I am an associate professor in Ecohydrology, with research interests spanning soil-vegetation-atmosphere interactions, hydro-climatic impacts on carbon and nutrient cycling, sustainable resource use and management, and ecological stoichiometry. My approach is based on process-based, conceptual, and stochastic models of water, carbon, and nutrient fluxes, which are tested using local and global datasets.
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- Malin Forsberg (Ph.D. student) - plant-microbial interactions
- Xiankun Li (Ph.D. student) - soil microbial responses to stress
- Erik Schwarz (Ph.D. student) - eco-evolutionary modelling of soil microbes
- Arjun Chakrawal (postdoc) - eco-evolutionary modelling of soil microbes
- Pierre Quévreux (postdoc) - modelling of soil microbes and soil food webs
- Caroline Greiser (collaborating researcher) - plants and microenvironment
- Swamini Khurana - now data scientist at McKinsey & Company
- John Livsey - now postdoc at SLU Uppsala
- Anna Scaini - now researcher at Stockholm University
Courses in the MSc Program in Hydrology, Hydrogeology and Water Resources:
- Water Resources Sustainability (GE7086)
- Ecohydrology (GE7087)
- Hydrological Modelling (GE8034)
PhD course Frontiers in Physical Geography (GE4FU01)
- Schmidt Futures program: Carbon Loss in Plants, Soils and Oceans (CALIPSO)
- European Research Council (ERC) Consolidator Grant: Soil MIcrobial responses to land use and climatic changes in the Light of Evolution (SMILE)
- Vetenskapsrådet Research Grant: Does nutrient limitation promote carbon storage in forest soils?
- EU-Horizon 2020 project: Holistic management practices, modelling and monitoring for European forest soils (HoliSoils)
- Collaboration with Formas special call project: Continuous-cover forestry in Sweden - carbon sink, economic returns and soil biodiversity (PI: B. Lindahl)
- Collaboration with DFG priority program SoilSystems: Integrated trait-based modeling of carbon and energy flows in soil systems (TraiMErgy)
- Soil carbon and water management in rice systems
- Upscaling soil carbon dynamics from pores to ecosystems
- Carbon-use efficiency across scales
- Ecological stoichiometry of decomposition
- Eco-hydrological optimality of plant form and function
- Predictive models of forest C dynamics based on metatranscriptomic analyses of microbial traits (joint project with B. Lindahl, SLU)
2018-2022 Highly Cited Researcher (category: cross-field), Clarivate Analytics
2014 Early Career Hydrologic Sciences Award, American Geophysical Union
A selection from Stockholm University publication database
Microbial carbon use efficiency promotes global soil carbon storage
2023. Feng Tao (et al.). Nature 618 (7967), 981-985Article
Soils store more carbon than other terrestrial ecosystems. How soil organic carbon (SOC) forms and persists remains uncertain, which makes it challenging to understand how it will respond to climatic change. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.
Decomposition rate as an emergent property of optimal microbial foraging
2023. Stefano Manzoni, Arjun Chakrawal, Glenn Ledder. Frontiers in Ecology and Evolution 11Article
Decomposition kinetics are fundamental for quantifying carbon and nutrient cycling in terrestrial and aquatic ecosystems. Several theories have been proposed to construct process-based kinetics laws, but most of these theories do not consider that microbial decomposers can adapt to environmental conditions, thereby modulating decomposition. Starting from the assumption that a homogeneous microbial community maximizes its growth rate over the period of decomposition, we formalize decomposition as an optimal control problem where the decomposition rate is a control variable. When maintenance respiration is negligible, we find that the optimal decomposition kinetics scale as the square root of the substrate concentration, resulting in growth kinetics following a Hill function with exponent 1/2 (rather than the Monod growth function). When maintenance respiration is important, optimal decomposition is a more complex function of substrate concentration, which does not decrease to zero as the substrate is depleted. With this optimality-based formulation, a trade-off emerges between microbial carbon-use efficiency (ratio of growth rate over substrate uptake rate) and decomposition rate at the beginning of decomposition. In environments where carbon substrates are easily lost due to abiotic or biotic factors, microbes with higher uptake capacity and lower efficiency are selected, compared to environments where substrates remain available. The proposed optimization framework provides an alternative to purely empirical or process-based formulations for decomposition, allowing exploration of the effects of microbial adaptation on element cycling.
