knowledge of the major correlates of their occurrence is pivotal in planning reliable conservation strategies. 2. To understand whether specific freshwater habitats are more likely to be invaded than others, a dataset on the occurrence of 1604 species in 54 taxonomic groups from 181 sites across the Italian peninsula was gathered. 3. TheEUNIShabitatclassificationwas used, selectingfor the study's seven habitat types at thesecondEUNIS level, including lentic (EUNIS C1; 64 sites), lotic (EUNIS C2; 99 sites) and highly artificial (EUNIS J5; 18 sites) habitats. 4. The aim of the study was to test whether the overall number of alien species and the proportion of alien species for each taxonomic group differed between habitat types and could be explained by environmental, human-mediated, or climatic factors. 5. Using generalized linear mixed effect models to account for potential confounding factors, only average air temperature of the site was a significant positive predictor of the occurrence of alien species, regardless of habitat type, species richness, and other climatic variables. 6. A direct effect of temperature could be excluded given the origin of alien species, mostly from colder areas than Italy. Thus, an indirect effect could be hypothesized at the Italian latitudes, with warmer areas potentially

Trait-mediated biotic interactions within zooplankton, such as inducible defences against predation, are key determinants of community structure and dynamics in lentic ecosystems. The role of such interactions in lotic environments, however, has been rarely investigated, as abiotic constraints related to hydrology are generally thought to impair the occurrence of biotic interactions in rivers. We hypothesize that, under conditions of reduced flow during summer, trait-mediated predator–prey interactions can be significant driving forces in the main channel of a large river, despite the disruptive effect of downstream transport. To verify this assumption, we carried out a field study in the lowland stretch of the Po River (Italy). We analysed temporal patterns of morphometric variation in a population of Brachionus calyciflorus, potentially triggered by the predatory rotifer Asplanchna brightwellii. Our results indicate that the presence of Asplanchna can impact the variability of different morphological traits in B. calyciflorus even under the disturbance effect of turbulence and drift. Asplanchna feeding electivity on several taxa was also investigated, confirming the predator ability to efficiently and selectively feed under lotic conditions. We suggest that complex interactions and trade-offs might occur among life-history traits, predator–prey relationships and physical constraints imposed by flow within zooplankton communities in large rivers.

While the importance of biotic interactions in shaping zooplankton communities has long been established in lentic environments, river plankton is traditionally thought to be primarily abiotically constrained. The role of interactions among zooplankters has thus only occasionally been examined and mainly regarded as secondary or negligible in rivers. This study addresses the question whether and under which conditions biotic interactions within the zooplankton can become the chief drivers of community structure and dynamics in riverine environments. A short-term, high-frequency sampling campaign was performed in the potamal reach of the Po River (Italy). To test for the presence of association patterns among zooplankters, which might be suggestive of potential trophic interactions (predation/competition), taxa were aggregated into functional groups according to their feeding ecology, and time series of their abundances were analysed by means of a variance ratio test, which revealed the occurrence of compensatory dynamics among functional groups under low and stable, although truly advective, discharge conditions. Evidence on the importance of predator–prey interactions and intrapopulation regulation mechanisms also came from further analyses of the dominant predator’s gut contents and of the main prey population dynamics. Our results show that, under certain conditions, zooplankton exhibit internal, self-regulatory mechanisms also in the main current of large rivers. The view of riverine zooplankton as a mere assemblage of taxa exclusively abiotically controlled is therefore oversimplified.

In recent years, phenology has been proposed as an indicator to monitor systematically the state of the ecosystem and to detect changes triggered by perturbation of the environmental conditions. Recorded changes in the seasonal timing allowed often to evaluate re-organizations of communities and drastic alterations to ecosystem structure. The European LTER represents one of the most important network in the collection of long time series ecological in Europe. EnvEurope Life+ project is working to integrate and harmonize long-term ecological research initiatives at European level, focusing on understanding the status, changes and trends of ecosystems. This preliminary work give an example on how the Europe LTER networks can make a contribution to compare the effect of changes in physical forcing or climatic modes on the ecosystem around Europe. The aims of this study are to (i) provide a standardized assessment of the rates phenological indexes in the LTER Europe aquatic sites (ii) evaluate changes in phenological indexes in relationship with ecological drivers (climate indices and physical parameters). For this work were collected monthly data from 15 LTER sites for a period from the '80s to today. Before to start with statistical analysis, harmonization of units of measure and selection of the sites has been performed. Will present the results of the descriptive analysis, and the results about pattern and rates of phenological indexes.

Surveys on the zooplankton of the middle reach of the Po River (Northern Italy) carried out from 2008 to 2010 led to the discovery of 24 species of monogonont rotifers that are new for Italy. Among the 17 recorded genera, six are new for the Italian fauna, while three species have never been reported in the Palaearctic Region before. Temporal patterns, abundance and site of occurrence of the species are provided. Available information on the ecology and distribution of each taxon was derived from the literature and is also reported. Most of the new records are littoral and/or benthic-periphytic taxa. Results of the present study underline the still unsatisfactory status of present biogeographical knowledge on monogonont rotifers and the need for detailed taxonomic surveys in order to improve our understanding of the ecology and distributional patterns of this group.