Identification of \u3ci\u3ePlanktothrix\u3c/i\u3e (Cyanobacteria) Blooms and Effects on the Aquatic Macroinvertebrate Community in the Non-Tidal Potomac River, USA

Using transverse cross-sectional transects, a survey of 31 km of the non-tidal Potomac River was conducted from White’s Ferry, Virginia to Brunswick, Maryland, USA, between June and September in 2013 through 2015 to assess a recurring benthic cyanobacteria bloom. Abundant benthic cyanobacteria blooms were detected during the 2014 and 2015 sampling seasons and the primary taxon was identified morphologically and molecularly as Planktothrix cf. isothrix. When present, P. cf. isothrix blooms were concentrated from river center to the Maryland shoreline. This pattern was correlated with significantly greater benthic chlorophyll-a and phycocyanin concentrations. In an apparent response to the P. cf. isothrix blooms in the study site, aquatic macroinvertebrate community assemblages were significantly different between areas with extensive benthic cyanobacterial growth compared to areas without cyanobacterial growth. Within the P. cf. isothrix mats, the percentage of pollution sensitive taxa was lower and the percentage of pollution tolerant taxa was greater. These data suggest that P. cf. isothrix can act as an ecosystem disruptor through direct impacts to the aquatic macroinvertebrate abundance and community structure within this section of the freshwater, non-tidal Potomac River

Leveraging multimission satellite data for spatiotemporally coherent cyanoHAB monitoring

Cyanobacteria harmful algal blooms (cyanoHABs) present a critical public health challenge for aquatic resource and public health managers. Satellite remote sensing is well-positioned to aid in the identification and mapping of cyanoHABs and their dynamics, giving freshwater resource managers a tool for both rapid and long-term protection of public health. Monitoring cyanoHABs in lakes and reservoirs with remote sensing requires robust processing techniques for generating accurate and consistent products across local and global scales at high revisit rates. We leveraged the high spatial and temporal resolution chlorophyll-a (Chla) and phycocyanin (PC) maps from two multispectral satellite sensors, the Sentinel-2 (S2) MultiSpectral Instrument (MSI) and the Sentinel-3 (S3) Ocean Land Colour Instrument (OLCI) respectively, to study bloom dynamics in Utah Lake, United States, for 2018. We used established Mixture Density Networks (MDNs) to map Chla from MSI and train new MDNs for PC retrieval from OLCI, using the same architecture and training dataset previously proven for PC retrieval from hyperspectral imagery. Our assessment suggests lower median uncertainties and biases (i.e., 42% and -4%, respectively) than that of existing top-performing PC algorithms. Additionally, we compared bloom trends in MDN-based PC and Chla products to those from a satellite-derived cyanobacteria cell density estimator, the cyanobacteria index (CI-cyano), to evaluate their utility in the context of public health risk management. Our comprehensive analyses indicate increased spatiotemporal coherence of bloom magnitude, frequency, occurrence, and extent of MDN-based maps compared to CI-cyano and potential for use in cyanoHAB monitoring for public health and aquatic resource managers

Phytoplankton composition from sPACE: Requirements, opportunities, and challenges

Ocean color satellites have provided a synoptic view of global phytoplankton for over 25 years through near surface measurements of the concentration of chlorophyll a. While remote sensing of ocean color has revolutionized our understanding of phytoplankton and their role in the oceanic and freshwater ecosystems, it is important to consider both total phytoplankton biomass and changes in phytoplankton community composition in order to fully understand the dynamics of the aquatic ecosystems. With the upcoming launch of NASA\u27s Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) mission, we will be entering into a new era of global hyperspectral data, and with it, increased capabilities to monitor phytoplankton diversity from space. In this paper, we analyze the needs of the user community, review existing approaches for detecting phytoplankton community composition in situ and from space, and highlight the benefits that the PACE mission will bring. Using this three-pronged approach, we highlight the challenges and gaps to be addressed by the community going forward, while offering a vision of what global phytoplankton community composition will look like through the “eyes” of PACE

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Examining the Relationship between Phytoplankton Community Structure and Water Quality Measurements in Agricultural Waters: A Machine Learning Application

