Spatial and temporal variation in positioning probability of acoustic telemetry arrays: fine-scale variability and complex interactions

BACKGROUND: As popularity of positional acoustic telemetry systems increases, so does the need to better understand how they perform in real-world applications, where variation in performance can bias study conclusions. Studies assessing variability in positional telemetry system performance have focused primarily on position accuracy, or comparing performance inside and outside the array. Here, we explored spatial and temporal variation in positioning probability within a 140-receiver Vemco Positioning System (VPS) array used to monitor lake trout, Salvelinus namaycush, spawning behavior over 23 km² in Lake Huron, North America. METHODS: Variability in VPS positioning probability was assessed between August and November from 2012 to 2014 using 43 stationary transmitters distributed throughout the array. Various analyses were used to relate positioning probability to number of fish transmitters in the array, wave height, and thermal stratification. We also assessed the prevalence of ‘close proximity detection interference’ (CPDI) in our array by analyzing detection probability of 35 transmitters on collocated receivers. RESULTS: Positioning probability of the VPS array varied greatly over time and space. Number of fish transmitters present in the array was a significant driver of reduced positioning probability, especially during lake trout spawning period when the fish were aggregated. Relationships between positioning probability and environmental variables were complex and varied over small spatial and temporal scales. One possible confounding variable was the large range of water depth over which receivers were deployed. Another confounding factor was the high prevalence of CPDI, which decreased exponentially with water depth and was less evident when wave heights were higher than normal. CONCLUSIONS: Some variables that negatively influenced positioning can be minimized through careful planning (e.g., number of tagged fish released, transmitter power level). However, results suggested that the acoustic environment was highly variable over small spatial and temporal scales in response to complex interactions between many variables. Therefore, models that predict positioning or detection efficiencies as a function of environmental variables may not be attainable in most systems. The best defense against biased study conclusions is incorporation of in situ measures of system performance that allow for retrospective analysis of array performance after a study is completed.