Abstract Hybridization between organisms from evolutionarily distinct lineages can have profound consequences on organismal ecology, with cascading effects on fitness and evolution. Most studies of hybrid organisms have focused on organismal traits, for example, various aspects of morphology and physiology. However, with the recent emergence of holobiont theory, there has been growing interest in understanding how hybridization impacts and is impacted by host‐associated microbiomes. Better understanding of the interplay between host hybridization and host‐associated microbiomes has the potential to provide insight into both the roles of host‐associated microbiomes as dictators of host performance as well as the fundamental rules governing host‐associated microbiome assembly. Unfortunately, there is a current lack of frameworks for understanding the structure of host‐associated microbiomes of hybrid organisms.In this paper, we develop four conceptual models describing possible relationships between the host‐associated microbiomes of hybrids and their progenitor or ‘parent’ taxa. We then integrate these models into a quantitative ‘4H index’ and present a new R package for calculation, visualization and analysis of this index.We demonstrate how the 4H index can be used to compare hybrid microbiomes across disparate plant and animal systems. Our analyses of these data sets show variation in the 4H index across systems based on host taxonomy, host site and microbial taxonomic group.Our four conceptual models, paired with our 4H index and associated visualization tools, facilitate comparison across hybrid systems. This, in turn, allows for systematic exploration of how different aspects of host hybridization impact the host‐associated microbiomes of hybrid organisms.
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Active learning for regression of structure–property mapping: the importance of sampling and representation
We develop an active workflow for calibrating microstructure–property relationships when a large dataset of microstructures is available, but the cost associated with evaluating the properties associated is high.
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- Award ID(s):
- 2027105
- PAR ID:
- 10591194
- Publisher / Repository:
- Royal Society of Chemistry
- Date Published:
- Journal Name:
- Digital Discovery
- Volume:
- 3
- Issue:
- 10
- ISSN:
- 2635-098X
- Page Range / eLocation ID:
- 1997 to 2009
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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