Suppression of rice methane emission by sulfate deposition in simulated acid rain

Sulfate in acid rain is known to suppress methane (CH4) emissions from natural freshwater wetlands. Here we examine the possibility that CH4 emissions from rice agriculture may be similarly affected by acid rain, a major and increasing pollution problem in Asia. Our findings suggest that acid rain rates of SO2-4 deposition may help to reduce CH4 emissions from rice agriculture. Emissions from rice plants treated with simulated acid rain at levels of SO2-4 consistent with the range of deposition in Asia were reduced by 24% during the grain filling and ripening stage of the rice season which accounts for 50% of the overall CH4 that is normally emitted in a rice season. A single application of SO2-4 at a comparable level reduced CH4 emission by 43%. We hypothesize that the reduction in CH4 emission may be due to a combination of effects. The first mechanism is that the low rates of SO2-4 may be sufficient to boost yields of rice and, in so doing, may cause a reduction in root exudates to the rhizosphere, a key substrate source for methanogenesis. Decreasing a major substrate source for methanogens is also likely to intensify competition with sulfate-reducing microorganisms for whom prior SO2-4 limitation had been lifted by the simulated acid rain S deposition

Simulation model to assess the validity of the clinical portfolio diet score used in the PortfolioDiet.app for dietary self-tracking: a secondary analysis of a randomized controlled trial in hyperlipidemic adults

IntroductionThe Portfolio Diet combines cholesterol-lowering plant foods for the management of cardiovascular disease risk. However, the translation of this dietary approach into clinical practice necessitates a user-friendly method for patients to autonomously monitor their adherence.ObjectiveThis study aimed to develop and validate the clinical-Portfolio Diet Score (c-PDS) as a food-based metric to facilitate self-tracking of the Portfolio Diet.MethodsUsing a simulation model to estimate the c-PDS, the validity was assessed in a secondary analysis of a completed trial of the Portfolio Diet in 98 participants with hyperlipidemia over 6 months. Concurrent and predictive validity of the estimated c-PDS were assessed against the reference measure (weighed 7-day diet records) and concomitant changes in LDL-C from baseline to 6 months. Bland–Altman analysis was used to assess the limits of agreement between the two methods.ResultsThe c-PDS was positively correlated with dietary adherence as measured using the 7-day diet records (r = 0.94, p < 0.001). The c-PDS was negatively correlated with change in LDL-C (r = −0.43, p < 0.001) with a 1-point increase in the c-PDS being associated with a − 0.04 mmol/L (CI:−0.06,−0.03; p < 0.001) or a 1.09% reduction in LDL-C. Visual evaluation of the Bland–Altman plots showed reasonable agreement.ConclusionThese findings indicate good validity of the c-PDS for primary prevention in adults with hyperlipidemia. The predictive validity findings have informed the goals and messaging within the PortfolioDiet.app, a digital health application for delivering the Portfolio Diet. Future research will assess the effectiveness of the intended combination of the c-PDS and the PortfolioDiet.app in supporting behavior change

Discovery of 95 PTSD loci provides insight into genetic architecture and neurobiology of trauma and stress-related disorders

Posttraumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 novel). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (e.g., GRIA1, GRM8, CACNA1E ), developmental, axon guidance, and transcription factors (e.g., FOXP2, EFNA5, DCC ), synaptic structure and function genes (e.g., PCLO, NCAM1, PDE4B ), and endocrine or immune regulators (e.g., ESR1, TRAF3, TANK ). Additional top genes influence stress, immune, fear, and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation

Patterns of flammability after a sequence of mixed-severity wildfire in dry eucalypt forests of southern Australia

