A phylogenetically diverse array of fungi live within healthy leaf tissue of dicotyledonous plants. Many studies have examined these endophytes within a single plant species and/or at small spatial scales, but landscape‐scale variables that determine their community composition are not well understood, either across geographic space, across climatic conditions, or in the context of host plant phylogeny. Here, we evaluate the contributions of these variables to endophyte beta diversity using a survey of foliar endophytic fungi in native Hawaiian dicots sampled across the Hawaiian archipelago. We used Illumina technology to sequence fungal ITS1 amplicons to characterize foliar endophyte communities across five islands and 80 host plant genera. We found that communities of foliar endophytic fungi showed strong geographic structuring between distances of 7 and 36 km. Endophyte community structure was most strongly associated with host plant phylogeny and evapotranspiration, and was also significantly associated with NDVI, elevation and solar radiation. Additionally, our bipartite network analysis revealed that the five islands we sampled each harboured significantly specialized endophyte communities. These results demonstrate how the interaction of factors at large and small spatial and phylogenetic scales shapes fungal symbiont communities.
Foliar fungi – pathogens, endophytes, epiphytes – form taxonomically diverse communities that affect plant health and productivity. The composition of foliar fungal communities is variable at spatial scales both small (e.g. individual plants) and large (e.g. continents), yet few studies have attempted to tease apart spatial from climatic factors influencing these communities. Moreover, few studies have sampled in more than 1 year to gauge interannual variation in community structure.
The Pacific Northwest of western North America.
Foliar fungi associated with the deciduous tree
In two consecutive years, we used DNA metabarcoding to characterize foliar fungal communities of
In both study years, we found that foliar fungal community composition varied among sites and between regions (east vs. west of the Cascades). We found that climate explained more variation in community composition than geographic distance, although the majority of variation explained by each was shared. We also found that interannual variation in community composition depended on environmental context: communities located in the dry, eastern portion of the tree's geographic range varied more between study years than those located in the wet, western portion of the tree's range.
Our results suggest that the environment plays a greater role in structuring foliar fungal communities than dispersal limitation.
- NSF-PAR ID:
- Publisher / Repository:
- Date Published:
- Journal Name:
- Journal of Biogeography
- Page Range / eLocation ID:
- p. 2001-2011
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Roots and rhizospheres host diverse microbial communities that can influence the fitness, phenotypes, and environmental tolerances of plants. Documenting the biogeography of these microbiomes can detect the potential for a changing environment to disrupt host‐microbe interactions, particularly in cases where microbes buffer hosts against abiotic stressors. We evaluated whether root‐associated fungi had poleward declines in diversity, tested whether fungal communities in roots shifted near host plant range edges, and determined the relative importance of environmental and host predictors of root fungal community structure.
North American plains grasslands.
Foundation grasses –
Andropogon gerardii, Bouteloua dactyloides, B. eriopoda, B. gracilis,and Schizachyrium scopariumand root fungi. Methods
At each of 24 sites representing three replicate 17°–latitudinal gradients, we collected roots from 12 individuals per species along five transects spaced 10 m apart (40 m × 40 m grid). We used next‐generation sequencing of ITS2, direct fungal culturing from roots, and microscopy to survey fungi associated with grass roots.
Root‐associated fungi did not follow the poleward declines in diversity documented for many animals and plants. Instead, host plant identity had the largest influence on fungal community structure. Edaphic factors outranked climate or host plant traits as correlates of fungal community structure; however, the relative importance of environmental predictors differed among plant species. As sampling approached host species range edges, fungal composition converged in similarity among individual plants of each grass species.
Environmental predictors of root‐associated fungi depended strongly on host plant species identity. Biogeographic patterns in fungal composition suggested a homogenizing influence of stressors at host plant range limits. Results predict that communities of non‐mycorrhizal, root‐associated fungi in the North American plains will be more sensitive to future changes in host plant ranges and edaphic factors than to the direct effects of climate.
Efforts to predict the responses of soil fungal communities to climate change are hindered by limited information on how fungal niches are distributed across environmental hyperspace. We predict the climate sensitivity of North American soil fungal assemblage composition by modelling the ecological niches of several thousand fungal species.
One hundred and thirteen sites in the United States and Canada spanning all biomes except tropical rain forest.
