Geology topics

James R. Bence

Publications and source records attributed to James R. Bence.

At least 19 recordsLinked to original sources

USGS2023

Estimates of adult Lake Trout mortality from coded wire tags in a population with developing natural reproduction in southern Lake Michigan

Objective Overfishing and Sea Lamprey Petromyzon marinus predation led to extirpation of Lake Trout Salvelinus namaycush from Lake Michigan in the 1950s. Large populations of hatchery‐reared fish were developed by the 1970s, but natural reproduction was limited until the early 2000s when it began to increase in the southern main basin. Hypothesizing that the relatively low mortality of spawning‐aged fish contributed to this reproductive success, we estimated the total annual mortality rate for this population. Methods We used catch curves to estimate the total instantaneous mortality rate Z using coded wire tags, which provided definitive ages. We made separate estimates from fish collected in three on‐going surveys: a spring gill‐net survey, a fall gill‐net spawning survey, and a sport fishery survey. Result Our estimates of Z ± SE were 0.297 ± 0.019, 0.239 ± 0.009, and 0.205 ± 0.007 for the spring, spawning, and sport fishery surveys, respectively. We suggest that the mean Z ± SE of all survey estimates of 0.247 ± 0.027 would be a reasonable estimate for this population, which equates to a total annual mortality of 22 ± 3%. This estimate is in the low range of rates reported for the species and is in the same range as other populations in the Great Lakes with well‐established natural reproduction. Conclusion We concluded that these low total mortality rates contributed to the reproductive success in southern Lake Michigan through increasing spawning stock density and age structure and that previous estimates of another important population parameter, the instantaneous natural mortality rate M , were too high. Estimates of M ranged from 0.210 to 0.240 and were based on the Pauly equation, a growth‐ and temperature‐based estimator. We suggest maximum‐age‐based estimators of M are more appropriate for Lake Trout. Several alternative maximum‐age‐based estimators produced estimates for M of 0.132–0.058, all of which are more compatible with our estimate of Z .

Lake Michigan↗

USGS2023

Longitudinal analyses of catch-at-age data for reconstructing year-class strength, with an application to lake trout (Salvelinus namaycush) in the main basin of Lake Huron

We investigated using longitudinal models to reconstruct year-class strength (YCS) from catch-at-age data, with an example application to lake trout ( Salvelinus namaycush ) in the main basin of Lake Huron. The best model structure depended on the age range used for model implementation. The YCS trajectory from the full age range (3–30 years) was similar to the trajectory from a narrow age range that approximated the age of recruitment to the fishing gears (5–7 years), but YCS estimates from the full age range included additional variations due to time-dependent selectivity and mortality. When using ages younger or older than the likely ages of recruitment, YCS estimates did not represent recruitment abundances and were also biased by trends in age-specific selectivity and mortality across years. Longitudinal YCS estimates are likely more robust than single-age recruitment indices, which are often subject to interannual changes in catchability and selectivity. Our findings provide guidance for future applications of the longitudinal YCS reconstruction that in turn may inform and supplement more comprehensive research and management programs for understanding fish recruitment dynamics.

Lake Huron↗

USGS2022

Estimating catch curve mortality based on relative return rates of coded wire tagged lake trout in US waters of Lake Huron

We estimated total mortality using catch curves based on relative return rates (RRs) of coded wire tagged lake trout ( Salvelinus namaycush ) in US waters of Lake Huron. RR was calculated as age-specific CPUE per million of fish stocked. Annual mortality for the late 1990s through early 2000s was estimated as 38% from the 1991–1995 year classes, with an effective age range of 5–10 years, and then was estimated as 24% for the post-2000 period from the 1996–2009 year classes. The two estimates from simple catch curve regressions based on average RR at age values were the same as from a mixed model with individual RR values from all stocking events. These two estimates were also comparable to the findings from statistical catch-at-age assessments with fundamentally different assumptions. Our approach is not constrained by the assumption that the expected recruitment is a constant over time and thus has the advantage to use multiple observations on each age from multiple cohorts. Our approach has broad applicability to aquatic ecosystems in which multiple mark-and-release events of fish stocking have been implemented.

