Tree-mycorrhizal associations detected remotely from canopy spectral properties

Synthetic microbiology in sustainability applications

Microorganisms are a promising means to address many societal sustainability challenges owing to their ability to thrive in diverse environments and interface with the microscale chemical world via diverse metabolic capacities. Synthetic biology can engineer microorganisms by rewiring their regulatory networks or introducing new functionalities, enhancing their utility for target applications. In this Review, we provide a broad, high-level overview of various research efforts addressing sustainability challenges through synthetic biology, emphasizing foundational microbiological research questions that can accelerate the development of these efforts. We introduce an organizational framework that categorizes these efforts along three domains - factory, farm and field - that are defined by the extent to which the engineered microorganisms interface with the natural external environment. Different application areas within the same domain share many fundamental challenges, highlighting productive opportunities for cross-disciplinary collaborations between researchers working in historically disparate fields.

Emerging sensing, imaging, and computational technologies to scale nano-to macroscale rhizosphere dynamics - Review and research perspectives

The soil region influenced by plant roots, i.e., the rhizosphere, is one of the most complex biological habitats on Earth and significantly impacts global carbon flow and transformation. Understanding the structure and function of the rhizosphere is critically important for maintaining sustainable plant ecosystem services, designing engineered ecosystems for long-term soil carbon storage, and mitigating the effects of climate change. However, studying the biological and ecological processes and interactions in the rhizosphere requires advanced integrated technologies capable of decoding such a complex system at different scales. Here, we review how emerging approaches in sensing, imaging, and computational modeling can advance our understanding of the complex rhizosphere system. Particularly, we provide our perspectives and discuss future directions in developing in situ rhizosphere sensing technologies that could potentially correlate local-scale interactions to ecosystem scale impacts. We first review integrated multimodal imaging techniques for tracking inorganic elements and organic carbon flow at nano- to microscale in the rhizosphere, followed by a discussion on the use of synthetic soil and plant habitats that bridge laboratory-to-field studies on the rhizosphere processes. We then describe applications of genetically encoded biosensors in monitoring nutrient and chemical exchanges in the rhizosphere, and the novel nanotechnology-mediated delivery approaches for introducing biosensors into the root tissues. Next, we review the recent progress and express our vision on field-deployable sensing technologies such as planar optodes for quantifying the distribution of chemical and analyte gradients in the rhizosphere under field conditions. Moreover, we provide perspectives on the challenges of linking complex rhizosphere interactions to ecosystem sensing for detecting biological traits across scales, which arguably requires using the best-available model predictions including the model-experiment and image-based modeling approaches. Experimental platforms relevant to field conditions like SMART (Sensors at Mesoscales with Advanced Remote Telemetry) soils testbed, coupled with ecosystem sensing and predictive models, can be effective tools to explore coupled ecosystem behavior and responses to environmental perturbations. Finally, we envision that with the advent of novel high-resolution imaging capabilities at nano- to macroscale, and remote biosensing technologies, combined with advanced computational models, future studies will lead to detection and upscaling of rhizosphere processes toward ecosystem and global predictions.

Innovations in plant science from integrative remote sensing research: an introduction to a Virtual Issue

This article is an Editorial to the Virtual issue on ‘Remote sensing’ that includes the following papers Chavana‐Bryant et al. (2017), Coupel‐Ledru et al. (2022), Cushman & Machado (2020), Disney (2019), D'Odorico et al. (2020), Dong et al. (2022), Fischer et al. (2019), Gamon et al. (2023), Gu et al. (2019), Guillemot et al. (2020), Jucker (2021), Koh et al. (2022), Konings et al. (2019), Kothari et al. (2023), Martini et al. (2022), Richardson (2019), Santini et al. (2021), Schimel et al. (2019), Serbin et al. (2019), Smith et al. (2019, 2020), Still et al. (2021), Stovall et al. (2021), Wang et al. (2020), Wong et al. (2020), Wu et al. (2021), Wu et al. (2017), Wu et al. (2018), Wu et al. (2019), Xu et al. (2021), Yan et al. (2021). Access the Virtual Issue at www.newphytologist.com/virtualissues.

