Abstract：
Spatial variation in parasitic infection may have many physical and biological drivers. Uncovering these drivers may be especially important for parasites of ecosystem engineers because the engineers are foundational to their communities. Oysters are an important coastal ecosystem engineer that have declined drastically worldwide, in part due to enhanced cases of lethal oyster diseases, such as Dermo and MSX, caused by the protozoan parasites Perkinsus marinus and Haplosporidium nelsoni, respectively. Besides water quality and hydrodynamics, there is little information on how other variables influence the prevalence and intensity of these pathogens in oysters across a regional scale. To examine drivers of spatial variation in these oyster parasites-including host size, local reef properties, and landscape properties-we sampled 24 reefs systematically spread along the coast of Georgia, USA. Across sites, we found universally high prevalence of oysters with at least one of these parasites (91.02% ± 8.89, mean ± SD). Not only are high levels of parasite prevalence potentially problematic for a pivotal ecosystem engineer, but also low spatial variability may limit the explanatory power of variables across a regional scale. Our statistical models explained between 18 and 42% of the variation in spatial patterns of prevalence and intensity of these microparasites. Interestingly, landscape context was a positive predictor of P. marinus, but a negative predictor of H. nelsoni. Overall, our findings suggest that factors driving parasite prevalence and intensity operate across multiple spatial scales, and the same factor can both facilitate and hinder different parasites within the same host species.
摘要：
寄生虫感染的空间变化可能具有许多物理和生物驱动因素。发现这些驱动因素对于生态系统工程师的寄生虫尤其重要，因为工程师是他们社区的基础。牡蛎是一个重要的沿海生态系统工程师，在全球范围内急剧下降，部分原因是致命牡蛎病的病例增加，比如Dermo和MSX，由原生动物寄生虫Perkinsusmarinus和Laplosporidiumnelsoni引起，分别。除了水质和流体动力学，关于其他变量如何在区域范围内影响牡蛎中这些病原体的患病率和强度的信息很少。为了检查这些牡蛎寄生虫空间变异的驱动因素，包括宿主大小，当地的珊瑚礁属性，和景观属性——我们采样了24个系统地分布在佐治亚州海岸的珊瑚礁，美国。跨站点,我们发现至少有一种寄生虫的牡蛎患病率普遍很高(91.02%±8.89,平均值±SD).对于一个关键的生态系统工程师来说，高水平的寄生虫流行不仅是潜在的问题，而且低空间变异性可能会限制变量在区域范围内的解释能力。我们的统计模型解释了这些微寄生虫的患病率和强度的空间格局变化的18％至42％。有趣的是,景观环境是P.marinus的积极预测因子，而是H.Nelsoni的负面预测因子.总的来说,我们的研究结果表明，驱动寄生虫患病率和强度的因素在多个空间尺度上运作，相同的因素可以促进和阻碍同一宿主物种中的不同寄生虫。
