scholarly journals Heterogeneity of soil nutrients in ecosystems: a review of methodology, variability and impact factors

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Shaoliang Zhang
Keyword(s):  
Land Use ◽  
Soil Nutrients ◽  
Spatial Dependence ◽  
Soil Nutrient ◽  
Moderate Level ◽  
Impact Factors ◽  
Driving Mechanism ◽  
Nutrient Heterogeneity ◽  
Soil Nutrient Heterogeneity ◽  
The Impact

Soil nutrient heterogeneity highly correlates to plant growth and development of environmental quality. In order to better understand nutrient cycling, heterogeneity of soil nutrients and their driving mechanism in different land use types were summarized from 1945 to 2016. By grouping keywords indexed in the titles of articles from the data base of Web of Science, two hundred and thirty one publications related to our topics were used for analysis. Soil sampling and statistical method were compared, and spatial dependence and the impact factors for soil organic matter (SOM), Nitrogen (N), Phosphorus (P) and Potassium (K). The results showed that soil nutrient heterogeneity was influenced by different factors at different scales. The spatial dependence of SOM, N and P were mainly at the moderate level (48.9-59.0%) and strong level (33.3-42.2%), while for K was at strong level (63.6-84.6%) and moderate level (15.4-36.4%). This was mainly influenced by topography, soil loss, weather condition, parent material, soil type, soil texture, land use, human activities, soil moisture, mineral element, soil structure, animal and plant. These impact factors were summarized separately, and the influence of factors at different spatiotemporal scales was discussed. At the end of the review, the ideas for further research were postulated.

scholarly journals Landscape pattern and economic factors’ effect on prediction accuracy of cellular automata-Markov chain model on county scale

2020 ◽  
Vol 12 (1) ◽  
pp. 626-636
Author(s):  
Wang Song ◽  
Zhao Yunlin ◽  
Xu Zhenggang ◽  
Yang Guiyan ◽  
Huang Tian ◽  
...  
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Cellular Automata ◽  
Markov Model ◽  
Prediction Accuracy ◽  
Driving Mechanism ◽  
Economic Factors ◽  
Chain Model ◽  
The Impact ◽  
County Scale

AbstractUnderstanding and modeling of land use change is of great significance to environmental protection and land use planning. The cellular automata-Markov chain (CA-Markov) model is a powerful tool to predict the change of land use, and the prediction accuracy is limited by many factors. To explore the impact of land use and socio-economic factors on the prediction of CA-Markov model on county scale, this paper uses the CA-Markov model to simulate the land use of Anren County in 2016, based on the land use of 1996 and 2006. Then, the correlation between the land use, socio-economic data and the prediction accuracy was analyzed. The results show that Shannon’s evenness index and population density having an important impact on the accuracy of model predictions, negatively correlate with kappa coefficient. The research not only provides a reference for correct use of the model but also helps us to understand the driving mechanism of landscape changes.

Whole-tree Harvesting Depletes Soil Nutrients

1974 ◽  
Vol 4 (4) ◽  
pp. 530-535 ◽  
Author(s):  
Edwin H. White
Keyword(s):  
Soil Nutrients ◽  
Nutrient Removal ◽  
Cropping Systems ◽  
Soil Nutrient ◽  
Site Conditions ◽  
Nutrient Pool ◽  
Whole Tree Harvesting ◽  
The Impact ◽  
Whole Tree ◽  
Tree Harvesting

This paper reports the effects of whole-tree harvesting of eight cottonwood stands on the soil nutrient pool. The data indicate possible site degradation by depletion of soil reserves of N, P, and K but not Ca and Mg on a range of alluvial site conditions in Alabama. Foresters must establish the rate of nutrient removal in intensive tree cropping systems for a variety of species and sites and develop prescriptions to minimize the impact.

scholarly journals Assessment of Land Cover Changes in the Hinterland of Barranquilla (Colombia) Using Landsat Imagery and Logistic Regression

Land ◽  
2018 ◽  
Vol 7 (4) ◽  
pp. 152 ◽  
Author(s):  
Henry Schubert ◽  
Andrés Caballero Calvo ◽  
Markus Rauchecker ◽  
Oscar Rojas-Zamora ◽  
Grischa Brokamp ◽  
...  
Keyword(s):  
Land Use ◽  
Logistic Regression ◽  
Land Cover ◽  
Rural Areas ◽  
Vegetation Cover ◽  
Landsat Imagery ◽  
Impact Factors ◽  
Land Cover Changes ◽  
Dynamic Changes ◽  
The Impact

Barranquilla is known as a dynamically growing city in the Colombian Caribbean. Urbanisation induces land use and land cover (LULC) changes in the city and its hinterland affecting the region’s climate and biodiversity. This paper aims to identify the trends of land use and land cover changes in the hinterland of Barranquilla corresponding to 13 municipalities in the north of the Department Atlántico. Landsat TM/ETM/OLI imagery from 1985 to 2017 was used to map and analyse the spatio-temporal development of land use and land cover changes. During the investigation period, the settlement areas grew by approximately 50% (from 103.3 to 153.6 km2), while areas with woody vegetation cover experienced dynamic changes and increased in size since 2001. Peri-urban and rural areas were characterized by highly dynamic changes, particularly regarding clearing and recovery of vegetated areas. Regression analyses were performed to identify the impact factors of detected vegetation cover changes. Computed logistic regression models included 20 independent variables, such as relief, climate, soil, proximity characteristics and socio-economic data. The results of this study may act as a basis to enable researchers and decision-makers to focus on the most important signals of systematic landscape transformations and on the conservation of ecosystems and the services they provide.

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