Mapping forest stand age in China using remotely sensed forest height and observation data

Abstract

Forest stand age plays a crucial role in determining the terrestrial carbon source or sink strength and reflects major disturbance information. Forests in China have changed drastically in recent decades, but quantification of spatially explicit forest age at national level has been lacking to date. This study generated a national map of forest age at 1 km spatial resolution using the remotely sensed forest height and forest type data in 2005, as well as relationships between age and height retrieved from field observations. These relationships include biomass as an intermediate parameter for major forest types in different regions of China. Biomass-height and age-biomass relationships were well fitted using field observations, with respective R 2 values greater than 0.60 and 0.71 (P < 0.01), indicating the viability of age-height relationships developed for age estimation in China. The resulting map was evaluated by comparison with national, provincial, and county forest inventories. The validation had high regional (R 2 = 0.87, 2-8 years errors in six regions), provincial (R 2 = 0.53, errors less than 10 years and consistent age structure in most provinces), and plot (R 2 values of 0.16À0.32, P < 0.01) agreement between map values and inventory-based estimates. This confirms the reliability and applicability of the age-height approach demonstrated in this study for quantifying forest age over large regions. The map reveals a large spatial heterogeneity of forest age in China: old in southwestern, northwestern, and northeastern areas, and young in southern and eastern regions.

Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: A perspective from long‐term data assimilation

“…Regarding the pattern of these key processes, f auto first decreased and then increased as temperature increased at the turning point of approximately 11°C, which was highly congruent with the synthetic analysis based on the global forest database and could be ascribed to the asymmetric response of RE and GPP to rising temperature (Piao et al., ). The decrease in f woo with increasing latitude and decreasing temperature was supported by the inventory‐based synthesis in Chinese forests (Li, Zhou, & He, ), and this pattern may be explained by the adaptive strategies of forest trees to temperature (Reich et al., ) as well as the age‐structure‐related strategy (Zhou, Shi, et al., ), which tends to allocate less C to the structural pool in old forests mainly distributed in cold, high‐latitude regions in China (Zhang et al., ). θ woo and θ som both increased with rising temperature, which agrees well with the variation in the plant mortality rate based on forest inventory (Mantgem et al., ; Zhou, Peng, et al., ) and the variation in soil C decomposition based on Rs observations from the chamber or isotope method (Chen, Huang, Zou, & Shi, ; Frank, Pontes, & McFarlane, ; Karhu et al., ).…”

Mapping spatial distribution of forest age in China

“…Repeated historical human disturbances and recent national afforestation campaigns are the main reasons for China's relatively young forests. Similar to a previous study [ Zhang et al , ], the young forests are mainly found in south China and peripheral regions of large mountains in northeast China (Figure a), in accordance with regions of heavy national afforestation campaigns since the end of 1970s. Recent statistics [ State Forestry Administration of the People's Republic of China's , ] suggest that 42% of the total planted forests are distributed in six southern provinces (Guangxi, Guangdong, Hunan, Sichuan, Yunnan, and Fujian).…”

“…The large variation of the optimized parameters indicates large distinctions of age-height relationships among different forest types, even for some types whose dominant species belong to the same genus (e.g., Pinus tabulaeformis and Pinus massoniana), which indicates that it could be a large source of uncertainties to assume similar growth parameters for closely related species or forest types [e.g., Yin et al, 2015;Zhang et al, 2014]. Furthermore, our results also highlight the significant influence of environment factors on ageheight relationship, which was usually ignored in previous tree growth equations [Wang et al, 2007;Dai et al, 2011;Zhang et al, 2014].…”

Forest drought resistance distinguished by canopy height

“…This dataset was downloaded from http://landscape.jpl.nasa.gov. It provided estimated canopy height values across the land surface, and had good correlation with the tree height observed in the field at both global and regional scales (Simard et al 2011, Zhang et al 2014.…”