ResearchPad - soil-chemistry https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Selected wetland soil properties correlate to Rift Valley fever livestock mortalities reported in 2009-10 in central South Africa]]> https://www.researchpad.co/article/elastic_article_15754 Outbreaks of Rift Valley fever have devastating impacts on ruminants, humans, as well as on regional and national economies. Although numerous studies on the impact and outbreak of Rift Valley fever exist, relatively little is known about the role of environmental factors, especially soil, on the aestivation of the virus. This study thus selected 22 sites for study in central South Africa, known to be the recurrent epicenter of widespread Rift Valley fever outbreaks in Southern Africa. Soils were described, sampled and analyzed in detail at each site. Of all the soil variables analyzed for, only eight (cation exchange capacity, exchangeable Ca2+, exchangeable K+, exchangeable Mg2+, soluble Ca2+, medium sand, As, and Br) were statistically identified to be potential indicators of sites with reported Rift Valley fever mortalities, as reported for the 2009–2010 Rift Valley fever outbreak. Four soil characteristics (exchangeable K+, exchangeable Mg2+, medium sand, and Br) were subsequently included in a discriminant function that could potentially be used to predict sites that had reported Rift Valley fever-associated mortalities in livestock. This study therefore constitutes an initial attempt to predict sites prone to Rift Valley fever livestock mortality from soil properties and thus serves as a basis for broader research on the interaction between soil, mosquitoes and Rift Valley fever virus. Future research should include other environmental components such as vegetation, climate, and water properties as well as correlating soil properties with floodwater Aedes spp. abundance and Rift Valley fever virus prevalence.

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<![CDATA[Analysis on hydraulic characteristics of improved sandy soil with soft rock]]> https://www.researchpad.co/article/N42f3b4c1-ffad-4b27-9297-98b538f1063a

Hydraulic properties of sandy soil from the Mu Us sandy land of Shaanxi Province were analyzed by using SEM technology. Soil porosity, the water characteristic curve, and unsaturated hydraulic conductivity of aeolian sandy soil with added soft rock were analyzed, and fractal characteristics were established. Soil hydraulic properties revealed the effect of soft rock application on soil structure and hydraulic properties. Mass ratios of soft rock to aeolian sand were 1:5, 1:2, and 1:1. Results showed that the addition of soft rock can significantly increase the bulk density of sandy soil and reduce the total porosity and macroporosity. The mass fraction of water-stable aggregates greater than 0.25mm increases significantly, increasing the fractal dimension of soil pores; reducing the soil saturated water content and saturated hydraulic conductivity. SEM technology and pore fractal theory were used to predict the soil salinity curve and unsaturated hydraulic conductivity of the improved saline soil.

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<![CDATA[Building geochemically based quantitative analogies from soil classification systems using different compositional datasets]]> https://www.researchpad.co/article/5c75abe2d5eed0c484d07e1f

Soil heterogeneity is a major contributor to the uncertainty in near-surface biogeochemical modeling. We sought to overcome this limitation by exploring the development of a new classification analogy concept for transcribing the largely qualitative criteria in the pedomorphologically based, soil taxonomic classification systems to quantitative physicochemical descriptions. We collected soil horizons classified under the Alfisols taxonomic Order in the U.S. National Resource Conservation Service (NRCS) soil classification system and quantified their properties via physical and chemical characterizations. Using multivariate statistical modeling modified for compositional data analysis (CoDA), we developed quantitative analogies by partitioning the characterization data up into three different compositions: Water-extracted (WE), Mehlich-III extracted (ME), and particle-size distribution (PSD) compositions. Afterwards, statistical tests were performed to determine the level of discrimination at different taxonomic and location-specific designations. The analogies showed different abilities to discriminate among the samples. Overall, analogies made up from the WE composition more accurately classified the samples than the other compositions, particularly at the Great Group and thermal regime designations. This work points to the potential to quantitatively discriminate taxonomically different soil types characterized by varying compositional datasets.

