Recruitment Relationship Research Articles

Examining nonstationarity in the recruitment dynamics of fishes using Bayesian change point analysis

Marine ecosystems can undergo regime shifts, which result in nonstationarity in the dynamics of the fish populations inhabiting them. The assumption of time-invariant parameters in stock–recruitment models can lead to severe errors when forecasting renewal ability of stocks that experience shifts in their recruitment dynamics. We present a novel method for fitting stock–recruitment models using the Bayesian online change point detection algorithm, which is able to cope with sudden changes in the model parameters. We validate our method using simulations and apply it to empirical data of four demersal fishes in the southern Gulf of St. Lawrence. We show that all of the stocks have experienced shifts in their recruitment dynamics that cannot be captured by a model that assumes time-invariant parameters. The detected shifts in the recruitment dynamics result in clearly different parameter distributions and recruitment predictions between the regimes. This study illustrates how stock–recruitment relationships can experience shifts, which, if not accounted for, can lead to false predictions about a stock’s recovery ability and resilience to fishing.

A limit reference point to prevent recruitment overfishing of Pacific bluefin tuna

Pacific bluefin tuna (PBF) (Thunnus orientalis) is commercially important in the North Pacific Ocean. Although its stock has been relatively low for decades, international discussions on a long-term management framework, including the definition of a limit reference point (LRP), have only recently started. This paper argues that an LRP for PBF could be developed by determining a biomass level that would prevent recruitment overfishing. First, it reviews the development of LRPs for various tuna species and demonstrates that most of these limits are not necessarily based on biological information on the respective species. Then, the current management of PBF is also reviewed as background information for considering an LRP for PBF. Finally, a variety of simple analyses of the stock–recruitment relationship of PBF are conducted to find a biomass level that would prevent recruitment overfishing—i.e. an LRP below which stocks should not fall. It is concluded that, for the first time to our knowledge, defining such an LRP for a tuna species is possible (about 30 thousand tonnes or 5% of estimated unfished spawning stock biomass in our calculation). Not only is the LRP based on actual experience, but also the logic behind it would be easier for stakeholders to understand than the theoretical LRPs used elsewhere. This LRP should be useful in future in more comprehensive management framework, such as one through management strategy evaluations, in which stakeholder involvement in decision-making is crucial.

Demographic responses of boreal caribou to cumulative disturbances highlight elasticity of range-specific tolerance thresholds

Conserving species-at-risk requires quantifiable knowledge of the key drivers of population change. Non-linear demographic responses to habitat loss have been documented for many species and may serve to establish quantitative habitat thresholds for management purposes. In Canada, boreal populations of woodland caribou are considered threatened; Environment Canada’s empirical model of calf recruitment–range disturbance suggests that at least 65% undisturbed habitat is required to ensure viability. We tested the relationship upon which this conservation guideline is based by pairing demographic estimates with range conditions over a 10-year period for three boreal caribou populations. Our objectives were (1) to evaluate evidence of intra-population demographic responses to fluctuations in range quality over time; (2) to evaluate inter-population differences in demographic responses to cumulative range disturbances; and (3) to evaluate the sensitivity of disturbance tolerance thresholds to variation in local population demography. We found strong evidence in support of the disturbance–recruitment relationship for within-population responses over time (R2 = 0.77). Mixed effects logistic regression modeling revealed variations in local population responses to cumulative habitat depletion. Range-specific disturbance thresholds derived from Monte Carlo simulations were highly elastic in response to observed variation in local population demography, suggesting that 65% undisturbed habitat is insufficient when adult female survival and/or sex ratio is suboptimal. Study populations were determined to be not self-sustaining (Pr(λ ≥ 0.99) = 37–47%). Adult survival was comparable to estimates reported elsewhere despite Aboriginal harvesting for subsistence purposes. Results underscored potential trade-offs between forest harvesting and wildlife habitat conservation. Protection and restoration of sufficient quantities of undisturbed habitat, particularly via road reclamation, is essential for caribou population recovery.

Non‐parametric modeling reveals environmental effects on bluefin tuna recruitment in Atlantic, Pacific, and Southern Oceans

AbstractEnvironment–recruitment relationships can be difficult to delineate with parametric statistical models and can be prone to misidentification. We use non‐parametric time‐series modeling which makes no assumptions about functional relationships between variables, to reveal environmental influences on early life stages of bluefin tuna and demonstrate improvement in prediction of subsequent recruitment. The influence of sea surface temperature, which has been previously associated with larval growth and survival, was consistently detected in recruitment time series of bluefin tuna stocks that spawn in the Mediterranean Sea, the North Pacific, and the Southern Ocean. Short time series for the Gulf of Mexico stock may have precluded a clear determination of environmental influences on recruitment fluctuations. Because the non‐parametric approach does not require specification of equations to represent system dynamics, predictive models can likely be developed that appropriately reflect the complexity of the ecological system under investigation. This flexibility can potentially overcome methodological challenges of specifying structural relationships between environmental conditions and fish recruitment. Consequently, there is potential for non‐parametric time series modeling to supplement traditional stock recruitment models for fisheries management.

