The Impact of Desertification Dynamics on Regional Ecosystem Services: A Case Study of Inner Mongolia (China)

As one of the most important ecosystems of our planet, desert and desertified land have provided critical ecosystem services to support inhabitants of dry lands, and the desertification dynamics would have greatly impact on regional ecosystem services and economical-social development. In this study, the desertification dynamics in Inner Mongolia, China, and its impact on regional ecosystem services were analyzed by combining multisource data, GIS, and sensitivity analysis method. The results showed that the total ecosystem service value (ESV) decreased by 67.16 billion yuan from 1981 to 2010, and desertification dynamics had moderate linear correlation with ESV, which caused 23.7% decrease of ESV. The impacts of desertification dynamics on the change of ESV in different subregions had spatial heterogeneity, which had promoting effects in southwest of Inner Mongolia and reverse effects in northeast subregions. The sensitivity of ESV to desertification dynamics in different subregions also had obvious differences, and subregions with higher vegetation coverage always showed larger SAF (sensitivity coefficient). Different measures, such as reasonably utilizing water and soil resources, adopting water-saving technology, adjusting the industry structure, and developing the ecological industry, should be adopted by the government to control desertification and promote the ecosystem services

Chemical compositions of fog and precipitation at Sejila Mountain in the southeast Tibetan Plateau, China

Chemical compositions of fog and rain water were measured between July 2017 and September 2018 at Sejila Mountain, southeast Tibet, where fog events frequently occurred in original fir forests at altitude 3950 m. Fog water samples were collected using a Caltech Active Strand Cloud Collector (CASCC), and rain samples were collected using a precipitation gauge. Differences were observed between fog water and rain composition for most analyzed ions. Ion abundance in fog water was Ca2+ > Cl− > Na+ > SO42− > Mg2+ > NH4+ >K+ > NO3− whereas an order of Ca2+ > Na+ > Cl− > Mg2+ > SO42− > NO3− > K+ > NH4+ was observed for rain water. All ion concentrations were higher in fog water than in rain water. Additionally, Ca2+ was the dominant cation in both fog and rain samples, accounting for more than half of all measured cations. NH4+ and SO42− concentrations were notable for being higher in fog than rain water when compared with other ions. For trace elements, Al, As, Mn and Se were the most abundant elements in fog water; only Al and As were detected in rain water. Seventy-two hour back-trajectory analysis showed that air masses during fog and/or rain events mainly came from the south of Sejila Mountain. Spearman correlation analysis and source contribution calculations indicated that both marine and terrestrial sources contributed to the observed ion concentrations. Considering the higher concentrations of NH4+ and higher ratio of NH4+/NO3− measured in fog than in rain, we suggest that quantification of fog nitrogen deposition and its ecological effect in this area should be given more attention

Quantitative Assessment of Desertification Using Landsat Data on a Regional Scale – A Case Study in the Ordos Plateau, China

Desertification is a serious threat to the ecological environment and social economy in our world and there is a pressing need to develop a reasonable and reproducible method to assess it at different scales. In this paper, the Ordos Plateau in China was selected as the research region and a quantitative method for desertification assessment was developed by using Landsat MSS and TM/ETM+ data on a regional scale. In this method, NDVI, MSDI and land surface albedo were selected as assessment indicators of desertification to represent land surface conditions from vegetation biomass, landscape pattern and micrometeorology. Based on considering the effects of vegetation type and time of images acquired on assessment indictors, assessing rule sets were built and a decision tree approach was used to assess desertification of Ordos Plateau in 1980, 1990 and 2000. The average overall accuracy of three periods was higher than 90%. The results showed that although some local places of Ordos Plateau experienced an expanding trend of desertification, the trend of desertification of Ordos Plateau was an overall decrease in from 1980 to 2000. By analyzing the causes of desertification processes, it was found that climate change could benefit for the reversion of desertification from 1980 to 1990 at a regional scale and human activities might explain the expansion of desertification in this period; however human conservation activities were the main driving factor that induced the reversion of desertification from 1990 to 2000

Novel ultra-fast pulsed laser sources for bio-imaging applications

This thesis presents new techniques for the development of compact and reliable laser sources using advanced fibre laser technology, aiming to enhance the multiphoton microscopy (MPM) for biomedical imaging applications. Our work explores second-order multiphoton-based imaging systems, including second harmonic generation (SHG), two-photon exited fluorescence (TPEF), and coherent antiStokes Raman scattering (CARS) microscopy. These systems require picosecond (ps) pulsed lasers with specific spectral and tunability characteristics. I demonstrate a compact, continuous wave (CW) seeded, synchronization-free optical parametric amplifier (OPA), bypassing the complex cavity design of optical parametric oscillators (OPOs). The OPA with 175 mW power level, 8 cm−1 spectral resolution, and 2 ps pulse duration is optimized for CARS microscopy, with rapid and precise tuning achieved through the periodically-poled lithium niobate (PPLN) OPA crystal. We also delve into third-order multiphoton imaging and three-photon microscopy (3PM) systems, which offer improved resolution and penetration depth. These systems require ultrafast lase

