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Testing assumptions for conservation of migratory shorebirds and coastal managed wetlands

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Abstract

Managed wetlands provide critical foraging and roosting habitats for shorebirds during migration; therefore, ensuring their availability is a priority action in shorebird conservation plans. Contemporary shorebird conservation plans rely on a number of assumptions about shorebird prey resources and migratory behavior to determine stopover habitat requirements. For example, the US Shorebird Conservation Plan for the Southeast-Caribbean region assumes that average benthic invertebrate biomass in foraging habitats is 2.4 g dry mass m−2 and that the dominant prey item of shorebirds in the region is Chironomid larvae. For effective conservation and management, it is important to test working assumptions and update predictive models that are used to estimate habitat requirements. We surveyed migratory shorebirds and sampled the benthic invertebrate community in coastal managed wetlands of South Carolina. We sampled invertebrates at three points in time representing early, middle, and late stages of spring migration, and concurrently surveyed shorebird stopover populations at approximately 7-day intervals throughout migration. We used analysis of variance by ranks to test for temporal variation in invertebrate biomass and density, and we used a model based approach (linear mixed model and Monte Carlo simulation) to estimate mean biomass and density. There was little evidence of a temporal variation in biomass or density during the course of spring shorebird migration, suggesting that shorebirds did not deplete invertebrate prey resources at our site. Estimated biomass was 1.47 g dry mass m−2 (95 % credible interval 0.13–3.55), approximately 39 % lower than values used in the regional shorebird conservation plan. An additional 4728 ha (a 63 % increase) would be required if habitat objectives were derived from biomass levels observed in our study. Polychaetes, especially Laeonereis culveri (2569 individuals m−2), were the most abundant prey in foraging habitats at our site. Polychaetes have lower caloric content than levels assumed in the regional plan; when lower caloric content and lower biomass levels are used to determine habitat objectives, an additional 6395 ha would be required (86 % increase). Shorebird conservation and management plans would benefit from considering the uncertainty in parameters used to derive habitat objectives, especially biomass and caloric content of prey resources. Iterative testing of models that are specific to the planning region will provide rapid advances for management and conservation of migratory shorebirds and coastal managed wetlands.

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Acknowledgments

A. Brees, F. Collazo, and J. Perkins provided expert assistance in the field. We thank R. Joyner, Center Manager, and the staff of the Tom Yawkey Wildlife Center for logistic support. Funding was provided by the US Geological Survey Species at Risk Program. B. Andres and two anonymous referees provided helpful comments on the manuscript. The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the US Fish and Wildlife Service. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the US Government.

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Author notes

  1. Garth Herring

    Present address: Forest and Rangeland Ecosystem Science Center, U.S. Geological Survey, Corvallis, OR, 97331, USA

Authors and Affiliations

  1. Division of Migratory Bird Management, U.S. Fish and Wildlife Service, Patuxent Wildlife Research Center, 11510 American Holly Drive, Laurel, MD, 20708, USA

    James E. Lyons

  2. North Carolina Cooperative Fish and Wildlife Research Unit, North Carolina State University, U.S. Geological Survey, Raleigh, NC, 27695, USA

    Jaime A. Collazo & Garth Herring

Authors
  1. James E. Lyons
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Corresponding author

Correspondence to James E. Lyons.

Electronic supplementary material

Appendix: Example R code for fitting linear mixed model and Monte Carlo simulation

Appendix: Example R code for fitting linear mixed model and Monte Carlo simulation

# final model by REML

fm3b.lmer < - lmer(log(biomass.s + 0.5) ∼ 1 + (1|impoundment), data = df1, REML = TRUE)

# prediction interval with predictive and inferential uncertainty

n.sim < - 1000

library(arm)

fm3.sim < - sim(fm3b.lmer, n.sim)

fixef.fm3.sim < - fixef(fm3.sim)

sigma.fm3.sim < - sigma.hat(fm3.sim)

pred < - rnorm(n.sim, fixef.fm3.sim, sigma.fm3.sim)

unlogged < - (exp(pred)-0.5)*42.441318

quantile(unlogged[unlogged >=0], c(0.025, 0.5, 0.975))

Although this program has been used by the U.S. Geological Survey (USGS), no warranty, expressed or implied, is made by the USGS or the U.S. Government as to the accuracy and functioning of the program and related program material nor shall the fact of distribution constitute any such warranty, and no responsibility is assumed by the USGS in connection therewith.

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Lyons, J.E., Collazo, J.A. & Herring, G. Testing assumptions for conservation of migratory shorebirds and coastal managed wetlands. Wetlands Ecol Manage 24, 507–520 (2016). https://doi.org/10.1007/s11273-015-9477-4

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