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<![CDATA[Responses of soil respiration to nitrogen addition in the Sanjiang Plain wetland, northeastern China]]> https://www.researchpad.co/article/5c5ca2b4d5eed0c48441e90e

This study was designed to test the hypothesis that nitrogen (N) addition leads to enhanced soil respiration (SR) in nitrogen deficient marsh. Here, we report the response of SR to simulated N deposition in a temperate marsh of northeastern China from June 2009 to September 2011. The experiment included three-levels of N treatment (control: no N addition, Low-N: 4g N m-2 y-1, and High-N: 8 g N m-2 y-1). Our study showed various responses of SR to level and duration of N addition. Yearly SR was increased by 11.8%-15.2% (P<0.05) under Low-N addition during the three years, while SR showed a strong increase by 27.5% (P<0.05) in the first year and then decreased by 4.4% (P>0.05) and 15.4% (P<0.05) in the next two years under High-N addition. Soil respiration was positively correlated with soil temperature and negatively correlated with soil water content. High-N treatment reduced soil pH value (P<0.05). The negative response of SR to High-N addition in the following two years may attribute to lower microbial activity, microbial biomass and alteration in the microbial community due to lower soil pH, which consequently leads to decreased SR. Meanwhile, we found root biomass were increased under High-N addition. This implies that the increase of autotrophic respiration was lower than the decline of heterotrophic respiration in the following two years. Our findings suggest complex interactions between N deposition and SR, which is needed to be further investigated in the future studies.

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<![CDATA[Effects of long-term fertilization on soil organic carbon mineralization and microbial community structure]]> https://www.researchpad.co/article/5c57e66bd5eed0c484ef30c6

Soil microorganisms play a pivotal role in carbon mineralization and their diversity is crucial to the function of soil ecosystems. However, the effects of long-term fertilization on microbial-mediated carbon mineralization are poorly understood. To identify the relative roles of microbes in carbon mineralization of yellow paddies, we investigated the long-term fertilization effects on soil properties and microbial communities and their relationships with carbon mineralization. The treatments included: no fertilization (CK), chemical fertilizer (NPK), organic fertilizer (M), and constant organic-inorganic fertilizer (MNPK). NPK treatment significantly increased soil water content (WC), while M and MNPK treatments significantly increased the content of soil organic carbon (SOC), total nitrogen (TN), soil microbial biomass carbon (SMBC), soil microbial biomass nitrogen (SMBN), and WC. Strong increases in CO2 emissions, potential mineralized carbon, and turnover rate constant were observed in both organic-fertilizer treatments (M and MNPK), relative to the CK treatment. These changes in soil properties can be attributed to the variation in microbial communities. NPK treatment had no significant effect. Different fertilization treatments changed soil microbial community; SOC and SMBN were the most important contributors to the variance in microbial community composition. The variations in community composition did not significant influence carbon mineralization; however, carbon mineralization was significantly influenced by the abundance of several non-dominant bacteria. The results suggest that SOC, SMBN, and non-dominant bacteria (Gemmatimonadetes and Latescibacteria), have a close relationship to carbon mineralization, and should be preferentially considered in predicting carbon mineralization under long-term fertilization.

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<![CDATA[Generalizing soil properties in geographic space: Approaches used and ways forward]]> https://www.researchpad.co/article/5c269731d5eed0c48470ee42

Soil is one of the most complex systems on Earth, functioning at the interface between the lithosphere, biosphere, hydrosphere, and atmosphere and generating a multitude of functions. Moreover, soil constitutes the belowground environment from which plants capture water and nutrients. Despite their great importance, soil properties are often not sufficiently considered in other disciplines, especially in spatial studies of plant distributions. Most soil properties are available as point data and, to be used in spatial analyses, need to be generalised over entire regions (i.e. digital soil mapping). Three categories of statistical approaches can be used for such purpose: geostatistical approaches (GSA), predictive-statistical approaches (PSA), and hybrid approaches (HA) that combine the two previous ones. How then to choose the best approach in a given soil study context? Does it depend on the soil properties to be spatialized, the study area’s characteristics, and/or the availability of soil data? The main aims of this study was to review the use of these three approaches to derive maps of soil properties in relation to the soil parameters, the study area characteristics, and the number of soil samples. We evidenced that the approaches that tend to show the best performance for spatializing soil properties were not necessarily the ones most used in practice. Although PSA was the most widely used, it tended to be outperformed by HA in many cases, but the latter was far less used. However, as the study settings were not always properly described and not all situations were represented in the set of papers analysed, more comparative studies would be needed across a wider range of regions, soil properties, and spatial scales to provide robust conclusions on the best spatialization methods in a specific context.