Artificial Neural Network-Based Microwave Satellite Soil Moisture Reconstruction over the Qinghai–Tibet Plateau, China

Soil moisture is a key parameter for land-atmosphere interaction system; however, fewer existing spatial-temporally continuous and high-quality observation records impose great limitations on the application of soil moisture on long term climate change monitoring and predicting. Therefore, this study selected the Qinghai–Tibet Plateau (QTP) of China as research region, and explored the feasibility of using Artificial Neural Network (ANN) to reconstruct soil moisture product based on AMSR-2/AMSR-E brightness temperature and SMAP satellite data by introducing auxiliary variables, specifically considering the sensitivity of different combination of input variables, number of neurons in hidden layer, sample ratio, and precipitation threshold in model building. The results showed that the ANN model had the highest accuracy when all variables were used as inputs, it had a network containing 12 neurons in a hidden layer, it had a sample ratio 80%-10%-10% (training-validation-testing), and had a precipitation threshold of 8.75 mm, respectively. Furthermore, validation of the reconstructed soil moisture product (named ANN-SM) in other period were conducted by comparing with SMAP (April 2019 to July 2021) for all grid cells and in situ soil moisture sites (August 2010 to March 2015) of QTP, which achieved an ideal accuracy. In general, the proposed method is capable of rebuilding soil moisture products by adopting different satellite data and our soil moisture product is promising for serving the studies of long-term global and regional dynamics in water cycle and climate

Dataset in support of the Southampton doctoral thesis 'Novel ultra-fast pulsed laser sources for bio-imaging applications'

This dataset contains: originally measured and calculated data for plotting figures within the thesis The figures are as follows: Figure 5.3: Spectrum of conventional soliton mode locking output: experimental result (solid red line) and numerical simulation result (dashed black line). Water absorption lines (solid blue line) Figure 5.4: Auto-correlation of the pulse: red points: experimental auto-correlation traces; dashed black line: Sech2 fitting of the auto-correlation Figure 5.10: Tunable coupler coupling ratio Figure 5.11: Tunable coupler wavelength dependence (Scale setting on the ro-tary knob 27 :blue, 28: green, 29 red.) Figure 5.12: Spectrum of conventional soliton mode locking output: experimen-tal result (solid red line) and numerical simulation result (dashed black line). Figure 5.13: Auto-correlation of the pulse: red points: experimental auto-correlation traces; dashed black line: Sech2 fitting of the auto-correlation. Figure 5.14: Mode-locked oscilloscope traces (single-pulse) Figure 5.19: Spectrum of the stretched pulse mode locking output: experimentalresult (solid red line) and numerical simulation result (dashed black line) Figure 5.24: Spectrum of dissipative soliton mode locking output: experimentalresult (solid red line) and numerical simulation result (dashed black line) Figure 5.25: Auto-correlation of direct output pulse Figure 5.27: Auto-correlation of compressed pulse by 6.5 m long SMF. Figure 5.28: Cavity output power curve (Decrease the pump power). Figure 5.29: Cavity output power stability test over 100mins. Inset: Pulsestability in the oscilloscope over 100 mins. Figure 5.30: Spectral stability over 100mins</span

Afforestation Subsidy Determination for <i>Haloxylon ammodendron</i> (C.A.Mey.) Bunge in China Based on Cost–Benefit Analysis

Subsidies are an effective instrument to encourage farmers to engage in afforestation which provides many ecosystem services. A scientific and reasonable subsidy level should reflect the demands of various stakeholders so that the subsidy scheme can be accepted by both farmers and the government. This study aimed to establish a framework for designing an afforestation subsidy to attract voluntary participation in a way that seeks to raise both farmers’ and government’s returns while reducing financial expenditure. The framework determines the optimal subsidy level by integrating direct costs, opportunity costs, and ecological benefits to conduct cost–benefit analysis over the period of afforestation. As a case study, we focus on the planting of Haloxylon ammodendron (C.A.Mey.) Bunge in Alxa, Inner Mongolia. The results show that the subsidy level required to motivate farmers is lower than the subsidy level according to the government’s willingness to pay. Under the optimal subsidy level, the government and farmers can reach a balance point that provides effective incentives for afforestation without requiring unreasonable spending. Additionally, the current subsidy is substantially lower than the recommended subsidy; there is still room for improvement in the subsidy policy. The research framework developed herein can help policy and decision makers to design afforestation subsidy schemes and contribute to ecological restoration in the future