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首页> 外文期刊>Ecological Modelling >Modeling the habitat associations and spatial distribution of benthic macroinvertebrates: A hierarchical Bayesian model for zero-inflated biomass data
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Modeling the habitat associations and spatial distribution of benthic macroinvertebrates: A hierarchical Bayesian model for zero-inflated biomass data

机译：底栖大型无脊椎动物的栖息地关联和空间分布建模：零膨胀生物量数据的分层贝叶斯模型

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摘要

Biomass samples from marine scientific surveys are commonly used to investigate spatial and temporal variations in stock abundances. Biomass records are often characterized by a high proportion of zeros on the one hand, and occasional large catches on the other. These features induce a modeling challenge when trying to understand the state of populations and their ecological associations with one another and with habitat. We develop a hierarchical Bayesian model to represent the spatial structure of biomass and analyze the spatial distribution and habitat associations of three species of macro-invertebrates sampled in the southern Gulf of St. Lawrence (Canada). A zero-inflated distribution based on a compound Poisson with Gamma marks is used for the observation layer, and a linear model with spatial correlated errors accounts for the role of habitat variables (temperature, depth and sediment type) in the process layer. Maps of quantities of interest (e.g. probability of presence, quantity of biomass) are produced, taking into account the uncertainty of the estimated parameters and observation errors. This hierarchical Bayesian modeling approach provides a useful tool for spatial management of human activities that may affect living resources that may affect living resources, such as marine protected areas.
机译：来自海洋科学研究的生物质样品通常用于调查种群数量的时空变化。生物量记录的特征通常是一方面具有高比例的零，另一方面具有偶尔的大捕获量。当试图了解人口的状况及其相互之间以及与栖息地的生态联系时，这些特征引发了建模挑战。我们开发了一个分层的贝叶斯模型来表示生物量的空间结构，并分析了在圣劳伦斯湾（加拿大）南部采样的三种无脊椎动物的空间分布和生境关联。观测层使用基于带有Gamma标记的复合Poisson的零膨胀分布，具有空间相关误差的线性模型说明了栖息层变量（温度，深度和沉积物类型）在过程层中的作用。考虑到估计参数的不确定性和观测误差，制作了感兴趣数量的图（例如，存在概率，生物量的数量）。这种分层的贝叶斯建模方法为空间活动的人类活动提供了有用的工具，这些活动可能会影响可能影响生物资源的生物资源，例如海洋保护区。

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