Centro de Biotecnología y Genómica de Plantas UPM-INIA and Escuela Técnica Superior de Ingeniería Agronómica, Agroambiental y de Biosistemas (ETSIAAB), Universidad Politécnica de Madrid, Campus de Montegancedo, Pozuelo de Alarcón, Madrid 28223, Spain.
Centro de Biotecnología y Genómica de Plantas UPM-INIA and Escuela Técnica Superior de Ingeniería Agronómica, Agroambiental y de Biosistemas (ETSIAAB), Universidad Politécnica de Madrid, Campus de Montegancedo, Pozuelo de Alarcón, Madrid 28223, Spain
Proc Biol Sci. 2017 Dec 20;284(1869). doi: 10.1098/rspb.2017.2066.
Processes that generate the distribution of pathogens and their interactions with hosts are not insensitive to changes in spatial scale. Spatial scales and species traits are often selected intentionally, based on practical considerations, ignoring biases that the scale and type of observation may introduce. Specifically, these biases might change the interpretation of disease-diversity relationships that are reported as either 'dilution' or 'amplification' effects. Here, we combine field data of a host-pathogen community with empirical models to test the effects that (i) spatial scale and (ii) host range have on the relationship between plant-virus infection prevalence and diversity. We show that prevalence-diversity relationships are scale-dependent and can produce opposite effects associated with different habitats at sub-ecosystem scales. The total number of host species of each virus reflected generalism at the ecosystem scale. However, plasticity in host range resembled habitat-specific specialization and also changed model predictions. We show that habitat heterogeneity, ignored at larger (ecosystem) spatial scales, influences pathogen distributions. Hence, understanding disease distributions and the evolution of pathogens requires reconciling specific hypotheses of the study with an appropriate spatial scale, or scales, and consideration of traits, such as host range, that might strongly contribute to biotic interactions.
产生病原体分布及其与宿主相互作用的过程对空间尺度的变化并非不敏感。空间尺度和物种特征通常是根据实际考虑有意选择的,忽略了观察的尺度和类型可能引入的偏差。具体来说,这些偏差可能会改变报告为“稀释”或“放大”效应的疾病多样性关系的解释。在这里,我们将宿主-病原体群落的实地数据与经验模型相结合,以测试(i)空间尺度和(ii)宿主范围对植物-病毒感染流行率与多样性之间关系的影响。我们表明,流行率-多样性关系是尺度依赖的,并可能在亚生态系统尺度上与不同生境产生相反的影响。每种病毒的宿主物种总数反映了生态系统尺度上的一般性。然而,宿主范围的可塑性类似于特定栖息地的专业化,也改变了模型预测。我们表明,忽略了更大(生态系统)空间尺度的栖息地异质性会影响病原体的分布。因此,要了解疾病的分布和病原体的进化,需要将研究的具体假设与适当的空间尺度或尺度协调起来,并考虑到可能强烈影响生物相互作用的宿主范围等特征。