Meta-analysis of the effects of abiotic factors on plant microbes

The abiotic environment exerts strong effects on plant-associated microbes, shaping their interactions with plants and resulting ecosystem processes. However, these abiotic effects on plant-microbe interactions are often highly specific and contingent on the abiotic driver or microbial group, requiring synthesis work describing general patterns and from this generate hypotheses and guide mechanistic work. To address this, we conducted a meta-analysis of the effects of climate change-related abiotic factors, namely warming, drought, and eCO2, on plant-associated microbes distinguishing by microbial taxonomic or biological group (bacteria, fungi or virus) and the plant part where microbes are found or associated with (phyllosphere or rhizosphere). We found abiotic driver-specific patterns, whereby drought significantly reduced microbial abundance, whereas warming and eCO2 had no significant effects. In addition, these abiotic effects were contingent on the microbial taxonomic group, with fungi being negatively affected by drought but positively affected by warming (eCO2 enrichment had no effect), whereas bacteria and viruses were not significantly affected by any factor. Likewise, rhizopheric microbes were negatively affected by drought but positively affected by warming (eCO2 enrichment had no effect), whereas phyllospheric microbes were not significantly affected by any factor. Collectively, these findings point to important implications for global change research by highlighting contrasting effects of climate change-related abiotic drivers on plant-associated microbes and the contingency of such effects on microbe life histories and the nature of their interactions with plants.

Methods
Data collection

We carried out an extensive literature search in Scopus database in May 2022 using a combination of the following keywords: ((plant OR tree OR shrub) AND (drought OR warming OR co2 OR flooding OR wind OR salt OR salin OR deposit) AND (microb OR bacter OR fung OR virus OR protist OR alga OR nematod OR mycorrhiz)). We retained only articles, book chapters, reviews, theses, dissertations and abstracts published in English. To further limit the search to relevant papers, we filtered outputs to consider only the following research areas: Agricultural and Biological science, Biochemistry, Genetics and Molecular Biology, Environmental Science, Immunology and Microbiology. This search spanned published work from 1967 to 2022. In addition, we also surveyed the references in review articles on climate change and interactions between plants and microbes and included any studies that were missed in our Scopus search. In total, our initial search yielded 5450 papers.

To be included in our analysis, studies had to meet the following criteria: (a) provide a measure of plant-associated microbial abundance (e.g., amount, frequency, disease intensity, transmission rate, virus load) in the phyllosphere or rhizosphere of plants growing under experimental manipulation of climate change-related abiotic conditions (eCO2, warming, drought, etc.), and (b) report treatment level means (abiotic manipulation vs unmanipulated control), variability (i.e., variance, standard error or standard deviation), and the sample size in either the text, figures, tables or appendices. When needed, we extracted data from figures following digitalization using WebPlotDigitizer software. We excluded studies that applied two or more different abiotic manipulations together on the same plants. After applying these criteria, the resulting dataset consisted of 513 case studies from 96 studies (out of the original 5450) from the primary literature published between 1975 and 2021 in 47 scientific journals. Study cases represented data points, i.e., treatment vs. control comparisons, drawn from a single primary study, where a single study may have one or more study cases. The occurrence of more than one study case in a given study took place when more than one response was measured and/or more than one abiotic treatment was tested (against a control), in which case the number of study cases in a given study equaled the number of responses by the number of treatment level vs. control comparisons. We used different approaches to account for both sources of non-independence in our analyses and assessed the robustness of our conclusions to the inclusion of multiple study cases per primary study.

For each study case, we compiled the following moderators: plant species and growth form (herbaceous or woody), experimental conditions (field or controlled, i.e., greenhouse or laboratory), climate change-related abiotic factors (warming, drought, eCO2), microbial taxonomical group (i.e., bacteria, fungus, or virus), and the plant part where microbes were found (phyllosphere or rhizosphere).