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Soil thickness is a fundamental variable in many earth science disciplines due to its critical role in many hydrological and ecological processes, but it is difficult to predict. Here we show a strong linear relationship ( r 2  = 0.87, RMSE = 0.19 m) between soil thickness and hillslope curvature across both convergent and divergent parts of the landscape at a field site in Idaho. We find similar linear relationships across diverse landscapes ( n  = 6) with the slopes of these relationships varying as a function of the standard deviation in catchment curvatures. This soil thickness-curvature approach is significantly more efficient and just as accurate as kriging-based methods, but requires only high-resolution elevation data and as few as one soil profile. Efficiently attained, spatially continuous soil thickness datasets enable improved models for soil carbon, hydrology, weathering, and landscape evolution. Soil thickness is a key parameter in earth system models, yet how it varies spatially at catchment scales is largely unknown due to measurement challenges. Here, the authors show that a continuous field of thicknesses can be predicted using high-resolution topography and a few soil thickness measurements.

Background:Arterial hypertension is a common comorbidity in patients with osteoarthritis (OA). Several antihypertensive drugs (conversion enzyme inhibitor, calcium antagonists, angiotensin receptor antagonists, beta-blokers) have been suggested to affect the course of OA progression. Furthermore some calcium antagonists were shown to inhibit hyaluronan export, loss of proteoglycans, and degradation of collagen from OA cartilage.Objectives:To evaluate whether the duration of effectiveness (DE) of viscosupplementation is prolonged in patients with knee OA treated concomitantly for arterial hypertension.Methods:Cross-sectional clinical trial (ClinicalTrials.gov Identifier: NCT04988698). All consecutive patients with knee OA who consulted in our Rheumatology department and who have been treated within the 3 last years with intra-articular hyaluronic acid injection were included. The primary outcome was the DE, self-assessed by the patients in weeks of effectiveness. The relationship between DE and the following items (demographics, disease duration, knee radiological features -Kellgren grade and involved knee compartments, comorbidities, previous and current treatments for OA and comorbidities, sport activity, number of previous viscosupplementations) were studied in bivariate and multivariate analysis.Results:105 patients (65 women, 149 treated knees) were included. Mean age and BMI were 66.1 ± 13.2 years and 27.5 kg/m2 respectively. 38% of patients were treated for AH. The average DE of viscosupplementation was 48.2 +24.8 weeks [range 0-156]. In bivariate analysis, DE was significantly longer in subjects with: BMI<27.5 (p=0.002), Kellgren-lawrence radiological grade <4 (p=0.008), active versus sedentary subjects (p=0.00 5), unicompartmental involvement (p=0.01), medial tibiofemoral joint space narrowing (p=0.046) and number of previous viscosupplementation <4. Mean DE was 53.1 ± 31.3 weeks in patients treated for arterial hypertension versus 45.4 ± 19.8 in those who were not (p=0.06), despite patients with arterial hypertension had higher BMI (29.8 versus 25.2, p=0.001) and were less active (p=0.07). In multivariate analysis arterial hypertension was highly related to a longer DE (p<0.001). The other factors independently related to a longer DE were: BMI<27.5 kg/m2 (p<0.001), unicompartmental OA (p=0.02), less than 4 previous viscosupplementations (p=0.02), active patients (p=0.027).Conclusion:The present study suggests that antihypertensive medications may increase the duration of effectiveness of viscosupplementation in patients with knee osteoarthritis. Inhibition of hyaluronan export could be an explanation. Additional studies, specially designed for this purpose, are necessary to confirm or refute these results.REFERENCES:[1] Daniilidis K, Georges P, Tibesku CO, Prehm P. Positive side effects of Ca antagonists for osteoarthritic joints-results of an in vivo pilot study. J Orthop Surg Res. 2015 Jan 9;10:1. doi: 10.1186/s13018-014-0138-8.Acknowledgements:The authors acknowledge Charlotte Bourgoin and the staff of the HNFC Clinical Research Unit for their assistanceDisclosure of Interests:Charles RAPP: None declared, Feriel BOUDIF: None declared, Thomas LOHSE: None declared, Clara DOLCI: None declared, Anne Lohse Abbvie; Jensen, Thierry CONROZIER MEDAC, LABRHA; SYMATESE; MEDAC.

