Novel Analyses of Long-Term Data Provide a Scientific Basis for Chlorophyll-a Thresholds in San Francisco Bay

Spatiotemporal and vertical variability of water quality in lentic small water bodies: implications of varying rainfall and land use conditions

Lentic small water bodies (LSWBs) deteriorate owing to anthropogenic activities, such as untreated domestic and agricultural waste disposal. Moreover, different turnover mechanisms occur during different seasons, contributing to nutrient enrichment and consequent degradation of LSWBs. However, understanding their spatial, temporal, and vertical variations during different seasons is understudied. In addition, studies on the variation in water quality under varying rainfall and land-use conditions are limited. Therefore, in this study, three LSWBs located in Northern India were studied during the pre-monsoon and monsoon seasons (December 2022 to October 2023). Total nitrogen (TN), chlorophyll-a (Chl-a), total phosphorus (TP), temperature, pH, dissolved oxygen (DO), total dissolved solids (TDS), chemical oxygen demand (COD), secchi disk depth (SDD), and water level (WL) were measured monthly. Sentinel-2 and CHIRPS pentad data were used for land use, land cover classification, and rainfall analysis. The spatial analysis indicates that the seasonal shift affects the water quality distribution, especially near the inlets and at the edges. The overall concentrations of TN and TP decreased during the monsoon season; however, they increased significantly at the inlets of the LSWBs. On the other hand, the Chl-a concentration shifted towards the edges due to the inflow during the monsoon. Temporal analysis also suggests that the arrival of the monsoon lowers pH, DO, and TDS. However, the concentrations of TN and TP increased because of agricultural runoff. Chl-a and COD show distinct variations due to the individual LSWBs' local conditions. Vertical variability analysis demonstrated pH, temperature, and TN stratification during the pre-monsoon period. However, during the monsoon, stratification is less significant due to intermixing. Redundancy analysis (RDA) showed that land use and rainfall patterns affected the water quality of LSWB 1, 2, and 3 by 53.49%, 81.62%, and 92.64%, respectively. This shows that land use, land cover, and rainfall changes affect the water quality of LSWBs. This study highlights the negative impact of runoff from agricultural land use as the main factor responsible for increased nutrient levels in the LSWBs.

A cross-regional examination of patterns and environmental drivers of Pseudo-nitzschia harmful algal blooms along the California coast

Pseudo-nitzschia species with the ability to produce the neurotoxin domoic acid (DA) are the main cause of harmful algal blooms (HABs) along the U.S. West Coast, with major impacts on ecosystems, fisheries, and human health. While most Pseudo-nitzschia (PN) HAB studies to date have focused on their characteristics at specific sites, few cross-regional comparisons exist, and mechanistic understanding of large-scale HAB drivers remains incomplete. To close these gaps, we compiled a nearly 20-year time series of in situ particulate DA and environmental observations to characterize similarities and differences in PN HAB drivers along the California coast. We focus on three DA hotspots with the greatest data density: Monterey Bay, the Santa Barbara Channel, and the San Pedro Channel. Coastwise, DA outbreaks are strongly correlated with upwelling, chlorophyll-a, and silicic acid limitation relative to other nutrients. Clear differences also exist across the three regions, with contrasting responses to climate regimes across a north to south gradient. In Monterey Bay, PN HAB frequency and intensity increase under relatively nutrient-poor conditions during anomalously low upwelling intensities. In contrast, in the Santa Barbara and San Pedro Channels, PN HABs are favored under cold, nitrogen-rich conditions during more intense upwelling. These emerging patterns provide insights on ecological drivers of PN HABs that are consistent across regions and support the development of predictive capabilities for DA outbreaks along the California coast and beyond.

