scholarly journals Local influence diagnostics for the retrospective problem in sequential population analysis

2005 ◽  
Vol 62 (2) ◽  
pp. 256-265 ◽  
Author(s):  
Noel G. Cadigan ◽  
Patrick J. Farrell
Keyword(s):  
Stock Assessment ◽  
Population Analysis ◽  
Scientific Information ◽  
Local Influence ◽  
Natural Mortality ◽  
Abundance Index ◽  
Stock Size ◽  
Influence Diagnostics ◽  
Proportional Relationship

Abstract The retrospective problem involves systematic differences in sequential population analysis (SPA) estimates of stock size or some other quantity in a reference year. The differences occur as successively more data are used for estimation, and they appear to be structural biases caused by a mis-specification of the SPA. In some cases the retrospective problem is so severe that the SPA is considered to be too unreliable for stock assessment purposes. There are many possible sources of retrospective patterns, and it is usually difficult in practice to determine which are more likely. We propose diagnostics to help determine the more likely causes. We use local influence diagnostics to investigate whether small changes or perturbations to SPA input components such as catches or natural mortalities can remove or reduce retrospective patterns. We show, for the fall-spawning herring stock in the southern Gulf of St. Lawrence SPA, that relatively small age- and year-specific changes to the SPA assumptions about the proportional relationship between an abundance index and stock size can result in greatly reduced retrospective patterns. We therefore conclude primafacie that these assumptions are a plausible source of the retrospective pattern. Larger changes to catches, natural mortality assumptions, or estimation weights are required to reduce the retrospective pattern. These other factors seem to be less plausible sources of the retrospective pattern, although this is best assessed by the herring stock experts who are more knowledgeable about the fishery and other scientific information for this stock.

Stock Reduction Analysis, Another Solution to the Catch Equations

1982 ◽  
Vol 39 (11) ◽  
pp. 1467-1472 ◽  
Author(s):  
Daniel K. Kimura ◽  
Jack V. Tagart
Keyword(s):  
Mortality Rate ◽  
Stock Assessment ◽  
Clupea Harengus ◽  
New Method ◽  
Total Biomass ◽  
Natural Mortality ◽  
Catch Per Unit Effort ◽  
Available N ◽  
Stock Size ◽  
Virtual Population

In fishery stock assessments, catch equations provide the critical link between stock size, natural mortality rate, fishing rate, and catch size. Catch equations are most powerful when age data are available, allowing cohorts to be followed through time using Virtual Population and Cohort Analysis. In this paper we propose a simple new method of linking catch equations when age data are not available. Assuming catches are given in biomass, catch equations are written for each year with a constant recruitment (R), based on a single parameter, added to the total biomass at the beginning of each year. In addition to the catch equations, a final equation is added describing the change in biomass caused by the years of fishing. If n years of catch data are available, n + 1 equations can be written. By conditioning on instantaneous natural mortality rate (M), initial stock size (B1) and the decline in stock size (P) (note P = Bn+1/B1), the n + 1 simultaneous nonlinear equations can be solved iteratively for instantaneous fishing mortality rates (F1, …, Fn) and recruitment (R). When properly plotted, the solution set to this system of equations was found to be a helpful tool to aid in the evaluation of stock condition. In particular, the plots provide a method for incorporating ancillary information from diverse sources such as hydroacoustic surveys, analysis of catch per unit effort data, and Virtual Population Analysis. This new method of stock assessment, which we call Stock Reduction Analysis, is applied to Pacific ocean perch (Sebastes alutus), Pacific herring (Clupea harengus pallasi), and Pacific hake (Merluccius productus) stocks being actively managed by the State of Washington.Key words: Stock Reduction Analysis, stock assessment, catch equations, computer modeling

Incorporating Uncertainty into Fishery Models

2002 ◽  
Keyword(s):  
Striped Bass ◽  
Population Model ◽  
Input Data ◽  
Stock Assessment ◽  
Population Analysis ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Sources Of Uncertainty ◽  
Incorrect Model ◽  
Age Structured

<em>Abstract.—</em> A stock assessment of Atlantic striped bass <em>Morone saxatilis </em> was presented to illustrate potential sources of uncertainty in application of an age-based population model. Erroneous conclusions in stock assessment can result from incorrect model selection, input data that are not representative of the target population, and improper configuration of the selected model. Influence of incorrect input data and model configuration was investigated using striped bass catch-at-age data analyzed with a tuned virtual population analysis model (ADAPT VPA). Variations in model configurations were explored in addition to sensitivity to input parameters such as natural mortality. Violation of the assumption of constant natural mortality-at-age had a significant influence on the resulting estimates of <EM>F </EM> and stock size. Discard losses, particularly from the commercial fishery, were the largest source of uncertainty in the catch-at-age. Uncertainty due to process error in the VPA model was characterized by bootstrap realizations of the nonlinear least-squares estimates of fishing mortality. The implications associated with fishing at various <EM>F</EM> s were also examined using a stochastic projection model. A comparison of fishing mortality estimates derived from two independent models, an age-structured population model and a tag-recovery model, indicated that both methods produced equivalent results. Evaluation of the striped bass stock assessment demonstrates that uncertainty could result from a variety of sources but this variability was only partially captured within the model framework. Understanding the possible sources of uncertainty and implications in interpreting model results should benefit the analyst in providing assessment advice to managers.

