Impacts of human pressure and climate on biodiversity-multifunctionality relationships on the Qinghai-Tibetan Plateau.

Many studies have investigated the effects of environmental context on biodiversity or multifunctionality in alpine regions, but it is uncertain how human pressure and climate may affect their relationships. Here, we combined the comparative map profile method with multivariate datasets to assess the spatial pattern of ecosystem multifunctionality and further identify the effects of human pressure and climate on the spatial distribution of biodiversity-multifunctionality relationships in alpine ecosystems of the Qinghai-Tibetan Plateau (QTP). Our results indicate that at least 93% of the areas in the study region show a positive correlation between biodiversity and ecosystem multifunctionality across the QTP. Biodiversity-multifunctionality relationships with increasing human pressure show a decreasing trend in the forest, alpine meadow, and alpine steppe ecosystems, while an opposite pattern was found in the alpine desert steppe ecosystem. More importantly, aridity significantly strengthened the synergistic relationship between biodiversity and ecosystem multifunctionality in forest and alpine meadow ecosystems. Taken together, our results provide insights into the importance of protecting and maintaining biodiversity and ecosystem multifunctionality in response to climate change and human pressure in the alpine region.

Whole Transcriptomic Analysis of Key Genes and Signaling Pathways in Endogenous ARDS.

Objective: To analyze the differentially expressed genes (DEGs) in rats with endogenous acute respiratory distress syndrome (ARDS) lung injury and explore the pathogenesis and early diagnostic molecular markers using whole transcriptomic data. Methods: Twelve 8-week-old male Sprague Dawley rats were selected and randomly and equally divided into ARDS lung injury group and normal control group. RNA was extracted from the left lung tissues of both the groups and sequenced using the paired-end sequencing mode of the Illumina Hiseq sequencing platform. The DEGs of miRNA, cirRNA, lncRNA, and mRNA were screened using DESeq2 software, and the ceRNA regulatory network was constructed using Cytoscape. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed using the mRNA DEGs. STRING and Cytoscape software were used to construct the protein interaction network and identify the 15 key genes, which were verified using quantitative real-time polymerase chain reaction (qRT-PCR). Results: Based on different screening conditions, and compared with the control group, the ARDS lung injury group showed 836 mRNA DEGs (386 upregulated and 450 downregulated), 110 lncRNA DEGs (53 upregulated and 57 downregulated), 19 circRNA DEGs (3 upregulated and 16 downregulated), and 6 miRNA DEGs (5 upregulated and 1 downregulated gene). GO showed that the DEGs of mRNA were mainly involved in biological processes, such as defense response to lipopolysaccharide and other organisms, leukocyte chemotaxis, neutrophil chemotaxis, and cytokine-mediated signaling. KEGG enrichment analysis showed that the DEGs played their biological roles mainly by participating in IL-17, TNF, and chemokine signaling pathways. The PPI analysis showed a total of 281 node proteins and 634 interaction edges. The top 15 key genes, which were screened, included Cxcl10, Mx1, Irf7, Isg15, Ifit3, Ifit2, Rsad2, Ifi47, Oasl, Dhx58, Usp18, Cmpk2, Herc6, Ifit1, and Gbp4. The ceRNA network analysis showed 69 nodes and 73 correlation pairs, where the key gene nodes were miR-21-3p, Camk2g, and Stx2. Conclusions: The chemotaxis, migration, and degranulation of inflammatory cells, cytokine immune response, autophagy, and apoptosis have significant biological functions in the occurrence and development of endogenous acute lung injury during ARDS. Thus, the camk2g/miR-21-3p/lncRNA/circRNA network, CXCL10/CXCR3, and IL-17 signaling pathways might provide novel insights and targets for further studying the lung injury mechanism and clinical treatment.

Identification and validation of autophagy-related genes in exogenous sepsis-induced acute respiratory distress syndrome.

OBJECTIVE: To analyze the differential expression of autophagy-related genes of sepsis-induced acute respiratory distress syndrome (ARDS) as potential markers for early diagnosis. METHODS: Male Sprague-Dawley rats (aged 8 weeks) were selected and randomly divided into sepsis-induced ARDS group (n = 6) and a normal control group (n = 6). Lung tissue samples were collected for high-throughput sequencing using Illumina HiSeq sequencing platform in the paired-end sequencing mode. Differentially expressed genes (DEGs) were screened by DESeq. 2 software [|log2FC | ≥1 and p < .05] and autophagy-related genes were identified using Mouse Genome Informatics. Co-expressed autophagy-related DEGs from these two datasets were filtered by construction of a Venn diagram. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on these autophagy-related DEGs and a protein interaction network was constructed using STRING and Cytoscape software to identify hub genes, which were verified by real-time quantitative polymerase chain reaction (qRT-PCR). RESULTS: A total of 42 autophagy-related DEGs (26 upregulated genes and 16 downregulated genes) were identified. The GO and KEGG pathway analyses showed enrichment in 969 biological processes (BPs), three cellular components (CCs), eight molecular functions (MFs) and 27 signaling pathways. The protein interaction (PPI) network revealed 42 node proteins and 75 interacting edges, with an average node degree of 3.52, and an average local clustering coefficient of 0.509. Among the top 10 hub genes with the RNA-Seq, six hub genes (Stat3, Il10, Ifng, Hmox1, Hif1a, and Nod2) were validated by qRT-PCR (all p < .05). CONCLUSION: 42 potential autophagy-related genes associated with sepsis-induced ARDS lung injury were identified and six hub genes (Stat3, Il10, Ifng, Hmox1, Hif1a, and Nod2) may affect the development of ARDS by regulating autophagy. These results expanded our understanding of ARDS and might be useful in treatment of exogenous sepsis-induced ARDS.

