Identifying when tagged fishes have been consumed by piscivorous predators: application of multivariate mixture models to movement parameters of telemetered fishes

Romine, Jason G.; Perry, Russell W.; Johnston, Samuel V.; Fitzer, Christopher W; Pagliughi, Stephen W; Blake, Aaron R.

doi:10.1186/2050-3385-2-3

Cited by 37 publications

(41 citation statements)

References 24 publications

(37 reference statements)

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“…However, this approach is heavily reliant on the subjective identification of predation events based on what is perceived to be abnormal behaviour. In an effort to increase autonomy and reduce the subjectivity of the identification of predation, Romine et al (2014) were able to successfully contrast predator and prey movements using high-resolution three-dimensional telemetry data collected over a small spatial scale and a finite mixture model. Although survival estimates were not reported by the authors, this approach could greatly improve survival estimates in 3D telemetry arrays.…”

Section: Effects Of Predation On Survival Estimatesmentioning

confidence: 99%

Effects of predation on telemetry-based survival estimates: insights from a study on endangered Atlantic salmon smolts

Gibson

Halfyard

Bradford

et al. 2015

Can. J. Fish. Aquat. Sci.

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Telemetry is increasingly being used to estimate population-level survival rates. However, these estimates may be affected by the detectability of telemetry tags and are reliant on the assumption that telemetry data represent the movements of the tagged fish. Predation on tagged fish has the potential to bias survival estimates, and unlike the issue of detectability, methods to correct for the resulting bias (termed "predation bias") are not yet developed. In an acoustic telemetry study on inner Bay of Fundy Atlantic salmon (Salmo salar) smolts during 2008 and 2011, unusual tag detection patterns were indicative that some data may have been representative of the movements of predators rather than smolts. To incorporate predation effects into the resulting survival estimates, a suite of 11 summary migration metrics were compared between Atlantic salmon smolts and striped bass (Morone saxatilis). Cluster analyses revealed that 2.4% to 13.6% of tags implanted in smolts exhibited migration patterns more similar to striped bass than to other smolts, which was interpreted here as evidence of predation. Reassigning the fate of these tags as "depredated-died" reduced estimated survival from 43.5% to 41.1% in 2008 and from 32.6% to 19.0% in 2011 relative to a traditional mark-recapture model, illustrating the effect of predation bias in this case study.Résumé : L'utilisation de la télémétrie pour estimer les taux de survie à l'échelle de la population est de plus en plus répandue. Ces estimations peuvent toutefois être influencées par la détectabilité des étiquettes utilisées et reposent sur le principe que les données de télémétrie rendent compte des déplacements des poissons marqués. La prédation de ces derniers pourrait cependant biaiser les estimations des taux de survie et, contrairement au problème de détectabilité, il n'existe pas encore de méthode permettant de corriger le biais qui en résulte (appelé « biais de prédation »). Dans une étude de télémétrie acoustique portant sur des saumoneaux de saumon atlantique (Salmo salar) de la haute baie de Fundy, menée en 2008 et 2011, des motifs de détection d'étiquettes inhabituels indiquaient que certaines données pouvaient refléter les déplacements de prédateurs plutôt que ceux des saumoneaux. Afin d'intégrer les effets de la prédation dans les estimations des taux de survie en découlant, 11 paramètres sommaires associés à la migration de saumoneaux de saumon atlantique et de bars d'Amérique (Morone saxatilis) ont été comparés. Des analyses typologiques ont révélé que de 2,4 % à 13,6 % des étiquettes implantées dans des saumoneaux témoignaient d'habitudes migratoires plus semblables à celles de bars d'Amérique qu'à celles d'autres saumoneaux, ce qui a été interprété comme une preuve de prédation. La réaffectation du destin de ces étiquettes à des individus « morts-victimes de prédation » s'est traduite par une réduction des taux de survie estimés de 43,5 % à 41,1 % pour 2008, et de 32,6 % à 19,0 % pour 2011, par rapport aux résultats d'un modèle de marquage-recapture tra...

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Section: Effects Of Predation On Survival Estimatesmentioning

confidence: 99%

Effects of predation on telemetry-based survival estimates: insights from a study on endangered Atlantic salmon smolts

Gibson

Halfyard

Bradford

et al. 2015

Can. J. Fish. Aquat. Sci.

