Summary Soil microbes and enzymes play vital roles in the decomposition and transformation of soil material, nutrient cycling, energy flow and physicochemical properties. However, the responses of soil microbes and enzymes to warming remains poorly understood, which limits our ability to predict the consequences of future climate warming. To understand better how climate warming will alter the activity of soil microbes and enzymes, we established a field experiment to manipulate temperature in an alpine meadow in northwestern Sichuan, China. After 5 years of experimental warming, soil bacterial communities were assessed by MiSeq sequencing of 16S rRNA gene amplicons. The results showed that the experimental warming treatments increased the soil acid phosphatase, invertase and urease activity, and available nutrients, but decreased the catalase activity and soil organic matter (SOM) at the 0–10‐cm soil depth. However, the warming treatment increased catalase activity, SOM, available nitrogen (AN) and available potassium (AK), but decreased invertase activity at the 10–20‐cm soil depth. Warming significantly increased the relative abundance of Chloroflexi at the 0–10‐cm depth, whereas it significantly increased the relative abundance of Cyanobacteria and decreased the relative abundance of Firmicutes at the 10–20‐cm depth. Similarly, warming altered the relative abundance of bacterial genera, for example Candidatus Solibacter increased, whereas Pseudomonas and Janthinobacterium decreased. Warming did not significantly affect diversity or structure of the soil bacterial community. The soil acid phosphatase and urease activity, and SOM, total potassium (TK), AK and total phosphorus (TP) contents were strongly correlated with the soil bacterial community. Overall, despite the pronounced changes in soil enzyme activity and plant nutrient contents under warming, composition and diversity of the soil bacterial community were not changed. This study helps to elucidate soil responses in grasslands to climate warming. Highlights Warming promoted nutrient mineralization and altered soil enzyme activity. Warming decreased diversity of the soil bacterial community. Specific taxa responded differentially to experimental warming. Soil microorganisms regulated plant nutrient cycling under continuous climate warming.
Germination of dragon spruce (Picea asperata Mast.) seeds pretreated with gibberellin (GA) in response to water stress and changes in the levels of osmotic adjustments as well as in activities of antioxidant enzymes were investigated. With decreasing water potential caused by increasing concentrations of PEG 6000, germination percentage and germination index decreased gradually; the decrease was especially prominent under the serious water stress from PEG -0.6 MPa. In contrast, osmotic regulation substances (free proline and soluble sugar contents), lipid peroxidation (MDA), and activities of antioxidant enzyme (ascorbate peroxidase, catalase, and peroxidase) increased markedly with decreased water potential. Similarly, the values in all parameters under -0.6 MPa PEG treatment were markedly higher than the control and -0.2 MPa PEG treatment. These results suggested that P. asperata seed germination was insensitive to water stress. In addition, seeds pretreated with GA had increased tolerance to water stress as measured by germination percentage and germination index, osmotic regulation substance, and antioxidant enzyme activities.
Non-destructive and rapid monitoring methods for crude protein content (CPC) in rice grain are of significance in nitrogen diagnosis and grain quality monitoring, and in enhancing nutritional management and use efficiency. In this study, CPC and canopy spectra in rice were measured based on rice field experiment. Key spectral bands were selected by principal component analysis (PCA) method, and the predicted models were built by multiple linear regressions (MLR), artificial neural network (ANN) and partial least squares regression (PLSR). The results showed that there is a significant correlation between CPC content and key spectral bands. The results of prediction for the three models were in order of PLSR > ANN > MLR with correlation values of 0.96, 0.92 and 0.90, respectively, for the validation data. Therefore, it is implied that CPC in rice (grain quality) could be estimated by canopy spectral data.
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