Pathways to improving carbon emission efficiency in provinces: A comparative qualitative analysis based on the technology-organization-environment framework.

Achieving carbon peaking and carbon neutrality are important issues for global climate governance. The study of carbon emission efficiency in China's provincial regions is of practical significance for the country to achieve carbon peaking and carbon neutrality goals. Based on the framework of Technology-Organization-Environment (TOE), choosing technological progress, economic development, industrial structure, energy structure, energy prices, and carbon emission trading market as condition variables, collecting the panel data from 30 provinces in China from 2010 to 2020, the mixed study of Necessary Condition Analysis (NCA) and the fuzzy set Qualitative Comparative Analysis (fsQCA) was used to explore the complex influence mechanism of carbon emission efficiency. The findings indicate: (1) none of the single conditions are necessary for the effect of carbon emission efficiency, but technology plays an important role in supporting the improvement of carbon emission efficiency. (2) There are four recipes for the improvement of carbon emission efficiency, which are summarized into four modes: Technology-Organization dual core modes, Environment core-Organization support modes, Technology-Organization-Environment linkage modes, and Organization core-Technology support modes. Among them, the recipe of Organization core-Technology support covers the largest number of provinces, indicating that for the developed provinces, it is necessary to accelerate technological innovation, make the deep integration of economic development and technological innovation, and promote the adjustment of the industrial structure, thereby improving the carbon emission efficiency (CEE). This study contributes to carbon emission efficiency literature by providing a new theoretical perspective based on the TOE analysis framework, and development strategies for provinces to optimize the combination according to their condition endowment.

Predicting the current and future distributions of Pennisetum alopecuroides (L.) in China under climate change based on the MaxEnt model.

Pennisetum alopecuroides (L.), one of the important exotic plants, gives great economic value to animal husbandry in China. In order to study the distribution of Pennisetum alopecuroides (L.) in China and its response to climate change, based on the distribution records of Pennisetum alopecuroides (L.), our study used the Maximum Entropy (MaxEnt) model and geographic information system (GIS) methods, combined with environmental factors such as climate and terrain, to predict the potential distribution areas suitable for Pennisetum alopecuroides (L.) under current and future climate scenarios. The results showed that annual precipitation was the most important factor affecting the distribution of Pennisetum alopecuroides (L.). In current climate scenario, the total area of suitable for Pennisetum alopecuroides (L.) growth was about 576.5 km2, accounting for about 60.5% of the total land area of China. Among all the suitable areas, the area of low, middle and high fitness areas accounted for 5.69%, 20.55% and 33.81% of the total area respectively. In future climate scenarios (RCP4.5), the suitable area of Pennisetum alopecuroides (L.) would decrease with climate change, showing a clear trend of northward expansion in China. A concentrated and contiguous distribution region for Pennisetum alopecuroides (L.) would appear in northeast China. The model was tested by the receiver operating characteristic curve (ROC), and the average area under the curve of ROC of the training set was 0.985, which was reliable. This work provided an important reference and theoretical basis for the efficient utilization and plant regionalization of Pennisetum alopecuroides (L.) in future.

Ratio of carbon and nitrogen in fertilizer treatment drives distinct rhizosphere microbial community composition and co-occurrence networks.

