Estimates of tidal-marsh bird densities using Bayesian networks

Whitney A. Wiest, Maureen D. Correll, Bruce G. Marcot, Brian J. Olsen, Chris S. Elphick, Thomas P. Hodgman, Glenn R. Guntenspergen, W. Gregory Shriver

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Conserving tidal-marsh bird communities requires strategies to address continuing pressures from human development to the effects of increasing rates of sea-level rise. Knowing tidal-marsh bird distributions and population sizes are important for developing these strategies. In the Northeast United States, where estimates of sea-level rise are 3 times higher than the global average, 5 bird species are tidal-marsh specialists: clapper rail (Rallus crepitans), willet (Tringa semipalmata), Nelson's sparrow (Ammospiza nelsoni), saltmarsh sparrow (A. caudacuta), and seaside sparrow (A. maritima). We used a regional marsh bird survey to develop Bayesian network models to identify factors that influence patch-scale species density and to estimate regional population sizes. We modeled species density as a function of habitat covariates at the patch, local, landscape, and regional spatial scales. Densities were most sensitive to patch location and dimension, patch geomorphic setting, indices of human development, and changes in mean sea level. We estimated 110,000 clapper rails (95% CI = 61,000–159,000), 111,000 willets (95% CI = 70,000–152,000), 7,000 Nelson's sparrows (95% CI = 4,000–10,000), 60,000 saltmarsh sparrows (95% CI = 40,000–80,000), and 234,000 seaside sparrows (95% CI = 112,000–356,000) from the United States–Canada border to, and including, the mouth of the Chesapeake Bay, Virginia, USA. Our abundance estimates can be used to identify priority conservation areas at multiple geographic scales and our models help identify key habitat and landscape components for tidal-marsh restoration and management to benefit tidal-marsh birds and can be modified for other species.

Original languageEnglish (US)
Pages (from-to)109-120
Number of pages12
JournalJournal of Wildlife Management
Volume83
Issue number1
DOIs
StatePublished - Jan 2019
Externally publishedYes

Bibliographical note

Funding Information:
The findings and conclusions in this article are those of the author(s) and do not necessarily represent the views of the United States Forest Service (USFS) or United States Fish and Wildlife Service. Any use of trade, commercial and non-commercial products, or firm names is for descriptive purposes only and does not imply endorsement by the United States Government. We thank the Saltmarsh Habitat and Avian Research Program, Northeast partners, field crews, and private landowners for their assistance with the regional marsh bird survey. G. R. Guntenspergen acknowledges support from the U.S. Geological Survey (USGS) Land Change Science Program and the USGS Ecosystem Program. B. G. Marcot acknowledges the USGS and USFS Interagency Agreement. We thank J. B. Grace for his early input in model development and other helpful discussions for this paper. No funders had input on this manuscript nor required approval of the manuscript before submission or publication. Funding was provided by a Competitive State Wildlife Grant (U2-5-R-1) via Federal Aid in Sportfish and Wildlife Restoration to the States of Delaware, Maryland, Connecticut, and Maine. Additional funding was provided by Northeast Regional Conservation Needs Grant 2010-03, National Science Foundation RAPID Grant DEB-1340008, and Audubon New York.

Funding Information:
The findings and conclusions in this article are those of the author(s) and do not necessarily represent the views of the United States Forest Service (USFS) or United States Fish and Wildlife Service. Any use of trade, commercial and noncommercial products, or firm names is for descriptive purposes only and does not imply endorsement by the United States Government. We thank the Saltmarsh Habitat and Avian Research Program, Northeast partners, field crews, and private landowners for their assistance with the regional marsh bird survey. G. R. Guntenspergen acknowledges support from the U.S. Geological Survey (USGS) Land Change Science Program and the USGS Ecosystem Program. B. G. Marcot acknowledges the USGS and USFS Interagency Agreement. We thank J. B. Grace for his early input in model development and other helpful discussions for this paper. No funders had input on this manuscript nor required approval of the manuscript before submission or publication. Funding was provided by a Competitive State Wildlife Grant (U2-5-R-1) via Federal Aid in Sportfish and Wildlife Restoration to the States of Delaware, Maryland, Connecticut, and Maine. Additional funding was provided by Northeast Regional Conservation Needs Grant 2010-03, National Science Foundation RAPID Grant DEB-1340008, and Audubon New York.

Keywords

  • Bayesian network
  • Northeast USA
  • density
  • model-based
  • monitoring
  • predictive model
  • tidal-marsh birds

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