{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T03:06:27Z","timestamp":1788923187231,"version":"build-2803163510"},"reference-count":36,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2026,8,15]],"date-time":"2026-08-15T00:00:00Z","timestamp":1786752000000},"content-version":"am","delay-in-days":14,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,15]],"date-time":"2026-08-15T00:00:00Z","timestamp":1786752000000},"content-version":"vor","delay-in-days":14,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100011735","name":"Bioenergy Technologies Office","doi-asserted-by":"publisher","award":["DE\u2010EE0009279"],"award-info":[{"award-number":["DE\u2010EE0009279"]}],"id":[{"id":"10.13039\/100011735","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Ecology and Evolution"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Passive Acoustic Monitoring (PAM) is a novel method for estimating avian biodiversity, producing results comparable to traditional methods, such as point count surveys. However, uncertainty in the detection space around acoustic recording units (ARUs) can complicate monitoring designs and potentially lead to biased results. Therefore, understanding ARU detection space in different environments is essential to advancing the reliability of PAM for avian population monitoring. In this study, we used a distance\u2010based broadcasting method at seven distances from ARUs in grassland systems in eastern Nebraska, USA, to quantify the detection space for six focal species common in this landscape. We found that detection space was species\u2010specific but, overall, most confirmed detections (detection probability \u2265\u20090.50) occurred within 100\u2009m (m) of the ARU. Detectability was positively influenced by amplitude, while the effect of vocalization frequency varied, producing species\u2010specific differences in detectability. Detection space is a highly variable yet essential consideration in the design of large\u2010scale PAM systems, and its estimation should be a key first step in any PAM study. We demonstrate a replicable method for assessing detection space that can be applied in other ecosystems and for other bird species. Although more labor\u2010intensive than other approaches, this method provides reliable estimates of detection space, which are important considerations for the ongoing application of PAM technologies for biodiversity conservation.<\/jats:p>","DOI":"10.1002\/ece3.74181","type":"journal-article","created":{"date-parts":[[2026,8,15]],"date-time":"2026-08-15T07:20:30Z","timestamp":1786778430000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Detection Range of Acoustic Monitoring Devices in an Open Grassland Ecosystem"],"prefix":"10.1002","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2599-4935","authenticated-orcid":false,"given":"Grace E.","family":"Schuster","sequence":"first","affiliation":[{"name":"School of Natural Resources University of Nebraska\u2010Lincoln  Lincoln Nebraska USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6569-1223","authenticated-orcid":false,"given":"Leroy J.","family":"Walston","sequence":"additional","affiliation":[{"name":"Environmental Science Division Argonne National Laboratory  Lemont Illinois USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew R.","family":"Little","sequence":"additional","affiliation":[{"name":"School of Natural Resources University of Nebraska\u2010Lincoln  Lincoln Nebraska USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,15]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.2193\/2006-161"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.2307\/3803155"},{"key":"e_1_2_11_4_1","doi-asserted-by":"crossref","unstructured":"Barto\u0144 K.2010.\u201cMuMIn: Multi\u2010Model Inference.\u201dR package version 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