Evolutionary history explains foliar spectral differences between arbuscular and ectomycorrhizal plant species

Leaf spectra are integrated foliar phenotypes that capture a range of traits and can provide insight into ecological processes. Leaf traits, and therefore leaf spectra, may reflect belowground processes such as mycorrhizal associations. However, evidence for the relationship between leaf traits and mycorrhizal association is mixed, and few studies account for shared evolutionary history. We conduct partial least squares discriminant analysis to assess the ability of spectra to predict mycorrhizal type. We model the evolution of leaf spectra for 92 vascular plant species and use phylogenetic comparative methods to assess differences in spectral properties between arbuscular mycorrhizal and ectomycorrhizal plant species. Partial least squares discriminant analysis classified spectra by mycorrhizal type with 90% (arbuscular) and 85% (ectomycorrhizal) accuracy. Univariate models of principal components identified multiple spectral optima corresponding with mycorrhizal type due to the close relationship between mycorrhizal type and phylogeny. Importantly, we found that spectra of arbuscular mycorrhizal and ectomycorrhizal species do not statistically differ from each other after accounting for phylogeny. While mycorrhizal type can be predicted from spectra, enabling the use of spectra to identify belowground traits using remote sensing, this is due to evolutionary history and not because of fundamental differences in leaf spectra due to mycorrhizal type.

Influence of Mycorrhiza on C:N:P Stoichiometry in Senesced Leaves

Senesced leaves play a vital role in nutrient cycles in the terrestrial ecosystem. The carbon (C), nitrogen (N) and phosphorus (P) stoichiometries in senesced leaves have been reported, which are influenced by biotic and abiotic factors, such as climate variables and plant functional groups. It is well known that mycorrhizal types are one of the most important functional characteristics of plants that affect leaf C:N:P stoichiometry. While green leaves' traits have been widely reported based on the different mycorrhiza types, the senesced leaves' C:N:P stoichiometries among mycorrhizal types are rarely investigated. Here, the patterns in senesced leaves' C:N:P stoichiometry among plants associated with arbuscular mycorrhizal (AM), ectomycorrhizal (ECM), or AM + ECM fungi were explored. Overall, the senesced leaves' C, with 446.8 mg/g in AM plants, was significantly lower than that in AM + ECM and ECM species, being 493.1 and 501.4 mg/g, respectively, which was mainly caused by boreal biomes. The 8.9 mg/g senesced leaves' N in ECM plants was significantly lower than in AM (10.4 mg/g) or AM + ECM taxa (10.9 mg/g). Meanwhile, the senesced leaves' P presented no difference in plant associations with AM, AM + ECM and ECM. The senesced leaves' C and N presented contrary trends with the changes in mean annual temperature (MAT) and mean annual precipitation (MAP) in ECM or AM + ECM plants. The differences in senesced leaves' C and N may be more easily influenced by the plant mycorrhizal types, but not P and stoichiometric ratios of C, N and P. Our results suggest that senesced leaves' C:N:P stoichiometries depend on mycorrhizal types, which supports the hypothesis that mycorrhizal type is linked to the evolution of carbon-nutrient cycle interactions in the ecosystem.

Higher productivity in forests with mixed mycorrhizal strategies

Decades of theory and empirical studies have demonstrated links between biodiversity and ecosystem functioning, yet the putative processes that underlie these patterns remain elusive. This is especially true for forest ecosystems, where the functional traits of plant species are challenging to quantify. We analyzed 74,563 forest inventory plots that span 35 ecoregions in the contiguous USA and found that in ~77% of the ecoregions mixed mycorrhizal plots were more productive than plots where either arbuscular or ectomycorrhizal fungal-associated tree species were dominant. Moreover, the positive effects of mixing mycorrhizal strategies on forest productivity were more pronounced at low than high tree species richness. We conclude that at low richness different mycorrhizal strategies may allow tree species to partition nutrient uptake and thus can increase community productivity, whereas at high richness other dimensions of functional diversity can enhance resource partitioning and community productivity. Our findings highlight the importance of mixed mycorrhizal strategies, in addition to that of taxonomic diversity in general, for maintaining ecosystem functioning in forests.

