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Telesh I, Schubert H, Skarlato S. Wide ecological niches ensure frequent harmful dinoflagellate blooms. Heliyon 2024; 10:e26495. [PMID: 38404903 PMCID: PMC10884921 DOI: 10.1016/j.heliyon.2024.e26495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 02/08/2024] [Accepted: 02/14/2024] [Indexed: 02/27/2024] Open
Abstract
Harmful algal blooms (HABs) and their consequences cause multiple devastating effects in various freshwater, brackish and marine ecosystems. However, HAB species at moderate population densities have positive ecological roles as primary producers of organic matter and food for zooplankton and fish. They also enhance benthic-pelagic coupling and participate in the biogeochemical cycles. The consequences of HABs are transported across the conventional environmental boundaries by numerous cascade effects in the food webs and beyond. Meanwhile, forecasts of bloom events are still limited, largely because of scarcity of reliable information on ecological niches of the bloom-forming algae. To fill up this knowledge gap, this study focused on dinoflagellates, a diverse group of mostly photosynthesizing protists (unicellular eukaryotes) capable of mixotrophy, since they play a key role in primary production and formation of blooms in marine and brackish waters worldwide. In this study, ecological niches of 17 abundant bloom-forming dinoflagellate species from coastal regions of the southern Baltic Sea were identified for the first time. It was hypothesized that wider ecological niches ensure more frequent dinoflagellate blooms compared to the species with narrower niches. This hypothesis was verified using the long-term (44 years) database on phytoplankton abundance and physical-chemical characteristics of the environment. It were analyzed 4534 datasets collected from 1972 to 2016. Fourteen abiotic parameters (water temperature, salinity, Secchi depth, pH, Chl a, and concentration of basic nutrients) were considered as ecological niche dimensions. The Principal Component Analysis presented the dissolved inorganic nitrogen, total nitrogen, Chl a, and temperature as principal niche dimensions of dinoflagellates. The algal bloom criteria were refined. It was for the first time proved statistically that HAB frequency of dinoflagellate species robustly correlated with the width of their ecological niches.
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Affiliation(s)
- Irena Telesh
- Zoological Institute of the Russian Academy of Sciences, St. Petersburg 199034, Russia
| | - Hendrik Schubert
- Institute of Biological Sciences, University of Rostock, Rostock 18059, Germany
| | - Sergei Skarlato
- Institute of Cytology of the Russian Academy of Sciences, St. Petersburg 194064, Russia
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Lopez Barreto BN, Hestir EL, Lee CM, Beutel MW. Satellite Remote Sensing: A Tool to Support Harmful Algal Bloom Monitoring and Recreational Health Advisories in a California Reservoir. GEOHEALTH 2024; 8:e2023GH000941. [PMID: 38404693 PMCID: PMC10885757 DOI: 10.1029/2023gh000941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 12/08/2023] [Accepted: 01/31/2024] [Indexed: 02/27/2024]
Abstract
Cyanobacterial harmful algal blooms (cyanoHABs) can harm people, animals, and affect consumptive and recreational use of inland waters. Monitoring cyanoHABs is often limited. However, chlorophyll-a (chl-a) is a common water quality metric and has been shown to have a relationship with cyanobacteria. The World Health Organization (WHO) recently updated their previous 1999 cyanoHAB guidance values (GVs) to be more practical by basing the GVs on chl-a concentration rather than cyanobacterial counts. This creates an opportunity for widespread cyanoHAB monitoring based on chl-a proxies, with satellite remote sensing (SRS) being a potentially powerful tool. We used Sentinel-2 (S2) and Sentinel-3 (S3) to map chl-a and cyanobacteria, respectively, classified chl-a values according to WHO GVs, and then compared them to cyanotoxin advisories issued by the California Department of Water Resources (DWR) at San Luis Reservoir, key infrastructure in California's water system. We found reasonably high rates of total agreement between advisories by DWR and SRS, however rates of agreement varied for S2 based on algorithm. Total agreement was 83% for S3, and 52%-79% for S2. False positive and false negative rates for S3 were 12% and 23%, respectively. S2 had 12%-80% false positive rate and 0%-38% false negative rate, depending on algorithm. Using SRS-based chl-a GVs as an early indicator for possible exposure advisories and as a trigger for in situ sampling may be effective to improve public health warnings. Implementing SRS for cyanoHAB monitoring could fill temporal data gaps and provide greater spatial information not available from in situ measurements alone.
