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  • 1
    Online Resource
    Online Resource
    Elsevier BV ; 2016
    In:  Tourism Management Vol. 55 ( 2016-08), p. 261-271
    In: Tourism Management, Elsevier BV, Vol. 55 ( 2016-08), p. 261-271
    Type of Medium: Online Resource
    ISSN: 0261-5177
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2016
    detail.hit.zdb_id: 2001580-X
    SSG: 3,2
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  • 2
    Online Resource
    Online Resource
    Wiley ; 2015
    In:  International Journal of Climatology Vol. 35, No. 10 ( 2015-08), p. 2752-2758
    In: International Journal of Climatology, Wiley, Vol. 35, No. 10 ( 2015-08), p. 2752-2758
    Abstract: Surface greenness and rainfall in spring have changed from the 1980s to 1990s over the North China Plain (NCP). The greenness changes are characterized by large increase in north and little in south with an obvious greening zone from the centre of the NCP to the northeast. The rainfall change has a similar spatial pattern with reversed sign. The correlation between changes in greenness and rainfall is significant and the correlation ( r  = −0.71, p   〈  0.001) is highest for light rainfall. The number of light rainfall days decreased by only ∼10% at the stations where the Normalized Differences Vegetation Index (NDVI) did not change, whereas it decreased by up to ∼30% at the stations where NDVI increased by 20%. Further analyses found that surface greening increased evaporation wetting the atmosphere and, meanwhile, reduced sensible heat flux to cooling surface air. The cooling surface promotes the air stability and thus suppresses the occurrence of rainfall. This finding supports that surface cooling effects from greening play a more dominant role on occurrence of spring rainfall than the wetting effect in the NCP.
    Type of Medium: Online Resource
    ISSN: 0899-8418 , 1097-0088
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2015
    detail.hit.zdb_id: 1491204-1
    SSG: 14
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  • 3
    Online Resource
    Online Resource
    Wiley ; 2018
    In:  International Journal of Climatology Vol. 38, No. 13 ( 2018-11), p. 5030-5036
    In: International Journal of Climatology, Wiley, Vol. 38, No. 13 ( 2018-11), p. 5030-5036
    Abstract: Temperature sensitivity ( S T ) of phenology, defined as the shift of phenophase with per unit change of preseason temperature, has been widely used to quantify phenological response to climate change. The spatial variation in S T of spring phenology has been well studied for several woody plants, but how to explain it became a challenge. Several hypotheses to explain the spatial variation in S T have been proposed, but studies examining all potential factors together were very limited. In this study, using first flowering date (FFD) data for five widespread woody plants at 47 stations in China and the other five species at 421 stations in central Europe during 1964–2014, we calculated S T by using the Sen's slope of FFD on mean preseason temperature for each species at each station. Subsequently, multiple regression analysis was applied to examining whether S T followed the geographical (latitudinal, longitudinal, or vertical) gradients. At last, four potential influencing factors of S T were tested by Spearman partial correlation analysis. We found that S T of FFD was higher at lower latitude for most species in China. However, in central Europe, the variation of S T did not follow the geographical gradient for most species. Only one species ( Fraxinus excelsior ) showed a latitudinal gradient, and one ( Betula pendula ) showed a longitudinal gradient. For most species in both regions, the strength of FFD–temperature relationship and the preseason length could account for the spatial variation of S T to a more considerable extent compared to preseason temperature variance and chilling conditions. Our results suggest that we need to consider the effects of multiple factors on phenological response to temperature when simulating future phenological change.