Fine-resolution global maps of root biomass carbon colonized by arbuscular and ectomycorrhizal fungi

Despite the recognized importance of mycorrhizal associations in ecosystem functioning, the actual abundance patterns of mycorrhizal fungi belowground are still unknown. This information is key for better quantification of mycorrhizal impacts on ecosystem processes and for incorporating mycorrhizal pathways into global biogeochemical models. Here we present the first high-resolution maps of fine root stocks colonized by arbuscular mycorrhizal (AM) and ectomycorrhizal (EcM) fungi (MgC ha-1). The maps were assembled by combining multiple open-source databases holding information on root biomass carbon, the proportion of AM and EcM tree biomass, plot-level relative abundance of plant species and intensity of AM and EcM root colonization. We calculated root-associated AM and EcM abundance in 881 spatial units, defined as the combination of ecoregions and land cover types across six continents. The highest AM abundances are observed in the (sub-)tropics, while the highest EcM abundances occur in the taiga regions. These maps serve as a basis for future research where continuous spatial estimates of root mycorrhizal stocks are needed.

Modeling Global Carbon Costs of Plant Nitrogen and Phosphorus Acquisition

Most Earth system models (ESMs) do not explicitly represent the carbon (C) costs of plant nutrient acquisition, which leads to uncertainty in predictions of the current and future constraints to the land C sink. We integrate a plant productivity-optimizing nitrogen (N) and phosphorus (P) acquisition model (fixation & uptake of nutrients, FUN) into the energy exascale Earth system (E3SM) land model (ELM). Global plant N and P uptake are dynamically simulated by ELM-FUN based on the C costs of nutrient acquisition from mycorrhizae, direct root uptake, retranslocation from senescing leaves, and biological N fixation. We benchmarked ELM-FUN with three classes of products: ILAMB, a remotely sensed nutrient limitation product, and CMIP6 models; we found significant improvements in C cycle variables, although the lack of more observed nutrient data prevents a comprehensive level of benchmarking. Overall, we found N and P co-limitation for 80% of land area, with the remaining 20% being either predominantly N or P limited. Globally, the new model predicts that plants invested 4.1 Pg C yr-1 to acquire 841.8 Tg N yr-1 and 48.1 Tg P yr-1 (1994-2005), leading to significant downregulation of global net primary production (NPP). Global NPP is reduced by 20% with C costs of N and 50% with C costs of NP. Modeled and observed nutrient limitation agreement increases when N and P are considered together (r 2 from 0.73 to 0.83).

Remote Sensing of Surface and Subsurface Soil Organic Carbon in Tidal Wetlands: A Review and Ideas for Future Research

Tidal wetlands, widely considered the most extensive reservoir of soil organic carbon (SOC), can benefit from remote sensing studies enabling spatiotemporal estimation and mapping of SOC stock. We found that a majority of the remote-sensing-based SOC mapping efforts have been focused on upland ecosystems, not on tidal wetlands. We present a comprehensive review detailing the types of remote sensing models and methods used, standard input variables, results, and limitations for the handful of studies on tidal wetland SOC. Based on that synthesis, we pose several unexplored research questions and methods that are critical for moving tidal wetland SOC science forward. Among these, the applicability of machine learning and deep learning models for predicting surface SOC and the modeling requirements for SOC in subsurface soils (soils without a remote sensing signal, i.e., a soil depth greater than 5 cm) are the most important. We did not find any remote sensing study aimed at modeling subsurface SOC in tidal wetlands. Since tidal wetlands store a significant amount of SOC at greater depths, we hypothesized that surface SOC could be an important covariable along with other biophysical and climate variables for predicting subsurface SOC. Preliminary results using field data from tidal wetlands in the southeastern United States and machine learning model output from mangrove ecosystems in India revealed a strong nonlinear but significant relationship (r2 = 0.68 and 0.20, respectively, p < 2.2 × 10−16 for both) between surface and subsurface SOC at different depths. We investigated the applicability of the Soil Survey Geographic Database (SSURGO) for tidal wetlands by comparing the data with SOC data from the Smithsonian’s Coastal Blue Carbon Network collected during the same decade and found that the SSURGO data consistently over-reported SOC stock in tidal wetlands. We concluded that a novel machine learning framework that utilizes remote sensing data and derived products, the standard covariables reported in the limited literature, and more importantly, other new and potentially informative covariables specific to tidal wetlands such as tidal inundation frequency and height, vegetation species, and soil algal biomass could improve remote-sensing-based tidal wetland SOC studies.

