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One of the world's largest "blue carbon" ecosystems, Louisiana's tidal wetlands on the US Gulf of Mexico coast, is rapidly being lost. Louisiana's strong legal, regulatory, and monitoring framework, developed for one of the world's largest tidal wetland systems, provides an opportunity for a programmatic approach to blue carbon accreditation to support restoration of these ecologically and economically important tidal wetlands. Louisiana's coastal wetlands span ∼1.4 million ha and accumulate 5.5–7.3 Tg yr−1 of blue carbon (organic carbon), ∼6%–8% of tidal marsh blue carbon accumulation globally. Louisiana has a favorable governance framework to advance blue carbon accreditation, due to centralized restoration planning, long term coastal monitoring, and strong legal and regulatory frameworks around carbon. Additional restoration efforts, planned through Louisiana's Coastal Master Plan, over 50 years are projected to create, or avoid loss of, up to 81,000 ha of wetland. Current restoration funding, primarily from Deepwater Horizon oil spill settlements, will be fully committed by the early 2030s and additional funding sources are required. Existing accreditation methodologies have not been successfully applied to coastal Louisiana's ecosystem restoration approaches or herbaceous tidal wetland types. Achieving financial viability for accreditation of these restoration and wetland types will require expanded application of existing blue carbon crediting methodologies. It will also require expanded approaches for predicting the future landscape without restoration, such as numerical modeling, to be validated. Additional methodologies (and/or standards) would have many common elements with those currently available but may be beneficial, depending on the goals and needs of both the state of Louisiana and potential purchasers of Louisiana tidal wetland carbon credits. This study identified twenty targeted needs that will address data and knowledge gaps to maximize financial viability of blue carbon accreditation for Louisiana's tidal wetlands. Knowledge needs were identified in five categories: legislative and policy, accreditation methodologies and standards, soil carbon flux, methane flux, and lateral carbon flux. Due to the large spatial scale and diversity of tidal wetlands, it is expected that progress in coastal Louisiana has high potential to be generalized to similar wetland ecosystems across the northern Gulf of Mexico and globally. [ABSTRACT FROM AUTHOR]

A dual approach is an effective method for formulating climate change adaptation measures. It combines both a top-down approach, whereby plans are formulated based on climate change projections, and a bottom-up approach, in which plans are formulated based on the situation in the target region. I analyse Japan's advanced measures and a development case in Timor-Leste, where some level of adaptation effectiveness is expected. In Timor-Leste, the inadequacy of scientific data makes the top-down approach difficult, but the bottom-up approach based on thorough field surveys can promote climate-resilient development which can be expected to have high adaptation effects in such circumstances. To achieve this, it is necessary to complement scientific data with available data, further strengthen the current system in which each actor thinks independently and works and collaborates with others, and train facilitators who can understand scientific data. [ABSTRACT FROM AUTHOR]

This paper proposes a flood vulnerability index utilizing publicly available data that can be applied to different spatial scales. The index enables the development of an appropriate flood risk management strategy, tailored to those factors of vulnerability that have the greatest impact on the overall flood vulnerability of a given place. Currently, following a shift in the approach to flood protection, vulnerability has become a critical element of disaster mitigation. This index is an important contribution to the existing body of research as it can be applied to flood risk management strategies overcoming the ambiguity of definitions of vulnerability and the dynamic nature of temporal and spatial scales of analysis. The proposed flood vulnerability index is a multifaceted approach, encompassing physical, social, economic, environmental, and institutional attributes. In order to create the index, the literature on flood vulnerability was reviewed, including definitions, research methods, as well as the factors and constituents that are major components of vulnerability. The proposed indicator can be used by policy-makers responsible for flood risk management, especially in EU countries, in order to minimize the negative consequences of floods. Compared to other methods used (i.e., disaster loss estimation or modeling), the flood vulnerability index is easy to use when comparing different areas. [ABSTRACT FROM AUTHOR]

Microfluidic devices began to be used to facilitate sweat and interstitial fluid (ISF) sensing in the mid-2010s. Since then, numerous prototypes involving microfluidics have been developed in different form factors for sensing biomarkers found in these fluids under in vitro, ex vivo, and in vivo (on-body) settings. These devices transport and manipulate biofluids using microfluidic channels composed of silicone, polymer, paper, or fiber. Fluid flow transport and sample management can be achieved by controlling the flow rate, surface morphology of the channel, and rate of fluid evaporation. Although many devices have been developed for estimating sweat rate, electrolyte, and metabolite levels, only a handful have been able to proceed beyond laboratory testing and reach the stage of clinical trials and commercialization. To further this technology, this review reports on the utilization of microfluidics towards sweat and ISF management and transport. The review is distinguished from other recent reviews by focusing on microfluidic principles of sweat and ISF generation, transport, extraction, and management. Challenges and prospects are highlighted, with a discussion on how to transition such prototypes towards personalized healthcare monitoring systems. [ABSTRACT FROM AUTHOR]

The influence of mineral dust deposition on soil formation in the mountain critical zone was evaluated at six sites in southwestern North America. Passive samplers collected dust for 2 years, and representative soil and rock were gathered in the vicinity of each dust sampler. All materials (dust, soil, and rock) were analyzed to determine their mineralogy (with X-ray diffraction), geochemistry (with inductively coupled plasma mass spectrometry (ICP-MS)), and radiogenic isotope fingerprint (87Sr/86Sr and εNd). In addition, the grain size distribution of dust and soil samples was determined with laser scattering, and standard soil fertility analysis was conducted on the soil samples. Results reveal that minerals present in the dust but absent in the local bedrock are detectable in the soil. Similarly, the geochemistry and isotopic fingerprint of soil samples are more similar to dust than to local bedrock. End-member mixing models evaluating soil as a mixture of dust and rock suggest that the fine fractions of the sampled soils are dominated by dust deposition, with dust contents approaching 100 %. Dust content is somewhat higher in soils compared to bedrock types more resistant to weathering. These results emphasize the dominant control that mineral dust deposition can exert on pedogenesis in the mountain critical zone. [ABSTRACT FROM AUTHOR]

Aquatic communities are increasingly subjected to multiple stressors through global change, including warming, pH shifts, and elevated nutrient concentrations. These stressors often surpass species tolerance range, leading to unpredictable consequences for aquatic communities and ecosystem functioning. Phytoplankton, as the foundation of the aquatic food web, play a crucial role in controlling water quality and the transfer of nutrients and energy to higher trophic levels. Despite the significance in understanding the effect of multiple stressors, further research is required to explore the combined impact of multiple stressors on phytoplankton. In this study, we used a combination of crossed experiment and mechanistic model to analyze the ecological and biogeochemical effects of global change on aquatic ecosystems and to forecast phytoplankton dynamics. We examined the effect of dust (0–75 mg L−1), temperature (19–27°C), and pH (6.3–7.3) on the growth rate of the algal species Scenedesmus obliquus. Furthermore, we carried out a geospatial analysis to identify regions of the planet where aquatic systems could be most affected by atmospheric dust deposition. Our mechanistic model and our empirical data show that dust exerts a positive effect on phytoplankton growth rate, broadening its thermal and pH tolerance range. Finally, our geospatial analysis identifies several high‐risk areas including the highlands of the Tibetan Plateau, western United States, South America, central and southern Africa, central Australia as well as the Mediterranean region where dust‐induced changes are expected to have the greatest impacts. Overall, our study shows that increasing dust storms associated with a more arid climate and land degradation can reverse the negative effects of high temperatures and low pH on phytoplankton growth, affecting the biogeochemistry of aquatic ecosystems and their role in the cycles of the elements and tolerance to global change. [ABSTRACT FROM AUTHOR]

Soils store the largest amount of carbon (C) in the biosphere, and the C pool in soil is critical to the global C balance. Numerous microbial models have been developed over the last few decades to represent microbial processes that regulate the responses of soil organic carbon (SOC) to climate change. However, the representation of microbial processes varies, and how microbial processes are incorporated into SOC models has not been well explored. Here, we reviewed 71 microbial models to characterize the microbial processes incorporated into SOC models and analyzed variations in mechanistic complexity. We revealed that (a) four processes (microbial‐mediated decomposition, mineral interaction, microbial necromass recycling, and active and dormant microbial dynamics) are commonly incorporated in microbial models, (b) ∼48% of models simulate only one microbial process (i.e., microbial‐mediated decomposition) and 35% of models simulate two microbial processes: for example, microbial‐mediated decomposition and mineral interaction, (c) more than 80% microbial models use nonlinear equations, such as forward Michaelis‐Menten kinetics, to represent SOC decomposition, (d) the concept of persistence of SOC due to its intrinsic properties has been replaced by organo‐mineral interaction (∼39% of microbial models) that protects SOC from decomposition, and (e) various temperature and moisture modifiers and pH effects have been used to explain the environmental effect on microbial processes. In the future, to realistically incorporate microbial processes into Earth System Models, it is imperative to identify experimental evidence on rate limitation processes and firmly ground model structure on the field and laboratory data. Plain Language Summary: Soil stores the largest amount of carbon (C) in land ecosystems and, thus, has the potential to regulate climate change. To understand soil C processes under climate change, researchers have developed numerous microbial models that focus on the role of microorganisms in soil organic carbon (SOC) decomposition. In this study, we reviewed 71 microbial models on how microbial processes are represented for their regulation of SOC dynamics. These models commonly include four processes: microbially mediated decomposition, mineral interaction, microbial necromass recycling, and dormancy of microbial activity. More than three‐fourths of the models use nonlinear equations to describe the decomposition of SOC. The concept of SOC stability has shifted from chemical‐based properties of SOC to interactions between SOC and minerals. Our review also revealed that microbial models vary greatly in representing environmental effects, such as temperature, soil moisture, and soil pH, on microbial processes. Finally, we recommend the use of data in guiding the future development of microbial models. Key Points: More than 70 microbial models have recently been developed to simulate soil carbon dynamicsDiversity in model structures and parameters indicates uncertainty in translating current knowledge of microbial processes into modelsData‐driven model development and parameterization are highly recommended to improve the prediction of microbial models [ABSTRACT FROM AUTHOR]

