@article{fdi:010074075,
  title = {{L}ikely locations of sea turtle stranding mortality using experimentally-calibrated, time and space-specific drift models},
  author = {{S}antos, {B}. {S}. and {F}riedrichs, {M}. {A}. {M}. and {R}ose, {S}. {A}. and {B}arco, {S}. {G}. and {K}aplan, {D}avid},
  editor = {},
  language = {{ENG}},
  abstract = {{S}ea turtle stranding events provide an opportunity to study drivers of mortality, but causes of strandings are poorly understood. {A} general sea turtle carcass oceanographic drift model was developed to estimate likely mortality locations from coastal sea turtle stranding records. {K}ey model advancements include realistic direct wind forcing on carcasses, temperature driven carcass decomposition and the development of mortality location predictions for individual strandings. {W}e applied this model to 2009-2014 stranding events within the {C}hesapeake {B}ay, {V}irginia. {P}redicted origin of vessel strike strandings were compared to commercial vessel data, and potential hazardous turtle-vessel interactions were identified in the southeastern {B}ay and {J}ames {R}iver. {C}ommercial fishing activity of gear types with known sea turtle interactions were compared to predicted mortality locations for stranded turtles with suggested fisheries-induced mortality. {P}robable mortality locations for these strandings varied seasonally, with two distinct areas in the southwest and southeast portions of the lower {B}ay. {S}patial overlap was noted between potential mortality locations and gillnet, seine, pot, and pound net fisheries, providing important information for focusing future research on mitigating conflict between sea turtles and human activities. {O}ur ability to quantitatively assess spatial and temporal overlap between sea turtle mortality and human uses of the habitat were hindered by the low resolution of human use datasets, especially those for recreational vessel and commercial fishing gear distributions. {T}his study highlights the importance of addressing these data gaps and provides a meaningful conservation tool that can be applied to stranding data of sea turtles and other marine megafauna worldwide.},
  keywords = {{S}ea turtle strandings ; {S}ea turtle mortality ; {C}hesapeake {B}ay ; {D}rift simulations ; {F}isheries and vessel interactions ; {E}ndangered species ; {M}arine conservation ; {P}rotected species management ; {ETATS} {UNIS} ; {ATLANTIQUE} {NORD} {OUEST} ; {CHESAPEAKE} {BAIE}},
  booktitle = {},
  journal = {{B}iological {C}onservation},
  volume = {226},
  numero = {},
  pages = {127--143},
  ISSN = {0006-3207},
  year = {2018},
  DOI = {10.1016/j.biocon.2018.06.029},
  URL = {https://www.documentation.ird.fr/hor/fdi:010074075},
}