Dispersal and survival of sea lamprey in Lake Erie and connected waterways
Data files
Aug 28, 2025 version files 516.84 KB
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goodness_of_fit_simulations.R
47.72 KB
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hessian_all_data_TribUnobservedState_12222024.rds
217.08 KB
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opt_all_data_TribUnobservedState_12222024.rds
1.87 KB
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README.md
7.09 KB
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rtmb_unobserved_trib_state_all_data_f.rds
212.62 KB
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run_RTMB_model_v_constant_mort.r
9.55 KB
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sd_all_data_TribUnobservedState_12222024.rds
2.97 KB
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simulate_dataset.R
17.95 KB
Abstract
Invasive sea lamprey inhabiting the North American Laurentian Great Lakes are the target of the world’s longest running vertebrate invasive species control program. However, metapopulation dynamics comprising survival and dispersal during the sea lampreys’ lake-resident life stages are poorly understood. We applied acoustic telemetry and continuous-time multistate capture-recapture modeling to address this knowledge gap in Lake Erie. We acoustic-tagged sea lamprey (n = 619) and deployed acoustic receivers into all known connected waterways containing larval sea lamprey rearing habitat (n = 23), including the Detroit River (connecting Lake Erie to Lake Huron) and distributaries to Lake Ontario. Distribution of tagged sea lamprey to putative spawning waterways was shaped by heterogeneous stream attractiveness and distance-limited dispersal. Using parameter estimates from our capture-recapture model and simulation, we predicted survival and dispersal outcomes for a hypothetical sea lamprey population evenly distributed throughout Lake Erie at the beginning of January (34% pre-spawn mortality, 45% dispersal into Lake Erie tributaries, 19% dispersal into the Detroit River, and 2% dispersal into Lake Ontario). The methodology we applied may be widely useful for investigating dispersal and survival of aquatic organisms.
Dataset DOI: 10.5061/dryad.ffbg79d5z
Description of the data and file structure
Sea lamprey were tagged during the juvenile and adult life stage from 2016-2018. Juveniles were obtained from commercial fishers in northern Lake Huron during October-January (n = 124). Adults were obtained from assessment traps located in northern Lake Huron during April–May (n = 497). Fish were tagged at Hammond Bay Biological Station (USGS field station on the shore or northern Lake Huron) and transported to Lake Erie for release. Tagged lampreys were released from shore and were roughly evenly distributed among seven locations in Lake Erie. All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.
Autonomous acoustic telemetry receivers (model VR2W-180; Innovasea) were placed in each of 22 tributaries and 2 distributaries (Niagara River and Welland Canal) to Lake Erie. In most Lake Erie tributaries (21 of 22) at least two receivers were spaced at least 500 m apart to form two distinct gates near the mouth of the tributary. In some streams, a third receiver array was placed farther upstream. The study design called for receivers to be deployed prior to the winter release of tagged fish and remain in place through the end of July. However, some connected waterways were added to the study design during year two or three of the research and, in some cases, deployed receivers were not recovered (Figure 2). Detections on compatible receivers deployed for other research projects, namely in the Detroit River and Credit River, were obtained from the Great Lakes Acoustic Telemetry Observation System.
Files and variables
File: run_RTMB_model_v_constant_mort.r
Description: Code for running the continuous-time multi-state capture recapture model using the RTMB R package
File: goodness_of_fit_simulations.R
Description: Code for running the goodness of fit simulations, which uses the hessian from the optimized model and calls the 'simulate_dataset' function.
File: simulate_dataset.R
Description: a custom function for simulating datasets that match the empirical study design.
File: sd_all_data_TribUnobservedState_12222024.rds
Description: Parameter estimates and standard errors for all model parameters
File: opt_all_data_TribUnobservedState_12222024.rds
Description: Optimized model output (mean parameter estimates and negative log likelihood).
File: hessian_all_data_TribUnobservedState_12222024.rds
Description: Hessian for the optimized model. This is used to simulate parameter values from a multivariate-normal distribution, using the empirical covariance structure from the optimization.
File: rtmb_unobserved_trib_state_all_data_f.rds
Description: Data input for running the model. This includes the telemetry data as well as indices to construct the multi-state capture-recapture framework described in the manuscript.
Attributes
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N: number of tagged sea lamprey in the dataset
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NState: number of states in the multistate model
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NObsState: Number of states in which detection is an estimated rate (not fixed at zero)
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ObsStateIDs: Indices for states with an estimated detection rate
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NTrans: Number of transition rates between states
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from: The 'from' column of a from-to matrix describing all allowable transitions between states
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to: The 'to' column of a from-to matrix describing all allowable transitions between states
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trib_id: Indices relating the state in the 'to' column to a geographic habitat patch (including both lake and stream locations)
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type_ID: index relating transitions to a specific type of transition rate (lake-to-lake, lake-to-mortality, tributary-to-tributary (upstream), tributary downstream, tributary to spawn)
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type_ID_by_dist: index with the same categories as 'type_ID' but starting from 1 for each distribution type. (either exponential or Weibull).
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dist_type_ID: index relating transition rates to distribution type (1=exponential, 2=Weibull)
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P: number of change points for piecewise constant Weibull distribution
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exactObsState: dummy code indicating detection events that are observed at the exact state transition time
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first_det: dummy code indicating the first detection event of each tagged sea lamprey
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seasonID: index indicating the seasonID (month) in which each detection event occurred
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mu_config: a matrix with rows equal to the number of acoustic receiver array configuration changes and columns equal to the number of states in the model (NState). Each cell of the matrix has a 0 for when the state is unmonitored and a 1 for when at least one acoustic receiver was deployed.
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config_id: index relating each detection to a row of the mu_config matrix
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mu_low_ind: dummy code indicating if a detection occurred during a low or high ping rate period.
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last_det: dummy code indicating the last detection event for each tagged sea lamprey
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detection: dummy code for all events indicating if a detection occurred (1) or not (0). Events without detections were inserted into the data to account for changes in piecewise movement rate (month break points) and changes in the acoustic receiver array configuration (rows of mu_config).
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start_interval: dummy code indicating that an event is the start of a detection interval. An interval includes all events that fall between a detection.
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Nids: index relating events to individuals
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time: time that each event occurred
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c_p: mid-point of each time period (length P). Used for Weibull distributed rates.
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D: number of events in the dataset
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state: index indicating the ending state for each event
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n_exp: number of exponentially distributed transition types
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n_weibull: number of Weibull distributed transition types
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not_detected: dummy variable indicating sea lamprey that were not detected after release
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lake_to_lake_id: transition rates that at lake-to-lake transitions (-99 equals not applicable)
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allTribEntrances: state IDs for tributary entrances
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upstream_trib_id: transition rates that are upstream trib-to-trib movements
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trib_state_id: index linking transition rates to tributary ID (-99 equals not applicable)
Code/software
All data analysis and processing was conducted using the following version of R:
R version 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
Required R packages to implement the workflow:
- for statistical analysis (RTMB)
- for plotting and summarizing data (ggplot2, plyr, scico, gridExtra, ggtext, ggrepel)
Access information
Other publicly accessible locations of the data:
- unformatted telemetry data used for this research is publicly available through the Great Lakes Acoustic Telemetry Data Portal https://glatos.glos.us/portal