    Type of Medium: Online Resource
    ISSN: 0899-8418 , 1097-0088
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 1491204-1
    SSG: 14
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  • 4
    Online Resource
    Online Resource
    Wiley ; 2021
    In:  Journal of the Science of Food and Agriculture Vol. 101, No. 9 ( 2021-07), p. 3644-3653
    In: Journal of the Science of Food and Agriculture, Wiley, Vol. 101, No. 9 ( 2021-07), p. 3644-3653
    Abstract: Adaptive crop management is critical to food security in a changing climate, but the respective contributions of climate change and crop management to yields remain unclear. Thus, we distinguished and quantified the respective contribution of climate change and crop management on wheat yield between 1981 and 2018 in China, using first‐difference multivariate regression model. RESULTS Wheat production in China has increased over the past four decades. Under the sole impact of climate change, wheat yield generally decreased (−5.45 to +1.09% decade −1 ). Crop management increased the wheat yield from 7.11 to 19.94% decade −1 . Sensitivities of wheat yield to climatic variables (average temperature, accumulated sunshine hours, accumulated precipitation) were spatially heterogeneous; notably, in spring‐wheat planting areas, wheat yield was more susceptible to the negative impact of warming. In terms of relative contribution, the contribution of climate change to spring wheat yield was −24.08% to −5.41%, and the contribution to winter wheat was −4.98% to +34.69%. Crop management had a positive contribution to all wheat‐growing areas (65.31–96.84%). CONCLUSION Crop management had a greater effect on wheat yield than climate change did. Among the three climatic variables investigated, average temperature had the dominant effect on wheat yield change; the impact of precipitation was minimal but mostly negative. The results provide insight regarding the contribution of climate change and crop management to wheat yield; adaptation measures may be more effective in planting areas where crop management contributes more, which will help stakeholders optimize crop management and adaptation strategies. © 2020 Society of Chemical Industry
    Type of Medium: Online Resource
    ISSN: 0022-5142 , 1097-0010
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2001807-1
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  • 5
    Online Resource
    Online Resource
    Wiley ; 2018
    In:  International Journal of Climatology Vol. 38, No. 7 ( 2018-06), p. 2922-2939
    In: International Journal of Climatology, Wiley, Vol. 38, No. 7 ( 2018-06), p. 2922-2939
    Abstract: Understanding how different climate factors interact and impact rice yield is essential for effective agricultural management strategies and policies. However, the potential impacts are less clear at the regional scale. In this work, we used the latest version of the ORYZA crop model to evaluate the impacts of climate change and carbon dioxide (CO 2 ) on rice yields in the Sichuan Basin of China based on high‐quality agricultural experimental, meteorological and soil data and the incorporation of future climate data generated by five general circulation models (GCMs) under three newly released representative concentration pathway (RCP) 2.6, 4.5 and 8.5 scenarios. Considering climate change alone, our modelling results indicated a continuing rice reduction for most stations by 2–17, 4–28 and 1–43% under the RCP2.6, 4.5 and 8.5 scenarios, respectively; when considering the CO 2 fertilizer effect, rice yields increased by 3–10, 4–13 and 5–20% under the RCP2.6, 4.5 and 8.5 scenarios, respectively. However, for most stations, the CO 2 fertilizer effect could not completely offset the negative impacts of climate change on rice yields. In addition, temperature and radiation were the main climate factors that cause yield variation by affecting the rice maturity periods (DAE), spikelet fertility factor (SPFERT) and spikelet number (NSP). The uncertainty arising from the climate models was less than 10% under the RCP2.6 scenario, 15% under the RCP4.5 scenario and 20% under the RCP8.5 scenario, indicating good consistency in rice yield simulations. These findings offer insight into the physiological mechanisms and the degree of climate change impacts on rice yields, thus informing appropriate adaptive strategies for rice planting in the Sichuan Basin, China.
    Type of Medium: Online Resource
    ISSN: 0899-8418 , 1097-0088
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 1491204-1
    SSG: 14
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  • 6
    Online Resource
    Online Resource
    Wiley ; 2023
    In:  International Journal of Climatology
    In: International Journal of Climatology, Wiley
    Abstract: Hydroclimate variations over eastern China are affected by the Asian monsoon, exhibiting great variability and frequent extreme events occurrence. However, the driving mechanisms of their spatial and temporal variabilities are not fully understood due to the short period of available climate observation data. Here we used interpolated dry/wet grades dataset derived from Chinese historical documents and method of regional division to reconstruct a new annual hydroclimatic variation dataset dating back 1000 years, including nine regions of eastern China. This dataset reveals the spatial coverage and trend of long‐lasting extreme drought and flood events, and discloses the spatial patterns and similarities of interannual (2–7‐year) and interdecadal (15–35‐year) hydroclimate variations under the different temperature backgrounds of the Medieval Climate Anomaly (MCA), Little Ice Age (LIA) and Current Warm Period. Although no obvious drying or wetting trends were detected in the past 1000 years, the frequencies of extreme flood and drought events during the two warm periods of 960–1300 and 1901–2000 were higher than those during the cold period of 1301–1900. There are 17 long‐lasting and even severe than 1637–1641 large spatial scale extreme drought events during the past 1000 years. The observed spatial dipole pattern of flooding in the south and drought in the north, or the opposite pattern, was rare during the historical period. However, it was the second leading mode explaining the low variances in the principal component analysis for 2–7‐year hydroclimatic variations, which were not related to temperature change. Moreover, the stability of the teleconnection between the hydroclimate over eastern China and the climatic modes of Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation was further discussed.