Clockwise Loops and Anticlockwise Loops Observed in a Stock-Recruitment Relationship

Loop-shaped trajectories are commonly observed in the stock recruitment relationship (SRR). A mechanism has been proposed that explains why the loops emerge in SRR. The aim of this study is to validate the mechanism using data for the stocks of 24 fish s...

Correction of “A Recruitment Forecasting Model for the Pacific Stock of the Japanese Sardine (Sardinops melanostictus) That Does Not Assume Density-Dependent Effects”

This study developed a recruitment forecasting model based on a new concept of the stock recruitment relationship. No density-dependent effect in the relationship was assumed in the model, which showed that fluctuations in recruitment and spawning stock biomass of Japanese sardine in the northwestern Pacific can be explained mainly by environmental factors and the effects of fishing. The February Arctic Oscillation (AO) and sea surface temperature over the southern area of the Kuroshio Extension (30 - 35°N and 145 - 180°E; KEST) were used as the environmental factors. The recruitment forecasting model is proposed: The values for recruitment (), spawning stock biomass, (), in year t, forecast by this model accurately reproduced those estimated by tuning virtual population analysis (VPA), and the pattern of variability in the stock recruitment relationship was also reproduced well. In conclusion, a density-dependent effect does not necessarily have to be included to explain the large variations in recruitment and the spawning stock biomass of the Japanese sardine.

A Framework for Exploring How Density Dependence Early in the Life History Can Affect Louisiana's Brown Shrimp Fishery

AbstractThe dynamics underlying fisheries stock–recruitment relationships are often obscure, especially with relatively short-lived invertebrate species, such as the brown shrimp Farfantepenaeus aztecus. Nonetheless, disentangling these dynamics can help to reveal optimal management strategies for long-term sustainability. We developed a matrix model to link early shrimp life history with the fishable stock and nested the degree of density-dependent settler (i.e., juvenile) survival in a Beverton–Holt framework. Density dependence in the settler stage was assumed to have an inverse relationship with marsh habitat availability. Thus, we could determine the level of potential compensation in the settler stage and compare how changes in habitat versus fishing pressure could ultimately affect Louisiana’s brown shrimp population. A simplified Bayesian state-space (i.e., hierarchical) model provided a theoretical framework for estimating density dependence and exploring how substantial increases in catch or den...

Rising temperatures increased recruitment of brown tiger prawn (Penaeus esculentus) in Moreton Bay (Australia)

Abiotic factors are fundamental drivers of the dynamics of wild marine fish populations. Identifying and quantifying their influence on species targeted by the fishing industry is difficult and very important for managing fisheries in a changing climate. Using multiple regression, we investigated the influence of both temperature and rainfall on the variability of recruitment of a tropical species, the brown tiger prawn (Penaeus esculentus), in Moreton Bay which is located near the southern limit of its distribution on the east coast of Australia. A step-wise selection between 60 environmental variables identified temperature as the most important environmental factor to explain the variations of recruitment between 1990 and 2014. Including temperature into the Beverton and Holt stock–recruitment relationship explained 69% of the recruitment variability compared with 9.5% when omitted. This analysis indicates that increasing temperatures have increased recruitment of brown tiger prawn in Moreton Bay.

Exploring optimal walleye exploitation rates for northern Wisconsin Ceded Territory lakes using a hierarchical Bayesian age-structured model

We assessed population dynamics of walleye (Sander vitreus) in multiple Ceded Territory lakes, which support recreational and tribal fisheries, using a hierarchical Bayesian age-structured model. We used distributions of parameter estimates to develop a dynamic simulation model to forecast performances of walleye fisheries across these lakes under alternative recreational and tribal fishing scenarios. Application of a hierarchical approach allowed us to obtain more accurate estimates of stock–recruitment relationships, natural mortality, maturity and selectivity schedules, and growth parameters for individual lakes, especially for those with relatively uninformative data, and to characterize their variability among lakes. Using standing spawning stock biomass, recreational and tribal harvest, and probability of population collapse as performance metrics, our simulations suggest that northern Wisconsin walleye populations can sustain a regional optimal exploitation rate of about 20% on average given the existing recreational and tribal gear selectivities. However, lake-specific optimal exploitation rates may be higher or lower depending on estimated lake productivities, suggesting that effective management of the Ceded Territory walleye fisheries should account for variability in population dynamics among lakes.

