scholarly journals Knowledge Spillover and Positive Environmental Externality in Agricultural Decision Making under Performance-Based Payment Programs

2020 ◽  
Vol 49 (2) ◽  
pp. 270-290
Author(s):  
Hongxing Liu ◽  
Christopher S. Ruebeck
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Management Practice ◽  
Profit Maximization ◽  
Spillover Effect ◽  
Cost Effective ◽  
Knowledge Spillover ◽  
Program Participation ◽  
Policy Makers ◽  
World Government

Agricultural activities have imposed significant impacts on water resources, leading to hypoxic zones and harmful algal blooms all over the world. Government agencies, nongovernmental organizations, and individuals have been making various efforts to reduce this non-point source pollution. Among those efforts, even the more cost-effective examples of performance-based environmental payment programs generally have low participation rates. We investigate the effects of externalities in farmers’ decisions on neighboring farms, incorporating both a knowledge spillover effect and a positive environmental outcome externality of farmers’ best-management practice (BMP) adoption decisions. Our focus is on how these effects may influence the outcome of performance-based payment programs and how policy makers might recognize these effects in the design of cost-effective policies to promote program participation and BMP adoption. Rather than imposing an assumption of profit-maximization or forward-looking behavior, we allow outcomes to emerge from interactions among neighboring farmers. We recommend cost-effective policies across communities depending on their composition. It is more cost-effective to target communities with fewer innovators and/or target the programs towards the least-innovative individuals.

scholarly journals Photodynamic Controls of Harmful Algal Blooms by an Ultra-efficient and Degradable AIEgen-based Photosensitizer

2020 ◽  
Author(s):  
Qiang Yue ◽  
Xuewen He ◽  
Neng Yan ◽  
sidan tian ◽  
Chenchen LIU ◽  
...  
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Water Solubility ◽  
Irradiation Time ◽  
Effective Means ◽  
Cost Effective ◽  
Weather Conditions ◽  
New Paradigm ◽  
Green Governance ◽  
Positively Charged

Harmful <a></a><a>algal blooms</a> (HAB) have severe impacts on human health, aquatic ecosystems, and economy. There is still a lack of effective means to control the algal blooms. Herein, a positively charged photosensitizer with aggregation induced emission (AIE) characteristics, namely TVP-A, is reported for its super-efficient, cost-effective, and eco-friendly governance of HAB. TVP-A possesses a characteristically high quantum yield of harvesting white light into reactive oxygen species (ROS). Attributed to its positive charges, TVP-A has good water solubility and can quickly adsorb onto algal cells floating on the water surface. It effectively triggers cell death through oxidative destruction of the nuclei and chloroplasts of algae. The extremely low effective concentration of TVP-A and the short irradiation time by natural light in removing algal blooms ensure its application at large scales under most weather conditions, without affecting other existing organisms. The slow but consistent self-degradation of TVP-A during the photodynamic controls of algal blooms avoids generating any environmental residues or secondary pollution to environmental systems. TVP-A thereby serves as an excellent candidate for the green governance of HAB, and this work represents a new paradigm for the development of efficient and degradable AIEgens for future environmental applications.

scholarly journals Photodynamic Controls of Harmful Algal Blooms by an Ultra-efficient and Degradable AIEgen-based Photosensitizer

2020 ◽  
Author(s):  
Qiang Yue ◽  
Xuewen He ◽  
Neng Yan ◽  
sidan tian ◽  
Chenchen LIU ◽  
...  
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Water Solubility ◽  
Irradiation Time ◽  
Effective Means ◽  
Cost Effective ◽  
Weather Conditions ◽  
New Paradigm ◽  
Green Governance ◽  
Positively Charged

