Spatiotemporal Changes in Gibberellin Content are Required for Soybean Nodulation

Abstract Yongding River is one of the five major river systems in Beijing. It is located to the west of Beijing. It has influenced culture along its basin. The river supports both rural and urban areas. Furthermore, it influences economic development, water conservation, and the natural environment. However, during the past few decades, due to the combined effect of increasing population and economic activities, a series of changes have led to problems such as the reduction in water volume and the exposure of the riverbed. In this study, remote sensing images were used to derive land cover maps and compare spatiotemporal changes during the past 40 years. As a result, the following data were found: forest changed least; cropland area increased to a large extent; bareland area was reduced by a maximum of 63%; surface water area in the study area was lower from 1989 to 1999 because of the excessive use of water in human activities, but it increased by 92% from 2010 to 2018 as awareness about protecting the environment arose; there was a small increase in the built-up area, but this was more planned. These results reveal that water conservancy construction, agroforestry activities, and increasing urbanization have a great impact on the surrounding environment of the Yongding River (Beijing section). This study discusses in detail how the current situation can be attributed to of human activities, policies, economic development, and ecological conservation Furthermore, it suggests improvement by strengthening the governance of the riverbed and the riverside. These results and discussion can be a reference and provide decision support for the management of southwest Beijing or similar river basins in peri-urban areas.

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Early Maturing Soybean Nodulation and Performance with Selected Bradyrhizobium japonicum Strains

Agronomy Journal ◽

10.2134/agronj1992.00021962008400030019x ◽

1907 ◽

Vol 84 (3) ◽

pp. 449-458 ◽

Cited By ~ 14

Author(s):

J. V. Wiersma ◽

J. H. Orf

Keyword(s):

Bradyrhizobium Japonicum ◽

Early Maturing ◽

And Performance ◽

Soybean Nodulation

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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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