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We study studied the alpine meadow soil in Gannan Prefecture. Geostatistical analysis showed that Circular [soil total nitrogen (STN), soil total potassium (STK), soil available phosphorus (SAP)] model, index [bulk density (BD), soil water content (SWC), soil organic carbon (SOC), soil available nitrogen (SAN)] model and Gaussian [soil total phosphorus (STP), soil available potassium (SAK)] model is universal Kriging Method semi-variation function optimization fitting model. In the model, the spatial correlation is weak to medium, and SOC, STN, STP, STK, SAN, SAP, SAK, and SWC have specific spatial trend effects. Then principal component analysis was used to obtain three key factors (SOC, BD, and SWC) affecting soil quality, which accounted for 81.91% of the total variation of soil quality. These factors were taken as the minimum data set (MDS) and soil quality index (SQI) was calculated. According to SQI, the whole region was divided into three soil management zones (SMZs). Recommendations are made for different management areas to ensure resource conservation and reduce environmental footprint. [ABSTRACT FROM AUTHOR]

Wild licorice in China is mainly distributed in northern China, such as Gansu, Ningxia, and Inner Mongolia Provinces. The origin of wild licorice has varied among historical periods. The cultivated origin of planted licorice has the same as 59.26% of wild licorice. The distribution of cultivated licorice was shifted to the northwest relative to that of wild licorice. The yield and quality of cultivated licorice vary greatly from different origins, showing a certain pattern of variation from west to east. The same batch of licorice seedlings was planted at 8 sites overlapping the main licorice production areas in China. The yield and quality of licorice in the Baicheng experimental plot were low. The yield of licorice in the Jingtai and Altay experimental plots was high, but the quality was poor. The quality of licorice in Chifeng and Yuzhong experimental sites was high, but the yield was low. Principal component analysis of environmental and soil factors generated five characteristic roots with a cumulative contribution rate of 80%, three of which were related to soil and referred to as the soil charge factor, soil water factor, and soil nutrient factor, and the load coefficients of the water and nutrient factor were the largest. Soil conditions, especially water and nutrients, might have a substantial effect on the observed changes in the licorice production area. Generally, the regulation of water and nutrients merits special attention when selecting areas for the production and cultivation of licorice. This study can provide reference for the selection of cultivated licorice production areas and the research of high-quality cultivation techniques. [ABSTRACT FROM AUTHOR]

Drought is one of the most devastating natural hazards in the world, affecting millions of individuals in in different ways, so it's better monitoring and comprehensive assessment is important. Univariate or multivariate drought indices are able to monitor one type of drought and can not reflect comprehensive drought information from meteorological to agricultural aspects. For this purpose, by combining the Vegetation Condition Index (VCI), Temperature Condition Index (TCI), the Soil Water Index (SWI) and the precipitation condition index (PCI) a comprehensive drought index called Combined Drought Index (CDI) was proposed. In this study, meteorological and agricultural droughts from 2001 to 1397 in Karkheh Basin in southwestern Iran were monitored. The Principal Component Analysis (PCA) method, which is a mainstay of modern data analysis tools for constructing a composite index, was applied to a data matrix that contains the time series of the computed PCI, VCI, TCI, and SWI indices for a given location, and the first leading component of the PCA was introduced as CDI index. The results indicated that the highest correlation (r = 0.53, r = 0.56) between the CDI, SPI-1 and SDI was observed respectively, which indicates the ability of this index for drought comprehensive monitoring. It is also suggested that in order to improve the performance of the CDI, in addition to the considered parameters in this study, other factors affecting the performance of each of the remote sensing indicators such as vegetation type, plant root, soil texture type, evaporation and Transpiration also be considered in future studies. [ABSTRACT FROM AUTHOR]

Aims: Ecosystems with higher latitude in the northern hemisphere are expected to face the largest loss of soil organic carbon (C) due to global warming. The concentrations, distributions, morphology of phytoliths and their associations with soil properties show fundamental significance in actually assessing the potential C sequestration of forest soils. Methods: We examined soil phytolith contents and soil properties of Larix gmelinii forest from the Greater Khingan Mountains. ANOVA, bivariate correlation, regression analysis, principal component analysis and redundancy analysis were conducted to interpret the relations between soil phytoliths and soil properties. Results: The soil phytoliths in the studied area were mainly elongate in shape with a mean content of 19.1 g kg−1. The phytoliths had a significant correlation with phosphorus rather than potassium and nitrogen, while they had no correlation with soil water content. Soil phytolith storage in the cold temperate zone (41.0 t ha−1) was significantly higher than in the tropical and subtropical zones. Conclusions: Soil phytolith storage in Larix gmelinii forest is affected by soil properties and climate, which have a certain relation with soil organic C, pH, nutrients and mineral elements. The C sequestration capacity of soils could be elevated by the increase of phytolith contents in the cold temperate coniferous forest. Analyses of small-sized and fragile phytogenic Si structures are urgently needed in future work as they are the most important drivers of Si cycling in terrestrial biogeosystems, which is very important to accurately quantify the phytoliths contents and the pool of C sequestered in phytoliths. [ABSTRACT FROM AUTHOR]