Abiotic Stress and Belowground Microbiome: The Potential of Omics Approaches

Nowadays, the worldwide agriculture is experiencing a transition process toward more sustainable production, which requires the reduction of chemical inputs and the preservation of microbiomes’ richness and biodiversity. Plants are no longer considered as standalone entities, and the future of agriculture should be grounded on the study of plant-associated microorganisms and all their potentiality. Moreover, due to the climate change scenario and the resulting rising incidence of abiotic stresses, an innovative and environmentally friendly technique in agroecosystem management is required to support plants in facing hostile environments. Plant-associated microorganisms have shown a great attitude as a promising tool to improve agriculture sustainability and to deal with harsh environments. Several studies were carried out in recent years looking for some beneficial plant-associated microbes and, on the basis of them, it is evident that Actinomycetes and arbuscular mycorrhizal fungi (AMF) have shown a considerable number of positive effects on plants’ fitness and health. Given the potential of these microorganisms and the effects of climate change, this review will be focused on their ability to support the plant during the interaction with abiotic stresses and on multi-omics techniques which can support researchers in unearthing the hidden world of plant–microbiome interactions. These associated microorganisms can increase plants’ endurance of abiotic stresses through several mechanisms, such as growth-promoting traits or priming-mediated stress tolerance. Using a multi-omics approach, it will be possible to deepen these mechanisms and the dynamic of belowground microbiomes, gaining fundamental information to exploit them as staunch allies and innovative weapons against crop abiotic enemies threatening crops in the ongoing global climate change context.

A multi-omics approach to solving problems in plant disease ecology

The swift rise of omics-approaches allows for investigating microbial diversity and plant-microbe interactions across diverse ecological communities and spatio-temporal scales. The environment, however, is rapidly changing. The introduction of invasive species and the effects of climate change have particular impact on emerging plant diseases and managing current epidemics. It is critical, therefore, to take a holistic approach to understand how and why pathogenesis occurs in order to effectively manage for diseases given the synergies of changing environmental conditions. A multi-omics approach allows for a detailed picture of plant-microbial interactions and can ultimately allow us to build predictive models for how microbes and plants will respond to stress under environmental change. This article is designed as a primer for those interested in integrating -omic approaches into their plant disease research. We review -omics technologies salient to pathology including metabolomics, genomics, metagenomics, volatilomics, and spectranomics, and present cases where multi-omics have been successfully used for plant disease ecology. We then discuss additional limitations and pitfalls to be wary of prior to conducting an integrated research project as well as provide information about promising future directions.

The Snowmelt Niche Differentiates Three Microbial Life Strategies That Influence Soil Nitrogen Availability During and After Winter

Soil microbial biomass can reach its annual maximum pool size beneath the winter snowpack and is known to decline abruptly following snowmelt in seasonally snow-covered ecosystems. Observed differences in winter versus summer microbial taxonomic composition also suggests that phylogenetically conserved traits may permit winter- versus summer-adapted microorganisms to occupy distinct niches. In this study, we sought to identify archaea, bacteria, and fungi that are associated with the soil microbial bloom overwinter and the subsequent biomass collapse following snowmelt at a high-altitude watershed in central Colorado, United States. Archaea, bacteria, and fungi were categorized into three life strategies (Winter-Adapted, Snowmelt-Specialist, Spring-Adapted) based upon changes in abundance during winter, the snowmelt period, and after snowmelt in spring. We calculated indices of phylogenetic relatedness (archaea and bacteria) or assigned functional attributes (fungi) to organisms within life strategies to infer whether phylogenetically conserved traits differentiate Winter-Adapted, Snowmelt-Specialist, and Spring-Adapted groups. We observed that the soil microbial bloom was correlated in time with a pulse of snowmelt infiltration, which commenced 65 days prior to soils becoming snow-free. A pulse of nitrogen (N, as nitrate) occurred after snowmelt, along with a collapse in the microbial biomass pool size, and an increased abundance of nitrifying archaea and bacteria (e.g., Thaumarchaeota, Nitrospirae). Winter- and Spring-Adapted archaea and bacteria were phylogenetically clustered, suggesting that phylogenetically conserved traits allow Winter- and Spring-Adapted archaea and bacteria to occupy distinct niches. In contrast, Snowmelt-Specialist archaea and bacteria were phylogenetically overdispersed, suggesting that the key mechanism(s) of the microbial biomass crash are likely to be density-dependent (e.g., trophic interactions, competitive exclusion) and affect organisms across a broad phylogenetic spectrum. Saprotrophic fungi were the dominant functional group across fungal life strategies, however, ectomycorrhizal fungi experienced a large increase in abundance in spring. If well-coupled plant-mycorrhizal phenology currently buffers ecosystem N losses in spring, then changes in snowmelt timing may alter ecosystem N retention potential. Overall, we observed that snowmelt separates three distinct soil niches that are occupied by ecologically distinct groups of microorganisms. This ecological differentiation is of biogeochemical importance, particularly with respect to the mobilization of nitrogen during winter, before and after snowmelt.

