Time-Varying Stock-Recruitment Model For Estimating Population Characteristics of Green Turtles

The stock-recruitment relationship (SR), customarily used in fisheries assessment, can be used to analyze demographic data of sea turtles to infer changes in hatchling production (R) as a function of nester abundance (S), recruitment rates and the influence of environmental conditions on these population features. The SR Cushing model (R=aS^b), where a and b are the model parameters) is well-suited for representing the dynamics of recovering populations, such as the green turtle (Chelonia mydas) in Campeche, Mexico. This study aimed to explore the SR Cushing model using a time series of the abundance of nesters and hatchlings (1984–2020). By applying local regressions (9-yr moving windows), we found that the time series of parameter b (the change in R as a function of S) and the recruitment rate (hatchlings per nester) were inversely correlated with a 26-yr cycle of the Atlantic Multidecadal Oscillation –sea surface temperature (SST), over the Atlantic– (r^2=0.83) and (r^2=0.64), respectively, at a 3-yr lag). Model diagnostics using the time-dependent Cushing model substantiated that the log-normal distribution of hatchlings of C. mydas in Campeche depends on the abundance of nesting females and on a low frequency SST signal (r^2=0.98). The positive trend in nester numbers of green turtles in Campeche during the past 44 years may be the result of persistent conservation efforts, while the drastic and sporadic changes in the growth rate of annual arrivals and hatchling production are suggestive of population dynamics driven by low frequency, basin-wide environmental signals.

Assessment of Four Major Fish Species Stocks in the Lithuanian and Russian Parts of Curonian Lagoon (SE Baltic Sea) Using CMSY Method

Fisheries in the Curonian Lagoon (1584 km2 coastal lagoon in South-east Baltic) can be classified as artisanal, small-scale, multi-species, and multi-gear. Such types of fisheries are characterised as data-poor and require appropriate investigation methods. We used CMSY (version CMSY_2019_9f. R) to assess maximum sustainable yield (MSY) and related indicators for freshwater bream, roach, pike-perch, and European perch. A decline in pike-perch and roach was identified, while the stocks of freshwater bream and European perch were sustained. As the CMSY model does not consider the impact of environmental factors, the decline in roach stock may be attributed to the increase in salinity rather than to overfishing. In the case of freshwater bream and pike-perch, the method cannot consider the increase of the percentage of small-sized fishes in catches due to the allowance of low-selectivity gears in the fishery. Additionally, in the case of the pike-perch, the model does not take into account the interannual fluctuations in the stock-recruitment system. The assessment of the European perch stock can be considered to be good. However, the accuracy of CMSY is limited, and it should be used for fisheries management only in combination with other methods.

Extending process and understanding for the development of complex ecosystem models, with application to the Chatham Rise Atlantis model

<p>The Chatham Rise is a highly productive deep-sea ecosystem that supports numerous substantial commercial fisheries, and is therefore a likely candidate for an ecosystem based approach to fisheries management in New Zealand. This thesis describes model construction, calibration and validation, for the first end-to-end ecosystem model of the Chatham Rise, New Zealand. The work extends beyond what has previously been done for validating such models, and explores uncertainty analyses through bootstrapping the oceanographic variables, perturbing the model's initial conditions, and analysing species interaction effects, with the results further analysed with respect to known data gaps. This enables the inclusion of uncertainty in simulated scenarios using the Chatham Rise Atlantis model, thus providing an envelope of results with which to analyse and understand the likely responses of the Chatham Rise ecosystem. The model was designed with 24 dynamic polygons, 5 water column depth bins, 55 species functional groups, and used 12-hour timesteps. The transfer of energy was tracked throughout the system using nitrogen as the model's main currency. The model simulated the system from 1900–2015, preceded by a 35 year burn-in period. The model produced very similar biomass trajectories in response to historical fishing to corresponding fisheries stock assessment models for key fisheries species. Population dynamics and system interactions were considered realistic with respect to growth rates, mortality rates, diets and species group interactions. The model was found to be generally stable under perturbations to the initial conditions, with lower trophic level species groups having the most variability. The specification of the Spawning Stock Recruitment curve was explored, as it relates to the multi-species and ecosystem models within which it is now applied. Close attention needs to be given to population dynamics specific to multi-species interactions such as predation-release, in particular the Spawning Stock Recruitment curve. Potentially misleading dynamics under predation-release were identified, and the simple solution of applying a cap to recruitment when biomass exceeds virgin levels was explored. The population dynamics of myctophids under fishing induced predation release were analysed with and without limiting recruitment to virgin levels. The effects were evident in several ecosystem indicators, suggesting unintentional mis-specification could lead to erroneous model results. It raises several questions around the specification of the Spawning Stock Recruitment relationship for multispecies models, and more generally, whether the concept of ‘virgin’ (or ‘unfished’) biomass should be reconsidered to reflect dynamic natural mortality and potentially changing unfished states. The model components that had knowledge gaps and were found to most likely to influence model results were the initial conditions, oceanographic variables, and the aggregate species groups ‘seabird’ and ‘cetacean other’. It is recommended that applications of the model, such as forecasting biomasses under various fishing regimes, should include alternatives that vary these components, and present appropriate levels of uncertainty in results. Initial conditions should be perturbed, with greater variability applied to species groups modelled as biomass-pools, and age-structured species groups that have little data available from the literature.</p>

