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  • 标题:Rekindling old friendships in new landscapes: The environment–microbiome–health axis in the realms of landscape research
  • 本地全文:下载
  • 作者:Jake M. Robinson ; Anna Jorgensen
  • 期刊名称:People and Nature
  • 电子版ISSN:2575-8314
  • 出版年度:2020
  • 卷号:2
  • 期号:2
  • 页码:339-349
  • DOI:10.1002/pan3.10082
  • 出版社:Wiley
  • 摘要:1. Humans are spending less time in biodiverse environments, and according to the Old Friends and Biodiversity hypotheses, this has led to fewer interactions with diverse immunoregulatory micro-organisms or ‘old friends’. 2. Non-communicable diseases such as asthma and inflammatory bowel disease are on the rise, and the development and progression of these ‘modern’ diseases may be attributed in part, to the breakdown of this evolutionary relationship between humans and environmental microbiota. 3. There is a growing interest in the environment–microbiome–health axis as a mechanism to explain some of the health benefits linked to spending time in nature. 4. This may provide a platform for proposing a new, holistic and transdisciplinary approach to public and environmental health. 5. The field of landscape research—which combines social and natural sciences— responds to emerging socioecological issues and can make a significant contribution towards this approach. 6. This paper explores innovative, landscape research-based approaches to understanding the complex relationships between the environment, the microbiome and human health. 7. Transdisciplinarity will play an important role moving forward. This forms a major discussion point in this paper, along with future research directions, key research questions and novel concepts supported by recent technological advancements. 8. The development of a new field of study—Microbioscape Research as a crossover between microbiome science and landscape research—is also discussed.
  • 关键词:biodiversity hypothesis; environmental microbiome; greenspace; landscape research; microbiome; microbiome-inspired green infrastructure; non-communicable disease; Old Friends hypothesis
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