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Net Primary Productivity (NPP) is one of the significant indicators to measure environmental changes; thus, the relevant study of NPP in Northeast China, Asia, is essential to climate changes and ecological sustainable development. Based on the Global Production Efficiency (GLO-PEM) model, this study firstly estimated the NPP in Northeast China, from 2001 to 2019, and then analyzed its spatio-temporal evolution, future changing trend and phenology regularity. Over the years, the NPP of different forests type in Northeast China showed a gradual increasing trend. Compared with other different time stages, the high-value NPP (700–1300 gC·m−2·a−1) in Changbai Mountain, from 2017 to 2019, is more widely distributed. For instance, the NPP has an increasing rate of 6.92% compared to the stage of 2011–2015. Additionally, there was a significant advance at the start of the vegetation growth season (SOS), and a lag at the end of the vegetation growth season (EOS), from 2001 to 2019. Thus, the whole growth period of forests in Northeast China became prolonged with the change of phenology. Moreover, analysis on the sustainability of NPP in the future indicates that the reverse direction feature of NPP change will be slightly stronger than the co-directional feature, meaning that about 30.68% of the study area will switch from improvement to degradation. To conclude, these above studies could provide an important reference for the sustainable development of forests in Northeast China.

In arid regions, land development and degradation (LDD) is sustained by the undesirable land development, human production and living, and climate change. Therefore, the understanding of LDD processes and their driving mechanism in the arid or semi-arid regions is significant to guarantee the sustainable development of ecological environment. This study explored the critical LDD processes in the Heihe River Basin (HRB) during 1990-2010 with the spatio-temporal evaluation of critical land use dynamics and its land quality changing trends. Then, the driving mechanism of cultivated land development process, grassland degradation process and water resource change process were analyzed by a simultaneous equations model which took the interaction of three processes into account. The results showed that the mutual transfers of cultivated land were primarily gathered in the middle reaches from 1990 to 2010. Its area grew by 13.5% and the average dynamic degree remained at 0.61%. The transfers between grassland and cultivated land, unused land were more remarkable, which led to the decline of grassland quality and even grassland degradation. Water area maintained a dynamic balance with almost unchanged area, but its dynamic trend was initially increasing and then decreasing. However, the average degradation of land quality in the whole study area is continuously alleviated. These changes were mainly due to the interaction of the LDD processes above, as well as socio-economic and climate change. Among them，agricultural research investments could restrain the unordered expansion of cultivated land resource for a relatively short period of time. Meanwhile, the variable of whether it is the main grain producing county is the main driver of grassland and water resource degradation in this region. These conclusions will provide scientific references for ecological land restoration and land quality improvement in the HRB.

Net primary productivity (NPP) lays the foundation for provision of various ecosystem services, and understanding the impacts of potential influencing factors on NPP is of great significance to formulating appropriate management measures to guarantee the sustainable provision of essential ecosystem services. This study analyzed the impacts of potential influencing factors on NPP in the lower Heihe River Basin, a typical arid and semi-arid region in China. First, NPP was estimated with the C-FIX model, and then the multilevel model was used to analyze the impacts of potential influencing factors on NPP during 2000-2008. Finally decomposition analysis was used to further analyze the contribution of influencing factors to NPP change during 2000-2008. The average NPP increased by approximately 9.07% during 2000-2008, and results of the multilevel model indicate that both the socioeconomic variables and demographic variables are useful in explaining NPP change. In particular, coefficients of rainfall and evapotranspiration which represent the water availability reached 0.0456 and 0.2956, respectively. Results of decomposition analysis suggested that the water availability played an important role in increasing NPP, with a contribution rate of 44.17%, and it is necessary to carry out some policies that can promote the water use efficiency to increase NPP under the background of climate change and intensified human activities. There are some uncertainties in the results of this study, but these results still can provide valuable reference information for the water resource management to increase the ecosystem service supply in the lower Heihe River Basin. (C) 2015 Elsevier Ltd. All rights reserved.

Land Use/Land Cover change (LUCC) is a key aspect of global environmental change, which has a significant impact on climate change. In the background of increasing global warming resulting from greenhouse effect, to understand the impact of land use change on climate change is necessary and meaningful. In this study, we choose China as the study area and explore the possible land use change trends based on the AgLU module and ERB module of global change assessment model (GCAM model and Global Change Assessment Model). We design three scenarios based on socioeconomic development and simulated the corresponding structure change of land use according to the three scenarios with different parameters. Then we simulate the different emission of CO2under different scenarios based on the simulation results of structure change of land use. At last, we choose the most suitable scenario that could control the emission of CO2best and obtain the relatively better land use structure change for adaption of climate change. Through this research we can provide a theoretical basis for the future land use planning to adapt to climate change.

Near surface energy budget changes have been proved to be induced by the land cover conversion through changing the surface physical properties, which can further impact the regional climate change. This study applies the DLS model to simulate the land cover under the business as usual (BAU) scenario and then analyses the seasonal and interannual variation of energy balance in the semiarid grassland area of China based on the simulated land cover with the Weather Research and Forecasting (WRF) model. The results indicate that the grassland will show a growing trend under the BAU scenario. Downward long wave radiation and downward short wave radiation will all have small-scale increase with time going by, while the surface net radiation will decrease from 2030 to 2050. However, there is obvious seasonal variation. Summer has the highest downward long wave radiation and downward short wave radiation, followed by spring and autumn. The lowest are in winter. As for the net surface radiation, there is obvious decrease in southeast of study area due to returning cropland to grassland. Those research conclusions can offer valuable information for the land use planning and relieving the effects of land cover change on climate change at the semiarid grassland area.

