Northeast China is a major grain production area, an ecological important forest area, and the largest old industrial base which is now suffering from economic growth slowdown and brain drain. Accurate and long-term dynamic land cover maps are highly demanded for many regional applications. In this study, we developed a set of continuous annual land cover mapping product at 30 m resolution using multi-temporal Landsat images. The maps in year 2000 and 2015 were tested using another independent validation dataset and the overall accuracies were 80.69% and 88.38%, respectively. The accuracies of the maps were improved by the integration of multi-temporal Landsat images and post-classification strategies. We found a general trend that the total area of land that experienced a change in land cover each year increased over time. The area change of each land cover type is also detected. The area of forests was $3.92\times {10}^5$ km ${}^2$ in 1986, fluctuated under fire disturbance, but declined in a quite high rate over the period of 1989 to 2006, and finally stayed relatively stable in area around $3.58\times {10}^5$ km ${}^2$ . The expansion of croplands was the leading land cover change from 1986 to 2000, and then the total area of croplands slightly declined under the Grain to Green Project of China, while shrublands, grasslands and wetlands began to increase. The area of impervious surfaces increased by more than 502% during the last three decades, and about 73% of the new built-up area was converted from croplands. We also demonstrated the our maps could capture the important land cover conversion processes, such as urbanization, forest logging activities, and agricultural expansion.

In this study, the potential climate change impacts on rice growth and rice yield under 1.5 and 2.0 °C warming scenarios, respectively, are simulated using the Ceres-Rice Model based on high-quality, agricultural, experimental, meteorological and soil data, and the incorporation of future climate data generated by four Global Climate Models (GCMs) in the Pearl River Delta, China. The climatic data is extracted from four Global Climate Models (GCMs) namely: The Community Atmosphere Model 4 (CAM4), The European Centre for Medium-Range Weather Forecasts-Hamburg 6 (ECHAM6), Model for Interdisciplinary Research On Climate 5 (MIROC5) and the Norwegian Earth System Model 1 (NorESM1). The modeling results show that climate change has major negative impacts on both rice growth and rice yields at all study sites. More specifically, the average of flowering durations decreases by 2.8 days (3.9 days), and the maturity date decreases by 11.0 days (14.7 days) under the 1.5 °C and (2.0 °C) warming scenarios, respectively. The yield for early mature rice and late mature rice are reduced by 292.5 kg/ha (558.9 kg/ha) and 151.8 kg/ha (380.0 kg/ha) under the 1.5 °C (2.0 °C) warming scenarios, respectively. Adjusting the planting dates of eight days later and 15 days earlier for early mature rice and late mature rice are simulated to be adaptively effective, respectively. The simulated optimum fertilizer amount is about 240 kg/ha, with different industrial fertilizer and organic matter being applied.

Biodiversity conservation is the cornerstone for sustainable development. Bold conservation targets provide the last opportunities to halt the human-driven mass extinction. Recently, bold conservation targets have been proposed to protect 30% or 50% of Earth. However, little is known about its potential impacts on cropland. We identify potential cropland losses when 30% and 50% of global terrestrial area is given back to nature by 2030/2050, at three spatial scales (global, biome and country) and using two approaches (“nature-only landscapes” and “shared landscapes”). We find that different targets, applied scales and approaches will lead to different cropland losses: (1) At the global scale, it is possible to protect 50% of the Earth while having minimum cropland losses. (2) At biome scale, 0.64% and 8.54% cropland will be lost globally in 2030 and 2050 under the nature-only approach while by contrast, the shared approach substantially reduces the number of countries confronted by cropland losses, demanding only 0% and 2.59% of global cropland losses in 2030 and 2050. (3) At the national scale, the nature-only approach causes losses of 3.58% and 10.73% of global cropland in 2030 and 2050, while the shared approach requires 0.77% and 7.55% cropland in 2030 and 2050. Our results indicate that bold conservation targets could be considered, especially when adopting the shared approach, and we suggest adopting ambitious targets (protecting at least 30% by 2030) at the UN Biodiversity Conference (COP 15) to ensure a sustainable future for Earth.