Drying intensity and acidity slow down microbial growth recovery after rewetting dry soils
2023. Xiankun Li (et al.). Soil Biology and Biochemistry 184Article
Soil microbes perceive drying and rewetting (DRW) events as more or less harsh depending on the previous soil moisture history. If a DRW event is not perceived as harsh, microbial growth recovers rapidly after rewetting (referred to as ‘type 1’ response), while a harsh DRW will be followed by a delayed growth recovery (‘type 2’ response). Predicting these responses based on pedoclimatic factors is important because they can determine how carbon is partitioned between growth (soil C stabilization) and respiration (C loss to the atmosphere). To characterize the microbially perceived harshness between the two extreme types 1 and 2, and its pedoclimatic drivers, we described microbial growth with a single logistic function and respiration with a rescaled gamma distribution using ∼100 growth and respiration datasets. These functions captured microbial growth and respiration rates well during the recovery phase after rewetting. Therefore, the fitted parameters from these functions could help us to capture the continuum of microbial recovery between type 1 and 2 and characterize harshness levels. The product of growth parameters τ (delay time) and b (the slope of the growth curve at time τ) was an effective index that could capture and quantify perceived harshness because it allowed separating type 1 and 2 responses better than τ or b alone or than any other parameter describing the growth or respiration response. The drier the soil before rewetting and the lower the pH, the higher was the perceived harshness (τ×b), the longer the delay of growth recovery, and the larger the CO2 loss at rewetting. Overall, this study places soil microbial responses to DRW along a continuous gradient from fast to slow recovery, where the faster the recovery, the better adapted the microbial community is to the DRW event.
Soil organic carbon models need independent time-series validation for reliable prediction
2023. Julia Le Noë (et al.). Communications Earth & Environment 4 (1)Article
Numerical models are crucial to understand and/or predict past and future soil organic carbon dynamics. For those models aiming at prediction, validation is a critical step to gain confidence in projections. With a comprehensive review of ~250 models, we assess how models are validated depending on their objectives and features, discuss how validation of predictive models can be improved. We find a critical lack of independent validation using observed time series. Conducting such validations should be a priority to improve the model reliability. Approximately 60% of the models we analysed are not designed for predictions, but rather for conceptual understanding of soil processes. These models provide important insights by identifying key processes and alternative formalisms that can be relevant for predictive models. We argue that combining independent validation based on observed time series and improved information flow between predictive and conceptual models will increase reliability in predictions.
Optimal plant water use strategies explain soil moisture variability
2023. Maoya Bassiouni, Stefano Manzoni, Giulia Vico. Advances in Water Resources 173Article
Plant responses to water stress influence water and carbon cycles and can lead to feedbacks on climate yet characterizing these responses at ecosystem levels remains uncertain. Quantifying ecosystem-level water use strategies is complex due to challenges of upscaling plant traits and disentangling confounding environmental factors, ultimately limiting our ability to understand and anticipate global change in ecosystem dynamics and ecohydrological fluxes. We reduce the dimensionality of this problem and quantify plant water use strategies by combining plant traits with soil and climate variables into parameter groups that synthesize key eco-physiological tradeoffs. Using a parsimonious soil water balance framework, we explore variations in plant water uptake capacity, water stress responses, and water use performance via these non-dimensional parameter groups. The group characterizing the synchronization of plant water transport and atmospheric water demand emerges as the primary axis of variation in water use strategies and interacts with the group representing plant hydraulic risk tolerance, especially in arid conditions when plant water transport is limiting. Next, we show that specific plant water use strategies maximize plant water uptake (leading to carbon gain benefits) weighted by risks of water stress (leading to higher costs of water use). A model-data comparison demonstrates that these ecohydrologically optimal parameter groups capture observed soil moisture variability in 40 ecosystems and beyond aridity, rainfall frequency is an important environmental control for plant water use strategies. The emerging parsimonious link between ecohydrological performance and non-dimensional parameters provides a tractable representation of plant water use strategies, relevant to parameterize global models while accounting for ecological and evolutionary constraints on the water cycle.
