Discrete-space continuous-time models of marine mammal exposure to Navy sonar.
Charlotte M Jones-Todd, Enrico Pirotta, John W Durban, Diane E Claridge, Robin W Baird, Erin A Falcone, Gregory S Schorr, Stephanie Watwood, Len Thomas
Author Information
Charlotte M Jones-Todd: Department of Statistics, University of Auckland, Auckland, 1142, New Zealand. ORCID
Enrico Pirotta: Department of Mathematics and Statistics, Washington State University, 14204 NE Salmon Creek Avenue, Vancouver, Washington, 98686, USA. ORCID
John W Durban: Southall Environmental Associates Inc., 9099 Soquel Drive, Suite 8, Aptos, California, 95003, USA.
Diane E Claridge: Bahamas Marine Mammal Research Organization, Marsh Harbour, Abaco, Bahamas.
Robin W Baird: Cascadia Research Collective, 218 ½ W. 4th Avenue, Olympia, Washington, 98501, USA.
Erin A Falcone: Marine Ecology and Telemetry Research, 2420 Nellita Road NW, Seabeck, Washington, 98380, USA.
Gregory S Schorr: Marine Ecology and Telemetry Research, 2420 Nellita Road NW, Seabeck, Washington, 98380, USA.
Stephanie Watwood: Naval Undersea Warfare Center Division, Code 70T, Newport, Rhode Island, 02841, USA.
Len Thomas: Centre for Research into Ecological and Environmental Modelling, The Observatory, University of St Andrews, St Andrews, KY16 9LZ, UK.
Assessing the patterns of wildlife attendance to specific areas is relevant across many fundamental and applied ecological studies, particularly when animals are at risk of being exposed to stressors within or outside the boundaries of those areas. Marine mammals are increasingly being exposed to human activities that may cause behavioral and physiological changes, including military exercises using active sonars. Assessment of the population-level consequences of anthropogenic disturbance requires robust and efficient tools to quantify the levels of aggregate exposure for individuals in a population over biologically relevant time frames. We propose a discrete-space, continuous-time approach to estimate individual transition rates across the boundaries of an area of interest, informed by telemetry data collected with uncertainty. The approach allows inferring the effect of stressors on transition rates, the progressive return to baseline movement patterns, and any difference among individuals. We apply the modeling framework to telemetry data from Blainville's beaked whale (Mesoplodon densirostris) tagged in the Bahamas at the Atlantic Undersea Test and Evaluation Center (AUTEC), an area used by the U.S. Navy for fleet readiness training. We show that transition rates changed as a result of exposure to sonar exercises in the area, reflecting an avoidance response. Our approach supports the assessment of the aggregate exposure of individuals to sonar and the resulting population-level consequences. The approach has potential applications across many applied and fundamental problems where telemetry data are used to characterize animal occurrence within specific areas.
