IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0125198.html
   My bibliography  Save this article

Current Status of Western Yellow-Billed Cuckoo along the Sacramento and Feather Rivers, California

Author

Listed:
  • Mark D Dettling
  • Nathaniel E Seavy
  • Christine A Howell
  • Thomas Gardali

Abstract

To evaluate the current status of the western population of the Yellow-billed Cuckoo (Coccyzus americanus) along the Sacramento and Feather rivers in California’s Sacramento Valley, we conducted extensive call playback surveys in 2012 and 2013. We also quantified the amount and distribution of potential habitat. Our survey transects were randomly located and spatially balanced to sample representative areas of the potential habitat. We estimated that the total area of potential habitat was 8,134 ha along the Sacramento River and 2,052 ha along the Feather River, for a total of 10,186 ha. Large-scale restoration efforts have created potential habitat along both of these rivers. Despite this increase in the amount of habitat, the number of cuckoos we detected was extremely low. There were 8 detection occasions in 2012 and 10 occasions in 2013 on the Sacramento River, in both restored and remnant habitat. We had no detections on the Feather River in either year. We compared our results to 10 historic studies from as far back as 1972 and found that the Yellow-billed Cuckoo had unprecedentedly low numbers in 2010, 2012, and 2013. The current limiting factor for the Yellow-billed Cuckoo in the Sacramento Valley is likely not the amount of appropriate vegetation, as restoration has created more habitat over the last 30 years. Reasons for the cuckoo decline on the Sacramento and Feather rivers are unclear.

Suggested Citation

  • Mark D Dettling & Nathaniel E Seavy & Christine A Howell & Thomas Gardali, 2015. "Current Status of Western Yellow-Billed Cuckoo along the Sacramento and Feather Rivers, California," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-16, April.
  • Handle: RePEc:plo:pone00:0125198
    DOI: 10.1371/journal.pone.0125198
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0125198
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0125198&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0125198?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Stevens, Don L. & Olsen, Anthony R., 2004. "Spatially Balanced Sampling of Natural Resources," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 262-278, January.
    2. Penteriani, Vincenzo & Otalora, Fermín & Ferrer, Miguel, 2008. "Floater mortality within settlement areas can explain the Allee effect in breeding populations," Ecological Modelling, Elsevier, vol. 213(1), pages 98-104.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tomasz Bąk, 2021. "Spatial sampling methods modified by model use," Statistics in Transition New Series, Polish Statistical Association, vol. 22(2), pages 143-154, June.
    2. Lorenzo Fattorini & Timothy G. Gregoire & Sara Trentini, 2018. "The Use of Calibration Weighting for Variance Estimation Under Systematic Sampling: Applications to Forest Cover Assessment," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(3), pages 358-373, September.
    3. Pommerening, Arne & Szmyt, Janusz & Zhang, Gongqiao, 2020. "A new nearest-neighbour index for monitoring spatial size diversity: The hyperbolic tangent index," Ecological Modelling, Elsevier, vol. 435(C).
    4. Anton Grafström & Niklas L. P. Lundström & Lina Schelin, 2012. "Spatially Balanced Sampling through the Pivotal Method," Biometrics, The International Biometric Society, vol. 68(2), pages 514-520, June.
    5. Raphaël Jauslin & Bardia Panahbehagh & Yves Tillé, 2022. "Sequential spatially balanced sampling," Environmetrics, John Wiley & Sons, Ltd., vol. 33(8), December.
    6. Xin Zhao & Anton Grafström, 2020. "A sample coordination method to monitor totals of environmental variables," Environmetrics, John Wiley & Sons, Ltd., vol. 31(6), September.
    7. Huan Xie & Fang Wang & Yali Gong & Xiaohua Tong & Yanmin Jin & Ang Zhao & Chao Wei & Xinyi Zhang & Shicheng Liao, 2022. "Spatially Balanced Sampling for Validation of GlobeLand30 Using Landscape Pattern-Based Inclusion Probability," Sustainability, MDPI, vol. 14(5), pages 1-19, February.
    8. Linda Altieri & Daniela Cocchi, 2021. "Spatial Sampling for Non‐compact Patterns," International Statistical Review, International Statistical Institute, vol. 89(3), pages 532-549, December.
    9. Sara Franceschi & Rosa Maria Di Biase & Agnese Marcelli & Lorenzo Fattorini, 2022. "Some Empirical Results on Nearest-Neighbour Pseudo-populations for Resampling from Spatial Populations," Stats, MDPI, vol. 5(2), pages 1-16, April.
    10. Matthew Nahorniak & David P Larsen & Carol Volk & Chris E Jordan, 2015. "Using Inverse Probability Bootstrap Sampling to Eliminate Sample Induced Bias in Model Based Analysis of Unequal Probability Samples," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-19, June.
    11. Robertson, Blair & Price, Chris, 2024. "One point per cluster spatially balanced sampling," Computational Statistics & Data Analysis, Elsevier, vol. 191(C).
    12. Alcasena, Fermín J. & Salis, Michele & Nauslar, Nicholas J. & Aguinaga, A. Eduardo & Vega-García, Cristina, 2016. "Quantifying economic losses from wildfires in black pine afforestations of northern Spain," Forest Policy and Economics, Elsevier, vol. 73(C), pages 153-167.
    13. Kathryn M. Irvine & T. J. Rodhouse & Ilai N. Keren, 2016. "Extending Ordinal Regression with a Latent Zero-Augmented Beta Distribution," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(4), pages 619-640, December.
    14. B. L. Robertson & J. A. Brown & T. McDonald & P. Jaksons, 2013. "BAS: Balanced Acceptance Sampling of Natural Resources," Biometrics, The International Biometric Society, vol. 69(3), pages 776-784, September.
    15. Shepherd, Keith D. & Shepherd, Gemma & Walsh, Markus G., 2015. "Land health surveillance and response: A framework for evidence-informed land management," Agricultural Systems, Elsevier, vol. 132(C), pages 93-106.
    16. B. L. Robertson & O. Ozturk & O. Kravchuk & J. A. Brown, 2022. "Spatially Balanced Sampling with Local Ranking," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(4), pages 622-639, December.
    17. Jacopo Paglia & Jo Eidsvik & Juha Karvanen, 2022. "Efficient spatial designs using Hausdorff distances and Bayesian optimization," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1060-1084, September.
    18. Galizia, Luiz Felipe & Alcasena, Fermín & Prata, Gabriel & Rodrigues, Marcos, 2021. "Assessing expected economic losses from wildfires in eucalypt plantations of western Brazil," Forest Policy and Economics, Elsevier, vol. 125(C).
    19. Skinner, C. J., 2015. "Cross-classified sampling: some estimation theory," LSE Research Online Documents on Economics 62261, London School of Economics and Political Science, LSE Library.
    20. Lorenzo Fattorini & Marzia Marcheselli & Caterina Pisani & Luca Pratelli, 2022. "Design‐based properties of the nearest neighbor spatial interpolator and its bootstrap mean squared error estimator," Biometrics, The International Biometric Society, vol. 78(4), pages 1454-1463, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0125198. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.