Phenology and allocation of belowground plant carbon at local to global scales

Forests play an important role in mitigating climate change by removing carbon dioxide (CO2) from the atmosphere via photosynthesis and storing it in plant tissues and soil organic matter (SOM). Plant roots are a major conduit for transporting recently fixed CO2 belowground, where carbon (C) remains in SOM or returns to the atmosphere via respiration of soil microbes. Compared to aboveground plant processes related to the C cycle, there is little understanding of how belowground plant-C allocation to roots, symbiotic root fungi and secretions into the soil influence the gain or loss of C from the soil. Further, the uncertainty in the timing and amount of root growth that occurs in forests is a barrier to understanding how root activity responds to global change and feeds back to the C cycle. Therefore, the objective of my research is to quantify the timing and magnitude of C allocation to roots and soil via data compilation, field studies and modeling across broad spatial scales. Using data compilation at the global scale, I show that root and shoot phenology are often asynchronous and that evergreen trees commonly have later root growth compared to deciduous trees using meta-analysis across four biomes. At the plot scale, field studies in a mid-latitude forest demonstrate that deciduous stands allocate more C belowground earlier in the growing season compared to a conifer stand. The difference in phenology between stands can be attributed to the timing of root growth. At the root scale, zymographic analysis demonstrates that microbial extracellular enzyme activity is concentrated near the surface of roots and that the rhizosphere can extend well beyond 2 mm from the root surface. Finally, I developed a new model of microbial physiology and extracellular enzyme activity to assess how climate change may affect plant - microbe interactions and soil organic matter decomposition. I show that increases in temperature and the quantity of C inputs substantially alter decomposition. Collectively, these results demonstrate the importance of belowground allocation to the C cycle of terrestrial ecosystems

Soil organic carbon models need independent time-series validation for reliable prediction

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

How does management affect soil C sequestration and greenhouse gas fluxes in boreal and temperate forests? : A review

Acknowledgements 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.Peer reviewedPublisher PD

Reviews and syntheses: The promise of big diverse soil data, moving current practices towards future potential

In the age of big data, soil data are more available and richer than ever, but – outside of a few large soil survey resources – they remain largely unusable for informing soil management and understanding Earth system processes beyond the original study. Data science has promised a fully reusable research pipeline where data from past studies are used to contextualize new findings and reanalyzed for new insight. Yet synthesis projects encounter challenges at all steps of the data reuse pipeline, including unavailable data, labor-intensive transcription of datasets, incomplete metadata, and a lack of communication between collaborators. Here, using insights from a diversity of soil, data, and climate scientists, we summarize current practices in soil data synthesis across all stages of database creation: availability, input, harmonization, curation, and publication. We then suggest new soil-focused semantic tools to improve existing data pipelines, such as ontologies, vocabulary lists, and community practices. Our goal is to provide the soil data community with an overview of current practices in soil data and where we need to go to fully leverage big data to solve soil problems in the next century

First molar size and wear within and among modern hunter-gatherers and agricultural populations

Apart from reflecting modern human dental variation, differences in dental size among populations provide a means for studying continuous evolutionary processes and their mechanisms. Dental wear, on the other hand, has been widely used to infer dietary adaptations and variability among or within diverse ancient human populations. Few such studies have focused on modern foragers and farmers, however, and diverse methods have been used. This research aimed to apply a single, standardized, and systematic quantitative procedure to measure dental size and dentin exposure in order to analyze differences among several hunter-gatherer and agricultural populations from various environments and geographic origins. In particular, we focused on sexual dimorphism and intergroup differences in the upper and lower first molars. Results indicated no sexual dimorphism in molar size and wear within the studied populations. Despite the great ethnographic variation in subsistence strategies among these populations, our findings suggest that differences in sexual division of labor do not affect dietary wear patterns.The study was funded by grants CGL2010-15340 and CGL2011-22999 (Ministerio de Educación y Ciencia de España) to APP

The Three-Dimensional Distribution of αA-Crystalline in Rat Lenses and Its Possible Relation to Transparency

Lens transparency depends on the accumulation of massive quantities (600–800 mg/ml) of twelve primary crystallines and two truncated crystallines in highly elongated “fiber” cells. Despite numerous studies, major unanswered questions are how this heterogeneous group of proteins becomes organized to bestow the lens with its unique optical properties and how it changes during cataract formation. Using novel methods based on conical tomography and labeling with antibody/gold conjugates, we have profiled the 3D-distribution of the αA-crystalline in rat lenses at ∼2 nm resolutions and three-dimensions. Analysis of tomograms calculated from lenses labeled with anti-αA-crystalline and gold particles (∼3 nm and ∼7 nm diameter) revealed geometric patterns shaped as lines, isosceles triangles and polyhedrons. A Gaussian distribution centered at ∼7.5 nm fitted the distances between the ∼3 nm diameter gold conjugates. A Gaussian distribution centered at ∼14 nm fitted the Euclidian distances between the smaller and the larger gold particles and another Gaussian at 21–24 nm the distances between the larger particles. Independent of their diameters, tethers of 14–17 nm in length connected files of gold particles to thin filaments or clusters to ∼15 nm diameter “beads.” We used the information gathered from tomograms of labeled lenses to determine the distribution of the αA-crystalline in unlabeled lenses. We found that αA-crystalline monomers spaced ∼7 nm or αA-crystalline dimers spaced ∼15 nm center-to-center apart decorated thin filaments of the lens cytoskeleton. It thus seems likely that lost or gain of long-range order determines the 3D-structure of the fiber cell and possible also cataract formation

