Sea Turtle Nesting Patterns In Florida Vis-À-Vis Satellite-Derived Measures Of Artificial Lighting

Keywords

Artificial light; DMSP; light pollution; marine turtles; nest surveys; simultaneous autoregressive modeling

Abstract

Light pollution contributes to the degradation and reduction of habitat for wildlife. Nocturnally nesting and hatching sea turtle species are particularly sensitive to artificial light near nesting beaches. At local scales (0.01–0.1 km), artificial light has been experimentally shown to deter nesting females and disorient hatchlings. This study used satellite-based remote sensing to assess broad scale (~1–100s km) effects of artificial light on nesting patterns of loggerhead (Caretta caretta), leatherback (Dermochelys coriacea) and green turtles (Chelonia mydas) along the Florida coastline. Annual artificial nightlight data from 1992 to 2012 acquired by the Defense Meteorological Satellite Program (DMSP) were compared to an extensive nesting dataset for 368, ~1 km beach segments from this same 21-year period. Relationships between nest densities and artificial lighting were derived using simultaneous autoregressive models to adjust for the presence of spatial autocorrelation. Though coastal urbanization increased in Florida during this period, nearly two-thirds of the surveyed beaches exhibited decreasing light levels (N = 249); only a small fraction of the beaches showed significant increases (N = 52). Nest densities for all three sea turtle species were negatively influenced by artificial light at neighborhood scales (<100 km); however, only loggerhead and green turtle nest densities were influenced by artificial light levels at the individual beach scale (~1 km). Satellite monitoring shows promise for light management of extensive or remote areas. As the spectral, spatial, and temporal resolutions of the satellite data are coarse, ground measurements are suggested to confirm that artificial light levels on beaches during the nesting season correspond to the annual nightlight measures.

Publication Date

2-1-2016

Publication Title

Remote Sensing in Ecology and Conservation

Volume

2

Issue

1

Number of Pages

59-72

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1002/rse2.12

Socpus ID

85021419389 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85021419389

This document is currently not available here.

Share

COinS