Integrated multi-timescale modeling untangles anthropogenic, environmental, and biological effects on catchability

2019 ◽  
Vol 76 (11) ◽  
pp. 2045-2056 ◽  
Author(s):  
Shota Nishijima ◽  
Shigenori Suzuki ◽  
Momoko Ichinokawa ◽  
Hiroshi Okamura
Keyword(s):  
Population Dynamics ◽  
Stock Assessment ◽  
Biological Effects ◽  
Predictive Ability ◽  
Fishing Effort ◽  
Estimation Accuracy ◽  
Takifugu Rubripes ◽  
Time Varying ◽  
Population Dynamics Model ◽  
Age Structured

Catchability plays a central role in fisheries stock assessment. Since catchability often varies with time depending on population density, environmental factors, and anthropogenic effects, assuming constant catchability in population models can lead to biased abundance estimates. Here we present a novel way to simultaneously estimate time-varying catchability and abundance by integrating a short-term (month-based) removal method and a long-term (year-based) age-structured population dynamics model. We applied this approach to commercial fishery data for a Japanese pufferfish (Takifugu rubripes) population and found that the models with time-varying catchability greatly outperformed the models with constant catchability in terms of predictive ability and model consistency. The temporal variation in catchability was parsimoniously predicted by fishing effort and population size, indicating the existence of effort- and density-dependent catchability. Our approach, integrating population dynamics at different timescales, will help avoid inadvertent overexploitation and contribute to sustainable harvesting by enhancing the estimation accuracy of time-varying catchability and abundance.

scholarly journals Integrating tagging and fisheries data into a spatial population dynamics model to improve its predictive skills

2020 ◽  
Vol 77 (3) ◽  
pp. 576-593 ◽  
Author(s):  
Inna Senina ◽  
Patrick Lehodey ◽  
John Sibert ◽  
John Hampton
Keyword(s):  
Population Dynamics ◽  
Stock Assessment ◽  
Spatial Dynamics ◽  
Likelihood Estimation ◽  
Fish Population ◽  
Environmental Data ◽  
Diffusion Reaction ◽  
Population Dynamics Model ◽  
The Pacific ◽  
Age Structured

SEAPODYM is a model developed for investigating spatiotemporal dynamics of fish populations under the influence of both fishing and the environment. The model simulates age-structured population dynamics using advection–diffusion–reaction equations describing movement, recruitment, and natural and fishing mortality. The dynamic processes are constrained by environmental data and distributions of prey species. Model parameter estimation using fishing data was implemented earlier based on a maximum likelihood estimation (MLE) approach and adjoint technique. Here, we describe the integration of tagging data into the existing MLE approach with application to skipjack tuna (Katsuwonus pelamis) in the Pacific Ocean. We find that tagging data improve estimates of species habitat parameters and movement rates and hence allow better representation of spatial dynamics of fish population. Due to estimated lower diffusion and higher advection rates, the model predicts less non-observed “cryptic” biomass, which leads to the stock sizes being closer to those estimated by stock assessment models commonly used by tuna commissions.

Incorporating habitat preference into the stock assessment and management of blue marlin (Makaira nigricans) in the Pacific Ocean

2012 ◽  
Vol 63 (7) ◽  
pp. 565 ◽  
Author(s):  
Nan-Jay Su ◽  
Chi-Lu Sun ◽  
André E. Punt ◽  
Su-Zan Yeh ◽  
Gerard DiNardo
Keyword(s):  
Population Dynamics ◽  
Habitat Preference ◽  
Stock Assessment ◽  
Ecosystem Approach ◽  
Maximum Sustainable Yield ◽  
Blue Marlin ◽  
Makaira Nigricans ◽  
Biological Variables ◽  
Population Dynamics Model ◽  
Spawning Stock

Stock assessments that include a spatial component or relate population dynamics to environmental conditions can be considered one way of implementing an ecosystem approach to fisheries. A spatially-structured population dynamics model that takes account of habitat preference is developed and then applied to Pacific blue marlin (Makaira nigricans), as they prefer certain habitats and migrate seasonally. The model is fitted to fishery catch-rate and size data, along with information on the relative density of the population over space derived from a habitat preference model fitted to oceanographic and biological variables. Results show that blue marlin are more abundant in tropical waters, and females account for most of the biomass. Assessments that allow for environmental factors, movement dynamics and sexual dimorphism indicate that this population is in an over-exploited state, with current spawning stock biomass below the level corresponding to maximum sustainable yield (SMSY) and current fishing mortality exceeding that needed to achieve MSY (FMSY). A risk analysis based on samples from a Bayesian posterior distribution suggests that the population will remain above SMSY after 20 years if exploitation rates are below the level corresponding to FMSY.