Climate-dependent responses of root and shoot biomass to drought duration and intensity in grasslands–a meta-analysis
2023. Daniela Guasconi, Stefano Manzoni, Gustaf Hugelius. Science of the Total Environment 903Article
Understanding the effects of altered precipitation regimes on root biomass in grasslands is crucial for predicting grassland responses to climate change. Nonetheless, studies investigating the effects of drought on belowground vegetation have produced mixed results. In particular, root biomass under reduced precipitation may increase, decrease or show a delayed response compared to shoot biomass, highlighting a knowledge gap in the relationship between belowground net primary production and drought. To address this gap, we conducted a meta-analysis of nearly 100 field observations of grassland root and shoot biomass changes under experimental rainfall reduction to disentangle the main drivers behind grassland responses to drought. Using a response-ratio approach we tested the hypothesis that water scarcity would induce a decrease in total biomass, but an increase in belowground biomass allocation with increased drought length and intensity, and that climate (as defined by the aridity index of the study location) would be an additional predictor. As expected, meteorological drought decreased root and shoot biomass, but aboveground and belowground biomass exhibited contrasting responses to drought duration and intensity, and their interaction with climate. In particular, drought duration had negative effects on root biomass only in wet climates while more intense drought had negative effects on root biomass only in dry climates. Shoot biomass responded negatively to drought duration regardless of climate. These results show that long-term climate is an important modulator of belowground vegetation responses to drought, which might be a consequence of different drought tolerance and adaptation strategies. This variability in vegetation responses to drought suggests that physiological plasticity and community composition shifts may mediate how climate affects carbon allocation in grasslands, and thus ultimately carbon storage in soil.
When dry soil is re-wet, trehalose is respired instead of supporting microbial growth
2023. Charles R. Warren, Stefano Manzoni. Soil Biology and Biochemistry 184Article
When dry soil is re-wet there is a rapid increase in CO2 efflux and rates can remain above those of well-watered controls for one or more days. These large pulses of CO2 efflux are known as the `Birch effect. To provide experimental evidence of different pools of C fuelling the Birch effect, we incubated a drying soil with 13C6glucose, re wet the soil and quantified 13C labelling of pools (microbial biomass, trehalose, extracellular, and old C) and soil CO2 efflux. We took advantage of trehalose being the most 13C-enriched pool (& delta;13C = +518%o) to obtain direct isotopic evidence of trehalose's contribution to respiration and microbial growth. For soil incubated with 13C6-glucose, the & delta;13C of soil respiration was +35%o in dry soil, increased to 100%o in the 10 min following rewetting, and subsequently decreased. During the first 5 h after re-wetting, trehalose must have been contributing to respiration given that & delta;13C of soil respiration was more 13C enriched than trehalose-free microbial biomass (& delta;13C = +30%o), extracellular C (& delta;13C = -17.7%o), and old C (& delta;13C = -22.9%o). A four-member isotopic mixing model suggested trehalose underpinned 16% of respiration in the 1st hour after rewetting, decreasing to 7% in the fifth hour. At times beyond 5 h after rewetting, trehalose underpinned 0-4% of respiration. In the seven days following rewetting, microbial biomass increased 2292 nmol C g-1. Isotopic mass balance indicated trehalose-C could account for no more than 5% of the gross influx of C into microbial biomass, instead the increase in microbial biomass was fuelled by unlabelled or weakly labelled pools such as old C and extracellular C. Collectively these data provide direct experimental evidence C from trehalose does not significantly contribute to microbial growth in re-wet soil, but instead contributes to respiration for the first 5 h after rewetting.
Primary production in subsidized green-brown food webs
2023. Yuval R. Zelnik, Stefano Manzoni, Riccardo Bommarco. Frontiers in Ecology and Evolution 11Article
Ecosystems worldwide receive large amounts of nutrients from both natural processes and human activities. While direct subsidy effects on primary production are relatively well-known (the green food web), the indirect effects of subsidies on producers as mediated by the brown food web and predators are poorly considered. With a dynamical green-brown food web model, parameterized using empirical estimates from the literature, we illustrate the effect of organic and inorganic nutrient subsidies on net primary production (NPP) (i.e., after removing loss to herbivory) in two idealized ecosystems—one terrestrial and one aquatic. We find that nutrient subsidies increase net primary production, an effect that saturates with increasing subsidies. Changing the quality of subsidies from inorganic to organic tends to increase net primary production in terrestrial ecosystems, but less often so in aquatic ecosystems. This occurs when organic nutrient inputs promote detritivores in the brown food web, and hence predators that in turn regulate herbivores, thereby promoting primary production. This previously largely overlooked effect is further enhanced by ecosystem properties such as fast decomposition and low rates of nutrient additions and demonstrates the importance of nutrient subsidy quality on ecosystem functioning.