Microplastic contamination is ubiquitous across the globe, even in remote locations. Still, the sources and pathways of microplastics to such locations are largely unknown. To investigate microplastic contamination in a semi-remote location, we measured microplastic concentrations in nine oligotrophic lakes within and around the International Institute for Sustainable Development-Experimental Lakes Area in northwestern Ontario, Canada. Our first objective was to establish ambient concentrations of microplastics in bottom sediments, surface water, and atmospheric deposition in semi-remote boreal lakes. Across all lakes, mean shallow and deep sediment microplastic concentrations, near-surface water microplastic concentrations from in situ filtering, and dry atmospheric microplastic deposition rates were 551 ± 354 particles kg -1 , 177 ± 103 particles kg -1 , 0.2 ± 0.3 particles L -1 , and 0.4 ± 0.2 particles m -2  day -1 , respectively. Our second objective was to investigate whether microplastic contamination of these lakes is driven by point sources including local runoff and direct anthropogenic inputs or nonpoint sources such as atmospheric deposition. Lakes were selected based on three levels of anthropogenic activity-low, medium, and high-though activity levels were minimal across all study lakes compared with highly populated areas. Whereas a positive correlation would indicate that point sources were a likely pathway, we observed no relationship between the level of anthropogenic activity and microplastic contamination of surface water. Moreover, the composition of microplastics in surface water and atmospheric deposition were similar, comprising mostly polyester and acrylic fibers. Together, these results suggest that atmospheric deposition may be the main pathway of microplastics to these remote boreal lakes. Environ Toxicol Chem 2024;43:999-1011. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC., (© 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.)

Greenland's ice sheet mass loss rate has tripled since the mid-1950s in concert with sharply lowered albedo leading to increased absorption of solar radiation and enhanced surface melt. Snow and ice melt driven by solar absorption is enhanced by the presence of light absorbing particles (LAPs), such as black carbon (BC) and dust. Yet, the LAP impact on melt is poorly constrained, partly due to scarce availability of in-situ measurements. Here, we present a survey of snow properties and LAPs deposited in winter snow layers at five sites in southwest Greenland collected in May 2017. At these sites, BC and dust concentrations were 0.62 ± 0.35 ng g-1 and 2.09 ± 1.60 µg g-1, respectively. By applying the SNICAR model, we show the LAP influence on albedo through the combined effect of surface darkening and snow metamorphism. While the LAP concentrations are low, they result in a 1.7% and 3.0% reduction in albedo within the visible spectrum for spring and summer, respectively. Past studies have shown that even minor LAP induced albedo reductions, if widespread, can have a large impact on the overall surface mass balance. SNICAR simulations constrained by our measurements show that LAP-snow aging feedback reduce albedo reduction 4 to 10 times more than previously thought, therefore LAPs are likely a significant contributor to Greenland's accelerated mass loss. As far as we know, this is the first field study to consider the LAP impact on snow aging on the Greenland ice sheet. [ABSTRACT FROM AUTHOR]

Dust emitted from North Africa is transported over long distances and has a strong impact on large areas over the North Tropical Atlantic Ocean. Sea salt emitted by the sea surface is the second source of essential elements transported in the atmosphere and plays a major role in the cycles of alkaline‐earth metals in the ecosystems of tropical North Atlantic Islands. The total atmospheric deposition fluxes were continuously sampled on a weekly basis in Guadeloupe, Lesser Antilles, from March 2015 to August 2018 (41 months). Elemental deposition fluxes, including Al, Ca, K, Mg, Fe, Na, P, S, and Zn, were measured for all samples to provide the first long time series of atmospheric elemental deposition fluxes over the Lesser Antilles region. It is shown that: (a) the three sources of atmospheric deposits in Guadeloupe for the presented elements are sea salt (for K, Ca, Mg, Na, and S), long‐range transported Saharan dust (for Al, Ca, K, and Fe), and biogenic particles (for P and Zn); (b) the average deposition mass fluxes of sea salt and Saharan dust are 17.4 and 11.2 g.m−2.year−1, respectively, without noticeable inter‐annual variations; (c) a pronounced seasonality is found for the Saharan dust deposition, for which maximum flux values are observed between June and July each year and 85% of the annual deposition flux occurs between April and September; (d) the deposition flux of sea salt is strongly correlated to local wind speed, without seasonality. Plain Language Summary: Saharan dust and sea salt contribute toward feeding trees living on Caribbean Island ground with alkaline, alkaline‐earth cations and other important elements. Saharan dust is transported time to time from North Africa with a higher frequency of events in summer. Sea salt is continuously locally emitted from the sea surface by the action of trade winds and storms on the sea surface that produces sea water brine. For the first time, we have measured the Saharan dust and sea salt deposition flux continuously for 3 years in Guadeloupe. We have found that Saharan dust brings iron, calcium, and potassium, and sea salt brings sodium, magnesium, sulfur, and potassium. The high flux of phosphorus is due to the local recycling of living debris and zinc which probably come from sea surface micro‐layer torn by the wind. These results enhance our knowledge of nutrients cycles in the North Atlantic region. Key Points: We have monitored atmospheric deposition in Guadeloupe over a 3‐year period with measurements of Al, Na, Mg, P, S, K, Ca, Fe, and ZnStrong seasonality for Saharan dust, no inter‐annual deposition flux variations for both sea salt and Saharan dustWe suggest that the contributions of Saharan dust, sea salt, and biogenic emissions explain the origin of the deposited elements [ABSTRACT FROM AUTHOR]

The Salt Lake Valley, UT, USA, is proximal to the desiccating Great Salt Lake (GSL). Prior work has found that this lakebed/playa contributes metals‐laden dust to snow in the Wasatch and Uinta Mountains. Dust and industrial particulate pollution are also delivered to communities along the Wasatch Front, but their sources, compositions, and fluxes are poorly characterized. In this study, we analyzed the dust deposited in 18 passive samplers positioned near the GSL, in cities in and near the Salt Lake Valley for total dust flux, the <63 µm dust fraction, 87Sr/86Sr, and trace element geochemistry. We compared spatial patterns in metal flux and abundance with community‐level socioeconomic metrics. We observed the highest dust fluxes at sites near the GSL playa. Within the urban corridor, 87Sr/86Sr and trace element relative abundances suggest that most of the dust to which people are regularly exposed may be fugitive dust from local soil materials. The trace metal content of dust deposited along the Wasatch Front exceeded Environmental Protection Agency screening levels and exhibited enrichment relative to both the upper continental crust and the dust collected adjacent to GSL. Sources of metals to dust deposited along the Wasatch Front may include industrial activities like mining, oil refining, as well as past historical pesticide and herbicide applications. Arsenic and vanadium indicated a statistically significant positive correlation with income, whereas lead, thallium, and nickel exhibited higher concentrations in the least wealthy and least white neighborhoods. Plain Language Summary: The Salt Lake Valley, UT, USA is near the drying Great Salt Lake. The shrinking lake reveals a playa, composed of fine grained, metal‐contaminated material. Dust storms lofting these sediments may pose a threat to air quality in the nearby cities of Ogden, Bountiful, Salt Lake, and Lehi. We investigated strontium isotopes as well as a suite of trace elements in dust sampled near the playa and within the urban corridor. We found the most, and coarsest dust was deposited outside of the city. The dust from the playa and the dust collected in the city were not similar in terms of trace elements or strontium isotopes, suggesting that much of the dust collected in the city may come from local fugitive dust sources. The dust within the city had many different metals that are known to be associated with anthropogenic and industrial activities, like mining, oil refining, and agriculture. Abundances of some metals, like As and V were higher in wealthier neighborhoods, while abundances of Pb, Tl, and Ni were higher in lower income and more ethnically diverse neighborhoods. Key Points: Dust near the Great Salt Lake playa differs from dust collected in nearby citiesMetals in city dust can be traced to specific nearby industriesFugitive dust may be an important dust source for human exposure within cities [ABSTRACT FROM AUTHOR]

Although models of social vulnerability to environmental hazards are commonly developed to support policy interventions in emergencies and disasters, their utility is hindered by a lack of contextual information on individuals exposed to and affected by hazards. We develop a novel approach to model social vulnerability that couples individuals and their varying forms of protective capacity with the social fabric of the communities in which they reside. The backbone of our model is the Public-Use Microdata Sample (PUMS), a product of the U.S. Census Bureau that preserves a representative sample of completed responses to the American Community Survey (ACS). The PUMS enables us to understand the full range of individual protective capacities against a hazard in an exposed area, which we term individual vulnerability profiles (IVPs). In this case, we examine IVPs in the Coney Island-Brighton Beach section of New York City, which suffered severe impacts during Hurricane Sandy in 2012. To manage the large number of unique IVPs in Coney Island-Brighton Beach, we perform a segmentation analysis to generalize them into thematic cohort vulnerability profiles (CVPs) representing a typology of vulnerable people in Coney Island-Brighton Beach during Sandy. From synthetic populations of CVPs, we then estimate how individuals in varying housing types were coexposed to Sandy at the census tract level by classifying these areas into community social vulnerability profiles (SVPs). Our results provide a topology of social vulnerability that simultaneously links individual, community, and population-wide concerns, enabling a more holistic understanding of resources and interventions beneficial to human security during events like Sandy than is attainable with area-level metrics. [ABSTRACT FROM AUTHOR]