Harmful <a></a><a>algal blooms</a> (HAB) have severe impacts on human health, aquatic ecosystems, and economy. There is still a lack of effective means to control the algal blooms. Herein, a positively charged photosensitizer with aggregation induced emission (AIE) characteristics, namely TVP-A, is reported for its super-efficient, cost-effective, and eco-friendly governance of HAB. TVP-A possesses a characteristically high quantum yield of harvesting white light into reactive oxygen species (ROS). Attributed to its positive charges, TVP-A has good water solubility and can quickly adsorb onto algal cells floating on the water surface. It effectively triggers cell death through oxidative destruction of the nuclei and chloroplasts of algae. The extremely low effective concentration of TVP-A and the short irradiation time by natural light in removing algal blooms ensure its application at large scales under most weather conditions, without affecting other existing organisms. The slow but consistent self-degradation of TVP-A during the photodynamic controls of algal blooms avoids generating any environmental residues or secondary pollution to environmental systems. TVP-A thereby serves as an excellent candidate for the green governance of HAB, and this work represents a new paradigm for the development of efficient and degradable AIEgens for future environmental applications.

scholarly journals Mapping and Forecasting Onsets of Harmful Algal Blooms Using MODIS Data over Coastal Waters Surrounding Charlotte County, Florida

2018 ◽  
Vol 10 (10) ◽  
pp. 1656 ◽  
Author(s):  
Sita Karki ◽  
Mohamed Sultan ◽  
Racha Elkadiri ◽  
Tamer Elbayoumi
Keyword(s):  
Remote Sensing ◽  
Harmful Algal Blooms ◽  
Multivariate Regression ◽  
Algal Blooms ◽  
Wildlife Conservation ◽  
River Mouth ◽  
Warning System ◽  
Remote Sensing Data ◽  
Cost Effective ◽  
Color Processing

Over the past two decades, persistent occurrences of harmful algal blooms (HAB; Karenia brevis) have been reported in Charlotte County, southwestern Florida. We developed data-driven models that rely on spatiotemporal remote sensing and field data to identify factors controlling HAB propagation, provide a same-day distribution (nowcasting), and forecast their occurrences up to three days in advance. We constructed multivariate regression models using historical HAB occurrences (213 events reported from January 2010 to October 2017) compiled by the Florida Fish and Wildlife Conservation Commission and validated the models against a subset (20%) of the historical events. The models were designed to capture the onset of the HABs instead of those that developed days earlier and continued thereafter. A prototype of an early warning system was developed through a threefold exercise. The first step involved the automatic downloading and processing of daily Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua products using SeaDAS ocean color processing software to extract temporal and spatial variations of remote sensing-based variables over the study area. The second step involved the development of a multivariate regression model for same-day mapping of HABs and similar subsequent models for forecasting HAB occurrences one, two, and three days in advance. Eleven remote sensing variables and two non-remote sensing variables were used as inputs for the generated models. In the third and final step, model outputs (same-day and forecasted distribution of HABs) were posted automatically on a web map. Our findings include: (1) the variables most indicative of the timing of bloom propagation are bathymetry, euphotic depth, wind direction, sea surface temperature (SST), ocean chlorophyll three-band algorithm for MODIS [chlorophyll-a OC3M] and distance from the river mouth, and (2) the model predictions were 90% successful for same-day mapping and 65%, 72% and 71% for the one-, two- and three-day advance predictions, respectively. The adopted methodologies are reliable at a local scale, dependent on readily available remote sensing data, and cost-effective and thus could potentially be used to map and forecast algal bloom occurrences in data-scarce regions.

scholarly journals Use of biosensors for the detection of marine toxins

2016 ◽  
Vol 60 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Daniel A. McPartlin ◽  
Michael J. Lochhead ◽  
Laurie B. Connell ◽  
Gregory J. Doucette ◽  
Richard J. O'Kennedy
Keyword(s):  
Climate Change ◽  
Economic Impact ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Cost Effective ◽  
Detection Methods ◽  
Global Effect ◽  
Economic Implications ◽  
Marine Biotoxins ◽  
Exciting Area