Interacting Bioenergetic and Stoichiometric Controls on Microbial Growth
2022. Arjun Chakrawal (et al.). Frontiers in Microbiology 13Article
Microorganisms function as open systems that exchange matter and energy with their surrounding environment. Even though mass (carbon and nutrients) and energy exchanges are tightly linked, there is a lack of integrated approaches that combine these fluxes and explore how they jointly impact microbial growth. Such links are essential to predicting how the growth rate of microorganisms varies, especially when the stoichiometry of carbon- (C) and nitrogen (N)-uptake is not balanced. Here, we present a theoretical framework to quantify the microbial growth rate for conditions of C-, N-, and energy-(co-) limitations. We use this framework to show how the C:N ratio and the degree of reduction of the organic matter (OM), which is also the electron donor, availability of electron acceptors (EAs), and the different sources of N together control the microbial growth rate under C, nutrient, and energy-limited conditions. We show that the growth rate peaks at intermediate values of the degree of reduction of OM under oxic and C-limited conditions, but not under N-limited conditions. Under oxic conditions and with N-poor OM, the growth rate is higher when the inorganic N (NInorg)-source is ammonium compared to nitrate due to the additional energetic cost involved in nitrate reduction. Under anoxic conditions, when nitrate is both EA and NInorg-source, the growth rates of denitrifiers and microbes performing the dissimilatory nitrate reduction to ammonia (DNRA) are determined by both OM degree of reduction and nitrate-availability. Consistent with the data, DNRA is predicted to foster growth under extreme nitrate-limitation and with a reduced OM, whereas denitrifiers are favored as nitrate becomes more available and in the presence of oxidized OM. Furthermore, the growth rate is reduced when catabolism is coupled to low energy yielding EAs (e.g., sulfate) because of the low carbon use efficiency (CUE). However, the low CUE also decreases the nutrient demand for growth, thereby reducing N-limitation. We conclude that bioenergetics provides a useful conceptual framework for explaining growth rates under different metabolisms and multiple resource-limitations.
Drought Legacy in Sub-Seasonal Vegetation State and Sensitivity to Climate Over the Northern Hemisphere
2022. Minchao Wu (et al.). Geophysical Research Letters 49 (15)Article
Droughts affect ecosystems at multiple time scales, but their sub-seasonal legacy effects on vegetation activity remain unclear. Combining the satellite-based enhanced vegetation index MODIS EVI with a novel location-specific definition of the growing season, we quantify drought impacts on sub-seasonal vegetation activity and the subsequent recovery in the Northern Hemisphere. Drought legacy effects are quantified as changes in post-drought greenness and sensitivity to climate. We find that greenness losses under severe drought are partially compensated by a ∼+5% greening within 2–6 growing-season months following the droughts, both in woody and herbaceous vegetation but at different timings. In addition, post-drought sensitivity of herbaceous vegetation to hydrological conditions increases noticeably at high latitudes compared with the local normal conditions, regardless of the choice of drought time scales. In general, the legacy effects on sensitivity are larger in herbaceous vegetation than in woody vegetation.
