Interdisciplinary science approach for harmful algal blooms (HABs) and algal toxins—A strategic science vision for the U.S. Geological Survey

U.S. Geological Survey circular/U.S. Geological Survey Circular, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

First posted May 23, 2024 For additional information, contact: Director, Water Resources Mission AreaU.S. Geological Survey12201 Sunrise Valley DriveReston, VA 20192Contact Pubs Warehouse Algal blooms in water, soils, dusts, and the environment have captured national attention because of concerns associated with exposure to algal toxins for humans animals. naturally occur all surface-water types are important primary producers aquatic ecosystems. However, excessive algae growth can be many harmful effects ranging from aesthetic toxicity concerns, so this is commonly called a bloom (HAB).Ecological imbalances that lead growth, such as increased nutrient availability waterbodies natural anthropogenic sources, well documented scientific literature. On other hand, fundamental understandings environmental causes controls leading toxin production, exposures, adverse health outcomes animals could benefit more by U.S. Survey (USGS) scientists. Understanding when, why, how produced individual cells or communities why released surrounding waterbody requires research determine toxin's role, whether it provides competitive advantage if potential reasons exist production release, secretions otherwise benign biological processes. This will require groundbreaking discovery about underlying biologic abiotic (non-living) processes complicated local variation land use, microbial species composition, ecosystem structure watershed.Although which HABs form may similar one another, controlled factors HAB development unique watershed. Consequently, science gaps prevent informed mitigation prevention toxic events. There also understanding conditions control specific watersheds. Addressing these needed inform evidence-based decisions protect human animal reduce recreational socioeconomic losses.

Язык: Английский

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Spatial Validation of Spectral Unmixing Results: A Systematic Review

Remote Sensing, Год журнала: 2023, Номер 15(11), С. 2822 - 2822

Опубликована: Май 29, 2023

The pixels of remote images often contain more than one distinct material (mixed pixels), and so their spectra are characterized by a mixture spectral signals. Since 1971, shared effort has enabled the development techniques for retrieving information from mixed pixels. most analyzed, implemented, employed procedure is unmixing. Among extensive literature on unmixing, nineteen reviews were identified, each highlighted many shortcomings spatial validation. Although an overview approaches used to spatially validate could be very helpful in overcoming its shortcomings, review them was never provided. Therefore, this systematic provides updated used, analyzing papers that published 2022, 2021, 2020, dated overview, not only 2011 2010, but also 1996 1995. key criterion results unmixing validated. Web Science Scopus databases searched, using all names assigned as keywords. A total 454 eligible included review. Their analysis revealed six issues validation considered differently addressed: number validated endmembers; sample sizes sampling designs reference data; sources creation fractional abundance maps; data with other minimization evaluation errors co-localization resampling. addressing these authors overcome some validation, it recommended addressed together. However, few together, did specify approach or adequately explain methods employed.

Язык: Английский

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Reporting of Freshwater Cyanobacterial Poisoning in Terrestrial Wildlife: A Systematic Map

Animals, Год журнала: 2022, Номер 12(18), С. 2423 - 2423

Опубликована: Сен. 14, 2022

Global warming and over-enrichment of freshwater systems have led to an increase in harmful cyanobacterial blooms (cyanoHABs), affecting human animal health. The aim this systematic map was detail the current literature surrounding cyanotoxin poisonings terrestrial wildlife identify possible improvements reports morbidity mortality from cyanotoxins. A search conducted using electronic databases Scopus Web Science, yielding 5059 published studies identifying 45 separate case North America, Africa, Europe, Asia. Currently, no gold standard for diagnosis intoxication exists wildlife, we present suggested guidelines here. These involved immunoassays analytical chemistry techniques toxin involved, PCR species evidence ingestion or exposure cyanotoxins animals affected. Of cases, our recommended methods concurred with 48.9% cases. Most often, cases were investigated after a event had already occurred, where mitigation implemented, only three successful their efforts. Notably, one invasive cyanobacteria recorded review despite being known occur throughout globe; could explain underreporting cyanobacteria. This highlights perceived absence robust detection, surveillance, poisoning wildlife. It may be true that is less susceptible these events; however, rates are likely much more than reported literature.

Язык: Английский

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Remote Sensing Identification of Harmful Algae in Ulansuhai Lake with Machine Learning

Water, Год журнала: 2024, Номер 17(1), С. 50 - 50

Опубликована: Дек. 28, 2024

Frequent algal blooms in lakes pose a serious threat to aquatic ecosystems. It is of great significance quickly and accurately monitor the distribution algae for regulation blooms. While remote sensing techniques machine learning methods can be used combination identify analyze their spatial temporal distribution, these still face challenges practical applications due uncertainties lake boundaries imbalances between non-algae. In order overcome difficulties, we studied dynamic open water range Ulansuhai Lake non-equilibrium data processing method its algae. We also performed spatiotemporal analysis over long time series. The results show that (1) spectral characteristics Landsat 8 images are very suitable identification based on sensing, especially random forest method, where fourth band plays an important role. (2) Among various methods, accuracy training set validation more than 90%. This indicates long-term monitoring study provides scientific technical support management Lake, which will helpful guiding future control work.

Язык: Английский

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Spatial and temporal distribution analysis of dominant algae in Lake Taihu based on ocean and land color instrument data

Ecological Indicators, Год журнала: 2023, Номер 155, С. 110959 - 110959

Опубликована: Сен. 27, 2023

The proliferation of algal blooms can lead to environmental issues. phytoplankton responsible for these are diverse. Different species bloom-forming algae have distinct characteristics and hazards, therefore need different treatment methods. An accurate quick determination the spatial temporal distribution is crucial lake ecological restoration. Based on differences in remote sensing reflectance (Rrs) various typical eutrophic lakes (including Microcystis aeruginosa, Aphanizomenon sp., Pseudanabaena sp. Cyanobacteria Chlorella Scenedesmus quadricauda Chlorophytes), difference index distinguishing were developed differentiate species. A validation, using an independent dataset from indoor experiment in-situ-measured satellite-image-derived Rrs, showed that algorithm provide reliable results (overall accuracies 81.97%, 81.25%, 60.42%, respectively). According Ocean Land Color Instrument images Lake Taihu period 2016 2020, was dominant algae, followed by Aphanizomenon. dominance two types Chlorophytes less pronounced. proportion as highest summer, while peaked winter. varied slightly throughout year, In terms distribution, patterns spring autumn relatively similar. approximately 80% dominated Microcystis. winter, more prevalent along southeastern shore Taihu. construction application this model a technical support prediction prevention inland lakes.

Язык: Английский

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