The impact of local and climate change drivers on the formation, dynamics, and potential recurrence of a massive fish-killing microalgal bloom in Patagonian fjord

Harmful algal blooms (HABs) in southern Chile are a serious threat to public health, tourism, artisanal fisheries, and aquaculture in this region. Ichthyotoxic HAB species have recently become a major annual threat to the Chilean salmon farming industry, due to their severe economic impacts. In early austral autumn 2021, an intense bloom of the raphidophyte Heterosigma akashiwo was detected in Comau Fjord, Chilean Patagonia, resulting in a high mortality of farmed salmon (nearly 6000 tons of biomass) within 15 days. H. akashiwo cells were first detected at the head of the fjord on March 16, 2021 (up to 478 cells mL^-1). On March 31, the cell density at the surface had reached a maximum of 2 × 10⁵ cells mL^-1, with intense brown spots visible on the water surface. Strong and persistent high-pressure anomalies over the southern tip of South America, consistent with the positive phase of the Southern Annular Mode (SAM), resulted in extremely dry conditions, high solar radiation, and strong southerly winds. A coupling of these features with the high water retention times inside the fjord can explain the spatial-temporal dynamics of this bloom event. Other factors, such as the internal local physical uplift process (favored by the north-to-south orientation of the fjord), salt-fingering events, and the uplift of subantarctic deep-water renewal, likely resulted in the injection of nutrients into the euphotic layer, which in turn could have promoted cell growth and thus high microalgal cell densities, such as reached by the bloom.

Assessment of seasonal and spatial water quality variation in a cascading lake system in Chennai, India

Water quality and scarcity are among the most severe problems humans have been facing in the last decades. India, as a fast-developing country, is not an exception. The surface water quality has deteriorated due to anthropogenic activities. Another factor which impacts the water quality is the heavy rainfall during monsoon season. To maintain the quality and the sustainability of water resources, there is the need to study how human activities impact water quality. We hypothesized that the water quality can be impacted by the spatial land use types and by the seasonality. In the present study, seasonal and spatial water quality regarding physical, chemical, and biological parameters from a lake cascading system was assessed monthly from July to December 2019. Land use/cover data was produced by Impact Observatory, Microsoft, and Esri based on the 10-m Sentinel-2 images. Redundancy analysis was applied to investigate the relationship between land use/cover data and water quality in the riparian of 500 and 1000 m to the lakes. Our results showed clear temporal and spatial variation of water quality in 2019, with better water quality in rainy season (Oct.-Dec.) and downstream lakes while relatively worse water quality was recorded in dry season (Jul.-Sep.) and upstream lakes. The water quality variation was explained 27.8 % and 42.7 % by the land use types within 500 m and 1000 m buffer widths, respectively. The outlet of the catchment showed exceptional results due to the impact of a dumpsite. Our findings indicate that the water quality is highly impacted by human-induced land use/cover. The land use/cover types, such as crops, woodland and urban area, show negative impacts and relate to the high level of nutrient concentrations. In opposite, grass land shows positive effects and leads to better water quality. Our study confirms that the lake water quality is distinguished in both spatial and seasonal aspects. Monsoon season improves the water quality.

Multi-scale trend analysis of water quality using error propagation of generalized additive models

Effective stewardship of ecosystems to sustain current ecological status or mitigate impacts requires nuanced understanding of how conditions have changed over time in response to anthropogenic pressures and natural variability. Detecting and appropriately characterizing changes requires accurate and flexible trend assessment methods that can be readily applied to environmental monitoring datasets. A key requirement is complete propagation of uncertainty through the analysis. However, this is difficult when there are mismatches between sampling frequency, period of record, and trends of interest. Here, we propose a novel application of generalized additive models (GAMs) for characterizing multi-decadal changes in water quality indicators and demonstrate its utility by analyzing a 30-year record of biweekly-to-monthly chlorophyll-a concentrations in the San Francisco Estuary. GAMs have shown promise in water quality trend analysis to separate long-term (i.e., annual or decadal) trends from seasonal variation. Our proposed methods estimate seasonal averages in a response variable with GAMs, extract uncertainty measures for the seasonal estimates, and then use the uncertainty measures with mixed-effects meta-analysis regression to quantify inter-annual trends that account for full propagation of error across methods. We first demonstrate that nearly identical descriptions of temporal changes can be obtained using different smoothing spline formulations of the original time series. We then extract seasonal averages and their standard errors for an a priori time period within each year from the GAM results. Finally, we demonstrate how across-year trends in seasonal averages can be modeled with mixed-effects meta-analysis regression that propagates uncertainties from the GAM fits to the across-year analysis. Overall, this approach leverages GAMs to smooth data with missing observations or varying sample effort across years to estimate seasonal averages and meta-analysis to estimate trends across years. Methods are provided in the wqtrends R package.

