Spatial patterns of Caragana korshinskii growth on hillslope scale and influencing factors in the semi-arid Loess Plateau

Abstract Rainfall pulses can significantly drive the evolution of the structure and function of semiarid ecosystems, and understanding the mechanisms that underlie the response of semiarid plants to rainfall is the key to understanding the responses of semi–arid ecosystems to global climatic change. We measured sap flow in the branches and stems of shrubs (Caragana korshinskii Kom. and Hippophae rhamnoides Linn.) using sap flow gauges, and studied the response of sap flow density to rainfall pulses using the “threshold–delay” model in the Chinese Loess Plateau. The results showed that the sap flow began about 1 h earlier, and increased twofold after rainfall, compared to its pre-rainfall value. The sap flow increased significantly with increasing rainfall classes, then gradually decreased. The response of sap flow was different among rainfall, species, position (branch and stem) during the pulse period, and the interactive effects also differed significantly (P < 0.0001). The response pattern followed the threshold–delay model, with lower rainfall thresholds of 5.2, 5.5 mm and 0.7, 0.8 mm of stem and branch for C. korshinskii and H. rhamnoides, demonstrating the importance of small rainfall events for plant growth and survival in semi–arid regions.

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The microbial biomass and activity in soil with shrub (Caragana korshinskii K.) plantation in the semi-arid loess plateau in China

European Journal of Soil Biology ◽

10.1016/j.ejsobi.2009.10.002 ◽

2010 ◽

Vol 46 (1) ◽

pp. 6-10 ◽

Cited By ~ 21

Author(s):

Guo-Mei Jia ◽

Bing-Ru Liu ◽

Gang Wang ◽

Baolin Zhang

Keyword(s):

Microbial Biomass ◽

Loess Plateau ◽

Caragana Korshinskii ◽

Semi Arid

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Soil erodibility and its influencing factors on the Loess Plateau of China: a case study in the Ansai watershed

Solid Earth ◽

10.5194/se-9-1507-2018 ◽

2018 ◽

Vol 9 (6) ◽

pp. 1507-1516 ◽

Cited By ~ 7

Author(s):

Wenwu Zhao ◽

Hui Wei ◽

Lizhi Jia ◽

Stefani Daryanto ◽

Xiao Zhang ◽

...

Keyword(s):

Influencing Factors ◽

Loess Plateau ◽

Sea Buckthorn ◽

Soil Erodibility ◽

Vegetation Types ◽

The Loess Plateau ◽

Caragana Korshinskii ◽

Native Grasslands ◽

Growing Conditions ◽

Soil Surveys

Abstract. The objectives of this work were to identify the best possible method to estimate soil erodibility (K) and understand the influencing factors of soil erodibility. In this study, 151 soil samples were collected during soil surveys in the Ansai watershed of the Loess Plateau of China. The K values were estimated by five methods: erosion-productivity impact model (EPIC), nomograph equation (NOMO), modified nomograph equation (M-NOMO), Torri model and Shirazi model. The main conclusions of this paper are (1) K values in the Ansai watershed ranged between 0.009 and 0.092 t ⋅ hm2 ⋅ h/(MJ ⋅ mm ⋅ hm2), and the maximum values were 1.9–7.3 times larger than the corresponding minimum values, and the Shirazi and Torri models were considered the optimal models for the Ansai watershed. (2) Different land use types had different levels of importance; the principal components (PCs) accounted for 100 % (native grassland), 48.88 % (sea buckthorn), 62.05 % (Caragana korshinskii), and 53.61 % (pasture grassland) of the variance in soil erodibility. (3) The correlations between soil erodibility and the selected environmental variables differed among different vegetation types. For native grasslands, soil erodibility had significant correlations with terrain factors. For the most artificially managed vegetation types (e.g., apple orchards) and artificially restored vegetation types (e.g., sea buckthorn), soil erodibility had significant correlations with the growing conditions of vegetation. Soil erodibility had indirect relationships with both environmental factors (e.g., elevation and slope) and human activities, which potentially altered soil erodibility.

