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Rising to meet global, interconnected challenges, such as food security and ecosystem resilience to global change, requires insights from across the Earth. This is especially true for belowground terrestrial ecological processes. Soil ecologists have answered this call: like mushrooms, large global datasets and databases on soil physics, chemistry and ecology are sprouting up everywhere (e.g. Fine‐Root Ecology Database (Iversen et al., 2018), FunFun (Zanne et al., 2020), GlobalFungi (Větrovský et al., 2020), COntinuous SOil REspiration (Jian et al., 2020), Global distribution of earthworm diversity (Philips et al., 2019) etc.). It is now time to leverage synergies among these datasets to link the continuum of belowground processes to ecosystem functions (e.g. decomposition, nutrient cycling and soil respiration). Built on interdisciplinary and international collaborations, data synthesis that leads to a holistic understanding is one of the best ways of predicting the future of terrestrial ecosystems and for preserving ecosystem services under global change. In 2020, global interconnectedness was on display as we saw a pandemic sweep across the world in weeks. The pandemic allowed the Ecological Society of America (ESA) to enter a new digital era by holding a fully virtual conference. While technology cannot yet replicate all aspects of an in‐person conference, the virtual platform increased accessibility and reduced the climate impact of the annual conference. It also provided an opportunity for early‐career plant and microbial ecologists from five ESA Organized Oral Sessions and one Inspire Session to organize Ecology Underground, a two‐day program of live virtual talks and open discussions on integrative belowground ecology on 4 and 5 August 2020. Ecology Underground was sponsored by New Phytologist, the ESA Soil Ecology Section, the US Department of Energy, Biological and Environmental Research program and the Oak Ridge Institute for Science and Education (ORISE), and gathered 453 participants over two days. The online platform allowed for participation across the globe (37 countries were represented; Fig. 1) and was an opportunity to think creatively about how scientific discussions and global collaborations can take place, now and in the future. Open in a separate window Fig. 1 The online platform of Ecology Underground allowed for participation across the globe.

Fungi are mediators of the nitrogen and carbon cycles in terrestrial ecosystems. Examining how nitrogen uptake and organic matter decomposition potential differs in fungi can provide insight into the underlying mechanisms driving fungal ecological processes and ecosystem functioning. In this study, we assessed the frequency of genes encoding for specific enzymes that facilitate nitrogen uptake and organic matter decomposition in 879 fungal genomes with fungal taxa grouped into trait-based categories. Our linked gene-trait data approach revealed that gene frequencies vary across and within trait-based groups and that trait-based categories differ in trait space. We present two examples of how this linked gene-trait approach can be used to address ecological questions. First, we show that this type of approach can help us better understand, and potentially predict, how fungi will respond to environmental stress. Specifically, we found that trait-based categories with high nitrogen uptake gene frequency increased in relative abundance when exposed to high soil nitrogen enrichment. Second, by comparing frequencies of nitrogen uptake and organic matter decomposition genes, we found that most ectomycorrhizal fungi in our dataset have similar gene frequencies to brown rot fungi. This demonstrates that gene-trait data approaches can shed light on potential evolutionary trajectories of life history traits in fungi. We present a framework for exploring nitrogen uptake and organic matter decomposition gene frequencies in fungal trait-based groups and provide two concise examples on how to use our framework to address ecological questions from a mechanistic perspective. Supplementary Information The online version contains supplementary material available at 10.1007/s00248-021-01687-x.

Humans are inextricably linked to each other and our natural world, and microorganisms lie at the nexus of those interactions. Microorganisms form genetically flexible, taxonomically diverse, and biochemically rich communities, i.e., microbiomes that are integral to the health and development of macroorganisms, societies, and ecosystems. Yet engagement with beneficial microbiomes is dictated by access to public resources, such as nutritious food, clean water and air, safe shelter, social interactions, and effective medicine. In this way, microbiomes have sociopolitical contexts that must be considered. The Microbes and Social Equity (MSE) Working Group connects microbiology with social equity research, education, policy, and practice to understand the interplay of microorganisms, individuals, societies, and ecosystems. Here, we outline opportunities for integrating microbiology and social equity work through broadening education and training; diversifying research topics, methods, and perspectives; and advocating for evidence-based public policy that supports sustainable, equitable, and microbial wealth for all.

