| Autor: |
Nigenare Amantai, Yuanyuan Meng, Shanshan Song, Zihui Li, Bowen Hou, Zhiyao Tang |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Remote Sensing, Vol 15, Iss 13, p 3380 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2072-4292 |
| DOI: |
10.3390/rs15133380 |
| Popis: |
Investigating how the productivity dynamics of planted forests vary over time is important for understanding the resilience of forests against disturbance and for maximizing ecological restoration and replanting efforts. In this study, the patterns of interannual variability in net primary production (NPP) were analyzed for planted forests as indicated by the inverse of the coefficient of variation (ICV) time series at a ten-year moving window on the Loess Plateau, China, from 2000 to 2021. The spatial–temporal patterns were defined based on the increase or decrease trend obtained using the ordinary least squares method between abrupt change points performed by a Mann–Kendall test in an ICV time series, as follows: only one linear trend, increase (LI), and decrease (LD); at least two trends, increase firstly and decrease lastly (ID) and decrease firstly and increase lastly (DI); and other trends. The results showed that 82.74% of the ICV on the Loess Plateau displayed LD and ID patterns, indicating an increasing variability of forest productivity in this region. Overall, 73.83% of the ICV had a lower degree of rate decrease in the last phase than during the initial increase. Thus, the variability was in an early stage of increasing degree. The ICV time series showed an LI pattern in the eastern Gansu and the southern Shanxi, indicating a decreased variability, due partly to the improved forest restoration. When the plantation age was considered, the newly planted forests (less than 19 a) exhibited a decreasing variability, indicating the proactive role of forest management and restoration in averting environmental disruptions in dry environments. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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