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
In this study, we have investigated the limits of taxonomic conservatism in host-plant use in the seed-beetle genus Bruchus. To reconstruct the insect phylogeny, parsimony and multiple partitioned Bayesian inference analyses were conducted on a combined data set of four genes. Permutation tests and both global and local maximum-likelihood optimizations of host preferences at distinct taxonomic levels revealed that host-fidelity is still discernible beyond the host-plant tribe level, suggesting the existence of more important than previously thought evolutionary constraints, which are further discussed in details. Our tree topologies are also mostly consistent with extant taxonomic groups. Through the analysis of this empirical data set we also provide meaningful insights on two methodological issues. First, Bayesian inference analyses suggest that partitioning by using codon positions greatly increase the accuracy of phylogenetical reconstructions. Regarding reconstruction of ancestral character states through maximum likelihood, the present study also highlights the usefulness of local optimizations. The issue of over-parameterization is also addressed, as the optimizations with the most parameter-rich models have returned the most counterintuitive results.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.ympev.2006.11.026 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!