Divergent Responses of NPP to Climate Factors among Forest Types at Interannual and Inter-Monthly Scales: An Empirical Study on Four Typical Forest Types in Subtropical China

Abstract

Identifying the main climatic controls of productivity differences in different forest ecosystems is beneficial for revealing the patterns of carbon cycle changes in terrestrial ecosystems. Moreover, exploring the differences in their productivity responses to temperature and precipitation at interannual and inter-monthly scales is conducive to identifying the mechanisms of carbon cycle changes in forest ecosystems, which can enhance the study of the forest ecosystem carbon cycle. In addition, the effect of climate factor changes on the net primary productivity (NPP) of typical forest types in subtropical areas remains unclear. Here, we simulated the dynamic changes in the NPP of four typical forest types (evergreen needleleaf forest (ENF), evergreen broadleaf forest (EBF), bamboo forest (BF), and evergreen needleleaf–broadleaf mixed forest (ENBMF)) in the Poyang Lake Basin from 1970 to 2021 using the Biome-BGC model where its parameters were adjusted according to the ecophysiological characteristics of forest types in this study. Then, the correlation between the NPP of the four typical forest types and climate factors was examined at interannual and inter-monthly scales; the response of the NPP of four typical forest types to future temperature and precipitation changes was explored. The results revealed that NPP showed a fluctuating downward trend after 2000 in ENF, EBF, and ENBMF. The NPP of the ENF was primarily driven by precipitation at the interannual and inter-monthly levels (p < 0.01). The impact of precipitation and accumulated temperature (AT) on NPP of EBF is not significant interannually; the NPP of BF demonstrated a minor correlation with AT and no significant correlation with precipitation. However, the NPP variation of EBF and BF was significantly affected by the temperature at the inter-monthly scale (p < 0.01), with R2 of 0.85 and 0.92, respectively. At the interannual scale, the NPP of ENBMF was mainly driven by precipitation (p < 0.01); at the inter-monthly scale, it was driven by precipitation (p < 0.01) and AT (p < 0.01), with R2 of 0.74 and 0.62, respectively. Under designed climate scenarios, the precipitation changes will have a greater impact on NPP of ENF; the NPP changes in the EBF, BF, and ENBMF will be mainly controlled by temperature increase, and only a 10% change in precipitation leads to its smaller impact on their NPP changes.