scholarly journals Looking in the rear-view mirror: bias and retrospective patterns in integrated, age-structured stock assessment models

2014 ◽  
Vol 72 (1) ◽  
pp. 99-110 ◽  
Author(s):  
Felipe Hurtado-Ferro ◽  
Cody S. Szuwalski ◽  
Juan L. Valero ◽  
Sean C. Anderson ◽  
Curry J. Cunningham ◽  
...  
Keyword(s):  
Life Histories ◽  
Temporal Change ◽  
Stock Assessment ◽  
Model Misspecification ◽  
Assessment Model ◽  
Time Varying ◽  
Simulation Framework ◽  
Zero Values ◽  
Age Structured ◽  
Management Advice

Abstract Retrospective patterns are systematic changes in estimates of population size, or other assessment model-derived quantities, that occur as additional years of data are added to, or removed from, a stock assessment. These patterns are an insidious problem, and can lead to severe errors when providing management advice. Here, we use a simulation framework to show that temporal changes in selectivity, natural mortality, and growth can induce retrospective patterns in integrated, age-structured models. We explore the potential effects on retrospective patterns of catch history patterns, as well as model misspecification due to not accounting for time-varying biological parameters and selectivity. We show that non-zero values for Mohn’s ρ (a common measure for retrospective patterns) can be generated even where there is no model misspecification, but the magnitude of Mohn’s ρ tends to be lower when the model is not misspecified. The magnitude and sign of Mohn’s ρ differed among life histories, with different life histories reacting differently from each type of temporal change. The value of Mohn’s ρ is not related to either the sign or magnitude of bias in the estimate of terminal year biomass. We propose a rule of thumb for values of Mohn’s ρ which can be used to determine whether a stock assessment shows a retrospective pattern.

scholarly journals Delay-dependent attractivity on a tick population dynamics model incorporating two distinctive time-varying delays

2021 ◽  
Vol 477 (2251) ◽  
pp. 20210302
Author(s):  
Chuangxia Huang ◽  
Jian Zhang ◽  
Jinde Cao
Keyword(s):  
Population Dynamics ◽  
Global Attractivity ◽  
Positive Equilibrium ◽  
Tick Population ◽  
Time Varying ◽  
Dynamics Model ◽  
Population Dynamics Model ◽  
All Solutions ◽  
Positive Equilibrium Point ◽  
Delay Dependent

In this paper, we aim to investigate the influence of delay on the global attractivity of a tick population dynamics model incorporating two distinctive time-varying delays. By exploiting some differential inequality techniques and with the aid of the fluctuation lemma, we first prove the persistence and positiveness for all solutions of the addressed equation. Consequently, a delay-dependent criterion is derived to assure the global attractivity of the positive equilibrium point. And lastly, some numerical simulations are presented to verify that the obtained results improve and complement some existing ones.

scholarly journals sPop: Age-structured discrete-time population dynamics model in C, Python, and R

F1000Research ◽  
2020 ◽  
Vol 7 ◽  
pp. 1220
Author(s):  
Kamil Erguler
Keyword(s):  
Population Dynamics ◽  
Discrete Time ◽  
Uniform Design ◽  
Disease Spread ◽  
Dependent Manner ◽  
Dynamics Model ◽  
Fixed Rate ◽  
Animal Populations ◽  
Population Dynamics Model ◽  
Age Structured

This article describes the sPop packages implementing the deterministic and stochastic versions of an age-structured discrete-time population dynamics model. The packages enable mechanistic modelling of a population by monitoring the age and development stage of each individual. Survival and development are included as the main effectors and they progress at a user-defined pace: follow a fixed rate, delay for a given time, or progress at an age-dependent manner. The model is implemented in C, Python, and R with a uniform design to ease usage and facilitate adoption. Early versions of the model were previously employed for investigating climate-driven population dynamics of the tiger mosquito and the chikungunya disease spread by this vector. The sPop packages presented in this article enable the use of the model in a range of applications extending from vector-borne diseases towards any age-structured population including plant and animal populations, microbial dynamics, host-pathogen interactions, infectious diseases, and other time-dependent epidemiological processes.

