Journal Paper Digests 2022 #18
- Cover crop functional types differentially alter the content and composition of soil organic carbon in particulate and mineral-associated fractions
- Design and development of low-power, long-range data acquisition system for beehives-BeeDAS
- On the Uncertainty Induced by Pedotransfer Functions in Terrestrial Biosphere Modeling
- Deep-C storage: Biological, chemical and physical strategies to enhance carbon stocks in agricultural subsoils
- Soil health and microplastics: a review of the impacts of microplastic contamination on soil properties
- Soil acidification induced by intensive agricultural use depending on climate
Soil acidification induced by intensive agricultural use depending on climate
Purpose Soil acidification is a major issue in agricultural ecosystems. However, how agricultural land uses shape the soil pH pattern and affect soil acidification on a regional scale are still poorly understood. The research aims to investigate the influences of typical agricultural practices on soil acidification across different climate zones of eastern China.
Materials and methods Soil samples were collected from 240 sites and 3 land uses per site (uplands, paddies, and adjacent woodlands) across four climate zones (mid-temperate, warm temperate, subtropical, and tropical regions) of eastern China. Soil pH was quantified for each soil samples. The mean annual temperature (MAT) and mean annual precipitation (MAP) at each site were also analyzed.
Results and discussion Climate was significantly associated with soil acidification. The differences in soil pH between adjacent land use types ranged from 0.02 to 1.12, whereas those between climate zones ranged from 0.34 to 2.22. Alkaline soils (cooler climates) exhibited a stronger acidification pace than acidic soils (warmer climates). Uplands resulted in alarming decrease in soil pH by 1.12 units relative to adjacent woodlands in mid-temperate zone, which may be induced by the dramatic loss of soil carbon. Acidification of uplands was stronger than that of paddies, owing to higher soil nitrification and carbon mineralization. Croplands had higher soil pH than adjacent woodlands only in the subtropics, indicating that agricultural practices in this zone were effective to retard soil acidification.
Conclusion We demonstrated, for the first time, the direction and intensity of the differences in soil pH levels among adjacent agricultural lands and woodlands depending on climate. As the two common agricultural croplands across eastern China, uplands have stronger acidification relative to paddies, particularly in the mid-temperate zone. Proper agricultural management practices to avoid carbon losses and preserve the flooding status of paddies should be considered to resist acidification of cropland soils.
Soil health and microplastics: a review of the impacts of microplastic contamination on soil properties
Purpose Soil is a thin coating of matter that covers the earth’s surface, formed through the process of rock weathering. It is a natural filter for impurities in groundwater and is very important to human health. Recently, some studies from around the world have confirmed that the presence of microplastics in soil is increasing. However, most of these studies only examined the impacts of soil microplastic contamination one or two soil health indicators, rather than study all three soil health indicators at once. Methods In this review, we selected papers published internationally in the past decade and examined the trend of the effects of soil microplastic contamination on all three soil health indicators. Results and discussion Soil microplastic contamination resulted in either an increase or decrease in the trend of the effects on physicochemical and biological soil properties. In other cases, microplastic contaminants do not affect soil properties. The alteration of soil health properties by microplastics was associated with a couple of reasons such as microplastic concentrations and types, changes in soil mechanics and microorganisms. Conclusions The current impact and severity of soil microplastic contamination on soil health properties are expected to persist for a long time, especially with increasing global plastic production. Therefore, more research is required to continuously assess the impact of microplastic contamination on other indicators of soil health that has not been studied previously.
Deep-C storage: Biological, chemical and physical strategies to enhance carbon stocks in agricultural subsoils
Due to their substantial volume, subsoils contain more of the total soil carbon (C) pool than topsoils. Much of this C is thousands of years old, suggesting that subsoils offer considerable potential for long-term C sequestration. However, knowledge of subsoil C behaviour and manageability remains incomplete, and subsoil C storage potential has yet to be realised at a large scale, particularly in agricultural systems. A range of biological (e.g. deep-rooting), chemical (e.g. biochar burial) and physical (e.g. deep ploughing) C sequestration strategies have been proposed, but are yet to be assessed. In this review, we identify the main factors that regulate subsoil C cycling and critically evaluate the evidence and mechanistic basis of subsoil strategies designed to promote greater C storage, with particular emphasis on agroecosystems. We assess the barriers and opportunities for the implementation of strategies to enhance subsoil C sequestration and identify 5 key current gaps in scientific understanding. We conclude that subsoils, while highly heterogeneous, are in many cases more suited to long-term C sequestration than topsoils. The proposed strategies may also bring other tangible benefits to cropping systems (e.g. enhanced water holding capacity and nutrient use efficiency). Furthermore, while the subsoil C sequestration strategies we reviewed have large potential, more long-term studies are needed across a diverse range of soils and climates, in conjunction with chronosequence and space-for-time substitutions. Also, it is vital that subsoils are more consistently included in modelled estimations of soil C stocks and C sequestration potential, and that subsoil-explicit C models are developed to specifically reflect subsoil processes. Finally, further mapping of subsoil C is needed in specific regions (e.g. in the Middle East, Eastern Europe, South and Central America, South Asia and Africa). Conducting both immediate and long-term subsoil C studies will fill the knowledge gaps to devise appropriate soil C sequestration strategies and policies to help in the global fight against climate change and decline in soil quality. In conclusion, our evidence-based analysis reveals that subsoils offer an untapped potential to enhance global C storage in terrestrial ecosystems.
