Abstract Spatial autocorrelation is common in environmental factors, species distributions, and predator-prey interactions. Spatially autocorrelated distribution of prey and strong prey selectivity by predators may cause spatial autocorrelation of the fish diet shown as higher similarity among diets of fish caught nearby or in the same trip. We explore the importance of spatial autocorrelation analysis in understanding the fish diet composition and predator-prey interaction in diet analysis based on one example fish whitespotted conger (Conger myriaster) in the Yellow Sea and its prey species that have been monitored across seasons. Among the spatial estimators, the cluster-based estimator is used to quantify fish diet similarity from the same trip, and the spatial Gaussian and exponential autocorrelated estimators are used to test the hypothesis that fish diet similarity decreases over distance. The two types of spatially autocorrelated estimators performed better than spatially-independent and cluster-based estimators, with lower mean square errors in a cross-validation procedure. Prey selectivity related to the prey availability, and the spatial overlap between predator and prey were likely important factors affecting seasonal and spatial variations in diet composition of the example fish species. Cross-variograms indicated that whitespotted conger and some of its dominant prey species were positively spatially autocorrelated, which suggested fishes generally aggregated in areas of high prey density. Our study provides a practical basis for considering the effect of spatial characteristics in quantifying the diet composition likely linked to the environmental driven distributions of both fishes and their prey.

中文翻译：

---

自相关对海洋鱼类季节性饮食组成影响的空间分析

摘要 空间自相关在环境因素、物种分布和捕食者-猎物相互作用中很常见。猎物的空间自相关分布和捕食者对猎物的强烈选择性可能导致鱼类饮食的空间自相关，表现为附近或同一次旅行中捕获的鱼类的饮食之间具有更高的相似性。我们探索了空间自相关分析在理解饮食分析中鱼类饮食组成和捕食者-猎物相互作用方面的重要性，该分析基于黄海中的一个示例鱼类白斑海鳗（Conger myriaster）及其跨季节监测的猎物物种。在空间估计器中，基于聚类的估计器用于量化来自同一行程的鱼类饮食相似性，空间高斯和指数自相关估计量用于检验鱼类饮食相似性随距离降低的假设。这两种类型的空间自相关估计量比空间独立估计量和基于聚类的估计量表现更好，在交叉验证过程中具有较低的均方误差。与猎物可用性相关的猎物选择性以及捕食者和猎物之间的空间重叠可能是影响示例鱼类饮食组成的季节性和空间变化的重要因素。交叉变异函数表明，白斑海鳗及其一些优势猎物物种在空间上呈正自相关，这表明鱼类通常聚集在猎物密度高的区域。