Readout of multiparametric environmental signals typically uses discrete sensing formats that individually require unique signal conditioning circuitry and/or processing pathways. Here, adaptable sensor networks composed exclusively of passive material architectures that enable spectrometric comonitoring of chemical or physical environmental signals are proposed. Herein, a single radio frequency (RF) reader wirelessly interacts first with an intermediate wireless relay coil—this is tunable in length and can be designed to conform around surfaces. This relay (that is fused on textiles or surfaces) is then wirelessly coupled to arrays of passive RF sensors with individually programmable flexibility/reactivity to environmental signals. Multiple chemical and physical signals can then be monitored within the single spectral readout of a wearable reader. This technique can probe over tunable length scales, and is robust to mechanical disturbances that limit present techniques. As a proof of concept, this approach is used to comonitor chemophysical metrics such as nutrients, temperature, pressure, pH, and more on the skin or in utensils with a single readout. This technique may form a cornerstone of zero‐microelectronic sensor networks. [ABSTRACT FROM AUTHOR]

Quantifying the impact of drought on microbial processes and its consequences for soil carbon cycling is hindered by the lack of underlying mechanistic understanding. Therefore, there is a need to scale up the physiological response to changing water status from individual soil microbes to collective communities across different ecosystems.Here we propose the use of a framework that incorporates trait‐based ecology to link drought‐impacted microbial processes to rates of soil carbon decomposition and stabilisation. We briefly synthesise existing knowledge on the effects of drought on microbial physiology at the individual to community scale, before integrating this understanding within a framework incorporating life‐history strategy, ecological strategy and biochemistry.This framework highlights a dynamic allocation to high yield (Y), resource acquisition (A) and stress tolerance (S) pathways as environmental conditions change. Y‐A‐S strategies represent sets of traits that tend to correlate due to physiological or evolutionary trade‐offs. This framework enables assessment of microbial processes along two key environmental gradients of water and resource availability, both of which are constrained by drought.The variable chemistry of biomass and necromass produced under different physiological strategies in response to drying–rewetting impacts organic matter decomposition and stabilisation in soils, and should also be considered when quantifying soil carbon balance. We highlight that diversion of resources away from microbial growth can alter soil organic matter chemistry and its persistence depending on the kind of microbial compounds produced.To advance such a framework, we highlight avenues of research that would enable the further identification and quantification of traits linked to Y‐A‐S strategies and the physiological outcomes at the community level under drought and rewetting, and conclude by hypothesising how ecosystem‐level changes might feedback on to the soil carbon cycle. A scalable understanding of microbial drought‐response mechanisms affecting soil carbon cycling will transform the way microbial physiology is represented in ecosystem studies. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Wearable sweat sensors have received significant research interest and have become popular as sweat contains considerable health information about physiological and psychological states. However, measured biomarker concentrations vary with sweat rates, which has a significant effect on the accuracy and reliability of sweat biosensors. Wearable sweat loss measuring devices (SLMDs) have recently been proposed to overcome the limitations of biomarker tracking and reduce inter‐ and intraindividual variability. In addition, they offer substantial potential for monitoring human body homeostasis, because sweat loss plays an indispensable role in thermoregulation and skin hydration. Previous studies have not carried out a comprehensive and systematic review of the principles, importance, and development of wearable SLMDs. This paper reviews wearable SLMDs with a new health perspective from the role of sweat loss to advanced mechanisms and designs. Two types of sweat and their measurement significance for practical applications are highlighted. Then, a comprehensive review of advances in different wearable SLMDs based on hygrometers, absorbent materials, and microfluidics is presented by describing their respective device architectures, present situations, and future directions. Finally, concluding remarks on opportunities for future application fields and challenges for future sweat sensing are presented. [ABSTRACT FROM AUTHOR]

Macroscopic models of soil organic matter (SOM) turnover have faced difficulties in reproducing SOM dynamics or in predicting the spatial distribution of carbon stocks. These models are based on a largely inadequate linear response of soil microorganisms to bulk concentrations of nutrients and it is clear that a new approach to SOM modelling is required. Introducing explicit microbial activity and organic matter (OM) reactivity in macroscopic models represents a challenge because of the fine spatial scales at which the processes occur. To get a better grasp on interactions that take place at the microscale, a new generation of SOM models have been developed at the spatial scale of the soil microenvironments where microorganisms evolve. These models are well adapted to challenge traditional hypotheses about the influence of soil architecture on soil microbial activity. Soil architecture provides the stage for a dynamic spatial accessibility of resources to microbes and the emergence of interactions between the actors in SOM decomposition. In this context, we review microscale models of microbial activity that have been designed for soils and soil analogues. To understand how these models account for spatial accessibility, we look in detail at how soil microenvironments are described in the different approaches and how microbial colonies are spatialized in these microenvironments. We present the advantages and disadvantages of the developed strategies and we discuss their limits. Highlights: We review the state of the art in the development of microscale models of soil microbial processes.Microscale models have integrated the tremendous progress in knowledge of OM cycling in soils.We categorize modelling approaches by how they deal with complexity of soil architecture.Modelling benchmarks are required to properly balance complexity and data uncertainty. [ABSTRACT FROM AUTHOR]

Explicit representations of microbial processes in soil organic carbon (SOC) decomposition models have received increasing attention, because soil heterotrophic respiration remains one of the greatest uncertainties in climate‐carbon feedbacks projected by Earth system models (ESMs). Microbial‐explicit models have been developed and applied in site‐ and global‐scale studies. These models, however, lack the ability to represent microbial respiration responses to drying‐wetting cycles, and few of them have been incorporated in land surface models (LSMs) and validated against field observations. In this study, we developed a multi‐layer, microbial‐explicit soil organic carbon decomposition model (MESDM), based on two main assumptions that (a) extracellular enzymes remain active at dry reaction microsites, and (b) microbes at wet microsites are active or potentially active, while microbes at the dry microsites are dormant, by dividing the soil volume into wet and dry zones. MESDM with O2 and CO2 gas transport models was coupled with Noah‐MP LSM and tested against half‐hourly field observations at a semiarid grassland site in the southwest US characterized by pulsed precipitation. The results show MESDM can reproduce the observed soil respiration pulses of various sizes in response to discrete precipitation events (Birch effect) and thus improve the simulation of net ecosystem exchange. Here, both microbial accessibility to accumulated dissolved organic carbon and reactivation of dormant microbes at the dry microsites upon rewetting are critical to reproducing the Birch effect. This study improves our understanding of and ability to simulate complex soil carbon dynamics that experience drying‐wetting cycle in climate‐carbon feedbacks. Plain Language Summary: Soil microbial respiration represented in Earth system models remains one of the greatest uncertainties in predicting the interactions between climate change and global carbon cycle. Explicit representations of soil microbial activities and respiration processes in soil organic carbon decomposition models (or the so called microbial‐explicit models) have received increasing attention, and advancements have been made in related studies. However, these microbial‐explicit models still fail to simulate soil microbial respiration responses to drying‐rewetting cycles and need to be incorporated into land surface models (LSMs) for further validation against field observations. In this study, we developed a new microbe‐explicit model accounting for soil moisture control on microbial physiological state and activity and extracellular enzyme activity at reaction microsites in soil pores. We then incorporated the new model into the Noah‐MP LSM in place of the conventional first‐order decay model. The results show that Noah‐MP coupled with the new microbial‐explicit model reproduces observed soil respiration pulses of various sizes in response to precipitation pulses in a semiarid grassland in the southwest US. Our study helps improve the projection of the interactions between climate changes and land carbon cycle. Key Points: We develop a microbial‐explicit soil organic carbon decomposition model considering dry enzyme activities and microbial dormancyThe model incorporated into a land surface model is tested against half‐hourly field observations at a semiarid grassland siteThe model reproduces the observed respiration pulses in response to rain pulses and improves the simulation of net ecosystem exchange [ABSTRACT FROM AUTHOR]

We report fallout radionuclide (FRN) and major/trace element (MTE) contributions to bulk atmospheric deposition in Hanover, NH, USA (43.7022°N, 72.2896°W). Deposition of 7Be, 210Pb, and SO4 covary [R2 > 0.4, n = 461] but are discriminated by production sources, depositional mechanisms, meteorological controls, MTE associations, and seasonal biases. 7Be is dominated by rainout (78% of total deposition), recharged by long‐range transport (+23% over mean, o.m.), influenced by stratosphere‐troposphere exchange (+9% o.m.), and solar activity (−2% per doubling of sunspot count). Correlation with particulate nitrogen (+9% per doubling of N) indicates 7Be affinity for biogenic aerosols. 210Pb is dominated by dry + washout deposition (54% of total) and convective storms (+107% o.m), depleted in marine moisture sources (−133% o.m.), correlated with S (+9% per doubling of S), and biased to autumn with Mn, Hg, and V (+7% o.m.). Coincident long‐term declines in S and 210Pb (−14%, −4% per year) suggest co‐scavenging by PbSO4. 7Be:210Pb ratios increase asymptotically with precipitation through the dry‐washout‐rainout transition and recharge of 7Be. At the global scale, 7Be:210Pb increases with precipitation for North American/European sites due to recharge of 7Be in midlatitude storm belts [R2 = 0.64, n = 31]. Conversely, 7Be:210Pb is independent of precipitation for Southeast/East Asian sites where 7Be recharge is low [R2 = 0.01, n = 40]. Globally, 7Be:210Pb ratios in dry deposition reflect resuspended aerosols with mean age of ca. 200 days, contributing <5% of 210Pb deposition. Different aerosol populations contributing to FRN deposition across spatial and temporal scales should emerge as a focus in terrestrial 7Be, 210Pb, and 10Be tracer applications. Plain Language Summary: Beryllium‐7 (7Be) and lead‐210 (210Pb) are natural radioactive elements that are produced in the atmosphere. They are powerful tools in earth and atmospheric sciences because they allow us to trace the movement of other atmospheric elements and particles such as sulphate (SO4), toxins such as mercury (Hg), or particulate matter small enough to damage human lungs (PM2.5). After production, 7Be, 210Pb, and associated particles reach Earth's surface in rainfall, pass through soils and sediments, and may be resuspended as dust that can pose ongoing risks of particulate exposure. To better understand how they trace atmospheric particles, we measured 7Be, 210Pb, SO4, and other elements and particles in rainwater each week for 9 years. By making many measurements we were able to see important differences in how 7Be, 210Pb, and SO4 are delivered to the Earth's surface, and differences among other elements that they associate with. These differences are likely to have implications for how 7Be and 210Pb are used to date geological deposits or to measure erosion or contaminant transport, but more work will be needed to fully understand them. Key Points: 7Be, 210Pb, and SO4 in bulk deposition represent unique mixtures of distinct aerosol populationsPrimary controls on 7Be:210Pb ratios include airmass altitude and origin, meteorology, precipitation depth, and resuspended aerosolsMultiple aerosol populations controlling FRN deposition should be investigated for their implications to terrestrial tracer studies [ABSTRACT FROM AUTHOR]