In-depth Spatiotemporal Characterization of Planktonic Archaeal and Bacterial Communities in North and South San Francisco Bay

Despite being the largest estuary on the west coast of North America, no in-depth survey of microbial communities in San Francisco Bay (SFB) waters currently exists. In this study, we analyze bacterioplankton and archaeoplankton communities at several taxonomic levels and spatial extents (i.e., North versus South Bay) to reveal patterns in alpha and beta diversity. We assess communities using high-throughput sequencing of the 16S rRNA gene in 177 water column samples collected along a 150-km transect over a 2-year monthly time-series. In North Bay, the microbial community is strongly structured by spatial salinity changes while in South Bay seasonal variations dominate community dynamics. Along the steep salinity gradient in North Bay, we find that operational taxonomic units (OTUs; 97% identity) have higher site specificity than at coarser taxonomic levels and turnover ("species" replacement) is high, revealing a distinct brackish community (in oligo-, meso-, and polyhaline samples) from fresh and marine end-members. At coarser taxonomic levels (e.g., phylum, class), taxa are broadly distributed across salinity zones (i.e., present/abundant in a large number of samples) and brackish communities appear to be a mix of fresh and marine communities. We also observe variations in brackish communities between samples with similar salinities, likely related to differences in water residence times between North and South Bay. Throughout SFB, suspended particulate matter is positively correlated with richness and influences changes in beta diversity. Within several abundant groups, including the SAR11 clade (comprising up to 30% of reads in a sample), OTUs appear to be specialized to a specific salinity range. Some other organisms also showed pronounced seasonal abundance, including Synechococcus, Ca. Actinomarina, and Nitrosopumilus-like OTUs. Overall, this study represents the first in-depth spatiotemporal survey of SFB microbial communities and provides insight into how planktonic microorganisms have specialized to different niches along the salinity gradient.

Messaging on Slow Impacts: Applying Lessons Learned from Climate Change Communication to Catalyze and Improve Marine Nutrient Communication

Building publics' understanding about human-environmental causes and impacts of nutrient pollution is difficult due to the diverse sources and, at times, extended timescales of increasing inputs, consequences to ecosystems, and recovery after remediation. Communicating environmental problems with "slow impacts" has long been a challenge for scientists, public health officials, and science communicators, as the time delay for subsequent consequences to become evident dilutes the sense of urgency to act. Fortunately, scientific research and practice in the field of climate change communication has begun to identify best practices to address these challenges. Climate change demonstrates a delay between environmental stressor and impact, and recommended practices for climate change communication illustrate how to explain and motivate action around this complex environmental problem. Climate change communication research provides scientific understanding of how people evaluate risk and scientific information about climate change. We used a qualitative coding approach to review the science communication and climate change communication literature to identify approaches that could be used for nutrients and how they could be applied. Recognizing the differences between climate change and impacts of nutrient pollution, we also explore how environmental problems with delayed impacts demand nuanced strategies for effective communication and public engagement. Applying generalizable approaches to successfully communicate the slow impacts related to nutrient pollution across geographic contexts will help build publics' understanding and urgency to act on comprehensive management of nutrient pollution, thereby increasing protection of coastal and marine environments.

Is San Francisco Bay resistant to Pseudo-nitzschia and domoic acid?

San Francisco Bay (SFB), California, USA is the largest estuary in the western United States and is home to more than 7 million people in nine counties and 101 cities. It is highly nutrient enriched and is directly connected to the Gulf of the Farallones and coastal Pacific ocean through the Golden Gate strait. The Gulf of the Farallones is one of several "hotspots" for the neurotoxin domoic acid, produced by members of the genus Pseudo-nitzschia. Despite the close proximity, SFB has few reports of harmful algal blooms and low concentrations of domoic acid, suggesting that SFB is somehow resistant to toxic blooms. Here we evaluate the potential growth and toxicity of the dominant toxigenic species in California coastal waters, P. australis and P. multiseries, to directly test the hypothesis that SFB waters confer resistance to blooms. We specifically evaluate the effect of varying temperature, salinity, and to a lesser extent, nutrients on growth and toxin production. Results show equivalent growth in SFB water (maximum growth rates of 0.71 and 1.35 d^-1 for P. multiseries and P. australis) compared to open-coast water, and comparable or greater toxicity (0 to >100 pg DA cell^-1). The historical resistance to blooms in SFB is hypothesized to be caused by a combination of insufficient acclimation time for advected Pseudo-nitzschia populations to become established and suppression of toxin production in warm waters.