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<![CDATA[Toxicity of phthalate esters to lettuce (Lactuca sativa) and the soil microbial community under different soil conditions]]> https://www.researchpad.co/article/5c254552d5eed0c48442c4fb

Phthalate esters (PAEs) are globally used plasticizers and typical endocrine disruptors that can readily accumulate in agricultural products and represent a substantial risk to human health via the food chain. The range of soil properties has an important influence on the expression of PAE toxicity, and the mechanisms by which soil physical and chemical properties affect the expression of toxicity of target PAEs to plants and microorganisms requires further investigation. Important soil factors affecting the eco-toxicological effects of two typical PAEs, di-n-butyl phthalate (DnBP) and bis (2-ethylhexyl) phthalate (DEHP), on lettuce (Lactuca sativa) in a spiked soil were investigated in the present study. Soil at various pH values was spiked with three PAE concentrations (1, 5 and 20 mg DnBP or DEHP kg-1 soil), organic matter contents and water holding contents to simulate the greenhouse soil environment for 30 days. Their influence on the biomass, photosynthetic pigment contents, various physiological changes and soil microbial communities was determined as endpoints. The toxicity to lettuce of DnBP was higher than that of DEHP in the soil and soil pH was the most important factor affecting their single toxicity, followed by soil organic matter content and soil moisture content in agreement with the Biolog test results. Under different soil conditions total protein, total soluble sugar and free amino acid contents were positively correlated with concentrations of the target PAEs, but leaf area, biomass, •O2- activity, vitamin C content and soil microbial diversity indices showed the opposite trend. Chlorophyll a and carotenoid contents were more inhibited by DnBP together with impacts on indices of soil microbial diversity. The results suggest that soil conditions in greenhouses directly explain the patterns of pollutant toxicity displayed and impact the quantity, quality and food safety of vegetables produced using highly intensive production systems.

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<![CDATA[Soil features in rookeries of Antarctic penguins reveal sea to land biotransport of chemical pollutants]]> https://www.researchpad.co/article/5aafcd32463d7e7f05234543

The main soil physical-chemical features, the concentrations of a set of pollutants, and the soil microbiota linked to penguin rookeries have been studied in 10 selected sites located at the South Shetland Islands and the Antarctic Peninsula (Maritime Antarctica). This study aims to test the hypothesis that biotransport by penguins increases the concentration of pollutants, especially heavy metals, in Antarctic soils, and alters its microbiota. Our results show that penguins do transport certain chemical elements and thus cause accumulation in land areas through their excreta. Overall, a higher penguin activity is associated with higher organic carbon content and with higher concentrations of certain pollutants in soils, especially cadmium, cooper and arsenic, as well as zinc and selenium. In contrast, in soils that are less affected by penguins’ faecal depositions, the concentrations of elements of geochemical origin, such as iron and cobalt, increase their relative weighted contribution, whereas the above-mentioned pollutants maintain very low levels. The concentrations of pollutants are far higher in those penguin rookeries that are more exposed to ship traffic. In addition, the soil microbiota of penguin-influenced soils was studied by molecular methods. Heavily penguin-affected soils have a massive presence of enteric bacteria, whose relative dominance can be taken as an indicator of penguin influence. Faecal bacteria are present in addition to typical soil taxa, the former becoming dominant in the microbiota of penguin-affected soils, whereas typical soil bacteria, such as Actinomycetales, co-dominate the microbiota of less affected soils. Results indicate that the continuous supply by penguin faeces, and not the selectivity by increased pollutant concentrations is the main factor shaping the soil bacterial community. Overall, massive penguin influence results in increased concentrations of certain pollutants and in a strong change in taxa dominance in the soil bacterial community.

