Item talk:Q308788

{

 "USGS Publications Warehouse": {
   "@context": "https://schema.org",
   "@type": "Article",
   "additionalType": "Journal Article",
   "name": "Ignoring species availability biases occupancy estimates in single-scale occupancy models",
   "identifier": [
     {
       "@type": "PropertyValue",
       "propertyID": "USGS Publications Warehouse IndexID",
       "value": "70250315",
       "url": "https://pubs.usgs.gov/publication/70250315"
     },
     {
       "@type": "PropertyValue",
       "propertyID": "USGS Publications Warehouse Internal ID",
       "value": 70250315
     },
     {
       "@type": "PropertyValue",
       "propertyID": "DOI",
       "value": "10.1111/2041-210X.13881",
       "url": "https://doi.org/10.1111/2041-210X.13881"
     }
   ],
   "journal": {
     "@type": "Periodical",
     "name": "Methods in Ecology and Evolution",
     "volumeNumber": "13",
     "issueNumber": "8"
   },
   "inLanguage": "en",
   "isPartOf": [
     {
       "@type": "CreativeWorkSeries",
       "name": "Methods in Ecology and Evolution"
     }
   ],
   "datePublished": "2022",
   "dateModified": "2023-12-07",
   "abstract": "Most applications of single-scale occupancy models do not differentiate between availability and detectability, even though species availability is rarely equal to one. Species availability can be estimated using multi-scale occupancy models; however, for the practical application of multi-scale occupancy models, it can be unclear what a robust sampling design looks like and what the statistical properties of the multi-scale and single-scale occupancy models are when availability is less than one.Using simulations, we explore the following common questions asked by ecologists during the design phase of a field study: (Q1) what is a robust sampling design for the multi-scale occupancy model when there are a priori expectations of parameter estimates? (Q2) what is a robust sampling design when we have no expectations of parameter estimates? and (Q3) can a single-scale occupancy model with a random effects term adequately absorb the extra heterogeneity produced when availability is less than one and provide reliable estimates of occupancy probability?Our results show that there is a tradeoff between the number of sites and surveys needed to achieve a specified level of acceptable error for occupancy estimates using the multi-scale occupancy model. We also document that when species availability is low (<0.40 on the probability scale), then single-scale occupancy models underestimate occupancy by as much as 0.40 on the probability scale, produce overly precise estimates, and provide poor parameter coverage. This pattern was observed when a random effects term was and was not included in the single-scale occupancy model, suggesting that adding a random-effects term does not adequately absorb the extra heterogeneity produced by the availability process. In contrast, when species availability was high (>0.60), single-scale occupancy models performed similarly to the multi-scale occupancy model.Users can further explore our results and sampling designs across a number of different scenarios using the RShiny app\u00a0https://gdirenzo.shinyapps.io/multi-scale-occ/. Our results suggest that unaccounted for availability can lead to underestimating species distributions when using single-scale occupancy models, which can have large implications on inference and prediction, especially for those working in the fields of invasion ecology, disease emergence, and species conservation.",
   "description": "15 p.",
   "publisher": {
     "@type": "Organization",
     "name": "British Ecological Society"
   },
   "author": [
     {
       "@type": "Person",
       "name": "Direnzo, Graziella Vittoria",
       "givenName": "Graziella Vittoria",
       "familyName": "Direnzo",
       "identifier": {
         "@type": "PropertyValue",
         "propertyID": "ORCID",
         "value": "0000-0001-5264-4762",
         "url": "https://orcid.org/0000-0001-5264-4762"
       },
       "affiliation": [
         {
           "@type": "Organization",
           "name": "Patuxent Wildlife Research Center",
           "url": "https://www.usgs.gov/centers/pwrc"
         }
       ]
     },
     {
       "@type": "Person",
       "name": "David A. W. Miller",
       "familyName": "David A. W. Miller",
       "affiliation": [
         {
           "@type": "Organization",
           "name": "Penn State University"
         }
       ]
     },
     {
       "@type": "Person",
       "name": "Campbell Grant, Evan H. ehgrant@usgs.gov",
       "givenName": "Evan H.",
       "familyName": "Campbell Grant",
       "email": "ehgrant@usgs.gov",
       "identifier": {
         "@type": "PropertyValue",
         "propertyID": "ORCID",
         "value": "0000-0003-4401-6496",
         "url": "https://orcid.org/0000-0003-4401-6496"
       },
       "affiliation": [
         {
           "@type": "Organization",
           "name": "Patuxent Wildlife Research Center",
           "url": "https://www.usgs.gov/centers/pwrc"
         }
       ]
     }
   ],
   "funder": [
     {
       "@type": "Organization",
       "name": "Coop Res Unit Leetown",
       "url": "https://www1.usgs.gov/coopunits/unit/Virginia"
     },
     {
       "@type": "Organization",
       "name": "Advanced Research Computing (ARC)",
       "url": "https://www.usgs.gov/ecosystems/land-change-science-program"
     }
   ]
 }

}