Michigan↗

USGS2021

Using simulation to understand annual sea lamprey marking rates on lake trout

Sea lampreys attack fish, killing some and leaving marks on others. Great Lakes fishery managers rely on observed marking rates to assess the success of the sea lamprey control program and estimate sea lamprey-induced mortality of lake trout. Because marking rates are only observed on survivors of sea lamprey attacks, they may not provide a reliable index of actual attack or mortality rates. To investigate the effect of survivor bias, we developed a simulation model representing a single season (June–December) of sea lamprey attacks. Simulated attack rates varied with month and lake trout size; simulated pierce and lethality rates varied with month alone. Surveyed marking rates were represented by simulated survivors in October; true rates were calculated from all simulated lake trout (dead and alive) in December. Simulation results were subsetted to include only those within the range of marking rates actually observed in the Great Lakes. Type A (piercing) marking rates were a good index of the sea lamprey attack rate and the sea lamprey-induced mortality rate if annual lethality rates were relatively constant. Type B (non-piercing) marking rates were a good index of the sea lamprey attack rate and the sea lamprey-induced mortality rate if annual pierce rates were relatively constant. Due to the uncertainty surrounding the pierce and lethality rates, we recommend that sea lamprey abundance information be incorporated in existing lake trout statistical catch-at-age models via a functional response component relating sea lamprey feeding to lake trout abundance, if possible.

Journal of Great Lakes Research↗

USGS2020

Dynamics of lake trout production in the main basin of Lake Huron

To inform lake trout (Salvelinus namaycush) fishery management in Lake Huron that has undergone rapid ecosystem changes, we quantified lake trout production dynamics by coupling age-structured stock assessment and fish bioenergetics models. Our approach revealed the connection between piscivore production and prey consumption, included growth compensation to reproduction losses, and allowed comparisons between long-term dynamics of fishery harvests and fish production. We found that despite the collapse of alewives, a major non-native pelagic prey fish, lake trout production appeared to be sustainable. To a certain degree, the effect of recent recruitment declines on lake trout production was offset by release of harvest pressure from subadult lake trout, and reduction of fishing and sea lamprey induced mortality on adult lake trout. Evidence for sustainability also included the finding that no changes in average ratios of annual production to beginning-of-the-year biomass. Juvenile P:B ratio remained as high as 2.1. The effect of growth declines on adult and subadult production was offset by reduction in population mortality. Body growth and condition did not continue to decline when lake trout became more and more reliant on round goby as food, and the dynamics of total consumption of prey fish continued to be recipient controlled.

Lake Huron↗

USGS2020

Investigating apparent misalignment of predator-prey dynamics: Great Lakes lake trout and sea lampreys

Interpreting ecological dynamics is challenging when observed patterns are not aligned with presumed models. Investigating possible sources of uncertainty is critical to understand the underlying system and ultimately inform management decisions. In this study, we used simulation to investigate the hypothesis that observed inconsistencies in Great Lakes lake trout ( Salvelinus namaycush ) and sea lamprey ( Petromyzon marinus ) predator-prey dynamics were caused by measurement error in the abundance and predation metrics. When lake trout abundances increase and sea lamprey abundances decrease, predation rates are expected to decline (and vice versa). Occasionally predation rates do not change as expected, leading to an inconsistency in expected predator-prey dynamics. We used a Type II functional response model to align lake trout relative abundance, adult sea lamprey abundance, and sea lamprey marking rates of lake trout in each Great Lake. Then we added measurement error to each of the simulated metrics to see how it contributed to observed inconsistencies in the marking rates. The simulated inconsistency rate was far less than the observed inconsistency rate in Lakes Superior and Erie, indicating that measurement error was not primarily responsible for the misalignment of metrics, contrary to our hypothesis. Rather than ignoring these inconsistencies as unfortunate consequences of imperfect assessments, we recommend that future inconsistencies be scrutinized for possible mechanistic explanations. We suspect that predator-prey dynamics are being influenced by spatially structured within-lake components and the presence of alternative hosts, neither of which were accounted for in the functional response model we used.

