Imperfect detection and misidentification affect inferences from data informing water operation decisions

Abstract

AbstractObjectiveManagers can modify river flow regimes using fish monitoring data to minimize impacts from water management infrastructure. For example, operation of the gate‐controlled Delta Cross Channel (DCC) in California can negatively affect the endangered Sacramento River Winter‐run Chinook Salmon Oncorhynchus tshawytscha. Although guidelines have been developed for DCC operations using real‐time juvenile fish sampling count data, there is uncertainty about how environmental conditions influence fish occupancy and to what extent those relationships are affected by sampling and identification error.MethodsWe evaluated the effect of environmental conditions, imperfect detection, and misidentification error on salmon occupancy by analyzing data using hierarchical multistate occupancy models. A total of 14,147 trawl tows and beach seine hauls were conducted on 1,058 sampling days between October and December from 1996 to 2019. During these surveys, 2,803 juvenile Winter‐run Salmon were identified, and approximately 29% of the sampling days had at least one juvenile Winter‐run Salmon detected.ResultsThe probability of misidentifying an individual juvenile Winter‐run Salmon in the field was estimated to be 0.056 based on fish identification examinations and genetic sampling. Occupancy varied considerably and was related to flow characteristics, water clarity, weather, time of year, and whether occupancy was detected during the previous sampling day. However, these relationships and their significance changed considerably when accounting for imperfect detection and the probability of misidentifying individual juvenile salmon. Detection was less than 0.3 under average sampling conditions during a single sample and was influenced by flow, water clarity, site and volume sampled.ConclusionOur modeling results indicate that DCC gate closure decisions could occur on fewer days when not accounting for imperfect detection and misidentification error. These findings demonstrate the need to account for identification and detection error while using monitoring data to assess factors influencing fish occupancy and inform future management decisions.