1 Introduction

The Earth’s surface temperatures became increasingly high during the last century due to human activities mainly fossil fuels burning, which were disturbing the planet and causing global warming (Hay 2014). Therefore, there is a growing public and scientific concern about the carbon sequestration potential of various terrestrial ecosystems with the increase of atmospheric CO2 concentration (Eid and Shaltout 2013). As a result, the Kyoto Protocol was signed to mitigate greenhouse gas concentrations in the atmosphere through improving the terrestrial carbon sinks (Yimer et al. 2006). Carbon sequestration refers simply to CO2 removal from the atmosphere and storage in an organic form in the soil or plants (Feller and Bernoux 2008). The carbon sequestration in soil has been widely considered to be a promising measure for mitigating the increasing atmospheric CO2 concentration (Smith 2008). Pacala and Socolow (2004) outlined 15 options for stabilizing the atmospheric concentration of CO2 by 2050 at approximately 550 ppm; three of these 15 options were based on carbon sequestration in terrestrial ecosystems.

Soil is a major carbon sink or source on terrestrial ecosystems (Cicuzza et al. 2015). The content and spatial distribution of soil organic carbon (SOC) is of great significance when studying the global carbon cycle and the greenhouse effect (Lal 2004), and provides a scientific basis for the assessment of the magnitude of carbon stored in each area (Wang et al. 2013). The SOC depends on climate, topography, hydrology, land-use, soil type, the balance between additions and losses of carbon, and other properties (Fang et al. 2012). Jobbagy and Jackson (2000) found that vegetation type and/or land-use are important factors in determining SOC depth distribution, especially close to the surface, and highlighting the importance of vegetation change for carbon sequestration strategies. Moreover, identifying changes in SOC distribution with depth by time would help in understanding the effect of climate and land-use changes on SOC stocks (Meersmans et al. 2009).

The management of crop land is among those activities that a country signatory of the Kyoto Protocol may elect for meeting its emission reduction target. SOC stock and dynamics in the soils of crop land are important for quantifying the carbon emissions and removals involved in land-use change processes (Chiti et al. 2012). In Egypt, the need for accurate information on SOC content has increased due to the importance of SOC stocks for sustainable use of natural resources. Moreover, information on SOC stocks is necessary for assessing the potential role of soils as CO2 sinks. Studying the SOC in relation to different land-uses and different vegetation types for ecological rehabilitation is crucial for improving SOC sequestration and soil quality (Fang et al. 2012). To evaluate the carbon sequestration potential of various terrestrial ecosystems, baseline data on SOC stocks are critical for understanding current conditions and the content of SOC that could be sequestrated both in natural and agricultural systems. According to the authors’ knowledge, so far, no country assessment of SOC stocks under different land-use practices has been carried out in Egypt. Thus, the objectives of the present study are: (1) to quantify the vertical distribution of the soil bulk density (SBD) and SOC content in the soil of north Nile Delta, Egypt under different types of land-use; (2) to provide estimates of the carbon sequestration rate (CSR) of those soils under different types of land-use; and (3) to establish a baseline data on SOC stocks for future studies on SOC dynamics. The definition of an SOC stock baseline is essential for future evaluations of the status of this stock. Furthermore, the identification of a baseline for the SOC stock in crop land and fish farm ecosystems could contribute to the assessment of the possible effects of conversion of virgin land to agricultural or fish farm uses on the SOC stocks in Nile Delta.

