Most desert plants form symbiotic relationships with arbuscular mycorrhizal fungi (AMF), yet fungal identity and impacts on host plants remain largely unknown. Despite widespread recognition of the importance of AMF relationships for plant functioning, we do not know how fungal community structure changes across a desert climate gradient, nor the impacts of different fungal communities on host plant species. Because climate change can shape the distribution of species through effects on species interactions, knowing how the ranges of symbiotic partners are geographically structured and the outcomes of those species interactions informs theory and improves management recommendations. Here we used high throughput sequencing to examine the AMF community of Joshua trees along a climate gradient in Joshua Tree National Park. We then used a range of performance measures and abiotic factors to evaluate how different AMF communities may affect Joshua tree fitness. We found that fungal communities change with elevation resulting in a spectrum of interaction outcomes from mutualism to parasitism that changed with the developmental stage of the plant. Nutrient accumulation and the mycorrhizal growth response of Joshua tree seedlings inoculated with fungi from the lowest (warmest) elevations was first negative, but after 9 months had surpassed that of plants with other fungal treatments. This indicates that low elevation fungi are costly for the plant to initiate symbiosis, yet confer benefits over time. The strong relationship between AMF community and plant growth suggests that variation in AMF community may have long term consequences for plant populations along an elevation gradient.

We developed the individual-based model PHYLLOSIM to explain observed variation in the size of bacterial clusters on plant leaf surfaces (the phyllosphere). Specifically, we tested how different 'waterscapes' impacted the diffusion of nutrients from the leaf interior to the surface and the growth of individual bacteria on these nutrients. In the 'null' model or more complex 'patchy' models, the surface was covered with a continuous water film or with water drops of equal or different volumes, respectively. While these models predicted the growth of individual bacterial immigrants into clusters of variable sizes, they were unable to reproduce experimentally derived, previously published patterns of dispersion which were characterized by a much larger variation in cluster sizes and a disproportionate occurrence of clusters consisting of only one or two bacteria. The fit of model predictions to experimental data was about equally poor (<5%) regardless of whether the water films were continuous or patchy. Only by allowing individual bacteria to detach from developing clusters and re-attach elsewhere to start a new cluster, did PHYLLOSIM come much closer to reproducing experimental observations. The goodness of fit including detachment increased to about 70-80% for all waterscapes. Predictions of this 'detachment' model were further supported by the visualization and quantification of bacterial detachment and attachment events at an agarose-water interface. Thus, both model and experiment suggest that detachment of bacterial cells from clusters is an important mechanism underlying bacterial exploration of the phyllosphere.

Orchids are highly dependent on their mycorrhizal fungal partners for nutrient supply, especially during early developmental stages. In addition to organic carbon, nitrogen (N) is probably a major nutrient transferred to the plant because orchid tissues are highly N-enriched. We know almost nothing about the N form preferentially transferred to the plant or about the key molecular determinants required for N uptake and transfer. We identified, in the genome of the orchid mycorrhizal fungus Tulasnella calospora, two functional ammonium transporters and several amino acid transporters but found no evidence of a nitrate assimilation system, in agreement with the N preference of the free-living mycelium grown on different N sources. Differential expression in symbiosis of a repertoire of fungal and plant genes involved in the transport and metabolism of N compounds suggested that organic N may be the main form transferred to the orchid host and that ammonium is taken up by the intracellular fungus from the apoplatic symbiotic interface. This is the first study addressing the genetic determinants of N uptake and transport in orchid mycorrhizas, and provides a model for nutrient exchanges at the symbiotic interface, which may guide future experiments.