To make predictions about the carbon cycling consequences of rising global surface temperatures, Earth system scientists rely on mathematical soil biogeochemical models (SBMs). However, it is not clear which models have better predictive accuracy, and a rigorous quantitative approach for comparing and validating the predictions has yet to be established. In this study, we present a Bayesian approach to SBM comparison that can be incorporated into a statistical model selection framework. We compared the fits of linear and nonlinear SBMs to soil respiration data compiled in a recent meta-analysis of soil warming field experiments. Fit quality was quantified using Bayesian goodness-of-fit metrics, including the widely applicable information criterion (WAIC) and leave-one-out cross validation (LOO). We found that the linear model generally outperformed the nonlinear model at fitting the meta-analysis data set. Both WAIC and LOO computed higher overfitting risk and effective numbers of parameters for the nonlinear model compared to the linear model, conditional on the data set. Goodness of fit for both models generally improved when they were initialized with lower and more realistic steady-state soil organic carbon densities. Still, testing whether linear models offer definitively superior predictive performance over nonlinear models on a global scale will require comparisons with additional site-specific data sets of suitable size and dimensionality. Such comparisons can build upon the approach defined in this study to make more rigorous statistical determinations about model accuracy while leveraging emerging data sets, such as those from long-term ecological research experiments.

The magnitude and direction of carbon cycle feedbacks under climate warming remain uncertain due to insufficient knowledge about the temperature sensitivities of soil microbial processes. Enzymatic rates could increase at higher temperatures, but this response could change over time if soil microbes adapt to warming. We used the Arrhenius relationship, biochemical transition state theory, and thermal physiology theory to predict the responses of extracellular enzyme Vmax and Km to temperature. Based on these concepts, we hypothesized that Vmax and Km would correlate positively with each other and show positive temperature sensitivities. For enzymes from warmer environments, we expected to find lower Vmax , Km , and Km temperature sensitivity but higher Vmax temperature sensitivity. We tested these hypotheses with isolates of the filamentous fungus Neurospora discreta collected from around the globe and with decomposing leaf litter from a warming experiment in Alaskan boreal forest. For Neurospora extracellular enzymes, Vmax Q10 ranged from 1.48 to 2.25, and Km Q10 ranged from 0.71 to 2.80. In agreement with theory, Vmax and Km were positively correlated for some enzymes, and Vmax declined under experimental warming in Alaskan litter. However, the temperature sensitivities of Vmax and Km did not vary as expected with warming. We also found no relationship between temperature sensitivity of Vmax or Km and mean annual temperature of the isolation site for Neurospora strains. Declining Vmax in the Alaskan warming treatment implies a short-term negative feedback to climate change, but the Neurospora results suggest that climate-driven changes in plant inputs and soil properties are important controls on enzyme kinetics in the long term. Our empirical data on enzyme Vmax , Km , and temperature sensitivities should be useful for parameterizing existing biogeochemical models, but they reveal a need to develop new theory on thermal adaptation mechanisms.

“This paper requires significant editing, as it is not written in sound English and cannot be accepted in its current form.” “This sentence does not make any sense.” “The authors need a native English-speaking co-author to thoroughly revise the grammar of this manuscript.” My heart sank when I received this feedback from a reviewer for the first paper I had ever submitted as a first author. The reviewer didn't say a thing about the underlying science—but isn't that what peer review is supposed to evaluate? Regardless, the reviewer recommended that our manuscript be rejected. This happened about 10 years ago. But as a nonnative English speaker who needs to publish in English, I still think about the experience today. ![][1] ILLUSTRATION: ROBERT NEUBECKER > “You are not a martyr or the savior of people who did not grow up speaking English.” I expected my paper to fare well. I knew the science was strong. I had the resources and backup data to make whatever scientific changes the reviewers suggested. I also knew that my English skills weren't great. But I had a native English-speaking co-author and an adviser who was proficient in English, and they both thoroughly revised the manuscript. When I received those comments from the reviewer, I was crushed. I felt our work wasn't being judged fairly. Had the reviewer assumed that, because my co-authors and I were all affiliated with the same Mexican research institute, none of us was proficient in English? My co-author told me I shouldn't take the comments personally, and that they did not reflect on the quality of my work, but that didn't make me feel any better. How could I succeed in academia if I could not manage to publish a paper in English? Luckily, the other two reviewers made useful suggestions about the science, and the editor invited us to submit a revised version. I modified the science based on the helpful reviewers' feedback and made the grammar and style corrections demanded by the rude reviewer, and my first first-author paper was accepted. Since then, no reviewers have had a problem with my English—maybe because I moved to the United States and started publishing with co-authors who have American-sounding names. I also put a lot of work into improving my language skills, including participating in writing workshops and reading books about writing in English. But many of my colleagues in Mexico tell me stories of dealing with reviewers who are harsh and patronizing about their English. And I know that other researchers around the world experience similar insults. Reviewers, you don't need to be rude. Here are three principles for providing constructive reviews, even when you think an article is poorly written. First and foremost, do not make assumptions about the quality of a paper based on the authors' names and affiliations. This form of bias is rooted in racism. Second, you are a reviewer—not an editor. Focus on the research. If the English is so poor you cannot review the paper or provide feedback on the science, tell the editor so that they can decide how to proceed. Third, if the paper is not written in sound English, it is OK to correct grammatical errors and help improve the writing. But remember that you are not a martyr or the savior of people who did not grow up speaking English. Be kind. For example, you can write, “I cannot understand what the authors are trying to communicate here.” You can also suggest editing help from someone with “full professional proficiency in English.” Don't demand “a native English speaker”; that is not synonymous with being a good writer. As reviewers, we help ensure that high-quality science gets published. We can—and should—do this without forgetting that behind every paper are people who worked hard to put together a manuscript reporting their cherished research. As scientists, we know that writing is hard. Keep in mind that writing in a second language is even harder. [1]: /embed/graphic-1.gif

