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Record W7011093456

Life in the leaves: diversity and distribution of foliar fungal endophytes

2022· other· en· W7011093456 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship (California Digital Library) · 2022
Typeother
Languageen
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsnot available
Fundersnot available
KeywordsSpecies richnessEndophyteTemperate climateLatitudeSpecies diversityBiodiversityBiogeographySymbiosis
DOInot available

Abstract

fetched live from OpenAlex

Understanding why species vary from place to place is a long-standing question in biogeography and ecology. To answer this, biologists have proposed “rules” to explain patterns of species diversity and distribution in plants and animals. Yet whether microbes play by the same set of rules as macroorganisms requires further investigation. In this dissertation, I tested whether biogeographic and community assembly rules could predict the diversity and distribution of foliar fungal endophytes (fungi that live inside plant leaves) across spatial and host scales. In Chapter 1, I tested whether endophytes displayed a latitudinal diversity gradient, a biogeographic pattern where species richness increases towards the equator, across a 55-degree latitudinal gradient from Alaska to Panama. I found that endophyte species richness (alpha diversity) generally increased towards the equator but varied bimodally as a function of latitude. Endophyte richness was greatest in Panama and was also pronounced, to lesser degree, in Canada and Oregon, where plant communities received high annual precipitation, experienced low precipitation seasonality, and had high photosynthetic biomass. On the other hand, endophyte richness was lowest in California, where plant communities received low annual precipitation, experienced high precipitation seasonality, and had low photosynthetic biomass. This suggests endophytes responded to a suite of factors that were not necessarily correlated with latitude and this shaped their bimodal pattern of richness across latitude. \nWhile endophyte alpha diversity increased towards the tropics, differences in endophyte species composition (beta diversity) among host species increased towards temperate regions. Additionally, endophytes in temperate plant communities occupied a lower proportion of their host communities, or had greater host specificity, than endophytes in sub-tropical and tropical plant communities. Beta diversity and host specificity were correlated and suggest that greater compositional dissimilarity among endophyte communities was driven by endophytes that were host-specific. \nI propose that host specificity is a major driver of contrasting patterns in endophyte alpha and beta diversity as a function of latitude. I hypothesize that species-rich host communities are heterogenous landscapes for endophytes and barriers to the evolution of host specificity because specialist endophytes cannot reliably colonize compatible hosts via passive dispersal. Therefore, species-rich host communities in the tropics should select for host generalism while temperate communities with fewer host species should select for host specificity, driving patterns of latitudinal beta diversity. I also hypothesize that because host specialists are adapted to their host’s chemistry or physiology, they competitively exclude other endophytes and reduce endophyte richness in hosts. Alternatively, host generalism may come at the cost of competitively ability and facilitates greater coexistence among endophytes. This allows hosts to accumulate endophyte species and shapes patterns of latitudinal alpha diversity. \nFindings from Chapter 1 indicate that host communities can determine the community composition of endophytes. I expanded upon this in Chapter 2 by reviewing different ways endophytes can vary in their specificity among host species depending on host sampling, host phylogenetic, and host spatial scale. I then explored the methodological effect of rare endophytes on metrics of host specificity because their low sequencing abundance is often correlated with high host specificity. I found that removing rare endophytes from the community made observed measures of host specificity indistinguishable from values expected by random community assembly. Thus, their inclusion can be important in detecting non-random community structure. Yet how rare endophytes could be fairly compared to their more abundant counterparts was still a remaining challenge. \nI addressed this in Chapter 3 by developing a method that allows one to consider the host specificity of rare endophytes while reducing the bias caused by their low sequencing abundances. I used this method to test whether two community assembly rules for host-associated microbial communities, the common host hypothesis (the effect of host abundance) or phylosymbiosis (the effect of host evolutionary history), could explain variation in endophyte distributions in a single plant community. I found that more abundant plant species harbored endophytes that were more host-specific. These endophytes occupied fewer plant species and were consistently found in the same plant species across the landscape, supportive of my hypothesis in Chapter 1 that low host density can be a barrier to the evolution of host-specific interactions. Host phylogenetic distance was not predictive of host specificity. \nIn the conclusion of this dissertation, I frame patterns of endophyte host specificity in Chapter 3 in the context of the latitudinal survey in Chapter 1. I discuss why host-specific interactions may explain contrasting patterns of endophyte alpha and beta diversity as a function of latitude and how studies that extrapolate global fungal biodiversity can better incorporate fungal biogeography and ecology into their estimates.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.055
GPT teacher head0.287
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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