Optimizing Process-Based Models to Predict Current and Future Soil Organic Carbon Stocks at High-Resolution

From hillslope to small catchment scales (\u3c 50 km2), 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 m2) 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

Soil Carbon Decomposition in Grass Based Biofuels

Biofuels from cellulosic bioenergy crops, which include perennial prairie grasses such as switchgrass (Panicum virgatum L.) and big bluestem (Andropogon gerardii Vitman) pose as a promising potential resource to help mitigate climate change. Ecological sustainability necessitates that growing these crops for bioenergy production promotes soil carbon (C) sequestration, such that their production contributes to removing CO2 from the atmosphere. Soil C sequestration is driven by the quantity of C that plants release into soil and by the quantity of this C that is decomposed by soil microorganisms and subsequently respired back into the atmosphere. Our previous research has ascertained that the quantity of C released into soil differs between switchgrass and big bluestem, but we are uncertain about loss of this C from soil through decomposition processes. This knowledge gap makes it difficult to predict long-term soil C sequestration in these biofuel cropping systems. This project asks if there are significant differences in soil C decomposition dynamics between two grass based biofuels? We are performing a long-term controlled laboratory incubation study with soils derived from switchgrass and big bluestem bioenergy cropping systems which were collected in 2018. The field experiment was initiated in 2008 at the Fermilab National Environmental Research Park, in northeastern Illinois, USA. Soils will be homogenized by sieving, weighed (20g) into airtight incubation chambers, wetted to 60% of water holding capacity and stored in a dark environment at 20oC for 480 days. We will quantify decomposition of soil C by measuring microbial CO2 respiration on days 1, 3, 7, 15, 30, 60, 120, 240, and 480. We will be able to disentangle whether respired C was derived from switchgrass or big bluestem versus the soil C that was present in the soil prior to planting these crops, by using the natural isotopic difference between C4 plants and the soil in which they had grown for 10 years, which was reflective of C3 plants. Understanding differences in the decomposition of C derived from switchgrass and big bluestem will help us determine which one of these species will offer a more promising solution to mitigating climate change

Root Traits of Perennial C\u3csub\u3e4\u3c/sub\u3e Grasses Contribute to Cultivar Variations in Soil Chemistry and Species Patterns in Particulate and Mineral-Associated Carbon Pool Formation

Recent studies have indicated that the C4 perennial bioenergy crops switchgrass (Panicum virgatum) and big bluestem (Andropogon gerardii) accumulate significant amounts of soil carbon (C) owing to their extensive root systems. Soil C accumulation is likely driven by inter- and intraspecific variability in plant traits, but the mechanisms that underpin this variability remain unresolved. In this study we evaluated how inter- and intraspecific variation in root traits of cultivars from switchgrass (Cave-in-Rock, Kanlow, Southlow) and big bluestem (Bonanza, Southlow, Suther) affected the associations of soil C accumulation across soil fractions using stable isotope techniques. Our experimental field site was established in June 2008 at Fermilab in Batavia, IL. In 2018, soil cores were collected (30 cm depth) from all cultivars. We measured root biomass, root diameter, specific root length, bulk soil C, C associated with coarse particulate organic matter (CPOM) and fine particulate organic matter plus silt- and clay-sized fractions, and characterized organic matter chemical class composition in soil using high-resolution Fourier-transform ion cyclotron resonance mass spectrometry. C4 species were established on soils that supported C3 grassland for 36 years before planting, which allowed us to use differences in the natural abundance of stable C isotopes to quantify C4 plant-derived C. We found that big bluestem had 36.9% higher C4 plant-derived C compared to switchgrass in the CPOM fraction in the 0–10 cm depth, while switchgrass had 60.7% higher C4 plant-derived C compared to big bluestem in the clay fraction in the 10–20 cm depth. Our findings suggest that the large root system in big bluestem helps increase POM-C formation quickly, while switchgrass root structure and chemistry build a mineral-bound clay C pool through time. Thus, both species and cultivar selection can help improve bioenergy management to maximize soil carbon gains and lower CO2 emissions

A Haploid Pseudo-Chromosome Genome Assembly for a Keystone Sagebrush Species of Western North American Rangelands

Increased ecological disturbances, species invasions, and climate change are creating severe conservation problems for several plant species that are widespread and foundational. Understanding the genetic diversity of these species and how it relates to adaptation to these stressors are necessary for guiding conservation and restoration efforts. This need is particularly acute for big sagebrush (Artemisia tridentata; Asteraceae), which was once the dominant shrub over 1,000,000 km2 in western North America but has since retracted by half and thus has become the target of one of the largest restoration seeding efforts globally. Here, we present the first reference-quality genome assembly for an ecologically important subspecies of big sagebrush (A. tridentata subsp. tridentata) based on short and long reads, as well as chromatin proximity ligation data analyzed using the HiRise pipeline. The final 4.2-Gb assembly consists of 5,492 scaffolds, with nine pseudo-chromosomal scaffolds (nine scaffolds comprising at least 90% of the assembled genome; n = 9). The assembly contains an estimated 43,377 genes based on ab initio gene discovery and transcriptional data analyzed using the MAKER pipeline, with 91.37% of BUSCOs being completely assembled. The final assembly was highly repetitive, with repeat elements comprising 77.99% of the genome, making the Artemisia tridentata subsp. tridentata genome one of the most highly repetitive plant genomes to be sequenced and assembled. This genome assembly advances studies on plant adaptation to drought and heat stress and provides a valuable tool for future genomic research

Structural and socio-cultural barriers to accessing mental healthcare among Syrian refugees and asylum seekers in Switzerland.

