The tremendous potential of the plant microbiome to improve plant growth and production means that microbes are in the process of becoming an everyday tool in agronomic practices. However, historically field applications of microbes have had low success. We propose that development and optimization of microbiome treatments will benefit from the integration of ecological and evolutionary niche theory into plant microbiome studies. Thus, we review several niche-based processes that can aid in the development and implementation of microbiome treatments. Current predictive approaches include evolutionary history, habitat origin, ecological traits, resource trade, and gene signatures, none of which are mutually exclusive. A robust predictive framework must further account for observed plasticity and context dependence in microbial function. Development of microbiome treatments that will successfully establish in the field can also benefit from a better understanding of niche-based processes such as niche partitioning to limit competitive interactions and maximize persistence, priority effects to allow establishment before resident taxa, storage effects that take advantage of temporal variation in niche availability, and local adaptation to specific environments. Using endophytic fungi as examples, we illustrate current knowledge and gaps in these areas. Finally, we address existing limitations to the broad-scale development of successful microbiome tools.

Ecosystem carbon losses from soil microbial respiration are a key component of global carbon cycling, resulting in the transfer of 40–70 Pg carbon from soil to the atmosphere each year. Because these microbial processes can feed back to climate change, understanding respiration responses to environmental factors is necessary for improved projections. We focus on respiration responses to soil moisture, which remain unresolved in ecosystem models. A common assumption of large-scale models is that soil microorganisms respond to moisture in the same way, regardless of location or climate. Here, we show that soil respiration is constrained by historical climate. We find that historical rainfall controls both the moisture dependence and sensitivity of respiration. Moisture sensitivity, defined as the slope of respiration vs. moisture, increased fourfold across a 480-mm rainfall gradient, resulting in twofold greater carbon loss on average in historically wetter soils compared with historically drier soils. The respiration–moisture relationship was resistant to environmental change in field common gardens and field rainfall manipulations, supporting a persistent effect of historical climate on microbial respiration. Based on these results, predicting future carbon cycling with climate change will require an understanding of the spatial variation and temporal lags in microbial responses created by historical rainfall.

Fungal symbionts are increasingly targeted as tools for crop management, but their use in the field requires an understanding of how fungi interact in a community context. Fungal interactions may result in additive effects on the host plant, which could be predicted simply based on individual fungal behavior. Alternatively, interactions among fungi may result in non-additive synergistic or antagonistic effects on plant performance that are more challenging to predict. Here, we hypothesized that the effects of fungal interactions on the plant host could be predicted from their niche overlap. To test this idea, we used foliar fungal endophytes with a range of niche overlap based on trait dissimilarities to examine the effects of six fungal species pairs compared to the corresponding individual fungal species on switchgrass (Panicum virgatum L.) in water-stressed and well-watered conditions. Mixtures of endophytes had either no effect or predictable, additive effects on plant tiller number, but effects on plant growth rate and wilting were largely non-additive. Moisture level, fungal stress, and metabolic trait dissimilarity predicted 51 to 92% of the deviation of fungal effects from additive, with less similar fungi likely to have more synergistic effects on the plant host. Furthermore, we identified indicator metabolites for fungal interaction outcomes. However, the effects of endophyte interactions on the plant host were environment dependent making single community applications more challenging. Overall, future development of microbial tools for use in agriculture must consider their interactions to optimize application.

Microbial responses to climate change will partly control the balance of soil carbon storage and loss under future temperature and precipitation conditions. We propose four classes of response mechanisms that can allow for a more general understanding of microbial climate responses. We further explore how a subset of these mechanisms results in microbial responses to climate change using simulation modeling. Specifically, we incorporate soil moisture sensitivity into two current enzyme-driven models of soil carbon cycling and find that moisture has large effects on predictions for soil carbon and microbial pools. Empirical efforts to distinguish among response mechanisms will facilitate our ability to further develop models with improved accuracy.

