Arrangement Plan of Inner Mongolia Buddhist Temple

Since BC, the construction of cities has been started in the Mongolian Plateau with the establishment of dynasties, but many were turned into ruins. However, the Tibetan Buddhist temples built after the 16th century, which are an indispensable element in the process of settling the Mongolians from nomadic life, have been relatively well preserved in Inner Mongolia. These temples have been thought to be the epitome of the Mongolian economy, culture, art, and construction technology. Therefore, it has a great significance to research them systematically. Interestingly, these temples in Mongolia were originated from Inner Mongolia, which is located on the south side of Mongolia. The architectural design of these temples has been primarily influenced by Chinese and Tibetan temple architecture, suggesting that the temples appear to be considered a vital sample for studying temple architecture in Mongolia or East Asia. So far, there is still no study systematically on temple architecture in Inner Mongolia. Therefore, this research aims to study the arrangement plan of Inner Mongolian Tibetan Buddhist temples, which is the most important factor to consider in the first stage of temple construction.

Spatial and Temporal Variation of Droughts in the Mongolian Plateau during 1959–2018 Based on the Gridded Self-Calibrating Palmer Drought Severity Index

Drought monitoring is challenging, but it is required for improving agricultural production, protecting the ecological environment, and reducing economic losses in drought-prone regions such as the Mongolian Plateau (MP). This study is a systematic analysis of the spatiotemporal changes in the characteristics of drought events (drought duration, severity, intensity, frequency, peak, and starting season) at the sub-regional scale between 1959 and 2018 based on the run theory and using the gridded self-calibrating Palmer Drought Severity Index (scPDSI) dataset. Principal component analysis and Varimax rotation and the Mann–Kendall trend and Sen’s slope were used for the sub-regional division and drought trend analysis, respectively. In addition, wavelet analysis was employed to analyze drought periodicity and determine the influence of large-scale climate indices on regional drought variation. The study results indicate clear differences in the spatial patterns of drought characteristics in the MP. The northern part suffered from droughts with longer duration and higher severity, whereas more drought events with shorter duration and less severity occurred in the southern part. Most of the MP experienced a relatively wet trend in 1996–2018 compared to the period of 1959–1995. The frequency of spring drought events showed an increasing trend in 1996–2018, unlike in 1959–1995. Some drought events simultaneously affected two or several sub-regions. The wavelet analysis results indicated that the drought periodicity in the MP was 10–64 months. The Arctic Oscillation (Pacific Decadal Oscillation) was significantly correlated with drought in the southern (northern) part.

Model Selection for Ecosystem Respiration Needs to Be Site Specific: Lessons from Grasslands on the Mongolian Plateau

Selecting an appropriate model for simulating ecosystem respiration is critical in modeling the carbon cycle of terrestrial ecosystems due to their magnitude and high variations in time and space. There is no consensus on the ideal model for estimating ecosystem respiration in different ecosystems. We evaluated the performances of six respiration models, including Arrhenius, logistic, Gamma, Martin, Concilio, and time series model, against measured ecosystem respiration during 2014–2018 in four grassland ecosystems on the Mongolian Plateau: shrubland, dry steppe, temperate steppe, and meadow ecosystems. Ecosystem respiration increased exponentially with soil temperature within an apparent threshold of ~19.62 °C at shrubland, ~16.05 °C at dry steppe, ~16.92 °C at temperate steppe, and ~15.03 °C at meadow. The six models explained approximately 50–80% of the variabilities of ecosystem respiration during the study period. Both soil temperature and soil moisture played considerable roles in simulating ecosystem respiration with R square, ranging from 0.5 to 0.8. The Martin model performed better than the other models, with a relatively high R square, i.e., R2 = 0.68 at shrubland, R2 = 0.57 at dry steppe, R2 = 0.74 at temperate steppe, and R2 = 0.81 at meadow. These models achieved good performance for around 50–80% of the simulations. No single model performs best for all four grassland types, while each model appears suitable for at least one type of ecosystem. Models that oil moisture include models, especially the Martin model, are more suitable for the accurate prediction of ecosystem respiration than Ts-only models for the four grassland ecosystems.

Dynamics of Vegetation Net Primary Productivity and Its Response to Drought in the Mongolian Plateau

Vegetation net primary productivity (NPP) is an important aspect of the global carbon cycle, and its change is closely related to climate change. This study analyzed the spatial-temporal variation of the standardized precipitation evapotranspiration index (SPEI) and NPP in the Mongolian Plateau, and investigated the effect of drought on NPP. To this end, NPP was simulated using the Carnegie-Ames-Stanford Approach (CASA) model. The results showed that from 1982 to 2014, NPP exhibited an upward trend in different seasons, and a significant increasing trend in most areas in the growing season and spring. The degree of drought also showed an increasing trend in each season. Moreover, the decrease in NPP and SPEI in Mongolia was larger than that in Inner Mongolia. Vegetation showed a positive correlation with SPEI in the growing season and summer, but a negative correlation in the other seasons. Moreover, the impact of drought on vegetation in the growing season showed a lag effect, whereas the lag response was inconspicuous during the early stages of the growing season. Different vegetation NPP responded strongly to the SPEI of the current month and the previous month.