Date of Graduation

2017

Document Type

Thesis

Degree Type

MS

College

Davis College of Agriculture, Natural Resources and Design

Department

Wildlife and Fisheries Resources

Committee Chair

James T Anderson

Committee Co-Chair

Todd E Katzner

Committee Member

Amy B Welsh

Abstract

Secretive marsh birds are challenging to monitor due to the difficulty in locating and trapping them within the dense emergent vegetation they occupy. Recently autonomous recording units (ARUs) have emerged as a novel alternative method to survey birds, although the technology has only been applied to a few species in specific field settings. There is limited information on how ARUs compare to human surveyors or how best to use ARU data that can be collected continuously. This thesis examines the applicability of ARUs for monitoring King (Rallus elegans) and Clapper ( R. crepitans) rails (collectively "rails") in two tidal marsh riverine systems of the Chesapeake Bay within intracoastal Virginia. It includes three chapters: (1) an evaluation of autonomous acoustic surveying techniques for rails; (2) an investigation of diel variation in detection and vocalization rates of rails; and, (3) a utilization of acoustic recordings to assess occupancy and distribution of rails. In the first chapter, I evaluated the effectiveness of an ARU in replacing human personnel by comparing the results of callback point count surveys to concurrent ARU sampling. The success of ARUs at detecting rails that human observers recorded decreased with distance (P ? 0.001), such that ARUs detected 90.3% of rails 75 m. I also investigated the use of subsampling schemes for 720 hours of continuous ARU data and recommended using a minimum of 30 minute subsampling intervals to effectively survey for presence and call rates of rails. In my second chapter, I investigated diel variation in rail vocal behavior using 3,600 hours of audio. I showed that naive rail occupancy did not vary hourly at either the marsh- or study area-level. Detection rates of rails varied as a function of time of day, marsh location, tidal stage, and date. However, vocalization rates varied as a function of time of day, marsh location, and date. Rail detections and vocalizations varied across marshes (P < 0.01) and decreased as the sampling season progressed. Rail detection was greatest during low tides rising (P < 0.01). Although there were statistically significant differences in hourly detection and vocalization rates (P < 0.01), because there were no patterns in these difference, they may not be biologically relevant and likely are of little use to management. In my third chapter, I evaluated the use of ARUs in conjunction with occupancy models. I found that both marsh riverine systems exhibited similarities in both mean occupancy probability of rails and detection probabilities, although their probabilities were explained by varying covariates by model selection. Areas of higher salinity produced higher estimates of occupancy probability by a factor of 1.62 (95% CI: 0.6, 2.65) per ppt of salinity. However, estimates of detection probability decreased by 0.02 (95% CI: -0.03, 0) per day as the season progressed. This multidimensional assessment of ARUs for monitoring King-Clapper Rails provides insight into the applicability of this alternative management tool for conducting long-term continuous monitoring over large spatial and temporal scales. Overall, species-, habitat-, and ARU-specific limitations to ARU sampling should be considered when making inferences about abundances and distributions from acoustic data.

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