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Affiliation(s)
- Brittany N. Lopez Barreto
- Environmental Systems Graduate GroupDepartment of Civil & Environmental EngineeringUniversity of California MercedMercedCAUSA
- Center for Information Technology Research in the Interest of SocietyThe Banatao InstituteUniversity of California MercedMercedCAUSA
| | - Erin L. Hestir
- Environmental Systems Graduate GroupDepartment of Civil & Environmental EngineeringUniversity of California MercedMercedCAUSA
- Center for Information Technology Research in the Interest of SocietyThe Banatao InstituteUniversity of California MercedMercedCAUSA
| | - Christine M. Lee
- NASA Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Marc W. Beutel
- Environmental Systems Graduate GroupDepartment of Civil & Environmental EngineeringUniversity of California MercedMercedCAUSA
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Murray JF, Lavery AM, Schaeffer BA, Seegers BN, Pennington AF, Hilborn ED, Boerger S, Runkle JD, Loftin K, Graham J, Stumpf R, Koch A, Backer L. Assessing the relationship between cyanobacterial blooms and respiratory-related hospital visits: Green bay, Wisconsin 2017-2019. Int J Hyg Environ Health 2024; 255:114272. [PMID: 37871346 DOI: 10.1016/j.ijheh.2023.114272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 09/25/2023] [Accepted: 10/04/2023] [Indexed: 10/25/2023]
Abstract
Potential acute and chronic human health effects associated with exposure to cyanobacteria and cyanotoxins, including respiratory symptoms, are an understudied public health concern. We examined the relationship between estimated cyanobacteria biomass and the frequency of respiratory-related hospital visits for residents living near Green Bay, Lake Michigan, Wisconsin during 2017-2019. Remote sensing data from the Cyanobacteria Assessment Network was used to approximate cyanobacteria exposure through creation of a metric for cyanobacteria chlorophyll-a (ChlBS). We obtained counts of hospital visits for asthma, wheezing, and allergic rhinitis from the Wisconsin Hospital Association for ZIP codes within a 3-mile radius of Green Bay. We analyzed weekly counts of hospital visits versus cyanobacteria, which was modelled as a continuous measure (ChlBS) or categorized according to World Health Organization's (WHO) alert levels using Poisson generalized linear models. Our data included 2743 individual hospital visits and 114 weeks of satellite derived cyanobacteria biomass indicator data. Peak values of ChlBS were observed between the months of June and October. Using the WHO alert levels, 60% of weeks were categorized as no risk, 19% as Vigilance Level, 15% as Alert Level 1, and 6% as Alert Level 2. In Poisson regression models adjusted for temperature, dewpoint, season, and year, there was no association between ChlBS and hospital visits (rate ratio [RR] [95% Confidence Interval (CI)] = 0.98 [0.77, 1.24]). There was also no consistent association between WHO alert level and hospital visits when adjusting for covariates (Vigilance Level: RR [95% CI] 0.88 [0.74, 1.05], Alert Level 1: 0.82 [0.67, 0.99], Alert Level 2: 0.98 [0.77, 1.24], compared to the reference no risk category). Our methodology and model provide a template for future studies that assess the association between cyanobacterial blooms and respiratory health.
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Affiliation(s)
- Jordan F Murray
- University of Wisconsin-Madison School of Medicine and Public Health, 610 Walnut St, Madison, WI, 53726, United States; Wisconsin Department of Health Services, 1 West Wilson St, Madison, WI, 53703, United States.
