Record Details
Defining habitat preferences of pelagic loggerhead sea turtles (Caretta caretta) in the North Atlantic through analysis of behavior and bycatch
ScholarsArchive at Oregon State University
| Field | Value |
|---|---|
| Title | Defining habitat preferences of pelagic loggerhead sea turtles (Caretta caretta) in the North Atlantic through analysis of behavior and bycatch |
| Names |
McCarthy, Abigail L.
(creator) Heppell, Selina S. (advisor) |
| Date Issued | 2007-02-05T17:12:04Z (iso8601) |
| Internet Media Type | application/pdf |
| Note | Graduation date: 2007 |
| Abstract | For many species of marine turtle the characteristics that define pelagic habitat have yet to be fully identified. A better understanding of these habitat characteristics is critical to reduce high seas fisheries interactions with turtles, especially as the status of many turtle populations has placed them on the threatened or endangered species list. The combination of high-resolution satellite-tracking data with remotely sensed oceanographic data makes it possible to identify habitat for loggerhead turtles by analyzing the behavior of individual animals. Bycatch of loggerhead turtles in longline fisheries can also be examined using the same high-resolution oceanographic data to determine if there are identifiable habitat differences in high- and low- bycatch areas. I analyzed the tracks of ten loggerhead turtles tagged in the spring and fall of 1998 near Madeira, Portugal in relation to the marine environment they occupied. To determine the relationship between an individual turtle and its environment, some measure of behavior was necessary. I calculated the straightness index (SI), the ratio of the displacement of the animal to the total distance traveled, for individual weekly segments of the ten tracks as a measure of individual behavior. I then extracted information about the chlorophyll, sea-surface temperature (SST), bathymetry, and geostrophic current of the ocean in a 20km buffer surrounding the tracks, and examined the relationship between the straightness index and those characteristics using logistic regression. Chlorophyll a value, bathymetry, and movement of the turtle with geostrophic currents were consistently related to the straightness index of the tracks of all ten animals (two-sided p-value from Wald's test: 0.005, 0.0017, and 0.0018, respectively). Tracks were less straight in high chlorophyll regions and in shallower ocean areas, and animals were more likely to be moving with prevailing geostrophic currents during straighter track segments. These results confirm comparable analyses of loggerhead tracks in the Pacific, and indicate that sea turtles alter their behavior (likely representing a shift from traveling to foraging) when they encounter high-chlorophyll regions. Turtles with highly sinuous tracks spend more time in a given area or habitat than those who pass straight through, and therefore may be more susceptible to incidental capture by fisheries operating in those habitats. To address the fisheries bycatch/ habitat interactions I analyzed longline bycatch data to determine whether the marine environmental variables identified in the first part of my study were related to the probability of catching a turtle on a given longline set. I performed a logistic regression analysis using bycatch of turtles as the response variable, and bathymetry, SST, SST gradient (indicative of frontal activity), chlorophyll a, and chlorophyll a gradient as the independent variables. I also included the location and the date of the longline sets as potential predictor variables. I found that the most important variables predicting the odds that a turtle would be caught on a given set were chlorophyll a value in the area of the haul ( Wald's test, p=0.009) and the latitude at the beginning of the haul (Wald's test, p=0.0005). Turtles were more likely to be caught on sets in lower chlorophyll regions and in higher latitude regions of the data set, and there was no indication of important effects of bathymetry. These results disagree with my predictions from the tracking analysis, either because the fisheries-dependent bycatch data set did not provide enough contrast of habitat types, or because bycatch probability is not related to turtle behavior. My results indicate a difference between the critical variables selected as predictors of turtle habitat using the bycatch data and those selected using the behavior of individual tracked animals. While bycatch information is important, the distribution of fisheries data is highly biased towards frontal zones and regions of historic high catch. Judgments about turtle behavior based on only fisheries interactions could lead to incorrect conclusions about where animals spend the majority of their time. Assuming that animals are more likely to have an increased probability of interaction with longlines in areas where they spend more time foraging, fishing pressure should be reduced in those areas of high-use for pelagic loggerheads. It is crucial to base fisheries time-area closures and the design of marine protected areas on the behavior of tracked animals, and not just on fisheries bycatch data. |
| Genre | Thesis |
| Topic | sea turtle |
| Identifier | http://hdl.handle.net/1957/3919 |
