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Additional file 2. The structural model of forest growth and carbon simulation from TRIPLEX1.0 (modified from Peng et al., 2002). Rectangles represent key pools or state variables, ovals represent core simulation processes, dotted lines represent controls, and solid lines represent the flow of carbon (C), nitrogen (N), water, and the fluxes between the forest ecosystem and external environment. Two arrow cycles refer to two feed-backs.

Additional file 5. Stand growth and tree species-specific parameters TRIPLEX1.6 applied to simulate growth of evergreen broad-leaved forest, deciduous and evergreen broad-leaved mixed forest, deciduous broad-leaved forest, and coniferous and broad-leaved mixed forest.

Additional file 4. Site-specific parameters used in TRIPLEX1.6 for simulating subtropical forest ecosystems in Hunan Province, subtropical China (Zhao et al., 2013).

Additional file 3. Compatibility superposition relative growth equation (lnWi = ßi0 + ßi1 × lnD ) regression coefficients of biomass ( Wi, kg) and DBH (D, cm) for each part of the tree species (values in parentheses is standard error) and fitting parameters.

Additional file 7. Descriptive statistics for spatial heterogeneity of climate and forest stand structure in all selected permanent forest sample plots in Hunan Province. Site variable: elevation (above mean sea level, m); climatic variables: annual average air temperature (°C), annual rainfall (mm yr-1) and the annual average vapor pressure deficit (mbar) between 2000 and 2014.

Additional file 1. Age group classification standard of subtropical natural secondary forests in Hunan Province.

Additional file 10. Variation of monthly average temperature and precipitation in Hunan Province from 2000 to 2014.

Additional file 6. Descriptive statistics for the spatial heterogeneity of stand growth by forests in all selected permanent forest plots in Hunan Province in 2014. Including stand-structure variables: stem density (stems ha-1), stand age (year), diameter at breast height (DBH, cm), height (m), NPP (t ha-1 yr-1) and stand biomass (t ha-1).

Additional file 9. Variation of monthly average temperature and precipitation in Hunan Province from 2000 to 2014.

Stem respiration is an important part of the annual carbon balance of forest ecosystems and consumes ca. 11%-33% of total net daytime carbon assimilation. Because of difficulties in measurement, little attention was paid to stem respiration studies in the past. However, with increasing atmospheric CO2 concentration, studies of stem respiration have become popular. Several methods were applied in earlier studies, including gas exchange measurements and closed method. An open flow system is employed in recent studies. Results from recent research show that the diurnal pattern of stem respiration is bimodal with a midday depression and that rates are the greatest in the growing season. Controlling factors include meteorological factors (e.g., stem temperature, CO2 concentration and humidity) and biological factors (tree species, tree age, diameter at breast height, sapwood size and nitrogen content in stem). Latitude, altitude and topographic factors indirectly influence respiration rates through meteorological or biological factors, in particular stem temperature. Stem respiration rate is positively correlated with stem temperature. The mechanism of stem respiration and its controlling factors will continue to be subjects of future research. Integration of meteorological and biological factors into models of stem respiration will provide insight into contribution of stem respiration to the carbon balance of forest ecosystems, role of forest ecosystems in reducing CO2 concentration elevation in the atmosphere, response of forest ecosystems to global changes, and development of carbon cycle models of forest ecosystems. These issues and measurement techniques remain challenging and fruitful areas for future research.