Plant physiological status is the interaction between the plant genome and the prevailing growth conditions. Accurate characterization of plant physiology is, therefore, fundamental to effective plant phenotyping studies; particularly those focused on identifying traits associated with improved yield, lower input requirements, and climate resilience. Here, we outline the approaches used to assess plant physiology and how these techniques of direct empirical observations of processes such as photosynthetic CO2 assimilation, stomatal conductance, photosystem II electron transport, or the effectiveness of protective energy dissipation mechanisms are unsuited to high-throughput phenotyping applications. Novel optical sensors, remote/proximal sensing (multi- and hyperspectral reflectance, infrared thermography, sun-induced fluorescence), LiDAR, and automated analyses of below-ground development offer the possibility to infer plant physiological status and growth. However, there are limitations to such indirect approaches to gauging plant physiology. These methodologies that are appropriate for the rapid high temporal screening of a number of crop varieties over a wide spatial scale do still require calibration or validation with direct empirical measurement of plant physiological status. The use of deep-learning and artificial intelligence approaches may enable the effective synthesis of large multivariate datasets to more accurately quantify physiological characters rapidly in high numbers of replicate plants. Advances in automated data collection and subsequent data processing represent an opportunity for plant phenotyping efforts to fully integrate fundamental physiological data into vital efforts to ensure food and agro-economic sustainability.

High soil salinity negatively influences plant growth and yield. Some taxa have evolved mechanisms for avoiding or tolerating elevated soil salinity, which can be modulated by the environment experienced by parents or offspring. We tested the contribution of the parental and offspring environments on salinity adaptation and their potential underlying mechanisms. In a two-generation greenhouse experiment, we factorially manipulated salinity concentrations for genotypes of Medicago truncatula that were originally collected from natural populations that differed in soil salinity. To compare population level adaptation to soil salinity and to test the potential mechanisms involved we measured two aspects of plant performance, reproduction and vegetative biomass, and phenological and physiological traits associated with salinity avoidance and tolerance. Saline-origin populations had greater biomass and reproduction under saline conditions than non-saline populations, consistent with local adaptation to saline soils. Additionally, parental environmental exposure to salt increased this difference in performance. In terms of environmental effects on mechanisms of salinity adaptation, parental exposure to salt spurred phenological differences that facilitated salt avoidance, while offspring exposure to salt resulted in traits associated with greater salt tolerance. Non-saline origin populations expressed traits associated with greater growth in the absence of salt while, for saline adapted populations, the ability to maintain greater performance in saline environments was also associated with lower growth potential in the absence of salt. Plastic responses induced by parental and offspring environments in phenology, leaf traits, and gas exchange contribute to salinity adaptation in M. truncatula. The ability of plants to tolerate environmental stress, such as high soil salinity, is likely modulated by a combination of parental effects and within-generation phenotypic plasticity, which are likely to vary in populations from contrasting environments.

Tuberaceae is one of the most diverse lineages of symbiotic truffle-forming fungi. To understand the molecular underpinning of the ectomycorrhizal truffle lifestyle, we compared the genomes of Piedmont white truffle (Tuber magnatum), Périgord black truffle (Tuber melanosporum), Burgundy truffle (Tuber aestivum), pig truffle (Choiromyces venosus) and desert truffle (Terfezia boudieri) to saprotrophic Pezizomycetes. Reconstructed gene duplication/loss histories along a time-calibrated phylogeny of Ascomycetes revealed that Tuberaceae-specific traits may be related to a higher gene diversification rate. Genomic features in Tuber species appear to be very similar, with high transposon content, few genes coding lignocellulose-degrading enzymes, a substantial set of lineage-specific fruiting-body-upregulated genes and high expression of genes involved in volatile organic compound metabolism. Developmental and metabolic pathways expressed in ectomycorrhizae and fruiting bodies of T. magnatum and T. melanosporum are unexpectedly very similar, owing to the fact that they diverged ~100 Ma. Volatile organic compounds from pungent truffle odours are not the products of Tuber-specific gene innovations, but rely on the differential expression of an existing gene repertoire. These genomic resources will help to address fundamental questions in the evolution of the truffle lifestyle and the ecology of fungi that have been praised as food delicacies for centuries.