Long-term trends, current status, and transitions of water quality in Chesapeake Bay

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.

How to avoid eutrophication in coastal seas? A new approach to derive river-specific combined nitrate and phosphate maximum concentrations

Since 1950, increase in nitrogen (N) and phosphorus (P) river loadings in the North-East Atlantic (NEA) continental seas has induced a deep change in the marine coastal ecosystems, leading to eutrophication symptoms in some areas. In order to recover a Good Ecological Status (GES) in the NEA, as required by European Water Framework Directive (WFD) and Marine Strategy Framework Directive (MSFD), reductions in N- and P-river loadings are necessary but they need to be minimal due to their economic impact on the farming industry. In the frame of the "EMoSEM" European project, we used two marine 3D ecological models (ECO-MARS3D, MIRO&CO) covering the Bay of Biscay, the English Channel and the southern North Sea to estimate the contributions of various sources (riverine, oceanic and atmospheric) to the winter nitrate and phosphate marine concentrations. The various distributed descriptors provided by the simulations allowed also to find a log-linear relationship between the 90th percentile of satellite-derived chlorophyll concentrations and the "fully bioavailable" nutrients, i.e. simulated nutrient concentrations weighted by light and stoichiometric limitation factors. Any GES threshold on the 90th percentile of marine chlorophyll concentration can then be translated in maximum admissible 'fully bioavailable' DIN and DIP concentrations, from which an iterative linear optimization method can compute river-specific minimal abatements of N and P loadings. The method has been applied to four major river groups, assuming either a conservative (8μgChlL^-1) or a more socially acceptable (15μgChlL^-1) GES chlorophyll concentration threshold. In the conservative case, maximum admissible winter concentrations for nutrients correspond to marine background values, whereas in the lenient case, they are close to values recommended by the WFD/MSFD. Both models suggest that to reach chlorophyll GES, strong reductions of DIN and DIP are required in the Eastern French and Belgian-Dutch river groups.

Cyanobacteria and cyanotoxins at the river-estuarine transition

We examined seasonal and longitudinal patterns in the occurrence of toxic cyanobacteria in the James River Estuary (Virginia). Highest chlorophyll and cyanobacteria levels were observed in the tidal freshwater segment, particularly during dry summers when freshwater replacement time was long. Cyanobacteria accounted for a small proportion of phytoplankton biomass (7-15%), and Microcystis comprised a small proportion of the cyanobacteria (<1%). Despite this, measureable levels of microcystin were commonly observed in water (>85% of samples in July, August and September), fish tissues (87% of planktivorous fishes) and shellfish (83% of individuals). Generic indicators of algal blooms (chlorophyll and algal biomass) had limited utility for predicting microcystin concentrations. However, chlorophyll was found to be a useful predictor for the probability of exceeding specific toxin thresholds. Tissue microcystin concentrations were highest in fish and shellfish collected from the tidal fresh segment, but were detectable in biota collected from the oligohaline at distances 50 km seaward.

Semivariance analysis and transinformation entropy for optimal redesigning of nutrients monitoring network in San Francisco bay

This paper introduces a Semivariance-Transinformation (S-T) based method for designing an optimum bay water nutrients monitoring network in San Francisco bay (S.F. bay), USA. Phosphorus and nitrogen are the most important nutrients that lead to eutrophic condition. The monthly phosphate and nitrate+nitrite data recorded during September 2006 to August 2015 was obtained over 14 active stations located at S.F. bay and was used in the research. Semivariance and discrete transinformation entropy have been applied to calculate the optimum range of the monitoring distance. The study indicated the ranges of 28 to 82 and 37 to 50km for the phosphate and nitrate+nitrite respectively. Useful information can be obtained from the monitoring network, if the monitoring distance is included in the mentioned intervals. The findings of the research introduce a new approach in the field of water quality monitoring networks design.