DOI: 10.5061/dryad.ffbg79d5z
title: Dispersal and survival of sea lamprey in Lake Erie and connected waterways

description: 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.
description: # Dispersal and survival of sea lamprey in Lake Erie and connected
 waterways Dataset DOI: [10.5061/dryad.ffbg79d5z](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* * N: number of tagged sea lamprey in the dataset
 * NState: number of states in the multistate model * NObsState: Number of
 states in which detection is an estimated rate (not fixed at zero) *
 ObsStateIDs: Indices for states with an estimated detection rate * NTrans:
 Number of transition rates between states * from: The 'from'
 column of a from-to matrix describing all allowable transitions between
 states * to: The 'to' column of a from-to matrix describing all
 allowable transitions between states * trib_id: Indices relating the state
 in the 'to' column to a geographic habitat patch (including both
 lake and stream locations) * 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) * type_ID_by_dist: index with the same categories as
 'type_ID' but starting from 1 for each distribution type.
 (either exponential or Weibull).  * dist_type_ID: index relating
 transition rates to distribution type (1=exponential, 2=Weibull) * P:
 number of change points for piecewise constant Weibull distribution *
 exactObsState: dummy code indicating detection events that are observed at
 the exact state transition time * first_det: dummy code indicating the
 first detection event of each tagged sea lamprey *  seasonID: index
 indicating the seasonID (month) in which each detection event occurred *
 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.
 * config_id: index relating each detection to a row of the mu_config
 matrix * mu_low_ind: dummy code indicating if a detection occurred during
 a low or high ping rate period. * last_det: dummy code indicating the last
 detection event for each tagged sea lamprey * 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). * 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. * Nids: index
 relating events to individuals * time: time that each event occurred *
 c_p: mid-point of each time period (length P). Used for Weibull
 distributed rates. * D: number of events in the dataset * state: index
 indicating the ending state for each event * n_exp: number of
 exponentially distributed transition types  * n_weibull: number of Weibull
 distributed transition types * not_detected: dummy variable indicating sea
 lamprey that were not detected after release * lake_to_lake_id: transition
 rates that at lake-to-lake transitions (-99 equals not applicable) *
 allTribEntrances: state IDs for tributary entrances * upstream_trib_id:
 transition rates that are upstream trib-to-trib movements * 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](https://glatos.glos.us/portal)