Three years of biochar amendment alters soil physiochemical properties and fungal community composition in a black soil of northeast China
TL;DR: In this paper, the authors investigated the long-term effects of biochar as a soil amendment in a black soil of northeast China over the long term and found that the changes in these soil characteristics were highly correlated with the amounts of Biochar addition, suggesting that the impacts of longterm biochar amendment on the soil fungal community occurred indirectly as a result of the alteration of soil physiochemical properties.
Abstract: Although biochar amendment has been extensively evaluated as a promising strategy to improve soil quality, most evaluations have been conducted in the laboratory or under short-term field conditions, which restricted us to understand the long-term effects of biochar as a soil amendment. As the residence time of biochar in soils is expected to be hundreds to thousands of years, this study focused on revealing whether biochar addition influences soil physiochemical properties and fungal community composition in a black soil of northeast China over the long term. Biochar was added to the micro-plots at 0%, 2%, 4%, and 8% of the total mass of the top 20 cm of the soil in the spring of 2012, and soil samples were collected seasonally four times in 2014. The results indicate that soil pH, moisture, total C, total N, total P, NO 3 − -N, available K and the C/N ratio significantly increased but soil bulk density and total K content decreased with biochar addition. The soil fungal abundance determined using quantitative real-time PCR showed that the number of fungal ITS gene copies increased with biochar addition. The soil fungal community composition determined using the Illumina MiSeq sequencing method showed that community diversity was not influenced by biochar addition but the community composition was influenced. The impact of biochar on changes in community composition was not reflected at the phylum level, but at the genus and operational taxonomic units (OTU) levels. The relative abundance of Fusarium decreased, but Guehomyces increased with biochar addition over the first three sampling dates. The relative abundances of several OTUs classified as potential crop pathogens decreased with biochar addition, suggesting that biochar amendment may be beneficial in terms of suppressing the occurrence of crop disease over the long term. In addition, canonical correspondence analysis indicated that fungal community composition was associated with soil parameters such as pH, soil moisture, total C, total N, total K and available K. The changes in these soil characteristics were highly correlated with the amounts of biochar addition, suggesting that the impacts of long-term biochar amendment on the soil fungal community occurred indirectly as a result of the alteration of soil physiochemical properties.
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TL;DR: FastTree as mentioned in this paper uses sequence profiles of internal nodes in the tree to implement neighbor-joining and uses heuristics to quickly identify candidate joins, then uses nearest-neighbor interchanges to reduce the length of the tree.
Abstract: Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.
2,436 citations
01 Jan 2015
TL;DR: In this paper, the authors meta-analyzed the biochar decomposition in soil and estimated its mean residence time (MRT), and concluded that only a small part of biochar is bioavailable and that the remaining 97% contribute directly to long-term carbon sequestration in soil.
Abstract: The stability and decomposition of biochar are fundamental to understand its persistence in soil, its contribution to carbon (C) sequestration, and thus its role in the global C cycle. Our current knowledge about the degradability of biochar, however, is limited. Using 128 observations of biochar‐derived CO2 from 24 studies with stable (13C) and radioactive (14C) carbon isotopes, we meta‐analyzed the biochar decomposition in soil and estimated its mean residence time (MRT). The decomposed amount of biochar increased logarithmically with experimental duration, and the decomposition rate decreased with time. The biochar decomposition rate varied significantly with experimental duration, feedstock, pyrolysis temperature, and soil clay content. The MRTs of labile and recalcitrant biochar C pools were estimated to be about 108 days and 556 years with pool sizes of 3% and 97%, respectively. These results show that only a small part of biochar is bioavailable and that the remaining 97% contribute directly to long‐term C sequestration in soil. The second database (116 observations from 21 studies) was used to evaluate the priming effects after biochar addition. Biochar slightly retarded the mineralization of soil organic matter (SOM; overall mean: −3.8%, 95% CI = −8.1–0.8%) compared to the soil without biochar addition. Significant negative priming was common for studies with a duration shorter than half a year (−8.6%), crop‐derived biochar (−20.3%), fast pyrolysis (−18.9%), the lowest pyrolysis temperature (−18.5%), and small application amounts (−11.9%). In contrast, biochar addition to sandy soils strongly stimulated SOM mineralization by 20.8%. This indicates that biochar stimulates microbial activities especially in soils with low fertility. Furthermore, abiotic and biotic processes, as well as the characteristics of biochar and soils, affecting biochar decomposition are discussed. We conclude that biochar can persist in soils on a centennial scale and that it has a positive effect on SOM dynamics and thus on C sequestration.
418 citations
TL;DR: In this article, humic acids were added to change the SOM content in black soil, and the results indicated that increased SOM led to increases in the soil available P and the P activation coefficient.