| | - Amy M Lavery
- Division of Environmental Health Science and Practice, National Center for Environmental Health, Centers for Disease Control and Prevention, 1600 Clifton Road, Atlanta, GA, 30329, United States
| | - Blake A Schaeffer
- Environmental Protection Agency, Office of Research and Development, Research Triangle Park, NC, 27711, United States
| | - Bridget N Seegers
- GESTAR II, Morgan State University, Baltimore, MD, United States; Ocean Ecology Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, United States
| | - Audrey F Pennington
- Division of Environmental Health Science and Practice, National Center for Environmental Health, Centers for Disease Control and Prevention, 1600 Clifton Road, Atlanta, GA, 30329, United States
| | - Elizabeth D Hilborn
- Environmental Protection Agency, Office of Research and Development, Research Triangle Park, NC, 27711, United States
| | - Savannah Boerger
- Oak Ridge Institute for Science and Education, 1299 Bethel Valley Rd, Oak Ridge, TN, 37830, United States
| | - Jennifer D Runkle
- North Carolina Institute for Climate Studies, North Carolina State University, The Cooperative Institute for Satellite Earth Systems Studies, NOAA National Centers for Environmental Information, 151 Patton Ave, Asheville, NC, 28801i, United States; Geological Survey, 1217 Biltmore Dr, Lawrence, KS, 66049, United States
| | - Keith Loftin
- U. S. Geological Survey, 1217 Biltmore Drive, Lawrence, KS, 66049, United States
| | - Jennifer Graham
- U.S. Geological Survey, 425 Jordan Road, Troy, NY, 12180, United States
| | - Richard Stumpf
- National Oceanic and Atmospheric Administration, National Centers for Coastal Ocean Science, 1305 East-West Highway Code N/SCI1, Silver Spring, MD, 20910, United States
| | - Amanda Koch
- Wisconsin Department of Health Services, 1 West Wilson St, Madison, WI, 53703, United States
| | - Lorraine Backer
- Division of Environmental Health Science and Practice, National Center for Environmental Health, Centers for Disease Control and Prevention, 1600 Clifton Road, Atlanta, GA, 30329, United States
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Schaeffer BA, Reynolds N, Ferriby H, Salls W, Smith D, Johnston JM, Myer M. Forecasting freshwater cyanobacterial harmful algal blooms for Sentinel-3 satellite resolved U.S. lakes and reservoirs. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 349:119518. [PMID: 37944321 PMCID: PMC10842250 DOI: 10.1016/j.jenvman.2023.119518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/19/2023] [Accepted: 10/31/2023] [Indexed: 11/12/2023]
Abstract
This forecasting approach may be useful for water managers and associated public health managers to predict near-term future high-risk cyanobacterial harmful algal blooms (cyanoHAB) occurrence. Freshwater cyanoHABs may grow to excessive concentrations and cause human, animal, and environmental health concerns in lakes and reservoirs. Knowledge of the timing and location of cyanoHAB events is important for water quality management of recreational and drinking water systems. No quantitative tool exists to forecast cyanoHABs across broad geographic scales and at regular intervals. Publicly available satellite monitoring has proven effective in detecting cyanobacteria biomass near-real time within the United States. Weekly cyanobacteria abundance was quantified from the Ocean and Land Colour Instrument (OLCI) onboard the Sentinel-3 satellite as the response variable. An Integrated Nested Laplace Approximation (INLA) hierarchical Bayesian spatiotemporal model was applied to forecast World Health Organization (WHO) recreation Alert Level 1 exceedance >12 μg L-1 chlorophyll-a with cyanobacteria dominance for 2192 satellite resolved lakes in the United States across nine climate zones. The INLA model was compared against support vector classifier and random forest machine learning models; and Dense Neural Network, Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Gneural Network (GNU) neural network models. Predictors were limited to data sources relevant to cyanobacterial growth, readily available on a weekly basis, and at the national scale for operational forecasting. Relevant predictors included water surface temperature, precipitation, and lake geomorphology. Overall, the INLA model outperformed the machine learning and neural network models with prediction accuracy of 90% with 88% sensitivity, 91% specificity, and 49% precision as demonstrated by training the model with data from 2017 through 2020 and independently assessing predictions with data from the 2021 calendar year. The probability of true positive responses was greater than false positive responses and the probability of true negative responses was less than false negative responses. This indicated the model correctly assigned lower probabilities of events when they didn't exceed the WHO Alert Level 1 threshold and assigned higher probabilities when events did exceed the threshold. The INLA model was robust to missing data and unbalanced sampling between waterbodies.
