4.7 Article

The Influence of Satellite-Derived Environmental and Oceanographic Parameters on Marine Turtle Time at Surface in the Gulf of Mexico

期刊

REMOTE SENSING
卷 14, 期 18, 页码 -

出版社

MDPI
DOI: 10.3390/rs14184534

关键词

dive behavior; marine turtle; Gulf of Mexico; satellite remote sensing; generalized additive models; bio-logging

资金

  1. U.S. Geological Survey (USGS) Ecosystems Mission Area Species Management Research program
  2. USGS Priority Ecosystems Science Program
  3. USGS Coastal and Marine Geology Program
  4. USGS Natural Resource Protection Program
  5. Natural Resource Damage Assessment for the Deepwater Horizon Oil Spill
  6. National Park Service

向作者/读者索取更多资源

The lack of baseline data for marine turtles in the Gulf of Mexico, especially after the Deepwater Horizon oil spill in 2010, has been highlighted. In this study, we analyzed dive and spatial data from satellite tags attached to threatened or endangered marine turtles over a period of 10 years. By examining environmental factors such as depth, salinity, and frontal features, we found that these factors are associated with the time marine turtles spend at the surface. This research contributes to a better understanding of turtle density and abundance estimates.
The aftermath of the 2010 Deepwater Horizon oil spill highlighted the lack of baseline spatial, behavioral, and abundance data for many species, including imperiled marine turtles, across the Gulf of Mexico. The ecology of marine turtles is closely tied to their vertical movements within the water column and is therefore critical knowledge for resource management in a changing ocean. A more comprehensive understanding of diving behavior, specifically surface intervals, can improve the accuracy of density and abundance estimates by mitigating availability bias. Here, we focus on the proportion of time marine turtles spend at the top 2 m of the water column to coincide with depths where turtles are assumed visible to observers during aerial surveys. To better understand what environmental and oceanographic conditions influence time at surface, we analyzed dive and spatial data from 136 satellite tags attached to three species of threatened or endangered marine turtles across 10 years. We fit generalized additive models with 11 remotely sensed covariates, including sea surface temperature (SST), bathymetry, and salinity, to examine dive patterns. Additionally, the developed model is the first to explicitly examine the potential connection between turtle dive patterns and ocean frontal zones in the Gulf of Mexico. Our results show species-specific associations of environmental covariates related to increased time at surface, particularly for depth, salinity, and frontal features. We define seasonal and spatial variation in time-at-surface patterns in an effort to contribute to marine turtle density and abundance estimates. These estimates could then be utilized to generate correction factors for turtle detection availability during aerial surveys.

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