ALBERT

Description: As a vast degraded land ecosystem, the karst region of southwest China is currently experiencing serious conflicts between restoration of degraded vegetation communities and agricultural activities. Furthermore, it is not clear what land use pattern suits local farmers best. To evaluate the sustainability of the degraded agricultural ecosystems in the region, methods for emergy analysis were used to compare the ecological and economic benefits from seven typical agroforestry planting patterns in the Yunnan province. The eco-efficiencies of the apple pattern (AP), pear pattern (PP), pomegranate pattern (PRP) were all lower than that of the traditional corn pattern (CP), although the economic benefit was higher than that of CP. Ecological benefits of the apple-soybean pattern (ASP) and the pear-pumpkin pattern (PPP) were not significantly improved, while ecological and economic benefits of the pomegranate-grass-sheep pattern (PGSP) was improved significantly. Intercropping pumpkin in PP increased the economic efficiency by 28.3%, which was superior to that of the intercropping of soybeans (4.6%) in AP. These data implied that interplanting crops in AP and PP might result in higher economic benefit than the existing interplanting pattern. The multistory agroforestry planting pattern and raising in PGSP could optimize the relationship among tree-grass-sheep and improve ecological and economic benefits. Additionally, scenario analysis showed that local farmers might enjoy better ecological and economic benefits at a large scale by optimizing current agricultural production patterns. Our results suggest that together, both the local government and farmers can adjust the structure of agroforestry ecosystems to foster the sustainable development of the ecological industry in the karst region of China.

Description: The influence of oxygen vacancy behaviors during a cooling process in semiconductor gas sensors is discussed by the numerical analysis method based on the gradient-distributed oxygen vacancy model. A diffusion equation is established to describe the behaviors of oxygen vacancies, which follows the effects of diffusion and exclusion in the cooling process. Numerical analysis is introduced to find the accurate solutions of the diffusion equation. The solutions illustrate the oxygen vacancy distribution profiles, which are dependent on the cooling rate as well as the temperature interval of the cooling process. The gas-sensing characteristics of reduced resistance and response are calculated. Both of them, together with oxygen vacancy distribution, show the grain size effects and the re-annealing effect. It is found that the properties of gas sensors can be controlled or adjusted by the designed cooling process. The proposed model provides a possibility for sensor characteristics simulations, which may be beneficial for the design of gas sensors. A quantitative interpretation on the gas-sensing mechanism of semiconductors has been contributed.

Description: The spatial pattern of landscape has great influence on the biodiversity provided by ecosystem. Understanding the impact of landscape pattern dynamics on habitat quality is significant in regional biodiversity conservation, ensuring ecological security guarantee, and maintaining the ecological environmental sustainability. Here, combining CA-Markov and InVEST model, we investigated the evolution of landscape pattern and habitat quality, and presented an explanation for variability of biodiversity linked to landscape pattern in Hubei section of Three Gorges Reservoir Area (TGRA). The spatial-temporal evolution characteristic of landscape pattern from 1990 to 2010 were analyzed by Markov chain. Then, the spatial pattern of habitat quality and its variation in three phases were computed by InVEST model. The driving force for landscape variation was explored by using Logistic regression analysis. Next, the CA-Markov model was used to simulate the future landscape pattern in 2020. Finally, future habitat quality maps were obtained by InVEST model predicted landscape maps. The results concluded that, the overall landscape pattern has changed slightly from 1990 to 2010. Woodland, waters and construction land had the greatest variations in proportion among the landscape types. The area of woodland has been decreasing gradually below the average elevation of 140 m, and the area of waters and construction land increased sharply. Logistics regression results indicated that terrain and climate were the most influencing natural factors compared with human factors. The Kappa coefficient reached 0.92, indicating that CA-Markov model had a good performance in future landscape prediction by adding nighttime light data as restriction factor. The biodiversity has been declining over the past 20 years due to the habitat degradation and landscape pattern variation. Overall, the maximum values of habitat degradation index were 0.1188, 0.1194 and 0.1195 respectively, showing a continuously increasing trend from 1990 to 2010. Main urban areas of Yichang city and its surrounding areas has higher habitat degradation index. The average values of habitat quality index of the whole region were 0.8563, 0.8529 and 0.8515 respectively, showing a continuously decreasing trend. The lower habitat quality index mainly located in the urban land as well as the main and tributary banks of the Yangtze River. Under the business as usual scenario, habitat quality continued to maintain the variation trend of the previous decade, showing a reducing habitat quality index and an increasing area of artificial surface. Under the ecological protection scenario, the variation of habitat quality in this scenario represented reverse trend to the previous decade, exhibiting an increase of habitat quality index and an increasing area of woodland and grassland. Construction of Three Gorges Dam, impoundment of Three Gorges Reservoir (TGR), resettlement of Three Gorges Project and urbanization were the most explanatory driving forces for landscape variation and degradation of habitat quality. The research may be useful for understanding the impact of landscape pattern dynamics on biodiversity, and provide scientific basis for optimizing regional natural environment, as well as effective decision-making support to local government for landscape planning and biodiversity conservation.