Soil profiles are rarely homogeneous. Resource availability and microbial abundances typically decrease with soil depth, but microbes found in deeper horizons are still important components of terrestrial ecosystems. By studying 20 soil profiles across the United States, we documented consistent changes in soil bacterial and archaeal communities with depth. Deeper soils harbored communities distinct from those of the more commonly studied surface horizons. Most notably, we found that the candidate phylum Dormibacteraeota (formerly AD3) was often dominant in subsurface soils, and we used genomes from uncultivated members of this group to identify why these taxa are able to thrive in such resource-limited environments. Simply digging deeper into soil can reveal a surprising number of novel microbes with unique adaptations to oligotrophic subsurface conditions. While most bacterial and archaeal taxa living in surface soils remain undescribed, this problem is exacerbated in deeper soils, owing to the unique oligotrophic conditions found in the subsurface. Additionally, previous studies of soil microbiomes have focused almost exclusively on surface soils, even though the microbes living in deeper soils also play critical roles in a wide range of biogeochemical processes. We examined soils collected from 20 distinct profiles across the United States to characterize the bacterial and archaeal communities that live in subsurface soils and to determine whether there are consistent changes in soil microbial communities with depth across a wide range of soil and environmental conditions. We found that bacterial and archaeal diversity generally decreased with depth, as did the degree of similarity of microbial communities to those found in surface horizons. We observed five phyla that consistently increased in relative abundance with depth across our soil profiles: Chloroflexi , Nitrospirae , Euryarchaeota , and candidate phyla GAL15 and Dormibacteraeota (formerly AD3). Leveraging the unusually high abundance of Dormibacteraeota at depth, we assembled genomes representative of this candidate phylum and identified traits that are likely to be beneficial in low-nutrient environments, including the synthesis and storage of carbohydrates, the potential to use carbon monoxide (CO) as a supplemental energy source, and the ability to form spores. Together these attributes likely allow members of the candidate phylum Dormibacteraeota to flourish in deeper soils and provide insight into the survival and growth strategies employed by the microbes that thrive in oligotrophic soil environments. IMPORTANCE Soil profiles are rarely homogeneous. Resource availability and microbial abundances typically decrease with soil depth, but microbes found in deeper horizons are still important components of terrestrial ecosystems. By studying 20 soil profiles across the United States, we documented consistent changes in soil bacterial and archaeal communities with depth. Deeper soils harbored communities distinct from those of the more commonly studied surface horizons. Most notably, we found that the candidate phylum Dormibacteraeota (formerly AD3) was often dominant in subsurface soils, and we used genomes from uncultivated members of this group to identify why these taxa are able to thrive in such resource-limited environments. Simply digging deeper into soil can reveal a surprising number of novel microbes with unique adaptations to oligotrophic subsurface conditions.

From hillslope to small catchment scales (< 50 km 2 ), soil carbon management and mitigation policies rely on estimates and projections of soil organic carbon (SOC) stocks. Here we apply a process-based modeling approach that parameterizes the MIcrobial-MIneral Carbon Stabilization (MIMICS) model with SOC measurements and remotely sensed environmental data from the Reynolds Creek Experimental Watershed in SW Idaho, USA. Calibrating model parameters reduced error between simulated and observed SOC stocks by 25%, relative to the initial parameter estimates and better captured local gradients in climate and productivity. The calibrated parameter ensemble was used to produce spatially continuous, high-resolution (10 m 2 ) estimates of stocks and associated uncertainties of litter, microbial biomass, particulate, and protected SOC pools across the complex landscape. Subsequent projections of SOC response to idealized environmental disturbances illustrate the spatial complexity of potential SOC vulnerabilities across the watershed. Parametric uncertainty generated physicochemically protected soil C stocks that varied by a mean factor of 4.4 × across individual locations in the watershed and a − 14.9 to + 20.4% range in potential SOC stock response to idealized disturbances, illustrating the need for additional measurements of soil carbon fractions and their turnover time to improve confidence in the MIMICS simulations of SOC dynamics.

