scholarly journals An extension of the stepwise stochastic simulation approach for estimating distributions of missing life history parameter values for sharks, groupers, and other taxa: supplementary table

2021 ◽  
Vol 119 (1) ◽  
Author(s):  
Kenneth A. Erickson ◽  
Marc O. Nadon
Keyword(s):  
Life History ◽  
Stochastic Simulation ◽  
Simulation Approach ◽  
Life History Parameter ◽  
Parameter Values

scholarly journals Ensemble models for data-poor assessment: accounting for uncertainty in life-history information

2019 ◽  
Vol 76 (4) ◽  
pp. 870-883 ◽  
Author(s):  
Merrill B Rudd ◽  
James T Thorson ◽  
Skyler R Sagarese
Keyword(s):  
Life History ◽  
Learning Algorithm ◽  
Stock Assessment ◽  
Model Averaging ◽  
Biological Information ◽  
Parameter Distribution ◽  
Life History Parameter ◽  
Multivariate Distributions ◽  
Life History Parameters ◽  
Parameter Values

Abstract Length measurements from fishery catch can be used in data-limited assessments to estimate important population parameters to guide management, but results are highly sensitive to assumptions about biological information. Ideally, local life history studies inform biological parameters. In the absence of reliable local estimates, scientists and managers face the difficult task of agreeing on fixed values for life-history parameters, often leading to additional uncertainty unquantified in the assessment or indecision defaulting to status-quo management. We propose an ensemble approach for incorporating life history uncertainty into data-limited stock assessments. We develop multivariate distributions of growth, mortality, and maturity parameter values, then use bivariate interpolation and stacking as an ensemble learning algorithm to propagate uncertainty into length-based, data-limited stock assessment models. Simulation testing demonstrated that stacking across life history parameter values leads to improved interval coverage over simple model averaging or assuming the parameter distribution means when the true life-history parameter values are unknown. We then applied the stacking approach for a U.S. Caribbean stock where the Scientific and Statistical Committee did not accept the assessment due to uncertainty in life history parameters. Stacking can better characterize uncertainty in stock status whenever life-history parameters are unknown but likely parameter distributions are available.

Stochastic simulation for determining the design flood of cascade reservoir systems

2012 ◽  
Vol 43 (1-2) ◽  
pp. 54-63 ◽  
Author(s):  
Baohong Lu ◽  
Huanghe Gu ◽  
Ziyin Xie ◽  
Jiufu Liu ◽  
Lejun Ma ◽  
...  
Keyword(s):  
Simulation Model ◽  
Stochastic Simulation ◽  
Southern China ◽  
Flow Simulation ◽  
Simulation Method ◽  
Simulation Approach ◽  
Design Flood ◽  
Design Values ◽  
Stochastic Simulation Model ◽  
The Impact

Stochastic simulation is widely applied for estimating the design flood of various hydrosystems. The design flood at a reservoir site should consider the impact of upstream reservoirs, along with any development of hydropower. This paper investigates and applies a stochastic simulation approach for determining the design flood of a complex cascade of reservoirs in the Longtan watershed, southern China. The magnitude of the design flood when the impact of the upstream reservoirs is considered is less than that without considering them. In particular, the stochastic simulation model takes into account both systematic and historical flood records. As the reliability of the frequency analysis increases with more representative samples, it is desirable to incorporate historical flood records, if available, into the stochastic simulation model. This study shows that the design values from the stochastic simulation method with historical flood records are higher than those without historical flood records. The paper demonstrates the advantages of adopting a stochastic flow simulation approach to address design-flood-related issues for a complex cascade reservoir system.

scholarly journals Testing temporal changes in allele frequencies: a simulation approach

2010 ◽  
Vol 92 (4) ◽  
pp. 309-320 ◽  
Author(s):  
EDSON SANDOVAL-CASTELLANOS
Keyword(s):  
Molecular Data ◽  
Temporal Changes ◽  
Allele Frequencies ◽  
Small Populations ◽  
Simulation Approach ◽  
Simulation Test ◽  
Agent Based ◽  
Binomial Sampling ◽  
Molecular Databases ◽  
Parameter Values

