Erratum: Validation of Abundance Estimates from Mark-Recapture and Removal Techniques for Rainbow Trout Captured by Electrofishing in Small Streams

It has been suggested that platypuses (Ornithorhynchus anatinus) may avoid nets following capture, compromising abundance estimates using mark–recapture models. Here, we present the first direct evidence of net avoidance behaviour by the platypus. Using acoustic telemetry, we record a platypus bypassing several nets following capture. Understanding variation in capture probabilities will lead to better estimation of platypus abundance, which is currently lacking.

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Evaluation of Long-Term Mark-Recapture Data for Estimating Abundance of Juvenile Fall-Run Chinook Salmon on the Stanislaus River from 1996 to 2017

San Francisco Estuary and Watershed Science ◽

10.15447/sfews.2019v17iss1art4 ◽

2019 ◽

Vol 17 (1) ◽

Cited By ~ 1

Author(s):

Tyler Pilger ◽

Matthew Peterson ◽

Dana Lee ◽

Andrea Fuller ◽

Doug Demko

Keyword(s):

Chinook Salmon ◽

Oncorhynchus Tshawytscha ◽

Estimation Method ◽

Central Valley ◽

Mark Recapture ◽

Important Species ◽

Trap Efficiency ◽

Monitoring Programs ◽

Abundance Estimates

Conservation and management of culturally and economically important species rely on monitoring programs to provide accurate and robust estimates of population size. Rotary screw traps (RSTs) are often used to monitor populations of anadromous fish, including fall-run Chinook Salmon (Oncorhynchus tshawytscha) in California’s Central Valley. Abundance estimates from RST data depend on estimating a trap's efficiency via mark-recapture releases. Because efficiency estimates are highly variable and influenced by many factors, abundance estimates can be highly uncertain. An additional complication is the multiple accepted methods for how to apply a limited number of trap efficiency estimates, each from discrete time-periods, to a population’s downstream migration, which can span months. Yet, few studies have evaluated these different methods, particularly with long-term monitoring programs. We used 21 years of mark-recapture data and RST catch of juvenile fall-run Chinook Salmon on the Stanislaus River, California, to investigate factors associated with trap efficiency variability across years and mark-recapture releases. We compared annual abundance estimates across five methods that differed in treatment of trap efficiency (stratified versus modeled) and statistical approach (frequentist versus Bayesian) to assess the variability of estimates across methods, and to evaluate whether method affected trends in estimated abundance. Consistent with short-term studies, we observed negative associations between estimated trap efficiency and river discharge as well as fish size. Abundance estimates were robust across all methods, frequently having overlapping confidence intervals. Abundance trends, for the number of increases and decreases from year to year, did not differ across methods. Estimated juvenile abundances were significantly related to adult escapement counts, and the relationship did not depend on estimation method. Understanding the sources of uncertainty related to abundance estimates is necessary to ensure that high-quality estimates are used in life cycle and stock-recruitment modeling.

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A novel approach for estimating densities of secretive species from road-survey and spatial-movement data

Wildlife Research ◽

10.1071/wr16175 ◽

2018 ◽

Vol 45 (5) ◽

pp. 446 ◽

Cited By ~ 3

Author(s):

John D. Willson ◽

Shannon E. Pittman ◽

Jeffrey C. Beane ◽

Tracey D. Tuberville

Keyword(s):