2 Methods

2.1 Study area

The study area (Lat. 30°34′–31°19′N, Long. 31°08′–31°38′E) lies in the north Nile Delta bounded by the two branches of the Nile: Rosetta to the west and Damietta to the east. The Nile Delta, an area of about 2200 × 103 ha, is a place of one of the most ancient agricultural systems in the world (Aly et al. 2013). It accounts for two-thirds of Egypt’s agricultural land (Abu Al-Izz 1971), and at the same time houses almost half of the population in a country with a high population growth rate (Alfiky et al. 2012). Agricultural lands represent 61% of the Nile Delta, virgin lands represent 13%, while fish farms represent 7% (Elhag et al. 2013). As reported in Alfiky et al. (2012), 25,200 ha of fertile agricultural lands are lost each year in Egypt and most of those lands are located in the Nile Delta. Moreover, virgin lands at the north of Nile Delta are subject to coastal erosion due to sea rise (El Nahry et al. 2008). In Egypt, most cultivated lands are irrigated through a network of canals integrated by a similar network of drainage canals (Shaltout et al. 2010). The total length of both networks exceeds 47,000 km, of which 31,000 km are irrigation canals (Khattab and El-Gharably 1984). There are three cropping seasons in Egypt: winter (November to May), summer (April/May to October) and nil (July/August to October). In Egypt, rice occupies about 588,000 ha (22% of field crops), sugar beet 16,380 ha (14% of sugar crops) and clover 974,400 ha (76% of fodder crops) (El-Nahrawy 2011). The fertilizer application was 476/238/0 kg ha−1 N/P/K for rice, 476/0/0 kg ha−1 N/P/K for clover and 476/476/119 kg ha−1 N/P/K for sugar beet (El Shimi 2005). Compost manure is used at 12 tons ha−1 on agricultural lands and added during soil preparation, prior to the cultivation of summer crops (cotton, maize, rice, sugar cane, citrus, grapes) as a first crop of agriculture rotation. However, the residual effect of organic matter will continue for the second crop in the winter season (wheat, fava bean, fodder, clover) (El Shimi 2005). Ploughing to 40 cm depth was done every year before planting.

According to the map of the world distribution of arid regions (UNESCO 1977), the northern part of Nile Delta lies in the arid region, while the southern part in the hyper-arid region. The climatic conditions are warm summers (20–30 °C) and mild winters (≥10 °C). The long-term annual mean air temperature decreases from 20.7 °C at the north to 19.9 °C at the middle of Nile Delta. The relative humidity decreases in the same direction from 69 to 65%. The average daily evaporation varies between 4.6 mm day−1 at the north and 6.8 mm day−1 at the middle. This is associated with an inverse gradient of annual precipitation where the annual rainfall varies between 175.2 mm year−1 at the north and 56.9 mm year−1 at the middle (EMA 1980).

2.2 Soil sampling

The main physiographic soil units in the study area are: alluvial plain (71.1%), lacustrine plain (19.3%), and marine plain (9.6%). Principal soils of the study area include Typic Torrifluvents, Vertic Torrifluvents, Typic Aquisalids and Typic Natrargids sub-great groups in alluvial plain; Typic Natrargids and Sodic Aquicambids in lacustrine plain; Typic Torripsamments sub-great group (see Elbasiouny et al. 2014). Ten sampling stations were selected to represent the north Nile Delta during May 2014. The sampling area was classified according to the dominant land-uses (crop land, permanent fish farm and virgin land). Virgin land is a wild and uninhabited area left in its natural condition with sparse vegetation such as Arthrocnemum macrostachyum (Moric.) K. Koch, Cressa cretica L., Halocnemum strobilaceum (Pall.) M. Bieb., Juncus acutus L., Phragmites australis (Cav.) Trin. ex Steud. and Tamarix nilotica (Ehrenb.) Bunge. Crop land was classified according to the cultivation history to 5, 15, 30 and 50 years old, and under each cultivation history to three crop types: clover (Trifolium alexandrinum L.), sugar beet (Beta vulgaris L.) and rice (Oryza sativa L.) fields. The age of the fish farms was 15 years and the average water depths ranged between 100 and 150 cm and soil sampling carried out along the shores where water depth less than 20 cm. In each of the sampling station, 4 sampling sites were selected to represent the virgin land, 4 to represent fish farm and 12 to represent crop land (four cultivation histories: 5, 15, 30 and 50 years × three crop types: clover, sugar beet and rice). Three soil cores were taken in each sampling site, spaced in a triangular pattern with 50 cm between each core, and were pooled together into one composite core per sampling site. One sample from each of the four soil layers (0–30, 30–60, 60–90 and 90–120 cm) at each of the 200 sampling sites, in total, 800 soil samples were collected to determine SBD, SOC content, and SOC stock.