Consistent responses of vegetation gas exchange to elevated atmospheric CO2 emerge from heuristic and optimization models
2022. Stefano Manzoni (et al.). Biogeosciences 19 (17), 4387-4414Article
Elevated atmospheric CO2 concentration is expected to increase leaf CO2 assimilation rates, thus promoting plant growth and increasing leaf area. It also decreases stomatal conductance, allowing water savings, which have been hypothesized to drive large-scale greening, in particular in arid and semiarid climates. However, the increase in leaf area could reduce the benefits of elevated CO2 concentration through soil water depletion. The net effect of elevated CO2 on leaf- and canopy-level gas exchange remains uncertain. To address this question, we compare the outcomes of a heuristic model based on the Partitioning of Equilibrium Transpiration and Assimilation (PETA) hypothesis and three model variants based on stomatal optimization theory. Predicted relative changes in leaf- and canopy-level gas exchange rates are used as a metric of plant responses to changes in atmospheric CO2 concentration. Both model approaches predict reductions in leaf-level transpiration rate due to decreased stomatal conductance under elevated CO2, but negligible (PETA) or no (optimization) changes in canopy-level transpiration due to the compensatory effect of increased leaf area. Leaf- and canopy-level CO2 assimilation is predicted to increase, with an amplification of the CO2 fertilization effect at the canopy level due to the enhanced leaf area. The expected increase in vapour pressure deficit (VPD) under warmer conditions is generally predicted to decrease the sensitivity of gas exchange to atmospheric CO2 concentration in both models. The consistent predictions by different models that canopylevel transpiration varies little under elevated CO2 due to combined stomatal conductance reduction and leaf area increase highlight the coordination of physiological and morphological characteristics in vegetation to maximize resource use (here water) under altered climatic conditions.
Dryland productivity under a changing climate
2022. Lixin Wang (et al.). Nature Climate Change 12 (11), 981-994Article
Understanding dryland dynamics is essential to predict future climate trajectories. However, there remains large uncertainty on the extent to which drylands are expanding or greening, the drivers of dryland vegetation shifts, the relative importance of different hydrological processes regulating ecosystem functioning, and the role of land-use changes and climate variability in shaping ecosystem productivity. We review recent advances in the study of dryland productivity and ecosystem function and examine major outstanding debates on dryland responses to environmental changes. We highlight often-neglected uncertainties in the observation and prediction of dryland productivity and elucidate the complexity of dryland dynamics. We suggest prioritizing holistic approaches to dryland management, accounting for the increasing climatic and anthropogenic pressures and the associated uncertainties.
Energetic scaling in microbial growth
2021. Salvatore Calabrese (et al.). Proceedings of the National Academy of Sciences of the United States of America 118 (47)Article
Microbial growth is a clear example of organization and structure arising in nonequilibrium conditions. Due to the complexity of the microbial metabolic network, elucidating the fundamental principles governing microbial growth remains a challenge. Here, we present a systematic analysis of microbial growth thermodynamics, leveraging an extensive dataset on energy-limited monoculture growth. A consistent thermodynamic framework based on reaction stoichiometry allows us to quantify how much of the available energy microbes can efficiently convert into new biomass while dissipating the remaining energy into the environment and producing entropy. We show that dissipation mechanisms can be linked to the electron donor uptake rate, a fact leading to the central result that the thermodynamic efficiency is related to the electron donor uptake rate by the scaling law eta proportional to M-1/2 ED and to the growth yield by eta proportional to Y4/5. These findings allow us to rederive the Pirt equation from a thermodynamic perspective, providing a means to compute its coefficients, as well as a deeper understanding of the relationship between growth rate and yield. Our results provide rather general insights into the relation between mass and energy conversion in microbial growth with potentially wide application, especially in ecology and biotechnology.
Leveraging energy flows to quantify microbial traits in soils
2021. Arjun Chakrawal, Anke M. Herrmann, Stefano Manzoni. Soil Biology and Biochemistry 155Article
Heat dissipation from organic matter decomposition is a well-recognized proxy for microbial activity in soils, but only a few modeling studies have used heat signals to quantify microbial traits such as maximum substrate uptake rate, specific growth rate, mortality rate, and growth efficiency. In this contribution, a hierarchy of coupled mass-energy balance models is proposed to estimate microbial traits encoded in model parameters using heat dissipation and respiration data from glucose induced microbial activity. Moreover, the models are used to explain the observed variability in calorespirometric ratios (CR)-the ratio of heat dissipation to respiration rate. We parametrized four model variants using heat dissipation and respiration rates measured in an isothermal calorimeter during the lag-phase only or during the whole growth-phase. The four variants are referred to as: (i) complex physiological model, (ii) simplified physiological model, (iii) lag-phase model, and (iv) growth-phase model. Model parameters were determined using three combinations of data: A) only the heat dissipation rate, B) only the respiration rate, and C) both heat dissipation and respiration rates. We assumed that the 'best' parameter estimates were those obtained when using all the data (i.e., option C). All model variants were able to fit the observed heat dissipation and respiration rates. The parameters estimated using only heat dissipation data were similar to the 'best' estimates compared to using only respiration rate data, suggesting that the observed heat dissipation rate can be used to constrain microbial models and estimate microbial traits. However, the observed variability in CR was not well captured by some model variants such as the simplified physiological model, in contrast to the lag- and growth-phase model that predicted CR well. This suggests that CR can be used to scrutinize how well metabolic processes are represented in decomposition models.