Abstract: Phosphorus (P) adsorption–desorption in soil is an important internal cycle related to soil fertility problems, as well as for determining the environmental fate of P. Soil organic matter (SOM) has been identified as an important factor affecting the adsorption–desorption of soil P through different mechanisms. In this study, humic acids were added to change the SOM content in black soil. Following an incubation period of 30 days, the changes in soil P adsorption–desorption capacity were studied. The results indicated that increased SOM led to increases in the soil available P and the P activation coefficient. All soil treatments fitted well with both Langmuir and Freundlich equations. The P adsorption and desorption characteristics were analyzed using the Langmuir equation as a local isotherm. The maximum adsorption capacity of P increased with the increase in SOM, but the P bonding energy and maximum buffering capacity first decreased, and then increased, with the lowest values obtained with a SOM content of 75.3 mg kg−1. Both the maximum desorption capacity of P and the ratio of soil P desorption showed a fluctuating trend, which were the greatest when the SOM content reached 75.3 g kg−1 in black soil, showing an improved ability to release P. Thus, the addition of organic matter could efficiently enhance P availability by reducing the strength of P adsorption and the maximum phosphate buffering capacity and increasing the desorption of P to some extent, with the greatest P availability obtained at a SOM content of 75.3 g kg−1.
168 citations
28 Sep 2020
TL;DR: In this paper, the fertilizer value of biochar, and its effects on soil properties, and nutrient use efficiency of crops, are discussed, where the authors show that biochar improves the nutrient retention capacity of soil, which depends on porosity and surface charge.
Abstract: Biochar, an environmentally friendly soil conditioner, is produced using several thermochemical processes. It has unique characteristics like high surface area, porosity, and surface charges. This paper reviews the fertilizer value of biochar, and its effects on soil properties, and nutrient use efficiency of crops. Biochar serves as an important source of plant nutrients, especially nitrogen in biochar produced from manures and wastes at low temperature (≤ 400 °C). The phosphorus, potassium, and other nutrient contents are higher in manure/waste biochars than those in crop residues and woody biochars. The nutrient contents and pH of biochar are positively correlated with pyrolysis temperature, except for nitrogen content. Biochar improves the nutrient retention capacity of soil, which depends on porosity and surface charge of biochar. Biochar increases nitrogen retention in soil by reducing leaching and gaseous loss, and also increases phosphorus availability by decreasing the leaching process in soil. However, for potassium and other nutrients, biochar shows inconsistent (positive and negative) impacts on soil. After addition of biochar, porosity, aggregate stability, and amount of water held in soil increase and bulk density decreases. Mostly, biochar increases soil pH and, thus, influences nutrient availability for plants. Biochar also alters soil biological properties by increasing microbial populations, enzyme activity, soil respiration, and microbial biomass. Finally, nutrient use efficiency and nutrient uptake improve with the application of biochar to soil. Thus, biochar can be a potential nutrient reservoir for plants and a good amendment to improve soil properties.
162 citations
TL;DR: This study investigated the temporal-spatial patterns of the soil erosion based on a modified version of Universal Soil Loss Equation (USLE) and conducted a soil erosion contribution analysis, demonstrating that land use changes had more significant impacts than soil property changes on soil erosion.
132 citations
Cites background from "Three years of biochar amendment al..."
...At the same time, the loss of soil organic matter had exerted an adverse influence on the agricultural development in this area (Yao et al., 2017)....
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References
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TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Abstract: Copyright (©) 1999–2012 R Foundation for Statistical Computing. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by the R Core Team.
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13,139 citations
TL;DR: UCHIME has better sensitivity than ChimeraSlayer (previously the most sensitive database method), especially with short, noisy sequences, and in testing on artificial bacterial communities with known composition, UCHIME de novo sensitivity is shown to be comparable to Perseus.
Abstract: Motivation: Chimeric DNA sequences often form during polymerase chain reaction amplification, especially when sequencing single regions (e.g. 16S rRNA or fungal Internal Transcribed Spacer) to assess diversity or compare populations. Undetected chimeras may be misinterpreted as novel species, causing inflated estimates of diversity and spurious inferences of differences between populations. Detection and removal of chimeras is therefore of critical importance in such experiments.
Results: We describe UCHIME, a new program that detects chimeric sequences with two or more segments. UCHIME either uses a database of chimera-free sequences or detects chimeras de novo by exploiting abundance data. UCHIME has better sensitivity than ChimeraSlayer (previously the most sensitive database method), especially with short, noisy sequences. In testing on artificial bacterial communities with known composition, UCHIME de novo sensitivity is shown to be comparable to Perseus. UCHIME is >100× faster than Perseus and >1000× faster than ChimeraSlayer.
Contact: [email protected]
Availability: Source, binaries and data: http://drive5.com/uchime.
Supplementary information:Supplementary data are available at Bioinformatics online.
11,904 citations
TL;DR: Cd-hit-2d compares two protein datasets and reports similar matches between them; cd- Hit-est clusters a DNA/RNA sequence database and cd- hit-est-2D compares two nucleotide datasets.
Abstract: Motivation: In 2001 and 2002, we published two papers (Bioinformatics, 17, 282--283, Bioinformatics, 18, 77--82) describing an ultrafast protein sequence clustering program called cd-hit. This program can efficiently cluster a huge protein database with millions of sequences. However, the applications of the underlying algorithm are not limited to only protein sequences clustering, here we present several new programs using the same algorithm including cd-hit-2d, cd-hit-est and cd-hit-est-2d. Cd-hit-2d compares two protein datasets and reports similar matches between them; cd-hit-est clusters a DNA/RNA sequence database and cd-hit-est-2d compares two nucleotide datasets. All these programs can handle huge datasets with millions of sequences and can be hundreds of times faster than methods based on the popular sequence comparison and database search tools, such as BLAST.
Availability: http://cd-hit.org
Contact: [email protected]
8,306 citations