Search for: All records

Abstract Forest canopy complexity (i.e., the three‐dimensional structure of the canopy) is often associated with increased species diversity as well as high primary productivity across natural forests. However, canopy complexity, tree diversity, and productivity are often confounded in natural forests, and the mechanisms of these relationships remain unclear. Here, we used two large tree diversity experiments in North America to assess three hypotheses: (1) increasing tree diversity leads to increased canopy complexity, (2) canopy complexity is positively related to tree productivity, and (3) the relationship between tree diversity and tree productivity is indirect and driven by the positive effects of canopy complexity. We found that increasing tree diversity from monocultures to mixtures of 12 species increases canopy complexity and productivity by up to 71% and 73%, respectively. Moreover, structural equation modeling indicates that the effects of tree diversity on productivity are indirect and mediated primarily by changes in internal canopy complexity. Ultimately, we suggest that increasing canopy complexity can be a major mechanism by which tree diversity enhances productivity in young forests. 

Abstract Ectomycorrhizal (EM) associations can promote the dominance of tree species in otherwise diverse tropical forests. These EM associations between trees and their fungal mutualists have important consequences for soil organic matter cycling, yet the influence of these EM-associated effects on surrounding microbial communities is not well known, particularly in neotropical forests. We examined fungal and prokaryotic community composition in surface soil samples from mixed arbuscular mycorrhizal (AM) and ectomycorrhizal (EM) stands as well as stands dominated by EM-associatedOreomunnea mexicana(Juglandaceae) in four watersheds differing in soil fertility in the Fortuna Forest Reserve, Panama. We hypothesized that EM-dominated stands would support distinct microbial community assemblages relative to the mixed AM-EM stands due to differences in carbon and nitrogen cycling associated with the dominance of EM trees. We expected that this microbiome selection in EM-dominated stands would lead to lower overall microbial community diversity and turnover, with tighter correspondence between general fungal and prokaryotic communities. We measured fungal and prokaryotic community composition via high-throughput Illumina sequencing of theITS2(fungi) and16SrRNA (prokaryotic) gene regions. We analyzed differences in alpha and beta diversity between forest stands associated with different mycorrhizal types, as well as the relative abundance of fungal functional groups and various microbial taxa. We found that fungal and prokaryotic community composition differed based on stand mycorrhizal type. There was lower prokaryotic diversity and lower relative abundance of fungal saprotrophs and pathogens in EM-dominated than AM-EM mixed stands. However, contrary to our prediction, there was lower homogeneity for fungal communities in EM-dominated stands compared to mixed AM-EM stands. Overall, we demonstrate that EM-dominated tropical forest stands have distinct soil microbiomes relative to surrounding diverse forests, suggesting that EM fungi may filter microbial functional groups in ways that could potentially influence plant performance or ecosystem function. 

Understanding the responses of plants, microbes, and their interactions to long-term climate change is essential to identifying the traits, genes, and functions of organisms that maintain ecosystem stability and function of the biosphere. However, many studies investigating organismal responses to climate change are limited in their scope along several key ecological, evolutionary, and environmental axes, creating barriers to broader inference. Broad inference, or the ability to apply and validate findings across these axes, is a vital component of achieving climate preparedness in the future. Breaking barriers to broad inference requires accurate cross-ecosystem interpretability and the identification of reliable frameworks for how these responses will manifest. Current approaches have generated a valuable, yet sometimes contradictory or context dependent, understanding of responses to climate change factors from the organismal- to ecosystem-level. In this synthesis, we use plants, soil microbial communities, and their interactions as examples to identify five major barriers to broad inference and resultant target research areas. We also explain risks associated with disregarding these barriers to broad inference and potential approaches to overcoming them. Developing and funding experimental frameworks that integrate basic ecological and evolutionary principles and are designed to capture broad inference across levels of organization is necessary to further our understanding of climate change on large scales. 