Global patterns and abiotic drivers of ecosystem multifunctionality in dominant natural ecosystems.

The potential patterns and processes of ecosystem multifunctionality (EMF) across global ecosystems are largely unknown, which limits our understanding of how ecosystems respond to drivers. Here we compile a global dataset that consists of 973 unique sites across the forest, grassland, and shrub ecosystems. We identify a critical global pattern of hump-shaped EMF relationship with mean annual precipitation at a threshold of ∼671 mm, where low and high precipitation patterns are discriminated. We find that climatic and soil factors jointly drive the EMF in low precipitation areas, and climatic factors dominate the EMF in high precipitation regions. However, when comparing across the three dominant ecosystems and precipitation regions, the key driver in EMF differs substantially. Specifically, climatic and soil factors dominate the EMF of low and high precipitation regions across forest ecosystems, respectively. Climatic drivers dominate the EMF under different precipitation conditions across grassland and shrub ecosystems. Overall, our findings highlight the importance of climatic and soil drivers on EMF, which should be considered in ecosystem stability models in response to global climate and land-use change scenarios.

Response of net reduction rate in vegetation carbon uptake to climate change across a unique gradient zone on the Tibetan Plateau.

The Tibetan Plateau (TP) has a variety of vegetation types that range from alpine tundra to tropic evergreen forest, which play an important role in the global carbon (C) cycle and is extremely vulnerable to climate change. The vegetation C uptake is crucial to the ecosystem C sequestration. Moreover, net reduction in vegetation C uptake (NRVCU) will strongly affect the C balance of terrestrial ecosystem. Until now, there is limited knowledge on the recovery process of vegetation net C uptake and the spatial-temporal patterns of NRVCU after the disturbance that caused by climate change and human activities. Here, we used the MODIS-derived net primary production to characterize the spatial-temporal patterns of NRVCU. We further explored the influence factors of the net reduction rate in vegetation C uptake (NRRVCU) and recovery processes of vegetation net C uptake across a unique gradient zone on the TP. Results showed that the total net reduction amount of vegetation C uptake gradually decreased from 2000 to 2015 on the TP (Slope = -0.002, P < 0.05). Specifically, an increasing gradient zone of multi-year average of net reduction rate in vegetation carbon uptake (MYANRRVCU) from east to west was observed. In addition, we found that the recovery of vegetation net C uptake after the disturbance caused by climate change and anthropogenic disturbance in the gradient zone were primarily dominated by precipitation and temperature. The findings revealed that the effects of climate change on MYANRRVCU and vegetation net C uptake recovery differed significantly across geographical space and vegetation types. Our results highlight that the biogeographic characteristics of the TP should be considered for combating future climate change.

Don't judge toxic weeds on whether they are native but on their ecological effects.

The sharp rise in anthropogenic activities and climate change has caused the extensive degradation of grasslands worldwide, jeopardizing ecosystem function, and threatening human well-being. Toxic weeds have been constantly spreading in recent decades; indeed, their occurrence is considered to provide an early sign of land degeneration. Policymakers and scientific researchers often focus on the negative effects of toxic weeds, such as how they inhibit forage growth, kill livestock, and cause economic losses. However, toxic weeds can have several potentially positive ecological impacts on grasslands, such as promoting soil and water conservation, improving nutrient cycling and biodiversity conservation, and protecting pastures from excessive damage by livestock. We reviewed the literature to detail the adaptive mechanisms underlying toxic weeds and to provide new insight into their roles in degraded grassland ecosystems. The findings highlight that the establishment of toxic weeds may provide a self-protective strategy of degenerated pastures that do not require special interventions. Consequently, policymakers, managers, and other personnel responsible for managing grasslands need to take appropriate actions to assess the long-term trade-offs between the development of animal husbandry and the maintenance of ecological services provided by grasslands.

Health Risk and Resilience Assessment with Respect to the Main Air Pollutants in Sichuan.

Rapid urbanization and industrialization in developing countries have caused an increase in air pollutant concentrations, and this has attracted public concern due to the resulting harmful effects to health. Here we present, through the spatial-temporal characteristics of six criteria air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) in Sichuan, a human health risk assessment framework conducted to evaluate the health risk of different age groups caused by ambient air pollutants. Public health resilience was evaluated with respect to the risk resulting from ambient air pollutants, and a spatial inequality analysis between the risk caused by ambient air pollutants and hospital density in Sichuan was performed based on the Lorenz curve and Gini coefficient. The results indicated that high concentrations of PM2.5 (47.7 µg m-3) and PM10 (75.9 µg m-3) were observed in the Sichuan Basin; these two air pollutants posed a high risk to infants. The high risk caused by PM2.5 was mainly distributed in Sichuan Basin (1.14) and that caused by PM10 was principally distributed in Zigong (1.01). Additionally, the infants in Aba and Ganzi had high health resilience to the risk caused by PM2.5 (3.89 and 4.79, respectively) and PM10 (3.28 and 2.77, respectively), which was explained by the low risk in these two regions. These regions and Sichuan had severe spatial inequality between the infant hazard quotient caused by PM2.5 (G = 0.518, G = 0.493, and G = 0.456, respectively) and hospital density. This spatial inequality was also caused by PM10 (G = 0.525, G = 0.526, and G = 0.466, respectively), which is mainly attributed to the imbalance between hospital distribution and risk caused by PM2.5 (PM10) in these two areas. Such research could provide a basis for the formulation of medical construction and future air pollution control measures in Sichuan.