Natural mortality diagnostics for state-space stock assessment models

2021 ◽  
Vol 243 ◽  
pp. 106062
Author(s):  
Andrea M.J. Perreault ◽  
Noel G. Cadigan
Keyword(s):  
State Space ◽  
Stock Assessment ◽  
Natural Mortality

Virtual Population Analysis (VPA) Equations for Nonhomogeneous Populations, and a Family of Approximations Including Improvements on Pope's Cohort Analysis

1986 ◽  
Vol 43 (12) ◽  
pp. 2406-2409 ◽  
Author(s):  
Alec D. MacCall
Keyword(s):  
Mortality Rate ◽  
Population Analysis ◽  
Seasonal Pattern ◽  
Cohort Analysis ◽  
Natural Mortality ◽  
Close Approximation ◽  
Virtual Population Analysis ◽  
Virtual Population ◽  
Special Case

A set of "backward" virtual population analysis (VPA) equations relates catch (Ct) from continuous fishing between times t and t + 1 to population n size (Nt, Nt+1) when a portion of the stock is unavailable to fishing. The usual VPA equations become a special case where the entire stock is available (i.e. the stock is homogeneous). A close approximation to the VPA equations is Nt = Nt+1 exp(M) + CtM/(1 − exp(−M)), which has properties similar to Pope's "cohort analysis" and is somewhat more accurate in the case of a continuous fishery, especially if the natural mortality rate (M) is large. Much closer simple approximations are possible if the seasonal pattern of catches is known.

Understanding historical summer flounder (Paralichthys dentatus) abundance patterns through the incorporation of oceanography-dependent vital rates in Bayesian hierarchical models

2019 ◽  
Vol 76 (8) ◽  
pp. 1275-1294 ◽  
Author(s):  
Cecilia A. O’Leary ◽  
Timothy J. Miller ◽  
James T. Thorson ◽  
Janet A. Nye
Keyword(s):  
Population Dynamics ◽  
Gulf Stream ◽  
Stock Assessment ◽  
Deviance Information Criterion ◽  
Information Criterion ◽  
Natural Mortality ◽  
Vital Rates ◽  
Summer Flounder ◽  
Paralichthys Dentatus ◽  
Abundance Patterns

Climate can impact fish population dynamics through changes in productivity and shifts in distribution, and both responses have been observed for many fish species. However, few studies have incorporated climate into population dynamics or stock assessment models. This study aimed to uncover how past variations in population vital rates and fishing pressure account for observed abundance variation in summer flounder (Paralichthys dentatus). The influences of the Gulf Stream Index, an index of climate variability in the Northwest Atlantic, on abundance were explored through natural mortality and stock–recruitment relationships in age-structured hierarchical Bayesian models. Posterior predictive loss and deviance information criterion indicated that out of tested models, the best estimates of summer flounder abundances resulted from the climate-dependent natural mortality model that included log-quadratic responses to the Gulf Stream Index. This climate-linked population model demonstrates the role of climate responses in observed abundance patterns and emphasizes the complexities of environmental effects on populations beyond simple correlations. This approach highlights the importance of modeling the combined effect of fishing and climate simultaneously to understand population dynamics.

scholarly journals An integrated tagging model to estimate mortality rates of Albemarle Sound – Roanoke River striped bass

2017 ◽  
Vol 74 (7) ◽  
pp. 1061-1076 ◽  
Author(s):  
Julianne E. Harris ◽  
Joseph E. Hightower
Keyword(s):  
Striped Bass ◽  
Stock Assessment ◽  
Mortality Rates ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Albemarle Sound ◽  
High Reward ◽  
Accuracy And Precision ◽  
Summer Mortality ◽  
Roanoke River

We developed an integrated tagging model to estimate mortality rates and run sizes of Albemarle Sound – Roanoke River striped bass (Morone saxatilis), including (i) a multistate component for telemetered fish with a high reward external tag; (ii) tag return components for fish with a low reward external or PIT tag; and (iii) catch-at-age data. Total annual instantaneous mortality was 1.08 for resident (458–899 mm total length, TL) and 0.45 for anadromous (≥900 mm TL) individuals. Annual instantaneous natural mortality was higher for resident (0.70) than for anadromous (0.21) fish due to high summer mortality in Albemarle Sound. Natural mortality for residents was substantially higher than currently assumed for stock assessment. Monthly fishing mortality from multiple sectors (including catch-and-release) corresponded to seasonal periods of legal harvest. Run size estimates were 499 000–715 000. Results and simulation suggest increasing sample size for the multistate component increases accuracy and precision of annual estimates and low reward tags are valuable for estimating monthly fishing mortality rates among sectors. Our results suggest that integrated tagging models can produce seasonal and annual mortality estimates needed for stock assessment and management.

Nonstationarity of Production Relationships in Exploited Populations

1987 ◽  
Vol 44 (S2) ◽  
pp. s156-s165 ◽  
Author(s):  
Carl J. Walters
Keyword(s):  
Environmental Changes ◽  
Historical Data ◽  
Stock Assessment ◽  
Policy Implications ◽  
Data Sets ◽  
Stock Structure ◽  
Stock Size ◽  
Rate Processes ◽  
And Shifts ◽  
Time Invariant

Stock assessment usually proceeds from the assumption that there are time-invariant relationships between stock size and rate processes such as recruitment, although such relationships are difficult to discern due to noise caused by factors other than stock size. There are good biological reasons not to trust this assumption in exploited populations, where persistent environmental changes and shifts in stock structure may cause various parameters to change. Graphical and statistical procedures can be used to detect this nonstationarity in historical data sets for which stock size has varied so as to repeatedly sample a range of sizes. The policy implications of nonstationarity depend on whether the changes are clearly observable as deviations from known, Song-term baseline responses. If the changes are observable, it is usually best to pretend that the current deviation will persist unless strong constraints on policy change make it necessary to plan for changes that may occur far into the future. If the changes are not observable (the usual case), then it is necessary to make a difficult policy choice between passively waiting for informative stock responses versus actively experimenting with harvest rates so as to quickly get information about responses over a range of stock sizes.

Sign in / Sign up

Export Citation Format

Share Document