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Harmful algal blooms (HABs) are on the rise worldwide. Known drivers for the proliferation and intensification of HAB events include increasing nutrient pollution, climate change, regulation and modification of hydrological flow, and the combined effect of climate drivers and nutrient pollution. The San Francisco Bay–Delta system has largely been immune to severe or acute HAB events, but there is both a potential and realized threat which has been underestimated and under-reported, in part because of the lack of coordinated sampling and data reporting. There is also increasing evidence that HABs must be considered in the context of a freshwater-to-marine continuum, and that the physical and political boundaries separating components of the Bay–Delta system are porous barriers to HABs and their toxins. Much remains to be learned about the ecology and physiology of HAB organisms in this system, but five primary environmental drivers can be identified: temperature, salinity, irradiance, nutrients, and stratification/residence time. All these drivers are responding rapidly to climate change, but nutrients are the primary variable that is largely under human control. Plans for the development of a comprehensive monitoring, prediction, and mitigation strategy across the freshwater-to-marine continuum have been documented; effectively following through on these plans provides a roadmap toward identifying the drivers and threats—and reducing the potential consequences now and in the future. While HABs alone are not a sufficient motivator for potentially costly and extensive mitigation efforts, there is strong evidence that decreasing nutrient loads, maintaining hydrological connectivity while minimizing stagnant regions, and managing the biota to maintain biodiversity of the Bay–Delta system will result in multiple co-benefits, including reduction of the HAB threat potential.

If we're lucky, most of us never come face-to-face with true devastation. For the residents of New Jersey's Barnegat Bay-Little Egg Harbor Estuary--no strangers to coastal storms--that luck ran out [...]

Estuarine-coastal ecosystems are rich areas of the global ocean with elevated rates of organic matter production supporting major fisheries. Net and gross primary production (NPP, GPP) are essential properties of these ecosystems, characterized by high spatial, seasonal, and inter-annual variability associated with climatic effects on hydrology. Over 20 years ago, Nixon defined the trophic classification of marine ecosystems based on annual phytoplankton primary production (APPP), with categories ranging from "oligotrophic" to "hypertrophic". Source data consisting of shipboard measurements of NPP and GPP from 1982 to 2004 for Chesapeake Bay in the mid-Atlantic region of the United States supported estimates of APPP from 300 to 500 g C m-2 yr-1, corresponding to "eutrophic" to "hypertrophic" categories. Here, we developed generalized additive models (GAM) to interpolate the limited spatio-temporal resolution of source data. Principal goals were: (1) to develop predictive models of NPP and GPP calibrated to source data (1982 to 2004); (2) to apply the models to historical (1960s, 1970s) and monitoring (1985 to 2015) data with adjustments for nutrient loadings and climatic effects; (3) to estimate APPP from model predictions of NPP; (4) to test effects of simulated reductions of phytoplankton biomass or nutrient loadings on trophic classification based on APPP. Simulated 40% decreases of euphotic-layer chl-a or TN and NO2 + NO3 loadings led to decreasing APPP sufficient to change trophic classification from "eutrophic' to "mesotrophic" for oligohaline (OH) and polyhaline (PH) salinity zones, and from "hypertrophic" to "eutrophic" for the mesohaline (MH) salinity zone of the bay. These findings show that improved water quality is attainable with sustained reversal of nutrient over-enrichment sufficient to decrease phytoplankton biomass and APPP.

Coincident climatic and human effects strongly influence water-quality properties in estuarine-coastal ecosystems around the world. Time-series data for a number of ecosystems reveal high spatio-temporal variability superimposed on secular trends traceable to nutrient over-enrichment. In this paper, we present new analyses of long-term data for Chesapeake Bay directed at several goals: (1) to distinguish trends from spatio-temporal variability imposed by climatic effects; (2) to assess long-term trends of water-quality properties reflecting degradation and recovery; (3) to propose numerical water-quality criteria as targets for restoration; (4) to assess progress toward attainment of these targets. The bay has experienced multiple impairments associated with nutrient over-enrichment since World War II, e.g., low dissolved oxygen (DO), decreased water clarity, and harmful algal blooms (HAB). Anthropogenic eutrophication has been expressed as increased chlorophyll-a (chl-a) driven by accelerated nutrient loading from 1945 to 1980. Management intervention led to decreased loading thereafter, but deleterious symptoms of excess nutrients persist. Climatic effects exemplified by irregular "dry" and "wet" periods in the last 30+ years largely explain high inter-annual variability of water-quality properties, requiring adjustments to resolve long-term trends. Here, we extend these analyses at a finer temporal scale to six decades of chl-a, Secchi depth, and nitrite plus nitrate (NO2 + NO3) data to support trend analyses and the development of numerical water-quality criteria. The proposed criteria build on a conceptual model emphasizing the need to distinguish climatic and human effects in gauging progress to reverse eutrophication in estuarine-coastal ecosystems.