Great Lakes↗

USGS2019

Evaluating the sustainability of a cisco fishery in Thunder Bay, Ontario, under alternative harvest policies

Sustainable management of fish stocks is promoted through the application of management strategy evaluations (MSEs), providing information to managers on the relative performance of alternative management approaches (strategies) while accounting for uncertainty. In this study, we developed a simplified MSE of a stock of Cisco Coregonus artedi in Thunder Bay, Ontario, to determine both the sustainability of the current harvest control rule (i.e., a constant exploitation rate [ U ] of 10%) and the performance of alternative harvest control rules in meeting fishery objectives. Success in meeting fishery objectives was evaluated through attained yields, interannual variation in yields, magnitude of spawning stock biomass (SB), and the risk of reaching low SB—performance metrics established based on consultation with an advisory group to Lake Superior fishery managers. Our simulations explicitly accounted for uncertainty in the frequency of strong year‐classes being produced by Cisco, the stock–recruit relationship, stock abundance, and the sex‐specific nature of roe harvest. Assuming that future productivity is similar to the productivity observed over the period from 1985 to 2015, results suggest that the current U of 10% is sustainable in terms of maintaining SB above 20% of the unfished level. Variants of constant U control rules that included thresholds defining when U is to decrease as a function of SB increased yield, decreased risk, and increased the magnitude of SB at the end of the simulation period. However, these advantages came at the expense of greater interannual variation in yield. Constant catch control rules greatly underperformed constant U control rules in terms of magnitude in yield; however, they did reduce interannual variation in yield compared to constant U control rules. Furthermore, conditional versions of constant catch control rules (i.e., threshold stock sizes below which the catch limit was reduced) mitigated risks of staying at low stock size.

Thunder Bay↗

USGS2019

Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data

Determining the degree to which predation affects prey abundance in natural communities constitutes a key goal of ecological research. Predators can affect prey through both consumptive effects (CEs) and nonconsumptive effects (NCEs), although the contributions of each mechanism to the density of prey populations remain largely hypothetical in most systems. Common statistical methods applied to time series data cannot elucidate the mechanisms responsible for hypothesized predator effects on prey density (e.g., differentiate CEs from NCEs), nor provide parameters for predictive models. State space models (SSMs) applied to time series data offer a way to meet these goals. Here, we employ SSMs to assess effects of an invasive predatory zooplankter, Bythotrephes longimanus, on an important prey species, Daphnia mendotae, in Lake Michigan. We fit mechanistic models in a SSM framework to seasonal time series (1994-2012) using a recently developed, maximum likelihood-based optimization method, iterated filtering, which can overcome challenges in ecological data (e.g. nonlinearities, measurement error, and irregular sampling intervals). Our results indicate that B. longimanus strongly influences D. mendotae dynamics, with mean annual peak densities of B. longimanus observed in Lake Michigan estimated to cause a 61% reduction in D. mendotae population growth rate and a 59% reduction in peak biomass density. Further, the observed B. longimanus effect is most consistent with an NCE via reduced birth rates. The SSM approach also provided estimates for key biological parameters (e.g., demographic rates) and the contribution of dynamic stochasticity and measurement error. Our study therefore provides evidence derived directly from survey data that the invasive zooplankter B. longimanus is affecting zooplankton demographics and offer parameter estimates needed to inform predictive models that explore the effect of B. longimanus under different scenarios such as climate change.

Ecology↗

USGS2019

A comparison of age- and size-structured assessment models applied to a stock of cisco in Thunder Bay, Ontario

Stock assessments are critical to modern fisheries management, supporting the calculation of key reference variables used to make informed management decisions. However, there is still considerable uncertainty as to which class of assessment models is appropriate to use under different circumstances. A common class of models used when age data are available are statistical catch-at-age assessment (SCAA) models, which track annual cohorts through time. When age data are unavailable, as is often the case in invertebrate fisheries where the lack of a bony structure such as otoliths makes aging difficult, statistical catch-at-size assessment (SCSA) models are more often employed, tracking fish or invertebrates through time by size-classes rather than ages. Do SCAA models actually perform better than SCSA models when age data are available, or is this just an assumption we make in fisheries research and management? We examined this question by evaluating the effectiveness of both SCAA and SCSA models in characterizing cisco, Coregonus artedi , population dynamics in Thunder Bay, Ontario. Both models were fit using an integrated framework with multiple sources of data including hydroacoustic estimates of spawning stock, fishery-dependent and -independent age/length compositions, and harvest data. Our results suggest that for cisco in Thunder Bay, data-limitations related to lack of size-composition data over the size range for which cisco growth is rapid resulted in difficulty estimating relative year-class strength within a SCSA. This led to parameter confounding and ultimately the inability to estimate natural mortality within a SCSA. This hampered the utility of a SCSA model in comparison with a SCAA model when age-composition data were available.