Extending process and understanding for the development of complex ecosystem models, with application to the Chatham Rise Atlantis model

<p>The Chatham Rise is a highly productive deep-sea ecosystem that supports numerous substantial commercial fisheries, and is therefore a likely candidate for an ecosystem based approach to fisheries management in New Zealand. This thesis describes model construction, calibration and validation, for the first end-to-end ecosystem model of the Chatham Rise, New Zealand. The work extends beyond what has previously been done for validating such models, and explores uncertainty analyses through bootstrapping the oceanographic variables, perturbing the model's initial conditions, and analysing species interaction effects, with the results further analysed with respect to known data gaps. This enables the inclusion of uncertainty in simulated scenarios using the Chatham Rise Atlantis model, thus providing an envelope of results with which to analyse and understand the likely responses of the Chatham Rise ecosystem. The model was designed with 24 dynamic polygons, 5 water column depth bins, 55 species functional groups, and used 12-hour timesteps. The transfer of energy was tracked throughout the system using nitrogen as the model's main currency. The model simulated the system from 1900–2015, preceded by a 35 year burn-in period. The model produced very similar biomass trajectories in response to historical fishing to corresponding fisheries stock assessment models for key fisheries species. Population dynamics and system interactions were considered realistic with respect to growth rates, mortality rates, diets and species group interactions. The model was found to be generally stable under perturbations to the initial conditions, with lower trophic level species groups having the most variability. The specification of the Spawning Stock Recruitment curve was explored, as it relates to the multi-species and ecosystem models within which it is now applied. Close attention needs to be given to population dynamics specific to multi-species interactions such as predation-release, in particular the Spawning Stock Recruitment curve. Potentially misleading dynamics under predation-release were identified, and the simple solution of applying a cap to recruitment when biomass exceeds virgin levels was explored. The population dynamics of myctophids under fishing induced predation release were analysed with and without limiting recruitment to virgin levels. The effects were evident in several ecosystem indicators, suggesting unintentional mis-specification could lead to erroneous model results. It raises several questions around the specification of the Spawning Stock Recruitment relationship for multispecies models, and more generally, whether the concept of ‘virgin’ (or ‘unfished’) biomass should be reconsidered to reflect dynamic natural mortality and potentially changing unfished states. The model components that had knowledge gaps and were found to most likely to influence model results were the initial conditions, oceanographic variables, and the aggregate species groups ‘seabird’ and ‘cetacean other’. It is recommended that applications of the model, such as forecasting biomasses under various fishing regimes, should include alternatives that vary these components, and present appropriate levels of uncertainty in results. Initial conditions should be perturbed, with greater variability applied to species groups modelled as biomass-pools, and age-structured species groups that have little data available from the literature.</p>

Fish Population Recruitment 2: Stock Recruit Relationships and why they matter for stock assessment

A good understanding of stock recruitment is essential for accurate stock assessment and good fisheries management. But recruitment and how it is used can be difficult to understand. This publication uses a recent Florida spotted seatrout stock assessment as an example to show how the stock-recruit relationship allows managers to determine whether or not a given fish population is overfished.