Earth's temperature is rising, and with this increase, fungal communities are responding and affecting soil carbon processes. At a long-term soil-warming experiment in a boreal forest in interior Alaska, warming and warming-associated drying alters the function of microbes, and thus, decomposition of carbon. But what genetic mechanisms and resource allocation strategies are behind these community shifts and soil carbon changes? Here, we evaluate fungal resource allocation efforts under long-term experimental warming (including associated drying) using soil metatranscriptomics. We profiled resource allocation efforts toward decomposition and cell metabolic maintenance, and we characterized community composition. We found that under the warming treatment, fungi allocate resources to cell metabolic maintenance at the expense of allocating resources to decomposition. In addition, we found that fungal orders that house taxa with stress-tolerant traits were more abundant under the warmed treatment compared to control conditions. Our results suggest that the warming treatment elicits an ecological tradeoff in resource allocation in the fungal communities, with potential to change ecosystem-scale carbon dynamics. Fungi preferentially invest in mechanisms that will ensure survival under warming and drying, such as cell metabolic maintenance, rather than in decomposition. Through metatranscriptomes, we provide mechanistic insight behind the response of fungi to climate change and consequences to soil carbon processes.

Soil microbes are key regulators of Earth's biogeochemical cycles, and their growth, turnover, and efficiency are important controls of organic matter decay and soil carbon (C) storage. A central roadblock to scaling microbial activity is explaining the incongruence between long- and short-term warming responses. In addition to the well-described kinetics which dominate the short-term warming response, the long-term response is also subject to indirect effects, such as substrate availability, soil moisture, and shifts in plant community composition, that influence microbial activity and community dynamics. Here we discuss possible mechanisms of this attenuation, synthesized in the context of five testable hypotheses, presented in order of decreasing current empirical support.

© 2018 Elsevier Ltd and British Mycological Society Fungal metabolic rates could increase under climate warming but may be counteracted by mechanisms of physiological acclimation and evolutionary adaptation. We hypothesized that Vmax and Km parameters of Neurospora discreta extracellular enzymes would acclimate to warmer temperatures through compensatory mechanisms. We also predicted that evolution under warmer temperatures would alter enzyme parameters and fungal respiration through adaptive mechanisms. In contrast to these predictions, growth at higher temperature (22 °C versus 16 °C) increased the temperature-corrected Vmax of three enzymes. The carbon substrate used for fungal growth (lignin versus sucrose) had a much greater impact on enzyme Vmax than temperature. Following experimental evolution, the enzymatic parameters of Neurospora strains did not adapt to higher temperatures as hypothesized; rather, enzyme Vmax values were unaffected, and respiration rates increased. Together, these results suggest that physiological and evolutionary mechanisms are unlikely to counteract soil carbon losses driven by saprotrophic fungi under climate warming.