Ontario↗

USGS2018

Hatchery strain contributions to emerging wild lake trout populations in Lake Huron

Recent assessments indicate the emergence of naturally produced lake trout ( Salvelinus namaycush ) recruitment throughout Lake Huron in the North American Laurentian Great Lakes (>50% of fish <7 years). Because naturally produced fish derived from different stocked hatchery strains are unmarked, managers cannot distinguish strains contributing to natural recruitment. We used 15 microsatellite loci to identify strains of naturally produced lake trout ( N = 1567) collected in assessment fisheries during early (2002–2004) and late (2009–2012) sampling periods. Individuals from 13 American and Canadian hatchery strains ( N = 1143) were genotyped to develop standardized baseline information. Strain contributions were estimated using a Bayesian inferential approach. Deviance information criteria were used to compare models evaluating strain contributions at different spatial and temporal scales. The best performing models were the most complex models, suggesting that hatchery strain contributions to naturally produced lake trout varied spatially among management districts and temporally between time periods. Contributions of Seneca strain lake trout were consistently high across most management districts, with contributions increasing from early to late time periods (estimates ranged from 52% to 94% for the late period across 8 of 9 districts). Strain contributions deviated from expectations based on historical stocking levels, indicating strains differed with respect to survival, reproductive success, and/or dispersal. Knowledge of recruitment levels of strains stocked in different management districts, and how strain-specific recruitment varies temporally, spatially, and as a function of local or regional stocking is important to prioritize strains for future stocking and management of the transition process from primarily hatchery to naturally produced stocks.

Journal of Heredity↗

USGS2017

Changes in movements of Chinook Salmon between lakes Huron and Michigan after Alewife population collapse

Alewives Alosa pseudoharengus are the preferred food of Chinook Salmon Oncorhynchus tshawytscha in the Laurentian Great Lakes. Alewife populations collapsed in Lake Huron in 2003 but remained comparatively abundant in Lake Michigan. We analyzed capture locations of coded-wire-tagged Chinook Salmon before, during, and after Alewife collapse (1993–2014). We contrasted the pattern of tag recoveries for Chinook Salmon released at the Swan River in northern Lake Huron and Medusa Creek in northern Lake Michigan. We examined patterns during April–July, when Chinook Salmon were primarily occupied by feeding, and August–October, when the salmon were primarily occupied by spawning. We found evidence that Swan River fish shifted their feeding location from Lake Huron to Lake Michigan after the collapse. Over years, proportions of Swan River Chinook Salmon captured in Lake Michigan increased in correspondence with the Alewife decline in Lake Huron. Mean proportions of Swan River fish captured in Lake Michigan were 0.13 (SD = 0.14) before collapse (1993–1997) and 0.82 (SD = 0.22) after collapse (2008–2014) and were significantly different. In contrast, proportions of Medusa Creek fish captured in Lake Michigan did not change; means were 0.98 (SD = 0.05) before collapse and 0.99 (SD = 0.01) after collapse. The mean distance to the center of the coastal distribution of Swan River fish during April–July shifted 357 km (SD = 169) from central Lake Huron before collapse to central Lake Michigan after collapse. The coastal distributions during August–October were centered on the respective sites of origin, suggesting that Chinook Salmon returned to release sites to spawn regardless of their feeding locations. Regarding the impact on Alewife populations, this shift in interlake movement would be equivalent to increasing the Chinook Salmon stocking rate within Lake Michigan by 30%. The primary management implication is that interlake coordination of Chinook Salmon stocking policies would be expected to benefit the recreational fishery.