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<![CDATA[Soil Quality Indexing Strategies for Evaluating Sugarcane Expansion in Brazil]]> https://www.researchpad.co/article/5989dacdab0ee8fa60bb50bc

Increasing demand for biofuel has intensified land-use change (LUC) for sugarcane (Saccharum officinarum) expansion in Brazil. Assessments of soil quality (SQ) response to this LUC are essential for quantifying and monitoring sustainability of sugarcane production over time. Since there is not a universal methodology for assessing SQ, we conducted a field-study at three sites within the largest sugarcane-producing region of Brazil to develop a SQ index (SQI). The most common LUC scenario (i.e., native vegetation to pasture to sugarcane) was evaluated using six SQI strategies with varying complexities. Thirty eight soil indicators were included in the total dataset. Two minimum datasets were selected: one using principal component analysis (7 indicators) and the other based on expert opinion (5 indicators). Non-linear scoring curves were used to interpret the indicator values. Weighted and non-weighted additive methods were used to combine individual indicator scores into an overall SQI. Long-term conversion from native vegetation to extensive pasture significantly decreased overall SQ. In contrast, conversion from pasture to sugarcane had no significant impact on overall SQ at the regional scale, but site-specific responses were found. In general, sugarcane production improved chemical attributes (i.e., higher macronutrient levels and lower soil acidity); however it has negative effects on physical and biological attributes (i.e., higher soil compaction and structural degradation as well as lower soil organic carbon (SOC), abundance and diversity of macrofauna and microbial activity). Overall, we found that simple, user-friendly strategies were as effective as more complex ones for identifying SQ changes. Therefore, as a protocol for SQ assessments in Brazilian sugarcane areas, we recommend using a small number of indicators (e.g., pH, P, K, Visual Evaluation of Soil Structure -VESS scores and SOC concentration) and proportional weighting to reflect chemical, physical and biological processes within the soil. Our SQ evaluations also suggest that current approaches for expanding Brazilian sugarcane production by converting degraded pasture land to cropland can be a sustainable strategy for meeting increasing biofuel demand. However, management practices that alleviate negative impacts on soil physical and biological indicators must be prioritized within sugarcane producing areas to prevent unintentional SQ degradation over time.

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<![CDATA[Evaluating the Applicability of Phi Coefficient in Indicating Habitat Preferences of Forest Soil Fauna Based on a Single Field Study in Subtropical China]]> https://www.researchpad.co/article/5989db2bab0ee8fa60bd15db

Phi coefficient directly depends on the frequencies of occurrence of organisms and has been widely used in vegetation ecology to analyse the associations of organisms with site groups, providing a characterization of ecological preference, but its application in soil ecology remains rare. Based on a single field experiment, this study assessed the applicability of phi coefficient in indicating the habitat preferences of soil fauna, through comparing phi coefficient-induced results with those of ordination methods in charactering soil fauna-habitat(factors) relationships. Eight different habitats of soil fauna were implemented by reciprocal transfer of defaunated soil cores between two types of subtropical forests. Canonical correlation analysis (CCorA) showed that ecological patterns of fauna-habitat relationships and inter-fauna taxa relationships expressed, respectively, by phi coefficients and predicted abundances calculated from partial redundancy analysis (RDA), were extremely similar, and a highly significant relationship between the two datasets was observed (Pillai's trace statistic = 1.998, P = 0.007). In addition, highly positive correlations between phi coefficients and predicted abundances for Acari, Collembola, Nematode and Hemiptera were observed using linear regression analysis. Quantitative relationships between habitat preferences and soil chemical variables were also obtained by linear regression, which were analogous to the results displayed in a partial RDA biplot. Our results suggest that phi coefficient could be applicable on a local scale in evaluating habitat preferences of soil fauna at coarse taxonomic levels, and that the phi coefficient-induced information, such as ecological preferences and the associated quantitative relationships with habitat factors, will be largely complementary to the results of ordination methods. The application of phi coefficient in soil ecology may extend our knowledge about habitat preferences and distribution-abundance relationships, which will benefit the understanding of biodistributions and variations in community compositions in the soil. Similar studies in other places and scales apart from our local site will be need for further evaluation of phi coefficient.