Identifying the physiological and genetic basis of stress tolerance in plants has proven to be critical to understanding adaptation in both agricultural and natural systems. However, many discoveries were initially made in the controlled conditions of greenhouses or laboratories, not in the field. To test the comparability of drought responses across field and greenhouse environments, we undertook three independent experiments using the switchgrass reference genotype Alamo AP13. We analyzed physiological and gene-expression variation across four locations, two sampling times and three years. Relatively similar physiological responses and expression coefficients of variation across experiments masked highly dissimilar gene expression responses to drought. Critically, a drought experiment utilizing small pots in the greenhouse elicited nearly identical physiological changes as an experiment conducted in the field, but an order of magnitude more differentially expressed genes. However, we were able to define a suite of several hundred genes that were differentially expressed in each experiment. This list was strongly enriched in photosynthesis, water status and reactive oxygen species responsive genes. The strong across-experiment correlations between physiological plasticity-but not differential gene expression-highlight the complex and diverse genetic mechanisms that can produce phenotypically similar responses to various soil water deficits.

Rainfall is recognized as a major factor affecting the rate of plant growth development. The impact of changes in amount and variability of rainfall on growth and production of different forage grasses needs to be quantified to determine how climate change can impact rangelands. Comparative studies to evaluate the growth of several perennial forage species at different rainfall rates will provide useful information by identifying forage management strategies under various rainfall scenarios. In this study, the combination of rainfall changes and soil types on the plant growth of 10 perennial forage species was investigated with both the experimental methods, using rainout shelters, and with the numerical methods using the plant growth simulation model, ALMANAC. Overall, most species significantly increased basal diameter and height as rainfall increased. Like measured volume, simulated yields for all species generally increased as rainfall increased. But, large volume and yield increases were only observed between 350 and 850 mm/yr. Simulating all species growing together competing agrees relatively well with observed plant volumes at low rainfall treatment, while simulating all species growing separately was slightly biased towards overestimation on low rainfall effect. Both simulations agree relatively well with observed plant volume at high rainfall treatment.

The high diversity of tree species has traditionally been considered an important controller of belowground processes in tropical rainforests. However, soil water availability and resources are also primary regulators of soil bacteria in many ecosystems. Separating the effects of these biotic and abiotic factors in the tropics is challenging because of their high spatial and temporal heterogeneity. To determine the drivers of tropical soil bacteria, we examined tree species effects using experimental tree monocultures and secondary forests at La Selva Biological Station in Costa Rica. A randomized block design captured spatial variation and we sampled at four dates across two years to assess temporal variation. We measured bacteria richness, phylogenetic diversity, community composition, biomass, and functional potential. All bacteria parameters varied significantly across dates. In addition, bacteria richness and phylogenetic diversity were affected by the interaction of vegetation type and date, whereas bacteria community composition was affected by the interaction of vegetation type and block. Shifts in bacteria community richness and composition were unrelated to shifts in enzyme function, suggesting physiological overlap among taxa. Based on the observed temporal and spatial heterogeneity, our understanding of tropical soil bacteria will benefit from additional work to determine the optimal temporal and spatial scales for sampling. Understanding spatial and temporal variation will facilitate prediction of how tropical soil microbes will respond to future environmental change.

Respiration of soil organic carbon is one of the largest fluxes of CO2 on earth. Understanding the processes that regulate soil respiration is critical for predicting future climate. Recent work has suggested that soil carbon respiration may be reduced by competition for nitrogen between symbiotic ectomycorrhizal fungi that associate with plant roots and free-living microbial decomposers, which is consistent with increased soil carbon storage in ectomycorrhizal ecosystems globally. However, experimental tests of the mycorrhizal competition hypothesis are lacking. Here we show that ectomycorrhizal roots and hyphae decrease soil carbon respiration rates by up to 67% under field conditions in two separate field exclusion experiments, and this likely occurs via competition for soil nitrogen, an effect larger than 2 °C soil warming. These findings support mycorrhizal competition for nitrogen as an independent driver of soil carbon balance and demonstrate the need to understand microbial community interactions to predict ecosystem feedbacks to global climate.

Horizontally-transmitted foliar endophytic fungi can moderate plant tolerance to abiotic and biotic stress. Previous studies have found correlations between climate and endophyte beta diversity, but were unable to clearly separate drivers related to long-term climate, annual weather, and host plants. To address this, we characterized endophyte communities in the perennial C4 grass, Panicum hallii, across a precipitation gradient in central Texas over 3 years. A total of 65 unique leaf endophytes were isolated and identified based on ITS and LSU regions of rDNA. Mean annual rainfall and temperature were the primary drivers of endophyte richness and community composition, followed by annual weather conditions. In contrast, little explanatory value was provided by plant host traits, vegetation structure, or spatial factors. The importance of historical climate and annual weather in endophyte distributions suggests that species sort by environment and are likely to be affected by future climate change.

Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442–887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios.

Differences in the arrival timing of plants and soil biota may result in different plant communities through priority effects, potentially affecting the success of native vs. exotic plants, but experimental evidence is largely lacking. We conducted a greenhouse experiment to investigate whether the assembly history of plants and fungal root endophytes could interact to influence plant emergence and biomass. We introduced a grass species and eight fungal species from one of three land-use types (undisturbed, disturbed, or pasture sites in a Florida scrubland) in factorial combinations. We then introduced all plants and fungi from the other land-use types 2 weeks later. Plant emergence was monitored for 6 months, and final plant biomass and fungal species composition assessed. The emergence and growth of the exotic Melinis repens and the native Schizacharyium niveum were affected negatively when introduced early with their “home” fungi, but early introduction of a different plant species or fungi from a different site type eliminated these negative effects, providing evidence for interactive priority effects. Interactive effects of plant and fungal arrival history may be an overlooked determinant of plant community structure and may provide an effective management tool to inhibit biological invasion and aid ecosystem restoration.

Soil nitrogen (N) availability constrains future predictions of ecosystem primary productivity and carbon storage. The progressive N limitation (PNL) hypothesis predicts that forest net primary productivity (NPP) will decline with age, and that the response of NPP to elevated CO2 will attenuate through time due to negative feedbacks of NPP on the soil N cycle. A central assumption of the PNL hypothesis is that, without changes in exogenous exchange of N in an ecosystem, increases in plant N uptake require increased soil N cycling rates. However, at ecosystem scale, microbial N uptake exceeds plant uptake. Hence, a change in the partitioning of N between plants and soil microorganisms may represent an alternative mechanism to sustain plant N uptake in the face of PNL. To estimate N partitioning of total N cycling between plants and microbes, we measured and modeled growth and N uptake of trees, bacteria, saprotrophic fungi, and ectomycorrhizal fungi across a forest succession and N limitation gradient. The combined plant and ectomycorrhizal N uptake increased from early to late succession, and nearly matched saprotrophic N uptake in late successional sites, while total N cycling remained stable or even declined. Changes in microbial community structure can thus mediate a redistribution of ecosystem nitrogen cycling, allowing an increase in plant N uptake without concomitant increases in soil N cycling. We further suggest that microbe-mediated changes in N partitioning can delay PNL and may thereby act as a mechanism to extend the duration of the land carbon sink in response to rising atmospheric CO2.

How soil processes such as carbon cycling will respond to future climate change depends on the responses of complex microbial communities, but most ecosystem models assume that microbial functional responses are resilient and can be predicted from simple parameters such as biomass and temperature. Here, we consider how historical contingencies might alter those responses because function depends on prior conditions or biota. Functional resilience can be driven by physiological, community or adaptive shifts; historical contingencies can result from the influence of historical environments or a combination of priority effects and biotic resistance. By modelling microbial population responses to environmental change, we demonstrate that historical environments can constrain soil function with the degree of constraint depending on the magnitude of change in the context of the prior environment. For example microbial assemblages from more constant environments were more sensitive to change leading to poorer functional acclimatisation compared to microbial assemblages from more fluctuating environments. Such historical contingencies can lead to deviations from expected functional responses to climate change as well as local variability in those responses. Our results form a set of interrelated hypotheses regarding soil microbial responses to climate change that warrant future empirical attention.

Many wet tropical forests, which contain a quarter of global terrestrial biomass carbon stocks, will experience changes in precipitation regime over the next century. Soil microbial responses to altered rainfall are likely to be an important feedback on ecosystem carbon cycling, but the ecological mechanisms underpinning these responses are poorly understood. We examined how reduced rainfall affected soil microbial abundance, activity, and community composition using a 6-month precipitation exclusion experiment at La Selva Biological Station, Costa Rica. Thereafter, we addressed the persistent effects of field moisture treatments by exposing soils to a controlled soil moisture gradient in the lab for 4 weeks. In the field, compositional and functional responses to reduced rainfall were dependent on initial conditions, consistent with a large degree of spatial heterogeneity in tropical forests. However, the precipitation manipulation significantly altered microbial functional responses to soil moisture. Communities with prior drought exposure exhibited higher respiration rates per unit microbial biomass under all conditions and respired significantly more CO2 than control soils at low soil moisture. These functional patterns suggest that changes in microbial physiology may drive positive feedbacks to rising atmospheric CO2 concentrations if wet tropical forests experience longer or more intense dry seasons in the future.

