Knowledge of the spatial and temporal distribution of specific mortality sources is crucial for management of species that are vulnerable to human interactions. Beachcast carcasses represent an unknown fraction of at-sea mortalities. While a variety of physical (e.g., water temperature) and biological (e.g., decomposition) factors as well as the distribution of animals and their mortality sources likely affect the probability of carcass stranding, physical oceanography plays a major role in where and when carcasses strand. Here, we evaluate the influence of nearshore physical oceanographic and wind regimes on sea turtle strandings to decipher seasonal trends and make qualitative predictions about stranding patterns along oceanfront beaches. We use results from oceanic drift-bottle experiments to check our predictions and provide an upper limit on stranding proportions. We compare predicted current regimes from a 3D physical oceanographic model to spatial and temporal locations of both sea turtle carcass strandings and drift bottle landfalls. Drift bottle return rates suggest an upper limit for the proportion of sea turtle carcasses that strand (about 20%). In the South Atlantic Bight, seasonal development of along-shelf flow coincides with increased numbers of strandings of both turtles and drift bottles in late spring and early summer. The model also predicts net offshore flow of surface waters during winter - the season with the fewest relative strandings. The drift bottle data provide a reasonable upper bound on how likely carcasses are to reach land from points offshore and bound the general timeframe for stranding post-mortem (< two weeks). Our findings suggest that marine turtle strandings follow a seasonal regime predictable from physical oceanography and mimicked by drift bottle experiments. Managers can use these findings to reevaluate incidental strandings limits and fishery takes for both nearshore and offshore mortality sources. ?? 2005 Elsevier Ltd. All rights reserved.
Additional publication details
Interpreting the spatio-temporal patterns of sea turtle strandings: Going with the flow