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“…Recently, Romine et al . () tracked both prey and predator inside a high‐density gridded two‐dimensional positioning system and used a multi‐variate mixture model to (i) describe the movements of predator and prey, and (ii) identify the suspected predation events where prey behaved similar to predators. A similar approach was used by Gibson et al .…”

Section: Introductionmentioning

confidence: 99%

Evaluation of an acoustic telemetry transmitter designed to identify predation events

et al. 2017

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Summary The field of acoustic telemetry has evolved rapidly and now permits the remote sensing of animal behaviour, movement, physiology and survival in environments, and species not previously possible. However, an inability to detect when a telemetered animal is consumed by a predator can complicate accurate interpretation of the telemetry data. In this paper, we describe the efforts taken to test the two generations of a novel prototype acoustic telemetry transmitter designed specifically to detect predation. Testing involved either staged predation events where tagged prey (Rainbow Trout Oncorhynchus mykiss and Yellow Perch Perca flavescens) were fed to captive Largemouth Bass Micropterus salmoides, or false‐positive testing where prey fish were tagged and held without the risk of predation. Metrics of interest were (i) the rate of correctly identifying the predation events, (ii) signal lag (i.e. the time required to detect a predation event), (iii) tag retention time in the predator's gut, and (iv) the rate of false‐positive triggering in both live and dead prey fishes. Staged predation events were successfully identified in 61/65 and 52/55 trials for generation 1 and 2 tags, respectively. Signal lag time was reduced in generation 1 tags (generally between 1 and 9 h) relative to generation 2 (3–29 h); although signal lag was highly variable. A generalized linear mixed model (GLMM) indicated strong evidence that signal lag and tag retention were both negatively correlated with water temperature, but were not affected by prey species and only slightly by individual predator traits. There was preliminary evidence that prey size may be an important determinant of both signal lag and tag retention. False‐positives in live fish were absent after 120 days for generation 1 tags (n = 31), however, the false‐positive rates were significantly higher (10/44) after only 66 days for generation 2 tags. False‐positives in dead fish showed that 20% of the generation 2 predation tags would falsely trigger 2–3 days post‐mortem. Testing of the novel predation tags was encouraging, however, further testing is recommended. Predation tags will be an important contribution to the field of acoustic telemetry, thus, permitting the improved data interpretation and less‐subjective estimates of predation rates in biotelemetry studies.

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“…Tag movement within the stomach of an aquatic predator is another potential source of bias in the alive fate classification (Romine et al. ; Gibson et al. ; Daniels et al.…”

Section: Discussionmentioning

confidence: 99%

Estimates of Red Drum Mortality via Acoustic Telemetry

Nelson

Powers

2020

Mar Coast Fish

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Subadult (age < 3) Red Drum Sciaenops ocellatus support a valuable recreational fishery, and mortality estimates for young Red Drum are needed for proper management. To obtain these estimates, age‐1 and age‐2 Red Drum were implanted with acoustic transmitters and external Floy tags in two coastal Alabama rivers (Fowl and Dog rivers). Fates of tagged fish were inferred from stationary receiver detections and active relocations over 1 year. These fates were used in a Bayesian multistate model to estimate instantaneous monthly and annual mortality and emigration rates for each river and overall from both rivers. Instantaneous monthly fishing mortality (F) ranged from 0.001 to 0.112 (annual F = 0.414) in Dog River, from 0.001 to 0.126 in Fowl River (annual F = 0.309), and was 0.001–0.054 (annual F = 0.337) overall. Instantaneous monthly natural mortality (M) ranged from 0.001 to 0.002 (annual M = 0.069) in Dog River, from 0.001 to 0.036 (annual M = 0.178) in Fowl River, and from 0.001 to 0.017 (annual M = 0.090) overall. The overall annual estimate of instantaneous total mortality (Z) was 0.435. The median escapement percentage was estimated at 36.3% (95% posterior credible interval = 19.5–56.0%) using M and Z from the overall model. Unfortunately, the error on this estimate was large and inconclusive as to whether the 30% escapement goal for juvenile Red Drum to the adult population from Dog and Fowl rivers is being met. Monthly residency estimates were typically greater than 0.90, and overall annual residency was estimated at 0.716. Fishing mortality estimates from the current study are higher than recent catch curve estimates that did not include young Red Drum. These results demonstrate that young Red Drum need to be accounted for when generating mortality estimates and provide needed data for the Red Drum recreational fishery.

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Identifying when tagged fishes have been consumed by piscivorous predators: application of multivariate mixture models to movement parameters of telemetered fishes

Cited by 37 publications

References 24 publications

Effects of predation on telemetry-based survival estimates: insights from a study on endangered Atlantic salmon smolts

Effects of predation on telemetry-based survival estimates: insights from a study on endangered Atlantic salmon smolts

Evaluation of an acoustic telemetry transmitter designed to identify predation events

Estimates of Red Drum Mortality via Acoustic Telemetry

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