Convergence and divergence emerging in climatic controls of polynomial trends for northern ecosystem productivity over 2000-2018.

Recent rapid warming has caused uneven impacts on the composition, structure, and functioning of northern ecosystems. It remains unknown how climatic drivers control linear and non-linear trends in ecosystem productivity. Based on a plant phenology index (PPI) product at a spatial resolution of 0.05° over 2000-2018, we used an automated polynomial fitting scheme to detect and characterize trend types (i.e., polynomial trends and no-trends) in the yearly-integrated PPI (PPIINT) for northern (> 30°N) ecosystems and their dependence on climatic drivers and ecosystem types. The averaged slope for the linear trends (p < 0.05) of PPIINT was positive across all the ecosystems, among which deciduous broadleaved forests and evergreen needle-leaved forests (ENF) showed the highest and lowest mean slopes, respectively. More than 50% of the pixels in ENF, arctic and boreal shrublands, and permanent wetlands (PW) had linear trends. A large fraction of PW also showed quadratic and cubic trends. These trend patterns agreed well with estimates of global vegetation productivity based on solar-induced chlorophyll fluorescence. Across all the biomes, PPIINT in pixels with linear trends showed lower mean values and higher partial correlation coefficients with temperature or precipitation than in pixels without linear trends. Overall, our study revealed the emergence of latitudinal convergence and divergence in climatic controls on the linear and non-linear trends of PPIINT, implying that northern shifts of vegetation and climate change may potentially increase the non-linear nature of climatic controls on ecosystem productivity. These results can improve our understanding and prediction of climate-induced changes in plant phenology and productivity and facilitate sustainable management of ecosystems by accounting for their resilience and vulnerability to future climate change.

Development of SYBR Green I-based polymerase chain reaction for feline bocavirus 1 detection.

Feline bocavirus 1 (FBoV-1) may be associated with diarrhea in cats. In this study, a SYBR Green I-based quantitative polymerase chain reaction (qPCR) assay was established to detect FBoV-1. The melting curve showed a single melting peak at 83.0 â„ƒ. The results of sensitivity showed that the detection limit of the qPCR was 3.87 × 101 copies/µL. Of note, the detection limit of the conventional polymerase chain reaction (cPCR) was 3.87 × 103 copies/µL. The highest intra-assay and inter-assay coefficients of variation (CV%) were 0.98% and 1.42%, respectively. The positive detection rate of 128 clinical samples using the qPCR and the cPCR was 7.0% (9/128) and 4.7% (6/128), respectively. Taken together, these results indicated that the established qPCR assay has good sensitivity, high specificity, and good reproducibility. Therefore, it could provide support for the rapid and efficient clinical detection of FBoV-1.

Development of SYBR Green I-based real-time reverse transcription polymerase chain reaction for the detection of feline astrovirus.

In this study, a SYBR Green I-based real-time reverse transcription-polymerase chain reaction (RT-PCR) was developed for the clinical diagnosis of feline astroviruses (FeAstVs). Specific primers were designed based on the conserved region of the FeAstV ORF1b gene. Experiments for specificity, sensitivity, and repeatability of the assay were carried out. In addition, the assay was evaluated using clinical samples. Specificity analysis indicated that the assay showed negative results with samples of Feline Parvovirus, Feline Herpesvirus, Feline Calicivirus, Feline Bocavirus, and Feline Coronavirus, indicating good specificity of the assay. Sensitivity analysis showed that the SYBR Green I-based real-time RT-PCR method could detect as low as 3.72 × 101 copies/µL of template, which is 100-fold more sensitive compared to the conventional RT-PCR. Both intra-assay and inter-assay variability were lower than 1 %, indicating good reproducibility. Furthermore, an analysis of 150 fecal samples showed that the positive detection rate of SYBR Green I-based real-time RT-PCR was higher than that of the conventional RT-PCR, indicating the high reliability of the method. The assay is cheap and effective. Therefore, it could provide support for the detection of FeAstV in large-scale clinical testing and epidemiological investigation.

Genetic and phylogenetic analysis of canine bufavirus from Anhui Province, Eastern China.

Bufavirus is a novel virus associated with canine gastroenteritis. Three strains of bufavirus were first detected in dog feces collected from Anhui province in Eastern China. The near-complete genome sequences were amplified. Sequence alignment showed 98.3-99.5% homology between the three bufavirus strains and reference strains. Phylogenetic analysis showed the distributed viruses forming a cluster of close relationships. Selective pressure analysis of the VP2 region indicated that the canine bufavirus (CBuV) was mainly subject to negative selection during evolution. The negative selection site was located on the residue of B-cell epitopes, indicating minimal change to the virus's immunogenicity. Since this is the first report of CBuV circulating in Anhui Province, this study will provide further understanding of the phylogenetic and molecular characteristics of CBuV and serve as a reference for prevention and vaccine development.

Genetic characterization and phylogenetic analysis of feline astrovirus from Anhui province in eastern China.

This study aimed to explore the phylogenetic and molecular characteristics of feline astrovirus. A total of 33 fecal samples of domestic cats with or without diarrhea were collected from the Anhui province, and two positive samples were detected. The complete genome and ORF2 of the two strains were sequenced and phylogenetically analyzed. AH-1-2020 and AH-2-2020 displayed 83.4% homology, and their homologies with other reference strains were 75.3%-83.4% and 83.4%-95.0%, respectively. Phylogenetic tree analysis revealed that all strains could be classified into three different clusters; therefore, the mean amino acid genetic distances (p-dist) among the three clusters were estimated. The results suggested that the two strains and other FeAstV strains were grouped into three genotypes, with AH-1-2020 belonging to a novel genotype. High similarity was observed (65.9%-66.5% nucleotide identity and 63.8%-64.8% amino acid identity) in ORF2 between porcine astrovirus type 1 and AH-1-2020. Furthermore, inter-specific recombination between porcine astrovirus type 1 and FeAstV was observed. We, therefore, inferred that inter-specific transmission may exist between pigs and cats; however, further studies are required to verify this. This is the first report on the genetic characterization and phylogenetic analysis of FeAstVs in the Anhui province and would further the current understanding of the genetic diversity and epidemiology of FeAstVs.