Soil compaction is a threat to agricultural soil function due to constriction of macro- and meso-pores necessary for air and water movement and crop root elongation. Soils are most vulnerable to compaction when moist. Agricultural soils saturated from winter precipitation or from intentional flooding for groundwater recharge may limit growers’ operational access to fields. The objective of this research was to develop guidance for rain-free “time-to-trafficability” (including shallow workability—when a soil is conducive to both tillage and traffic) after deep wetting, using soil survey data, pedotransfer functions, and a hydroclimatological modeling approach. Trafficability is defined as a threshold of field capacity (θfc) at the soil surface (0–10 cm), ranging from 85% of θfc (clays and silty clays) to 95% of θfc (sands and loamy sands). The θfc threshold is guided by the soil texture plasticity index, an indicator of compaction risk. 2911 soil profiles from soil survey databases were subjected to a wetting simulation, followed by drainage and evaporation using HYDRUS-1D across 11 locations representing mean annual potential evapotranspiration (PET) quantiles from 5% to 95%, four months (January-April), and three different years, assuming no precipitation. Rain-free time-to-trafficability was greatest in fine and loamy soils during cold months (January and February). However, seasonal effects on time-to-trafficability were more pronounced in loamy soils. Non-linear predictive functions were developed for each 0–10 cm textural class to enable mapping the typical time-to-trafficability across PET gradients, revealing clear regional and temporal patterns. Model derived estimates can inform agricultural managed aquifer recharge timing decisions and subsequent risk of soil compaction. Additional research is needed for validation and to better constrain time-to-trafficability estimates for loamy and fine textured soils, which show a greater degree of uncertainty amid greater risk of compaction indicated by plasticity indices.

Shallow soil temperature (Tss) was monitored at many clusters of sites in valley bottom areas, bordering mountain slopes, and subalpine upland areas within the Tahoe Basin of the Sierra Nevada, USA. Objectives of this survey were to: (i) accurately log Tss for an entire year across the panoply of ground surface environments that cover the southern Tahoe Basin area, and (ii) identify the primary factors responsible for inter-site variations in seasonal and annual mean Tss. The Tss data for snow-free and annual mean periods exhibit wider inter-site ranges than published observations for other regions, attributable to the great diversity of ground surface environments sampled. Two energy balance based models of ground surface temperature are introduced, each applicable to a wide variety of surface environments and formulated with regional calibration coefficients that can incorporate effects of seasonal snow-cover on annual mean Tss. The models closely fit summer monthly and annual mean Tss data from most sites, and confirm that the large inter-site range of shading (by vegetation and terrain) is responsible for most of the large inter-site range of observed Tss. Additionally, data and model results strongly suggest spatially heterogeneous soil warming rates in response to regional climate warming, and support the value of resolving spatial variations in Tss for groundwater flow tracing techniques.

Given the complex topography of California rangelands, contrasting microclimates affect forage growth at catchment scales. However, documentation of microclimate–forage growth associations is limited, especially in Mediterranean regions experiencing pronounced climate change impacts. To better understand microclimate–forage growth linkages, we monitored forage productivity and root-zone soil temperature and moisture (0–15 and 15–30 cm) in 16 topographic positions in a 10-ha annual grassland catchment in California's Central Coast Range. Data were collected through two strongly contrasting growing seasons, a wet year (2016–17) with 287-mm precipitation and a dry year (2017–18) with 123-mm precipitation. Plant-available soil water storage (0–30 cm) was more than half full for most of the wet year; mean peak standing forage was 2790 kg ha−1 (range: 1597–4570 kg ha−1). The dry year had restricted plant-available water and mean peak standing forage was reduced to 970 kg ha−1 (range: 462–1496 kg ha−1). In the wet year, forage growth appeared energy limited (light and temperature): warmer sites produced more forage across a 3–4°C soil temperature gradient but late season growth was associated with moister sites spanning this energy gradient. In the dry year, the warmest topographic positions produced limited forage across a 10°C soil temperature gradient until late season rainfall in March. Linear models accounting for interactions between soil moisture and temperature explained about half of rapid, springtime forage growth variance. These findings reveal dynamic but clear microclimate–forage growth linkages in complex terrain, and thus, have implications for rangeland drought monitoring and dryland ecosystems modeling under climate change.