Phytoplankton community composition has been utilized for water quality assessments of various freshwater sources, but studies are lacking on agricultural irrigation ponds. This work evaluated the performance of the random forest algorithm in estimating phytoplankton community structure from in situ water quality measurements at two agricultural ponds. Sampling was performed between 2017 and 2019 and measurements of three phytoplankton groups (green algae, diatoms, and cyanobacteria) and three sets of water quality parameters (physicochemical, organic constituents, and nutrients) were obtained to train and test mathematical models. Models predicting green algae populations had superior performance to the diatom and cyanobacteria models. Spatial models revealed that water in the ponds’ interior sections had lower root mean square errors (RMSEs) compared to nearshore waters. Furthermore, model performance did not change when input datasets were compounded. Models based on physicochemical parameters, which can be obtained in real time, outperformed models based on organic constituent and nutrient parameters. However, the use of nutrient parameters improved model performance when examining cyanobacteria data at the ordinal level. Overall, the random forest algorithm was useful for predicting major phytoplankton taxonomic groups in agricultural irrigation ponds, and this may help resource managers mitigate the use of cyanobacteria bloom-laden waters in agricultural applications

Examining the Relationship between Phytoplankton Community Structure and Water Quality Measurements in Agricultural Waters: A Machine Learning Application

Phytoplankton community composition has been utilized for water quality assessments of various freshwater sources, but studies are lacking on agricultural irrigation ponds. This work evaluated the performance of the random forest algorithm in estimating phytoplankton community structure from in situ water quality measurements at two agricultural ponds. Sampling was performed between 2017 and 2019 and measurements of three phytoplankton groups (green algae, diatoms, and cyanobacteria) and three sets of water quality parameters (physicochemical, organic constituents, and nutrients) were obtained to train and test mathematical models. Models predicting green algae populations had superior performance to the diatom and cyanobacteria models. Spatial models revealed that water in the ponds&rsquo; interior sections had lower root mean square errors (RMSEs) compared to nearshore waters. Furthermore, model performance did not change when input datasets were compounded. Models based on physicochemical parameters, which can be obtained in real time, outperformed models based on organic constituent and nutrient parameters. However, the use of nutrient parameters improved model performance when examining cyanobacteria data at the ordinal level. Overall, the random forest algorithm was useful for predicting major phytoplankton taxonomic groups in agricultural irrigation ponds, and this may help resource managers mitigate the use of cyanobacteria bloom-laden waters in agricultural applications

Variability in phytoplankton pigment biomass and taxonomic composition over tidal cycles in a salt marsh estuary

Tidal flow causes high temporal variability in environmental properties that impact ecosystem dynamics. Microbes such as phytoplankton are especially susceptible to tidal advection and mixing, and understanding their role in estuarine food webs and biogeochemical cycles requires information on their biomass and taxonomic composition over short time scales (e.g. tidal cycles). We conducted a survey of phytoplankton pigment biomass and taxonomic composition over complete tidal cycles in 2 salt marsh creeks on 5 sampling occasions from July to September 2000, and assessed environmental factors regulating phytoplankton properties. Tidal input of low chl a water combined with phytoplankton losses (microzooplankton grazing, oyster grazing, settling) caused large decreases in phytoplankton biomass (by 47 to 51% on average) on the flood tide, and also influenced the taxonomic composition. Depending on sampling date, pennate diatoms or flagellates were primarily reduced on the flood tide. One sampling date followed a heavy rain event, and was marked by substantial increases in tidal creek nutrient concentrations and reduced microzooplankton grazing rates, emphasizing the need to consider the combined influences of nutrients and grazing in explaining bloom formation following rain events. The high tidal variability in phytoplankton properties suggests that strict attention to tidal phase is needed in determining long-term trends or inter-estuary comparisons in phytoplankton biomass, and primary production in tidally-driven estuaries

Optical and Biochemical Properties of a Southwest Florida Whiting Event

“Whiting” in oceanography is a term used to describe a sharply defined patch of water that contains high levels of suspended, fine-grained calcium carbonate (CaCO3). Whitings have been reported in many oceanic and lake environments, and recently have been reported in southwest Florida coastal waters. Here, field and laboratory measurements were used to study optical, biological, and chemical properties of whiting waters off southwest Florida. No significant difference was found in chlorophyll a concentrations between whiting and outside waters (non-whiting water), but average particle backscattering coefficients in whiting waters were double those in outside waters, and remote sensing reflectance in whiting waters was higher at all wavelengths (400–700 nm). While other potential causes cannot be completely ruled out, particle composition and biochemical differences between sampled whiting water, contiguous water, and outside water indicate a biologically precipitated mode of whiting formation. Taxonomic examination of marine phytoplankton samples collected during a whiting event revealed a community dominated by autotrophic picoplankton and a small (\u3c10 μm), centric diatom species, identified as Thalassiosira sp. through the use of scanning electron microscopy. Amorphous to fully formed crystals of CaCO3 were observed along the girdle bands of Thalassiosira sp. cells and autotrophic picoplankton cells. Although carbonate parameters differed from whiting and contiguous to outside water, more sampling is needed to determine if these results are statistically significant