• Energy Research

Grasslands are important in sub-boreal climate agricultural systems and are managed with various combinations of N fertilization and plant species. Ammonia-oxidizing and denitrifying microorganisms are key players in determining the fate of nitrogen (N) and thereby also the yield in grassland systems and their impact on gaseous N losses and leaching. We established a three-year field study in southern Finland with fertilizer treatment as a main-plot factor, including organic and synthetic fertilizers and plant species and mixtures thereof as the sub-plot factor. We quantified six genes encoding key N-cycling enzymes by quantitative PCR to determine the abundance of the communities involved in N-transformation processes and also included previously published data on crop yield, soil properties and the overall bacterial community composition. With the exception of ammonia oxidizing bacteria (AOB), which were primarily affected by fertilization, the abundances of all other N-cycling communities changed over time with either an increase or decrease from summer to autumn. Differences in gene abundances between plant species treatments and in fertilizer by plant species interactions were detected mainly in the beginning of the cropping season during the first year. The nirS-type denitrifiers and nosZII nitrous oxide reducers responded more to changes in soil properties than their functional counterpart nirK and nosZI communities. Using structural equation modeling, we show that the overall microbial community composition and diversity played an important role in mediating the management effects on crop yield, genetic potential for N retention and N2O sink capacity. However, a trade-off between the genetic potential for N retention and N2O sink capacity was detected, indicating the challenges in managing grasslands in a sustainable way.ER - Grasslands are important in sub-boreal climate agricultural systems and are managed with various combinations of N fertilization and plant species. Ammonia-oxidizing and denitrifying microorganisms are key players in determining the fate of nitrogen (N) and thereby also the yield in grassland systems and their impact on gaseous N losses and leaching. We established a three-year field study in southern Finland with fertilizer treatment as a main-plot factor, including organic and synthetic fertilizers and plant species and mixtures thereof as the sub-plot factor. We quantified six genes encoding key N-cycling enzymes by quantitative PCR to determine the abundance of the communities involved in N-transformation processes and also included previously published data on crop yield, soil properties and the overall bacterial community composition. With the exception of ammonia oxidizing bacteria (AOB), which were primarily affected by fertilization, the abundances of all other N-cycling communities changed over time with either an increase or decrease from summer to autumn. Differences in gene abundances between plant species treatments and in fertilizer by plant species interactions were detected mainly in the beginning of the cropping season during the first year. The nirS-type denitrifiers and nosZII nitrous oxide reducers responded more to changes in soil properties than their functional counterpart nirK and nosZI communities. Using structural equation modeling, we show that the overall microbial community composition and diversity played an important role in mediating the management effects on crop yield, genetic potential for N retention and N2O sink capacity. However, a trade-off between the genetic potential for N retention and N2O sink capacity was detected, indicating the challenges in managing grasslands in a sustainable way.

Abstract Background Global biodiversity is rapidly declining, yet we still do not fully understand the relationships between biodiversity and human health and well-being. As debated, the loss of biodiversity or reduced contact with natural biodiversity may lead to more public health problems, such as an increase in chronic disease. There is a growing body of research that investigates how multiple forms of biodiversity are associated with an increasingly diverse set of human health and well-being outcomes across scales. This protocol describes the intended method to systematically mapping the evidence on the associations between biodiversity from microscopic to planetary scales and human health and well-being from individual to global scales. Methods We will systematically map secondary studies on the topic by following the Collaborations for Environmental Evidence Guidelines and Standards for Evidence Synthesis in Environment Management. We developed the searching strings to target both well established and rarely studied forms of biodiversity and human health and well-being outcomes in the literature. A pairwise combination search of biodiversity and human health subtopics will be conducted in PubMed, Web of Science platform (across four databases) and Scopus with no time restrictions. To improve the screening efficiency in EPPI reviewer, supervised machine learning, such as a bespoke classification model, will be trained and applied at title and abstract screening stage. A consistency check between at least two independent reviewers will be conducted during screening (both title-abstract and full-text) and data extraction process. No critical appraisal will be undertaken in this map. We may use topic modelling (unsupervised machine learning) to cluster the topics as a basis for further statistical and narrative analysis.

The global forest carbon (C) stock is estimated at 662 Gt of which 45% is in soil organic matter. Thus, comprehensive understanding of the effects of forest management practices on forest soil C stock and greenhouse gas (GHG) fluxes is needed for the development of effective forest-based climate change mitigation strategies. To improve this understanding, we synthesized peer-reviewed literature on forest management practices that can mitigate climate change by increasing soil C stocks and reducing GHG emissions. We further identified soil processes that affect soil GHG balance and discussed how models represent forest management effects on soil in GHG inventories and scenario analyses to address forest climate change mitigation potential. Forest management effects depend strongly on the specific practice and land type. Intensive timber harvesting with removal of harvest residues/stumps results in a reduction in soil C stock, while high stocking density and enhanced productivity by fertilization or dominance of coniferous species increase soil C stock. Nitrogen fertilization increases the soil C stock and N2O emissions while decreasing the CH4 sink. Peatland hydrology management is a major driver of the GHG emissions of the peatland forests, with lower water level corresponding to higher CO2 emissions. Furthermore, the global warming potential of all GHG emissions (CO2, CH4 and N2O) together can be ten-fold higher after clear-cutting than in peatlands with standing trees. The climate change mitigation potential of forest soils, as estimated by modelling approaches, accounts for stand biomass driven effects and climate factors that affect the decomposition rate. A future challenge is to account for the effects of soil preparation and other management that affects soil processes by changing soil temperature, soil moisture, soil nutrient balance, microbial community structure and processes, hydrology and soil oxygen concentration in the models. We recommend that soil monitoring and modelling focus on linking processes of soil C stabilization with the functioning of soil microbiota. This review has been supported by the grant Holistic management practices, modelling and monitoring for European forest soils – HoliSoils (EU Horizon 2020 Grant Agreement No 101000289) and the Academy of Finland Fellow project (330136, B. Adamczyk). In addition to the HoliSoils consortium partners, Dr. Abramoff contributed on this study and her work was supported by the United States Department of Energy, Office of Science, Office of Biological and Environmental Research. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the United States Department of Energy under contract DE-AC05-00OR22725.