首页> 外文期刊>The Journal of Applied Ecology >Missing the people for the trees:Identifying coupled natural– human system feedbacks driving the ecology of Lyme disease
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Missing the people for the trees:Identifying coupled natural– human system feedbacks driving the ecology of Lyme disease

机译:失踪的人树:识别耦合的自然-人工系统反馈开车莱姆病的生态

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1.Infectious diseases are rapidly emerging and many are increasing in incidence across the globe.Processes of land-use change,notably habitat loss and fragmentation,have been widely implicated in the emergence and spread of zoonoses such as Lyme disease,yet evidence remains equivocal.2.Here,we discuss and apply an innovative approach from the social sciences;instrumental variables,which seeks to tease out causality from observational data.Using this approach,we revisit the effect of forest fragmentation on Lyme disease incidence,focusing on human interaction with fragmented landscapes.Although human interaction with infected ticks is of clear and fundamental importance to human disease incidence,human activities that influence exposure have been largely overlooked in ecology literature.3.Using county-level land-use and Lyme disease incidence data for ~800 counties from the northeastern United States over the span of a decade,we illustrate (a) that human interaction with fragmented forest landscapes reliably predicts Lyme disease incidence,while ecological measures of forest fragmentation alone are unreliable predictors and (b) that identifying the effect of forest fragmentation on human disease entails addressing the feedback between Lyme disease risk and human decisions to avoid interaction with high-risk landscapes.4.Synthesis and applications.Our innovative approach and novel results help to clarify the equivocal literature on the effects of forest fragmentation on Lyme disease and illustrate the key role that human behaviour may be playing in the ecology of Lyme disease in North America.Accounting for human activity and behaviour in the ecology of disease more broadly may result in improved understanding of both the ecological drivers of disease,as well as actionable intervention strategies to reduce disease burden in a changing world.For example,our model results indicate that forest fragmentation by human settlement increases Lyme disease incidence,which has p
机译:1.许多人发病率的增加全球。栖息地的丧失和碎片,广泛涉及的出现和传播莱姆病等人畜共患病,但证据仍然equivocal.2。从社会创新的方法寻求科学;辅助变量从观测数据梳理出因果关系。这种方法,我们重温森林的影响碎片在莱姆病发病率,聚焦人机交互与分散风景。蜱虫是明确的和基本的重视人类疾病发病率、人类活动影响曝光在生态literature.3.Using,很大程度上被忽视了县级土地利用和莱姆病发病率数据从东北~ 800个县美国的十年间,我们人机交互的说明(a)支离破碎的森林景观可靠地预测莱姆病发病率,而生态措施的森林碎片是不可靠的预测和识别的影响(b)森林在人类疾病需要分裂解决莱姆病风险之间的反馈并避免与人类决策高风险landscapes.4。应用程序。结果有助于澄清模棱两可的文学在森林碎片在莱姆的影响疾病和说明人类的关键作用行为可能在莱姆的生态疾病在北美。活动和行为生态学的疾病更广泛的可能导致改进的理解的生态因素的疾病作为可行的干预策略来减少疾病负担在一个变化的世界。例子中,我们的模型结果表明,森林分裂的人类定居点增加莱姆疾病发病率,p

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