Background: Due to their experiences of major stressful life events, including post-displacement stressors, refugees and asylum seekers are vulnerable to developing mental health problems. Yet, despite the availability of specialized mental health services in Western European host countries, refugees and asylum seekers display low mental healthcare utilization. Objective: The aim of this study was to explore structural and socio-cultural barriers to accessing mental healthcare among Syrian refugees and asylum seekers in Switzerland. Method: In this qualitative study, key-informant (KI) interviews with Syrian refugees and asylum seekers, Swiss healthcare providers and other stakeholders (e.g. refugee coordinators or leaders) were conducted in the German-speaking part of Switzerland. Participants were recruited using snowball sampling. Interviews were audiotaped and transcribed, and then analysed using thematic analysis, combining deductive and inductive coding. Results: Findings show that Syrian refugees and asylum seekers face multiple structural and socio-cultural barriers, with socio-cultural barriers being perceived as more pronounced. Syrian key informants, healthcare providers, and other stakeholders identified language, gatekeeper-associated problems, lack of resources, lack of awareness, fear of stigma and a mismatch between the local health system and perceived needs of Syrian refugees and asylum seekers as key barriers to accessing care. Conclusions: The results show that for Syrian refugees and asylum seekers in Switzerland several barriers exist. This is in line with previous findings. A possible solution for the current situation might be to increase the agility of the service system in general and to improve the willingness to embrace innovative paths, rather than adapting mental healthcare services regarding single barriers and needs of a new target population

Labile Soil Carbon Inputs Mediate the Soil Microbial Community Composition and Plant Residue Decomposition Rates

• Root carbon (C) inputs may regulate decomposition rates in soil, and in this study we ask: how do labile C inputs regulate decomposition of plant residues, and soil microbial communities? • In a 14 d laboratory incubation, we added C compounds often found in root exudates in seven different concentrations (0, 0.7, 1.4, 3.6, 7.2, 14.4 and 21.7 mg C g soil) to soils amended with and without 13C-labeled plant residue. We measured CO2 respiration and shifts in relative fungal and bacterial rRNA gene copy numbers using quantitative polymerase chain reaction (qPCR). • Increased labile C input enhanced total C respiration, but only addition of C at low concentrations (0.7 mg C g-1) stimulated plant residue decomposition (+2%). Intermediate concentrations (1.4, 3.6 mg C g-1) had no impact on plant residue decomposition, while greater concentrations of C (\u3e 7.2 mg C g-1) reduced decomposition -50%). Concurrently, high exudate concentrations (\u3e 3.6 mg C g-1) increased fungal and bacterial gene copy numbers, whereas low exudate concentrations (\u3c 3.6 mg C g-1) increased metabolic activity rather than gene copy numbers. • These results underscore that labile soil C inputs can regulate decomposition of more recalcitrant soil C by controlling the activity and relative abundance of fungi and bacteria

A haploid pseudo-chromosome genome assembly for a keystone sagebrush species of western North American rangelands

Increased ecological disturbances, species invasions, and climate change are creating severe conservation problems for several plant species that are widespread and foundational. Understanding the genetic diversity of these species and how it relates to adaptation to these stressors are necessary for guiding conservation and restoration efforts. This need is particularly acute for big sagebrush (Artemisia tridentata; Asteraceae), which was once the dominant shrub over 1,000,000 km2 in western North America but has since retracted by half and thus has become the target of one of the largest restoration seeding efforts globally. Here, we present the first reference-quality genome assembly for an ecologically important subspecies of big sagebrush (A. tridentata subsp. tridentata) based on short and long reads, as well as chromatin proximity ligation data analyzed using the HiRise pipeline. The final 4.2-Gb assembly consists of 5,492 scaffolds, with nine pseudo-chromosomal scaffolds (nine scaffolds comprising at least 90% of the assembled genome; n = 9). The assembly contains an estimated 43,377 genes based on ab initio gene discovery and transcriptional data analyzed using the MAKER pipeline, with 91.37% of BUSCOs being completely assembled. The final assembly was highly repetitive, with repeat elements comprising 77.99% of the genome, making the Artemisia tridentata subsp. tridentata genome one of the most highly repetitive plant genomes to be sequenced and assembled. This genome assembly advances studies on plant adaptation to drought and heat stress and provides a valuable tool for future genomic research.This research was made possible by 2 NSF Idaho EPSCoR grants (award numbers OIA-1757324 and OIA-1826801), as well as a Dovetail Genomics Tree of Life Award.Introduction Materials and methods Sample collection, in vitro tissue propagation, and biomass production Flow cytometry and genome complexity analysis PacBio and Omni-C sequence data generation PacBio long-read de novo assembly and validation Pseudomolecule construction with HiRise Genome annotation RNA sequencing Repeat identification Functional annotation Results and discussion Validation of genome assembly and annotation Genome complexity and evidence of past polyploidization Comparing the A. tridentata and A. annua genome assemblies Applications of the sagebrush reference genome Data availability Acknowledgments Literature cite

Beyond the black box: Promoting mathematical collaborations for elucidating interactions in soil ecology

© 2019 The Authors. Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant-soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: Theory spanning scales and ecological hierarchies, processes, and evolution

Beyond the black box: promoting mathematical collaborations for elucidating interactions in soil ecology

This work is licensed under a Creative Commons Attribution 4.0 International License.Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant–soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: theory spanning scales and ecological hierarchies, processes, and evolution