Within the field of SOC sequestration research, attention has recently been drawn to sub-soils, since they store approximately 53% of the SOC in the 0–100 cm layer and 71% between 0 and 200 cm depth (Batjes 2014). In addition, sub-soils have attracted interest because SOC radiocarbon age increases with depth (Gleixner 2013) in all soil types (Mathieu et al. 2015), leading to the assumption that sub-soil SOC is highly stable (Alcántara et al. 2016). Thus, the soil samples were collected with a 7-cm-diameter hand sediment corer down to 120 cm depth. The soil core was removed from the corer slowly, and it was immediately sectioned with a blade into samples each of 30 cm thick (0–30, 30–60, 60–90 and 90–120 cm) and packed in plastic containers. The sample containers were sealed with parafilm and stored on ice to minimize microbial activity until analysis (Bernal and Mitsch 2008).

2.3 Analysis of soil organic carbon

Each soil sample was oven-dried at 105 °C for 3 days, cooled down to room temperature in a desiccator, and weighed to determine the SBD (g cm−3) following the method of Wilke (2005). Dry samples were ground and sieved to pass through 2-mm particle size, and the mass of fine soil was determined. Each sample was analyzed for SOC content by measuring soil organic matter (SOM) using loss-on-ignition method at 550 °C for 2 h as described in Jones (2001). SOC stock (kg C m−2), expressed as a mass per unit surface area to a fixed depth of a profile, was calculated following the method of Poeplau et al. (2017). The carbon sequestration in crop land (for each crop type) was determined by subtracting the value of SOC stocks at virgin soil from the value of SOC stocks after 5, 15, 30 and 50 years’ cultivation; and in fish farm was determined by subtracting the value of SOC stocks at virgin soil from the value of fish farm SOC stocks (15 years old) (Brar et al. 2013). The annual rate of SOC sequestration was calculated by changes in SOC stocks over total number of years.

2.4 Statistical analysis

Before performing the analysis of variance (ANOVA), the data were tested for their normality of distribution and homogeneity of variance, and when necessary, data were log-transformed. Two-way ANOVAs were used to identify statistically significant differences in SBD and SOC content among each of the land-use types and soil depth; cultivation histories and soil depth; and crop types and soil depth. Significant differences between means among the three land-uses, the five cultivation histories, the four crop types and the four soil depths were identified using the least significant difference (LSD) test at P < 0.05. The relationship between SOC content and SBD was examined with non-linear regression (Eid and Shaltout 2013, 2016; Eid et al. 2016). The significance of variation in SOC stock over the land-use types, cultivation histories and crop types was assessed using one-way ANOVA. The relationship between the cultivation history and its SOC stock for crop land was examined with a linear regression (Shrestha and Lal 2010). All statistical analyses were performed using SPSS 15.0 software (SPSS 2006).

3 Results

Total mean of SBD increased non-significantly from 1.31 g cm−3 at depth 0–30 cm up to 1.33 g cm−3 at depth 30–60 cm, and then slightly decreased to 1.30 g cm−3 at depth 90–120 cm (Table 1). SBD of the virgin land (1.38 g cm−3) was significantly higher than that of the crop land (1.30 g cm−3) (Figs. 1, 2). Cultivation history significantly affected SBD and the minimum value was recorded in crop land cultivated for 50 years (1.28 g cm−3). Crop type significantly affected SBD and the minimum value was recorded in crop land cultivated by clover (1.15 g cm−3).

