Data from: Co-infections and environmental conditions drive the distributions of blood parasites in wild birds

Experimental work increasingly suggests that non-random pathogen associations can affect the spread or severity of disease. Yet due to difficulties distinguishing and interpreting co-infections, evidence for the presence and directionality of pathogen co-occurrences in wildlife is rudimentary. We provide empirical evidence for pathogen co-occurrences by analysing infection matrices for avian malaria (Haemoproteus and Plasmodium spp.) and parasitic filarial nematodes (microfilariae) in wild birds (New Caledonian Zosterops spp.). Using visual and genus-specific molecular parasite screening, we identified high levels of co-infections that would have been missed using PCR alone. Avian malaria lineages were assigned to species level using morphological descriptions. We estimated parasite co-occurrence probabilities, while accounting for environmental predictors, in a hierarchical multivariate logistic regression. Co-infections occurred in 36% of infected birds. We identified both positively and negatively correlated parasite co-occurrence probabilities when accounting for host, habitat and island effects. Two of three pairwise avian malaria co-occurrences were strongly negative, despite each malaria parasite occurring across all islands and habitats. Birds with microfilariae had elevated heterophil to lymphocyte ratios and were all co-infected with avian malaria, consistent with evidence that host immune modulation by parasitic nematodes facilitates malaria co-infections. Importantly, co-occurrence patterns with microfilariae varied in direction among avian malaria species; two malaria parasites correlated positively but a third correlated negatively with microfilariae. We show that wildlife co-infections are frequent, possibly affecting infection rates through competition or facilitation. We argue that combining multiple diagnostic screening methods with multivariate logistic regression offers a platform to disentangle impacts of environmental factors and parasite co-occurrences on wildlife disease.

越来越多的实验研究表明，非随机的病原体关联可影响疾病的传播与严重程度。然而，由于难以区分和阐释共感染现象，野生生物中病原体共现的存在性与方向性的相关证据仍较为匮乏。本研究通过分析野生鸟类（新喀里多尼亚绣眼鸟属（Zosterops）物种）的感染矩阵，针对禽疟（avian malaria，涵盖血变虫属（Haemoproteus）与疟原虫属（Plasmodium）物种）及寄生丝虫线虫（parasitic filarial nematodes，即微丝蚴（microfilariae））的病原体共现情况提供了实证依据。本研究结合目视检测与属特异性分子寄生虫筛查手段，发现了大量仅通过聚合酶链式反应（PCR）无法检出的共感染病例。研究团队通过形态学描述将禽疟谱系划分至物种层级，并采用分层多变量逻辑回归（hierarchical multivariate logistic regression）模型，在纳入环境预测因子的前提下估算了寄生虫共现概率。受感染鸟类中有36%存在共感染现象。在控制宿主、栖息地及岛屿效应的前提下，本研究发现了正相关与负相关两类寄生虫共现概率模式：尽管每种疟原虫均分布于所有岛屿及栖息地中，三对禽疟共现关系中有两对呈现出显著的负相关。携带微丝蚴的鸟类其异嗜性粒细胞与淋巴细胞比值（heterophil to lymphocyte ratios）升高，且全部合并感染了禽疟，这与“寄生线虫通过调节宿主免疫促进疟原虫共感染”的相关研究结论相符。值得注意的是，不同禽疟物种与微丝蚴的共现模式存在方向性差异：两种疟原虫与微丝蚴呈正相关，而第三种疟原虫则与其呈负相关。本研究证实野生生物共感染现象较为普遍，其可能通过竞争或易化作用影响感染率。本研究认为，将多种诊断筛查手段与多变量逻辑回归模型相结合，可为厘清环境因子与寄生虫共现对野生生物疾病的影响提供可行的研究框架。