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<![CDATA[Decay and nutrient dynamics of coarse woody debris in the Qinling Mountains, China]]> https://www.researchpad.co/article/5989db51ab0ee8fa60bdc4d1

As an ecological unit, coarse woody debris (CWD) plays an essential role in productivity, nutrient cycling, carbon sequestration, community regeneration and biodiversity. However, thus far, the information on quantification the decomposition and nutrient content of CWD in forest ecosystems remains considerably limited. In this study, we conducted a long-term (1996–2013) study on decay and nutrient dynamics of CWD for evaluating accurately the ecological value of CWD on the Huoditang Experimental Forest Farm in the Qinling Mountains, China. The results demonstrated that there was a strong correlation between forest biomass and CWD mass. The single exponential decay model well fit the CWD density loss at this site, and as the CWD decomposed, the CWD density decreased significantly. Annual temperature and precipitation were all significantly correlated with the annual mass decay rate. The K contents and the C/N ratio of the CWD decreased as the CWD decayed, but the C, N, P, Ca and Mg contents increased. We observed a significant CWD decay effect on the soil C, N and Mg contents, especially the soil C content. The soil N, P, K, Ca and Mg contents exhibited large fluctuations, but the variation had no obvious regularity and changed with different decay times. The results showed that CWD was a critical component of nutrient cycling in forest ecosystems. Further research is needed to determine the effect of diameter, plant tissue components, secondary wood compounds, and decomposer organisms on the CWD decay rates in the Qinling Mountains, which will be beneficial to clarifying the role of CWD in carbon cycles of forest ecosystems.

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<![CDATA[Changes in soil bacterial community structure as a result of incorporation of Brassica plants compared with continuous planting eggplant and chemical disinfection in greenhouses]]> https://www.researchpad.co/article/5989db53ab0ee8fa60bdca3d

Greenhouse eggplant monocropping in China has contributed to the aggravation of soil-borne diseases, reductions in crop quality and yield, and the degradation of physical and chemical soil properties. Crop rotation is one effective way of alleviating the problems of continuous cropping worldwide; however, few studies have reported changes in soil bacterial community structures and physical and chemical soil properties after Brassica vegetables had been rotated with eggplant in greenhouses. In this experiment, mustard-eggplant (BFN) and oilseed rape-eggplant (BFC) rotations were studied to identify changes in the physicochemical properties and bacterial community structure in soil that was previously subject to monocropping. Samples were taken after two types of Brassica plants incorporated into soil for 15 days to compare with continually planted eggplant (control, CN) and chemical disinfection of soil (CF) in greenhouses. MiSeq pyrosequencing was used to analyze soil bacterial diversity and structure in the four different treatments. A total of 55,129 reads were identified, and rarefaction analysis showed that the soil treatments were equally sampled. The bacterial richness of the BFC treatment and the diversity of the BFN treatment were significantly higher than those of the other treatments. Further comparison showed that the bacterial community structures of BFC and BFN treatments were also different from CN and CF treatments. The relative abundance of several dominant bacterial genera in the BFC and BFN treatments (such as Flavobacteria, Stenotrophomonas, Massilia and Cellvibrio, which played different roles in improving soil fertility and advancing plant growth) was distinctly higher than the CN or CF treatments. Additionally, the total organic matter and Olsen-P content of the BFC and BFN treatments were significantly greater than the CN treatment. We conclude that Brassica vegetables-eggplant crop rotations could provide a more effective means of solving the problems of greenhouse eggplant monocultures.

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<![CDATA[Combining Forces - The Use of Landsat TM Satellite Imagery, Soil Parameter Information, and Multiplex PCR to Detect Coccidioides immitis Growth Sites in Kern County, California]]> https://www.researchpad.co/article/5989daa6ab0ee8fa60ba7a16

Coccidioidomycosis is a fungal disease acquired through the inhalation of spores of Coccidioides spp., which afflicts primarily humans and other mammals. It is endemic to areas in the southwestern United States, including the San Joaquin Valley portion of Kern County, California, our region of interest (ROI). Recently, incidence of coccidioidomycosis, also known as valley fever, has increased significantly, and several factors including climate change have been suggested as possible drivers for this observation. Up to date details about the ecological niche of C. immitis have escaped full characterization. In our project, we chose a three-step approach to investigate this niche: 1) We examined Landsat-5-Thematic-Mapper multispectral images of our ROI by using training pixels at a 750 m×750 m section of Sharktooth Hill, a site confirmed to be a C. immitis growth site, to implement a Maximum Likelihood Classification scheme to map out the locations that could be suitable to support the growth of the pathogen; 2) We used the websoilsurvey database of the US Department of Agriculture to obtain soil parameter data; and 3) We investigated soil samples from 23 sites around Bakersfield, California using a multiplex Polymerase Chain Reaction (PCR) based method to detect the pathogen. Our results indicated that a combination of satellite imagery, soil type information, and multiplex PCR are powerful tools to predict and identify growth sites of C. immitis. This approach can be used as a basis for systematic sampling and investigation of soils to detect Coccidioides spp.

