Aliphatic des-A-triterpenoids have been tentatively assigned in samples taken from a 260 cm thick peat sequence from the Dajiuhu Basin of southern China using gas chromatography–mass spectrometry (GC–MS). The compounds, possessing the carbon skeletons of oleanane, ursane or lupane, are generally considered as the microbial degradation products of plant triterpenoids under anoxic conditions. Abundant aliphatic des-A-triterpenoids were observed only in peat samples during the transitional period from the last glaciation to the early Holocene (9.5–11.6 cal 14C ka BP). Among these, des-A-lupane is the only saturated ring A-degraded compound, whilst mono- and di-unsaturated des-A-triterpenes are dominated by oleanane and ursane derivatives. The mono- and di-unsaturated des-A-triterpenes show a strong correlation (R2 0.94) in abundance, indicating that they may be derived from the same source or process. Des-A-lupane shows no correlation in abundance with the mono- or di-unsaturated des-A-triterpenes (R2 < 0.25) and may be derived from a different source or process in the catchment. The period with abundant aliphatic des-A-triterpenoids corresponds to the interval with relatively high sedimentation rate (> 0.3 mm per year). These data indicate that the abundance of aliphatic des-A-triterpenoids in the Dajiuhu peat deposit in the early Holocene may result from the prevailing reducing conditions in the water table or surficial sediment and/or rapid preservation of the early diagenetic products. Our study highlights the potential application of des-A-triterpenes in the reconstruction of palaeoenvironments based on peat sequences. 相似文献
Accurate simulation of rice yield is very important and vital for agriculture and food security. This study has analyzed the applicability of the RS-P-YEC (the remote-sensing-photosynthesis-yield estimation for crops) model for the rice yield simulation of the Middle and Lower Reaches of Yangtze River (MLRYR) in China. The simulated rice yield was compared with the actual statistical dataset, so as to obtain the accuracy of the model results. The results showed that the correlation coefficients (R) between simulated rice yield and statistical data is 0.708 (P < 0.01), the average relative errors were 9, 6.5, 7.2 %, and the root mean square errors were 777.5, 606.4, 693.4 kg/ha in 2007, 2008 and 2009, respectively. It indicated that the RS-P-YEC model can be used to estimate rice yield in the MLRYR region of China. 相似文献
Global increases in duration and prevalence of droughts require detailed drought characterization at various spatial and temporal scales. In this study, drought severity in Xinjiang, China was investigated between 1961 and 2012. Using meteorological data from 55 weather stations, the UNEP (1993) index (IA), Erinç’s aridity index (Im), and Sahin’s aridity index (Ish) were calculated at the monthly and annual timescales and compared to the Penman-Monteith based standard precipitation evapotranspiration index (SPEIPM). Drought spatiotemporal variability was analyzed for north (NX), south (SX), and entire Xinjiang (EX). Im could not be calculated at 51 stations in winter as Tmax was below 0. At the monthly timescale, IA, Im, and Ish correlated poorly to SPEIPM because of seasonality and temporal variability, but annual IA, Im, and Ish correlated well with SPEIPM. Annual IA, Im, and Ish showed strong spatial variability. The 15 extreme droughts denoted by monthly SPEIPM occurred in NX but out of phase in SX. Annual precipitation, maximum temperature, and relative and specific humidity increased, while air pressure and potential evapotranspiration decreased over 1961–2012. The resulting increases in the four drought indices indicated that drought severity in Xinjiang decreased, because the local climate became warmer and wetter.
Cellular automata (CA) have been widely used to simulate complex urban development processes. Previous studies indicated that vector-based cellular automata (VCA) could be applied to simulate urban land-use changes at a realistic land parcel level. Because of the complexity of VCA, these studies were conducted at small scales or did not adequately consider the highly fragmented processes of urban development. This study aims to build an effective framework called dynamic land parcel subdivision (DLPS)-VCA to accurately simulate urban land-use change processes at the land parcel level. We introduce this model in urban land-use change simulations to reasonably divide land parcels and introduce a random forest algorithm (RFA) model to explore the transition rules of urban land-use changes. Finally, we simulate the land-use changes in Shenzhen between 2009 and 2014 via the proposed DLPS-VCA model. Compared to the advanced Patch-CA and RFA-VCA models, the DLPS-VCA model achieves the highest simulation accuracy (Figure-of-Merit = 0.232), which is 32.57% and 18.97% higher respectively, and is most similar to the actual land-use scenario (similarity = 94.73%) at the pattern level. These results indicate that the DLPS-VCA model can both accurately split the land during urban land-use changes and significantly simulate urban expansion and urban land-use changes at a fine scale. Furthermore, the land-use change rules that are based on DPLS-VCA mining and the simulation results of several future urban development scenarios can act as guides for future urban planning policy formulation. 相似文献