SdrF, a Staphylococcus epidermidis Surface Protein, Contributes to the Initiation of Ventricular Assist Device Driveline–Related Infections

Staphylococcus epidermidis remains the predominant pathogen in prosthetic-device infections. Ventricular assist devices, a recently developed form of therapy for end-stage congestive heart failure, have had considerable success. However, infections, most often caused by Staphylococcus epidermidis, have limited their long-term use. The transcutaneous driveline entry site acts as a potential portal of entry for bacteria, allowing development of either localized or systemic infections. A novel in vitro binding assay using explanted drivelines obtained from patients undergoing transplantation and a heterologous lactococcal system of surface protein expression were used to identify S. epidermidis surface components involved in the pathogenesis of driveline infections. Of the four components tested, SdrF, SdrG, PIA, and GehD, SdrF was identified as the primary ligand. SdrF adherence was mediated via its B domain attaching to host collagen deposited on the surface of the driveline. Antibodies directed against SdrF reduced adherence of S. epidermidis to the drivelines. SdrF was also found to adhere with high affinity to Dacron, the hydrophobic polymeric outer surface of drivelines. Solid phase binding assays showed that SdrF was also able to adhere to other hydrophobic artificial materials such as polystyrene. A murine model of infection was developed and used to test the role of SdrF during in vivo driveline infection. SdrF alone was able to mediate bacterial adherence to implanted drivelines. Anti-SdrF antibodies reduced S. epidermidis colonization of implanted drivelines. SdrF appears to play a key role in the initiation of ventricular assist device driveline infections caused by S. epidermidis. This pluripotential adherence capacity provides a potential pathway to infection with SdrF-positive commensal staphylococci first adhering to the external Dacron-coated driveline at the transcutaneous entry site, then spreading along the collagen-coated internal portion of the driveline to establish a localized infection. This capacity may also have relevance for other prosthetic device–related infections

Structural Elucidation and Functional Characterization of the Hyaloperonospora arabidopsidis Effector Protein ATR13

The oomycete Hyaloperonospora arabidopsidis (Hpa) is the causal agent of downy mildew on the model plant Arabidopsis thaliana and has been adapted as a model system to investigate pathogen virulence strategies and plant disease resistance mechanisms. Recognition of Hpa infection occurs when plant resistance proteins (R-genes) detect the presence or activity of pathogen-derived protein effectors delivered to the plant host. This study examines the Hpa effector ATR13 Emco5 and its recognition by RPP13-Nd, the cognate R-gene that triggers programmed cell death (HR) in the presence of recognized ATR13 variants. Herein, we use NMR to solve the backbone structure of ATR13 Emco5, revealing both a helical domain and a disordered internal loop. Additionally, we use site-directed and random mutagenesis to identify several amino acid residues involved in the recognition response conferred by RPP13-Nd. Using our structure as a scaffold, we map these residues to one of two surface-exposed patches of residues under diversifying selection. Exploring possible roles of the disordered region within the ATR13 structure, we perform domain swapping experiments and identify a peptide sequence involved in nucleolar localization. We conclude that ATR13 is a highly dynamic protein with no clear structural homologues that contains two surface-exposed patches of polymorphism, only one of which is involved in RPP13-Nd recognition specificity

Amyloid-β Triggers the Release of Neuronal Hexokinase 1 from Mitochondria

Brain accumulation of the amyloid-β peptide (Aβ) and oxidative stress underlie neuronal dysfunction and memory loss in Alzheimer's disease (AD). Hexokinase (HK), a key glycolytic enzyme, plays important pro-survival roles, reducing mitochondrial reactive oxygen species (ROS) generation and preventing apoptosis in neurons and other cell types. Brain isozyme HKI is mainly associated with mitochondria and HK release from mitochondria causes a significant decrease in enzyme activity and triggers oxidative damage. We here investigated the relationship between Aβ-induced oxidative stress and HK activity. We found that Aβ triggered HKI detachment from mitochondria decreasing HKI activity in cortical neurons. Aβ oligomers further impair energy metabolism by decreasing neuronal ATP levels. Aβ-induced HKI cellular redistribution was accompanied by excessive ROS generation and neuronal death. 2-deoxyglucose blocked Aβ-induced oxidative stress and neuronal death. Results suggest that Aβ-induced cellular redistribution and inactivation of neuronal HKI play important roles in oxidative stress and neurodegeneration in AD