Increasing occurrences of harmful algal blooms (HABs) in the ocean are a major concern for countries around the globe, and with strong links between HABs and climate change and eutrophication, the occurrences are only set to increase. Of particular concern with regard to HABs is the presence of toxin-producing algae. Six major marine biotoxin groups are associated with HABs. Ingestion of such toxins via contaminated shellfish, fish, or other potential vectors, can lead to intoxication syndromes with moderate to severe symptoms, including death in extreme cases. There are also major economic implications associated with the diverse effects of marine biotoxins and HABs. Thus, effective monitoring programmes are required to manage and mitigate their detrimental global effect. However, currently legislated detection methods are labour-intensive, expensive and relatively slow. The growing field of biosensor diagnostic devices is an exciting area that has the potential to produce robust, easy-to-use, cost-effective, rapid and accurate detection methods for marine biotoxins and HABs. This review discusses recently developed biosensor assays that target marine biotoxins and their microbial producers, both in harvested fish/shellfish samples and in the open ocean. The effective deployment of such biosensor platforms could address the pressing need for improved monitoring of HABs and marine biotoxins, and could help to reduce their global economic impact.

scholarly journals Mapping and forecasting onsets of harmful algal blooms using MODIS data over coastal waters surrounding Charlotte County, Florida

2018 ◽  
Author(s):  
Sita Karki ◽  
Mohamed Sultan ◽  
Racha Elkadiri ◽  
Tamer Elbayoumi
Keyword(s):  
Remote Sensing ◽  
Harmful Algal Blooms ◽  
Multivariate Regression ◽  
Algal Blooms ◽  
Wildlife Conservation ◽  
River Mouth ◽  
Warning System ◽  
Remote Sensing Data ◽  
Cost Effective ◽  
Color Processing

Over the past two decades, persistent occurrences of harmful algal blooms (HAB; Karenia brevis) have been reported in Charlotte County, southwestern Florida. We developed data-driven models that rely on spatiotemporal remote sensing and field data to identify factors controlling HAB propagation, provide a same-day distribution (nowcasting), and forecast their occurrences up to three days in advance. We constructed multivariate regression models using historical HAB occurrences (213 events reported from January 2010 to October 2017) compiled by the Florida Fish and Wildlife Conservation Commission and validated the models against a subset (20%) of the reported historical events. The models were designed to specifically capture the onset of the HABs instead of those that developed days earlier and continued thereafter. A prototype of an early warning system was developed through a threefold exercise. The first step involved the automatic downloading and processing of daily Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua products using SeaDAS ocean color processing software to extract temporal and spatial variations of remote sensing-based variables over the study area. The second step involved the development of a multivariate regression model for same-day mapping of HABs and similar subsequent models for forecasting HAB occurrences one, two, and three days in advance. Eleven remote sensing variables and two non-remote sensing variables were used as inputs for the generated models. In the third and final step, model outputs (same-day and forecasted distribution of HABs) were posted automatically on a web-based GIS (http://www.esrs.wmich.edu/webmap/bloom/). Our findings include the following: (1) the variables most indicative of the timing of bloom propagation are bathymetry, euphotic depth, wind direction, SST, chlorophyll-a [OC3M] and distance from the river mouth, and (2) the model predictions were 90% successful for same-day mapping and 65%, 72% and 71% for the one-, two- and three-day advance predictions, respectively. The adopted methodologies are reliable, dependent on readily available remote sensing data sets, and cost-effective and thus could potentially be used to map and forecast algal bloom occurrences in data-scarce regions.

National coastal management challenges and needs

Shore & Beach ◽  
2020 ◽  
pp. 34-43
Author(s):  
Nicole Elko ◽  
Tiffany Roberts Briggs
Keyword(s):  
Coastal Management ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Local Community ◽  
Extreme Event ◽  
Technical Information ◽  
Interdisciplinary Approach ◽  
Beach Erosion ◽  
The U.S

