In this study, we used the SCAPE method17 to derive the intrinsic temperature sensitivity (Q 10s ), which relied on the high frequency fluctuations of measured time series and represent the short-term response of ecological processes to temperature change. The method reduces or excludes the influences of confounding factors (e.g., seasonal variability and water limitation)1, 17, 32, which should result in robust estimates of Q 10sG and Q 10sR .

GPP principally occurs through the photosynthesis, an endothermal reaction process, which requires distinctive activation energies for different ambient temperatures. More activation energy is required to complete the same reaction at a lower temperature33,34,35. Gillooly et al.20 have shown that Q 10 is positively correlated to activation energy. Therefore, the relationship between the temperature sensitivity of GPP and MAT (Table 1 and Fig. 2a) is attributable to the activation energy required in the different temperature zones.

On the contrary, respiration is a heat-releasing process that mainly depends on the availability of substrate (i.e., carbon sources). Because of the heterogeneity of carbon sources, it is expected that diverse activation energies and turnover times are required for decomposition of the different carbon pools in the ecosystem12, 36. The turnover time ranges from less than 1 yr for labile carbon pool to greater than 106 yr for recalcitrant carbon pool37, 38. As mentioned above, the Q 10sR reflected the temperature response of short-term decomposition of labile carbon pool. The required activation energy for decomposition of the labile carbon pool is considered to be a constant12, 20, 36. As a consequence, the temperature sensitivity of RE (Table 1 and Fig. 2b) was not significantly correlated to temperature, consistent with the result of Mahecha et al.17.

At the ecosystem level, the changes of GPP and RE with temperatures are different2, 39. Within the range of low temperatures in the boreal and temperate regions, GPP increases with temperature faster than RE, which results in an increase of CO 2 uptake under climate warming scenarios40.

The integrated response of an ecosystem may demonstrate the thermal optimality under temperature change and be interpreted as photosynthesis and respiration acclimation to temperature41, 42. The temperature acclimation process, also described as temperature adaption, indicates that with increasing global temperature, plants and microorganisms may generate reversible changes in a way that can optimize their functions under the warmer environment43, 44. Such adaptation mechanism should result in compensative responses of the ecological processes of GPP and RE for a change in temperature45,46,47. The changes of NEP response to temperature can be modulated by the disproportional extent of temperature acclimation of either GPP or RE48. It has been well documented that at the plant level, electron transport capacity and/or heat stability of Rubisco are enhanced with increasing temperature, which result in higher photosynthetic assimilation rates42. Furthermore, the increased CO 2 uptake in warmer temperatures may also be contributed by extended growing seasons, increased nitrogen mineralization and root growth29, 49. Respiration generally increases with temperature, however, water stress and respiratory acclimation can offset or reverse the direct temperature effect50, 51.

Our results showed that ecosystems in the boreal and temperate regions with different PFTs would become carbon sink with climate warming. Evidences have shown that the Earth is becoming greener since 1980s, indicating an increase in GPP52. This increase in GPP is mainly attributable to the rising atmospheric CO 2 level and temperature30, 31, 53. The potential greenhouse effect may further accelerate CO 2 uptake of plants54. In fact, the climate regions and PFTs interactively affect the temperature sensitivities of CO 2 balance processes55, 56. For instance, the needleleaf biome generally distributes in cold climates of the world57. Consequently, the temperature sensitivity results derived from the PFTs are generally consistent with those from the climate groups.

Besides the exponential function model (the Q 10 approach) used in this study, other models, such as linear function6 and convex curve models40, have been applied to characterize GPP changes vs. temperature. It is well documented that GPP is positively correlated to temperature, but very high temperatures should decrease CO 2 assimilation rates58, 59. Therefore, any model to characterize the GPP vs. temperature relationship should be applicable only within the temperature range for normal plant growth. Within the temperature range of this study (MAT: −4.67~16.0 °C), conceptually the exponential function model and the convex curve model should cross at a certain high temperature and the linear function model should be between the exponential function and the convex curve models. These models should cross at least at one point at the reference temperature (GPP 0 ) (Fig. 5). Among the exponential function, linear function, and convex curve models, the exponential function model predicts the lowest GPP value for a given temperature. Thus, the NEP values calculated in this study are more conservative than those calculated using other models. In other words, the conclusion of NEE with “sink” for most of the cases in this study should hold when other models of GPP vs. temperature are applied.

Figure 5 Conceptual models of the gross primary production (GPP) rates vs. temperature. Full size image