Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1075
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3195
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Sustainability of bivalve shellfish farming relies on clean coastal waters, however, high levels of faecal indicator organisms (FIOs, e.g. Escherichia coli) in shellfish results in temporary closure of shellfish harvesting beds to protect human health, but with economic consequences for the shellfish industry. Active Management Systems which can predict FIO contamination may help reduce shellfishery closures. This study evaluated predictors of E. coli concentrations in two shellfish species, the blue mussel (Mytilus edulis) and the Pacific oyster (Crassostrea gigas), at different spatial and temporal scales, within 12 estuaries in England and Wales. We aimed to: (i) identify consistent catchment-scale or within-estuary predictors of elevated E. coli levels in shellfish, (ii) evaluate whether high river flows associated with rainfall events were a significant predictor of shellfish E. coli concentrations, and the time lag between these events and E. coli accumulation, and (iii) whether operation of Combined Sewer Overflows (CSO) is associated with higher E. coli concentrations in shellfish. A cross-catchment analysis gave a good predictive model for contamination management (R = 0.514), with positive relationships between E. coli concentrations and river flow (p = 0.001), turbidity (p = 0.002) and nitrate (p = 0.042). No effect was observed for catchment area, the number of point source discharges, or agricultural land use type. 64% of all shellfish beds showed a significant relationship between E. coli and river flow, with typical lag-times of 1-3 days. Detailed analysis of the Conwy estuary indicated that E. coli counts were consistently higher when the CSO had been active the previous week. In conclusion, we demonstrate that real-time river flow and water quality data may be used to predict potential risk of E. coli contamination in shellfish at the catchment level, however, further refinement (coupling to fine-scale hydrodynamic models) is needed to make accurate predictions for individual shellfish beds within estuaries.
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http://dx.doi.org/10.1016/j.envpol.2024.125476 | DOI Listing |