North Carolina ◽

Radio Telemetry ◽

Model Parameters ◽

Vehicle Speed ◽

Mark Recapture ◽

Snake Species ◽

The North ◽

Abundance Estimates ◽

Spatial Movement ◽

Road Survey

Context Accurate estimates of population density are a critical component of effective wildlife conservation and management. However, many snake species are so secretive that their density cannot be determined using traditional methods such as capture–mark–recapture. Thus, the status of most terrestrial snake populations remains completely unknown. Aim We developed a novel simulation-based technique for estimating density of secretive snakes that combined behavioural observations of snake road-crossing behaviour (crossing speed), effort-corrected road-survey data, and simulations of spatial movement patterns derived from radio-telemetry, without relying on mark–recapture. Methods We used radio-telemetry data to parameterise individual-based movement models that estimate the frequency with which individual snakes cross roads and used information on survey vehicle speed and snake crossing speed to determine the probability of detecting a snake, given that it crosses the road transect during a survey. Snake encounter frequencies during systematic road surveys were then interpreted in light of detection probabilities and simulation model results to estimate snake densities and to assess various factors likely to affect abundance estimates. We demonstrated the broad applicability of this approach through a case study of the imperiled southern hognose snake (Heterodon simus) in the North Carolina (USA) Sandhills. Key results We estimated that H. simus occurs at average densities of 0.17 ha–1 in the North Carolina Sandhills and explored the sensitivity of this estimate to assumptions and variation in model parameters. Conclusions Our novel method allowed us to generate the first abundance estimates for H. simus. We found that H. simus exists at low densities relative to congeners and other mid-sized snake species, raising concern that this species may not only have declined in geographic range, but may also occur at low densities or be declining in their strongholds, such as the North Carolina Sandhills. Implications We present a framework for estimating density of species that have traditionally been considered too secretive to study at the population level. This method will greatly enhance our ability to study and manage a wide variety of snake species and could be applied to other secretive wildlife species that are most frequently encountered during road surveys.

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Effects of flow fluctuations on habitat use and survival of age-0 rainbow trout (Oncorhynchus mykiss) in a large, regulated river1This article is a companion to Korman et al. 2011, published this issue.

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f2011-045 ◽

2011 ◽

Vol 68 (6) ◽

pp. 1097-1109 ◽

Cited By ~ 10

Author(s):

Josh Korman ◽

Carl Walters ◽

S.J.D. Martell ◽

W.E. Pine ◽

Andrew Dutterer

Keyword(s):

Rainbow Trout ◽

Oncorhynchus Mykiss ◽

Early Life History ◽

Regulated Rivers ◽

Minimum Flow ◽

Glen Canyon Dam ◽

Rainbow Trout Oncorhynchus Mykiss ◽

Flow Fluctuations ◽

Abundance Estimates ◽

Hourly Variation

We evaluated effects of reduced hourly variation in flow from Glen Canyon Dam on survival of age-0 rainbow trout ( Oncorhynchus mykiss ) in the Colorado River, Arizona, USA, based on monthly abundance estimates. The proportion of the age-0 population in low-angle shorelines, which are potentially more sensitive to flow variability, declined from 70% in June to 20% in November as fish grew and made an ontogenetic habitat shift to deeper habitat. Average daily instantaneous mortality between August and September was 0.008 units lower in years when there was no change in the minimum flow compared with years when there was a sudden 50% reduction in the minimum flow. However, mortality was 0.006 units higher during the fall when there was no hourly variation in flow compared with years when flows fluctuated. As a result of these opposing patterns, 3-month age-0 survival across steady (0.31) and unsteady (0.28) flow regimes were very similar. While additional replication is required to strengthen inferences about effects of steadier flows, we demonstrate the utility of early life history monitoring for evaluating effects of flow management on fish populations in regulated rivers.

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Integrating Acoustic Telemetry into a Mark–Recapture Model to Improve Catchability Parameters and Abundance Estimates of Lake Sturgeon in Eastern Lake Erie

North American Journal of Fisheries Management ◽

10.1002/nafm.10321 ◽

2019 ◽

Vol 39 (5) ◽

pp. 913-920

Author(s):

Jonah L. Withers ◽

Donald Einhouse ◽

Michael Clancy ◽

Lori Davis ◽

Rachel Neuenhoff ◽

...