SummaryAnalysis of the temporal variation in allele frequencies is useful for studying microevolutionary processes. However, many statistical methods routinely used to test temporal changes in allele frequencies fail to establish a proper hypothesis or have theoretical or practical limitations. Here, a Bayesian statistical test is proposed in which the distribution of the distances among sampling frequencies is approached with computer simulations, and hypergeometric sampling is considered instead of binomial sampling. To validate the test and compare its performance with other tests, agent-based model simulations were run for a variety of scenarios, and two real molecular databases were analysed. The results showed that the simulation test (ST) maintained the significance value used (α=0·05) for a vast combination of parameter values, whereas other tests were sensitive to the effect of genetic drift or binomial sampling. The differences between binomial and hypergeometric sampling were more complex than expected, and a novel effect was described. This study suggests that the ST is especially useful for studies with small populations and many alleles, as in microsatellite or sequencing molecular data.

scholarly journals How to model honeybee population dynamics: stage structure and seasonality

2020 ◽  
pp. 1-34 ◽  
Author(s):  
Jun Chen ◽  
Komi Messan ◽  
Marisabel Rodriguez Messan ◽  
Gloria DeGrandi-Hoffman ◽  
Dingyong Bai ◽  
...  
Keyword(s):  
Age Structure ◽  
Theoretical Study ◽  
Stage Structure ◽  
Egg Laying ◽  
Life History Parameter ◽  
Honeybee Population ◽  
Honeybee Colony ◽  
Theoretical And Numerical Analysis ◽  
Parameter Values ◽  
Condition B

Western honeybees (Apis Mellifera) serve extremely important roles in our ecosystem and economics as  they are responsible for pollinating $ 215 billion dollars annually over the world.  Unfortunately,  honeybee population and their colonies have been declined dramatically. The purpose of this article is to explore how we should model honeybee population with age structure and validate the model using empirical data so that we can identify different factors that lead to the survival and healthy of the honeybee colony.  Our theoretical study combined with simulations and data validation suggests that the proper age structure incorporated in the model  and seasonality are important for modeling honeybee population.  Specifically, our work implies that the model assuming that (1) the adult bees are survived from the egg population rather than the brood population; and (2) seasonality in the queen egg laying rate, give the better fit than other honeybee models. The related theoretical and numerical analysis of the most fit model indicate that (a) the survival of honeybee colonies requires a large queen egg-laying rate and smaller values of the other life history parameter values in addition to proper initial condition; (b) both brood and adult bee populations are increasing with respect to the increase in the egg-laying rate and the decreasing in other parameter values; and (c) seasonality may promote/suppress the survival of the honeybee colony. 

Ontogenetic Niche Shifts

2013 ◽  
Author(s):  
André M. de Roos ◽  
Lennart Persson
Keyword(s):  
Life History ◽  
Extended Model ◽  
Full Model ◽  
Life History Stages ◽  
Ontogenetic Diet Shifts ◽  
Ontogenetic Niche Shifts ◽  
Niche Shifts ◽  
Limited Supply ◽  
Diet Shifts ◽  
Parameter Values

This chapter considers the consequences for community structure of ontogenetic diet shifts that involve the use of different resources in different life history stages, whereby these resources are in limited supply and are hence competed for by all individuals foraging on them. It explores the consequences of ontogenetic diet shifts using stage-structured biomass models that account for two basic resources, a stage-structured consumer population, for which we distinguish between juveniles and adults, and up to two unstructured predator populations. The most extended model is therefore closely related to the model analyzed in Chapter 5, except for the inclusion of an additional basic resource. The equations of the full model are summarized and default parameter values are listed.

scholarly journals Evaluating the consequences of common assumptions in run reconstructions on Pacific-salmon biological status assessments

2019 ◽  
Author(s):  
Stephanie J. Peacock ◽  
Eric Hertz ◽  
Carrie A. Holt ◽  
Brendan Connors ◽  
Cameron Freshwater ◽  
...  
Keyword(s):  
Data Analysis ◽  
Stochastic Simulation ◽  
Incomplete Data ◽  
Pacific Salmon ◽  
Management Strategies ◽  
Simulation Approach ◽  
The Face