The magnitude and direction of carbon cycle feedbacks under climate warming remain uncertain due to insufficient knowledge about the temperature sensitivities of soil microbial processes. Enzymatic rates could increase at higher temperatures, but this response could change over time if soil microbes adapt to warming. We used the Arrhenius relationship, biochemical transition state theory, and thermal physiology theory to predict the responses of extracellular enzyme V

Numerous field studies have found changes in soil respiration and microbial abundance under experimental warming. Yet, it is uncertain whether the magnitude of these responses remains consistent over the long-term. We performed a meta-analysis on 25 field experiments to examine how warming effects on soil respiration, microbial biomass, and soil microbial C respond to the duration of warming. For each parameter, we hypothesized that effect sizes of warming would diminish as the duration of warming increased. In support of our hypothesis, warming initially increased soil respiration, but the magnitude of this effect declined significantly as warming progressed as evidenced by the two longest studies in our meta-analysis. In fact, after 10 years of warming, soil respiration in warmed treatments was similar to controls. In contrast, warming effect sizes for fungal biomass, bacterial biomass, and soil microbial C did not respond significantly to the duration of warming. Microbial acclimation, community shifts, adaptation, or reductions in labile C may have ameliorated warming effects on soil respiration in the long-term. Accordingly, long-term soil C losses might be smaller than those suggested by short-term warming studies.

Over the long term, soil carbon (C) storage is partly determined by decomposition rate of carbon that is slow to decompose (i.e., recalcitrant C). According to thermodynamic theory, decomposition rates of recalcitrant C might differ from those of non-recalcitrant C in their sensitivities to global warming. We decomposed leaf litter in a warming experiment in Alaskan boreal forest, and measured mass loss of recalcitrant C (lignin) vs. non-recalcitrant C (cellulose, hemicellulose, and sugars) throughout 16 months. We found that these C fractions responded differently to warming. Specifically, after one year of decomposition, the ratio of recalcitrant C to non-recalcitrant C remaining in litter declined in the warmed plots compared to control. Consistent with this pattern, potential activities of enzymes targeting recalcitrant C increased with warming, relative to those targeting non-recalcitrant C. Even so, mass loss of individual C fractions showed that non-recalcitrant C is preferentially decomposed under control conditions whereas recalcitrant C losses remain unchanged between control and warmed plots. Moreover, overall mass loss was greater under control conditions. Our results imply that direct warming effects, as well as indirect warming effects (e.g. drying), may serve to maintain decomposition rates of recalcitrant C compared to non-recalcitrant C despite negative effects on overall decomposition.

Background Short-term experiments have indicated that warmer temperatures can alter fungal biomass production and CO2 respiration, with potential consequences for soil C storage. However, we know little about the capacity of fungi to adapt to warming in ways that may alter C dynamics. Thus, we exposed Neurospora discreta to moderately warm (16 °C) and warm (28 °C) selective temperatures for 1500 mitotic generations, and then examined changes in mycelial growth rate, biomass, spore production, and CO2 respiration. We tested the hypothesis that strains will adapt to its selective temperature. Specifically, we expected that adapted strains would grow faster, and produce more spores per unit biomass (i.e., relative spore production). In contrast, they should generate less CO2 per unit biomass due to higher efficiency in carbon use metabolism (i.e., lower mass specific respiration, MSR). Results Indeed, N. discreta adapted to warm temperatures, based on patterns of relative spore production. Adapted strains produced more spores per unit biomass than parental strains in the selective temperature. Contrary to our expectations, this increase in relative spore production was accompanied by an increase in MSR and a reduction in mycelial growth rate and biomass, compared to parental strains. Conclusions Adaptation of N. discreta to warm temperatures may have elicited a tradeoff between biomass production and relative spore production, possibly because relative spore production required higher MSR rates. Therefore, our results do not support the idea that adaptation to warm temperatures will lead to a more efficient carbon use metabolism. Our data might help improve climate change model simulations and provide more concise predictions of decomposition processes and carbon feedbacks to the atmosphere.

Fungi play fundamental ecological roles in terrestrial ecosystems. However, their distribution and diversity remain poorly described in natural communities, particularly in arid and semi-arid ecosystems. In order to identify environmental factors determining fungal community structure in these systems, we assessed their diversity in conjunction with soil physicochemical characteristics in a semi-arid ecosystem in Baja California, Mexico, endemic for Coccidioidomycosis (Valley Fever). Two different microhabitats, burrows (influenced by rodent activity) and topsoil, were compared in winter and summer. Using a metagenomic approach, the ITS1 region of nuclear ribosomal DNA was used as barcode. A total of 1940 Operational Taxonomic Units (OTUs) were identified from 362 332 ITS1 sequences obtained by 454 pyrosequencing. Differences in fungal composition between seasons were clearly identified. Moreover, differences in composition between microhabitats were mainly correlated to significant differences in environmental factors, such as moisture and clay content in topsoil samples, and temperature and electrical conductivity in burrow samples. Overall, the fungal community structure (dominated by Ascomycota and Basidiomycota) was less variable between seasons in burrow than in topsoil samples. Coccidioides spp. went undetected by pyrosequencing. However, a nested PCR approach revealed its higher prevalence in burrows.