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<![CDATA[The Effects of Warming and Nitrogen Addition on Soil Nitrogen Cycling in a Temperate Grassland, Northeastern China]]> https://www.researchpad.co/article/5989da03ab0ee8fa60b74c93

Background

Both climate warming and atmospheric nitrogen (N) deposition are predicted to affect soil N cycling in terrestrial biomes over the next century. However, the interactive effects of warming and N deposition on soil N mineralization in temperate grasslands are poorly understood.

Methodology/Principal Findings

A field manipulation experiment was conducted to examine the effects of warming and N addition on soil N cycling in a temperate grassland of northeastern China from 2007 to 2009. Soil samples were incubated at a constant temperature and moisture, from samples collected in the field. The results showed that both warming and N addition significantly stimulated soil net N mineralization rate and net nitrification rate. Combined warming and N addition caused an interactive effect on N mineralization, which could be explained by the relative shift of soil microbial community structure because of fungal biomass increase and strong plant uptake of added N due to warming. Irrespective of strong intra- and inter-annual variations in soil N mineralization, the responses of N mineralization to warming and N addition did not change during the three growing seasons, suggesting independence of warming and N responses of N mineralization from precipitation variations in the temperate grassland.

Conclusions/Significance

Interactions between climate warming and N deposition on soil N cycling were significant. These findings will improve our understanding on the response of soil N cycling to the simultaneous climate change drivers in temperate grassland ecosystem.

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<![CDATA[Properties of biochar derived from wood and high-nutrient biomasses with the aim of agronomic and environmental benefits]]> https://www.researchpad.co/article/5989db5aab0ee8fa60bdf6f9

Biochar production and use are part of the modern agenda to recycle wastes, and to retain nutrients, pollutants, and heavy metals in the soil and to offset some greenhouse gas emissions. Biochars from wood (eucalyptus sawdust, pine bark), sugarcane bagasse, and substances rich in nutrients (coffee husk, chicken manure) produced at 350, 450 and 750°C were characterized to identify agronomic and environmental benefits, which may enhance soil quality. Biochars derived from wood and sugarcane have greater potential for improving C storage in tropical soils due to a higher aromatic character, high C concentration, low H/C ratio, and FTIR spectra features as compared to nutrient-rich biochars. The high ash content associated with alkaline chemical species such as KHCO3 and CaCO3, verified by XRD analysis, made chicken manure and coffee husk biochars potential liming agents for remediating acidic soils. High Ca and K contents in chicken manure and coffee husk biomass can significantly replace conventional sources of K (mostly imported in Brazil) and Ca, suggesting a high agronomic value for these biochars. High-ash biochars, such as chicken manure and coffee husk, produced at low-temperatures (350 and 450°C) exhibited high CEC values, which can be considered as a potential applicable material to increase nutrient retention in soil. Therefore, the agronomic value of the biochars in this study is predominantly regulated by the nutrient richness of the biomass, but an increase in pyrolysis temperature to 750°C can strongly decrease the adsorptive capacities of chicken manure and coffee husk biochars. A diagram of the agronomic potential and environmental benefits is presented, along with some guidelines to relate biochar properties with potential agronomic and environmental uses. Based on biochar properties, research needs are identified and directions for future trials are delineated.

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<![CDATA[Soil Does Not Explain Monodominance in a Central African Tropical Forest]]> https://www.researchpad.co/article/5989da1cab0ee8fa60b7d606

Background

Soil characteristics have been hypothesised as one of the possible mechanisms leading to monodominance of Gilbertiodendron dewerei in some areas of Central Africa where higher-diversity forest would be expected. However, the differences in soil characteristics between the G. dewevrei-dominated forest and its adjacent mixed forest are still poorly understood. Here we present the soil characteristics of the G. dewevrei forest and quantify whether soil physical and chemical properties in this monodominant forest are significantly different from the adjacent mixed forest.