Lake Erie, USA–Canada, plays an important ecological and socioeconomic role but has suffered from chronic eutrophication. In particular, western Lake Erie (WLE) is the site of harmful algal blooms (HABs) which are suspected of being driven by excessive nutrient (phosphorus (P) and nitrogen (N)) inputs. During 2022 and 2023, in situ nutrient dilution and addition bioassays were conducted at a WLE bloom‐impacted location to investigate whether a nutrient reduction regime would be effective in limiting phytoplankton growth during the June diatom‐dominated spring blooms and August cyanobacteria‐dominated summer blooms. The primary objectives of this experiment were to (1) Determine if a proposed 40% P‐alone reduction would effectively reduce phytoplankton growth and mitigate blooms and (2) assess whether reductions in both P and N are more effective in controlling phytoplankton biomass than exclusive reductions in either N or P. Samples were analyzed for nutrient concentrations and growth rate responses for specific algal groups, utilizing diagnostic (for major algal groups) photopigments. Results indicated that although both 20% and 40% dilutions led to lower phytoplankton biomass and growth rates, 40% reductions were more effective. Our results support the USA–Canada Great Lakes Water Quality Agreement recommendation of a 40% P reduction, but also indicate that a parallel reduction of N input by 40% would be most effective in controlling bloom magnitudes. Overall, our findings underscore the recommendation that a year‐round dual N and P 40% reduction is needed for long‐term control of eutrophication and algal blooms, including cyanobacteria and diatoms, in Lake Erie. [ABSTRACT FROM AUTHOR]

Terrestrial hydrological and nutrient cycles are subjected to major disturbances by agricultural operations and urbanization that profoundly influence freshwater resources. Non‐point source pollution is one of the primary causes for water quality deterioration, and thus an emerging imperative in limnology is establishing empirical models that connect watershed attributes and hydrological drivers with lake nutrient dynamics. Here, we compiled three nation‐wide nutrient, meteorological, and watershed‐landscape data sets, to develop Generalized Linear Models that predict lake phosphorus and nitrogen concentrations as a function of the surrounding watershed characteristics within various hydrological distances across 104 Chinese lakes and reservoirs. Our national‐scale investigation revealed that lake nutrient concentrations can be satisfactorily predicted by proxies of natural drivers and anthropogenic activities, reflecting the properties of the surrounding watershed. Counter to previous studies, we found that China's lake nutrient concentrations strongly depend on watershed characteristics within a hydrological distance of less than 45 km rather than the entire watershed. Furthermore, extensive human activities in watersheds not only compromise our predictive capacity, but also increase the hydrological distance that is relevant to predict lake nutrients. This national‐scale characterization can inform one of the most contentious issues in the context of China's lake management, that is, the determination of the extent of the nearshore area, where nutrient control should be prioritized. As far as we know, our study represents the first attempt to apply the concept of hydrological distance and establish statistical models that can delineate the critical spatial domain primarily responsible for the nutrient conditions along the watershed‐lake continuum. Plain Language Summary: Connecting watershed attributes with lake water quality at multiple scales is an emerging imperative in limnology. This study introduces the concept of hydrological distance and establish lake‐watershed relationships based on a comprehensive water quality data set from 2,424 sampling sites across China. Our key finding is that lake nutrient levels strongly depend on watershed features within a <45 km hydrological distance rather than the entire watershed. Activities related to agriculture and urbanization increase the relevant hydrological distance to modulate lake nutrient levels, and our national‐scale analysis provides evidence that areas with discernible impact can be located far from the vicinity of a given lake. Key Points: China's lake nutrient concentrations can be accurately predicted by watershed attributesChina's lake nutrient levels depended on watershed features within a <45 km hydrological distanceHuman footprint increases the relevant hydrological distance to predict water quality for China's lakes [ABSTRACT FROM AUTHOR]

In early August 2014, the municipality of Toledo, OH (USA) issued a 'do not drink' advisory on their water supply directly affecting over 400,000 residential customers and hundreds of businesses (Wilson, 2014). This order was attributable to levels of microcystin, a potent liver toxin, which rose to 2.5μgL-1 in finished drinking water. The Toledo crisis afforded an opportunity to bring together scientists from around the world to share ideas regarding factors that contribute to bloom formation and toxigenicity, bloom and toxin detection as well as prevention and remediation of bloom events. These discussions took place at an NSF- and NOAA-sponsored workshop at Bowling Green State University on April 13 and 14, 2015. In all, more than 100 attendees from six countries and 15 US states gathered together to share their perspectives. The purpose of this review is to present the consensus summary of these issues that emerged from discussions at the Workshop. As additional reports in this special issue provide detailed reviews on many major CHAB species, this paper focuses on the general themes common to all blooms, such as bloom detection, modeling, nutrient loading, and strategies to reduce nutrients.

This article discusses the importance of accurate scientific communication through press releases and the potential consequences of disseminating inaccurate information. The authors address a specific press release about the water clarity of Lake Tahoe, which incorrectly attributed the improvement in clarity to zooplankton. They argue that the data and peer-reviewed scientific literature contradict this claim and suggest that other factors, such as sediment inputs and climate dynamics, are responsible for the changes in clarity. The authors also provide recommendations for improving the communication of scientific information through press releases, emphasizing the need for peer review and open data sharing. [Extracted from the article]