More above-ground biomass (kg m-2) grows in the northern Appalachian Mountains (USA) in forests on shale than on sandstone at all landscape positions other than ridgetops. This has been tentatively attributed to physical (rather than chemical) attributes of the substrates, such as elevation, particle size, and water capacity. However, shales have generally similar phosphorus (P) concentrations to sandstones and, in the Valley and Ridge province, they erode more quickly. This led us to hypothesize that faster replenishment of the lithogenic nutrient P in shale soils through erosion + soil production could instead control the differences in biomass. To test this, soils and foliage from 10 sites on shales and sandstones in the northern Appalachians from roughly the same elevation and aspect were analysed. We discovered that, when controlling for location, concentrations of bioavailable P in soils and P in foliage were higher and P resorbed from senescing red oak leaves was lower on slower-eroding sandstone than on faster-eroding shale. Lower resorption generally can be attributed to lower P limitation for trees. Further investigation of weathering and erosion on one of the sandstone-shale pairs within a larger, paired watershed study revealed that the differences in P concentrations in biomass and foliage between lithologies likely developed because sandstones act as 'collectors' that trap nutrients from residual and exogenous sources, while shales erode quickly and thus promote production of soil from bedrock that releases P to ecosystems. We concluded that the combined effects of differential rates of dust collection and erosion results in roughly equal biomass growing on sandstone and shale ridgetops. This work emphasizes the balance between a landscape's capacity to collect dust versus produce soil in controlling bioavailability of nutrients. [ABSTRACT FROM AUTHOR]

As a critical process in regulating terrestrial feedback to climate change, soil heterotrophic respiration is commonly simulated with the first‐order kinetics in current Earth system models. Compared with the first‐order kinetic models, explicit microbial models are expected to better simulate nonlinear carbon (C)‐cycle phenomena, such as the pulse dynamics of soil heterotrophic respiration driven by dry‐rewetting cycles in grasslands. However, these two types of models (i.e., linear conventional and nonlinear microbial models) have never been compared based on in situ observations of soil heterotrophic respiration in the semi‐arid grassland, which is significantly affected by the dry‐rewetting events. Here, based on the field data of soil heterotrophic respiration in a semi‐arid grassland in northern China, we first showed that the shift from a conventional linear model to a nonlinear microbial model did not substantially improve the simulation of soil heterotrophic respiration. Then, we quantified the contributions of different moisture‐response functions to the uncertainty in simulating the soil C dynamics. The results showed that the selection of moisture‐response functions combined with parameterization in the soil C models dominated the modeled uncertainties in soil heterotrophic respiration. These findings suggest that both the conventional linear model and nonlinear microbial model can simulate well the pulse dynamic of soil heterotrophic respiration in grasslands with an improved parameterization of water regulation on soil carbon decomposition. This study also calls for more observations of nonlinear C phenomena for reducing the simulation uncertainty on soil C cycling in Earth system models. Plain Language Summary: Soil heterotrophic respiration refers to the process of decomposing soil organic carbon and releasing CO2 into the atmosphere. Current soil carbon models use the first‐order kinetics to represent the decomposition process, but large uncertainties have emerged in simulating soil heterotrophic respiration among these models. Therefore, models incorporating microbial mechanisms are expected to better simulate soil carbon processes than the conventional models, especially in simulating the nonlinear phenomena of soil heterotrophic respiration. To test the ability of these two types of models (i.e., linear conventional and nonlinear microbial models) in simulating the nonlinear soil processes, we evaluate them based on in situ observations of the pulsed dynamics of soil heterotrophic respiration in a semi‐arid grassland. We found the microbial‐explicit model did not substantially improve the simulation of soil heterotrophic respiration. The moisture‐response function combined with parameterization played an important role in reducing the uncertainties in simulating the pulsed dynamics of soil heterotrophic respiration in both types of models. Key Points: Both conventional linear and microbial nonlinear models can capture the pulsed dynamics of heterotrophic respirationThe moisture‐response function combined with model parameterization dominates the modeled uncertainties in heterotrophic respirationMore observations of nonlinear C phenomena are needed to reduce the simulation uncertainty on soil C cycling in Earth system models [ABSTRACT FROM AUTHOR]

U–Pb dating of detrital zircons (DZ) in Quaternary slope deposits (cover beds) and examination of the surface structure of single zircon grains may enable reconstruction of the provenance of their aeolian components and help to reconstruct sedimentary palaeo‐transportation cascades. We distinguish several layers of slope deposits (cover beds) using a palaeosol‐supported sequence‐stratigraphic approach. In a pilot study, we demonstrate the usability of using end‐member‐modelled analyses of grain sizes to identify the aeolian matter, multi‐dimensional scaling and density functions (probability density functions (PDF) and Kernel density estimations (KDE)) of the U–Pb data, and the grain morphology of DZ, and show that the age and appearance variation of DZ in the Great Basin differ remarkably from those of the Colorado Plateau. All samples contain aeolian matter. Density functions of the DZ ages show similarities within each of the two regions. The Great Basin samples are dominated by late Cretaceous and Paleogene zircons, which are assumed to derive from volcanism. In contrast, the Colorado Plateau samples are almost free of these contributions. Presumably, the difference is due to palaeolakes, which were frequent in the Great Basin only, whose sediments contain a similar spectrum of DZ ages. Zircon morphology indicates that most grains have a history of aeolian transportation, whereas the grains assumed to be of volcanic origin often do not show similar transportation marks; this indicates that their transportation was dominated by the eruptive process but fewer steps of a transportation cascade. Multidimensional scaling of age data defines clusters of samples with similar DZ ages and – compared with published ages from possible sources – allows first interpretations of provenance. Quaternary aeolian sediments have not been studied in, and the applied mix of methods has not been applied to, the southwestern USA before. We demonstrate their feasibility for this study area. [ABSTRACT FROM AUTHOR]

A compact, high-performance bending sensor based on fiber microspheres array (FMA) Michelson interferometer (MI) was experimentally proved. The sensor consists of a refractive index modulation region (RIMR) fused by three microspheres, interference arm and end face protection. The RIMR acts as a modal coupling device between core and cladding modes. Due to the different stress for the RIMR in the middle (lowest point) of the stepper motor or the side (high point) during the bending process, the mode field distribution excited to the cladding is inconsistent which shows a discrepancy in sensitivity. The results show that the bending sensitivity at the lowest point is lower than the high point, which is consistent with the theory. Meanwhile, the variable range method is used to realize the repeatability verification of the sensor. Besides, the relative sensitivity (the ratio of wavelength sensitivity to intensity sensitivity) is defined to realize the resolution of strain and bending. [ABSTRACT FROM AUTHOR]

As a bridge linking propagating waves and surface waves, reflective metasurfaces (with metal cladding at the bottom) play a significant role in the field of beam steering. The feasibility and flexibility to control electromagnetic waves by reflective metasurfaces depend on the recognition of their physical properties by researchers. As for bianisotropic reflective metasurfaces, however, the effective‐medium characteristics cannot be appropriately described by conventional methods, which entail both transmission and reflection coefficients. Here, a robust method based on simplex S‐parameters is proposed to retrieve constitutive effective parameters (CEPs) for bianisotropic reflective metasurfaces. By illuminating the transverse electric‐polarization plane waves on a split‐ring unit cell normally and obliquely, the CEPs can be calculated with only S11 parameters. To demonstrate the effectiveness of the retrieval results, an analysis of small incident angles is employed to examine the consistency of both the x‐ and y‐directions effective impedance and determine the accurate range of the incident angles. Moreover, the sensitivity of the retrieval results to S‐parameters is also sufficiently discussed. This method is beneficial for the applications of one‐side complex materials, e.g., dual‐function reflective metasurfaces, multichannel reflectors, excitation of spoof space plasmon polaritons, and ground‐penetrating‐radar applications. [ABSTRACT FROM AUTHOR]

Oceans are, generally, relatively weak sources of ice nucleating particles (INPs). Thus, dust transported from terrestrial regions can dominate atmospheric INP concentrations even in remote marine regions. Studies of ocean‐emitted INPs have focused upon sea spray aerosols containing biogenic species. Even though large concentrations of dust are transported over marine regions, resuspended dust has never been explicitly considered as another possible source of ocean‐emitted INPs. Current models assume that deposited dust is not re‐emitted from surface waters. Our laboratory studies of aerosol particles produced from coastal seawater and synthetic seawater doped with dust show that dust can indeed be ejected from water during bubble bursting. INP concentration measurements show these ejected dust particles retain ice nucleating activity. Doping synthetic seawater to simulate a strong dust deposition event produced INPs active at temperatures colder than −13°C and INP concentrations 1 to 2 orders of magnitude greater than either lab sea spray or marine boundary layer measurements. The relevance of these laboratory findings is highlighted by single‐particle composition measurements along the Californian coast where at least 9% of dust particles were mixed with sea salt. Additionally, global modeling studies show that resuspension of dust from the ocean could exert the most impact over the Southern Ocean, where ocean‐emitted INPs are thought to dominate atmospheric INP populations. More work characterizing the factors governing the resuspension of dust particles is required to understand the potential impact upon clouds. Plain Language Summary: Clouds are formed through the deposition of water onto aerosol particles. A rare subset of these aerosol particles, ice nucleating particles (INPs), is required for cloud droplets to freeze at temperatures warmer than −38°C and can profoundly affect climate. Unfortunately, the identity and sources of INPs in marine regions are not well understood. Dust particles from land masses can be transported over marine regions where they commonly deposit to the ocean's surface in what has been assumed to be a one‐way atmospheric loss process. We show through a combination of lab, field, and modeling studies that dust can be re‐ejected in sea spray aerosols and still act as INPs. Modeling studies indicate that oceanic dust INPs will have the greatest influence over the Southern Ocean. Key Points: Terrestrial dust deposited in seawater can be re‐aerosolized inside sea spray aerosolRe‐aerosolized oceanic dust particles retain ice nucleation activity and may add to atmospheric ice nucleating particle populationsGlobal simulations estimate that the greatest impact of this process would be in the Southern Ocean [ABSTRACT FROM AUTHOR]