Methodology/Principal Findings

We sampled top soil (0–5, 5–10, 10–20, 20–30 cm) and subsoil (150–200 cm) using an augur in 6 × 1 ha areas of intact central Africa forest in SE Cameroon, three independent patches of G. dewevrei-dominated forest and three adjacent areas (450–800 m apart), all chosen to be topographically homogeneous. Analysis – subjected to Bonferroni correction procedure – revealed no significant differences between the monodominant and mixed forests in terms of soil texture, median particle size, bulk density, pH, carbon (C) content, nitrogen (N) content, C:N ratio, C:total NaOH-extractable P ratio and concentrations of labile phosphorous (P), inorganic NaOH-extractable P, total NaOH-extractable P, aluminium, barium, calcium, copper, iron, magnesium, manganese, molybdenum, nickel, potassium, selenium, silicon, sodium and zinc. Prior to Bonferroni correction procedure, there was a significant lower level of silicon concentration found in the monodominant than mixed forest deep soil; and a significant lower level of nickel concentration in the monodominant than mixed forest top soil. Nevertheless, these were likely to be the results of multiple tests of significance.

Conclusions/Significance

Our results do not provide clear evidence of soil mediation for the location of monodominant forests in relation to adjacent mixed forests. It is also likely that G. dewevrei does not influence soil chemistry in the monodominant forests.

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<![CDATA[Biodiversity of Mineral Nutrient and Trace Element Accumulation in Arabidopsis thaliana]]> https://www.researchpad.co/article/5989da7dab0ee8fa60b99273

In order to grow on soils that vary widely in chemical composition, plants have evolved mechanisms for regulating the elemental composition of their tissues to balance the mineral nutrient and trace element bioavailability in the soil with the requirements of the plant for growth and development. The biodiversity that exists within a species can be utilized to investigate how regulatory mechanisms of individual elements interact and to identify genes important for these processes. We analyzed the elemental composition (ionome) of a set of 96 wild accessions of the genetic model plant Arabidopsis thaliana grown in hydroponic culture and soil using inductively coupled plasma mass spectrometry (ICP-MS). The concentrations of 17–19 elements were analyzed in roots and leaves from plants grown hydroponically, and leaves and seeds from plants grown in artificial soil. Significant genetic effects were detected for almost every element analyzed. We observed very few correlations between the elemental composition of the leaves and either the roots or seeds. There were many pairs of elements that were significantly correlated with each other within a tissue, but almost none of these pairs were consistently correlated across tissues and growth conditions, a phenomenon observed in several previous studies. These results suggest that the ionome of a plant tissue is variable, yet tightly controlled by genes and gene×environment interactions. The dataset provides a valuable resource for mapping studies to identify genes regulating elemental accumulation. All of the ionomic data is available at www.ionomicshub.org.

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<![CDATA[Comparing the Effect of Naturally Restored Forest and Grassland on Carbon Sequestration and Its Vertical Distribution in the Chinese Loess Plateau]]> https://www.researchpad.co/article/5989daadab0ee8fa60baa053

Vegetation restoration has been conducted in the Chinese Loess Plateau (CLP) since the 1950s, and large areas of farmland have been converted to forest and grassland, which largely results in SOC change. However, there has been little comparative research on SOC sequestration and distribution between secondary forest and restored grassland. Therefore, we selected typical secondary forest (SF-1 and SF-2) and restored grassland (RG-1 and RG-2) sites and determined the SOC storage. Moreover, to illustrate the factors resulting in possible variance in SOC sequestration, we measured the soil δ13C value. The average SOC content was 6.8, 9.9, 17.9 and 20.4 g kg−1 at sites SF-1, SF-2, RG-1 and RG-2, respectively. Compared with 0–100 cm depth, the percentage of SOC content in the top 20 cm was 55.1%, 55.3%, 23.1%, and 30.6% at sites SF-1, SF-2, RG-1 and RG-2, suggesting a higher SOC content in shallow layers in secondary forest and in deeper layers in restored grassland. The variation of soil δ13C values with depth in this study might be attributed to the mixing of new and old carbon and kinetic fractionation during the decomposition of SOM by microbes, whereas the impact of the Suess effect (the decline of 13C atmospheric CO2 values with the burning of fossil fuel since the Industrial Revolution) was minimal. The soil δ13C value increased sharply in the top 20 cm, which then increased slightly in deeper layers in secondary forest, indicating a main carbon source of surface litter. However the soil δ13C values exhibited slow increases in the whole profile in the restored grasslands, suggesting that the contribution of roots to soil carbon in deeper layers played an important role. We suggest that naturally restored grassland would be a more effective vegetation type for SOC sequestration due to higher carbon input from roots in the CLP.

