A spatial point process model to estimate individual centres of activity from passive acoustic telemetry data. Issue 11 (11th September 2018)

• Record Type: Journal Article
• Authors: Winton, Megan V.; Kneebone, Jeff; Zemeckis, Douglas R.; Fay, Gavin
• Editors: Jones, Kate
• Is Part Of: Methods in ecology and evolution. Volume 9:Issue 11(2018)
• Page Start: 2262
• Page End: 2272
• Publication Date: 2018-09-11
• Subjects: acoustic transmitter -- centre of activity -- detection range -- latent spatial process -- observation network -- passive acoustic telemetry -- tag‐integrated model; Ecology -- Periodicals; Evolution -- Periodicals; 577
• DOI: 10.1111/2041-210X.13080
• Languages: English
• ISSNs: 2041-210X

Abstract

Abstract: Failure to account for time‐varying detection ranges when inferring space use of marine species from passive acoustic telemetry data can bias estimates and result in erroneous biological conclusions. This potential source of bias is widely acknowledged but often ignored in practice due to a lack of available statistical methods. Here, we describe and apply a spatial point process model for estimating individual centres of activity (COAs) from acoustic telemetry data that can be modified to account for both receiver‐ and time‐specific detection probabilities. We use simulation testing to evaluate the suitability of the proposed models for estimating COAs and compare their performance to that of the popular mean‐weighted COA method for a variety of scenarios. We illustrate how the approach can be applied to correct for variable detection ranges by integrating data from moored test tags and demonstrate how accounting for time‐varying detection probabilities can impact space use estimates by fitting the model to data collected from a black sea bass ( Centropristis striata ) on a receiver array off the east coast of the United States. The proposed model reduced bias in COA estimates, particularly when tagged individuals occurred along the periphery of the receiver array. The test tag‐integrated model largely corrected the bias associated with receiver‐ and time‐specific detection probabilities. When applied to the black sea bass detection data, the model revealed fine‐scale movements not apparent when detection ranges were assumed constant. Spatial management practices for coastal marine species are often based on trends in space use inferred from passive acoustic telemetry data, which can be misinterpreted when factors influencing detection ranges are not accounted for. Our approach provides a general framework for estimating individual COAs that can be modified on a study‐specific basis to ensure resulting patterns of space use reflect a species' movements and behaviour, rather than variation in receiver detection ranges.