Persistence of soil organic carbon caused by functional complexity
2020. Johannes Lehmann (et al.). Nature Geoscience 13, 529-534Article
Soil organic carbon management has the potential to aid climate change mitigation through drawdown of atmospheric carbon dioxide. To be effective, such management must account for processes influencing carbon storage and re-emission at different space and time scales. Achieving this requires a conceptual advance in our understanding to link carbon dynamics from the scales at which processes occur to the scales at which decisions are made. Here, we propose that soil carbon persistence can be understood through the lens of decomposers as a result of functional complexity derived from the interplay between spatial and temporal variation of molecular diversity and composition. For example, co-location alone can determine whether a molecule is decomposed, with rapid changes in moisture leading to transport of organic matter and constraining the fitness of the microbial community, while greater molecular diversity may increase the metabolic demand of, and thus potentially limit, decomposition. This conceptual shift accounts for emergent behaviour of the microbial community and would enable soil carbon changes to be predicted without invoking recalcitrant carbon forms that have not been observed experimentally. Functional complexity as a driver of soil carbon persistence suggests soil management should be based on constant care rather than one-time action to lock away carbon in soils. Dynamic interactions between chemical and biological controls govern the stability of soil organic carbon and drive complex, emergent patterns in soil carbon persistence.
Organizing principles for vegetation dynamics
2020. Oskar Franklin (et al.). Nature plants 6 (5), 444-453Article
Plants and vegetation play a critical-but largely unpredictable-role in global environmental changes due to the multitude of contributing processes at widely different spatial and temporal scales. In this Perspective, we explore approaches to master this complexity and improve our ability to predict vegetation dynamics by explicitly taking account of principles that constrain plant and ecosystem behaviour: natural selection, self-organization and entropy maximization. These ideas are increasingly being used in vegetation models, but we argue that their full potential has yet to be realized. We demonstrate the power of natural selection-based optimality principles to predict photosynthetic and carbon allocation responses to multiple environmental drivers, as well as how individual plasticity leads to the predictable self-organization of forest canopies. We show how models of natural selection acting on a few key traits can generate realistic plant communities and how entropy maximization can identify the most probable outcomes of community dynamics in space- and time-varying environments. Finally, we present a roadmap indicating how these principles could be combined in a new generation of models with stronger theoretical foundations and an improved capacity to predict complex vegetation responses to environmental change. Integrating natural selection and other organizing principles into next-generation vegetation models could render them more theoretically sound and useful for earth system applications and modelling climate impacts.
A plant-microbe interaction framework explaining nutrient effects on primary production
2018. P. T. Capek (et al.). Nature Ecology & Evolution 2 (10), 1588-1596Article
In most terrestrial ecosystems, plant growth is limited by nitrogen and phosphorus. Adding either nutrient to soil usually affects primary production, but their effects can be positive or negative. Here we provide a general stoichiometric framework for interpreting these contrasting effects. First, we identify nitrogen and phosphorus limitations on plants and soil microorganisms using their respective nitrogen to phosphorus critical ratios. Second, we use these ratios to show how soil microorganisms mediate the response of primary production to limiting and non-limiting nutrient addition along a wide gradient of soil nutrient availability. Using a meta-analysis of 51 factorial nitrogen-phosphorus fertilization experiments conducted across multiple ecosystems, we demonstrate that the response of primary production to nitrogen and phosphorus additions is accurately predicted by our stoichiometric framework. The only pattern that could not be predicted by our original framework suggests that nitrogen has not only a structural function in growing organisms, but also a key role in promoting plant and microbial nutrient acquisition. We conclude that this stoichiometric framework offers the most parsimonious way to interpret contrasting and, until now, unresolved responses of primary production to nutrient addition in terrestrial ecosystems.