Crop production on the Chinese Loess Plateau under 1.5 and 2.0 °C global warming scenarios.

Global warming is a crucial factor affecting crop production in ecologically vulnerable areas. Warming-induced changes in the yields of different crops could pose significant challenges to food security and sustainability assessment. In this study, the World Food Studies model and a remote sensing product assimilation algorithm were used to develop a spatially explicit crop assimilation model applicable to the Loess Plateau of China. The model was used to simulate potential changes in actual yields and yield gaps for winter wheat and maize under three typical climate scenarios (Representative Concentration Pathways (RCPs): RCP 2.6, RCP 4.5, and RCP 8.5) from 2016 to 2060. Average yields increased in both winter wheat (2.38 %-4.96 %) and maize (5.41 %-6.85 %), with maize (RCP 4.5 > RCP 8.5 > RCP 2.6) more adapted to climate warming than winter wheat (RCP 2.6 > RCP 8.5 > RCP 4.5) in terms of yield increase rate. The yield increase and yield gap for winter wheat decreased most significantly in RCP2.6 (-2.28 %). Maize yield did not exceed 80 % of the potential yield in any scenario. The average phenological periods for winter wheat and maize are predicted be 2-4 and 9-16 days earlier, respectively. Crop yields were negatively correlated with radiation and yield gaps were positively correlated with precipitation. Future climate change will likely cause dramatic interannual crop yield fluctuations. Winter wheat is predicted to experience yield stagnation after 2050, whereas maize production potential will increase briefly before experiencing a long-term decline in growth. The results of this multi-scenario simulation assessment of crop production provide scientific support for implementing climate-adapted crop management strategies and integrated dry-crop-irrigated agriculture to meet food security objectives in this ecologically fragile area. We recommend integrated management measures to ensure regional food security through crop variety improvement, irrigation regulation, and planting structure optimization.

Habitat quality assessment provides indicators for socio-ecological management: a case study of the Chinese Loess Plateau.

The impact of changing land use and land cover (LULC) on regional habitat quality have attracted extensive attention. The Loess Plateau is an ecologically fragile area; LULC changes in this region have complex impacts on habitat quality at multiple spatiotemporal scales. This study developed an integrated assessment method based on multi-source data to assess habitat quality changes in the Loess Plateau during recent years (2000-2015) and in the future (2015-2050) under four typical scenarios. A significant increase in urban land use was observed on the Loess Plateau from 2000 to 2050, which resulted in a continuous decrease in the cropland area. The area of forest and grassland landscapes was also reduced by both urban and cropland expansion, with the most significant loss in the grasslands. A future overall decreasing trend in overall habitat quality is predicted, but the SSP1-2.6 scenario is significantly better than the SSP5-8.5 scenario. Urban expansion contributes a rapidly increasing proportion of habitat quality decline on the Loess Plateau; urban land will become the most significant threat to regional habitat quality by 2030. Policies for socio-ecological protection with clear, high-level objectives can effectively promote habitat quality. It is recommended that national nature reserves be delineated and ecological functions in the study area be continuously monitored. This research provides a potential socio-ecological baseline and implementation strategy for the habitat conservation-oriented management of large and fragile ecological regions.

Integrating the SD-CLUE-S and InVEST models into assessment of oasis carbon storage in northwestern China.

Spatio-temporal integrated assessment of land-use change impacts on carbon storage services is a new and important research field in land science and landscape ecology. The objective of this paper is to use an integrated SD-CLUE-S and InVEST model to simulate and predict land-use changes impacts during 2000-2018 on carbon storage at pixel and regional scales in the Zhangye oasis, Northwest China. The SD-CLUE-S model was used to simulate land-use change, and three land-use scenarios (current trend, moderate protection, and strict protection) were defined in collaboration with oasis socioeconomic development and ecological environment conservation by local government. The InVEST model was then used to simulate land-use change impacts on carbon storage at different scales in the oasis. The results showed that: (1) the effects of built-up land expansion were especially notable, with a rapid decrease in cropland during 2009-2018; (2) the strict protection scenario saved the largest amount of carbon storage for the oasis compared with the current trend and moderate protection scenarios. The scientific value of this study has been to show that the proposed modeling method can be used to reflect different land-use patterns and their effects on ecosystem services at multiple scales in the oasis. Furthermore, this research can be used to help government managers encourage stakeholders to contribute funds and strategies to maintain oasis landscape patterns and ecological processes by implementing local plans for potential conservation projects.