On the Uncertainty Induced by Pedotransfer Functions in Terrestrial Biosphere Modeling
Hydrological, ecohydrological, and terrestrial biosphere models depend on pedotransfer functions for computing soil hydraulic parameters based on easily measurable variables, such as soil textural and physical properties. Several pedotransfer functions have been derived in the last few decades, providing divergent estimates of soil hydraulic parameters. In this study, we quantify how uncertainties embedded in using different pedotransfer functions propagate to ecosystem dynamics, including simulated hydrological fluxes and vegetation response to water availability. Using a state-of-the-art ecohydrological model applied at 79 sites worldwide, we show that uncertainties related to pedotransfer functions can affect both hydrological and vegetation dynamics. Uncertainties in evapotranspiration, plant productivity, and vegetation structure, quantified as leaf area, are in the order of similar to 10% at annual time scales. Runoff and groundwater recharge uncertainties are one order of magnitude larger. All uncertainties are largely amplified when small-scale topography is taken into account in a distributed domain, especially for water-limited ecosystems with low permeability soils. Overall, pedotransfer function related uncertainties for a given soil type are higher than uncertainties across soil types in both hydrological and ecosystem dynamics. The magnitude of uncertainties is climate-dependent but not soil type-dependent. Evapotranspiration, vegetation structure, and plant productivity uncertainties are higher in water-limited semiarid climates, whereas groundwater recharge uncertainties are higher in climates where potential evapotranspiration is comparable to precipitation.
Cover crop functional types differentially alter the content and composition of soil organic carbon in particulate and mineral-associated fractions
Cover crops (CCs) can increase soil organic carbon (SOC) sequestration by providing additional OC residues, recruiting beneficial soil microbiota, and improving soil aggregation and structure. The various CC species that belong to distinct plant functional types (PFTs) may differentially impact SOC formation and stabilization. Biogeochemical theory suggests that selection of PFTs with distinct litter quality (C:N ratio) should influence the pathways and magnitude of SOC sequestration. Yet, we lack knowledge on the effect of CCs from different PFTs on the quantity and composition of physiochemical pools of SOC. We sampled soils under monocultures of three CC PFTs (legume [crimson clover]; grass [triticale]; and brassica [canola]) and a mixture of these three species, from a long-term CC experiment in Pennsylvania, USA. We measured C content in bulk soil and C content and composition in contrasting physical fractions: particulate organic matter, POM; and mineral-associated organic matter, MAOM. The bulk SOC content was higher in all CC treatments compared to the fallow. Compared to the legume, monocultures of grass and brassica with lower litter quality (wider C:N) had higher proportion of plant-derived C in POM, indicating selective preservation of complex structural plant compounds. In contrast, soils under legumes had greater accumulation of microbial-derived C in MAOM. Our results for the first time, revealed that the mixture contributed to a higher concentration of plant-derived compounds in POM relative to the legume, and a greater accumulation of microbial-derived C in MAOM compared to monocultures of grass and brassica. Mixtures with all three PFTs can thus increase the short- and long-term SOC persistence balancing the contrasting effects on the chemistries in POM and MAOM imposed by monoculture CC PFTs. Thus, despite different cumulative C inputs in CC treatments from different PFTs, the total SOC stocks did not vary between CC PFTs, rather PFTs impacted whether C accumulated in POM or MAOM fractions. This highlights that CCs of different PFTs may shift the dominant SOC formation pathways (POM vs. MAOM), subsequently impacting short- and long-term SOC stabilization and stocks. Our work provides a strong applied field test of biogeochemical theory linking litter quality to pathways of C accrual in soil.
Design and development of low-power, long-range data acquisition system for beehives-BeeDAS
Decision making capability of a system is highly dependent upon the quality and quantity of training data. Majority of beehive monitoring systems developed for research purposes are designed to collect data through a small set of sensors, and from locations with little geographic diversity. This hinders the development of a dataset that can be used to effectively train machine learning models. In this work, we explain the design and development of a multi-sensory, remote data acquisition system for beehives (BeeDAS), with focus on low-power consumption and long-range communication. We address design challenges associated with such systems and highlight the critical issues that need consideration. The proposed system enables collection of data from beehives at remote locations and harsh environment. Results of field deployments elucidate the effectiveness of various sensors which measure temperature, humidity, atmospheric pressure, CO2, acoustics, vibrations and the weight of a hive in hostile environment. This work also uses random forest regression to evaluate the feature importance of different sensors, environmental variables such as temperature, humidity, rain, wind speed as well as the information related to seasons, towards estimating the daily hive weight change, on a dataset comprised of 1,250 days of sensor recordings. We also evaluate the protocol designed for communication using Narrow Band Internet of Things (NB-IoT). The issues related to power optimization, sleep intervals and data storage in remote monitoring are also discussed.