Using multivariate generalized linear latent variable models to measure the difference in event count for stranded marine animals

R. Caraka, R. Chen, Youngjo Lee, T. Toharudin, Cahyo Rahmadi, M. Tahmid, A. Achmadi
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引用次数: 10

Abstract

BACKGROUND AND OBJECTIVES: The classification of marine animals as protected species makes data and information on them to be very important. Therefore, this led to the need to retrieve and understand the data on the event counts for stranded marine animals based on location emergence, number of individuals, behavior, and threats to their presence. Whales are generally often stranded in very shallow areas with sloping sea floors and sand. Data were collected in this study on the incidence of stranded marine animals in 20 provinces of Indonesia from 2015 to 2019 with the focus on animals such as Balaenopteridae, Delphinidae, Lamnidae, Physeteridae and Rhincodontidae. METHODS:Multivariate latent generalized linear model was used to compare several distributions to analyze the diversity of event counts. Two optimization models including Laplace and Variational approximations were also applied. RESULTS: The best theta parameter in the latent multivariate latent generalized linear latent variable model was found in the Akaike Information Criterion, Akaike Information Criterion Corrected and Bayesian Information Criterion values, andthe information obtained was used to create a spatial cluster. Moreover, there was a comprehensive discussion on ocean-atmosphere interaction and the reasons the animals were stranded. CONCLUSION: The changes in marine ecosystems due to climate change, pollution, overexploitation, changes in sea use, and the existence of invasive alien species deserve serious attention.
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使用多元广义线性潜变量模型测量搁浅海洋动物事件计数的差异
背景与目的:海洋动物作为受保护物种的分类使得它们的数据和信息非常重要。因此,这导致需要检索和了解搁浅海洋动物的事件计数数据,这些数据基于位置出现、个体数量、行为和对它们存在的威胁。鲸鱼通常被困在非常浅的地方,有倾斜的海底和沙子。本研究收集了2015 - 2019年印度尼西亚20个省搁浅海洋动物的发生率数据,重点研究了Balaenopteridae、Delphinidae、Lamnidae、Physeteridae和Rhincodontidae等动物。方法:采用多元潜在广义线性模型比较几种分布,分析事件计数的多样性。同时应用了拉普拉斯和变分逼近两种优化模型。结果:发现赤池信息准则、赤池信息准则修正值和贝叶斯信息准则值在潜多元广义线性潜变量模型中theta参数最佳,并利用所得信息构建空间聚类。此外,还就海洋与大气的相互作用以及动物搁浅的原因进行了全面的讨论。结论:气候变化、污染、过度开发、海洋利用方式变化和外来入侵物种的存在等因素对海洋生态系统的影响值得重视。
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来源期刊
CiteScore
7.90
自引率
2.90%
发文量
11
审稿时长
8 weeks
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