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  • 1
    In: Forests, MDPI AG, Vol. 10, No. 8 ( 2019-08-20), p. 708-
    Abstract: Subtropical forests have great potential as carbon sinks; however, the relationship between net ecosystem productivity (NEP) and climate change is still unclear. This study took Zhejiang Province, a subtropical region, as an example. Based on remote sensing classification data of forest resources, the integrated terrestrial ecosystem carbon cycle (InTEC) model was used to simulate the spatiotemporal dynamics of the forest NEP in Zhejiang Province during 1985–2015 and analyze its response to meteorological factors such as temperature, precipitation, relative humidity, and radiation. Three patterns emerged: (1) The optimized InTEC model can better simulate the forest NEP in Zhejiang Province, and the correlation coefficient between the simulated NEP and observed NEP was up to 0.75. (2) From 1985 to 2015, the increase in the total NEP was rapid, with an average annual growth rate of 1.52 Tg·C·yr−1. During 1985–1988, the forests in Zhejiang Province were carbon sources. After 1988, the forests turned into carbon sinks and this continued to increase. During 2000–2015, more than 97% of the forests in Zhejiang Province were carbon sinks. The total NEP reached 32.02 Tg·C·yr−1, and the annual mean NEP increased to 441.91 gC·m−2·yr−1. The carbon sequestration capacity of forests in the east and southwest of Zhejiang Province is higher than that in the northeast of Zhejiang Province. (3) From 2000 to 2015, there was an extremely significant correlation between forest NEP and precipitation, with a correlation coefficient of 0.85. Simultaneously, the forest NEP showed a negative correlation with temperature and radiation, with a correlation coefficient of −0.56 for both, and the forest NEP was slightly negatively correlated with relative humidity. The relative contribution rates of temperature, precipitation, relative humidity, and radiation data to NEP showed that the contribution of precipitation to NEP is the largest, reaching 61%, followed by temperature and radiation at 18% and 17%, respectively. The relative contribution rate of relative humidity is the smallest at only 4%. During the period of 1985–1999, due to significant man-made disturbances, the NEP had a weak correlation with temperature, precipitation, relative humidity, and radiation. The results of this study are important for addressing climate change and illustrating the response mechanism between subtropical forest NEP and climate change.
    Type of Medium: Online Resource
    ISSN: 1999-4907
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2527081-3
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  • 2
    In: Journal of Environmental Management, Elsevier BV, Vol. 248 ( 2019-10), p. 109265-
    Type of Medium: Online Resource
    ISSN: 0301-4797
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2019
    detail.hit.zdb_id: 1469206-5
    SSG: 12
    SSG: 14
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  • 3
    In: Remote Sensing, MDPI AG, Vol. 11, No. 1 ( 2018-12-29), p. 56-
    Abstract: The highly accurate multiresolution leaf area index (LAI) is an important parameter for carbon cycle simulation for bamboo forests at different scales. However, current LAI products have discontinuous resolution with 1 km mostly, that makes it difficult to accurately quantify the spatiotemporal evolution of carbon cycle at different resolutions. Thus, this study used MODIS LAI product (MOD15A2) and MODIS reflectance data (MOD09Q1) of Moso bamboo forest (MBF) from 2015, and it adopted a hierarchical Bayesian network (HBN) algorithm coupled with a dynamic LAI model and the PROSAIL model to obtain high-precision LAI data at multiresolution (i.e., 1000, 500, and 250 m). The results showed the LAIs assimilated using the HBN at the three resolutions corresponded with the actual growth trend of the MBF and correlated significantly with the observed LAI with a determination coefficient (R2) value of 〉 0.80. The highest-precision assimilated LAI was obtained at 1000-m resolution with R2 values of 0.91. The LAI assimilated using the HBN algorithm achieved better accuracy than the MODIS LAI with increases in the R2 value of 2.7 times and decreases in the root mean square error of 87.8%. Therefore, the HBN algorithm applied in this study can effectively obtain highly accurate multiresolution LAI time series data for bamboo forest.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2513863-7
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  • 4
    Online Resource
    Online Resource
    Institute of Electrical and Electronics Engineers (IEEE) ; 2020
    In:  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 13 ( 2020), p. 113-128
    In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Institute of Electrical and Electronics Engineers (IEEE), Vol. 13 ( 2020), p. 113-128
    Type of Medium: Online Resource
    ISSN: 1939-1404 , 2151-1535
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2020
    detail.hit.zdb_id: 2457423-5
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  • 5
    In: Land Degradation & Development, Wiley, Vol. 31, No. 8 ( 2020-05-15), p. 939-958
    Abstract: Properly mapping the sustainability of bamboo forest production plays an important role in providing basic strategies for decision makers to ensure sustainable use of bamboo resources. Understanding the response pattern of drought, poor management, elevation, and barren soil to bamboo forest ecosystem productivity is critical to formulating appropriate improvement strategies of sustainable management of bamboo forest productivity for addressing growing challenges of bamboo forest land degradation. The objectives of this study were to quantify differences in productivity, meteorological, topographical, soil, and bamboo distribution and structure factors under different sustainable management levels of bamboo forest ecosystem productivity in order to support management decision making in a spatiotemporally explicit context. We constructed an innovative three‐layer index system for the sustainable management of bamboo forest productivity by integrating productivity, meteorological, soil, topographic, bamboo distribution, and structure factors to promote sustainable management and spatiotemporal decision making, particularly in bamboo forest areas with low productivity. The partial least squares (PLS) path model was used to analyze the spatiotemporal effects of different factors on bamboo forest productivity and to create sustainable management maps that could be used for spatially informed decision making regarding bamboo forest production. The results showed the spatial and temporal variations in gross primary productivity (GPP), net primary productivity (NPP), and net ecosystem exchange (NEE) in bamboo forests. The sustainable management index was also mapped each year throughout the study area. We divided the index value range into five management‐friendly classes, which were shown to be directly related to GPP, NPP, NEE, Slope, Aspect, soil texture, hydrolytic nitrogen, and Abundance. We found that the areas with relatively high sustainable management levels (I and II) occupied only 18.94% of the bamboo forest area and exhibited a highly clustered distribution. Most of the other areas (78.67%) had relatively low levels of sustainable management (III and IV), and their distribution was rather scattered. The remaining 2.39% of the bamboo forest area that had the lowest sustainable management level (V) was small in area, fragmented, and not conducive to intensive management. The results of the present study can serve as a useful reference for bamboo forest management, which is of great importance for bamboo‐based ecosystems and economies.
    Type of Medium: Online Resource
    ISSN: 1085-3278 , 1099-145X
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2021787-0
    detail.hit.zdb_id: 1319202-4
    SSG: 14
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