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Affiliation(s)
| | | | | | - Wilson Salls
- US EPA, Office of Research and Development, Durham, NC, USA
| | - Deron Smith
- US EPA, Office of Research and Development, Athens, GA, USA
| | | | - Mark Myer
- US EPA, Office of Chemical Safety and Pollution Prevention, Durham, NC, USA
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Lai L, Liu Y, Zhang Y, Cao Z, Yang Q, Chen X. MODIS Terra and Aqua images bring non-negligible effects to phytoplankton blooms derived from satellites in eutrophic lakes. WATER RESEARCH 2023; 246:120685. [PMID: 37804806 DOI: 10.1016/j.watres.2023.120685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 09/18/2023] [Accepted: 09/29/2023] [Indexed: 10/09/2023]
Abstract
Phytoplankton-induced lake eutrophication has drawn ongoing interest on a global scale. One of the most popular remote sensing satellite data for observing long-term dynamic changes in phytoplankton is Moderate-resolution Imaging Spectroradiometer (MODIS). However, it is worth noting that MODIS provides two images with different transit times: Terra (local time, about 10:30 am) and Aqua (local time, about 1:30 pm), which may result in a considerable bias in monitoring phytoplankton bloom areas due to the rapid migration of phytoplankton under wind or hydrodynamic conditions. To analyze this quantitatively, we selected MODIS Terra and Aqua images to generate datasets of phytoplankton bloom areas in Lake Taihu from 2003 to 2022. The results showed that Terra more frequently detected larger ranges of phytoplankton blooms than Aqua, whether on daily, monthly, or annual scales. In addition, long-term trend changes, seasonal characteristics, and abrupt years also varied with different transit times. Terra detected mutation years earlier, while Aqua displayed more pronounced seasonal characteristics. There were also differences in sensitivity to climate factors, with Terra being more responsive to temperature and wind speed on monthly and annual scales, while Aqua was more sensitive to nutrient and meteorological factors. These conclusions have also been further confirmed in Lake Chaohu, Lake Dianchi, and Lake Hulun. In conclusion, our findings strongly advocate for a linear relationship to fit Terra to Aqua results to mitigate long-term monitoring errors of phytoplankton blooms in inland lakes (R2 = 0.70, RMSE = 101.56). It is advised to utilize satellite data with transit times between 10 am and 1 pm to track phytoplankton bloom changes and to consider the diverse applications resulting from the transit times of Terra and Aqua.
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Affiliation(s)
- Lai Lai
- Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; University of Chinese Academy of Sciences, Beijing ,100049, China
| | - Yuchen Liu
- School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China; Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing, 210093, China
| | - Yuchao Zhang
- Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; University of Chinese Academy of Sciences, Beijing ,100049, China.
| | - Zhen Cao
- Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; University of Chinese Academy of Sciences, Beijing ,100049, China
| | - Qiduo Yang
- Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; University of Chinese Academy of Sciences, Beijing ,100049, China
| | - Xi Chen
- Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; Nanjing University of Information Science and Technology, Nanjing, 210044, China
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Mishra S, Stumpf RP, Schaeffer BA, Werdell PJ. Recent changes in cyanobacteria algal bloom magnitude in large lakes across the contiguous United States. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 897:165253. [PMID: 37394074 PMCID: PMC10835736 DOI: 10.1016/j.scitotenv.2023.165253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 06/25/2023] [Accepted: 06/29/2023] [Indexed: 07/04/2023]
Abstract
Cyanobacterial blooms in inland lakes produce large quantities of biomass that impact drinking water systems, recreation, and tourism and may produce toxins that can adversely affect public health. This study analyzed nine years of satellite-derived bloom records and compared how the bloom magnitude has changed from 2008-2011 to 2016-2020 in 1881 of the largest lakes across the contiguous United States (CONUS). We determined bloom magnitude each year as the spatio-temporal mean cyanobacteria biomass from May to October and in concentrations of chlorophyll-a. We found that bloom magnitude decreased in 465 (25 %) lakes in the 2016-2020 period. Conversely, there was an increase in bloom magnitude in only 81 lakes (4 %). Bloom magnitude either didn't change, or the observed change was in the uncertainty range in the majority of the lakes (n = 1335, 71 %). Above-normal wetness and normal or below-normal maximum temperature over the warm season may have caused the decrease in bloom magnitude in the eastern part of the CONUS in recent years. On the other hand, a hotter and dryer warm season in the western CONUS may have created an environment for increased algal biomass. While more lakes saw a decrease in bloom magnitude, the pattern was not monotonic over the CONUS. The variations in temporal changes in bloom magnitude within and across climatic regions depend on the interactions between land use land cover (LULC) and physical factors such as temperature and precipitation. Despite expectations suggested by recent global studies, bloom magnitude has not increased in larger US lakes over this time period.