In partnership with the U.S. Geological Survey Coastal and Marine Hazards and Resources Program (USGS CMHRP) and the U.S. Coastal Research Program (USCRP), the American Shore and Beach Preservation Association (ASBPA) has identified coastal stakeholders’ top coastal management challenges. Informed by two annual surveys, a multiple-choice online poll was conducted in 2019 to evaluate stakeholders’ most pressing problems and needs, including those they felt most ill-equipped to deal with in their day-to-day duties and which tools they most need to address these challenges. The survey also explored where users find technical information and what is missing. From these results, USGS CMHRP, USCRP, ASBPA, and other partners aim to identify research needs that will inform appropriate investments in useful science, tools, and resources to address today’s most pressing coastal challenges. The 15-question survey yielded 134 complete responses with an 80% completion rate from coastal stakeholders such as local community representatives and their industry consultants, state and federal agency representatives, and academics. Respondents from the East, Gulf, West, and Great Lakes coasts, as well as Alaska and Hawaii, were represented. Overall, the prioritized coastal management challenges identified by the survey were: Deteriorating ecosystems leading to reduced (environmental, recreational, economic, storm buffer) functionality, Increasing storminess due to climate change (i.e. more frequent and intense impacts), Coastal flooding, both Sea level rise and associated flooding (e.g. nuisance flooding, king tides), and Combined effects of rainfall and surge on urban flooding (i.e. episodic, short-term), Chronic beach erosion (i.e. high/increasing long-term erosion rates), and Coastal water quality, including harmful algal blooms (e.g. red tide, sargassum). A careful, systematic, and interdisciplinary approach should direct efforts to identify specific research needed to tackle these challenges. A notable shift in priorities from erosion to water-related challenges was recorded from respondents with organizations initially formed for beachfront management. In addition, affiliation-specific and regional responses varied, such as Floridians concern more with harmful algal blooms than any other human and ecosystem health related challenge. The most common need for additional coastal management tools and strategies related to adaptive coastal management to maintain community resilience and continuous storm barriers (dunes, structures), as the top long-term and extreme event needs, respectively. In response to questions about missing information that agencies can provide, respondents frequently mentioned up-to-date data on coastal systems and solutions to challenges as more important than additional tools.

scholarly journals Marine harmful algal blooms (HABs) in the United States: History, current status and future trends

Harmful Algae ◽  
2021 ◽  
pp. 101975
Author(s):  
Donald M. Anderson ◽  
Elizabeth Fensin ◽  
Christopher J. Gobler ◽  
Alicia E. Hoeglund ◽  
Katherine A. Hubbard ◽  
...  
Keyword(s):  
United States ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
United States History ◽  
The United States ◽  
Current Status ◽  
Future Trends ◽  
States History

scholarly journals Mitochondrial genome evolution in pelagophyte algae

2021 ◽  
Author(s):  
Shannon J Sibbald ◽  
Maggie Lawton ◽  
John M Archibald
Keyword(s):  
Mitochondrial Genome ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
23S Rrna ◽  
Mitochondrial Genomes ◽  
Trna Genes ◽  
Unique Region ◽  
Long Read ◽  
Genomic Studies ◽  
Aureoumbra Lagunensis

Abstract The Pelagophyceae are marine stramenopile algae that include Aureoumbra lagunensis and Aureococcus anophagefferens, two microbial species notorious for causing harmful algal blooms. Despite their ecological significance, relatively few genomic studies of pelagophytes have been carried out. To improve understanding of the biology and evolution of pelagophyte algae, we sequenced complete mitochondrial genomes for A. lagunensis (CCMP1510), Pelagomonas calceolata (CCMP1756) and five strains of A. anophagefferens (CCMP1707, CCMP1708, CCMP1850, CCMP1984 and CCMP3368) using Nanopore long-read sequencing. All pelagophyte mitochondrial genomes assembled into single, circular mapping contigs between 39,376 base-pairs (bp) (P. calceolata) and 55,968 bp (A. lagunensis) in size. Mitochondrial genomes for the five A. anophagefferens strains varied slightly in length (42,401 bp—42,621 bp) and were 99.4%-100.0% identical. Gene content and order was highly conserved between the A. anophagefferens and P. calceolata genomes, with the only major difference being a unique region in A. anophagefferens containing DNA adenine and cytosine methyltransferase (dam/dcm) genes that appear to be the product of lateral gene transfer from a prokaryotic or viral donor. While the A. lagunensis mitochondrial genome shares seven distinct syntenic blocks with the other pelagophyte genomes, it has a tandem repeat expansion comprising ∼40% of its length, and lacks identifiable rps19 and glycine tRNA genes. Laterally acquired self-splicing introns were also found in the 23S rRNA (rnl) gene of P. calceolata and the coxI gene of the five A. anophagefferens genomes. Overall, these data provide baseline knowledge about the genetic diversity of bloom-forming pelagophytes relative to non-bloom-forming species.

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