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<![CDATA[Toward a Mechanistic Modeling of Nitrogen Limitation on Vegetation Dynamics]]> https://www.researchpad.co/article/5989dad1ab0ee8fa60bb659a

Nitrogen is a dominant regulator of vegetation dynamics, net primary production, and terrestrial carbon cycles; however, most ecosystem models use a rather simplistic relationship between leaf nitrogen content and photosynthetic capacity. Such an approach does not consider how patterns of nitrogen allocation may change with differences in light intensity, growing-season temperature and CO2 concentration. To account for this known variability in nitrogen-photosynthesis relationships, we develop a mechanistic nitrogen allocation model based on a trade-off of nitrogen allocated between growth and storage, and an optimization of nitrogen allocated among light capture, electron transport, carboxylation, and respiration. The developed model is able to predict the acclimation of photosynthetic capacity to changes in CO2 concentration, temperature, and radiation when evaluated against published data of Vc,max (maximum carboxylation rate) and Jmax (maximum electron transport rate). A sensitivity analysis of the model for herbaceous plants, deciduous and evergreen trees implies that elevated CO2 concentrations lead to lower allocation of nitrogen to carboxylation but higher allocation to storage. Higher growing-season temperatures cause lower allocation of nitrogen to carboxylation, due to higher nitrogen requirements for light capture pigments and for storage. Lower levels of radiation have a much stronger effect on allocation of nitrogen to carboxylation for herbaceous plants than for trees, resulting from higher nitrogen requirements for light capture for herbaceous plants. As far as we know, this is the first model of complete nitrogen allocation that simultaneously considers nitrogen allocation to light capture, electron transport, carboxylation, respiration and storage, and the responses of each to altered environmental conditions. We expect this model could potentially improve our confidence in simulations of carbon-nitrogen interactions and the vegetation feedbacks to climate in Earth system models.

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<![CDATA[Biogeochemical Typing of Paddy Field by a Data-Driven Approach Revealing Sub-Systems within a Complex Environment - A Pipeline to Filtrate, Organize and Frame Massive Dataset from Multi-Omics Analyses]]> https://www.researchpad.co/article/5989da76ab0ee8fa60b968d5

We propose the technique of biogeochemical typing (BGC typing) as a novel methodology to set forth the sub-systems of organismal communities associated to the correlated chemical profiles working within a larger complex environment. Given the intricate characteristic of both organismal and chemical consortia inherent to the nature, many environmental studies employ the holistic approach of multi-omics analyses undermining as much information as possible. Due to the massive amount of data produced applying multi-omics analyses, the results are hard to visualize and to process. The BGC typing analysis is a pipeline built using integrative statistical analysis that can treat such huge datasets filtering, organizing and framing the information based on the strength of the various mutual trends of the organismal and chemical fluctuations occurring simultaneously in the environment. To test our technique of BGC typing, we choose a rich environment abounding in chemical nutrients and organismal diversity: the surficial freshwater from Japanese paddy fields and surrounding waters. To identify the community consortia profile we employed metagenomics as high throughput sequencing (HTS) for the fragments amplified from Archaea rRNA, universal 16S rRNA and 18S rRNA; to assess the elemental content we employed ionomics by inductively coupled plasma optical emission spectroscopy (ICP-OES); and for the organic chemical profile, metabolomics employing both Fourier transformed infrared (FT-IR) spectroscopy and proton nuclear magnetic resonance (1H-NMR) all these analyses comprised our multi-omics dataset. The similar trends between the community consortia against the chemical profiles were connected through correlation. The result was then filtered, organized and framed according to correlation strengths and peculiarities. The output gave us four BGC types displaying uniqueness in community and chemical distribution, diversity and richness. We conclude therefore that the BGC typing is a successful technique for elucidating the sub-systems of organismal communities with associated chemical profiles in complex ecosystems.

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