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Affiliation(s)
- Sachidananda Mishra
- Consolidated Safety Services Inc., Fairfax, VA 22030, USA; National Oceanic and Atmospheric Administration, National Centers for Coastal Ocean Science, Silver Spring, MD 20910, USA.
| | - Richard P Stumpf
- National Oceanic and Atmospheric Administration, National Centers for Coastal Ocean Science, Silver Spring, MD 20910, USA
| | - Blake A Schaeffer
- U.S. Environmental Protection Agency, Office of Research and Development, Durham, NC 27709, USA
| | - P Jeremy Werdell
- Ocean Ecology Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
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Sarpong L, Li Y, Cheng Y, Nooni IK. Temporal characteristics and trends of nitrogen loadings in lake Taihu, China and its influencing mechanism at multiple timescales. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 344:118406. [PMID: 37354595 DOI: 10.1016/j.jenvman.2023.118406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 06/03/2023] [Accepted: 06/12/2023] [Indexed: 06/26/2023]
Abstract
Climate warming impact on excessive nitrogen (N) load in sediment favours cyanobacterial blooms in eutrophic waters. The nitrate (NO3--N) and ammonium (NH4+-N) are two forms of N loads that contribute to algae blooms. However, little attention is paid to the impact of environmental factors on N loads variations at different time scales. This paper used a well-calibrated and validated EFDC model to investigate the temporal patterns and trends of ammonium and nitrate from June 2016 to June 2017. This paper presented the relationship and effects between these variations and environmental factors using data from satellite and reanalysis-based observations obtained for six meteorological parameters. The relationship and effects between these variations and environmental factors were also examined at different timescales (i.e., daily, monthly and seasonal scales). Model calibration results indicated that measured values reasonably matched simulated values. The validation results revealed that relative error (RE) values were within an acceptable range. The REs of ammonium at East Taihu (S12) and Xu Lake (S23) sampling sites were 55.83% and 57.61%, while that of nitrate was 24.37% (S12) and 41.08%, respectively. The daily analysis of NH4+-N and NO3--N variations was 7.318 ± 3.876 (g/m2/day) and 0.0275 ± 0.222 (g/m2/day), respectively. The monthly analysis showed NH4+-N and NO3-N range from 2.04 to 12.04 (g/m2/day) and 0.0008 to 0.064 (g/m2/day), respectively. The magnitude NH4+-N and NO3--N varied and showed distinct inter-monthly variations. , The relationship between sediment fluxes and meteorological parameters showed the magnitude of correlation coefficient (r) and strength of correlation varied significantly. At daily scales, the relationship of NH4+-N and NO3--N had a significant positive correlation with all meteorological parameters. At monthly, the correlation coefficient (r) of NH4+-N and NO3-N were heterogenous. At daily and monthly scales, air temperature and wind speed are the main drivers affecting sediment N loads' dynamics; however, the influence of relative humidity, precipitation, and evaporation on N loads are smaller. The study demonstrates the contribution of meteorological conditions to the magnitude and timing of N loadings variability in water bodies. The findings provide more insight into lake ecosystem protection and environmental remediation.