Table 1 Total distribution (mean ± standard error) of soil bulk density (g cm−3) and soil organic carbon (SOC) content (g C kg−1) with soil depth in north Nile Delta, Egypt
Full size table
Fig. 1
figure 1

Mean distribution of soil bulk density (g cm−3) with soil depth (cm) in north Nile Delta, Egypt. Horizontal bars indicate the standard errors of the means. F values represent the two-way ANOVAs. *P < 0.05, ***P < 0.001, ns not significant (i.e., P > 0.05)

Full size image
Fig. 2
figure 2

Total mean ± standard error of soil bulk density (g cm−3) considering the entire soil profile (0–120 cm) in north Nile Delta, Egypt. F values represent the one-way ANOVA

Full size image

Total mean of SOC content declined significantly with depth from 9.7 g C kg−1 at depth 0–30 cm (43% of the SOC content was found in that depth) to 2.9 g C kg−1 at depth 90–120 cm (Table 1). The SOC content of the crop land (6.5 g C kg−1) was significantly higher than that of the fish farm (5.2 g C kg−1) and virgin land (3.8 g C kg−1) (Figs. 3, 4). Cultivation history significantly affected the SOC content and maximum value was in crop land cultivated for 50 years (7.3 g C kg−1). Crop type significantly affected the SOC content and maximum value was in crop land cultivated by rice (7.4 g C kg−1). As expected, an exponential function was developed between SBD (g cm−3) and SOC content (g C kg−1) for Egyptian north Nile Delta soils where SOC content and SBD were negatively correlated (Table 2).

Fig. 3
figure 3

Mean distribution of soil organic carbon content (g C kg−1) with soil depth (cm) in north Nile Delta, Egypt. Horizontal bars indicate the standard errors of the means. F values represent the two-way ANOVAs. **P < 0.01, ***P < 0.001

Full size image
Fig. 4
figure 4

Total mean ± standard error of soil organic carbon content (g C kg−1) considering the entire soil profile (0–120 cm) in north Nile Delta, Egypt. F values represent the one-way ANOVA

Full size image
Table 2 Equations used for the predicting of soil bulk density, SBD (g cm−3) using soil organic carbon (SOC) content (g C kg−1) in north Nile Delta, Egypt
Full size table

Significant differences in SOC stock were found related to land-use (Fig. 5). Considering the entire soil profile, 0–120 cm, virgin land (4.1 kg C m−2) showed significantly lower values than fish farm (6.2 kg C m−2) and crop land (6.6 kg C m−2). Cultivation history significantly affected the SOC stock and maximum value was in crop land cultivated for 50 years (7.2 kg C m−2). Crop type significantly affected the SOC stock and maximum value was in crop land cultivated by rice (7.5 kg C m−2). There was a strong correlation between the cultivation history and SOC stock for crop land. Thus, SOC stock of crop land can be estimated from the cultivation history using this equation:

Fig. 5
figure 5

Total summation (mean ± standard error) of soil organic carbon stock (kg C m−2) considering the entire soil profile (0–120 cm) in north Nile Delta, Egypt. F values represent the one-way ANOVA

Full size image

SOC stock (kg C m−2) = 5.3 + 0.04 × cultivation history (years), R 2 = 0.134, F value = 54.4, P < 0.001.

The average CSR of crop land was 352, 134, 88 and 62 g C m−2 year−1 for 5, 15, 30 and 50 years of cultivation, respectively. The highest CSR (545 g C m−2 year−1) was observed in crop land cultivated for 5 years by rice, while the lowest (21 g C m−2 year−1) was observed in crop land cultivated for 50 years by sugar beet. On the other hand, the average CSR of fish farm was 143 g C m−2 year−1.

