Soil organic carbon and soil total nitrogen stocks, soil quality and vegetation composition during natural revegetation processes in a Mediterranean mid-mountain area

Author(s):  
Estela Nadal Romero ◽  
Pedro Sánchez Navarrete ◽  
Makki Khorchani ◽  
Luis Miguel Medrano-Moreno ◽  
Teodoro Lasanta

<p>Mediterranean mid-mountain areas have been subject to significant human pressure through deforestation, cultivation of steep slopes, fires and overgrazing. However, during the 20<sup>th</sup> century, the mountainous areas of the northern rim of the Mediterranean region were affected by abandonment of cultivated fields and natural revegetation processes. Natural revegetation occurred in most of the lands where human activity (farming on steep slopes, grazing) declined in intensity or was abandoned, resulting in the expansion of shrubs, bushes and forests. What are the consequences of such processes on soil quality, soil organic carbon (SOC) and soil total nitrogen (TN) stocks and vegetation composition? What are the differences between the different land uses and land covers (LULCs)? The general aim of this study is to study the effects of natural revegetation processes after land abandonment on soil quality, SOC and soil TN stocks and vegetation composition in the Leza Valley (Iberian System, Spain). We hypothesized that natural revegetation processes improves soil quality and higher SOC and TN stocks. For this purpose, we analyzed 60 soil samples, from 5 LULCs and four depths (0-10, 10-20, 20-30, 30-40 cm): pasture, shrubs characterized by the presence of Cistus laurifolius, bushed characterized by the presence of Juniperus communis, Young forest (Quercus faginea), and old forest or dehesa. In addition, plant species inventories were carried out in each LULC.</p><p>The results related to physico-chemical soil properties indicated: (i) significant differences in soil quality between the first stages of natural revegetation (pasture and shrubs) and young forest (limited to the first 20 cm between shrub and young forest); (ii)  significant differences in SOC stocks between the first stage of natural revegetation (pasture) and young and old forests; (iii) significant differences in soil TN stocks between pasture and shrubs and young and old forests; and (iv) significant differences between the shrub families. Final results obtained through a Principal Component Analysis with all the variables differentiate forests from shrubs, bushes and pastures confirming our first hypothesis. We can conclude that natural revegetation is an effective strategy to improve soil quality and increase SOC and soil TN stocks.</p>

Geoderma ◽  
2017 ◽  
Vol 305 ◽  
pp. 250-263 ◽  
Author(s):  
Shuai Wang ◽  
Qianlai Zhuang ◽  
Qiubing Wang ◽  
Xinxin Jin ◽  
Chunlan Han

2021 ◽  
Author(s):  
chao wang ◽  
Chuanyan Zhao ◽  
Kaiming Li ◽  
Shouzhang Peng ◽  
Ying Wang

Abstract Soil organic carbon and soil total nitrogen stocks are important indicators for evaluating soil health and stability. Accurately predicting the spatial distribution of soil organic carbon and total nitrogen stocks is an important basis for mitigating global warming, ensuring regional food security, and maintaining the sustainable development of ecologically fragile areas. On the basis of field sampling data and remote sensing technology, this study divided the topsoil (0–30 cm) into three soil layers of 0–10 cm, 10–20 cm, and 20–30 cm to carry out soil organic carbon and soil total nitrogen stocks estimation experiments in the Qilian Mountains in western China. A multiple linear regression model and a stepwise multiple linear regression model were used to estimate soil organic carbon and soil total nitrogen stocks. A total of 119 topsoil samples and nine remotely sensed environmental variables were collected and used for model development and validation. The results indicated that these two linear regression models showed good performance. The modified soil-adjusted vegetation index (MSAVI), perpendicular vegetation index (PVI), aspect, elevation, and solar radiation were the key environmental variables affecting soil organic carbon and total nitrogen stocks. In topsoil, remote sensing technology could be used to predict the soil properties in layers; however, as the soil depth increased, the performance of the linear regression models gradually decreased.


2011 ◽  
Vol 02 (01) ◽  
pp. 34-40 ◽  
Author(s):  
Maruf Kajogbola Adebayo Adeboye ◽  
Abdullahi Bala ◽  
Akim Oserhien Osunde ◽  
Anthony Ozoemenam Uzoma ◽  
Ayo Joshua Odofin ◽  
...  

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