Shaw Grace, Lilly Marie, Mai Vincent, Clark Jacoby, Summers Shannon, Slater Kimetha, Karpathy Sandor, Nakano Angie, Crews Arielle, Lawrence Alexandra, Salomon Jordan, Sambado Samantha Brianne, Swei Andrea
Department of Biology, San Francisco State University, Holloway Avenue, San Francisco, CA 1600, USA.
Department of Ecology, Evolution and Environmental Biology, Columbia University, Amsterdam Avenue, New York, NY 1200, USA.
R Soc Open Sci. 2024 Nov 6;11(11):240837. doi: 10.1098/rsos.240837. eCollection 2024 Nov.
Habitat loss and forest fragmentation are often linked to increased pathogen transmission, but the extent to which habitat isolation and landscape connectivity affect disease dynamics through movement of disease vectors and reservoir hosts has not been well examined. Tick-borne diseases are the most prevalent vector-borne diseases in the United States and on the West Coast, is one of the most epidemiologically important vectors. We investigated the impacts of habitat fragmentation on pathogens transmitted by and sought to disentangle the effects of wildlife communities and landscape metrics predictive of pathogen diversity, prevalence and distribution. We collected pathogen data for four co-occurring bacteria transmitted by and measured wildlife parameters. We also used spatial data and cost-distance analysis integrating expert opinions to assess landscape metrics of habitat fragmentation. We found that landscape metrics were significant predictors of tick density and pathogen prevalence. However, wildlife variables were essential when predicting the prevalence and distribution of pathogens reliant on wildlife reservoir hosts for maintenance. We found that landscape structure was an informative predictor of tick-borne pathogen richness in an urban matrix. Our work highlights the implications of large-scale land management on human disease risk.
栖息地丧失和森林破碎化往往与病原体传播增加有关,但栖息地隔离和景观连通性通过病媒和宿主的移动对疾病动态的影响程度尚未得到充分研究。蜱传疾病是美国最普遍的病媒传播疾病,在西海岸,蜱是流行病学上最重要的病媒之一。我们调查了栖息地破碎化对蜱传播病原体的影响,并试图厘清野生动物群落和预测病原体多样性、流行率及分布的景观指标的作用。我们收集了由蜱传播的四种共生细菌的病原体数据,并测量了野生动物参数。我们还利用空间数据和整合专家意见的成本距离分析来评估栖息地破碎化的景观指标。我们发现,景观指标是蜱密度和病原体流行率的重要预测因子。然而,在预测依赖野生动物宿主维持生存的病原体的流行率和分布时,野生动物变量至关重要。我们发现,景观结构是城市环境中蜱传病原体丰富度的有效预测因子。我们的研究突出了大规模土地管理对人类疾病风险的影响。