Stock-recruitment models, principles of management and rules for regulating the fishery on the main Chukotka stocks of sockeye and chum salmon

Fishery pressure on populations of pacific salmons has increased in the Rusian Far East in the last decade because of growing fishing and processing capacity, so measures for the fishery regulation are necessary, as the regime of pass days in rivers and marine coastal areas. Chukotka is now almost the only region where such restrictions are still absent. However, if the interest of fishery industry to the stocks of pacific salmon in Chukotka will grow, a successful scientifically based strategy of fishery should be developed to maintain exploitation of the stocks without exceeding the limits of excessive use. Year-to-year time series on spawning stock and recruitment of chum salmon in the Anadyr area and sockeye salmon in the Meynypilgyn area were analysed for development of recruitment models and establishment of general principles for adaptive fishery management. Nonlinear adaptive fishery management based on principles of buffer managing is proposed and tested under various regimes of landing using the stock simulation models accounting deviations from the standard stock-recruitment model. There is concluded that the level of exploitation is much lower than optimal for the Anadyr chum salmon, whereas escapement for spawning of the Meynypilgyn sockeye salmon should be increased in cases of low spawning stock of this species.

Unveiling the recovery dynamics of Walleye after the invisible collapse

Walleye (Sander vitreus) populations in Alberta, Canada collapsed by the mid-1990s and were a case study in the paper Canada’s Recreational Fisheries: The Invisible Collapse? Here we fit age-structured population dynamics models to data from a landscape-scale monitoring program to assess Walleye population status and reconstruct recruitment dynamics following the invisible collapse. Assessments indicated that populations featured low F_msy values of approximately 0.2-0.3 under conservative assumptions for the stock-recruitment relationship but that many populations were lightly exploited during 2000-2018. Recruitment reconstructions showed that recovery from collapse in 33/55 lakes was driven in part by large positive recruitment anomalies that occurred during 1998-2002. Additionally, 15/55 lakes demonstrated cyclic recruitment dynamics. Both the recruitment anomalies and cyclic fluctuations could be due to environmental effect(s) and(or) cannibalism, and experimentation may be necessary to resolve this uncertainty. These findings contribute new information on the recovery dynamics of Walleye following the invisible collapse, and demonstrate the effectiveness of coupling traditional fisheries science models with broad-scale monitoring data to improve understanding of population dynamics and sustainability across landscapes.

Coupling and Decoupling of Reproduction and Larval Recruitment

Stock-recruitment relationships for managing commercial fisheries are difficult to measure and notoriously poor, so marine ecologists have relied on larval recruitment as a proxy for how planktonic processes regulate populations and communities. However, my literature review revealed that coupling between reproductive output and recruitment in benthic populations was common, occurring in 62% of 112 studies and 64% of 81 species. Coupling was considerably stronger for studies on brooders (72%) than broadcast-spawners (46%) and taxa with short (74%) than long (56%) planktonic larval durations (PLDs); hence, it was highest for brooders with short PLDs (94%). Coupling was similar in studies on benthic animals (63%) and seagrasses and kelp (56%). Coupling was detected more often by quantifying both reproductive output and settlement (79%) than adult density and recruitment (60%). It also was detected in 83% of just 21% of studies that estimated dispersal. Coupling was even detected by 55% of the 46% of studies conducted at just one site and 58% of the 65% of studies lasting no longer than 3 years. Decoupling was detected 33 times in invertebrates and fishes, occurring more often in the plankton (48.5%) and during reproduction (45.5%) than after settlement (6%), and nine times in seagrasses and kelp, occurring more often during reproduction (44.4%) than postsettlement (33.3%) or in the plankton (22.2%). Widespread coupling between reproductive output and settlement for sedentary, benthic species suggests that the poor stock-recruitment relationships typical of vagile, wide-ranging, pelagic species may be due more to the difficulty of detecting them than decoupling.