General state-space population dynamics model for Bayesian stock assessment

Mantyniemi Samu H. P.; Whitlock Rebecca E.; Perala Tommi A.; Blomstedt Paul A.; Vanhatalo Jarno P.; Maria Rincon Margarita; Kuparinen Anna K.; Pulkkinen Henni P.; Kuikka O. Sakari

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General state-space population dynamics model for Bayesian stock assessment

机译：贝叶斯股票评估的一般状态空间人口动力学模型

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This study presents a state-space modelling framework for the purposes of stock assessment. The stochastic population dynamics build on the notion of correlated survival and capture events among individuals. The correlation is thought to arise as a combination of schooling behaviour, a spatially patchy environment, and common but unobserved environmental factors affecting all the individuals. The population dynamics model isolates the key biological processes, so that they are not condensed into one parameter but are kept separate. This approach is chosen to aid the inclusion of biological knowledge from sources other than the assessment data at hand. The model can be tailored to each case by choosing appropriate models for the biological processes. Uncertainty about the model parameters and about the appropriate model structures is then described using prior distributions. Different combinations of, for example, age, size, phenotype, life stage, species, and spatial location can be used to structure the population. To update the prior knowledge, the model can be fitted to data by defining appropriate observation models. Much like the biological parameters, the observation models must also be tailored to fit each individual case.

机译：这项研究提出了用于库存评估的状态空间建模框架。随机种群动态建立在个体之间相关的生存和捕获事件的概念上。这种相关性被认为是学校教育行为，空间上零散的环境以及影响所有个体的常见但未观察到的环境因素的结合。种群动力学模型将关键的生物过程隔离开来，因此它们不会被浓缩为一个参数，而是保持分离。选择这种方法是为了帮助从现有评估数据以外的其他来源中获取生物学知识。通过为生物过程选择适当的模型，可以为每种情况定制模型。然后使用先验分布描述模型参数和适当模型结构的不确定性。可以使用例如年龄，大小，表型，生命阶段，种类和空间位置的不同组合来构造种群。为了更新现有知识，可以通过定义适当的观察模型将模型拟合到数据。就像生物学参数一样，观察模型也必须经过调整以适合每个个案。

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来源
《ICES Journal of Marine Science》 |2015年第8期|2209-2222|共14页
作者
Mantyniemi Samu H. P.; Whitlock Rebecca E.; Perala Tommi A.; Blomstedt Paul A.; Vanhatalo Jarno P.; Maria Rincon Margarita; Kuparinen Anna K.; Pulkkinen Henni P.; Kuikka O. Sakari;
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作者单位

Univ Helsinki, Dept Environm Sci, Fisheries & Environm Management Grp FEM, FIN-00014 Helsinki, Finland;

Swedish Univ Agr Sci, Dept Aquat Resources, S-17893 Drottningholm, Sweden;

Univ Helsinki, Dept Environm Sci, Fisheries & Environm Management Grp FEM, FIN-00014 Helsinki, Finland;

Univ Helsinki, Dept Environm Sci, Fisheries & Environm Management Grp FEM, FIN-00014 Helsinki, Finland;

Univ Helsinki, Dept Environm Sci, Fisheries & Environm Management Grp FEM, FIN-00014 Helsinki, Finland;

ICMAN CSIC, Consejo Super Invest Cient, Inst Ciencias Marinas Andalucia, Puerto Real, Cadiz, Spain;

Univ Helsinki, Dept Environm Sci, Fisheries & Environm Management Grp FEM, FIN-00014 Helsinki, Finland;

Nat Resources Inst Finland, FI-90014 Oulu, Finland;

Univ Helsinki, Dept Environm Sci, Fisheries & Environm Management Grp FEM, FIN-00014 Helsinki, Finland;

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正文语种 eng
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关键词
Dirichlet-Multinomial distribution; effective population size; Markov chain Monte Carlo; stock assessment; uncertainty;

机译：Dirichlet-多项式分布;有效人口规模;马尔可夫链蒙特卡洛;股票评估;不确定性;

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专利

1. On the latent state estimation of nonlinear population dynamics using Bayesian and non-Bayesian state-space models [J] . Wang GM Ecological Modelling . 2007,第3a4期

机译：基于贝叶斯和非贝叶斯状态空间模型的非线性种群动力学的潜在状态估计
2. In search of climate effects on Atlantic Croaker (Micropogonias undulatus) stock off the US Atlantic coast with Bayesian state-space biomass dynamic models [J] . Munyandorero Joseph Fishery Bulletin . 2014,第1期

机译：利用贝叶斯状态空间生物量动力学模型寻找气候对美国大西洋沿岸大西洋Cro鱼（Micropogonias undulatus）种群的影响
3. Bayesian stock assessment using a state-space implementation of the delaydifference model [J] . Meyer R., Millar RB. Canadian Journal of Fisheries and Aquatic Sciences . 1999,第1期

机译：使用时差模型的状态空间实现贝叶斯股票评估
4. Toward dynamic marine spatial planning tools: Can we inform fisheries stock assessments by using dynamic habitat models informed by the integrated ocean observing system (IOOS)? [C] . Kohut Josh, Palamara Laura, Curchitser Enrique, 2014 Oceans-St. John's Conference . 2014

机译：建立动态海洋空间规划工具：我们能否利用综合海洋观测系统（IOOS）提供的动态生境模型为渔业种群评估提供信息？
5. State-Space Population Dynamics Models with Applications to Population Viability Analysis, the Conservation of Sagebrush Birds in the Great Basin and Estimating Fisheries Catch-Per-Unit-Effort Indices [D] . See, Kevin Engler 2011

机译：状态空间人口动力学模型及其在种群生存力分析，大盆地鼠尾草鸟类保护和估算渔业捕捞量/单位努力指标中的应用
6. Bayesian salamanders: analysing the demography of an underground population of the European plethodontid Speleomantes strinatii with state-space modelling [O] . Jan Lindström, Richard Reeve, Sebastiano Salvidio 2010

机译：贝叶斯sal：使用状态空间模型分析欧洲食齿动物Speleomantes strinatii地下人口的人口统计
7. In search of climate effects on Atlantic Croaker (Micropogonias undulatus) stock off the U.S. Atlantic coast with Bayesian state-space biomass dynamic modelsud [O] . Munyandorero Joseph 2014

机译：使用贝叶斯状态空间生物量动态模型寻找对美国大西洋沿岸大西洋coast鱼（Micropogonias undulatus）种群的气候影响 ud

General state-space population dynamics model for Bayesian stock assessment

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