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Comparative species abundance modeling of Capitellidae (Annelida) in Tampa Bay, Florida, USA
Marine Ecology Progress Series ( IF 2.2 ) Pub Date : 2020-10-29 , DOI: 10.3354/meps13484
J Hilliard 1 , D Karlen 2 , T Dix 2 , S Markham 2 , A Schulze 1
Affiliation  

ABSTRACT: Capitellid polychaetes are ubiquitous throughout the world’s oceans and are often encountered in high abundance. We used an extensive dataset of species abundance and distribution records of the Capitella capitata complex, C. aciculata, C. jonesi, Heteromastus filiformis, Mediomastus ambiseta, and M. californiensis from Tampa Bay, Florida, USA, as a model system of closely related species filling a similar ecological niche. We sought to (1) characterize the spatial distribution of each species, (2) determine if a single species abundance modeling strategy could be applied to them all, and (3) assess environmental drivers of species distribution and abundance. We found that all species had a zero-inflated abundance distribution and there was spatial autocorrelation by bay regions. Lorenz curves were an effective tool to assess spatial patterns of species abundance across large areas. Bay segment, depth, and dissolved oxygen were the most important environmental drivers. Modeling was accomplished by comparing 6 different approaches: 4 generalized additive models (GAMs: Poisson, negative binomial, Tweedie, and zero-inflated Poisson distributions), hurdle models, and boosted regression trees. There was no single model with top performance for every species. However, GAM-Tweedie and hurdle models performed well overall and may be useful for studies of other benthic marine invertebrates.

中文翻译:

美国佛罗里达州坦帕湾海豚科(Annelida)的比较物种丰度模型

摘要:Capitellid多毛猎犬在世界各地的海洋中无处不在,并且经常以高丰度遇到。我们使用的品种数量和分布记录的广泛数据集Capitella结球甘蓝复杂,C. aciculataC. jonesiHeteromastus丝状Mediomastus ambisetaM. californiensis来自美国佛罗里达坦帕湾的模型,是密切相关物种的模型系统,填补了类似的生态位。我们试图(1)描述每个物种的空间分布特征,(2)确定是否可以将单个物种丰度建模策略应用于所有物种,以及(3)评估物种分布和丰度的环境驱动因素。我们发现所有物种都具有零膨胀的丰度分布,并且各海湾地区存在空间自相关。洛伦兹曲线是评估大面积物种丰富度空间格局的有效工具。湾段,深度和溶解氧是最重要的环境驱动因素。通过比较6种不同的方法来完成建模:4种广义加性模型(GAM:泊松,负二项式,特威迪和零膨胀泊松分布),跨栏模型,并增加了回归树。没有哪个模型能为每个物种提供最佳性能。但是,GAM-Tweedie模型和跨栏模型总体上表现良好,对于研究其他底栖海洋无脊椎动物可能有用。
更新日期:2020-10-30
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