scholarly journals sPop: Age-structured discrete-time population dynamics model in C, Python, and R

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1220 ◽  
Author(s):  
Kamil Erguler
Keyword(s):  
Population Dynamics ◽  
Discrete Time ◽  
Uniform Design ◽  
Disease Spread ◽  
Dependent Manner ◽  
Dynamics Model ◽  
Fixed Rate ◽  
Animal Populations ◽  
Population Dynamics Model ◽  
Age Structured

This article describes the sPop packages implementing the deterministic and stochastic versions of an age-structured discrete-time population dynamics model. The packages enable mechanistic modelling of a population by monitoring the age and development stage of each individual. Survival and development are included as the main effectors and they progress at a user-defined pace: follow a fixed-rate, delay for a given time, or progress at an age-dependent manner. The model is implemented in C, Python, and R with a uniform design to ease usage and facilitate adoption. Early versions of the model were previously employed for investigating climate-driven population dynamics of the tiger mosquito and the chikungunya disease spread by this vector. The sPop packages presented in this article enable the use of the model in a range of applications extending from vector-borne diseases towards any age-structured population including plant and animal populations, microbial dynamics, host-pathogen interactions, infectious diseases, and other time-delayed epidemiological processes.

Stock assessment of school shark, Galeorhinus galeus, based on a spatially explicit population dynamics model

2000 ◽  
Vol 51 (3) ◽  
pp. 205 ◽  
Author(s):  
André E. Punt ◽  
Fred Pribac ◽  
Terence I. Walker ◽  
Bruce L. Taylor ◽  
Jeremy D. Prince
Keyword(s):  
Population Dynamics ◽  
Spatial Structure ◽  
Stock Assessment ◽  
Dynamics Model ◽  
Point Estimates ◽  
Population Dynamics Model ◽  
Equilibrium Size ◽  
Assessment Approach ◽  
The Status ◽  
Galeorhinus Galeus

The school shark (Galeorhinus galeus) resource off southern Australia is assessed by use of an assessment approach that takes account of the spatial structure of the population. The population dynamics model underlying the assessment considers the spatial as well as the age-specific characteristics of school shark. It allows for a series of fisheries (each based on a different gear type), explicitly models the pupping/recruitment process, and allows for multiple stocks. The values for the parameters of this model are determined by fitting it to catch-rate data and information from tagging studies. The point estimates of the pup production at the start of 1997 range from 12% to 18% of the pre-exploitation equilibrium size, depending on the specifications of the assessment. Allowing for spatial structure and incorporating tag release–recapture data lead to reduced uncertainty compared with earlier assessments. The status of the resource, as reflected by the ratio of present to virgin pup production and total (1+) biomass, is sensitive to the assumed level of movement between the stocks in New Zealand and those in Australia, with lower values corresponding to higher levels of movement.

Evaluation of alternative modelling approaches to account for spatial effects due to age-based movement

2017 ◽  
Vol 74 (11) ◽  
pp. 1832-1844 ◽  
Author(s):  
Hui-Hua Lee ◽  
Kevin R. Piner ◽  
Mark N. Maunder ◽  
Ian G. Taylor ◽  
Richard D. Methot
Keyword(s):  
Population Dynamics ◽  
Stock Assessment ◽  
Simulated Data ◽  
Assessment Method ◽  
Error Modeling ◽  
Assessment Model ◽  
Future Research ◽  
Observation Error ◽  
Time Varying ◽  
Spatial Effects

Spatial patterns due to age-specific movement have been a source of unmodelled process error. Modeling movement in spatially explicit stock assessments is feasible, but hampered by a paucity of data from appropriate tagging studies. This study uses simulation analyses to evaluate alternative model structures that either explicitly or implicitly account for the process of time-varying age-based movement in a population dynamics model. We simulated synthetic populations using a two-area stochastic population dynamics operating model. Simulated data were fit in seven different estimation models. Only the model that includes the correct spatial dynamic results in unbiased and precise estimates of derived and management quantities. In a single-area assessment model, using the fleets-as-area (FAA) approach may be the second best option to estimate both length-based and time-varying age-based selectivity to implicitly account for the contact selectivity and annual availability. An FAA approach adds additional observation error performed nearly as well. Future research could evaluate which stock assessment method is robust to uncertainty in movement and is more appropriate for achieving intended management objectives.

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