Competing effects of soil fertility and toxicity on tropical greening

Tropical forests are expected to green up with increasing atmospheric CO2 concentrations, but primary productivity may be limited by soil nutrient availability. However, rarely have canopy-scale measurements been assessed against soil measurements in the tropics. Here, we sought to assess remotely sensed canopy greenness against steep soil nutrient gradients across 50 1-ha mature forest plots in Panama. Contrary to expectations, increases in in situ extractable soil phosphorus (P) and base cations (K, Mg) corresponded to declines in remotely sensed mean annual canopy greenness (r2 = 0.77-0.85; p < 0.1), controlling for precipitation. The reason for this inverse relationship appears to be that litterfall also increased with increasing soil P and cation availability (r2 = 0.88-0.98; p < 0.1), resulting in a decline in greenness with increasing annual litterfall (r2 = 0.94; p < 0.1). As such, greater soil nutrient availability corresponded to greater leaf turnover, resulting in decreased greenness. However, these decreases in greenness with increasing soil P and cations were countered by increases in greenness with increasing soil nitrogen (N) (r2 = 0.14; p < 0.1), which had no significant relationship with litterfall, likely reflecting a direct effect of soil N on leaf chlorophyll content, but not on litterfall rates. In addition, greenness increased with extractable soil aluminum (Al) (r2 = 0.97; p < 0.1), but Al had no significant relationship with litterfall, suggesting a physiological adaptation of plants to high levels of toxic metals. Thus, spatial gradients in canopy greenness are not necessarily positive indicators of soil nutrient scarcity. Using a novel remote sensing index of canopy greenness limitation, we assessed how observed greenness compares with potential greenness. We found a strong relationship with soil N only (r2 = 0.65; p < 0.1), suggesting that tropical canopy greenness in Panama is predominantly limited by soil N, even if plant productivity (e.g., litterfall) responds to rock-derived nutrients. Moreover, greenness limitation was also significantly correlated with fine root biomass and soil carbon stocks (r2 = 0.62-0.71; p < 0.1), suggesting a feedback from soil N to canopy greenness to soil carbon storage. Overall, these data point to the potential utility of a remote sensing product for assessing belowground properties in tropical ecosystems.

Climate change influences mycorrhizal fungal-plant interactions, but conclusions are limited by geographical study bias

Climate change is altering the interactions among plants and soil organisms in ways that will alter the structure and function of ecosystems. We reviewed the literature and developed a map of studies focused on how the three most common types of mycorrhizal fungi (arbuscular mycorrhizal [AM], ectomycorrhizal [EcM], and ericoid mycorrhizal [ErM] fungi) respond to elevated atmospheric carbon dioxide concentrations (eCO₂ ), climatic warming, and changes in the distribution of precipitation. Broadly, we ask how do mycorrhizal fungi respond to climate change, how do these responses vary by fungal type, and how do mycorrhizal traits influence plant adaptation, movement, or extinction in response to climatic change? First, we found that 92% of studies were conducted in the northern hemisphere, and plant host, ecosystem type and study location were only correlated with each other in the northern hemisphere because studies across all mycorrhizal fungal types were only common in the northern hemisphere. Second, we show that temperature and rainfall variability had more variable effects than eCO₂ on mycorrhizal fungal structures, but these effects were context dependent. Third, while mycorrhizal fungal types vary in their responses to climate change, it appears that warming leads to more variable responses in ectomycorrhizal than in arbuscular mycorrhizal fungi. Finally, we discuss common traits of mycorrhizal fungi that could aid in fungal and plant adaption to climate change. We posit that mycorrhizal fungi can buffer plant hosts against extinction risk, they can facilitate or retard the dispersal success of plants moving away from poor environments, and, by buffering host plants, they can enable host plant adaptation to new climates. All of these influences are, however, context dependent a finding that reflects the complex traits of mycorrhizal fungi as a group, the diversity of plant species they associate with and the variation in ecosystems in which they reside. Overall, while we point out many gaps in our understanding of the influence of climate changes on mycorrhizal fungi, we also highlight the large number of opportunities for researching plant and mycorrhizal fungal responses to and mitigation of climate changes.

