首页> 外文期刊>The Journal of Applied Ecology >Performance of a state-space multispecies model: What are the consequences of ignoring predation and process errors in stock assessments?
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Performance of a state-space multispecies model: What are the consequences of ignoring predation and process errors in stock assessments?

机译:的性能状态multispecies模型:忽略捕食的后果是什么在股票评估和处理错误吗?

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1. Having a realistic representation of ecosystems in fisheries models is important in the context of ecosystem-based fisheries management (EBFM). While different modelling approaches support EBFM, accounting for trophic interactions and uncertainty in stock dynamics is important for management advice. Multispecies models exist, but are rarely used for assessments. Most stock assessments are single species models and predation is subsumed into natural mortality, which is often an assumed known value. The use of state-space assessment models, which account for stochasticity in unobserved processes (process errors), is increasing. However, many stocks are managed assuming deterministic processes. Little is known of how ignoring predation and process errors in stock assessment can impact the perception of the stocks and therefore fisheries management. 2. We developed an age-structured multispecies operating model that simulated data with errors in observations, recruitment and fish abundance. Four estimation models (EMs) that differed according to whether or not they accounted for predation or process errors were fitted to the simulated data. Relative differences between true and predicted outputs were estimated as a measure of bias. Equilibrium unfished biomass was estimated for each model as a proxy reference point. 3. Ignoring predation had the largest impact on stock perception and resulted in large bias in parameters, derived outputs and absolute or relative reference points. Estimating unobserved processes was not sufficient in limiting the bias when natural mortality was misspecified. 4. Ignoring process errors had limited bias but the bias increased when no contrasts existed in fishing mortality over time. 5. Looking solely at likelihood values to choose among models is misleading and predictive ability could be used to prevent selecting models that overfit the data. 6. Synthesis and applications. Ignoring trophic interactions that occur in marine ecosystems in
机译:1. 在渔业模型中是很重要的基于生态系统的渔业管理(EBFM)。而不同的建模方法支持EBFM,占营养交互和股票动态的不确定性是非常重要的管理的建议。很少用于评估。评估模型和单一的物种捕食并入自然死亡率,这通常是一个假定的已知值。状态评估模型,占未被注意的流程(过程中特性转化错误),正在增加。假设确定的流程管理。被忽视捕食和如何处理错误的股票会影响评估对股票的看法,因此渔业管理。multispecies操作模型,模拟数据错误的观察,招聘和鱼丰富。根据他们是否不同占捕食或流程错误安装在模拟数据。真正的和预测输出之间的区别估计的测量偏差。为每个模型unfished生物量估计代理参考点。对股市影响最大的知觉和导致大偏差参数,导出输出和绝对或相对参考点。足够的极限偏差时自然死亡率misspecified。错误偏差但偏差增加有限当没有对比中存在钓鱼死亡率随着时间的推移。选择模型是一种误导和可以用来防止预测能力overfit数据的选择模型。合成和应用程序。发生在海洋生态系统的相互作用

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