Fertilization is the main strategy to accelerate vegetation restoration and improve the rhizosphere microbial community in the northeast China. However, the responses of rhizosphere microbial community structure, specific microbial community and symbiotic pattern to manure fertilization in grassland (alfalfa only) are not well clear. In this study, the variation of bacterial community structures in R_Manure (extracted liquid of fermented cow manure), E_Manure (extracted residue of fermented cow manure), F_Manure (full fermented cow manure), and Control (without fermented cow manure) collected from the rhizosphere microbial community of alfalfa were analyzed by the application of an Illumina HiSeq high-throughput sequencing technique. A total of 62,862 microbial operational taxonomic units (OTUs) were detected and derived from 21 phyla of known bacteria. The dominant bacteria in the rhizosphere include Proteobacteria (70.20%), Acidobacteria (1.24%), Actinobacteria (2.11%), Bacteroidetes (6.15%), Firmicutes (4.21%), and Chlorofexi (2.13%) accounting for 86% of the dominant phyla in all treatments. At the genus level, the dominant genus include NB1-j, Lysobacter, Alphaproteobacteria, Subgroup_6, Actinomarinales, Saccharimonadales, Aneurinibacillus, MO-CFX2, SBR1031, Caldilineaceae, and so on with the average relative abundance (RA) of 1.76%, 1.52%, 1.30%, 1.24%, 1.61%, 2.39%, 1.36%, 1.42%, 1.27%, and 1.03%, respectively. Bacterial diversities and community structures were significantly differentiated by different treatments of fertilization. The results of community structure composition showed that R_Manure treatment significantly increased the population abundance of Firmicutes, Chlorofexi, and Patescibacteria by 34.32%, 6.85%, and 2.70%, and decreased the population abundance of Proteobacteria and Actinobacteria by 16.83% and 1.04%, respectively. In addition, it showed that all treatments significantly resulted in an increase or decrease at the genus level. R_Manure had the higher richness and diversity of the bacterial community, with the greatest topology attributes of the co-occurrence networks. Through the analysis of the molecular ecological network (MENA), the co-occurrence networks had a shorter average path distance and diameter in R_Manure than in others, implying more stability to environmental changes. Redundancy analysis (RDA) showed that the ratio of carbon and nitrogen (C/N) was the main factor affecting rhizosphere microbial community composition while driving distinct rhizosphere bacterial community and its co-occurrence networks. The R_Manure associated with more C/N had relatively complex microbial co-occurrence network with a large number of nodes and edges, while the microbial network of others associated with less C/N had fewer taxa with loose mutual interactions. These results suggested that organic fertilizer with high C/N can regulate the rhizosphere microorganism, while high C/N can determine bacterial community structures, specific bacterial taxa, and their relationships with the nodule size of alfalfa. These significant changes can be used to evaluate soil fertility and fertilizer management in the artificial grassland system, while the potential biological indicators of the rhizosphere microbial community will play an important role in future eco-agriculture.

Comparison of soil microbial community between reseeding grassland and natural grassland in Songnen Meadow.

Microorganisms have important ecological functions in ecosystems. Reseeding is considered as one of the main strategies for preventing grassland degradation in China. However, the response of soil microbial community and diversity to reseeding grassland (RG) and natural grassland (NG) remains unclear, especially in the Songnen Meadow. In this study, the soil microbial community compositions of two vegetation restoration types (RG vs NG) were analyzed using a high-throughput sequencing technique. A total of 23,142 microbial OTUs were detected, phylogenetically derived from 11 known bacterial phyla. Soil advantage categories included Proteobacteria, Acidobacteria, Actinobacteria, and Bacteroidetes, which together accounted for > 78% of the all phyla in vegetation restoration. The soil microbial diversity was higher in RG than in NG. Two types of vegetation restoration had significantly different characteristics of soil microbial community (P < 0.001). Based on a molecular ecological network analysis, we found that the network in RG had a longer average path distance and modularity than in NG network, making it more resilient to environment changes. Meanwhile, the results of the canonical correspondence analysis and molecular ecological network analysis showed that soil pH (6.34 ± 0.35 in RG and 7.26 ± 0.28 in NG) was the main factor affecting soil microbial community structure, followed by soil moisture (SM) in the Songnen meadow, China. Besides, soil microbial community characteristics can vary significantly in different vegetation restoration. Thus, we suggested that it was necessary and reasonable for this area to popularize reseeding grassland in the future.

Efficient Generation of CRISPR/Cas9-Mediated Homozygous/Biallelic Medicago truncatula Mutants Using a Hairy Root System.

In the process of acquiring mutants mediated by CRISPR/Cas9, plantlets are often regenerated from both mutated and non-mutated cells in a random manner, which increase the odds of chimeric mutated plant. In general, it's necessary to infect more explants or grow to next generation for the need of generating more biallelic or homozygous mutants. In present study, an efficient way of obtaining biallelic or homozygous mutated lines via fast-growing hairy root system without increasing numbers of infected explants or prolonging sexual propagation generation is reported. The fast growing lateral branches of hair roots are originated deep within the parental root from a small number of founder cells at the periphery, and therefore were employed as a library that classify different editing types in different lateral branches in which the homozygous or biallelic lines were screened. Here, MtPDS was employed in a proof-of-concept experiment to evaluate the efficiency of genome editing with our hairy root system. Homozygous/biallelic mutations were found only 1 of the 20 lines in the 1st generation hairy roots, and 8 lines randomly selected were cultured to obtain their branch roots, homozygous/biallelic mutations were found in 6 of the 8 lines in their branch roots. We also tested the method with MtCOMT gene and got the same result. All of the seedlings regenerated from the homozygous/biallelic hairy root mutation lines of MtPDS displayed albino phenotypes. The entire process from vector design to the recovery of plantlets with homozygous/biallelic mutations took approximately 4.5-6.5 months. The whole process could bring inspiration for efficiently generating homozygous/biallelic mutants through CRISPR/Cas9 system from the hairy root or root system of a chimeric mutated transformants, especially for the rare and endangered plants whose explants sources are very limited or the plants that lack of tissue culture and rapid propagation system.