Plant respiration and photosynthesis are the two main processes influencing carbon (C) flux balance at leaf‐to‐ecosystem scales. The ratio of respiration to photosynthesis (R:A) or carbon use efficiency (CUE) is considered an important trait for determining global carbon storage in the near future. One school of thought assumes that R:A is constant in terrestrial productivity models, irrespective of biomass, climate, and species. Others believe it is variable, although within a limited range. Semiarid systems dominated by woody vegetation, such as sagebrush steppe, have been recognized as potentially important C sinks on regional to global scales in the context of future climate scenarios. Therefore, there is a critical need to study R:A over different organizational scales (i.e., at the leaf, whole plant, and ecosystem scales) to use this approach for future C flux predictions under climate change scenarios. The objective of this study was to compare leaf‐, shrub‐, and ecosystem‐scale R:A among three sagebrush (Artemisia spp.) communities, and to determine how R:A varies throughout the growing season (i.e., early, mid‐, and late summer) among these communities. We measured photosynthesis and respiration monthly in three sagebrush communities spanning a 685‐m elevation gradient at the Reynolds Creek Experimental Watershed and Critical Zone Observatory in southwestern Idaho. Consistent with our expectations, we found large seasonal variations in R and A at all scales, but with differences in A among the three sagebrush communities significant only at the leaf scale. The R:A ratio was not significantly different among the three species at all organizational scales. However, the R:A ratio did vary among months at the leaf level and there was a statistical interaction between species and month at both leaf and shrub levels. Our study indicates that the R:A ratio is generally conservative, although not tightly constrained (range: 0.12–0.77) among three sagebrush species. Therefore, approaches that assume conservative R:A ratios in terrestrial productivity models need to be considered carefully to evaluate the impact of projected climatic changes on future C cycling in shrub‐dominated rangeland ecosystems.

Chemical stabilization of microbial-derived products such as extracellular enzymes (EE) onto mineral surfaces has gained attention as a possibly important mechanism leading to the persistence of soil organic carbon (SOC). While the controls on EE activities and their stabilization in the surface soil are reasonably well-understood, how these activities change with soil depth and possibly diverge from those at the soil surface due to distinct physical, chemical, and biotic conditions remains unclear. We assessed EE activity to a depth of 1 m (10 cm increments) in 19 soil profiles across the Critical Zone Observatory Network, which represents a wide range of climates, soil orders, and vegetation types. For all EEs, activities per mass of soil correlated positively with microbial biomass (MB) and SOC, and all three of these variables decreased logarithmically with depth (p < 0.05). Across all sites, over half of the potential EE activities per mass soil consistently occurred below 20 cm for all measured EEs. Activities per unit MB or SOC were substantially higher at depth (soils below 20 cm accounted for 80% of whole-profile EE activity), suggesting an accumulation of stabilized (i.e. mineral sorbed) EEs in subsoil horizons. The pronounced enzyme stabilization in subsurface horizons was corroborated by mixed-effects models that showed a significant, positive relationship between clay concentration and MB-normalized EE activities in the subsoil. Furthermore, the negative relationships between soil C, N, and P and C-, N-, and P-acquiring EEs found in the surface soil decoupled below 20 cm, which could have also been caused by EE stabilization. This finding suggests that EEs may not reflect soil nutrient availabilities deeper in the soil profile. Taken together, our results suggest that deeper soil horizons hold a significant reservoir of EEs, and that the controls of subsoil EEs differ from their surface soil counterparts.