Mineral aerosols may affect global climate indirectly by enhancing net primary productivity (NPP) upon deposition to the oceans and associated atmosphere‐to‐ocean CO2 flux. This mechanism is hypothesized to have contributed significantly to the last interglacial‐to‐glacial climatic transition. However, the dust‐NPP connection remains contentious for the present‐day climate system. We analyze the impact of southernmost Patagonian dust emissions on southwestern Atlantic Ocean continental shelf and proximal open ocean satellite chlorophyll‐a concentration. We use the first decadal time series of surface dust mass flux in southern Patagonia, along with in situ visibility data, to model dust emission, transport, and deposition to the ocean. We then perform a dust event‐based analysis of chlorophyll‐a time series, using a novel approach by which time series are corrected for post‐depositional particle advection due to ocean currents. Finally, we performed chemical analysis of iron in dust samples, a key micronutrient limiting phytoplankton biomass in high‐nutrient, low‐chlorophyll oceans such as offshore of the 200‐m isobath off Patagonia. We find no compelling evidence for an influence of dust as an enhancer of phytoplankton biomass either on shelf or proximal open ocean waters of the southwestern Atlantic Ocean. For open ocean waters this is consistent with a lack of source‐inherited bioavailable iron in dust samples. Future case studies addressing similar questions should concentrate on dust sources with identified high contents of bioavailable iron, particularly in the Southern Hemisphere where atmospheric processing of iron is weak. Key Points: We present the first decadal time series of surface dust mass flux in PatagoniaThe first event‐based study in the southwestern Atlantic Ocean shows no evidence for an influence of dust on chlorophyll‐a concentrationsSource‐inherited low concentrations of bioavailable iron preclude enhancement of primary producers' biomass in proximal open ocean waters [ABSTRACT FROM AUTHOR]

This review provides a synthesis of what is currently known about the natural and anthropogenic fluxes of fluorine on Earth, offering context for an evaluation of the growing environmental impact of human‐induced F mobilization and use. The largest flux of F at the Earth's surface derives from the mobilization of F during chemical (2.2 Tg F/yr (where 1 Tg = 1012 g) and mechanical (7 Tg F/yr) weathering of rocks. Humans supplement these fluxes by mining fluorospar and apatite ores to make a variety of industrial chemicals and fertilizers, mobilizing 2.9 and 7.6 Tg F/yr, respectively. Other large anthropogenic fluxes derive from the manufacture of bricks (1.8 Tg F/yr) and extraction of groundwater (0.9 to 1.7 Tg F/yr). Rivers deliver ~3.6 Tg/yr of dissolved fluoride to the oceans, where the mean residence time of dissolved F in seawater is ~500,000 yr. F is removed from the oceans by the deposition of terrigenous (4.3 Tg F/yr) and authigenic sediments (1.24 Tg F/yr), and approximately 10 Tg F/yr is removed from the surface of the Earth by subduction of the oceanic lithosphere. Humans have increased the flux of F to the atmosphere and in rivers by more than a factor of 2, with the largest impacts stemming from the use of phosphorus fertilizers, the production of brick, and extraction of groundwater. Despite their well‐documented toxicity, perfluoroalkyl substances make only a small contribution to F emitted to the atmosphere and natural waters. Key Point: The movement of F in its global cycle has been substantially impacted by human activities [ABSTRACT FROM AUTHOR]

A large amount of soil carbon in northern temperate and boreal regions could be emitted as greenhouse gases in a warming future. However, lacking detailed microbial processes such as microbial dormancy in current biogeochemistry models might have biased the quantification of the regional carbon dynamics. Here the effect of microbial dormancy was incorporated into a biogeochemistry model to improve the quantification for the last century and this century. Compared with the previous model without considering the microbial dormancy, the new model estimated the regional soils stored 75.9 Pg more C in the terrestrial ecosystems during the last century and will store 50.4 and 125.2 Pg more C under the RCP8.5 and RCP2.6 scenarios, respectively, in this century. This study highlights the importance of the representation of microbial dormancy in earth system models to adequately quantify the carbon dynamics in the northern temperate and boreal natural terrestrial ecosystems. [ABSTRACT FROM AUTHOR]

Primary productivity of forest ecosystems depends on the availability of plant‐essential mineral nutrients. Because nutrient demand of trees often exceeds nutrient supply from rock, tree nutrition is sustained by efficient reutilization of organic‐bound nutrients. These nutrients are continuously returned from trees to the forest floor in litterfall. However, over millennia nutrient limitation may develop in landscapes from which nutrients are permanently lost by drainage and erosion. Such a deficit is prevented if advection of unweathered bedrock toward the surface as driven by erosion continuously supplies fresh nutrients. Yet the mechanisms and the depth range over which this deep nutrient resource is accessed are poorly known. We show that in two montane temperate forest ecosystems in the Black Forest and Bavarian Forest the geogenic source of nutrients was found within a depth zone of several meters. This deep zone contains a large pool of biologically available nutrients. We applied isotope ratios as proxies for nutrient uptake depth, and we tracked the regolith depth at which the isotope ratios of 87Sr/86Sr and 10Be(meteoric)/9Be match the respective values in plant tissue. We mapped the depth distribution of the biologically available calcium‐bound form of the most plant‐essential mineral nutrient phosphorus and found that the depth of phosphorus availability is as deep or even deeper as the range defined by the isotope ratios. We conclude that nutrient supply from a regolith depth of several meters is critical for forest ecosystem function in landscapes of moderate hillslopes and rainfall that are affected by permanent nutrient loss. Key Points: Combined 87Sr(radiogenic)/86Sr and 10Be(cosmogenic)/9Be isotope ratios were applied as proxies for mineral nutrient uptake depthThese systems suggest mineral nutrient uptake by Picea abies and Fagus sylvatica of 2 to >10 m depthPotentially biologically available calcium phosphate is not available at a depth shallower than 3 mLoss of mineral nutrients from the nutrient‐rich forest floor is balanced by mineral nutrient uptake from the deep saprolite [ABSTRACT FROM AUTHOR]

Soil drying and wetting cycles promote carbon (C) release through large heterotrophic respiration pulses at rewetting, known as the "Birch" effect. Empirical evidence shows that drier conditions before rewetting and larger changes in soil moisture at rewetting cause larger respiration pulses. Because soil moisture varies in response to rainfall, these respiration pulses also depend on the random timing and intensity of precipitation. In addition to rewetting pulses, heterotrophic respiration continues during soil drying, eventually ceasing when soils are too dry to sustain microbial activity. The importance of respiration pulses in contributing to the overall soil heterotrophic respiration flux has been demonstrated empirically, but no theoretical investigation has so far evaluated how the relative contribution of these pulses may change along climatic gradients or as precipitation regimes shift in a given location. To fill this gap, we start by assuming that heterotrophic respiration rates during soil drying and pulses at rewetting can be treated as random variables dependent on soil moisture fluctuations, and we develop a stochastic model for soil heterotrophic respiration rates that analytically links the statistical properties of respiration to those of precipitation. Model results show that both the mean rewetting pulse respiration and the mean respiration during drying increase with increasing mean precipitation. However, the contribution of respiration pulses to the total heterotrophic respiration increases with decreasing precipitation frequency and to a lesser degree with decreasing precipitation depth, leading to an overall higher contribution of respiration pulses under future more intermittent and intense precipitation. Specifically, higher rainfall intermittency at constant total rainfall can increase the contribution of respiration pulses up to ∼10 % or 20 % of the total heterotrophic respiration in mineral and organic soils, respectively. Moreover, the variability of both components of soil heterotrophic respiration is also predicted to increase under these conditions. Therefore, with future more intermittent precipitation, respiration pulses and the associated nutrient release will intensify and become more variable, contributing more to soil biogeochemical cycling. [ABSTRACT FROM AUTHOR]

Widespread destruction from large-scale disasters results in lengthy and costly recovery of damaged infrastructure and communities, with societal and economic impacts persisting many years after a hazard event. Robust and coherent reconstruction planning and rapid execution play pivotal roles in ameliorating time-consuming postdisaster recovery. Reconstruction generally constitutes a considerable portion of an entire disaster recovery process that requires significant resources, including materials, workforce, funding, time, and others. To pursue maximum socioeconomic benefits, which can be one of the critical goals of the postdisaster recovery process, optimized recovery strategies should be designed by considering given federal, state, and local resources. Even though recent studies have proposed disaster recovery planning and execution models, they rarely addressed social and economic indicators required for comprehensive postdisaster recovery plans. This paper presents a new postdisaster recovery prioritization model, including social and economic factors, that evaluates priorities of damaged facilities recovery projects in affected regions through a resource allocation analysis. The primary goal of the proposed model is to optimize resource allocation and quantify and maximize socioeconomic benefits for a postdisaster reconstruction project portfolio through multicriteria decision analysis and multiobjective optimization. Also, this research study adopts a modular construction technique as a potential solution for facilitating the recovery processes, which can significantly reduce their time and cost. The proposed model is expected to provide a comprehensive decision-making process for researchers and practitioners to design a postdisaster recovery plan and arrange their available resources by considering the socioeconomic factors of affected communities. [ABSTRACT FROM AUTHOR]

