Pacific Parasites Data - Life history mediates the association between parasite abundance and geographic features

1. Though parasites are ubiquitous in marine ecosystems, predicting the abundance of parasites present within marine ecosystems has proven challenging due to the unknown effects of multiple interacting environmental gradients and stressors. Furthermore, parasites often are considered as a uniform group within ecosystems despite their significant diversity.

2. We aim to determine the potential importance of multiple predictors of parasite abundance in coral reef ecosystems, including reef area, island area, human population density, chlorophyll-a, host diversity, coral cover, host abundance, and island isolation.

3. Using a model selection approach within a database of more than 1200 individual fish hosts and their parasites from 11 islands within the Pacific Line Islands archipelago, we reveal that geographic gradients, including island area and island isolation, emerged as the best predictors of parasite abundance.

4. Life history moderated the relationship; parasites with complex life cycles increased in abundance with increasing island isolation, while parasites with direct life cycles decreased with increasing isolation. Direct life cycle parasites increased in abundance with increasing island area, though complex life cycle parasite abundance was not associated with island area.

5. This novel analysis of a unique dataset indicates that parasite abundance in marine systems cannot be predicted precisely without accounting for the independent and interactive effects of each parasite’s life history and environmental conditions.

1. 尽管寄生虫（parasite）在海洋生态系统（marine ecosystem）中无处不在，但由于多种相互作用的环境梯度与胁迫因子的影响尚未明确，预测海洋生态系统内寄生虫的丰度仍极具挑战性。此外，尽管寄生虫类群存在显著的多样性，过往研究常将其视为生态系统中无差异的统一类群。
2. 本研究旨在明确珊瑚礁生态系统（coral reef ecosystem）中多种寄生虫丰度预测因子的潜在重要性，涵盖珊瑚礁面积、岛屿面积、人类人口密度、叶绿素a（chlorophyll-a）、宿主多样性（host diversity）、珊瑚覆盖度（coral cover）、宿主丰度（host abundance）以及岛屿隔离度（island isolation）。
3. 本研究依托太平洋莱恩群岛（Pacific Line Islands archipelago）11座岛屿的1200余尾鱼类宿主个体及其对应寄生虫的数据库，采用模型选择（model selection）方法开展分析，结果显示岛屿面积、岛屿隔离度等地理梯度因子是预测寄生虫丰度的最优指标。
4. 生活史（life history）会调控该关联：具有复杂生命周期（complex life cycles）的寄生虫丰度随岛屿隔离度升高而增加，而具有直接生命周期（direct life cycles）的寄生虫丰度则随隔离度升高而降低。直接生命周期寄生虫的丰度随岛屿面积增大而升高，但复杂生命周期寄生虫的丰度与岛屿面积并无显著关联。
5. 本研究针对该独特数据集开展的创新性分析表明，若不考虑每种寄生虫的生活史与环境条件的独立及交互效应，则无法精准预测海洋系统中的寄生虫丰度。