Macroimmunology: the drivers and consequences of spatial patterns in wildlife immune defense,Journal of Animal Ecology

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Macroimmunology: the drivers and consequences of spatial patterns in wildlife immune defense
Journal of Animal Ecology ( IF 3.5 ) Pub Date : 2020-04-01 , DOI: 10.1111/1365-2656.13166
Daniel J Becker _{1,

2} , Gregory F Albery ₃ , Maureen K Kessler ₄ , Tamika J Lunn ₅ , Caylee A Falvo ₆ , Gábor Á Czirják ₇ , Lynn B Martin ₈ , Raina K Plowright ₆

Affiliation

The prevalence and intensity of parasites in wild hosts varies across space and is a key determinant of infection risk in humans, domestic animals, and threatened wildlife. Because the immune system serves as the primary barrier to infection, replication, and transmission following exposure, we here consider the environmental drivers of immunity. Spatial variation in parasite pressure, abiotic and biotic conditions, and anthropogenic factors can all shape immunity across spatial scales. Identifying the most important spatial drivers of immunity could help preempt infectious disease risks, especially in the context of how large-scale factors such as urbanization affect defense by changing environmental conditions. We provide a synthesis of how to apply macroecological approaches to the study of ecoimmunology (i.e., macroimmunology). We first review spatial factors that could generate spatial variation in defense, highlighting the need for large-scale studies that can differentiate competing environmental predictors of immunity and detailing contexts where this approach might be favored over small-scale experimental studies. We next conduct a systematic review of the literature to assess the frequency of spatial studies and to classify them according to taxa, immune measures, spatial replication and extent, and statistical methods. We review 210 ecoimmunology studies sampling multiple host populations. We show that whereas spatial approaches are relatively common, spatial replication is generally low and unlikely to provide sufficient environmental variation or power to differentiate competing spatial hypotheses. We also highlight statistical biases in macroimmunology, in that few studies characterize and account for spatial dependence statistically, potentially affecting inferences for the relationships between environmental conditions and immune defense. We use these findings to describe tools from geostatistics and spatial modeling that can improve inference about the associations between environmental and immunological variation. In particular, we emphasize exploratory tools that can guide spatial sampling and highlight the need for greater use of mixed-effects models that account for spatial variability while also allowing researchers to account for both individual- and habitat-level covariates. We lastly discuss future research priorities for macroimmunology, including focusing on latitudinal gradients, range expansions, and urbanization as being especially amenable to large-scale spatial approaches. Methodologically, we highlight critical opportunities posed by assessing spatial variation in host tolerance, using metagenomics to quantify spatial variation in parasite pressure, coupling large-scale field studies with small-scale field experiments and longitudinal approaches, and applying statistical tools from macroecology and meta-analysis to identify generalizable spatial patterns. Such work will facilitate scaling ecoimmunology from individual- to habitat-level insights about the drivers of immune defense and help predict where environmental change may most alter infectious disease risk.

中文翻译：

宏观免疫学：野生动物免疫防御空间模式的驱动因素和后果

野生宿主中寄生虫的流行和强度因空间而异，是人类、家畜和受威胁野生动物感染风险的关键决定因素。因为免疫系统是暴露后感染、复制和传播的主要屏障，所以我们在这里考虑免疫的环境驱动因素。寄生虫压力、非生物和生物条件以及人为因素的空间变化都可以在空间尺度上形成免疫。确定免疫最重要的空间驱动因素有助于预防传染病风险，尤其是在城市化等大规模因素如何通过改变环境条件影响防御的背景下。我们综合介绍了如何将宏观生态学方法应用于生态免疫学（即宏观免疫学）研究。我们首先回顾了可能产生防御空间变化的空间因素，强调需要进行大规模研究，以区分竞争的免疫环境预测因子，并详细说明这种方法可能优于小规模实验研究的背景。接下来，我们对文献进行系统回顾，以评估空间研究的频率，并根据分类群、免疫措施、空间复制和范围以及统计方法对其进行分类。我们回顾了对多个宿主群体进行抽样的 210 项生态免疫学研究。我们表明，虽然空间方法相对普遍，但空间复制通常很低，不太可能提供足够的环境变化或能力来区分竞争的空间假设。我们还强调了宏观免疫学中的统计偏差，因为很少有研究从统计学上描述和解释空间依赖性，这可能会影响对环境条件和免疫防御之间关系的推断。我们使用这些发现来描述来自地质统计学和空间建模的工具，这些工具可以改进对环境和免疫变异之间关联的推断。特别是，我们强调可以指导空间采样的探索性工具，并强调需要更多地使用混合效应模型来解释空间变异性，同时还允许研究人员考虑个体和栖息地水平的协变量。我们最后讨论了宏观免疫学的未来研究重点，包括关注纬度梯度、范围扩展和城市化，因为它们特别适合大规模空间方法。在方法论上，我们强调了通过评估宿主耐受性的空间变化、使用宏基因组学来量化寄生虫压力的空间变化、将大规模田间研究与小规模田间实验和纵向方法相结合以及应用宏观生态学和元数据的统计工具所带来的关键机会。分析以识别可概括的空间模式。这样的工作将有助于将生态免疫学从个体层面扩展到栖息地层面的关于免疫防御驱动因素的见解，并有助于预测环境变化最可能改变传染病风险的地方。将大规模实地研究与小规模实地实验和纵向方法相结合，并应用宏观生态学和元分析的统计工具来确定可概括的空间模式。这样的工作将有助于将生态免疫学从个体层面扩展到栖息地层面的关于免疫防御驱动因素的见解，并有助于预测环境变化最可能改变传染病风险的地方。将大规模实地研究与小规模实地实验和纵向方法相结合，并应用宏观生态学和元分析的统计工具来确定可概括的空间模式。这样的工作将有助于将生态免疫学从个体层面扩展到栖息地层面的关于免疫防御驱动因素的见解，并有助于预测环境变化最可能改变传染病风险的地方。

更新日期：2020-04-01

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