As atmospheric dust deposition continues to increase across the southwestern United States, it has the potential to alter ecosystem productivity and structure by delivering nutrients, base cations, and pollutants to remote mountain sites. Due to the sparse distribution of dust monitoring sites, open questions remain about the spatial and temporal variability of dust fluxes and composition across mountainous terrain. We present a 1 year (November 2017 to November 2018) record of seasonal dust fluxes and composition from an elevation transect across the Colorado Front Range extending from the urban plains to the remote alpine. At all nine sites, dust was enriched in the essential nutrient phosphorus and the metals copper, zinc, lead, and cadmium, elements that are enriched in dust deposited at sites across the Rocky Mountain West. We observed a seasonal pattern in dust composition, with the highest concentrations of zinc and cadmium during the summer, when back trajectory modeling suggested a greater contribution of dust from local urban and agricultural regions to the east of the collection sites. During the summer, there was also a trend of higher dust fluxes at lower elevations; dust fluxes ranged from 18.9 ± 0.1 g m−2 yr−1 on the plains to 5.9 ± 0.2 g m−2 yr−1 in the alpine. Our results suggest that urban and agricultural land east of the Colorado Front Range is an important source of nutrients and pollutants to all elevations of the mountain range. Plain Language Summary: Atmospheric dust deposition can be an important source of nutrients and pollutants to ecosystems and has been responsible for changes in ecosystem productivity and biodiversity. Currently, dust activity is increasing across the southwestern United States due to land use change and drought. Many questions remain about how the amount and chemical composition of dust varies throughout the year and across mountainous terrain. Over 1 year and at nine sites, we measured the amount and chemical composition of dust deposited to the Colorado Front Range. We found that during the summer, there was more dust deposited at lower elevations, which are close to urban and agricultural dust sources. In addition, the dust contained high levels of the nutrient phosphorus and many metals that are associated with anthropogenic emissions. Our results suggest that anthropogenic dust is transported up into the mountains, where it could influence ecosystem biodiversity and water quality. Given the growing evidence that the Southwest is becoming dustier, we call for more comprehensive dust monitoring and land management practices that work to limit dust emissions. Key Points: Atmospheric dust was enriched in phosphorus and metals, similar to dust deposited across the Rocky Mountain WestHigh metal concentrations during the summer corresponded to upslope winds, which bring urban air masses into the mountainsDuring the summer, dust deposition was higher at low‐elevation sites that are close to urban and agricultural dust sources [ABSTRACT FROM AUTHOR]

Dust emissions from southwestern North America (Southwest) impact human health and water resources. Whereas a growing network of regional dust reconstructions characterizes the long‐term natural variability of dustiness in the Southwest, short‐term fluctuations remain unexplored. We present a 4.5‐millennia near‐annual record of dust mass accumulation rates from the southern Rocky Mountains, CO. Using microscanning X‐ray fluorescence and a geochemical end‐member mixing model, the record confirms dust increased with human disturbance beginning around 1880 CE, reversing a long‐term decreasing trend potentially related to changes in effective moisture, wind, and vegetation. However, increases in dust mass accumulation rates do not correspond to years or periods of drought, as characterized by tree rings. This result suggests sediment supply and transport mechanisms have a strong influence on dust deposition. The record shows the Southwest is naturally prone to dustiness; however, human disturbances have a large influence on dust emissions, which can be mitigated by changing land use. Plain Language Summary: We use a sediment record to characterize the long‐term naturally driven changes in dust deposition over the past 4.5 millennia. The record shows a long‐term trend toward decreasing dust deposition, which was reversed with human‐induced land disturbance beginning in the middle nineteenth century. The long‐term trend may be related to effective moisture, wind, and vegetation. Nonetheless, there appears to be little relationship between known drought events and increased dust deposition, suggesting the controls on dust deposition include factors such as sediment source and transport mechanisms acting independently of drought. Key Points: A new 4,500‐year‐long record of natural dust deposition shows a long‐term decreasing trendDrought variability, as characterized by tree rings, is not closely linked with dust mass accumulationHuman disturbance substantially increased dust deposition since 1880 CE [ABSTRACT FROM AUTHOR]

Soil microorganisms are known to survive periods of aridity and to recover rapidly after wetting events, with the ability to transition between a dormant state in dry conditions and an active state in wet conditions. Though this dynamic behavior has been previously incorporated into soil carbon respiration modeling frameworks, a direct comparison between this active‐dormant transition mechanism and a more simplified first‐order model has yet to be made. Here, we demonstrate the necessary extent of model complexity needed to reproduce transient carbon respiration rates obtained from a set of soil incubation experiments implemented over a range of soil depths and time intervals. Two approaches are tested, one uses simplified first‐order kinetics, whereas the other employs a transition between active and dormant biomass. The performance of each model is evaluated using an Akaike Information Criterion (AIC) based on the accuracy with which they reproduce an experimental dataset consisting of two sets of time series soil incubations collected across a range of time and depth resolutions. Based on the AIC evaluation and model‐data comparison, we conclude that a dormancy‐enabled model featuring two distinct microbial strategists performs best for the majority of the soil profile (above 108 cm) for both high and low depth resolution and sampling frequency, despite the added parameters required. In contrast, the first‐order model achieves better AIC scores when simulating our deepest soils (112–165 cm), where moisture fluctuations are expected to be less prevalent. These results guide how and where we choose to apply more cost intensive models. Plain Language Summary: Microorganisms in the soil environment respire substantial amounts of CO2, comprising an important flux of carbon to the atmosphere and playing a key role in moderating carbon storage. We seek to improve our ability to model the amount of CO2 emitted from soil by evaluating two modeling frameworks against lab‐measured respiration rates using natural soil samples at a range of soil moistures. Results show that a simplified model is more suitable for interpreting the soil respiration rates below 100 cm, while a more complex simulation of the activity of microbes as a function of soil moisture is necessary for shallower depths. Key Points: Soil incubation results exhibit a transient response in soil carbon respiration rates after a wetting event (the Birch effect)Two models with different structures and levels of complexity (first‐order and dormancy‐incorporated) were tested against two sets of data with distinct spatial and temporal resolutionThe dormancy‐incorporated model achieves statistically favorable values while simulating incubation data for soil samples taken above ~100 cm, and the first‐order model achieves better AIC values when simulating deeper soil samples, which comprise a minor portion of the overall CO2 flux [ABSTRACT FROM AUTHOR]

Snowmelt‐fed springs and small (0.5 km2) upland catchments in alpine areas of the western United States contribute significantly to the quantity and inorganic chemistry of water delivered to downstream basins but have not been studied extensively. Mineral weathering, transit time, and hydrologic mixing control the solute chemistry of waters that drain the upland zone of Niwot Ridge, Colorado Front Range, and adjacent areas in the granitic core of the Southern Rocky Mountains. Water in 37 springs sampled in this study flows in generally short steep paths (~0.3 km) through shallow regolith with mean transit times (MTT) of weeks to months, producing solutions dominated by Si, Ca2+, Na+, and HCO3−, locally SO42−. Rock type is a significant control on spring, surface, and shallow groundwater chemistry, and plagioclase (oligoclase) is the major source of dissolved Na+ and Si. Concentrations of Ca2+ exceed stoichiometric predictions of oligoclase weathering by ~3.5×; excess Ca2+ likely represents weathering of aeolian material, vein calcite, or trace minerals. Concentrations of base cations and Si increase slowly with estimated MTT of 0.2 years for Niwot Ridge spring waters, and several years for shallow groundwater sampled by wells. Chemical weathering of silicate minerals is slow with estimated rates of ~2.0 and 0.2 pmol·m−2·s−1 for oligoclase and microcline, respectively; the most mineralized spring waters are saturated only with respect to kaolinite and montmorillonite. More than 50% of the dissolved base cations + Si measured in Boulder Creek at Orodell (~25 km downstream) accumulate before water emerges from alpine springs on Niwot Ridge. Warming global temperatures are shifting more high‐elevation precipitation to rain, potentially changing run‐off patterns, transit time, and solute loads. Acquisition of solutes by alpine waters thus has implications far beyond small upland catchments. [ABSTRACT FROM AUTHOR]

Developing and testing decadal‐scale predictions of soil response to climate change is difficult because there are few long‐term warming experiments or other direct observations of temperature response. As a result, spatial variation in temperature is often used to characterize the influence of temperature on soil organic carbon (SOC) stocks under current and warmer temperatures. This approach assumes that the decadal‐scale response of SOC to warming is similar to the relationship between temperature and SOC stocks across sites that are at quasi steady state; however, this assumption is poorly tested. We developed four variants of a Reaction‐network‐based model of soil organic matter and microbes using measured SOC stocks from a 4,000‐km latitudinal transect. Each variant reflects different assumptions about the temperature sensitivities of microbial activity and mineral sorption. All four model variants predicted the same response of SOC to temperature at steady state, but different projections of transient warming responses. The relative importance of Qmax, mean annual temperature, and net primary production, assessed using a machine‐learning algorithm, changed depending on warming duration. When mineral sorption was temperature sensitive, the predicted average change in SOC after 100 years of 5 °C warming was −18% if warming decreased sorption or +9% if warming increased sorption. When microbial activity was temperature sensitive but mineral sorption was not, average site‐level SOC loss was 5%. We conclude that spatial climate gradients of SOC stocks are insufficient to constrain the transient response; measurements that distinguish process controls and/or observations from long‐term warming experiments, especially mineral fractions, are needed. Key Points: Spatial climate gradients are insufficient for inferring transient temperature response of soil carbon decomposition and stocksThe temperature sensitivity of both microbial activity and mineral sorption has large effects on SOC responseMore comprehensive data, including SOC in mineral fractions, from long‐term warming experiments may help distinguish between model assumptions [ABSTRACT FROM AUTHOR]

