Designing a Monitoring Program to Estimate Estuarine Survival of Anadromous Salmon Smolts: Simulating the Effect of Sample Design on Inference

• Published in: PloS one Vol. 10; no. 7; p. e0132912
• Main Authors: Romer, Jeremy D, Gitelman, Alix I, Clements, Shaun, Schreck, Carl B
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 21.07.2015; Public Library of Science (PLoS)
• Subjects: Acoustics; Algorithms; Animal Migration; Animals; Biotelemetry; Cell migration; Coasts; Computer Simulation; Conservation of Natural Resources - methods; Creeks & streams; Data recovery; Diurnal variations; Ecosystem; Estimates; Estuaries; Fish; Fishes; Life cycle engineering; Life Cycle Stages; Life cycles; Long term; Marking; Migration; Missing data; Monitoring; Oncorhynchus kisutch; Oncorhynchus mykiss; Oncorhynchus tshawytscha; Population; Probability; Recovery plans; Research Design; Restoration; Rivers; Salmon; Salmon - physiology; Salmonidae; Sampling; Sampling designs; Seasons; Simulation; Studies; Survival; Tagging; Telemetry; Trout; Variation
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0132912

A number of researchers have attempted to estimate salmonid smolt survival during outmigration through an estuary. However, it is currently unclear how the design of such studies influences the accuracy and precision of survival estimates. In this simulation study we consider four patterns of smolt survival probability in the estuary, and test the performance of several different sampling strategies for estimating estuarine survival assuming perfect detection. The four survival probability patterns each incorporate a systematic component (constant, linearly increasing, increasing and then decreasing, and two pulses) and a random component to reflect daily fluctuations in survival probability. Generally, spreading sampling effort (tagging) across the season resulted in more accurate estimates of survival. All sampling designs in this simulation tended to under-estimate the variation in the survival estimates because seasonal and daily variation in survival probability are not incorporated in the estimation procedure. This under-estimation results in poorer performance of estimates from larger samples. Thus, tagging more fish may not result in better estimates of survival if important components of variation are not accounted for. The results of our simulation incorporate survival probabilities and run distribution data from previous studies to help illustrate the tradeoffs among sampling strategies in terms of the number of tags needed and distribution of tagging effort. This information will assist researchers in developing improved monitoring programs and encourage discussion regarding issues that should be addressed prior to implementation of any telemetry-based monitoring plan. We believe implementation of an effective estuary survival monitoring program will strengthen the robustness of life cycle models used in recovery plans by providing missing data on where and how much mortality occurs in the riverine and estuarine portions of smolt migration. These data could result in better informed management decisions and assist in guidance for more effective estuarine restoration projects.