Amos, A.F.

Kemp’s Ridley Sea Turtle (Lepidochelys kempii) Nesting on the Texas Coast: Geographic, Temporal, and Demographic Trends Through 2014

Kemp’s ridley (Lepidochelys kempii) is the world’s most endangered sea turtle species, and nests primarily on the Gulf of Mexico coast in Mexico. In 1978, a binational project was initiated to form a secondary nesting colony of this species in south Texas at Padre Island National Seashore (PAIS), as a safeguard against extinction. During 1978–2014, we documented 1,667 Kemp’s ridley nests in Texas, with 56% found at PAIS. Most nests (89%) found in south Texas were from wild-stock turtles; south Texas is the northern extent of the documented historic nesting range for the species. We documented nesting in north Texas starting in 2002, and most nests (53%) found there were from turtles that had been head-started (reared in captivity for 9–11 mo), and released off the Texas coast as yearlings. Kemp’s ridley nesting increased in Texas during the mid-1990s through 2009, before annual nest numbers dropped in 2010, rebounded and plateaued in 2011 and 2012, and then decreased again in 2013 and 2014. Annual numbers of nests found in Texas and Mexico followed similar trends and were correlated (R2 1⁄4 0.95). We examined nesting turtles for presence of tags at 55% of the nests located in Texas. Of the Kemp’s ridleys we examined during 2000–14, the annual percentage of apparent neophytes decreased and the annual percentage of remigrants increased over time. Mean annual remigration intervals of Kemp’s ridleys increased steadily from 1.9 yr in 2008 to 3.3 yr in 2014. These changes in demographic parameters are critical to understanding the recent fluctuation in the number of nesting Kemps ridleys and will be used in population models to investigate possible causes of the recent and sudden decline of nesting Kemp’s ridleys in Texas and Mexico. 

Date
2016
Data type
Scientific article
Theme
Research and monitoring

Development of a Kemp’s Ridley Sea Turtle Stock Assessment Model

We developed a Kemp’s ridley (Lepidochelys kempii) stock assessment model to evaluate the relative contributions of conservation efforts and other factors toward this critically endangered species’ recovery. The Kemp’s ridley demographic model developed by the Turtle Expert Working Group (TEWG) in 1998 and 2000 and updated for the binational recovery plan in 2011 was modified for use as our base model. The TEWG model uses indices of the annual reproductive population (number of nests) and hatchling recruitment to predict future annual numbers of nests on the basis of a series of assumptions regarding age and maturity, remigration interval, sex ratios, nests per female, juvenile mortality, and a putative ‘‘turtle excluder device effect’’ multiplier starting in 1990. This multiplier was necessary to fit the number of nests observed in 1990 and later. We added the effects of shrimping effort directly, modified by habitat weightings, as a proxy for all sources of anthropogenic mortality. Additional data included in our model were incremental growth of Kemp’s ridleys marked and recaptured in the Gulf of Mexico, and the length frequency of stranded Kemp’s ridleys. We also added a 2010 mortality factor that was necessary to fit the number of nests for 2010 and later (2011 and 2012). Last, we used an empirical basis for estimating natural mortality, on the basis of a Lorenzen mortality curve and growth estimates. Although our model generated reasonable estimates of annual total turtle deaths attributable to shrimp trawling, as well as additional deaths due to undetermined anthropogenic causes in 2010, we were unable to provide a clear explanation for the observed increase in the number of stranded Kemp’s ridleys in recent years, and subsequent disruption of the species’ exponential growth since the 2009 nesting season. Our consensus is that expanded data collection at the nesting beaches is needed and of high priority, and that 2015 be targeted for the next stock assessment to evaluate the 2010 event using more recent nesting and in-water data. 

Date
2016
Data type
Scientific article
Theme
Research and monitoring