Ecological theory predicts a pulse disturbance results in loss of soil organic carbon and short-term respiration losses that exceed recovery of productivity in many ecosystems. However, fundamental uncertainties remain in our understanding of ecosystem recovery where spatiotemporal variation in structure and function are not adequately represented in conceptual models. Here we show that wildfire in sagebrush shrublands results in multiscale responses that vary with ecosystem properties, landscape position, and their interactions. Consistent with ecological theory, soil pH increased and soil organic carbon (SOC) decreased following fire. In contrast, SOC responses were slope aspect and shrub-microsite dependent, with a larger proportional decrease under previous shrubs on north-facing aspects compared to south-facing ones. In addition, respiratory losses from burned aspects were not significantly different than losses from unburned aspects. We also documented the novel formation of soil inorganic carbon (SIC) with wildfire that differed significantly with aspect and microsite scale. Whereas pH and SIC recovered within 37 months post-fire, SOC stocks remained reduced, especially on north-facing aspects. Spatially, SIC formation was paired with reduced respiration losses, presumably lower partial pressure of carbon dioxide (pCO 2 ), and increased calcium availability, consistent with geochemical models of carbonate formation. Our findings highlight the formation of SIC after fire as a novel short-term sink of carbon in non-forested shrubland ecosystems. Resiliency in sagebrush shrublands may be more complex and integrated across ecosystem to landscape scales than predicted based on current theory.

A changing climate has the potential to mobilize soil carbon, shifting seasonally snow-covered, forested ecosystems from carbon sinks to sources. To determine the sensitivity of soil carbon fluxes to changes in temperature and moisture, we quantified seasonal and spatial variability of soil carbon dioxide (CO₂) fluxes (N = 746) and dissolved organic carbon (DOC) in leachate (N = 260) in high-elevation, mixed conifer forests in Arizona and New Mexico. All sites have cold winters, warm summers, and bimodal soil moisture patterns associated with snowmelt and summer monsoon rainfall. We employed a state factor approach, quantifying how distal controls (parent material, regional climate, topography) interacted with proximal variability in soil temperature (−3 to 26 °C) and moisture (2–76 %) to influence carbon effluxes. Carbon loss was dominated by CO₂flux (250–1220 g C m⁻² year⁻¹) rather than leached DOC (7.0–9.4 g C m⁻² year⁻¹). Significant differences in mean growing season CO₂flux were associated with parent material and aspect; differences appear to be mediated by how these distal controls influence primarily moisture and secondarily temperature. Across all sites, a multiple linear regression model (MLR) relying on moisture and temperature best described growing season CO₂fluxes (r² = 0.63, p < 0.001). During winter, the MLR describing soil CO₂flux (r² = 0.98, p < 0.001) relied on distal factors including snow cover, clay content, and bulk carbon, all factors that influence liquid water content. Our findings highlight the importance of state factors in controlling soil respiration primarily through influencing spatial and temporal heterogeneity in soil moisture.

