Shorebird Monitoring Using Spatially Explicit Occupancy and Abundance

Author:

Bohnett Eve12ORCID,Schulz Jessica3,Dobbs Robert4,Hoctor Thomas25,Hulse Dave26,Ahmad Bilal7ORCID,Rashid Wajid8ORCID,Waddle Hardin1

Affiliation:

1. U.S. Geological Survey, Gainesville, FL 32601, USA

2. Department of Landscape Architecture, University of Florida, Gainesville, FL 32601, USA

3. New Hampshire Department of Environmental Services, Concord, NH 03301, USA

4. Wildlife Diversity Program, Louisiana Department of Wildlife and Fisheries, Lafayette, CA 70506, USA

5. Center for Landscape Conservation Planning, University of Florida, Gainesville, FL 32601, USA

6. Florida Institute for Built Environment Resilience, University of Florida, Gainesville, FL 32601, USA

7. Institute of Agriculture Sciences and Forestry, University of Swat, Mingora 19130, Pakistan

8. Department of Environmental and Conservation Sciences, University of Swat, Mingora 19130, Pakistan

Abstract

Loss of habitat and human disturbance are major factors in the worldwide decline of shorebird populations, including that of the threatened migratory piping plover (Charadrius melodus). From 2013 to 2018, we conducted land-based surveys of the shorebird community every other week during the peak piping plover season (September to March). We assessed the ability of a thin plate spline occupancy model to identify hotspot locations on Whiskey Island, Louisiana, for the piping plover and four additional shorebird species (Wilson’s plover (Charadrius wilsonia), snowy plover (Charadrius nivosus), American oystercatcher (Haematopus palliatus), and red knot (Calidris canutus)). By fitting single-species occupancy models with geographic thin plate spline parameters, hotspot priority regions for conserving piping plovers and the multispecies shorebird assemblage were identified on the island. The occupancy environmental covariate, distance to the coastline, was weakly fitting, where the spatially explicit models were heavily dependent on the spatial spline parameter for distribution estimation. Additionally, the detectability parameters for Julian date and tide stage affected model estimations, resulting in seemingly inflated estimates compared to assuming perfect detection. The models predicted species distributions, biodiversity, high-use habitats for conservation, and multispecies conservation areas using a thin-plate spline for spatially explicit estimation without significant landscape variables, demonstrating the applicability of this modeling approach for defining areas on a landscape that are more heavily used by a species or multiple species.

Publisher

MDPI AG

Subject

Nature and Landscape Conservation,Ecology,Global and Planetary Change

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