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Evaluation of adaptability of conservation tillage in Loess Plateau semi-arid areas

CHINESE JOURNAL OF ECO-AGRICULTURE ◽

10.3724/sp.j.1011.2008.01122 ◽

2009 ◽

Vol 16 (5) ◽

pp. 1122-1126

Author(s):

Li-Jun SUN

Keyword(s):

Loess Plateau ◽

Conservation Tillage ◽

Arid Areas ◽

Semi Arid

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Appropriate Management Scale of Farmland and Regional Differences under Different Objectives in Shaanxi Province, China

Land ◽

10.3390/land10030314 ◽

2021 ◽

Vol 10 (3) ◽

pp. 314

Author(s):

Qianxi Zhang ◽

Zehui Chen ◽

Fei Li

Keyword(s):

Influencing Factors ◽

Loess Plateau ◽

Regional Differences ◽

Agricultural Development ◽

Shaanxi Province ◽

Employment Rate ◽

Grain Production ◽

The Loess Plateau ◽

Surplus Labor ◽

The Government

Agricultural development is facing two problems: insufficient grain production and low profit of farmers. There is a contradiction between the government’s goal of increasing production and the farmer’s goal of increasing profit. Exploring the appropriate management scale of farmland under different objectives is of great significance to alleviate the conflict of interests between the government and farmers. In this study the Cobb-Douglas production function model was used to measure the appropriate management scale of farmland under different objectives in Shaanxi Province and analyze the regional differences. Under the two objectives, the appropriate management scale of the Loess Plateau was the largest in the three regions, followed by Qinba Mountains and Guanzhong Plain. Farmland area and quality were the main influencing factors for the appropriate management scale of farmland under the goal of maximizing the farmland yield, while the nonagricultural employment rate and farmland transfer rate were the main influencing factors under the goal of maximizing farmers’ profits. It is easy for Shaanxi Province to increase farmers’ profits, but more land needed to be transferred to increase farmland yield. These results suggest that in order to balance the goal of increasing yield and profit, the transfer of rural surplus labor should be promoted, and the nonagricultural employment rate should be improved. In Loess Plateau, restoring the ecological environment and enhancing the farmland quality. In Guanzhong Plain, avoiding urban land encroachment on farmland. In Qinba Mountains, developing farming techniques and moderately increasing the intensity of farmland exploit.

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Spatial patterns in a two-tiered semi-arid shrubland in southeastern Spain

Journal of Vegetation Science ◽

10.2307/3236301 ◽

1996 ◽

Vol 7 (4) ◽

pp. 527-534 ◽

Cited By ~ 108

Author(s):

Peter Haase ◽

Francisco I. Pugnaire ◽

S.C. Clark ◽

L.D. Incoll

Keyword(s):

Spatial Patterns ◽

Southeastern Spain ◽

Semi Arid

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Spatiotemporal Changes in Vegetation Cover and Its Influencing Factors in the Loess Plateau of China Based on the Geographically Weighted Regression Model

Forests ◽

10.3390/f12060673 ◽

2021 ◽

Vol 12 (6) ◽

pp. 673

Author(s):

Chen Yang ◽

Meichen Fu ◽

Dingrao Feng ◽

Yiyu Sun ◽

Guohui Zhai

Keyword(s):

Regression Model ◽

Influencing Factors ◽

Loess Plateau ◽

Geographically Weighted Regression ◽

Vegetation Cover ◽

Weighted Regression ◽

Vegetation Coverage ◽

The Loess Plateau ◽

Geographically Weighted Regression Model ◽

Spatiotemporal Changes

Vegetation plays a key role in ecosystem regulation and influences our capacity for sustainable development. Global vegetation cover has changed dramatically over the past decades in response to both natural and anthropogenic factors; therefore, it is necessary to analyze the spatiotemporal changes in vegetation cover and its influencing factors. Moreover, ecological engineering projects, such as the “Grain for Green” project implemented in 1999, have been introduced to improve the ecological environment by enhancing forest coverage. In our study, we analyzed the changes in vegetation cover across the Loess Plateau of China and the impacts of influencing factors. First, we analyzed the latitudinal and longitudinal changes in vegetation coverage. Second, we displayed the spatiotemporal changes in vegetation cover based on Theil-Sen slope analysis and the Mann-Kendall test. Third, the Hurst exponent was used to predict future changes in vegetation coverage. Fourth, we assessed the relationship between vegetation cover and the influence of individual factors. Finally, ordinary least squares regression and the geographically weighted regression model were used to investigate the influence of various factors on vegetation cover. We found that the Loess Plateau showed large-scale greening from 2000 to 2015, though some regions showed decreasing vegetation cover. Latitudinal and longitudinal changes in vegetation coverage presented a net increase. Moreover, some areas of the Loess Plateau are at risk of degradation in the future, but most areas showed a sustainable increase in vegetation cover. Temperature, precipitation, gross domestic product (GDP), slope, cropland percentage, forest percentage, and built-up land percentage displayed different relationships with vegetation cover. Geographically weighted regression model revealed that GDP, temperature, precipitation, forest percentage, cropland percentage, built-up land percentage, and slope significantly influenced (p < 0.05) vegetation cover in 2000. In comparison, precipitation, forest percentage, cropland percentage, and built-up land percentage significantly affected (p < 0.05) vegetation cover in 2015. Our results enhance our understanding of the ecological and environmental changes in the Loess Plateau.

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