Global mycorrhizal plant distribution linked to terrestrial carbon stocks

Vegetation impacts on ecosystem functioning are mediated by mycorrhizas, plant-fungal associations formed by most plant species. Ecosystems dominated by distinct mycorrhizal types differ strongly in their biogeochemistry. Quantitative analyses of mycorrhizal impacts on ecosystem functioning are hindered by the scarcity of information on mycorrhizal distributions. Here we present global, high-resolution maps of vegetation biomass distribution by dominant mycorrhizal associations. Arbuscular, ectomycorrhizal, and ericoid mycorrhizal vegetation store, respectively, 241 ± 15, 100 ± 17, and 7 ± 1.8 GT carbon in aboveground biomass, whereas non-mycorrhizal vegetation stores 29 ± 5.5 GT carbon. Soil carbon stocks in both topsoil and subsoil are positively related to the community-level biomass fraction of ectomycorrhizal plants, though the strength of this relationship varies across biomes. We show that human-induced transformations of Earth's ecosystems have reduced ectomycorrhizal vegetation, with potential ramifications to terrestrial carbon stocks. Our work provides a benchmark for spatially explicit and globally quantitative assessments of mycorrhizal impacts on ecosystem functioning and biogeochemical cycling.

The Importance of Consistent Global Forest Aboveground Biomass Product Validation

Several upcoming satellite missions have core science requirements to produce data for accurate forest aboveground biomass mapping. Largely because of these mission datasets, the number of available biomass products is expected to greatly increase over the coming decade. Despite the recognized importance of biomass mapping for a wide range of science, policy and management applications, there remains no community accepted standard for satellite-based biomass map validation. The Committee on Earth Observing Satellites (CEOS) is developing a protocol to fill this need in advance of the next generation of biomass-relevant satellites, and this paper presents a review of biomass validation practices from a CEOS perspective. We outline the wide range of anticipated user requirements for product accuracy assessment and provide recommendations for the validation of biomass products. These recommendations include the collection of new, high-quality in situ data and the use of airborne lidar biomass maps as tools toward transparent multi-resolution validation. Adoption of community-vetted validation standards and practices will facilitate the uptake of the next generation of biomass products.

Misdiagnosis of mycorrhizas and inappropriate recycling of data can lead to false conclusions

We draw attention to a worrying trend for the uncritical use of 'recycled' mycorrhizal data to compile host species lists that include obvious errors or undertake risky analyses that correlate mycorrhizal colonisation levels with environmental or physiological factors despite inherent limitations in datasets. We are not suggesting that all meta-studies are wrong, only that more care should be taken to resolve what can safely be done with recycled mycorrhizal data in the future. We also recommend that mycorrhizal species lists should be checked against standard references since the majority of EM hosts and NM plant belong to families that are well resolved. However, additional research is required in cases where plant families have multiple root types within genera or occur in habitats where mycorrhizal associations are often suppressed (see Brundrett & Tedersoo, 2018). We hope that the mycorrhizal science community will work together more closely in the future to develop and enforce standards for mycorrhizal diagnosis and to share carefully corrected datasets for realistic meta-studies.

Continental-scale nitrogen pollution is shifting forest mycorrhizal associations and soil carbon stocks

Most tree roots on Earth form a symbiosis with either ecto- or arbuscular mycorrhizal fungi. Nitrogen fertilization is hypothesized to favor arbuscular mycorrhizal tree species at the expense of ectomycorrhizal species due to differences in fungal nitrogen acquisition strategies, and this may alter soil carbon balance, as differences in forest mycorrhizal associations are linked to differences in soil carbon pools. Combining nitrogen deposition data with continental-scale US forest data, we show that nitrogen pollution is spatially associated with a decline in ectomycorrhizal vs. arbuscular mycorrhizal trees. Furthermore, nitrogen deposition has contrasting effects on arbuscular vs. ectomycorrhizal demographic processes, favoring arbuscular mycorrhizal trees at the expense of ectomycorrhizal trees, and is spatially correlated with reduced soil carbon stocks. This implies future changes in nitrogen deposition may alter the capacity of forests to sequester carbon and offset climate change via interactions with the forest microbiome.

