Severity: Warning
Message: file_get_contents(https://...@remsenmedia.com&api_key=81853a771c3a3a2c6b2553a65bc33b056f08&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
We use data from a survey of several hundred lakes in the northeastern United States by the U.S. Environmental Protection Agency to illustrate an approach to identifying promising indicators of lake condition. We construct a hypothetical gold standard of water quality from the first principal component of 16 chemical variables measured in the lakes, and examine its associations with 71 candidate indicators based on measurements of human activity, birds, fish and zooplankton in the lakes or their watersheds. Nonparametric summaries of these associations--based on rank correlations and receiver-operating-characteristic curves--suggest that variables summarizing the extent of human disturbance are generally the strongest indicators. To the extent that our water-quality variable is a useful proxy for ecological condition, our results suggest that easily-obtained measures of human activity are at least as predictive as many of the harder-to-measure biological indicators that have been proposed.
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Source |
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http://dx.doi.org/10.1007/s10661-005-9011-x | DOI Listing |
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