Net ecosystem productivity (NEP) is a key indicator to describe terrestrial ecosystem functions and carbon sinks. The CASA model was improved by optimizing the parameters optimum temperature and maximum light use efficiency ( $\varepsilon_{max}$ ), and the NEP value of the European terrestrial ecosystem was calculated by combining the soil respiration model. The results showed that when using vegetation classification data to optimize parameter $\varepsilon_{max}$ , the R2 of NEP between estimates and observations increased from 0.252 to 0.403, and the RMSE decreased from 84.557 gC·m ^-2 ·month ^-1 to 64.466 gC·m ^-2 ·month ^-1 . After further optimizing the optimum temperature, R2 increased to 0.428, and the RMSE decreased to 63.720 gC·m ^-2 ·month ^-1 . It indicated that the CASA model could be improved by optimizing $\varepsilon_{max}$ as well as optimum temperature, which was a good approach to improve the NEP estimations. Based on this, the NEP spatiotemporal changes in various regions of Europe were analyzed using the optimization results. The NEP values of European terrestrial ecosystem has regional differences, showing a pattern of western region > southern region > central region > eastern region > northern region. The monthly change of NEP in each region is a single peak curve with high in summer and low in winter, and the annual overall value is positive (i.e., it shows a carbon sink). The research can enable us to obtain the carbon source/sink distribution information in Europe more accurately and provide a scientific reference for carbon balance policy formulation in the region.

Net ecosystem productivity (NEP) is a critical indicator of the CO2 capture capacity of vegetation ecosystems. Based on the land classification and clumping index (CI) datasets, the key parameters of the CASA model, including fraction of photosynthetic active radiation (FPAR) and maximum light use efficiency ( $\varepsilon_{max}$ ), were optimized. Then, the NEP of China's terrestrial ecosystems was estimated, using the improved CASA coupled with a soil respiration model. Finally, the accuracy of NEP estimation was evaluated by observation data from ChinaFLUX station. The research results indicated the RMSE of the improved NEP estimations decreased from 21.139 to 10.179 (unit: gC⋅m ⁻² ⋅month ⁻¹ , and the R ² value increased from 0.413 to 0.832, indicating that optimizing the parameters ( $\varepsilon_{max}$ ) and FPAR are both effective methods to improve the model. The spatiotemporal variation of China's NEP was analyzed using the optimized results. The NEP value of China shows a decreasing distribution pattern from southeast to northwest, and the values of different regions are in the order South > North > Qinghai–Tibet > Northwest. The monthly NEP variation in different regions of China is a unimodal curve, reaching the maximum in summer. This study optimized the NEP estimation, which can better characterize the distribution pattern of carbon sinks/sources in China's terrestrial ecosystems and lay a scientific foundation for developing regional carbon neutrality schemes.

The net primary productivity (NPP) of vegetation is an important indicator used to evaluate the quality of terrestrial ecosystems and characterize the carbon balance of ecosystems. In this study, the spatiotemporal distribution and dynamic change in NPP in Africa from 1981 to 2018 were analyzed using the long time series data of NPP. The results of the trend and fluctuation analysis showed that the NPP in the Sahara arid region in northern Africa and the arid region in South Africa exhibited a significant reduction and a high degree of fluctuation; most of the NPP in the tropical rainforests in central Africa and the deciduous broadleaved forests and deciduous needle-leaved forests on the north and south sides of the tropical rainforests increased and showed a low degree of fluctuation; the Congo basin, Gabon, Cameroon, Ghana, Nigeria, Tanzania, and other regions were affected by human activities, while the NPP in these regions exhibited a significant reduction and a high degree of fluctuation. Anomaly analysis showed that the NPP in Africa generally exhibited a slow upward trend during the period from 1981 and 2018. The trend was basically consistent in different seasons, and can be segmented into three phases: (1) a phase of descent from 1981 to 1992, with the NPP below the average value in most years; (2) a phase of steady growth from 1993 to 2000, reaching a peak in 2000; (3) a phase of fluctuations from 2001 to 2018, where the NPP value was above the average value in all years except 2015 and 2016, when the NPP value was low due to abnormally high temperatures and drought. The Mann–Kendall test further showed that the annual and seasonal NPP in Africa exhibited a significant upward trend, and the mutation time points occurred around 1995. The wavelet time series analysis revealed obvious periodic changes in the time series of NPP in Africa. The annual and seasonal NPP showed clear oscillations on time scales of 7, 20, 29, and 55 years. The 55-year period had the strongest signal, and was the first main period. The study can provide a scientific gist for the sustainable development of environmental ecology, agricultural production, and the social economy in Africa.