Tree mycorrhizal type predicts within-site variability in the storage and distribution of soil organic matter

Forest soils store large amounts of carbon (C) and nitrogen (N), yet how predicted shifts in forest composition will impact long-term C and N persistence remains poorly understood. A recent hypothesis predicts that soils under trees associated with arbuscular mycorrhizas (AM) store less C than soils dominated by trees associated with ectomycorrhizas (ECM), due to slower decomposition in ECM-dominated forests. However, an incipient hypothesis predicts that systems with rapid decomposition-e.g. most AM-dominated forests-enhance soil organic matter (SOM) stabilization by accelerating the production of microbial residues. To address these contrasting predictions, we quantified soil C and N to 1 m depth across gradients of ECM-dominance in three temperate forests. By focusing on sites where AM- and ECM-plants co-occur, our analysis controls for climatic factors that covary with mycorrhizal dominance across broad scales. We found that while ECM stands contain more SOM in topsoil, AM stands contain more SOM when subsoil to 1 m depth is included. Biomarkers and soil fractionations reveal that these patterns are driven by an accumulation of microbial residues in AM-dominated soils. Collectively, our results support emerging theory on SOM formation, demonstrate the importance of subsurface soils in mediating plant effects on soil C and N, and indicate that shifts in the mycorrhizal composition of temperate forests may alter the stabilization of SOM.

Beyond ICOM8: perspectives on advances in mycorrhizal research from 2015 to 2017

This report reviews important advances in mycorrhizal research that occurred during the past 2 years. We highlight major advancements both within and across levels of biological organization and describe areas where greater integration has led to unique insights. Particularly active areas of research include exploration of the mechanisms underpinning the development of the mycorrhizal symbiosis, the mycorrhizal microbiome, comparisons among types of mycorrhizas from molecular to ecosystem scales, the extent and function of mycorrhizal networks and enhanced understanding of the role of mycorrhizas in carbon dynamics from local to global scales. The top-tier scientific journals have acknowledged mycorrhizas to be complex adaptive systems that play key roles in the development of communities and ecosystem processes. Understanding the mechanisms driving these large-scale effects requires integration of knowledge across scales of biological organization.

The mycorrhizal type governs root exudation and nitrogen uptake of temperate tree species

Even though the two dominant mycorrhizal associations of temperate tree species differentially couple carbon (C) and nitrogen (N) cycles in temperate forests, systematic differences between the biogeochemical cycles of arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) tree species remain poorly described. A classification according to the mycorrhizal type offers the chance, though, to develop a global frame concept for the prediction of temperate ecosystem responses to environmental change. Focusing on the influence of mycorrhizal types on two key plant processes of biogeochemical cycling (root exudation and N acquisition), we investigated four temperate deciduous tree species per mycorrhizal type in a drought experiment in large mesocosms. We hypothesized that (H1) C loss by root exudation is higher in ECM than in AM trees, (H2) drought leads to higher reductions in root exudation of drought-sensitive ECM trees and (H3) inorganic N uptake is higher in AM than in ECM trees. In contradiction to H2, we found no systematic difference in root exudation between the mycorrhizal types at ample soil moisture, but almost twofold higher exudation in ECM trees when exposed to soil drought. In addition, photosynthetic C cost of root exudation strongly increased by ~10-fold in drought-treated ECM trees, while it only doubled in AM trees, which confirms H1. With respect to H3, we corroborated that AM trees had higher absolute and relative inorganic N acquisition rates than ECM trees, while the organic N uptake did not differ between mycorrhizal types. We conclude that ECM trees are less efficient in inorganic N uptake than AM trees, but ECM trees increase root C release as an adaptive response to dry soil to maintain hydraulic conductivity and/or nutrient availability. These systematic differences in key biogeochemical processes support hints on the key role of the mycorrhizal types in coupling C and N cycles in temperate forests.

