Spatially dynamic abundance patterns for a rare fish species.

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Title: Spatially dynamic abundance patterns for a rare fish species.
Authors: Steen, Valerie A.1 (AUTHOR) valerie.steen@gmail.com, Peterson, James T.2 (AUTHOR), Duarte, Adam3 (AUTHOR)
Source: Ecosphere. Jul2025, Vol. 16 Issue 7, p1-20. 20p.
Subject Terms: *Rare fishes, *Ecological models, *Estuaries, *Habitats, *Environmental indicators, *Species distribution, Spatial behavior
Geographic Terms: San Francisco Bay (Calif.)
Abstract: Recovery of rare and imperiled species is often supported by targeting the dynamic drivers of abundance patterns. However, knowledge of these drivers can be obscured by challenges stemming from species detectability and autocorrelated data. Longfin Smelt (Spirinchus thaleichthys) in the San Francisco Bay‐Delta have become rare as the result of dramatic declines in abundance. Abundance indices from a multitude of surveys in the Bay‐Delta have documented these declines, but utilizing survey data to support recovery has been more challenging. To elucidate the spatiotemporal drivers of Longfin Smelt abundance patterns, we employed spatial multistate ("abundant") dynamic occupancy models that integrated surveys across seasons from three fish monitoring programs. We found that species occupancy may be driven by broad‐scale temporal and spatial processes not accounted for in the environmental covariates we used given the relative importance of day of year and spatial and year random effects. However, we also found that relatively high abundance may be driven in part by local habitat conditions. Our analysis approach allowed us to capture various sources of heterogeneity in the data and map seasonal distribution and abundance patterns for this rare species that can be used to inform policy and management decisions in the Bay‐Delta. [ABSTRACT FROM AUTHOR]
Copyright of Ecosphere is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Spatially dynamic abundance patterns for a rare fish species.
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  Data: <searchLink fieldCode="AR" term="%22Steen%2C+Valerie+A%2E%22">Steen, Valerie A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> valerie.steen@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Peterson%2C+James+T%2E%22">Peterson, James T.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Duarte%2C+Adam%22">Duarte, Adam</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Ecosphere%22">Ecosphere</searchLink>. Jul2025, Vol. 16 Issue 7, p1-20. 20p.
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  Data: *<searchLink fieldCode="DE" term="%22Rare+fishes%22">Rare fishes</searchLink><br />*<searchLink fieldCode="DE" term="%22Ecological+models%22">Ecological models</searchLink><br />*<searchLink fieldCode="DE" term="%22Estuaries%22">Estuaries</searchLink><br />*<searchLink fieldCode="DE" term="%22Habitats%22">Habitats</searchLink><br />*<searchLink fieldCode="DE" term="%22Environmental+indicators%22">Environmental indicators</searchLink><br />*<searchLink fieldCode="DE" term="%22Species+distribution%22">Species distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Spatial+behavior%22">Spatial behavior</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22San+Francisco+Bay+%28Calif%2E%29%22">San Francisco Bay (Calif.)</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Recovery of rare and imperiled species is often supported by targeting the dynamic drivers of abundance patterns. However, knowledge of these drivers can be obscured by challenges stemming from species detectability and autocorrelated data. Longfin Smelt (Spirinchus thaleichthys) in the San Francisco Bay‐Delta have become rare as the result of dramatic declines in abundance. Abundance indices from a multitude of surveys in the Bay‐Delta have documented these declines, but utilizing survey data to support recovery has been more challenging. To elucidate the spatiotemporal drivers of Longfin Smelt abundance patterns, we employed spatial multistate ("abundant") dynamic occupancy models that integrated surveys across seasons from three fish monitoring programs. We found that species occupancy may be driven by broad‐scale temporal and spatial processes not accounted for in the environmental covariates we used given the relative importance of day of year and spatial and year random effects. However, we also found that relatively high abundance may be driven in part by local habitat conditions. Our analysis approach allowed us to capture various sources of heterogeneity in the data and map seasonal distribution and abundance patterns for this rare species that can be used to inform policy and management decisions in the Bay‐Delta. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Ecosphere is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1002/ecs2.70326
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      – Code: eng
        Text: English
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        PageCount: 20
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      – SubjectFull: Rare fishes
        Type: general
      – SubjectFull: Ecological models
        Type: general
      – SubjectFull: Estuaries
        Type: general
      – SubjectFull: Habitats
        Type: general
      – SubjectFull: Environmental indicators
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      – SubjectFull: Species distribution
        Type: general
      – SubjectFull: Spatial behavior
        Type: general
      – SubjectFull: San Francisco Bay (Calif.)
        Type: general
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      – TitleFull: Spatially dynamic abundance patterns for a rare fish species.
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            NameFull: Steen, Valerie A.
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            NameFull: Peterson, James T.
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            NameFull: Duarte, Adam
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            – D: 01
              M: 07
              Text: Jul2025
              Type: published
              Y: 2025
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