2017
DOI: 10.1111/fme.12257
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Understanding imperfect detection in a San Francisco Estuary long‐term larval and juvenile fish monitoring programme

Abstract: Imperfect detection can present a significant challenge when monitoring for a rare and imperilled species. Here, a long-term larval and early-juvenile fish monitoring programme in the upper San Francisco Estuary was examined to evaluate its overall reliability in detecting various fish species, including the imperilled delta smelt, Hypomesus transpacificus McAllister, for which the programme was designed. Using occupancy modelling, detection probability of species with pelagic larval or juvenile life stages wa… Show more

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Cited by 20 publications
(29 citation statements)
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“…, Mahardja et al. ). Contrary to the constant impact assumption, the completely catchable assumption is likely not able to be addressed through increased computational power alone.…”
Section: Discussionmentioning
confidence: 99%
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“…, Mahardja et al. ). Contrary to the constant impact assumption, the completely catchable assumption is likely not able to be addressed through increased computational power alone.…”
Section: Discussionmentioning
confidence: 99%
“…While it is generally presumed that the efficiency of the 20-mm net at capturing delta smelt increases with fish size (Kimmerer 2008, Merz et al 2011, no published studies have explicitly quantified the efficiency of the net, either generally or as a function of size. Previous work suggests net efficiency increases with size up tõ 15 mm and then does not change with size for larger smelt (Merz et al 2011), although that conclusion is contingent upon the model used and it is possible that larger smelt may exhibit a decreased detection probability (Mahardja et al 2017). For the present analyses, we restricted our dataset to smelt that were at least 15 mm in length and made the assumption that smelt over 15 mm do not show a change in detection with size, allowing us to avoid the complexity associated with modeling the smelt size distribution alongside their population density.…”
Section: Data Preparation and Summarymentioning
confidence: 95%
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