    Type of Medium: Online Resource
    ISSN: 0899-8418 , 1097-0088
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 1491204-1
    SSG: 14
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  • 7
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2010
    In:  Science China Earth Sciences Vol. 53, No. 5 ( 2010-5), p. 694-699
    In: Science China Earth Sciences, Springer Science and Business Media LLC, Vol. 53, No. 5 ( 2010-5), p. 694-699
    Type of Medium: Online Resource
    ISSN: 1674-7313 , 1869-1897
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2010
    detail.hit.zdb_id: 2546528-4
    SSG: 6,25
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  • 8
    Online Resource
    Online Resource
    American Meteorological Society ; 2016
    In:  Journal of Applied Meteorology and Climatology Vol. 55, No. 6 ( 2016-06), p. 1359-1376
    In: Journal of Applied Meteorology and Climatology, American Meteorological Society, Vol. 55, No. 6 ( 2016-06), p. 1359-1376
    Abstract: Climate change will inevitably continue for the next few decades and will have an impact on climate-sensitive agricultural production, emphasizing the need to design effective adaptive strategies to cope with climate risk or take advantage of potential climatic benefits. In this study, the latest version of the Crop Environment Resource Synthesis-Rice (CERES-Rice) model was applied to assess the impacts of climate change and carbon dioxide (CO 2 ) fertilization on rice yield, as well as the effectiveness of two popularly adopted adaptive measures in Hunan Province, the main rice-production location in China. The simulation spanned 30 years of baseline (1981–2010) as well as three future periods (2011–40, 2041–70, and 2071–99) with climate data generated by five general circulation models under the newly developed representative concentration pathway (RCP) 4.5 and 8.5 scenarios. The simulation results showed that, in comparison with average rice yield during the baseline (1981–2010), the ensemble-average yield of all cultivars during the 2020s, 2050s, and 2080s would decrease under both RCPs without CO 2 fertilization effects. The ensemble-average yield reduction during the 2080s was alleviated under both RCPs if CO 2 fertilization effects were accounted for. Adaptation simulations indicated that two adaptive measures (switching cultivars and changing planting dates) could mitigate the adverse effect to different extents. The intermodel variability under both RCPs was generally small. These findings may provide useful insight into the potential impacts of climate change on rice yield and effective adaptive measures to mitigate the adverse effect of future climate change in Hunan Province.
    Type of Medium: Online Resource
    ISSN: 1558-8424 , 1558-8432
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2016
    detail.hit.zdb_id: 2227779-1
    detail.hit.zdb_id: 2227759-6
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  • 9
    In: Journal of Rare Earths, Elsevier BV, Vol. 33, No. 1 ( 2015-01), p. 1-12
    Type of Medium: Online Resource
    ISSN: 1002-0721
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2015
    detail.hit.zdb_id: 2238797-3
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  • 10
    Online Resource
    Online Resource
    IOP Publishing ; 2020
    In:  Environmental Research Letters Vol. 15, No. 9 ( 2020-08-25), p. 094055-
    In: Environmental Research Letters, IOP Publishing, Vol. 15, No. 9 ( 2020-08-25), p. 094055-
    Type of Medium: Online Resource
    ISSN: 1748-9326
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2020
    detail.hit.zdb_id: 2255379-4
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