Evaluation of methods for monitoring changes in abundance and productivity of pacific salmon populations

对太平洋鲑鱼种群的丰度和生产力的估计往往有很大的置信限，并受到偏见的影响。这种情况可能导致根据保护标准对种群濒危程度进行错误分类。这种错误分类可能增加生物养护的风险，或不必要地减少渔业或其他水生系统用途的社会和经济利益。然而，用于监测的预算有限。因此，我们建议使用基于经验的计算机模拟，以确定可靠的，具有成本效益的监测和评估方法鲑鱼。这些方法将包括各种数据收集计划、采样的空间和时间模式以及分析所得数据的技术。我们将确定可以估计鲑鱼丰度和生产力的方法，以及它们的保护状况，具有低偏差和高精度。这些方法将减少对鲑鱼种群状态的错误分类的机会，从而增加维持鲑鱼种群处于生产状态的机会。为了与新兴的“以证据为基础的保护”概念保持一致，我们还将评估鲑鱼监测计划的不同实验设计的优点，以找到那些减少混淆因素（例如，环境或人为引起的变化）。这种设计将缩小关于过去丰度变化原因的合理假设的范围，并将更可靠地评估恢复行动的有效性。因此，这项研究将有助于确定哪些监测方法和实验设计是可行的，最有效地实现保护和恢复目标。

Estimates of abundance and productivity for Pacific salmon populations often have wide confidence limits and are subject to bias. This situation can lead to misclassification of a population's level of endangerment based on conservation criteria. Such misclassifications may increase biological conservation risks or unnecessarily decrease social and economic benefits of fishing or other uses of aquatic systems. However, budgets for monitoring are limited. We therefore propose to use empirically based computer simulations to identify reliable, cost-effective monitoring and assessment methods for salmon. Such methods will consist of various data collection schemes, spatial and temporal patterns of sampling, and techniques for analyzing the resulting data. We will identify methods that can estimate salmon abundance and productivity, as well as their conservation status, with low bias and high precision. Those methods will reduce the chance of misclassifying the status of salmon populations and thereby increase the chance of maintaining them in a productive state.In keeping with the emerging concept of "evidence-based conservation", we will also evaluate the merits of different experimental designs of salmon monitoring programs to find those that reduce the influence of confounding factors (e.g., simultaneous environmental or human-induced changes). Such designs will narrow the range of plausible hypotheses about causes of past changes in abundance and will more reliably evaluate the effectiveness of recovery actions. This research will thus help determine which monitoring methods and experimental designs are both feasible and most effective at achieving conservation and recovery goals.