James Umbanhowar

From Lilliput to Brobdingnag: Extending Models of Mycorrhizal Function across Scales

ABSTRACT Mycorrhizae occur in nearly all terrestrial ecosystems. Resource exchange between host plants and mycorrhizal fungi influences community, ecosystem, and even global patterns and processes. Understanding the mechanisms and consequences of mycorrhizal symbioses across a hierarchy of scales will help predict system responses to environmental change and facilitate the management of these responses for sustainability and productivity. Conceptual and mathematical models have been developed to help understand and predict mycorrhizal functions. These models are most developed for individual- and population-scale processes, but models at community, ecosystem, and global scales are also beginning to emerge. We review seven types of mycorrhizal models that vary in their scale of resolution and dynamics, and discuss approaches for integrating these models with each other and with general models of terrestrial ecosystems.

Elevated CO2 spurs reciprocal positive effects between a plant virus and an arbuscular mycorrhizal fungus

Plants form ubiquitous associations with diverse microbes. These interactions range from parasitism to mutualism, depending partly on resource supplies that are being altered by global change. While many studies have considered the separate effects of pathogens and mutualists on their hosts, few studies have investigated interactions among microbial mutualists and pathogens in the context of global change. Using two wild grass species as model hosts, we grew individual plants under ambient or elevated CO(2), and ambient or increased soil phosphorus (P) supply. Additionally, individuals were grown with or without arbuscular mycorrhizal inoculum, and after 2 wk, plants were inoculated or mock-inoculated with a phloem-restricted virus. Under elevated CO(2), mycorrhizal association increased the titer of virus infections, and virus infection reciprocally increased the colonization of roots by mycorrhizal fungi. Additionally, virus infection decreased plant allocation to root biomass, increased leaf P, and modulated effects of CO(2) and P addition on mycorrhizal root colonization. These results indicate that plant mutualists and pathogens can alter each others success, and predict that these interactions will respond to increased resource availability and elevated CO(2). Together, our findings highlight the importance of interactions among multiple microorganisms for plant performance under global change.

MycoDB, a global database of plant response to mycorrhizal fungi

Plants form belowground associations with mycorrhizal fungi in one of the most common symbioses on Earth. However, few large-scale generalizations exist for the structure and function of mycorrhizal symbioses, as the nature of this relationship varies from mutualistic to parasitic and is largely context-dependent. We announce the public release of MycoDB, a database of 4,010 studies (from 438 unique publications) to aid in multi-factor meta-analyses elucidating the ecological and evolutionary context in which mycorrhizal fungi alter plant productivity. Over 10 years with nearly 80 collaborators, we compiled data on the response of plant biomass to mycorrhizal fungal inoculation, including meta-analysis metrics and 24 additional explanatory variables that describe the biotic and abiotic context of each study. We also include phylogenetic trees for all plants and fungi in the database. To our knowledge, MycoDB is the largest ecological meta-analysis database. We aim to share these data to highlight significant gaps in mycorrhizal research and encourage synthesis to explore the ecological and evolutionary generalities that govern mycorrhizal functioning in ecosystems.

Modeling landscape-scale pathogen spillover between domesticated and wild hosts: Asian soybean rust and kudzu

Many emerging pathogens infect both domesticated and wild host species, creating the potential for pathogen transmission between domesticated and wild populations. This common situation raises the question of whether managing negative impacts of disease on a focal host population (whether domesticated, endangered, or pest) requires management of only the domesticated host, only the wild host, or both. To evaluate the roles of domesticated and wild hosts in the dynamics of shared pathogens, we developed a spatially implicit model of a pathogen transmitted by airborne spores between two host species restricted to two different landscape patch types. As well as exploring the general dynamics and implications of the model, we fully parameterized our model for Asian soybean rust, a multihost infectious disease that emerged in the United States in 2004. The rust fungus Phakopsora pachyrhizi infects many legume species, including soybeans (Glycine max) and the nonnative invasive species kudzu (Pueraria montana var. lobata). Our model predicts that epidemics are driven by the host species that is more abundant in the landscape. In managed landscapes, this will generally be the domesticated host. However, many pathogens overwinter on a wild host, which acts as the source of initial inoculum at the start of the growing season. Our model predicts that very low local densities of infected wild hosts, surviving in landscape patches separate from the domesticated host, are sufficient to initiate epidemics in the domesticated host, such that managing epidemics by reducing wild host local density may not be feasible. In contrast, managing to reduce pathogen infection of a domesticated host can reduce disease impacts on wild host populations.

