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Gravity surveys constitute an important method for investigating the Earth's interior based on density contrasts related to Earth material differentials. Because lithology depends on the environment and the period of formation, there are generally clear boundaries between rocks with different lithologies. Inversions with convex functions for approximating the L0 norm are used to detect boundaries in reconstructed models. Optimizations can easily be found because of the convex transformations; however, the volume of the reconstructed model depends on the weighting parameter and the density constraint rather than the model sparsity. To determine and adapt the modelling size, a novel non-convex framework for gravity inversion is proposed. The proposed optimization aims to directly reduce the L0 norm of the density matrix. An improved iterative hard thresholding algorithm is developed to linearly reduce the L0 penalty during the inner iteration. Accordingly, it is possible to determine the modelling scale during the iteration and achieve an expected scale for the reconstructed model. Both simple and complex model experiments demonstrate that the proposed method efficiently reconstructs models. In addition, granites formed during the Yanshanian and Indosinian periods in the Nanling region, China, are reconstructed according to the modelling size evaluated in agreement with the magnetotelluric profile and density statistics of rock samples. The known ores occur at the contact zones between the sedimentary rocks and the reconstructed Yanshanian granites. The ore-forming bodies, periods, and processes are identified, providing guidance for further deep resource exploration in the study area.

 

Systemic Acquired Resistance (SAR) improves immunity of plant systemic tissue after local exposure to a pathogen. Guard cells that form stomatal pores on leaf surfaces recognize bacterial pathogens via pattern recognition receptors, such as Flagellin Sensitive 2 (FLS2). However, how SAR affects stomatal immunity is not known. In this study, we aim to reveal molecular mechanisms underlying the guard cell response to SAR using multi-omics of proteins, metabolites and lipids. Arabidopsis plants previously exposed to pathogenic bacteria Pseudomonas syringae pv. tomato DC3000 (Pst) exhibit an altered stomatal response compared to control plants when they are later exposed to the bacteria. Reduced stomatal apertures of SAR primed plants lead to decreased number of bacteria in leaves. Multi-omics has revealed molecular components of SAR response specific to guard cells functions, including potential roles of reactive oxygen species (ROS) and fatty acid signaling. Our results show an increase in palmitic acid and its derivative in the primed guard cells. Palmitic acid may play a role as an activator of FLS2, which initiates stomatal immune response. Improved understanding of how SAR signals affect stomatal immunity can aid biotechnology and marker-based breeding of crops for enhanced disease resistance. 

Abstract. In the global methane budget, the largest natural sourceis attributed to wetlands, which encompass all ecosystems composed ofwaterlogged or inundated ground, capable of methane production. Among them,northern peatlands that store large amounts of soil organic carbon have beenfunctioning, since the end of the last glaciation period, as long-termsources of methane (CH4) and are one of the most significant methanesources among wetlands. To reduce uncertainty of quantifying methane flux in theglobal methane budget, it is of significance to understand the underlyingprocesses for methane production and fluxes in northern peatlands. A methanemodel that features methane production and transport by plants, ebullitionprocess and diffusion in soil, oxidation to CO2, and CH4 fluxes tothe atmosphere has been embedded in the ORCHIDEE-PEAT land surface modelthat includes an explicit representation of northern peatlands.ORCHIDEE-PCH4 was calibrated and evaluated on 14 peatland sites distributedon both the Eurasian and American continents in the northern boreal andtemperate regions. Data assimilation approaches were employed to optimizedparameters at each site and at all sites simultaneously. Results show thatmethanogenesis is sensitive to temperature and substrate availability overthe top 75 cm of soil depth. Methane emissions estimated using single siteoptimization (SSO) of model parameters are underestimated by 9 g CH4 m−2 yr−1 on average (i.e., 50 % higher than the site average ofyearly methane emissions). While using the multi-site optimization (MSO),methane emissions are overestimated by 5 g CH4 m−2 yr−1 onaverage across all investigated sites (i.e., 37 % lower than the siteaverage of yearly methane emissions). 

Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO₂ fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (V_cmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r² =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r² =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r² =  0.42, MEF  =  0.14) and and net ecosystem CO₂ exchange (NEE, r² =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r² values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r² values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r² < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized V_cmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average V_cmax value. 

Urban community gardens have increased in prevalence as a means to generate fresh fruits and vegetables, including in areas lacking access to healthy food options. However, urban soils may have high levels of toxic heavy metals, including lead and cadmium and the metalloid arsenic, which can lead to severe health risks. In this study, fruit and vegetable samples grown at an urban community garden in southeastern San Diego, the Ocean View Growing Grounds, were sampled repeatedly over a four‐year time period in order to measure potential contamination of toxic heavy metals and metalloids and to develop solutions for this problem. Metal nutrient, heavy metal, and metalloid concentrations were monitored in the leaf and fruit tissues of fruit trees over the sampling period. Several of the fruit trees showed uptake of lead in the leaf samples, with Black Mission fig measuring 0.843–1.531 mg/kg dry weight and Mexican Lime measuring 1.103–1.522 mg/kg dry weight over the sampling period. Vegetables that were grown directly in the ground at this community garden and surrounding areas showed arsenic, 0.80 + 0.073 mg/kg dry weight for Swiss chard, and lead, 0.84 ± 0.404 mg/kg dry weight for strawberries, in their edible tissues. The subsequent introduction of raised beds with uncontaminated soil is described, which eliminated any detectable heavy metal or metalloid contamination in these crops during the monitoring period. Recommendations for facilitating the monitoring of edible tissues and for reducing risk are discussed, including introduction of raised beds and collaborations with local universities and research groups.