Present gaps in the representation of key soil biogeochemical processes such as the partitioning of soil organic carbon among functional components, microbial biomass and diversity, and the coupling of carbon and nutrient cycles present a challenge to improving the reliability of projected soil carbon dynamics. We introduce a new soil biogeochemistry module linked with a well‐tested terrestrial biosphere model T&C. The module explicitly distinguishes functional soil organic carbon components. Extracellular enzymes and microbial pools are differentiated based on the functional roles of bacteria, saprotrophic, and mycorrhizal fungi. Soil macrofauna is also represented. The model resolves the cycles of nitrogen, phosphorus, and potassium. Model simulations for 20 sites compared favorably with global patterns of litter and soil stoichiometry, microbial and macrofaunal biomass relations with soil organic carbon, soil respiration, and nutrient mineralization rates. Long‐term responses to bare fallow and nitrogen addition experiments were also in agreement with observations. Some discrepancies between predictions and observations are appreciable in the response to litter manipulation. Upon successful model reproduction of observed general trends, we assessed patterns associated with the carbon cycle that were challenging to address empirically. Despite large site‐to‐site variability, fine root, fungal, bacteria, and macrofaunal respiration account for 33%, 40%, 24%, and 3% on average of total belowground respiration, respectively. Simulated root exudation and carbon export to mycorrhizal fungi represent on average about 13% of plant net primary productivity. These results offer mechanistic and general estimates of microbial biomass and its contribution to respiration fluxes and to soil organic matter dynamics. Key Points: We introduce a new microbial explicit soil biogeochemistry module into a terrestrial biosphere modelUncalibrated model simulations compared favorably with global patterns of soil biogeochemistry processesResults offer mechanistic estimates of microbe contribution to soil respiration and carbon dynamics [ABSTRACT FROM AUTHOR]

Aeolian dust is emerging as a significant vehicle for long‐range transport of microorganisms. Nonetheless, many factors relating to this highly influential dispersal mechanisms remain unresolved, including the variation in dispersal bacterial communities during stochastic desert dust events, and the effect of aeolian transit over continental and oceanic surfaces to these communities. Here we report a temporal study that encompassed multiple dust events to elucidate 16S rRNA gene‐defined changes in airborne bacterial communities at a continental‐peninsula site (Yongin, central South Korea) and a downwind offshore island site (Yonago, Honshu Island, Japan) both lying along the trajectory for dust event transport. Aerosol collected on nondust days at both sites generally reflected local origin from freshwater, marine, plant, and animal sources. At both sites, the relative abundance of spore‐forming bacteria (Bacillaceae) and organic‐aggregating bacteria (Cytophagaceae) was positively correlated with the mineral particle. Actinobacteria increased in relative abundance at the continental‐peninsula site during dust events, while marine bacterial signatures (mainly Alphaproteobacteria) were more prevalent in island site after dust events dissipated upon Japanese Sea. Overall, dust events increased the richness of airborne bacteria communities originating from inland desert and other area during early spring and are associated with more variations in airborne bacteria in the island site than the continental‐peninsula site. Airborne desert dust is likely a significant transport vehicle for bacteria. The transit of air masses over continental and marine surfaces is selective for some taxa which can be transported to distant sinks with potential impacts toward ecosystems and public health. Plain Language Summary: This is the first long‐term study for demonstrating microbial transport from desert storms, at the continent‐to‐island scale. The high throughput approach provides robust support for the key findings: (a) the diversities of airborne bacteria increased with dust dispersals from Chinese desert to the Japanese coast; (b) bacterial taxa include markers associated with desert microbial communities as well as human and plant pathogens were detected; and (c) transit over oceanic waters and anthropogenic polluted areas strongly selects for airborne bacterial populations through atmospheric stressors. These findings have broad relevance to understanding the drivers of global microbial biogeography. The issue of large range microbial transport has a wide‐ranging appeal in several areas including microbial ecology, oceanography (ocean‐atmospheric interactions), and public health (epidemiology of pathogens). Key Points: The richness of airborne bacteria increased with dust dispersals from Chinese desert to the Japanese coastBacterial taxa include markers associated with desert microbial communities as well as human and plant pathogens were detectedTransit over oceanic waters and anthropogenic polluted areas strongly selects for airborne bacterial populations through atmosphere [ABSTRACT FROM AUTHOR]

Soil organic matter (SOM) dynamics in ecosystem-scale biogeochemical models have traditionally been simulated as immeasurable fluxes between conceptually defined pools. This greatly limits how empirical data can be used to improve model performance and reduce the uncertainty associated with their predictions of carbon (C) cycling. Recent advances in our understanding of the biogeochemical processes that govern SOM formation and persistence demand a new mathematical model with a structure built around key mechanisms and biogeochemically relevant pools. Here, we present one approach that aims to address this need. Our new model (MEMS v1.0) is developed from the Microbial Efficiency-Matrix Stabilization framework, which emphasizes the importance of linking the chemistry of organic matter inputs with efficiency of microbial processing and ultimately with the soil mineral matrix, when studying SOM formation and stabilization. Building on this framework, MEMS v1.0 is also capable of simulating the concept of C saturation and represents decomposition processes and mechanisms of physico-chemical stabilization to define SOM formation into four primary fractions. After describing the model in detail, we optimize four key parameters identified through a variance-based sensitivity analysis. Optimization employed soil fractionation data from 154 sites with diverse environmental conditions, directly equating mineral-associated organic matter and particulate organic matter fractions with corresponding model pools. Finally, model performance was evaluated using total topsoil (0–20 cm) C data from 8192 forest and grassland sites across Europe. Despite the relative simplicity of the model, it was able to accurately capture general trends in soil C stocks across extensive gradients of temperature, precipitation, annual C inputs and soil texture. The novel approach that MEMS v1.0 takes to simulate SOM dynamics has the potential to improve our forecasts of how soils respond to management and environmental perturbation. Ensuring these forecasts are accurate is key to effectively informing policy that can address the sustainability of ecosystem services and help mitigate climate change. [ABSTRACT FROM AUTHOR]

Summary: Microbial phylogenetic diversity and species interactions in natural ecosystems have been investigated extensively, but our knowledge about their ecological roles, community dynamics and succession patterns is far from complete. This knowledge is essential to understand the complicated interactions of microorganisms in natural ecosystems. Here, an artificial ecosystem model of microorganisms was constructed from oil‐well products and cultivated in a chemostat to investigate the succession pattern of alkane‐degrading bacteria, a functional population in oil reservoirs. Their abundance was quantified by an improved qPCR technique. Our results showed that the phylogenetic structure of this artificial ecosystem model is stable during most of the chemostat cultivation process, while the genotype structure of alkane‐degrading bacteria containing alkB genes shifted and their relative abundance oscillated similarly to a sinusoidal curve, like the succession pattern of producers in the Lotka–Volterra model. These results suggest that some theoretical frameworks of macroecology may work well in microbial ecosystems and be an efficient tool to understand them. [ABSTRACT FROM AUTHOR]

Abstract: A large gap in understanding the effects of atmospheric dust at all spatial scales is uncertainty about how much and whence dust is emitted annually. Direct digital recording of dust emission at high spatial and temporal resolution would together with periodic flux measurements support improved estimates of local‐scale dust flux. Remote camera recording of dust‐emitting settings on and around Soda Lake (Mojave Desert) was conducted every 15 min during daylight between 10 November 2010 and 31 December 2016. Examination of 135,000 images revealed frequent dust events characterized as dust days, 68 per year on average, when dust plumes obscured mountains beyond areas of dust generation. Dust was not observed from examination of satellite retrievals (Moderate Resolution Imaging Spectroradiometer and Geostationary Operational Environmental Satellite System) during six cloudless days of extreme emission. Estimated masses of emitted dust fractions were made from measured horizontal mass flux, sediment particle sizes, and areas of dust generation. Between April 2000 and June 2013, nearly 4 Tg/year of dust (particles < 63 μm) were emitted across the study area. Higher rates (about 7 Tg/year) were estimated following the December 2010 Mojave River flood that deposited sediment across the lake basin. Within the Mojave and Great Basin deserts of western North America, many settings akin to those at Soda Lake similarly emit dust that is rarely detected in satellite retrievals, implying that local and regional dust emissions from western North America are far underestimated and that, by extension to relatively small dust‐source areas across all drylands, global dust emissions may also be greatly underestimated. [ABSTRACT FROM AUTHOR]

Abstract: Airborne dust can alter ecosystem productivity and biogeochemical cycling by enhancing atmospheric nutrient and pollutant deposition. Wet dust deposition (dust‐in‐rain) is less frequently quantified than dry deposition but represents a potentially significant flux to ecosystems. We quantified dust‐in‐rain event frequency, dust influence on rainwater ionic and elemental composition, and wet dissolved and particulate deposition during weeks affected by dust‐in‐rain and all other weeks (background samples) at two sites across Texas (one arid, Guadalupe Mountains, and one humid, Gulf coastal prairie) during the centennial‐scale 2012 drought. Although dust‐in‐rain was sporadic, a clear dust signature was evident in rainwater. Compared to background samples, crustal species (Fe and Mn) were more prevalent than anthropogenic species (Cu and Zn) in dust‐in‐rain. Volume‐weighted mean rainwater concentrations of K+, Na+, and Cl− and of all particulate elements were also significantly greater in dust‐in‐rain than in background samples. In the Guadalupe Mountains, West Texas, dust‐in‐rain contributed nearly 50% of annual wet dissolved Na+ and Cl− and 22–35% of dissolved Ca2+, Mg2+, K+, and PO43− deposition. In the Gulf coastal prairie, East Texas, dust‐in‐rain delivered 19%, 13%, and 9% of annual wet dissolved PO43−, Ca2+, and K+ deposition, respectively. A major proportion of annual wet particulate deposition (>56% in Guadalupe Mountains and ~30% in Gulf coastal prairie) similarly occurred with dust‐in‐rain. Our findings show that infrequent dust‐in‐rain events constitute an important but overlooked pathway for elemental flux to ecosystems in arid source and humid receptor sites during severe drought. Quantifying these fluxes is crucial to determine dust impacts on ecosystem processes. [ABSTRACT FROM AUTHOR]