Keyword(s):

Acoustic Telemetry ◽

Lake Erie ◽

Lake Sturgeon ◽

Mark Recapture ◽

Abundance Estimates

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Integrating acoustic telemetry into mark–recapture models to improve the precision of apparent survival and abundance estimates

Oecologia ◽

10.1007/s00442-015-3280-z ◽

2015 ◽

Vol 178 (3) ◽

pp. 761-772 ◽

Cited By ~ 29

Author(s):

Christine L. Dudgeon ◽

Kenneth H. Pollock ◽

J. Matias Braccini ◽

Jayson M. Semmens ◽

Adam Barnett

Keyword(s):

Acoustic Telemetry ◽

Apparent Survival ◽

Mark Recapture ◽

Abundance Estimates

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Evaluating mark - recapture sampling designs for fish in an open riverine system

Marine and Freshwater Research ◽

10.1071/mf10217 ◽

2011 ◽

Vol 62 (7) ◽

pp. 835 ◽

Cited By ~ 10

Author(s):

Daniel C. Gwinn ◽

Paul Brown ◽

Jakob C. Tetzlaff ◽

Mike S. Allen

Keyword(s):

Open Systems ◽

Monitoring Program ◽

Sampling Area ◽

Mark Recapture ◽

Closed Population ◽

Management Objectives ◽

Monitoring Programs ◽

Abundance Estimates ◽

Simulation Results ◽

Murray Cod

Sampling designs for effective monitoring programs are often specific to individual systems and management needs. Failure to carefully evaluate sampling designs of monitoring programs can lead to data that are ineffective for informing management objectives. We demonstrated the use of an individual-based model to evaluate closed-population mark–recapture sampling designs for monitoring fish abundance in open systems, using Murray cod (Maccullochella peelii (Mitchell, 1838)) in the Murray–Darling River basin, Australia, as an example. The model used home-range, capture-probability and abundance estimates to evaluate the influence of the size of the sampling area and the number of sampling events on bias and precision of mark–recapture abundance estimates. Simulation results indicated a trade-off between the number of sampling events and the size of the sampling reach such that investigators could employ large sampling areas with relatively few sampling events, or smaller sampling areas with more sampling events to produce acceptably accurate and precise abundance estimates. The current paper presents a framework for evaluating parameter bias resulting from migration when applying closed-population mark–recapture models to open populations and demonstrates the use of simulation approaches for informing efficient and effective monitoring-program design.

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Predicting fish abundance using single-pass removal sampling

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f00-025 ◽

2000 ◽

Vol 57 (5) ◽

pp. 951-961 ◽

Cited By ~ 29

Author(s):

Matthew G Mitro ◽

Alexander V Zale

Keyword(s):

Rainbow Trout ◽

Prediction Interval ◽

Prediction Intervals ◽

Total Abundance ◽

Simulated Population ◽

River Section ◽

Single Pass ◽

Rainbow Trout Oncorhynchus Mykiss ◽

Abundance Estimates ◽

Removal Sampling

Three-pass removal data for juvenile rainbow trout (Oncorhynchus mykiss) along bank areas of the Henrys Fork of the Snake River, Idaho, were used to construct a mean capture probability (MCP) model to predict abundance from single-pass catch data. We evaluated the MCP model by simulation. The precision of the MCP model was poor when predicting abundance within a specific bank unit. MCP model prediction intervals were about 7.5 times greater than three-pass removal intervals. However, the MCP model performed about the same as three-pass removal for predicting total abundance in a river section from multiple bank samples. We evaluated how the MCP model can be used to improve precision of total abundance estimates. Reallocating effort to sample 150 bank units by single-pass removal rather than 50 bank units by three-pass removal resulted in a 48% increase in prediction interval precision for a simulated population of 10 000 fish. Precision also increased when allocating effort to sampling more bank units of smaller length versus fewer bank units of longer length. Sampling 1500 m of bank as one hundred 15-m bank units increased precision by about 28% versus sampling fifty 30-m bank units and by about 50% versus sampling twenty-five 60-m bank units.

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