建模恐龙在西方Andalucía使用自回归隐马尔可夫模型。

IF 3 4区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Environmental and Ecological Statistics Pub Date : 2022-09-01 DOI:10.1007/s10651-022-00534-7
Jordan Aron, Paul S Albert, Matthew O Gribble
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引用次数: 0

摘要

Dinophysis sp .可以产生腹泻性贝类毒素(DST),包括冈田酸和dinophysistoxin,一些菌株也可以产生非腹泻性pectenotoxins。尽管持久性有机污染物与人类健康有关,并在许多地方推动了环境监测计划,但这些监测计划往往存在时间上的数据差距(例如,没有测量的天数)。本文提出了一个历史时间序列模型,在2015-2020年期间,在西部Andalucía的8个监测地点,每天产生DST的产毒恐龙,包括藻类数量和DST水平的测量。我们拟合了一个双变量隐马尔可夫模型(HMM),该模型包含了观测到的DST测量之间的自回归相关性,以解释DST的环境持久性。然后,我们使用Viterbi算法以每日间隔重建水柱中藻类存在的最大似然分布。利用Andalucía的历史监测数据,该模型估计,根据地点和年份的不同,潜在的产毒藻在< 1%到>10%的时间内以大于或等于250个细胞/L的速度存在。通过这种方法实现的历史时间序列重建可能有助于未来对产毒藻华时间动态的研究。
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Modeling Dinophysis in Western Andalucía using an autoregressive hidden Markov model.

Dinophysis spp. can produce diarrhetic shellfish toxins (DST) including okadaic acid and dinophysistoxins, and some strains can also produce non-diarrheic pectenotoxins. Although DSTs are of human health concern and have motivated environmental monitoring programs in many locations, these monitoring programs often have temporal data gaps (e.g., days without measurements). This paper presents a model for the historical time-series, on a daily basis, of DST-producing toxigenic Dinophysis in 8 monitored locations in western Andalucía over 2015-2020, incorporating measurements of algae counts and DST levels. We fitted a bivariate hidden Markov Model (HMM) incorporating an autoregressive correlation among the observed DST measurements to account for environmental persistence of DST. We then reconstruct the maximum-likelihood profile of algae presence in the water column at daily intervals using the Viterbi algorithm. Using historical monitoring data from Andalucía, the model estimated that potentially toxigenic Dinophysis algae is present at greater than or equal to 250 cells/L between < 1% and >10% of the year depending on the site and year. The historical time-series reconstruction enabled by this method may facilitate future investigations into temporal dynamics of toxigenic Dinophysis blooms.

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来源期刊
Environmental and Ecological Statistics
Environmental and Ecological Statistics 环境科学-环境科学
CiteScore
5.90
自引率
2.60%
发文量
27
审稿时长
>36 weeks
期刊介绍: Environmental and Ecological Statistics publishes papers on practical applications of statistics and related quantitative methods to environmental science addressing contemporary issues. Emphasis is on applied mathematical statistics, statistical methodology, and data interpretation and improvement for future use, with a view to advance statistics for environment, ecology and environmental health, and to advance environmental theory and practice using valid statistics. Besides clarity of exposition, a single most important criterion for publication is the appropriateness of the statistical method to the particular environmental problem. The Journal covers all aspects of the collection, analysis, presentation and interpretation of environmental data for research, policy and regulation. The Journal is cross-disciplinary within the context of contemporary environmental issues and the associated statistical tools, concepts and methods. The Journal broadly covers theory and methods, case studies and applications, environmental change and statistical ecology, environmental health statistics and stochastics, and related areas. Special features include invited discussion papers; research communications; technical notes and consultation corner; mini-reviews; letters to the Editor; news, views and announcements; hardware and software reviews; data management etc.
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