Policy interest in socio‐ecological systems has driven attempts to define and map socio‐ecological zones (SEZs), that is, spatial regions, distinguishable by their conjoined social and bio‐geo‐physical characteristics. The state of Idaho, USA, has a strong need for SEZ designations because of potential conflicts between rapidly increasing and impactful human populations, and proximal natural ecosystems. Our Idaho SEZs address analytical shortcomings in previously published SEZs by: (1) considering potential biases of clustering methods, (2) cross‐validating SEZ classifications, (3) measuring the relative importance of bio‐geo‐physical and social system predictors, and (4) considering spatial autocorrelation. We obtained authoritative bio‐geo‐physical and social system datasets for Idaho, aggregated into 5‐km grids = 25 km2, and decomposed these using principal components analyses (PCAs). PCA scores were classified using two clustering techniques commonly used in SEZ mapping: hierarchical clustering with Ward's linkage, and k‐means analysis. Classification evaluators indicated that eight‐ and five‐cluster solutions were optimal for the bio‐geo‐physical and social datasets for Ward's linkage, resulting in 31 SEZ composite types, and six‐ and five‐cluster solutions were optimal for k‐means analysis, resulting in 24 SEZ composite types. Ward's and k‐means solutions were similar for bio‐geo‐physical and social classifications with similar numbers of clusters. Further, both classifiers identified the same dominant SEZ composites. For rarer SEZs, however, classification methods strongly affected SEZ classifications, potentially altering land management perspectives. Our SEZs identify several critical regions of social–ecological overlap. These include suburban interface types and a high desert transition zone. Based on multinomial generalized linear models, bio‐geo‐physical information explained more variation in SEZs than social system data, after controlling for spatial autocorrelation, under both Ward's and k‐means approaches. Agreement (cross‐validation) levels were high for multinomial models with bio‐geo‐physical and social predictors for both Ward's and k‐means SEZs. A consideration of historical drivers, including indigenous social systems, and current trajectories of land and resource management in Idaho, indicates a strong need for rigorous SEZ designations to guide development and conservation in the region. Our analytical framework can be broadly applied in SES research and applied in other regions, when categorical responses—including cluster designations—have a spatial component.

Objectives Somatostatin receptor positron emission tomography/computed tomography (SSTR-PET/CT) using [ 68 Ga]-labeled tracers is a widely used imaging modality for neuroendocrine tumors (NET). Recently, [ 18 F]SiTATE, a SiFAlin tagged [Tyr3]-octreotate (TATE) PET tracer, has shown great potential due to favorable clinical characteristics. We aimed to evaluate the reproducibility of Somatostatin Receptor-Reporting and Data System 1.0 (SSTR-RADS 1.0) for structured interpretation and treatment planning of NET using [ 18 F]SiTATE. Methods Four readers assessed [ 18 F]SiTATE-PET/CT of 95 patients according to the SSTR-RADS 1.0 criteria at two different time points. Each reader evaluated up to five target lesions per scan. The overall scan score and the decision on peptide receptor radionuclide therapy (PRRT) were considered. Inter- and intra-reader agreement was determined using the intraclass correlation coefficient (ICC). Results The ICC analysis on the inter-reader agreement using SSTR-RADS 1.0 for identical target lesions (ICC ≥ 85%), overall scan score (ICC ≥ 90%), and the decision to recommend PRRT (ICC ≥ 85%) showed excellent agreement. However, significant differences were observed in recommending PRRT among experienced readers (ER) ( p  = 0.020) and inexperienced readers (IR) ( p  = 0.004). Compartment-based analysis demonstrated good to excellent inter-reader agreement for most organs (ICC ≥ 74%), except for lymph nodes (ICC ≥ 53%). Conclusion SSTR-RADS 1.0 represents a highly reproducible and consistent framework system for stratifying SSTR-targeted PET/CT scans, even using the novel SSTR-ligand [ 18 F]SiTATE. Some inter-reader variability was observed regarding the evaluation of uptake intensity prior to PRRT as well as compartment scoring of lymph nodes, indicating that those categories require special attention during further clinical validation and might be refined in a future SSTR-RADS version 1.1. Clinical relevance statement SSTR-RADS 1.0 is a consistent framework for categorizing somatostatin receptor-targeted PET/CT scans when using [ 18 F]SiTATE. The framework serves as a valuable tool for facilitating and improving the management of patients with NET. Key Points SSTR-RADS 1.0 is a valuable tool for managing patients with NET . SSTR-RADS 1.0 categorizes patients with showing strong agreement across diverse reader expertise . As an alternative to [ 68 Ga]-labeled PET/CT in neuroendocrine tumor imaging, SSTR-RADS 1.0 reliably classifies [ 18 F]SiTATE-PET/CT .