2022
DOI: 10.3390/land12010077
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Spatial and Temporal Patterns of Carbon and Water Use Efficiency on the Loess Plateau and Their Influencing Factors

Abstract: Quantitative assessment of the dynamics of carbon and water use efficiency on the Loess Plateau in the context of complex climate change and its driving mechanisms is important for the improvement of the regional ecological environment and the enhancement of ecological service functions. In order to assess the impact of climate change and human activities on the carbon and water use efficiency of the Loess Plateau, this study investigates the spatial and temporal rates of change in CUE, WUE, and meteorological… Show more

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Cited by 6 publications
(3 citation statements)
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“…The results show that GDP per capita does not have a significant and small coefficient on forest carbon sink efficiency in the nationwide regression; however, the regressions for the four regions show completely different conclusions: The change of GDP per capita in the eastern and northeastern regions had a positive impact on the efficiency of forest carbon sinks, indicating that the forestry development level in these two regions is at a high level, which has a positive radiation and driving effect on forest carbon sinks and is conducive to improving the efficiency of forest carbon sinks; the economic development level in the central and western regions shows a significant negative correlation to forest carbon sinks, revealing that the development level of the forestry industry in this region is not high and that forestry production is still dominated by crude management, which is facing a severe test in forest carbon sinks. This is consistent with the findings of Zhang H. et al [32] regarding the large disparity in the impact of GDP per capita on carbon sinks across Chinese counties. In addition, for every 1% increase in urbanization level, the efficiency of forest carbon sinks will increase by about 0.12%.…”
Section: Results and Analysissupporting
confidence: 93%
“…The results show that GDP per capita does not have a significant and small coefficient on forest carbon sink efficiency in the nationwide regression; however, the regressions for the four regions show completely different conclusions: The change of GDP per capita in the eastern and northeastern regions had a positive impact on the efficiency of forest carbon sinks, indicating that the forestry development level in these two regions is at a high level, which has a positive radiation and driving effect on forest carbon sinks and is conducive to improving the efficiency of forest carbon sinks; the economic development level in the central and western regions shows a significant negative correlation to forest carbon sinks, revealing that the development level of the forestry industry in this region is not high and that forestry production is still dominated by crude management, which is facing a severe test in forest carbon sinks. This is consistent with the findings of Zhang H. et al [32] regarding the large disparity in the impact of GDP per capita on carbon sinks across Chinese counties. In addition, for every 1% increase in urbanization level, the efficiency of forest carbon sinks will increase by about 0.12%.…”
Section: Results and Analysissupporting
confidence: 93%
“…This has led to environmental stresses such as drought and high temperatures, which have intensified plant respiration and may lead to a decrease in CUE [62,63]. However, plants have adapted to these stresses by adjusting stomatal conductance, optimizing water use strategies, and altering leaf structure and chlorophyll content, thereby enhancing WUE and LUE [64,65]. Furthermore, a series of ecological restoration projects have been implemented in southwestern China over the past 20 years, such as Grain for Green and Natural Forests Protection [33].…”
Section: Interaction Of Driving Factors For Com Divergencementioning
confidence: 99%
“…Combining partial correlation coefficients and significance test formulas, this paper calculates the correlation between CUE and temperature/precipitation at the pixel scale based on the monthly datasets from 2001 to 2021, aiming to explore the relationship between CUE variation and temperature/precipitation [44]. Investigating the correlation at the pixel scale can better control unrelated variables and reduce the noise generated by extreme or abrupt temperature, precipitation, and CUE values.…”
Section: Variation Of Cue With Temperature and Precipitationmentioning
confidence: 99%