Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Of the many ways biological control can be incorporated into Integrated Pest Management (IPM) programs, natural enemy thresholds are arguably most easily adopted by stakeholders. Integration of natural enemy thresholds into IPM programs requires ecological and cost/benefit crop production data, threshold model validation, and an understanding of the socioeconomic factors that influence stakeholder decisions about biological control. These thresholds are more likely to be utilized by stakeholders when integrated into dynamic web-based IPM decision support systems that summarize pest management data and push site-specific biological control management recommendations to decision-makers. We highlight recent literature on topics related to natural enemy thresholds and how findings may allow pest suppression services to be incorporated into advanced IPM programs.
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Source |
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http://dx.doi.org/10.1016/j.cois.2017.03.009 | DOI Listing |
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