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: 3122
Function: getPubMedXML
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
It is widely recognized that both local and landscape-scale factors can be important drivers of crop pests, natural enemies, and biocontrol services. However, recent syntheses have found that landscape effects are inconsistent across study systems, highlighting the need for system-specific research to guide management decisions. In particular, studies conducted in perennial crops and that examine landscape configuration, not just composition, are especially lacking. We studied the impact of local and landscape factors on alfalfa weevil Hypera postica and its parasitoid Bathyplectes curculionis. Although classical biological control efforts have largely suppressed H. postica in the eastern United States, it remains problematic in the western United States. We sampled 20 production alfalfa fields in southeastern Wyoming to estimate H. postica density, parasitism rates by B. curculionis, and vegetation at local scales. We used remotely sensed imagery to characterize both landscape composition and configuration surrounding each sampled field. We used a hypothesis-driven modeling approach to determine which model was most predictive of H. postica and parasitism rate by B. curculionis. Landscape composition was the best model to predict H. postica densities. Host density was the best predictor of parasitism rates by B. curculionis. Production fields that had received insecticide applications in the last 5 years had higher weevil densities than fields that had not received insecticide applications. Stand age was not associated with weevil density or parasitism rate. In conclusion, we found local, landscape, and management components to be important in this system.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9585371 | PMC |
http://dx.doi.org/10.1093/ee/nvac057 | DOI Listing |
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