Roles of spatial scale in quantifying stock–recruitment relationships for American lobsters in the inshore Gulf of Maine

It is well known in ecological studies that the choice of spatial scale can influence the possibility of detecting ecological patterns and the type of patterns observed. However, this has rarely been evaluated for fish stock–recruitment (SR) dynamics. Inappropriate scales may result in failure to identify possible SR relationships, especially for species with complicated life history and stock structure and locally generated recruitment. Using American lobster (Homarus americanus) in the Gulf of Maine (GOM) as an example, we tested the hypotheses that the SR relationship is detectable only at certain spatial scales and the functional SR relationships vary with spatial scales. We estimated the SR relationship separately for American lobster in the eastern and western GOM, which have strongly differing oceanographic conditions that may result in different suitable spatial scale and SR dynamics for lobster. We analyzed data of 11 different spatial scales using a Bayesian method. The model fit and performances in the posterior predictive assessment for the SR models were convexly related to the spatial scales. The functional SR relationships differed for different spatial scale. The SR parameter estimates are negatively or concavely related to the spatial scale. The best model was found at medium spatial scale for both the eastern and western GOM, and the scale differed between the eastern and western GOM, suggesting that optimal spatial scale might be process-related. We demonstrated that the choice of spatial scale directly affected the possibility of identifying the SR relationship, the estimation of SR parameters, the type of SR relationships, and the predictive abilities of the SR models.

Chilean fishing law, maximum sustainable yield, and the stock recruitment relationship

During 2013, the Chilean fishing law was amended to incorporate, among other changes, the maximum sustainable yield (MSY) as target reference point for managing fishery resources. This mandate triggered the estimation of MSY-based reference points (RPs) in each fishery subject to catch limits in Chile. Recent investigations indicate that production models provide MSY-based RPs, which are predicted only by using the steepness of the stock-recruitment relationship ( h ). In this paper, we compare predicted MSY-based RPs using production models with estimates from an age-structured per-recruit model for eleven demersal stocks harvested in Chile.

In what direction should the fishing mortality target change when natural mortality increases within an assessment?

Traditionally, the natural mortality rate (M) in a stock assessment is assumed to be constant. When M increases within an assessment, the question arises how to change the fishing mortality rate target (FTarget). Per recruit considerations lead to an increase in FTarget, while limiting total mortality leads to a decrease in FTarget. Application of either approach can result in nonsensical results. Short-term gains in yield associated with high FTarget values should be considered in light of potential losses in future yield if the high total mortality rate leads to a decrease in recruitment. Examples using yellowtail flounder (Limanda ferruginea) and Atlantic cod (Gadus morhua) are used to demonstrate that FTarget can change when M increases within an assessment and to illustrate the consequences of different FTarget values. When a change in M within an assessment is contemplated, first consider the amount and strength of empirical evidence to support the change. When the empirical evidence is not strong, we recommend using a constant M. If strong empirical evidence exists, we recommend estimating FTarget for a range of stock–recruitment relationships and evaluating the trade-offs between risk of overfishing and forgone yield.

A biophysical model to assess the trade-off between larval recruitment and catch in southern Australia's largest prawn fishery

Data from stock assessment surveys, published research and climate sensors were linked to model the interaction between fishing, physical‐oceanographic processes and spatial patterns of larval settlement for western king prawn [Penaeus (Melicertus) latisulcatus]. This information was used to evaluate the trade‐off between larval recruitment and catch during fishing periods that demand high prices but coincide with spawning. Total rates of larval settlement were maximized when tidal currents and atmospheric physical‐forcing components were coupled with simulations of larval swimming behaviour under average gulf temperatures. Average gulf temperatures sustained longer larval durations and increased larval settlement rates by over 12% compared with warmer gulf conditions simulated under a scenario of global warming. Reproductive data coupled with outputs from the biophysical model identified consistent inter‐annual patterns in the areas contributing to larval settlement success. Areas located in the north‐east, and central‐west of the fishery, consistently contributed to over 40% of all larvae reaching a settlement in each year. Harvest sensitivity analyses indicated that changes in the spatial patterns of pre‐Christmas fishing could lead to improvements in overall rates of the larval settlement while maintaining or improving the levels of catch. Future studies to refine the model inputs relating to physical processes, larval behaviour and mortality rates for P. latisulcatus coupled with surveys of juvenile prawn abundance to ground truth the modelled predictions, would allow stock recruitment relationships to be more closely examined and inform adaptive management of the fishery in the future.

