Item talk:Q303010

{

 "USGS Publications Warehouse": {
   "@context": "https://schema.org",
   "@type": "Article",
   "additionalType": "Journal Article",
   "name": "A new approach to automated incubation recess detection using temperature loggers",
   "identifier": [
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       "value": "70199046",
       "url": "https://pubs.usgs.gov/publication/70199046"
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       "value": 70199046
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       "propertyID": "DOI",
       "value": "10.1650/CONDOR-18-6.1",
       "url": "https://doi.org/10.1650/CONDOR-18-6.1"
     }
   ],
   "journal": {
     "@type": "Periodical",
     "name": "The Condor",
     "volumeNumber": "120",
     "issueNumber": "4"
   },
   "inLanguage": "en",
   "isPartOf": [
     {
       "@type": "CreativeWorkSeries",
       "name": "The Condor"
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   ],
   "datePublished": "2018",
   "dateModified": "2018-08-30",
   "abstract": "Nest attendance during incubation is an important facet of avian nesting behavior, and understanding the number, timing, and duration of incubation recesses can improve our understanding of the factors determining avian reproductive success. Temperature loggers are a low-cost, noninvasive method for studying nest attendance, but processing and interpreting the data present logistical challenges for investigators. We developed an accurate automated method for processing data from temperature loggers to identify incubation recesses. This automated method combines absolute changes in nest temperature over time and changes relative to daily nest-specific variation in temperature to identify incubation recesses. We validated this method through comparison with recesses observed during continuous infrared video monitoring of 3 Mallard (Anas platyrhynchos) and 7 Gadwall (Mareca strepera) nests in northern California, USA. Of 116 recesses observed on camera, we detected 102 (88%) with automated recess detection. After excluding 7 recesses in which nest temperature did not decrease during the recess, and which would therefore have been undetectable without ancillary data, we detected 102 of 109 (94%) recesses with automated recess detection. The time lag in detecting a hen's departure from her nest (i.e. when the recess had begun) was influenced by ambient temperature, although detection of the recess itself was not. The lag in detecting the start of a recess was (mean \u00b1 SD) 6.9 \u00b1 2.7 min when ambient temperatures were below 30\u00b0C, and 13.7 \u00b1 3.2 min at temperatures above 30\u00b0C. The lag in detecting the end of a recess was 1.7 \u00b1 3.2 min and was not affected by ambient temperature. Recesses observed on camera were slightly longer (178.3 \u00b1 122.2 min) than those estimated with automated recess detection (158.7 \u00b1 93.1 min), with the time lag in detecting the start of a recess under warm ambient temperatures contributing the most to the difference. These results demonstrate the accuracy of the automated method that we have developed for identifying the timing and duration of incubation recesses using nest temperature data. This method was developed using data from dabbling ducks but is readily adaptable to other avian taxa with appropriate changes in user-defined criteria for identifying incubation recesses.",
   "description": "12 p.",
   "publisher": {
     "@type": "Organization",
     "name": "American Ornithological Society"
   },
   "author": [
     {
       "@type": "Person",
       "name": "Hartman, C. Alex chartman@usgs.gov",
       "givenName": "C. Alex",
       "familyName": "Hartman",
       "email": "chartman@usgs.gov",
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         "value": "0000-0002-7222-1633",
         "url": "https://orcid.org/0000-0002-7222-1633"
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           "name": "Western Ecological Research Center",
           "url": "https://www.usgs.gov/centers/werc"
         }
       ]
     },
     {
       "@type": "Person",
       "name": "Ackerman, Joshua T. jackerman@usgs.gov",
       "givenName": "Joshua T.",
       "familyName": "Ackerman",
       "email": "jackerman@usgs.gov",
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       "name": "Herzog, Mark P. mherzog@usgs.gov",
       "givenName": "Mark P.",
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     },
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       "@type": "Person",
       "name": "Casazza, Michael L. mike_casazza@usgs.gov",
       "givenName": "Michael L.",
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       "name": "Croston, Rebecca",
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}