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Affiliation(s)
- Linda Sarpong
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, Hohai University, Nanjing, 210098, China; College of Environment, Hohai University, Nanjing, 210098, China.
| | - Yiping Li
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, Hohai University, Nanjing, 210098, China; College of Environment, Hohai University, Nanjing, 210098, China.
| | - Yue Cheng
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, Hohai University, Nanjing, 210098, China; College of Environment, Hohai University, Nanjing, 210098, China.
| | - Isaac Kwesi Nooni
- School of Atmospheric Science and Remote Sensing, Wuxi University, Wuxi, 214105, China; School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
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Bloch RA, Faulkner G, Hilborn ED, Wismer T, Martin N, Rhea S. Geographic Variability, Seasonality, and Increase in ASPCA Animal Poison Control Center Harmful Blue-Green Algae Calls-United States and Canada, 2010-2022. Toxins (Basel) 2023; 15:505. [PMID: 37624262 PMCID: PMC10467101 DOI: 10.3390/toxins15080505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/31/2023] [Accepted: 08/05/2023] [Indexed: 08/26/2023] Open
Abstract
Harmful cyanobacteria (blue-green algae) exposures can cause illness or death in humans and animals. We characterized American Society for the Prevention of Cruelty to Animals (ASPCA) Animal Poison Control Center (APCC) harmful blue-green algae (HBGA) call data, compared it to a measure of harmful algal bloom public awareness, and considered its suitability as a public health information source. ASPCA APCC dog and cat "HBGA exposure" calls made 1 January 2010-31 December 2022 were included. We calculated annual HBGA call percentages and described calls (species, month, origin, exposure route). We characterized public awareness by quantifying Nexis Uni® (LexisNexis Academic; New York, NY, USA)-indexed news publications (2010-2022) pertaining to "harmful algal bloom(s)". Call percentage increased annually, from 0.005% (2010) to 0.070% (2022). Of 999 HBGA calls, 99.4% (n = 993) were dog exposures. Over 65% (n = 655) of calls were made July-September, largely from the New England (n = 154 (15.4%)) and Pacific (n = 129 (12.9.%)) geographic divisions. Oral and dermal exposures predominated (n = 956 (95.7%)). Harmful algal bloom news publications increased overall, peaking in 2019 (n = 1834). Higher call volumes in summer and in the New England and Pacific geographic divisions drove HBGA call increases; public awareness might have contributed. Dogs and humans have similar exposure routes. ASPCA APCC HBGA call data could serve as a public health information source.
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Affiliation(s)
- Rebecca A. Bloch
- College of Veterinary Medicine, Department of Population Health and Pathobiology, North Carolina State University, Raleigh, NC 27606, USA; (R.A.B.); (G.F.); (E.D.H.)
| | - Grace Faulkner
- College of Veterinary Medicine, Department of Population Health and Pathobiology, North Carolina State University, Raleigh, NC 27606, USA; (R.A.B.); (G.F.); (E.D.H.)
| | - Elizabeth D. Hilborn
- College of Veterinary Medicine, Department of Population Health and Pathobiology, North Carolina State University, Raleigh, NC 27606, USA; (R.A.B.); (G.F.); (E.D.H.)
- Center for Public Health and Environmental Assessment, Office of Research and Development, United States Environmental Protection Agency, Chapel Hill, NC 27514, USA
| | - Tina Wismer
- American Society for the Prevention of Cruelty to Animals, Animal Poison Control Center, Champaign, IL 61820, USA; (T.W.); (N.M.)
| | - Nicole Martin
- American Society for the Prevention of Cruelty to Animals, Animal Poison Control Center, Champaign, IL 61820, USA; (T.W.); (N.M.)
| | - Sarah Rhea
- College of Veterinary Medicine, Department of Population Health and Pathobiology, North Carolina State University, Raleigh, NC 27606, USA; (R.A.B.); (G.F.); (E.D.H.)
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Lim CC, Yoon J, Reynolds K, Gerald LB, Ault AP, Heo S, Bell ML. Harmful algal bloom aerosols and human health. EBioMedicine 2023; 93:104604. [PMID: 37164781 PMCID: PMC10363441 DOI: 10.1016/j.ebiom.2023.104604] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 03/17/2023] [Accepted: 04/20/2023] [Indexed: 05/12/2023] Open
Abstract
Harmful algal blooms (HABs) are increasing across many locations globally. Toxins from HABs can be incorporated into aerosols and transported inland, where subsequent exposure and inhalation can induce adverse health effects. However, the relationship between HAB aerosols and health outcomes remains unclear despite the potential for population-level exposures. In this review, we synthesized the current state of knowledge and identified evidence gaps in the relationship between HAB aerosols and human health. Aerosols from Karenia brevis, Ostreopsis sp., and cyanobacteria were linked with respiratory outcomes. However, most works did not directly measure aerosol or toxin concentrations and instead relied on proxy metrics of exposure, such as cell concentrations in nearby waterbodies. Furthermore, the number of studies with epidemiological designs was limited. Significant uncertainties remain regarding the health effects of other HAB species; threshold dose and the dose-response relationship; effects of concurrent exposures to mixtures of toxins and other aerosol sources, such as microplastics and metals; the impact of long-term exposures; and disparities in exposures and associated health effects across potentially vulnerable subpopulations. Additional studies employing multifaceted exposure assessment methods and leveraging large health databases could address such gaps and improve our understanding of the public health burden of HABs.