Soil fungal communities have high local diversity and turnover, but the relative contribution of environmental and regional drivers to those patterns remains poorly understood. Local factors that contribute to fungal diversity include soil properties and the plant community, but there is also evidence for regional dispersal limitation in some fungal communities. We used different plant communities with different soil conditions and experimental manipulations of both vegetation and dispersal to distinguish among these factors. Specifically, we compared native shrublands with former native shrublands that had been disturbed or converted to pasture, resulting in soils progressively more enriched in carbon and nutrients. We tested the role of vegetation via active removal, and we manipulated dispersal by adding living soil inoculum from undisturbed native sites. Soil fungi were tracked for 3 years, with samples taken at ten time points from June 2006 to June 2009. We found that soil fungal abundance, richness, and community composition responded primarily to soil properties, which in this case were a legacy of plant community degradation. In contrast, dispersal had no effect on soil fungi. Temporal variation in soil fungi was partly related to drought status, yet it was much broader in native sites compared to pastures, suggesting some buffering due to the increased soil resources in the pasture sites. The persistence of soil fungal communities over 3 years in this study suggests that soil properties can act as a strong local environmental filter. Largely persistent soil fungal communities also indicate the potential for strong biotic resistance and soil legacies, which presents a challenge for both the prediction of how fungi respond to environmental change and our ability to manipulate fungi in efforts such as ecosystem restoration

Increasingly, the success of management interventions aimed at biodiversity conservation are viewed as being dependent on the ‘resilience’ of the system. Although the term ‘resilience’ is increasingly used by policy makers and environmental managers, the concept of ‘resilience’ remains vague, varied and difficult to quantify. Here we clarify what this concept means from an ecological perspective, and how it can be measured and applied to ecosystem management. We argue that thresholds of disturbance are central to measuring resilience. Thresholds are important because they offer a means to quantify how much disturbance an ecosystem can absorb before switching to another state, and so indicate whether intervention might be necessary to promote the recovery of the pre-disturbance state. We distinguish between helpful resilience, where resilience helps recovery, and unhelpful resilience where it does not, signalling the presence of a threshold and the need for intervention. Data to determine thresholds are not always available and so we consider the potential for indices of functional diversity to act as proxy measures of resilience. We also consider the contributions of connectivity and scale to resilience and how to incorporate these factors into management. We argue that linking thresholds to functional diversity indices may improve our ability to predict the resilience of ecosystems to future, potentially novel, disturbances according to their spatial and temporal scales of influence. Throughout, we provide guidance for the application of the resilience concept to ecosystem management. In doing so, we confirm its usefulness for improving biodiversity conservation in our rapidly changing world.

The restoration of disturbed ecosystems is challenging and often unsuccessful, particularly when non-native plants are abundant. Ecosystem restoration may be hindered by the effects of non-native plants on soil biogeochemical characteristics and microbial communities that persist even after plants are removed. To examine the importance of soil legacy effects, we used experimental restorations of Florida shrubland habitat that had been degraded by the introduction of non-native grasses coupled with either mechanical disturbance or pasture conversion. We removed non-native grasses and inoculated soils with native microbial communities at each degraded site, then examined how habitat structure, soil nitrogen, soil microbial abundances, and native seed germination responded over two years compared to undisturbed native sites. Grass removal treatments effectively restored some aspects of native habitat structure, including decreased exotic grass cover, increased bare ground, and reduced litter cover. Soil fungal abundance was also somewhat restored by grass removals, but soil algal abundance was unaffected. In addition, grass removal and microbial inoculation improved seed germination rates in degraded sites, but these remained quite low compared to native sites. High soil nitrogen persisted throughout the experiment regardless of treatment. Many treatment effects were site-specific, however, with legacies in the more degraded vegetation type tending to be more difficult to overcome. These results support the need for context-dependent restoration approaches and suggest that the degree of soil legacy effects may be a good indicator of restoration potential.