Lake Huron, Lake Michigan↗

USGS2017

Using variance structure to quantify responses to perturbation in fish catches

We present a case study evaluation of gill-net catches of Walleye Sander vitreus to assess potential effects of large-scale changes in Oneida Lake, New York, including the disruption of trophic interactions by double-crested cormorants Phalacrocorax auritus and invasive dreissenid mussels. We used the empirical long-term gill-net time series and a negative binomial linear mixed model to partition the variability in catches into spatial and coherent temporal variance components, hypothesizing that variance partitioning can help quantify spatiotemporal variability and determine whether variance structure differs before and after large-scale perturbations. We found that the mean catch and the total variability of catches decreased following perturbation but that not all sampling locations responded in a consistent manner. There was also evidence of some spatial homogenization concurrent with a restructuring of the relative productivity of individual sites. Specifically, offshore sites generally became more productive following the estimated break point in the gill-net time series. These results provide support for the idea that variance structure is responsive to large-scale perturbations; therefore, variance components have potential utility as statistical indicators of response to a changing environment more broadly. The modeling approach described herein is flexible and would be transferable to other systems and metrics. For example, variance partitioning could be used to examine responses to alternative management regimes, to compare variability across physiographic regions, and to describe differences among climate zones. Understanding how individual variance components respond to perturbation may yield finer-scale insights into ecological shifts than focusing on patterns in the mean responses or total variability alone.

Transactions of the American Fisheries Society↗

USGS2016

Reply to comments by Riley and Dunlop on He et al. (2015)

He et al. (2015) described piscivory patterns in the main basin of Lake Huron 1984-2010, during which there was also a pattern of stepwise declines in the abundance of dominant prey fish species. The approach of He et al. (2015) was to couple age-structured stock assessment and fish bioenergetics models to estimate prey fish consumption, and to compare these patterns with prey fish biomass from a bottom trawl survey. Riley and Dunlop (2015) were highly critical of the methods and conclusions reached by He et al. (2015). They claimed that we incorrectly interpreted the bottom trawl survey data, and did not account for uncertainty. We respond to these and other criticisms below, which we find do not undermine our findings.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2015

Coupling age-structured stock assessment and fish bioenergetics models: a system of time-varying models for quantifying piscivory patterns during the rapid trophic shift in the main basin of Lake Huron

We quantified piscivory patterns in the main basin of Lake Huron during 1984–2010 and found that the biomass transfer from prey fish to piscivores remained consistently high despite the rapid major trophic shift in the food webs. We coupled age-structured stock assessment models and fish bioenergetics models for lake trout ( Salvelinus namaycush ), Chinook salmon ( Oncorhynchus tshawytscha ), walleye ( Sander vitreus ), and lake whitefish ( Coregonus clupeaformis ). The model system also included time-varying parameters or variables of growth, length–mass relations, maturity schedules, energy density, and diets. These time-varying models reflected the dynamic connections that a fish cohort responded to year-to-year ecosystem changes at different ages and body sizes. We found that the ratio of annual predation by lake trout, Chinook salmon, and walleye combined with the biomass indices of age-1 and older alewives ( Alosa pseudoharengus ) and rainbow smelt ( Osmerus mordax ) increased more than tenfold during 1987–2010, and such increases in predation pressure were structured by relatively stable biomass of the three piscivores and stepwise declines in the biomass of alewives and rainbow smelt. The piscivore stability was supported by the use of alternative energy pathways and changes in relative composition of the three piscivores. In addition, lake whitefish became a new piscivore by feeding on round goby ( Neogobius melanostomus ). Their total fish consumption rivaled that of the other piscivores combined, although fish were still a modest proportion of their diet. Overall, the use of alternative energy pathways by piscivores allowed the increases in predation pressure on dominant diet species.