4 Discussion

Soil bulk density (SBD) is needed for estimating soil water retention characteristics and it is an essential input parameter for sediment, water and nutrient transport models (Boucneau et al. 1998). Furthermore, SBD is used as an indicator of site productivity, soil strength, porosity and/or mechanical resistance to plant growth, and can thus affect distribution of SOC (Drewry et al. 2008; Tamminen and Starr 1994). SBD influences agriculture by restricting air and water movement and has been recognized as a key soil quality indicator (Andrews et al. 2002). Land-use can affect SBD (Chen 2000), as reported in the present study. SBD of crop land was inversely related to the cultivation history, indicating a decrease in soil compaction with an increase in cultivation period. The decrease in SBD over the years could be attributed to the addition of roots (SBD has been found to correlate negatively with roots density, Salifu et al. 1999) and plant biomass, which might have increased the biological activities of the soil, and to the conversion of some micro-pores into macro-pores due to cementing action of organic acids and polysaccharides formed during the decomposition of organic residues by higher microbial activities (Shrestha and Lal 2010; Sombrero and de Benito 2010).

Field sampling and direct measurement of SBD is considered labor intensive, costly, time consuming, and often boring (Boucneau et al. 1998). To outdo this problem, Pedo Transfer Functions (PTFs) are frequently used to estimate SBD (De Vos et al. 2005). PTFs are empirically determined by regression (Jalabert et al. 2010) where SBD generally has been based on SOC content only (Périé and Ouimet 2008; Kobal et al. 2011), and less commonly on further variables, such as soil texture (Bernoux et al. 1998; De Vos et al. 2005). In dataset of De Vos et al. (2005), models based on SOC content account for 55–57% of the total variation in SBD, while soil texture explains only 20–26% which in1dicates that SOC content alone accounted for twice as much variability as soil texture. Thus, simple models based on SOC content only are suitable and easy to use (De Vos et al. 2005). In the present study, we developed a negative exponential function for Egyptian north Nile Delta soils, where SBD increased and SOC content decreased with soil depth. It is similar to the result of Yang et al. (2007) who developed a negative exponential function with SOC content for Chinese soils. In addition, Abdelbaki (2016) evaluated the performance of 48 published PTFs that required inputs of OM and SOC contents and particle size distribution for predicting SBD. He found that the exponential PTF (SBD = 1.838 × e−0.006 × SOC content) which required input of SOC contents only is the best PTF which demonstrated best performance and this indicated the great effect of the SOC contents on SBD predictions. Estimation of SBD in organic soils through PTFs is particularly problematic, and sometimes no relationship has been found between SBD and SOC content (Vanguelova et al. 2016). Thus, in the present study, despite the statistical significance of exponential functions, most r coefficients are often very low (Table 2). As reported in some previous studies (Howard et al. 1995; De Vos et al. 2005; Yu et al. 2007; Périé and Ouimet 2008; Eid and Shaltout 2013, 2016; Eid et al. 2016), SOC content and SBD were negatively correlated. This indicates that this negative relationship between SBD and SOC content is valid across varying soil types and geographical regions.

The comparison of SOC content between virgin land, crop land and fish farm gives a unique opportunity to compare the SOC stocks under different land-use types and to evaluate the long-term carbon sequestration in crop lands and fish farms over time. The present study shows that the effect of land-use types and soil depth, as well as their interaction on SOC contents as well as SOC stocks are significant, and these results were consistent with previous relevant studies (Chen et al. 2007; Fang et al. 2012). We found that SOC content is greatest in the surface soil where most carbon inputs occur, and decreases with depth. This is so in agreement with previous studies which indicated that the surface soil is more active for SOC sequestration (Munoz-Rojas et al. 2012; Zhang et al. 2013), while only few soils show a different pattern. Land-use and degree of development of the soil as well as the soil type are the important factors influencing the vertical distribution of SOC in the soils (Parras-Alcántara et al. 2015; Vanguelova et al. 2016). Moreover, this variation could also be a result of interaction of complex processes such as decomposition, land management, biological cycling, leaching, illuviation, soil erosion, weathering of minerals, atmospheric deposition and application of manure (Lorenz and Lal 2005; Girmay and Singh 2012).