Stagnating potato tuber yields in Prince Edward Island (PEI) are a major economic concern. Identification of factors influencing within-field yield variation may provide insight into strategies for overcoming yield limitations. A survey approach was used where soil samples were collected from 49 commercial fields from 2014 to 2017 from a total of 289 sampling points, with points identified as having either "high" or "low" yield, determined by yield monitor as being 5.6–11.2 t ha−1 above or below average field yield, respectively. A suite of 33 measures of soil physical and chemical properties and soil pathogens were measured. Principal component analysis identified three principal components (PCs) which accounted for 85.6% of the total variation. The PC1 (reflecting 42.3% of the total variance) was associated primarily with soil texture (i.e., sand, clay) and parameters which were highly correlated with soil texture. Under the rainfed potato production on sandy-loam soils in PEI, finer soil texture is likely related to increased yield through its effect on improved soil water holding capacity. The PC2 (reflecting 29.0% of the total variance) was primarily associated with soil fertility and the PC3 (reflecting 14.4% of the total variance) was associated primarily with soil organic matter quality and soil structure. Although soil pathogens were measured at levels high enough to impact yield, they did not differ significantly between high and low yield locations. The findings of this study highlight the value in using multivariate approaches to overcome the challenges in identifying factors which control within-field yield variability. [ABSTRACT FROM AUTHOR]

Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data were analyzed to study the vegetation dynamics over different meteorological subdivisions in India for the period 2000–2016. Soil moisture (SM), rainfall (RF), and land use land cover (LULC) data were analyzed to identify the climatic and anthropogenic drivers that cause vegetation changes at the subdivision scale. Principal component analysis and MK (Mann-Kendall) test showed significant greening trend over semi-arid regions of Northwest India (NWI) and South India (SI) while slight browning trend seen over some of the subdivisions in Indo-Gangetic (IG) plains and Western Ghats (WG). It is found that the NDVI has superior correlation with soil moisture compared with rainfall and the croplands (CL) found to have significant increasing trend over the NWI and SI. Increasing trend in soil moisture over the NWI and SI may have contributed to increase in CL area and the greening trend. Over IG plains, the NDVI showed moderate correlation with SM and RF, and the greening trend (browning trend) in some regions can be attributed to increase in natural vegetation mosaic (decrease of CL). The NDVI has shown browning trend over the core monsoon regions of Madhya Pradesh (an increase of barren lands over west MP and decrease of CL over east MP) and Western Ghats (significant decrease of CL over Konkan and Goa). This study revealed that the soil moisture and LULC changes are the major driving factors for the vegetation changes over majority of the subdivisions in India. [ABSTRACT FROM AUTHOR]

The Community Land Model version 3.5 is driven by an observation-based meteorological dataset to simulate soil moisture over China for the period 1951-2008. A method for identifying the patterns of interannual variability that arise from slow (potentially predictable) and intraseasonal (unpredictable) variability is also applied; this allows identification of the sources of the predictability of seasonal soil moisture in China, during March-April-May (MAM), June-July-August (JJA), September-October-November (SON) and December-January-February (DJF). The potential predictability (slow-to-total) of the soil moisture above 1 m is high, with lowest value of 0.76 in JJA and highest value of 0.94 in DJF. The spatial distribution of the potential predictability comprises a northwest-southeast gradient, with a minimum center over East China and a maximum center over the northwest. The most important source of predictability is from the soil moisture persistence, which generally accounts for more than 50 % of the variability in soil moisture. The SSTs in the Indian Ocean, the North Atlantic and the eastern tropical Pacific Oceans are also identified as important sources of variability in the soil moisture, during MAM, JJA and SON/DJF, respectively. In addition, prolonged linear trends in each season are an important source. Using the slow principal component time series as predictands, a statistical scheme for the seasonal forecasting of soil moisture across China is developed. The prediction skills, in terms of the percentage of explained variance for the verification period (1992-2008), are 59, 51, 62 and 77 % during MAM-DJF, respectively. This is considerably higher than a normal grid prediction scheme. [ABSTRACT FROM AUTHOR]

Competition for light has driven forest trees to grow exceedingly tall, but the lack of a single universal limit to tree height indicates multiple interacting environmental limitations. Because soil nutrient availability is determined by both nutrient concentrations and soil water, water and nutrient availabilities may interact in determining realised nutrient availability and consequently tree height. In SW Australia, which is characterised by nutrient impoverished soils that support some of the world's tallest forests, total [P] and water availability were independently correlated with tree height ( r = 0.42 and 0.39, respectively). However, interactions between water availability and each of total [P], pH and [Mg] contributed to a multiple linear regression model of tree height ( r = 0.72). A boosted regression tree model showed that maximum tree height was correlated with water availability (24%), followed by soil properties including total P (11%), Mg (10%) and total N (9%), amongst others, and that there was an interaction between water availability and total [P] in determining maximum tree height. These interactions indicated a trade-off between water and P availability in determining maximum tree height in SW Australia. This is enabled by a species assemblage capable of growing tall and surviving (some) disturbances. The mechanism for this trade-off is suggested to be through water enabling mass-flow and diffusive mobility of P, particularly of relatively mobile organic P, although water interactions with microbial activity could also play a role. [ABSTRACT FROM AUTHOR]