11 research outputs found

    Estimated <i>RR</i> for province.

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    <p>Fig 3a. Estimated unadjusted spatial <i>RR</i> for provinces, Fig 3b. Estimated spatial structured <i>RR</i> for provinces, Fig 3c. Estimated random effects <i>RR</i> of avtemp for provinces, Fig 3d. Estimated spatial unstructured <i>RR</i> for provinces(Fig 3a <i>RR</i> generated from null multilevel model unadjustment for spatial correlated strucuture effects and climatic varialbes, Fig 3b–3d <i>RR</i> generated from final multilevel model adjustment for spatial correlated effects and climatic variables).</p

    Relationship between climatic variables and HFMD incidence.

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    <p>Relative changes of HFMD incidence as smooth spline function of avtemp (2a), devtemp (2b), mavhmd (2c) and hsun (2d). (Solid line: fitted values; dash line: 95% confidence interval of fitted value; Vertical bar located on x-axis: distribution of climatic variables).</p

    Time series plot of weekly HFMD cases and climatic variables of China, 2008–2013.

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    <p>Pcase (weekly reported cases of HFMD), avtemp (weekly average temperature (°C)), maxtemp (weekly maximum temperature (°C)), mintemp (weekly minimum temperature (°C)), rainfall (weekly average 20–20 hours rainfall (0.1 millimeters)), mavhmd (weekly average relative humidity (0.1%)), hsun (weekly average hours of sunshine (0.1hours)), mavwspeed (weekly average wind speed (meters per second)).</p

    Additional file 1 of Nitrogen use efficiency of terrestrial plants in China: geographic patterns, evolution, and determinants

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    Additional file 1: Fig. S1. Spatial site distributions in the NUE database. Fig. S2. Phylogenetic tree and phylogenetic signals of NUE. Fig. S3. Bivariate relationships between NUE and plant foliar phosphorus (a), MAT (b), MAP (c) and AI (d) of different ecosystems. Fig. S4. Bivariate relationships between NUE and plant foliar phosphorus of different life forms. Fig. S5. The bivariate relationships between NUE and soil physical properties. Fig. S6. The bivariate relationships between NUE and soil physical properties of different ecosystems. Fig. S7. The bivariate relationships between NUE and soil chemical properties. Fig. S8. The bivariate relationships between NUE and soil chemical properties of different ecosystems. Fig. S9. The bivariate relationships between NUE and N:P ratios. Fig. S10. Changes in the leaf δ15N over evolutionary time at the family level

    Table_1_Seasonal and Inter-Annual Variations of Carbon Dioxide Fluxes and Their Determinants in an Alpine Meadow.docx

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    The alpine meadow is one of the most important ecosystems on the Qinghai-Tibet Plateau (QTP) due to its huge carbon storage and wide distribution. Evaluating the carbon fluxes in alpine meadow ecosystems is crucial to understand the dynamics of carbon storage in high-altitude areas. Here, we investigated the carbon fluxes at seasonal and inter-annual timescales based on 5 years of observations of eddy covariance fluxes in the Zoige alpine meadow on the eastern Tibetan Plateau. We found that the Zoige alpine meadow acted as a faint carbon source of 94.69 ± 86.44 g C m−2 y−1 during the observation periods with large seasonal and inter-annual variations (IAVs). At the seasonal scale, gross primary productivity (GPP) and ecosystem respiration (Re) were positively correlated with photosynthetic photon flux density (PPFD), average daily temperature (Ta), and vapor pressure (VPD) and had negative relationships with volumetric water content (VWC). Seasonal variations of net ecosystem carbon dioxide (CO2) exchange (NEE) were mostly explained by Ta, followed by PPFD, VPD, and VWC. The IAVs of GPP and Re were mainly attributable to the IAV of the maximum GPP rate (GPPmax) and maximum Re rate (Remax), respectively, both of which increased with the percentage of Cyperaceae and decreased with the percentage of Polygonaceae changes across years. The IAV of NEE was well explained by the anomalies of the maximum CO2 release rate (MCR). These results indicated that the annual net CO2 exchange in the alpine meadow ecosystem was controlled mainly by the maximum C release rates. Therefore, a better understanding of physiological response to various environmental factors at peak C uptake and release seasons will largely improve the predictions of GPP, Re, and NEE in the context of global change.</p

    Data for "Nitrogen enrichment induces more plant species loss under drier conditions"

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    Nitrogen (N) deposition is a major driver of plant species loss worldwide. However, what regulates N-driven species loss remains unclear. Based on a 7-year field experiment on the Qinghai-Tibetan Plateau, we found that the impact of N addition on plant species richness strongly depended on precipitation. During experimental years with lower precipitation, N addition induced more species loss. The main underlying mechanism was that lower precipitation stimulated soil inorganic N accumulation under N addition, resulting in stronger competitive exclusion and ammonium toxicity in plant communities. These site observations were complemented by a global synthesis derived from 45 N addition experiments, showing N-induced more species loss in dry than in wet ecosystems. Given the importance of plant species richness in supporting ecosystem functioning and stability, our findings suggest that ecosystems during drought periods or in arid areas are particularly sensitive to N deposition, having important implications for their management and conservation.</p
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