Hauser Cindy E, Pople Anthony R, Possingham Hugh P
Department of Mathematics, University of Queensland, St. Lucia, Queensland 4072, Australia.
Ecol Appl. 2006 Apr;16(2):807-19. doi: 10.1890/1051-0761(2006)016[0807:smpbme]2.0.co;2.
We often need to estimate the size of wild populations to determine the appropriate management action, for example, to set a harvest quota. Monitoring is usually planned under the assumption that it must be carried out at fixed intervals in time, typically annually, before the harvest quota is set. However, monitoring can be very expensive, and we should weigh the cost of monitoring against the improvement that it makes in decision making. A less costly alternative to monitoring annually is to predict the population size using a population model and information from previous surveys. In this paper, the problem of monitoring frequency is posed within a decision-theory framework. We discover that a monitoring regime that varies according to the state of the system can outperform fixed-interval monitoring. This idea is illustrated using data for a red kangaroo (Macropus rufus) population in South Australia. Whether or not one should monitor in a given year is dependent on the estimated population density in the previous year, the uncertainty in that population estimate, and past rainfall. We discover that monitoring is important when a model-based prediction of population density is very uncertain. This may occur if monitoring has not taken place for several years, or if rainfall has been above average. Monitoring is also important when prior information suggests that the population is near a critical threshold in population abundance. However, monitoring is less important when the optimal management action would not be altered by new information.
我们常常需要估计野生种群的规模，以便确定适当的管理措施，例如设定捕捞配额。监测通常是在这样的假设下进行规划的：即在设定捕捞配额之前，必须按照固定的时间间隔进行，通常是每年一次。然而，监测可能非常昂贵，我们应该权衡监测成本与其在决策方面带来的改进。一种比每年监测成本更低的替代方法是使用种群模型和以往调查的信息来预测种群规模。在本文中，监测频率问题是在决策理论框架内提出的。我们发现，根据系统状态而变化的监测方案可能比固定间隔监测更有效。以南澳大利亚红袋鼠（Macropus rufus）种群的数据为例说明了这一观点。在特定年份是否进行监测取决于上一年估计的种群密度、该种群估计的不确定性以及过去的降雨量。我们发现，当基于模型的种群密度预测非常不确定时，监测很重要。如果已经有几年没有进行监测，或者降雨量高于平均水平，就可能出现这种情况。当先前信息表明种群接近种群丰度的临界阈值时，监测也很重要。然而，当新信息不会改变最优管理措施时，监测的重要性就较低。