Introduction Alliaria petiolata (garlic mustard), an invasive forest herb in North America, often alters nutrient availability in its non-native ecosystems, but the mechanisms driving these changes have yet to be determined. We hypothesized three potential mechanisms through which garlic mustard could directly influence soil nitrogen (N) cycling: by increasing soil pH, by modifying soil microbial community composition, and by altering nutrient availability through litter inputs. Materials and methods To test these hypotheses, we evaluated garlic mustard effects on soil pH and other soil properties; fungal and prokaryotic (bacterial and archaeal) community composition; and soil N cycling rates (gross N mineralization and nitrification rates, microbial N assimilation rates, and nitrification- versus denitrification-derived nitrous oxide fluxes); and we assessed correlations among these variables. We collected soil samples from garlic mustard present, absent, and removed treatments in eight forests in central Illinois, United States, during the rosette, flowering, and senescence phenological stages of garlic mustard life cycle. Results We found that garlic mustard increased soil pH, altered fungal and prokaryotic communities, and increased rates of N mineralization, nitrification, nitrification-derived net N2O emission. Significant correlations between soil pH and microbial community composition suggest that garlic mustard effects on soil pH could both directly and indirectly influence soil N cycling rates. Discussion Correspondence of gross rates of N mineralization and nitrification with microbial community composition suggest that garlic mustard modification of soil microbial communities could directly lead to changes in soil N cycling. We had expected that early season, nutrient-rich litter inputs from mortality of young garlic mustard could accelerate gross N mineralization and microbial N assimilation whereas late season, nutrient poorer litter inputs from senesced garlic mustard could suppress N mineralization, but we did not observe these patterns in support of the litter input mechanism. Together, our results elucidate how garlic mustard effects on soil pH and microbial community composition can accelerate soil N cycling to potentially contribute to the invasion success of garlic mustard. 

ABSTRACT We develop a method to artificially select for rhizosphere microbiomes that confer salt tolerance to the model grass Brachypodium distachyon grown under sodium salt stress or aluminum salt stress. In a controlled greenhouse environment, we differentially propagated rhizosphere microbiomes between plants of a nonevolving, highly inbred plant population; therefore, only microbiomes evolved in our experiment, but the plants did not evolve in parallel. To maximize microbiome perpetuation when transplanting microbiomes between plants and, thus, maximize response to microbiome selection, we improved earlier methods by (i) controlling microbiome assembly when inoculating seeds at the beginning of each selection cycle; (ii) fractionating microbiomes before transfer between plants to harvest, perpetuate, and select on only bacterial and viral microbiome components; (iii) ramping of salt stress gradually from minor to extreme salt stress with each selection cycle to minimize the chance of overstressing plants; (iv) using two nonselection control treatments (e.g., nonselection microbial enrichment and null inoculation) that permit comparison to the improving fitness benefits that selected microbiomes impart on plants. Unlike previous methods, our selection protocol generated microbiomes that enhance plant fitness after only 1 to 3 rounds of microbiome selection. After nine rounds of microbiome selection, the effect of microbiomes selected to confer tolerance to aluminum salt stress was nonspecific (these artificially selected microbiomes equally ameliorate sodium and aluminum salt stresses), but the effect of microbiomes selected to confer tolerance to sodium salt stress was specific (these artificially selected microbiomes do not confer tolerance to aluminum salt stress). Plants with artificially selected microbiomes had 55 to 205% greater seed production than plants with unselected control microbiomes. IMPORTANCE We developed an experimental protocol that improves earlier methods of artificial selection on microbiomes and then tested the efficacy of our protocol to breed root-associated bacterial microbiomes that confer salt tolerance to a plant. Salt stress limits growth and seed production of crop plants, and artificially selected microbiomes conferring salt tolerance may ultimately help improve agricultural productivity. Unlike previous experiments of microbiome selection, our selection protocol generated microbiomes that enhance plant productivity after only 1 to 3 rounds of artificial selection on root-associated microbiomes, increasing seed production under extreme salt stress by 55 to 205% after nine rounds of microbiome selection. Although we artificially selected microbiomes under controlled greenhouse conditions that differ from outdoor conditions, increasing seed production by 55 to 205% under extreme salt stress is a remarkable enhancement of plant productivity compared to traditional plant breeding. We describe a series of additional experimental protocols that will advance insights into key parameters that determine efficacy and response to microbiome selection. 

Abstract Plants deploy both primary and species-specific, specialized metabolites to communicate with other organisms and adapt to environmental challenges, including interactions with soil-dwelling microbial communities. However, the role of specialized metabolites in modulating plant-microbiome interactions often remains elusive. In this study, we report that maize (Zea mays) diterpenoid metabolites with known antifungal bioactivities also influence rhizosphere bacterial communities. Metabolite profiling showed that dolabralexins, antibiotic diterpenoids that are highly abundant in roots of some maize varieties, can be exuded from the roots. Comparative 16S rRNA gene sequencing determined the bacterial community composition of the maize mutantZman2(anther ear 2), which is deficient in dolabralexins and closely related bioactive kauralexin diterpenoids. TheZman2rhizosphere microbiome differed significantly from the wild-type sibling with the most significant changes observed for Alphaproteobacteria of the order Sphingomonadales. Metabolomics analyses support that these differences are attributed to the diterpenoid deficiency of theZman2mutant, rather than other large-scale metabolome alterations. Together, these findings support physiological functions of maize diterpenoids beyond known chemical defenses, including the assembly of the rhizosphere microbiome.