CO2 production in soils responds strongly to changes in temperature and moisture, but the magnitude of such responses at different timescales remains difficult to predict. Knowledge of the mechanisms leading to the often observed interactions in the effects of these drivers on soil CO2 emissions is especially limited. Here we test the ability of different soil carbon models to simulate responses measured in soils incubated at a range of moisture levels and cycled through 5, 20, and 35°C. We applied parameter optimization methods while modifying two structural components of models: (1) the reaction kinetics of decomposition and uptake and (2) the functions relating fluxes to soil moisture. We found that the observed interactive patterns were best simulated by a model using Michaelis-Menten decomposition kinetics combined with diffusion of dissolved carbon (C) and enzymes. In contrast, conventional empirical functions that scale decomposition rates directly were unable to properly simulate the main observed interactions. Our best model was able to explain 87% of the variation in the data. Model simulations revealed a central role of Michaelis-Menten kinetics as a driver of temperature sensitivity variations as well as a decoupling of decomposition and respiration C fluxes in the short and mid-term, with general sensitivities to temperature and moisture being more pronounced for respiration. Sensitivity to different model parameters was highest for those affecting diffusion limitations, followed by activation energies, the Michaelis-Menten constant, and carbon use efficiency. Testing against independent data strongly validated the model (R2D 0:99) and highlighted the importance of initial soil C pool conditions. Our results demonstrate the importance of model structure and the central role of diffusion and reaction kinetics for simulating and understanding complex dynamics in soil C. [ABSTRACT FROM AUTHOR]

The role of soil microorganisms in regulating soil organic matter (SOM) decomposition is of primary importance in the carbon cycle, in particular in the context of global change. Modeling soil microbial community dynamics to simulate its impact on soil gaseous carbon (C) emissions and nitrogen (N) mineralization at large spatial scales is a recent research field with the potential to improve predictions of SOM responses to global climate change. In this study we present a SOM model called ORCHIMIC, which utilizes input data that are consistent with those of global vegetation models. ORCHIMIC simulates the decomposition of SOM by explicitly accounting for enzyme production and distinguishing three different microbial functional groups: fresh organic matter (FOM) specialists, SOM specialists, and generalists, while also implicitly accounting for microbes that do not produce extracellular enzymes, i.e., cheaters. ORCHIMIC and two other organic matter decomposition models, CENTURY (based on first-order kinetics and representative of the structure of most current global soil carbon models) and PRIM (with FOM accelerating the decomposition rate of SOM), were calibrated to reproduce the observed respiration fluxes of FOM and SOM from the incubation experiments of Blagodatskaya et al. (2014). Among the three models, ORCHIMIC was the only one that effectively captured both the temporal dynamics of the respiratory fluxes and the magnitude of the priming effect observed during the incubation experiment. ORCHIMIC also effectively reproduced the temporal dynamics of microbial biomass. We then applied different idealized changes to the model input data, i.e., a 5K stepwise increase of temperature and/or a doubling of plant litter inputs. Under 5K warming conditions, ORCHIMIC predicted a 0.002K-1 decrease in the C use efficiency (defined as the ratio of C allocated to microbial growth to the sum of C allocated to growth and respiration) and a 3% loss of SOC. Under the double litter input scenario, ORCHIMIC predicted a doubling of microbial biomass, while SOC stock increased by less than 1% due to the priming effect. This limited increase in SOC stock contrasted with the proportional increase in SOC stock as modeled by the conventional SOC decomposition model (CENTURY), which can not reproduce the priming effect. If temperature increased by 5K and litter input was doubled, ORCHIMIC predicted almost the same loss of SOC as when only temperature was increased. These tests suggest that the responses of SOC stock to warming and increasing input may differ considerably from those simulated by conventional SOC decomposition models when microbial dynamics are included. The next step is to incorporate the ORCHIMIC model into a global vegetation model to perform simulations for representative sites and future scenarios. [ABSTRACT FROM AUTHOR]

The evaluation of the forage quality nutritive value and biomass usually takes multiple harvests and is considered time consuming, labor intensive, and expensive. The use of sensors to evaluate different forage traits has been proposed as a method to alleviate this problem. However, most analytical techniques involve the use of traditional linear methods for prediction, but prediction models can still be improved with the use of nonlinear methods. Thus, the objectives of this study are twofold: (i) to evaluate the performance of different prediction methodologies in important forage agronomic traits; and (ii) to evaluate the impact of sensor variables on predictive model performance in the different methods. The nondestructive multisensor system that accommodates spectral, ultrasonic, and laser data was tested on a bermudagrass [Cynodon dactylon (L.) Pers] experiment. Partial least square regression, ridge regression, support vector machine with radial kernel (SVM), and random forest were tested for the prediction performance. The random forest had the best performance, with 0.89 correlation for dry matter yield trait prediction, whereas SVM performed best in the remaining 15 traits, with correlation ranging from 0.72 to 0.95. Besides the prediction performance of statistical models, this study also provided some insight about the importance of variables by removing variables and reevaluating the model performance in dry matter yield. Overall, most of the traits in this study could be reliably predicted by the SVM. The multisensor system can facilitate the measurement of agriculturally important traits in a time-, labor- and cost-efficient way. [ABSTRACT FROM AUTHOR]

Previous remote sensing studies (2005–2008) have identified Namibia’s Kuiseb as the dustiest river in southern Africa. The purpose of this study was to extend the dust event record through to 2014, and to examine the nature of the surfaces from which this satellite imagery indicates these dust plumes originate. The new 10-year record confirms the delta as the dustiest geomorphological unit (54% of plumes), followed by the gravel plain (28%) and then the river (8%). No dust originated from the Namib Sand Sea dunes or interdunes. Field observations provided detail about the geomorphological and sedimentological setting of the landscape components. The laboratory analysis focused on the size characteristics of 153 surface sediment samples collected from the Kuiseb main channel, its terraces, delta, gravel plain surfaces and tributaries, dunes and interdune. This study has identified that surface sediments suitable for dust production increase towards the coast with particular ‘dusty’ floodplain surfaces between Swartbank and Rooibank and the Kuiseb delta. We suggest that silt crusts formed as the flood water dissipate, provide a main source of potentially entrainable material for emission. The crusts consist entirely of silt- and clay-sized materials, with a maximum of 97% <63 μm, 39% <10 μm and 6% <2 μm. Anthropogenic disturbances of the surfaces are potentially playing a role in the production of dust, with the area undergoing significant development. [ABSTRACT FROM PUBLISHER]

The geochemical characteristics of aeolian and surface materials in potential source areas of dust are frequently employed in environmental reconstructions as proxies of past climate and as source tracers of aeolian sediments deposited in downwind areas. However, variations in the geochemical characteristics of these aeolian deposits that result from near-surface winds are currently poorly understood. In this study, we collected surface samples from the Ala Shan Plateau (a major potential dust source area in Central Asia) to determine the influence of aeolian processes on the geochemical characteristics of aeolian transported materials. Correlation analyses show that compared with surface materials, the elements in transported materials (e.g., Cu, As, Pb, Mn, Zn, Al, Ca, Fe, Ga, K, Mg, P, Rb, Co, Cr, Na, Nb, Si, and Zr) were subjected to significant sorting by aeolian processes, and the sorting also varied among different particle size fractions and elements. Variations in wind velocity were significantly correlated with the contents of Cr, Ga, Sr, Ca, Y, Nd, Zr, Nb, Ba, and Al, and with the Zr/Al, Zr/Rb, K/Ca, Sr/Ca, Rb/Sr, and Ca/Al ratios. Given the great variation in the geochemical characteristics of materials transported under different aeolian processes relative to those of the source materials, these results indicate that considerable uncertainty may be introduced to analyses by using surface materials to trace the potential source areas of aeolian deposits that accumulate in downwind areas. [ABSTRACT FROM AUTHOR]

Forest plantations have been widely used as an effective measure for increasing soil carbon (C), and nitrogen (N) stocks and soil enzyme activities play a key role in soil C and N losses during decomposition of soil organic matter. However, few studies have been carried out to elucidate the mechanisms behind the differences in soil C and N cycling by different tree species in response to climate warming. Here, we measured the responses of soil's extracellular enzyme activity (EEA) to a gradient of temperatures using incubation methods in 78-year-old forest plantations with different tree species. Based on a soil enzyme kinetics model, we established a new statistical model to investigate the effects of temperature and tree species on soil EEA. In addition, we established a tree species-enzyme-C=N model to investigate how temperature and tree species influence soil C=N contents over time without considering plant C inputs. These extracellular enzymes included C acquisition enzymes (β-glucosidase, BG), N acquisition enzymes (N-acetylglucosaminidase, NAG; leucine aminopeptidase, LAP) and phosphorus acquisition enzymes (acid phosphatases). The results showed that incubation temperature and tree species significantly influenced all soil EEA and Eucalyptus had 1.01-2.86 times higher soil EEA than coniferous tree species. Modeling showed that Eucalyptus had larger soil C losses but had 0.99-2.38 times longer soil C residence time than the coniferous tree species over time. The differences in the residual soil C and N contents between Eucalyptus and coniferous tree species, as well as between slash pine (Pinus elliottii Engelm. var. elliottii) and hoop pine (Araucaria cunninghamii Ait.), increase with time. On the other hand, the modeling results help explain why exotic slash pine can grow faster, as it has 1.22-1.38 times longer residual soil N residence time for LAP, which mediate soil N cycling in the long term, than native coniferous tree species like hoop pine and kauri pine (Agathis robusta C. Moore). Our results will be helpful for understanding the mechanisms of soil C and N cycling by different tree species, which will have implications for forest management. [ABSTRACT FROM AUTHOR]