Reconsidering the impossible — linking environmental drivers to growth, mortality, and recruitment of fish

After a century of research into the drivers of early life (EL) growth and mortality, fisheries science has acquired limited capacity to predict future recruitment. A meta-analysis of stock assessment time series revealed that it may be difficult to identify stock– or environmental–recruitment drivers given limited variability in spawner biomass, recruitment, and survivorship in most populations. In nearly 50% of the stocks, there was limited information at low spawner biomass, limiting the reliability of fits to stock–recruitment models. Furthermore, variations in survivorship in 50% of year-classes resulted in less than a 2.5-fold change in recruitment. Simulations of three scenarios of change in EL growth and mortality rates demonstrated that they must covary positively to reproduce variations in survivorship consistent with observations. The potentially limited reliability of stock–recruitment relationships to predict year-class strength in many stocks and the low variability in survivorship in a large proportion of year-classes has important implications for the development of projections of stock productivity used in scientific advice. Furthermore, if a positive growth–mortality relationship underlies variations in survivorship, new research approaches are required to understand the trophic relationships that govern the dynamics of early life stages of fish and patterns of recruitment variability.

Assumptions behind size-based ecosystem models are realistic

AbstractA recent publication about balanced harvesting (Froese et al., ICES Journal of Marine Science; 73: 1640–1650) contains several erroneous statements about size-spectrum models. We refute the statements by showing that the assumptions pertaining to size-spectrum models discussed by Froese et al. are realistic and consistent. We further show that the assumption about density-dependence being described by a stock recruitment relationship is responsible for determining whether a peak in the cohort biomass of a population occurs late or early in life. Finally, we argue that there is indeed a constructive role for a wide suite of ecosystem models to evaluate fishing strategies in an ecosystem context.

Spatial and temporal dynamics of Atlantic menhaden (Brevoortia tyrannus) recruitment in the Northwest Atlantic Ocean

AbstractAtlantic menhaden, Brevoortia tyrannus, is an abundant, schooling pelagic fish that is widely distributed in the coastal Northwest Atlantic. It supports the largest single-species fishery by volume on the east coast of the United States. However, relatively little is known about factors that control recruitment, and its stock–recruitment relationship is poorly defined. Atlantic menhaden is managed as a single unit stock, but fisheries and environmental variables likely act regionally on recruitments. To better understand spatial and temporal variability in recruitment, fishery-independent time-series (1959–2013) of young-of-year (YOY) abundance indices from the Mid-Atlantic to Southern New England (SNE) were analysed using dynamic factor analysis and generalized additive models. Recruitment time-series demonstrated low-frequency variability and the analyses identified two broad geographical groupings, the Chesapeake Bay (CB) and SNE. Each of these two regions exhibited changes in YOY abundance and different periods of relatively high YOY abundance that were inversely related to each other; CB indices were highest from ca. 1971 to 1991, whereas SNE indices were high from ca. 1995 to 2005. We tested for effects of climatic, environmental, biological, and fishing-related variables that have been documented or hypothesized to influence stock productivity. A broad-scale indicator of climate, the Atlantic Multidecadal Oscillation, was the best single predictor of coast-wide recruitment patterns, and had opposing effects on the CB and SNE regions. Underlying mechanisms of spatial and interannual variability in recruitment likely derive from interactions among climatology, larval transport, adult menhaden distribution, and habitat suitability. The identified regional patterns and climatic effects have implications for the stock assessment of Atlantic menhaden, particularly given the geographically constrained nature of the existing fishery and the climatic oscillations characteristic of the coastal ocean.

Testing for synchrony in recruitment among four Lake Michigan fish species

In the Great Lakes region, multiple fish species display intraspecific spatial synchrony in recruitment success, with interannual climate variation hypothesized as the most likely driver. In Lake Michigan, we evaluated whether climatic or other physical variables could also induce spatial synchrony across multiple species, including bloater (Coregonus hoyi), rainbow smelt (Osmerus mordax), yellow perch (Perca flavescens), and alewife (Alosa pseudoharengus). The residuals from stock–recruitment relationships revealed yellow perch recruitment to be correlated with recruitment of both rainbow smelt (r = 0.37) and alewife (r = 0.36). Across all four species, higher than expected recruitment occurred in 5 years between 1978 and 1987 and then switched to lower than expected recruitment in 5 years between 1996 and 2004. Generalized additive models revealed warmer spring and summer water temperatures and lower wind speeds corresponded to higher than expected recruitment for the nearshore-spawning species, and overall variance explained ranged from 14% (yellow perch) to 61% (alewife). For all species but rainbow smelt, higher recruitment also occurred in extremely high or low years of the North Atlantic Oscillation index. Future development of indices that describe the physical Great Lakes environment could improve understanding of how climate can synchronize fish populations within and across species.

