|Appears in Collections:||Biological and Environmental Sciences Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Pseudo-nitzschia Blooms in a Coastal Upwelling System: Remote Sensing Detection, Toxicity and Environmental Variables|
|Author(s):||Torres Palenzuela, Jesus M|
González Vilas, Luis
Bellas, Francisco M
|Citation:||Torres Palenzuela JM, González Vilas L, Bellas FM, Garet E, González-Fernández Á & Spyrakos E (2019) Pseudo-nitzschia Blooms in a Coastal Upwelling System: Remote Sensing Detection, Toxicity and Environmental Variables. Water, 11 (9), Art. No.: 1954. https://doi.org/10.3390/w11091954|
|Abstract:||The NW coast of the Iberian Peninsula is dominated by extensive shellfish farming, which places this region as a world leader in mussel production. Harmful algal blooms in the area frequent lead to lengthy harvesting closures threatening food security. This study developed a framework for the detection of Pseudo-nitzschia blooms in the Galician rias from satellite data (MERIS full-resolution images) and identified key variables that affect their abundance and toxicity. Two events of toxin-containing Pseudo-nitzschia were detected (up to 2.5 μg L−1 pDA) in the area. This study suggests that even moderate densities of Pseudo-nitzschia in this area might indicate high toxin content. Empirical models for particulate domoic acid (pDA) were developed based on MERIS FR data. The resulting remote-sensing model, including MERIS bands centered around 510, 560, and 620 nm explain 73% of the pDA variance (R2 = 0.73, p < 0.001). The results show that higher salinity values and lower Si(OH)4/N ratios favour higher Pseudo-nitzschia spp. abundances. High pDA values seem to be associated with relatively high PO43, low NO3− concentrations, and low Si(OH)4/N. While MERIS FR data and regionally specific algorithms can be useful for detecting Pseudo-nitzschia blooms, nutrient relationships are crucial for predicting the toxicity of these blooms.|
|Rights:||This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited|
|water-11-01954.pdf||Fulltext - Published Version||2.2 MB||Adobe PDF||View/Open|
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