Periodic Reporting for period 2 - SMILE (Soil MIcrobial responses to land use and climatic changes in the Light of Evolution)
Reporting period: 2022-11-01 to 2024-04-30
Soil microorganisms are responsible for a large fraction of greenhouse gas emissions from terrestrial ecosystems and produce most of the nutrients needed by plants to grow. They perform these important functions by decomposing organic matter, which is not easy for them to access in soil and is often not nutritionally balanced. In this project, we study soil microorganisms and the strategies they adopt to access soil resources. We hypothesize that soil microbes are such effective drivers of carbon and nutrient cycles because they have evolved to face the challenges of life in soil. In other words, they behave in the best possible way to guarantee their survival and reproduction.
We are incorporating this ecological concept into mathematical models of carbon and nutrient cycling, which now do not keep into account microbial adaptations to environmental conditions and thus cannot reliably predict how much soil organic carbon and nutrients vary due to land use or climatic changes. The newly developed models will improve the way we describe soil processes, thereby making predictions of soil responses more accurate. With this approach, we are answering the long-standing question—how are land use and climatic changes affecting soil fertility and the amount of carbon we can store in soil?
Our main objectives to answer this question are: i) determine how microorganisms adapt to varying resource and water availability in the soil and construct a new theory of microbial adaptation, ii) collect data from the scientific literature on microbial responses to soil amendments and variations in soil moisture, and create new databases with this data, iii) test the mathematical models of adaptation using the new databases and select the models that work best, and iv) assess impacts of land use and climatic changes on carbon and nutrient storage and fluxes using improved soil models that account for microbial adaptation based on the theory developed in objective i).
We are incorporating this ecological concept into mathematical models of carbon and nutrient cycling, which now do not keep into account microbial adaptations to environmental conditions and thus cannot reliably predict how much soil organic carbon and nutrients vary due to land use or climatic changes. The newly developed models will improve the way we describe soil processes, thereby making predictions of soil responses more accurate. With this approach, we are answering the long-standing question—how are land use and climatic changes affecting soil fertility and the amount of carbon we can store in soil?
Our main objectives to answer this question are: i) determine how microorganisms adapt to varying resource and water availability in the soil and construct a new theory of microbial adaptation, ii) collect data from the scientific literature on microbial responses to soil amendments and variations in soil moisture, and create new databases with this data, iii) test the mathematical models of adaptation using the new databases and select the models that work best, and iv) assess impacts of land use and climatic changes on carbon and nutrient storage and fluxes using improved soil models that account for microbial adaptation based on the theory developed in objective i).
We have developed new models of microbial adaptation focusing mostly on resource acquisition. Microorganisms need to acquire resources to grow, but by doing so they deplete their own source of substrate. Moreover, resource acquisition is costly for the microorganisms because they have to synthesize enzymes and maintain them. As a result, the timing of enzyme production needs to be tuned so that microorganisms get as much substrate as possible while avoiding unnecessary costs. While developing these new models, we have collected literature data on microbial growth and respiration after drying and rewetting, and found that fungal growth recovers faster than bacterial growth, and that in general recovery is slower in more acidic soil and after a longer dry period. A new dataset of soil carbon and nitrogen in fractions with different levels of accessibility to microorganisms has also been developed, and a new diagnostic model is used to interpret this data. We are also promoting an agenda for developing eco-evolutionary models of soils, where microbial adaptations as well as ecological processes are taken into account.
Our new models accounting for microbial adaptation can predict decomposition—the first step in soil carbon and nutrient cycles—as well as traditional models, but using fewer parameters. This means that they are more robust. These models are also helping to understand why certain compounds in plant residues are decomposed sooner than others, and when and why microorganisms alter their carbon-use efficiency—the fraction of carbon consumed that microorganisms convert in new biomass. This efficiency is crucial for understanding carbon stabilization in soil. In fact, through collaborative work, we found that microbial carbon-use efficiency is the most important parameter to determine global soil carbon stocks. Other collaborations led to the discovery of dynamic storage of carbon and nutrients within microbial cells along gradients of soil fertility—this finding could revolutionize the way we conceptualize microbial processes in soils, and points to gaps in our mathematical models that we have just started to fill.
We expect to continue with model development and testing, and plan to implement our mathematical models of adaptation in operational soil and ecosystem models. Work on adaptation in complex microbial communities has also started. The new databases (responses to rewetting; dynamics of carbon and nitrogen in soil fractions) are almost complete and will be made public.
We expect to continue with model development and testing, and plan to implement our mathematical models of adaptation in operational soil and ecosystem models. Work on adaptation in complex microbial communities has also started. The new databases (responses to rewetting; dynamics of carbon and nitrogen in soil fractions) are almost complete and will be made public.