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权衡未知因素:入侵管理中生物和操作不确定性的信息价值

Weighing the unknowns: Value of Information for biological and operational uncertainty in invasion management.

作者信息

Li Shou-Li, Keller Joseph, Runge Michael C, Shea Katriona

机构信息

Department of Biology The Pennsylvania State University University Park PA USA.

State Key Laboratory of Grassland Agro-Ecosystems Center for Grassland Microbiome, and College of Pastoral, Agriculture Science and Technology Lanzhou University Lanzhou People's Republic of China.

出版信息

J Appl Ecol. 2021 Aug;58(8):1621-1630. doi: 10.1111/1365-2664.13904. Epub 2021 Jun 22.

Abstract

The management of biological invasions is a worldwide conservation priority. Unfortunately, decision-making on optimal invasion management can be impeded by lack of information about the biological processes that determine invader success (i.e. biological uncertainty) or by uncertainty about the effectiveness of candidate interventions (i.e. operational uncertainty). Concurrent assessment of both sources of uncertainty within the same framework can help to optimize control decisions.Here, we present a Value of Information (VoI) framework to simultaneously analyse the effects of biological and operational uncertainties on management outcomes. We demonstrate this approach with a case study: minimizing the long-term population growth of musk thistle , a widespread invasive plant, using several insects as biological control agents, including , and .The ranking of biocontrol agents was sensitive to differences in the target weed's demography and also to differences in the effectiveness of the different biocontrol agents. This finding suggests that accounting for both biological and operational uncertainties is valuable when making management recommendations for invasion control. Furthermore, our VoI analyses show that reduction of all uncertainties across all combinations of demographic model and biocontrol effectiveness explored in the current study would lead, on average, to a 15.6% reduction in musk thistle population growth rate. The specific growth reduction that would be observed in any instance would depend on how the uncertainties actually resolve. Resolving biological uncertainty (across demographic model combinations) or operational uncertainty (across biocontrol effectiveness combinations) alone would reduce expected population growth rate by 8.5% and 10.5% respectively.. Our study demonstrates that intervention rank is determined both by biological processes in the targeted invasive populations and by intervention effectiveness. Ignoring either biological uncertainty or operational uncertainty may result in a suboptimal recommendation. Therefore, it is important to simultaneously acknowledge both sources of uncertainty during the decision-making process in invasion management. The framework presented here can accommodate diverse data sources and modelling approaches, and has wide applicability to guide invasive species management and conservation efforts.

摘要

生物入侵的管理是一项全球范围内的保护重点工作。遗憾的是,由于缺乏关于决定入侵者成功的生物过程的信息(即生物不确定性),或者由于候选干预措施有效性的不确定性(即操作不确定性),最优入侵管理的决策可能会受到阻碍。在同一框架内同时评估这两种不确定性来源有助于优化控制决策。在此,我们提出一个信息价值(VoI)框架,以同时分析生物和操作不确定性对管理结果的影响。我们通过一个案例研究来展示这种方法:使用几种昆虫作为生物防治剂,包括 、 和 ,来最小化广泛分布的入侵植物——矢车菊的长期种群增长。生物防治剂的排名对目标杂草种群统计学上的差异以及不同生物防治剂有效性的差异都很敏感。这一发现表明,在为入侵控制制定管理建议时,考虑生物和操作不确定性都是有价值的。此外,我们的VoI分析表明,在当前研究中探索的人口统计学模型和生物防治有效性的所有组合中,减少所有不确定性平均将导致矢车菊种群增长率降低15.6%。在任何情况下实际观察到的具体增长率降低将取决于不确定性如何实际解决。仅解决生物不确定性(跨人口统计学模型组合)或操作不确定性(跨生物防治有效性组合)分别会使预期种群增长率降低8.5%和10.5%。我们的研究表明,干预排名既由目标入侵种群中的生物过程决定,也由干预有效性决定。忽略生物不确定性或操作不确定性都可能导致次优建议。因此,在入侵管理的决策过程中同时认识到这两种不确定性来源很重要。这里提出的框架可以容纳各种数据源和建模方法,并且在指导入侵物种管理和保护工作方面具有广泛的适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cfa/8453580/039043b4821d/JPE-58-1621-g005.jpg

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