Interactions among symbionts operate across scales to influence parasite epidemics

Parasite epidemics may be influenced by interactions among symbionts, which can depend on past events at multiple spatial scales. Within host individuals, interactions can depend on the sequence in which symbionts infect a host, generating priority effects. Across host individuals, interactions can depend on parasite phenology. To test the roles of parasite interactions and phenology in epidemics, we embedded multiple cohorts of sentinel plants, grown from seeds with and without a vertically transmitted symbiont, into a wild host population, and tracked foliar infections caused by three common fungal parasites. Within hosts, parasite growth was influenced by coinfections, but coinfections were often prevented by priority effects among symbionts. Across hosts, parasite phenology altered host susceptibility to secondary infections, symbiont interactions and ultimately the magnitude of parasite epidemics. Together, these results indicate that parasite phenology can influence parasite epidemics by altering the sequence of infection and interactions among symbionts within host individuals.

Resource availability determines stability for mutualist–pathogen–host interactions

Traditional explorations of interspecific interactions have generated extensive bodies of theory on mutualism and disease independently, but few studies have considered the interaction between them. We developed a model exploring the interactions among a fungal mutualist, a viral pathogen, and their shared plant host. Both microbes were assumed to alter the uptake and use of nutrients by the plant. We found that the productivity of the system and the strength of the plant–fungal mutualism influenced community dynamics. In particular, at low productivity, the pathogen may depend on the presence of the fungal mutualist for persistence. Furthermore, under some conditions, both the productivity of the system and the strength of the plant–fungal mutualism may simultaneously cause the mutualist to go extinct. We note the presence of cyclic plant–pathogen population dynamics only in the presence of the mutualist. As found in other models of consumer–resource interactions, cyclic dynamics were driven by high productivity, but, in contrast to simpler systems, high pathogen effectiveness did not consistently lead to cyclic dynamics. In total, association with mutualists can alter host–pathogen interactions, and the reverse is also true in that pathogens may alter host–mutualist interactions.

The analysis and interpretation of critical temperatures

ABSTRACT Critical temperatures are widely used to quantify the upper and lower thermal limits of organisms. But measured critical temperatures often vary with methodological details, leading to spirited discussions about the potential consequences of stress and acclimation during the experiments. We review a model based on the simple assumption that failure rate increases with increasing temperature, independent of previous temperature exposure, water loss or metabolism during the experiment. The model predicts that mean critical thermal maximal temperature (CTmax) increases non-linearly with starting temperature and ramping rate, a pattern frequently observed in empirical studies. We then develop a statistical model that estimates a failure rate function (the relationship between failure rate and current temperature) using maximum likelihood; the best model accounts for 58% of the variation in CTmax in an exemplary dataset for tsetse flies. We then extend the model to incorporate potential effects of stress and acclimation on the failure rate function; the results show how stress accumulation at low ramping rate may increase the failure rate and reduce observed values of CTmax. We also applied the model to an acclimation experiment with hornworm larvae that used a single starting temperature and ramping rate; the analyses show that increasing acclimation temperature significantly reduced the slope of the failure rate function, increasing the temperature at which failure occurred. The model directly applies to critical thermal minima, and can utilize data from both ramping and constant-temperature assays. Our model provides a new approach to analyzing and interpreting critical temperatures. Summary: A new statistical model quantifies how methodology, heat stress and acclimation influence estimates of critical temperatures.

Evolutionary history of plant hosts and fungal symbionts predicts the strength of mycorrhizal mutualism

Most plants engage in symbioses with mycorrhizal fungi in soils and net consequences for plants vary widely from mutualism to parasitism. However, we lack a synthetic understanding of the evolutionary and ecological forces driving such variation for this or any other nutritional symbiosis. We used meta-analysis across 646 combinations of plants and fungi to show that evolutionary history explains substantially more variation in plant responses to mycorrhizal fungi than the ecological factors included in this study, such as nutrient fertilization and additional microbes. Evolutionary history also has a different influence on outcomes of ectomycorrhizal versus arbuscular mycorrhizal symbioses; the former are best explained by the multiple evolutionary origins of ectomycorrhizal lifestyle in plants, while the latter are best explained by recent diversification in plants; both are also explained by evolution of specificity between plants and fungi. These results provide the foundation for a synthetic framework to predict the outcomes of nutritional mutualisms.Jason Hoeksema et al. report a meta-analysis of the drivers of outcomes in mycorrhizal mutualisms across 646 plant–fungi combinations. They find that evolutionary history explains substantially more variation in the strength of mycorrhizal mutualisms than do ecological factors.