Accurate assessments of soil organic carbon (SOC) stocks are needed at multiple scales given their importance to both local soil health and global C cycles. Rangelands cover 54% of California, representing a large stock of SOC, but existing SOC estimates are uncertain. To improve understanding of fine-resolution SOC stocks in complex terrain and provide guidance to rangeland SOC inventories, we grid-sampled 105 locations (21-m grid cells) at two depths (0–10 and 10–30 cm) in a 10-ha annual grassland catchment in California's Central Coast Range. Soils were analyzed for bulk density, coarse fragments, SOC and texture. Monthly aerial imagery was acquired by an unmanned aerial vehicle to compare surface reflectance during two contrasting years (wet vs. dry) to SOC stocks. We found that the 0–30 cm soil thickness held 3.64 ± 0.71 kg SOC m−2 (mean ± SD) with a range of 1.97–5.49 kg SOC m−2. The 0–10 cm soil thickness stored 47% of the 0–30 cm SOC stock with SOC concentrations twice as high in the 0–10 cm layer (1.40 ± 0.38%) as in the 10–30 cm layer (0.71 ± 0.15% SOC). Multiple linear regression (MLR) models explained 50–57% of SOC variability at 0–30 and 10–30 cm, but only 25% of variability at 0–10 cm. Based on cross-validation tests, MLR outperformed spatial interpolation methods and Random Forest models, best explaining SOC stocks with five environmental covariates: wet-year greenness, mean curvature, elevation, insolation, and slope. Lower hillslope positions, concave landforms, and enhanced wet-year greenness were associated with more SOC, and explained 11%, 24%, and 31% of variability in 0–30 cm SOC stocks, respectively. This study demonstrates that the accuracy of regional-scale SOC mapping of California rangelands benefits from considering microclimatic and topographic controls at the catchment-scale, in addition to broader scale mineralogical and macroclimatic controls identified in previous SOC studies.

Rangelands cover ~23 million hectares and support a $3.4 billion annual cattle industry in California. Large variations in forage production from year to year and across the landscape make grazing management difficult. We here developed optimized methods to map high-resolution forage production using multispectral remote sensing imagery. We conducted monthly flights using a Small Unmanned Aerial System (sUAS) in 2017 and 2018 over a 10-ha deferred grazing rangeland. Daily maps of NDVI at 30-cm resolution were first derived by fusing monthly 30-cm sUAS imagery and more frequent 3-m PlanetScope satellite observations. We estimated aboveground net primary production as a product of absorbed photosynthetically active radiation (APAR) derived from NDVI and light use efficiency (LUE), optimized as a function of topography and climate stressors. The estimated forage production agreed well with field measurements having a R2 of 0.80 and RMSE of 542 kg/ha. Cumulative NDVI and APAR were less correlated with measured biomass (R2 = 0.68). Daily forage production maps captured similar seasonal and spatial patterns compared to field-based biomass measurements. Our study demonstrated the utility of aerial and satellite remote sensing technology in supporting adaptive rangeland management, especially during an era of climatic extremes, by providing spatially explicit and near-real-time forage production estimates.

Sensor networks within the Southern Sierra Critical Zone Observatory (SSCZO) and Kings River Experimental Watersheds (KREW) document changes in the water cycle spanning the west slope of the southern Sierra Nevada in California. The networks were established to document water dynamics throughout the critical zone spanning profile, hillslope, catchment, and watershed scales at key locations that reflect systematic differences in bioclimatic conditions imposed by a strong elevation gradient. The critical zone observatory attempts to constrain the hydrologic budget via representative measurements of streamflow, eddy flux covariance, snow depth, meteorological conditions, and water content and water potential in soil and deep regolith. These measurements reveal the complexity of interactions among all aspects of the water balance (runoff, storage, evapotranspiration [ET], and precipitation) through daily, seasonal, and annual timescales. Multiyear drought, catastrophic wildfires, insect outbreaks, and disease have caused widespread tree mortality in the Sierra Nevada. These disturbances offer a window into the future for this region, which is expected to undergo significant change in response to global warming. This hydrological observatory provides valuable hydrometric attributes and fluxes across the stream–groundwater– vadose zone–soil–vegetation–atmosphere continuum.

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

Background

Plasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants.

Methods

Proteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics).

Results

We identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10^-11. These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, β=0.61±0.05, P=3.27×10^-30) and MMP-3 (β=-0.60±0.05, P=1.67×10^-32), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, β=0.34±0.04, P=1.34×10^-17) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure.

Conclusions

Taken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.