Reduced-tillage management enhances soil properties and crop yields in a alfalfa-corn rotation: Case study of the Songnen Plain, China.

The reduced-tillage (Rt) has been proposed as a strategy to improve soil organic carbon and soil total nitrogen pools. However, little is known of the role of the reduced-tillage compared with the organic (Org) and conventional (Con) management in the Songnen Plain of China. We studied the 4 yr effect of three management strategies (Con, Org and Rt management) on labile soil organic carbon (C) and nitrogen (N) pools, including variation in mineralizable carbon and nitrogen, microbial biomass carbon and nitrogen, dissolved organic carbon and nitrogen in the rotation of alfalfa-corn established in 2009. Soil characteristics including soil organic carbon (SOC), soil total nitrogen (STN), dissolved organic carbon (DOC), dissolved organic nitrogen (DON), microbial biomass carbon (MBC), and microbial biomass nitrogen (MBN) were quantified in samples collected during the 9 yr rotation of 5yr-alfalfa (Medicago sativa L.) followed by 4 yr corn (Zea mays L.). The mineralizable C was increased in the four years, and although not statistically significant, 12% higher in the fourth year under reduced-tillage than conventional management (268 kg ha-1). Soil organic C was increased by 30% under reduced-tillage compared to conventional management (15.5 Mg ha-1). Three management strategies showed similar labile N pools in the Con and Org management, but differed in the Rt management. Org management showed significantly lesser mineralizable and inorganic N compared to other strategies, but soil microbial community and comparable crop yield across management strategy in year 4, indicating more efficient N use for organic than other management strategy. In our conditions, reduced-tillage for corn cropping after five years of alfalfa grassland can accumulate labile C and N and improve N utilization to for crop yields in the forage-based rotations. These findings suggest an optimal strategy for using Rt management to enhance soil properties and crop yield in plantation soils and provide a new perspective for understanding the potential role of Rt management in plantation soil.

Evaluation of Leymus chinensis quality using near-infrared reflectance spectroscopy with three different statistical analyses.

Due to a boom in the dairy industry in Northeast China, the hay industry has been developing rapidly. Thus, it is very important to evaluate the hay quality with a rapid and accurate method. In this research, a novel technique that combines near infrared spectroscopy (NIRs) with three different statistical analyses (MLR, PCR and PLS) was used to predict the chemical quality of sheepgrass (Leymus chinensis) in Heilongjiang Province, China including the concentrations of crude protein (CP), acid detergent fiber (ADF), and neutral detergent fiber (NDF). Firstly, the linear partial least squares regression (PLS) was performed on the spectra and the predictions were compared to those with laboratory-based recorded spectra. Then, the MLR evaluation method for CP has a potential to be used for industry requirements, as it needs less sophisticated and cheaper instrumentation using only a few wavelengths. Results show that in terms of CP, ADF and NDF, (i) the prediction accuracy in terms of CP, ADF and NDF using PLS was obviously improved compared to the PCR algorithm, and comparable or even better than results generated using the MLR algorithm; (ii) the predictions were worse compared to laboratory-based spectra with the MLR algorithmin, and poor predictions were obtained (R2, 0.62, RPD, 0.9) using MLR in terms of NDF; (iii) a satisfactory accuracy with R2 and RPD by PLS method of 0.91, 3.2 for CP, 0.89, 3.1 for ADF and 0.88, 3.0 for NDF, respectively, was obtained. Our results highlight the use of the combined NIRs-PLS method could be applied as a valuable technique to rapidly and accurately evaluate the quality of sheepgrass hay.