Major Taxa Studied
We combine internal transcribed spacer (ITS) sequences from two continental‐scale sampling networks in North America and cluster them into operational taxonomic units (OTUs) at 97% similarity. Using climate and soil data, we fit ecological niche models (ENMs) based on logistic ridge regression for all OTUs present in at least 10 sites (
n= 8597). To describe the compositional turnover of soil fungal assemblages over climatic gradients, we introduce a novel niche‐based metric of climate sensitivity, the Sørensen climate sensitivity index. Finally, we map climate sensitivity across North America. Results
ENMs have a mean out‐of‐sample predictive accuracy of 73.8%, with temperature variables being strong predictors of fungal distributions. Soil fungal climate niches clump together across environmental space, which suggests common physiological limits and predicts abrupt changes in composition with respect to changes in climate. Soil fungi in North American climates are more likely to be limited by cold and dry conditions than by warm and wet conditions, and ectomycorrhizal fungi generally tolerate colder temperatures than saprotrophic fungi. Sørensen climate sensitivity exhibits a multimodal distribution across environmental space, with a peak in climates corresponding to boreal forests.
The boreal forest occupies an especially precarious region of environmental space for the composition of soil fungal assemblages in North America, as even small degrees of warming could trigger large compositional changes characterized mainly by an influx of warm‐adapted species.
Understanding the factors that influence microbes’ environmental distributions is important for determining drivers of microbial community composition. These include environmental variables like temperature and pH, and higher-dimensional variables like geographic distance and host species phylogeny. In microbial ecology, “specificity” is often described in the context of symbiotic or host parasitic interactions, but specificity can be more broadly used to describe the extent to which a species occupies a narrower range of an environmental variable than expected by chance. Using a standardization we describe here, Rao’s (Theor Popul Biol, 1982. https://doi.org/10.1016/0040-5809(82)90004-1, Sankhya A, 2010. https://doi.org/10.1007/s13171-010-0016-3 ) Quadratic Entropy can be conveniently applied to calculate specificity of a feature, such as a species, to many different environmental variables.
We present our R package
specificityfor performing the above analyses, and apply it to four real-life microbial data sets to demonstrate its application. We found that many fungi within the leaves of native Hawaiian plants had strong specificity to rainfall and elevation, even though these variables showed minimal importance in a previous analysis of fungal beta-diversity. In Antarctic cryoconite holes, our tool revealed that many bacteria have specificity to co-occurring algal community composition. Similarly, in the human gut microbiome, many bacteria showed specificity to the composition of bile acids. Finally, our analysis of the Earth Microbiome Project data set showed that most bacteria show strong ontological specificity to sample type. Our software performed as expected on synthetic data as well. Conclusions specificityis well-suited to analysis of microbiome data, both in synthetic test cases, and across multiple environment types and experimental designs. The analysis and software we present here can reveal patterns in microbial taxa that may not be evident from a community-level perspective. These insights can also be visualized and interactively shared among researchers using specificity’s companion package, specificity.shiny.
Patterns of genetic diversity within species’ ranges can reveal important insights into effects of past climate on species’ biogeography and current population dynamics. While numerous biogeographic hypotheses have been proposed to explain patterns of genetic diversity within species’ ranges, formal comparisons and rigorous statistical tests of these hypotheses remain rare. Here, we compared seven hypotheses for their abilities to describe the geographic pattern of two metrics of genetic diversity in balsam poplar (
Populus balsamifera), a northern North American tree species. Location
Balsam poplar (
Populus balsamiferaL.). Methods
We compared seven hypotheses, representing effects of past climate and current range position, for their ability to describe the geographic pattern of expected heterozygosity and per cent polymorphic loci across 85 populations of balsam poplar. We tested each hypothesis using spatial and non‐spatial least‐squares regression to assess the importance of spatial autocorrelation on model performance.
We found that both expected heterozygosity and per cent polymorphic loci could best be explained by the current range position and genetic structure of populations within the contemporary range. Genetic diversity showed a clear gradient of being highest near the geographic and climatic range centre and lowest near range edges. Hypotheses accounting for the effects of past climate (e.g. past climatic suitability, distance from the southern edge), in contrast, had comparatively little support. Model ranks were similar among spatial and non‐spatial models, but residuals of all non‐spatial models were significantly autocorrelated, violating the assumption of independence in least‐squares regression.
Our work adds strong support for the “Central‐Periphery Hypothesis” as providing a predictive framework for understanding the forces structuring genetic diversity across species’ ranges, and illustrates the value of applying a robust comparative model selection framework and accounting for spatial autocorrelation when comparing biogeographic models of genetic diversity.