Section 9.2: Using Mark-Recapture Models to Estimate Survival from Telemetry Data
Russell W. Perry, Theodore Castro-Santos, Christopher M. Holbrook, and Benjamin P. Sandford
Analyzing telemetry data within a mark–recapture framework is a powerful approach for estimating demographic parameters (e.g., survival and movement probabilities) that might otherwise be difficult to measure. Yet many studies using telemetry techniques focus on fish behavior and fail to recognize the potential of telemetry data to provide information about fish survival. The sophistication of both mark–recapture modeling and telemetry has dramatically improved since the 1980s, largely due to technological advancements in computing power (for mark–recapture models) and electronic components (for telemetry). Such advances now allow mark–recapture models to take advantage of the detailed information that telemetry techniques can provide.
The key feature of mark–recapture models is simultaneous estimation of detection and survival probabilities. With telemetry, a “capture” event consists of detecting a given tag code one or more times at a specific location or time. By contrast, in some studies interest may focus on the probability of detecting a single tag transmission (see Sections 7.2 and 9.1). Compared to conventional mark and recapture methods, telemetry methods often have greater detection probabilities due to large detection ranges, increased “effort” (i.e., continuous monitoring with autonomous receivers), and ability to simultaneously monitor multiple locations. Nonetheless, perfect detectability is rare in telemetry studies because both random (e.g., from electronic noise) and nonrandom processes (e.g., receiver loses power temporarily) can allow a fish to pass a receiver undetected. Failure to account for imperfect detection can lead to serious bias in survival estimates. When using telemetry to estimate survival, it is therefore critical to explicitly estimate detection probabilities to ensure unbiased estimates of survival (see Section 7.2). Fortunately, using telemetry techniques and mark–recapture models together yields the best of both worlds: Well-designed telemetry systems deliver high detection probabilities that result in precise estimates from small sample sizes. Mark–recapture models ensure estimates of the demographic parameters are unbiased with respect to the detection process.