Building a better foundation: improving root-trait measurements to understand and model plant and ecosystem processes

Trait-based approaches provide a useful framework to investigate plant strategies for resource acquisition, growth, and competition, as well as plant impacts on ecosystem processes. Despite significant progress capturing trait variation within and among stems and leaves, identification of trait syndromes within fine-root systems and between fine roots and other plant organs is limited. Here we discuss three underappreciated areas where focused measurements of fine-root traits can make significant contributions to ecosystem science. These include assessment of spatiotemporal variation in fine-root traits, integration of mycorrhizal fungi into fine-root-trait frameworks, and the need for improved scaling of traits measured on individual roots to ecosystem-level processes. Progress in each of these areas is providing opportunities to revisit how below-ground processes are represented in terrestrial biosphere models. Targeted measurements of fine-root traits with clear linkages to ecosystem processes and plant responses to environmental change are strongly needed to reduce empirical and model uncertainties. Further identifying how and when suites of root and whole-plant traits are coordinated or decoupled will ultimately provide a powerful tool for modeling plant form and function at local and global scales.

Connecting Earth observation to high-throughput biodiversity data

Understandably, given the fast pace of biodiversity loss, there is much interest in using Earth observation technology to track biodiversity, ecosystem functions and ecosystem services. However, because most biodiversity is invisible to Earth observation, indicators based on Earth observation could be misleading and reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing and modern ecological modelling to extract much more of the information available in Earth observation data. This approach is achievable now, offering efficient and near-real-time monitoring of management impacts on biodiversity and its functions and services.

Dominant mycorrhizal association of trees alters carbon and nutrient cycling by selecting for microbial groups with distinct enzyme function

While it is well established that plants associating with arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) fungi cycle carbon (C) and nutrients in distinct ways, we have a limited understanding of whether varying abundance of ECM and AM plants in a stand can provide integrative proxies for key biogeochemical processes. We explored linkages between the relative abundance of AM and ECM trees and microbial functioning in three hardwood forests in southern Indiana, USA. Across each site's 'mycorrhizal gradient', we measured fungal biomass, fungal : bacterial (F : B) ratios, extracellular enzyme activities, soil carbon : nitrogen ratio, and soil pH over a growing season. We show that the percentage of AM or ECM trees in a plot promotes microbial communities that both reflect and determine the C to nutrient balance in soil. Soils dominated by ECM trees had higher F : B ratios and more standing fungal biomass than AM stands. Enzyme stoichiometry in ECM soils shifted to higher investment in extracellular enzymes needed for nitrogen and phosphorus acquisition than in C-acquisition enzymes, relative to AM soils. Our results suggest that knowledge of mycorrhizal dominance at the stand or landscape scale may provide a unifying framework for linking plant and microbial community dynamics, and predicting their effects on ecological function.

Root morphology and mycorrhizal symbioses together shape nutrient foraging strategies of temperate trees

Photosynthesis by leaves and acquisition of water and minerals by roots are required for plant growth, which is a key component of many ecosystem functions. Although the role of leaf functional traits in photosynthesis is generally well understood, the relationship of root functional traits to nutrient uptake is not. In particular, predictions of nutrient acquisition strategies from specific root traits are often vague. Roots of nearly all plants cooperate with mycorrhizal fungi in nutrient acquisition. Most tree species form symbioses with either arbuscular mycorrhizal (AM) or ectomycorrhizal (EM) fungi. Nutrients are distributed heterogeneously in the soil, and nutrient-rich "hotspots" can be a key source for plants. Thus, predicting the foraging strategies that enable mycorrhizal root systems to exploit these hotspots can be critical to the understanding of plant nutrition and ecosystem carbon and nutrient cycling. Here, we show that in 13 sympatric temperate tree species, when nutrient availability is patchy, thinner root species alter their foraging to exploit patches, whereas thicker root species do not. Moreover, there appear to be two distinct pathways by which thinner root tree species enhance foraging in nutrient-rich patches: AM trees produce more roots, whereas EM trees produce more mycorrhizal fungal hyphae. Our results indicate that strategies of nutrient foraging are complementary among tree species with contrasting mycorrhiza types and root morphologies, and that predictable relationships between below-ground traits and nutrient acquisition emerge only when both roots and mycorrhizal fungi are considered together.