AbstractInformation on biological status is essential for designing, implementing, and evaluating management strategies and recovery plans for threatened or exploited species. However, the data required to quantify status are often limited, and it is important to understand how assessments of status may be biased by assumptions in data analysis. For Pacific salmon, biological status assessments based on spawner abundances and spawner-recruitment (SR) analyses often involve “run reconstructions” that impute missing spawner data, expand observed spawner abundance to account for unmonitored streams, assign catch to individual stocks, and quantify age-at-return. Using a stochastic simulation approach, we quantified how common assumptions in run reconstructions biased assessments of biological status based on spawner abundance. We found that status assessments were robust to most common assumptions in run reconstructions, even in the face of declining monitoring coverage, but that overestimating catch tended to increase rates of status misclassification. Our results lend confidence to biological status assessments based on spawner abundances and SR analyses, even in the face of incomplete data.

scholarly journals Evaluating the consequences of common assumptions in run reconstructions on Pacific salmon biological status assessments

2020 ◽  
Vol 77 (12) ◽  
pp. 1904-1920
Author(s):  
Stephanie J. Peacock ◽  
Eric Hertz ◽  
Carrie A. Holt ◽  
Brendan Connors ◽  
Cameron Freshwater ◽  
...  
Keyword(s):  
Data Analysis ◽  
Stochastic Simulation ◽  
Incomplete Data ◽  
Pacific Salmon ◽  
Management Strategies ◽  
Simulation Approach ◽  
The Face

Information on biological status is essential for designing, implementing, and evaluating management strategies and recovery plans for threatened or exploited species. However, the data required to quantify status are often limited, and it is important to understand how assessments of status may be biased by assumptions in data analysis. For Pacific salmon, biological status assessments based on spawner abundances and spawner–recruitment (SR) analyses often involve “run reconstructions” that impute missing spawner data, expand observed spawner abundance to account for unmonitored streams, assign catch to individual stocks, and quantify age-at-return. Using a stochastic simulation approach, we quantified how common assumptions in run reconstructions biased assessments of biological status based on spawner abundance. We found that status assessments were robust to most common assumptions in run reconstructions, even in the face of declining monitoring coverage, but that overestimating catch tended to increase rates of status misclassification. Our results lend confidence to biological status assessments based on spawner abundances and SR analyses, even in the face of incomplete data.

scholarly journals The theoretical surrender value in life insurance

2016 ◽  
Vol 7 (1) ◽  
pp. 31-44 ◽  
Author(s):  
Nicolino Ettore D’Ortona ◽  
Maria Sole Staffa
Keyword(s):  
Stochastic Simulation ◽  
Life Insurance ◽  
Stochastic Models ◽  
Calculation Method ◽  
Risk Model ◽  
Insurance Company ◽  
Simulation Approach ◽  
Method Of Calculation ◽  
Insurance Portfolio ◽  
Value Determination

In the context of the stochastic models for the management of life insurance portfolio, the authors explore, with simulation approach, the effects induced by the application of a particular method of calculation of the surrender value. In the life insurance, the policyholder position is, at any moment, quantified by the mathematical reserve. In case the reserve amount results are positive, the insurance company can allow the contract surrender, consisting in an amount payment, called surrender value, commensurate with the mathematical reserve. Generally, the insurance company enforces some restrictions in the surrender value determination, in order to avoid, first of all, that an amount is disbursed to the policyholder while, on the contrary, he results to be indebted to the Company. In this paper the authors will consider a surrender value calculation method based precisely on the profit recovery concept which shall be supplied by the contract in case it remains in the portfolio. Additionally, the authors shall analyze, by simulation approach, the effects caused by the enforcement of the surrender value calculation concept on a life portfolio profitability, and on the penalties extent enforced to the policyholders which cancel from the contract. Keywords: surrender value, life insurance, internal risk model, stochastic simulation

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