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Affiliation(s)
- Chris C Lim
- Zuckerman College of Public Health, The University of Arizona, Tucson, Arizona, USA.
| | - Jeonggyo Yoon
- Zuckerman College of Public Health, The University of Arizona, Tucson, Arizona, USA
| | - Kelly Reynolds
- Zuckerman College of Public Health, The University of Arizona, Tucson, Arizona, USA
| | - Lynn B Gerald
- Population Health Sciences Program, Office of the Vice Chancellor for Health Affairs, University of Illinois Chicago, Chicago, Illinois, USA
| | - Andrew P Ault
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan, USA
| | - Seulkee Heo
- School of the Environment, Yale University, New Haven, Connecticut, USA
| | - Michelle L Bell
- School of the Environment, Yale University, New Haven, Connecticut, USA
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Handler AM, Compton JE, Hill RA, Leibowitz SG, Schaeffer BA. Identifying lakes at risk of toxic cyanobacterial blooms using satellite imagery and field surveys across the United States. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 869:161784. [PMID: 36702268 PMCID: PMC10018780 DOI: 10.1016/j.scitotenv.2023.161784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 01/18/2023] [Accepted: 01/19/2023] [Indexed: 06/18/2023]
Abstract
Harmful algal blooms caused by cyanobacteria are a threat to global water resources and human health. Satellite remote sensing has vastly expanded spatial and temporal data on lake cyanobacteria, yet there is still acute need for tools that identify which waterbodies are at-risk for toxic cyanobacterial blooms. Algal toxins cannot be directly detected through imagery but monitoring toxins associated with cyanobacterial blooms is critical for assessing risk to the environment, animals, and people. The objective of this study is to address this need by developing an approach relating satellite imagery on cyanobacteria with field surveys to model the risk of toxic blooms among lakes. The Medium Resolution Imaging Spectrometer (MERIS) and United States (US) National Lakes Assessments are leveraged to model the probability among lakes of exceeding lower and higher demonstration thresholds for microcystin toxin, cyanobacteria, and chlorophyll a. By leveraging the large spatial variation among lakes using two national-scale data sources, rather than focusing on temporal variability, this approach avoids many of the previous challenges in relating satellite imagery to cyanotoxins. For every satellite-derived lake-level Cyanobacteria Index (CI_cyano) increase of 0.01 CI_cyano/km2, the odds of exceeding six bloom thresholds increased by 23-54 %. When the models were applied to the 2192 satellite monitored lakes in the US, the number of lakes identified with ≥75 % probability of exceeding the thresholds included as many as 335 lakes for the lower thresholds and 70 lakes for the higher thresholds, respectively. For microcystin, the models identified 162 and 70 lakes with ≥75 % probability of exceeding the lower (0.2 μg/L) and higher (1.0 μg/L) thresholds, respectively. This approach represents a critical advancement in using satellite imagery and field data to identify lakes at risk for developing toxic cyanobacteria blooms. Such models can help translate satellite data to aid water quality monitoring and management.
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Affiliation(s)
- Amalia M Handler
- Center for Public Health and Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Corvallis, OR 97333, United States of America.
| | - Jana E Compton
- Center for Public Health and Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Corvallis, OR 97333, United States of America
| | - Ryan A Hill
- Center for Public Health and Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Corvallis, OR 97333, United States of America
| | - Scott G Leibowitz
- Center for Public Health and Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Corvallis, OR 97333, United States of America
| | - Blake A Schaeffer
- Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC 27711, United States of America
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