Lake Huron↗

USGS2015

Using time-varying asymptotic length and body condition of top piscivores to indicate ecosystem regime shift in the main basin of Lake Huron: a Bayesian hierarchical modeling approach

We evaluated the ecosystem regime shift in the main basin of Lake Huron that was indicated by the 2003 collapse of alewives, and dramatic declines in Chinook salmon abundance thereafter. We found that the period of 1995-2002 should be considered as the early phase of the final regime shift. We developed two Bayesian hierarchical models to describe time-varying growth based on the von Bertalanffy growth function and the length-mass relationship. We used asymptotic length as an index of growth potential, and predicted body mass at a given length as an index of body condition. Modeling fits to length and body mass at age of lake trout, Chinook salmon, and walleye were excellent. Based on posterior distributions, we evaluated the shifts in among-year geometric means of the growth potential and body condition. For a given top piscivore, one of the two indices responded to the regime shift much earlier than the 2003 collapse of alewives, the other corresponded to the 2003 changes, and which index provided the early signal differed among the three top piscivores.

Lake Huron↗

USGS2014

A multispecies statistical age-structured model to assess predator-prey balance: application to an intensively managed Lake Michigan pelagic fish community

Using a Bayesian model fitting approach, we developed a multispecies statistical catch-at-age model to assess trade-offs between predatory demands and prey productivities, focusing on the Lake Michigan pelagic fish community. We assessed these trade-offs in terms of predation mortalities and productivities of alewife (Alosa pseudoharengus) and rainbow smelt (Osmerus mordax) and functional responses of salmonines. Our predation mortality estimates suggest that salmonine consumption has been a major driver of historical fluctuations in prey abundance, with sharp declines in alewife abundance in the 1980s and 2000s coinciding with estimated increases in predation mortalities. While Chinook salmon (Oncorhynchus tshawytscha) were food limited during periods of low alewife abundance, other salmonines appeared to maintain a (near) maximum per-predator consumption across all observed prey densities, suggesting that feedback mechanisms are unlikely to help maintain a balance between predator consumption and prey productivity in Lake Michigan. This study demonstrates that a multispecies modeling approach that combines stock assessment methods with explicit consideration of predator–prey interactions could provide the basis for tactical decision-making from a broader ecosystem perspective.

Lake Michigan↗

USGS2013

Detecting temporal change in freshwater fisheries surveys: statistical power and the important linkages between management questions and monitoring objectives

Monitoring to detect temporal trends in biological and habitat indices is a critical component of fisheries management. Thus, it is important that management objectives are linked to monitoring objectives. This linkage requires a definition of what constitutes a management-relevant “temporal trend.” It is also important to develop expectations for the amount of time required to detect a trend (i.e., statistical power) and for choosing an appropriate statistical model for analysis. We provide an overview of temporal trends commonly encountered in fisheries management, review published studies that evaluated statistical power of long-term trend detection, and illustrate dynamic linear models in a Bayesian context, as an additional analytical approach focused on shorter term change. We show that monitoring programs generally have low statistical power for detecting linear temporal trends and argue that often management should be focused on different definitions of trends, some of which can be better addressed by alternative analytical approaches.

Fisheries↗

USGS2012

Estimating spatial and temporal components of variation in count data using negative binomial mixed models

P artitioning total variability into its component temporal and spatial sources is a powerful way to better understand time series and elucidate trends. The data available for such analyses of fish and other populations are usually nonnegative integer counts of the number of organisms, often dominated by many low values with few observations of relatively high abundance. These characteristics are not well approximated by the Gaussian distribution. We present a detailed description of a negative binomial mixed-model framework that can be used to model count data and quantify temporal and spatial variability. We applied these models to data from four fishery-independent surveys of Walleyes Sander vitreus across the Great Lakes basin. Specifically, we fitted models to gill-net catches from Wisconsin waters of Lake Superior; Oneida Lake, New York; Saginaw Bay in Lake Huron, Michigan; and Ohio waters of Lake Erie. These long-term monitoring surveys varied in overall sampling intensity, the total catch of Walleyes, and the proportion of zero catches. Parameter estimation included the negative binomial scaling parameter, and we quantified the random effects as the variations among gill-net sampling sites, the variations among sampled years, and site × year interactions. This framework (i.e., the application of a mixed model appropriate for count data in a variance-partitioning context) represents a flexible approach that has implications for monitoring programs (e.g., trend detection) and for examining the potential of individual variance components to serve as response metrics to large-scale anthropogenic perturbations or ecological changes.

Iowa, Maine, Michigan, Ohio, Wisconsin↗