HIV Prevalence, Estimated Incidence, and Risk Behaviors Among People Who Inject Drugs in Kenya

HIV infection in sub-Saharan Africa increasingly occurs among people who inject drugs (PWID). Kenya is one of the first to implement a national needle and syringe program. Our study undertook a baseline assessment as part of evaluating needle and syringe program in a seek, test, treat, and retain approach. Participants enrolled between May and December 2012 from 10 sites. Respondent-driven sampling was used to reach 1785 PWID for HIV-1 prevalence and viral load determination and survey data. Estimated HIV prevalence, adjusted for differential network size and recruitment relationships, was 14.5% in Nairobi (95% CI: 10.8 to 18.2) and 20.5% in the Coast region (95% CI: 17.3 to 23.6). Viral load (log10 transformed) in Nairobi ranged from 1.71 to 6.12 (median: 4.41; interquartile range: 3.51-4.94) and in the Coast from 1.71 to 5.88 (median: 4.01; interquartile range: 3.44-4.72). Using log10 viral load 2.6 as a threshold for HIV viral suppression, the percentage of HIV-infected participants with viral suppression was 4.2% in Nairobi and 4.6% in the Coast. Heroin was the most commonly injected drug in both regions, used by 93% of participants in the past month, typically injecting 2-3 times/day. Receptive needle/syringe sharing at last injection was more common in Nairobi (23%) than in the Coast (4%). Estimated incidence among new injectors was 2.5/100 person-years in Nairobi and 1.6/100 person-years in the Coast. The HIV epidemic is well established among PWID in both Nairobi and Coast regions. Public health scale implementation of combination HIV prevention has the potential to greatly limit the epidemic in this vulnerable and bridging population.

Seasonal temperature and precipitation regulate brook trout young‐of‐the‐year abundance and population dynamics

Summary Abundance of the young‐of‐the‐year (YOY) fish can vary greatly among years and it may be driven by several key biological processes (i.e. adult spawning, egg survival and fry survival) that span several months. However, the relative influence of seasonal weather patterns on YOY abundance is poorly understood. We assessed the importance of seasonal air temperature (a surrogate for stream temperature) and precipitation (a surrogate for stream flow) on brook trout (Salvelinus fontinalis) YOY summer abundance using a 29‐year data set from 115 sites in Shenandoah National Park, Virginia, U.S.A. We used a Bayesian hierarchical model that allowed the effect of seasonal weather covariates to vary among sites and accounted for imperfect detection of individuals. Summer YOY abundance was affected by preceding seasonal air temperature and precipitation, and these regional‐scale drivers led to spatial synchrony in YOY abundance dynamics across the 170‐km‐long study area. Mean winter precipitation had the greatest effect on YOY abundance and the relationship was negative. Mean autumn precipitation, and winter and spring temperature had significantly positive effects on YOY abundance, and mean autumn temperature had a significant negative effect. In addition, the effect of summer precipitation differed along a latitudinal gradient, with YOY abundance at more northern sites being more responsive to inter‐annual variation in summer precipitation. Strong YOY years resulted in high abundance of adults (>age 1 + fish) in the subsequent year at more than half of sites. However, higher adult abundance did not result in higher YOY abundance in the subsequent year at any of the study sites (i.e. no positive stock–recruitment relationship). Our results indicate that YOY abundance is a key driver of brook trout population dynamics that is mediated by seasonal weather patterns. A reliable assessment of climate change impacts on brook trout needs to account for how alternations in seasonal weather patterns impact YOY abundance and how such relationships may differ across the range of brook trout distribution.

Identification and quantification of heteroscedasticity in stock–recruitment relationships

Nonconstant variance (heteroscedasticity) in the stock–recruitment (S-R) relationship is proposed as an important factor in sustainable fisheries management, but its reliable estimation from noisy populations is problematic. We developed methods for both frequentist and Bayesian approaches to test whether we can accurately estimate the degree of heteroscedasticity in 90 published S-R populations. We estimated the confidence interval for the heteroscedastic regression model via a parametric bootstrap approach and the credible interval for the Bayesian method via a Markov chain Monte Carlo sampling algorithm. We found strong evidence of negative heteroscedasticity in several stocks, regardless of the statistical paradigm, the details of density dependence, and the methods used to generate the original populations. This statistical framework, together with its associated freely available software, provides an efficient and reliable setting for assessing heteroscedasticity of the S-R relationship in fisheries.