Water and heat fluxes of terrestrial ecosystem play an important role in the sustainable development of ecosystem services. In this chapter, we first investigated the spatial variation of heat fluxes and surface temperature in an inland irrigation area of the northern China. Irrigated agriculture has the potential to alter regional to global climate significantly. We investigate how irrigation will affect regional climate in the future in an inland irrigation area of northern China, focusing on its effects on heat fluxes and near-surface temperature. Using the Weather Research and Forecasting (WRF) model, we compare simulations among three land cover scenarios: the control scenario (CON), the irrigation scenario (IRR), and the irrigated cropland expansion scenario (ICE). Our results show that the surface energy budgets and temperature are sensitive to changes in the extent and spatial pattern of irrigated land. Conversion to irrigated agriculture at the contemporary scale leads to an increase in annual mean latent heat fluxes of 12.10 W m−2, a decrease in annual mean sensible heat fluxes of 8.85 W m−2, and a decrease in annual mean temperature of 1.3 °C across the study region. Further expansion of irrigated land increases annual mean latent heat fluxes by 18.08 W m−2, decreases annual mean sensible heat fluxes by 12.31 W m−2, and decreases annual mean temperature by 1.7 °C. Our simulated effects of irrigation show that changes in land use management such as irrigation can be an important component of climate change and need to be considered together with greenhouse forcing in climate change assessments. Then, the spatial variation of surface temperature and precipitation due to grassland conversion to forestry area in southeast China was examined. The land use/land cover change (LUCC) is the synthetic result of natural processes and human activities; it largely depends on the surface vegetation conditions, and the mutual conversion among land cover types can accelerate or alleviate the regional and global climate change. Aiming at analyzing the regional climatic effects of the conversion from grassland to forestland, especially in the long-term perspective, we carried out the comparison simulation using the WRF model in Fujian Province, and results indicated that this conversion had a significant influence on the regional climate; the annual average temperature decreased by 0.11 °C, and the annual average precipitation increased by 46 mm after 11.2 % of the grassland was converted into the forestland in the study area from 2000 to 2008. In the future (from 2010 to 2050), the conversion from grassland to forestland is significant under two representative concentration pathways (RCPs) (RCP6 and RCP8.5); the spatial pattern of this conversion under the two scenarios is simulated by dynamics of land system (DLS); then, the regional climate effects of the conversion are simulated using WRF model. Further, the spatial variation of surface heat fluxes due to land use change across China was estimated. We estimate the heat flux changes caused by the projected land transformation over the next 40 years across China to improve the understanding of the impacts of land dynamics on regional climate. We use the WRF model to investigate these impacts in four representative land transformation zones, where reclamation, overgrazing, afforestation, and urbanization dominate the LUCC in each zone, respectively. As indicated by the significant variance of albedo due to different LUCCs, different surface properties cause great spatial variance of the surface flux. From the simulation results, latent heat flux increases by 2 and 21 W/m2 in the reclamation and afforestation regions, respectively. On the contrary, overgrazing and urban expansion result in decrease of latent heat flux by 5 and 36 W/m2, correspondingly. Urban expansion leads to an average increase of 40 W/m2 of sensible heat flux in the future 40 years, while reclamation, afforestation, and overgrazing result in the decrease of sensible heat flux. Results also show that reclamation and overgrazing lead to net radiation decrease by approximately 4 and 7 W/m2, respectively; however, afforestation and urbanization lead to net radiation increase by 6 and 3 W/m2, respectively. The simulated impacts of projected HLCCs on surface energy fluxes will inform sustainable land management and climate change mitigation. Finally, we summarized the predicted impacts of land use change on surface temperature in the typical areas around the world. This study focuses on the potential impacts of large-scale LUCC on surface temperature from a global perspective. As important types of LUCC, urbanization, deforestation, cultivated land reclamation, and grassland degradation have effects on the climate, the potential changes of the surface temperature caused by these four types of large-scale LUCC from 2010 to 2050 are downscaled, and this issue is analyzed worldwide along with RCPs of the Intergovernmental Panel on Climate Change (IPCC). The first case study presents some evidence of the effects of future urbanization on surface temperature in the Northeast megalopolis of the USA. In order to understand the potential climatological variability caused by future forest deforestation and vulnerability, we chose Brazilian Amazon region as the second case study. The third selected region in India is a typical region of cultivated land reclamation, where the possible climatic impacts are explored. In the fourth case study, we simulate the surface temperature changes caused by future grassland degradation in Mongolia. Results show that the temperature in built-up area would increase obviously throughout the four land types. In addition, the effects of all four large-scale LUCCs on monthly average temperature change would vary from month to month with obviously spatial heterogeneity.

This chapter focuses on the climate effect of ecological restoration programs in China. The fourth assessment report of Intergovernmental Panel on Climate Change (IPCC AR4) indicated that the human activities are a significant influencing factor of climate change. Deforestation, grassland degradation, and desertification, which are mainly induced by human activities, have been greatly intensified due to the irrational exploitation of the natural resources, rapid population growth, and the expansion of road network in the past decades. Some ecological restoration programs have been recently carried out, e.g., Green for Grain Project, which can affect the climate through not only the carbon sink but also the thermal properties of the land surface.