Dynamics and responses of vegetation to climatic variations in Ziya-Daqing basins,China

Examining the direct and indirect effects of climatic factors on vegetation growth is critical to understand the complex linkage between climate change and vegetation dynamics. Based on the Moderate Resolution Imaging Spectroradiometer(MODIS) Normalized Difference Vegetation Index(NDVI) data and meteorological data(temperature and precipitation) from 2001 to 2012, the trend of vegetation dynamics were examined in the Ziya-Daqing basins, China. The path analysis was used to obtain the information on the relationships among climatic factors and their effects on vegetation growth. It was found that the trends of growing season NDVI were insignificant in most plain dry land, while the upward trends were significant in forest, grass and dry land in Taihang Mountains. According to the path analysis, in 23% of the basins the inter-annual NDVI variation was dominated by the direct effect of precipitation, in 5% by the direct effects of precipitation and temperature, and in less than 1% by the direct effect of temperature or indirect effects of these two climatic factors. It indicated that precipitation significantly affected the vegetation growth in the whole basins, and this effect was not regulated by temperature. Precipitation increase(especially in July, August and September) was favorable to greenness enhancement. Summer temperature rising showed negative effect on plant productivity enhancement, but temperature rise in April was beneficial for the vegetation growth. When April temperature increases by 1℃, the onset date of greenness for natural vegetation will be 2 days in advance. There was a lag-time effect of precipitation or temperature on monthly NDVI for all land use types except grass.     

Impact factors identification of spatial heterogeneity of herbaceous plant diversity on five southern islands of Miaodao Archipelago in North China

Herbaceous plants are widely distributed on islands and where they exhibit spatial heterogeneity. Accurately identifying the impact factors that drive spatial heterogeneity can reveal typical island biodiversity patterns. Five southern islands in the Miaodao Archipelago, North China were studied herein. The spatial distribution of herbaceous plant diversity on these islands was analyzed, and the impact factors and their degree of impact on spatial heterogeneity were identified using CCA ordination and ANOVA. The results reveal 114 herbaceous plant species, belonging to 94 genera from 34 families in the 50 plots sampled. The total species numbers on different islands were significantly positively correlated with island area, and the average α diversity was correlated with human activities, while the β diversity among islands was more affected by island area than mutual distances. Spatial heterogeneity within islands indicated that the diversities were generally high in areas with higher altitude, slope, total nitrogen, total carbon, and canopy density, and lower moisture content, pH, total phosphorus, total potassium, and aspect. Among the environmental factors, pH, canopy density, total K, total P, moisture content, altitude, and slope had significant gross effects, but only canopy density exhibited a significant net effect. Terrain affected diversity by restricting plantation, plantation in turn influenced soil properties and the two together affected diversity. Therefore, plantation was ultimately the fundamental driving factor for spatial heterogeneity in herbaceous plant diversity on the five islands.     

The morphological characteristics of gully systems and watersheds in Dry-Hot Valley,SW China

Gully systems and watersheds are geomorphic units with clear boundaries that are relatively independent of basin landscapes and play an important role in natural geography. In order to explore the morphological characteristics of gully systems and watersheds in the Dry-Hot Valley [South West (SW) China], gullies are interpreted from online Google images with high resolution and watersheds are extracted from digital elevation model at a scale of 1:50,000. The results show that: (1) There are 17,382 gullies (with a total area of 1141.66 km²) and 42 watersheds in the study area. (2) The average gully density of the study area (D) is 4.29 km/km², gully frequency (F) is 14.39 gullies/km², the branching ratio (B) is 5.13, the length ratio (L) is 3.12, and the coefficient of the main and tributary gullies (M) is 0.06. The degree of gully erosion is strong to extremely strong, the main development intensity of gully erosion ranges from intense to moderate, and the type of gully system is tributary. (3) The watershed areas (A) are between 0.39 and 96.43 km², the relief ratio (R) is from 0.10 to 0.19, the circularity ratio (C) is from 0.30 to 0.83, the texture ratio (T) is from 0.82 to 39.35, and the dominant geomorphological texture type is fine. (4) There is a quantitative relationship between F and D:F?=?0.624D² (R?=0.84) and T is closely related to D, F, M (R²?>?0.7). A, R and C are related to M (R²?>?0.5). The development of gully systems is the result of coupling effects between multiple factors. In this area, the degree of erosion and the condition of the main and tributary gullies can be controlled by the degree of topographic breakage in the watershed, which provides some theoretical basis for the evaluation of gully erosion by the latter. In addition, the scale, relief, and shape have a significant impact on the locations of the main and tributary gullies. For tributary gullies, attention should be paid to the interception and control of runoff and sediment in the small confluence branches in order to prevent gully expansion and head advance. These features can inform the development of targeted measures for the control of soil erosion.     

Constraints on sedimentary ages of the Chuanlinggou Formation in the Ming Tombs,Beijing, North China Craton: LA-ICP-MS and SHRIMP U–Pb dating of detrital zircons

Detrital zircons in five sedimentary samples, MC1 to MC5, from the bottom of the Chuanlinggou Formation in the Ming Tombs District, Beijing, were dated with the LA-ICP-MS and SHRIMP U–Pb methods. Age spectra of the five samples show a major peak at 2500 Ma and a secondary peak at 2000 Ma, suggesting their provenances were mainly from the crystalline basement of the North China Craton and the Trans-North China Orogen. The youngest zircon has an age of 1673 ± 44 Ma, indicating that the Chuanlinggou Formation was deposited after this age. From sample MC4 to MC5, lithology changed from a clastic rock (fine-grained sandstone) to a carbonate rock (fine-grained dolomite), suggesting that the depositional basin became progressively deeper. The age spectrum of sample MC5 shows a major peak at 2500 Ma and a secondary peak at 2000 Ma. Sample MC4, which is stratigraphically lower than sample MC5, only had one peak at 2500 Ma. We conclude that there was a transgressive event when sediments represented by MC5 was deposited, and seawater carried ca. 2000 Ma clastic materials to the basin where the Chuanlinggou Formation was deposited, leading to the addition of ca. 2000 Ma detritus. Our research indicates that the source area for the sediments became more extensive with time. We conclude that the Chuanlinggou Formation in the Ming Tombs District was deposited in a low-energy mud flat sedimentary environment in the inter-supra tidal zone because it is mainly composed of silty mudstone and fine-grained sandstone with relatively simple sedimentary structures.     

Development mechanism for the landslide at Xinlu Village,Chongqing, China

Due to the continuous and intense rainfall from June 26 to 28, 2016, Xinlu Village in Ganshui Town, Qijiang District, Chongqing, experienced a unitary-slip landslide at approximately UTC+8 19:30 on June 28. This landslide disrupted the Chuan-Qian railway and damaged four residential buildings. To analyze and rehabilitate the landslide, the engineering geology, hydrological conditions, and deformation instability mechanism of this landslide were investigated and comprehensively analyzed based on an in situ survey, geophysical drilling, and a laboratory quick-shearing test. The results show that the landslide is a typical gradual progressive landslide.