Fire severity is the impact of a fire on the landscape, particularly the physical impact on vegetation. Previous studies have established that the severity of a fire can be influenced by the severity of previous fires. Many of these studies were conducted in mixed-conifer forests, while little is known of this process in temperate eucalypt forests. Barker and Price in their 2018 publication (“Positive severity feedback between consecutive fires in dry eucalypt forests of southern Australia,” Ecosphere 9:e02110) found that high severity fire promotes high severity fire in eucalypt forests, but how is the severity of a fire in these systems affected by the severity of two sequential previous fires? This was investigated using remotely sensed and mapped fire severity data. We found that high severity fire is more likely after at least one previous high severity fire, regardless of its position in the sequence. A sequence of low or moderate severity fire followed by low severity fire resulted in the lowest proportion of high severity in the response fire. Our results suggest that low severity fire maintains the structure of forest fuels, so flammability remains relatively constant. A single high severity fire drives change, altering the structure and flammability of the vegetation and promoting more severe fire. However, the effects were small, so a cycle of high severity fire may be easily broken due to the influence of other variables, such as weather. Repeated high severity fire may also result in a decline in the ability of plants to recover from fire, leading to a compositional and structural change and potentially reducing the flammability of a forest

The effects of inter-fire interval on flora-fauna interactions in a sub-alpine landscape

© 2020 Elsevier B.V. Attributes of the historical fire regime can influence fauna dynamics by moderating vegetation composition and the availability of appropriate habitat. Despite this, the indirect impacts of specific aspects of the long-term fire regime are often overlooked. Here we conduct a field survey at 27 sites in sub-alpine forests of Namadgi National Park (Australia) to determine if one aspect of the historical fire regime, inter-fire interval, influences vertebrate fauna and fauna habitat. Sites were stratified between three inter-fire interval categories (20, 65–70 and 83 years between the previous two fires) in areas last burned 15-years prior to the field survey. All other environmental attributes thought to impact vegetation dynamics were controlled for in the study design. Fauna activity was monitored for four weeks using trail cameras and 15 habitat attributes were assessed using field and remote-sensing survey techniques. Most fauna and habitat variables did not differ among the inter-fire interval categories. However, mountain brush-tail possum detections increased with inter-fire interval length, with 260% more observations within the older treatment when compared with the younger treatment. Large tree density, maximum tree height, and tree canopy cover were 40%, 38% and 12% higher within the older than younger treatment, respectively. Conversely, small tree density was 78% lower within the older treatment. Our results show a limited response of fauna to historical fire-return intervals of \u3e20 years within a fire-prone forest, however also highlight that species-/habitat-specific responses do manifest via indirect effects pathways at longer fire return intervals

Framework for assessing live fine fuel loads and biomass consumption during fire

Accurate quantification of fine fuel loads (e.g. foliage and twigs) in forests is required for many fire behaviour models, and for assessing post-fire changes in carbon stocks and modelling smoke emissions. Fine fuels burn readily and are thus often targeted for fuel load assessments. Estimates of fine live fuel loads often rely on visual assessments or utilise allometric equations that relate stem diameter of plants to total above-ground biomass. Here, we develop allometric equations for shrubs that relate stem diameter to the portion of above-ground biomass comprised of fine fuel. Our study area is within the temperate eucalypt forests of south-eastern Australia. We present equations for (i) foliage; (ii) all biomass \u3c 3 mm diameter; (iii) all biomass \u3c 6 mm diameter; and (iv) all above-ground biomass. Simple power-law models were developed for five shrub species and saplings of two tree species. Models combining all species (RMSE = 0.03–0.0.06) worked similarly well to species-specific models (RMSE = 0.01–0.08). We then applied these all-species combined models to field observations of shrub stem diameters, measured before and after planned burns. In unburnt forest, the proportion of shrub biomass comprised of fine fuel varied considerably (from 6 to 58%). Fine fuel loads were positively related to total above-ground biomass (R2 = 0.75) and basal area of shrubs (R2 = 0.79). There was considerable variation in consumption of fine fuel. The median reduction in fine fuel load was 22.4%, whereas the median reduction in total above-ground biomass was only 2.3%. Our models of shrub fine fuels can be readily applied to field-based assessments or combined with existing models or remotely sensed estimates of above-ground biomass to model fine fuel loads over large heterogeneous study areas