The content of SOC in the 0–30 cm soil depth accounts for 43% of the total content of SOC in the soil indicating the importance of topsoil layers as good sources of carbon sink, but also as a potential for large amount of CO2 emission upon conversion and mismanagement. Similar results were reported by Yimer et al. (2006) in Ethiopia who found that 45% of the SOC content was in the top 30 cm of the soil profile, and by Batjes (2002) who indicated that about 44% of the total SOC stock down to 100 cm soil depth was situated within the top 30 cm of the soil, where as a corresponding 55–65% was measured by De Vos et al. (2015) for European forest soils.

In the present study, SOC content and SOC stock in virgin land is about 42 and 38% lower than in the crop land in North Nile Delta. The high mean SOC content as well as SOC stock for soils under agricultural land-use can be attributed to a decrease in soil erosion because of vegetation protection and agricultural practices, such as fertilization, irrigation, addition of manure, which can increase plant production and the rate of plant residue return into soil (Rasmussen and Collins 1991; Han et al. 2010; Fallahzade and Hajabbasi 2012). On the other hand, the high SOC content and SOC stock in the fish farm soils could be ascribed to the prolonged saturation (anoxic conditions) of soils under this land-use, which have slower decomposition rates of litter and soil organic matter (Bouchard and Cochran 2006).

Further, the current study points out that, high SOC content and SOC stock under rice compared with clover and sugar beet may be attributed to greater aboveground biomass production and favorable water regime under rice fields (Kukal et al. 2009). In the study of Chiti et al. (2012) in Italy, the rice field soils showed a higher mean SOC stock than the other arable land soils. In China, the results of Huang et al. (2012) showed that rice cropping significantly increased SOC stocks by 9%. Pan et al. (2010) reported that rice paddies not only held higher SOC stocks compared with dry croplands in China, but showed greater sequestration rates. Sahrawat (2004) concluded that there is preferential accumulation of OM in submerged rice soils as compared with aerobic soils due to incomplete decomposition of organic materials, and decreased humification of OM under flooded conditions. In addition, Hanke et al. (2013) in their investigation reported that carbon accumulation in rice soils may result from a microbial community well adapted to anoxic conditions, but less efficient in mineralizing carbon during transient oxic periods. Hence, the increased SOC content and SOC stock with time in rice soils is probably due to less degradation under oxic conditions (Bossio and Scow 1995).

Our results show that when virgin land was converted into crop land or fish farm, SOC stock to a 120-cm depth increased by 60 or 52%. The study of Zhang et al. (2014) suggested that converting virgin land to crop land in arid region of the Yanqi Basin, China, not only enhances SOC stocks, but also leads to longer-term SOC storage. Converting virgin land to crop land in the north Nile Delta results in an increase of SOC stock (0–120 cm) by 2.5 kg C m−2. Zhang et al. (2014) reported that conversion from virgin land to irrigated crop land increased SOC stock (0–100 cm) by 3.7 kg m−2, while Zhang et al. (2012) reported that conversion from desert steppe to crop land in China led to increase in SOC stock from 3.9 to 5.1 kg m−2 in the top 100 cm as a result of 20 years of cropping. These results imply that the longer the cropping is, the greater the SOC stock increase will become.

In general, SOC content and SOC stock increased with the increase in cultivation history of crop land. Similar increase in SOC content and SOC stock with increase in cultivation history under cultivated land was reported in the Netherlands (Reijneveld et al. 2009), under forest in Germany (Fettweis et al. 2005) and under forest in USA (Shrestha and Lal 2010). Estimates in this study show that, after 50 years of cultivation, SOC stock increased by 76% in crop land compared with those of the initial stock (virgin land). The cultivation history is important to understand temporal changes in ecosystem carbon stock in reclaimed soils (Knops and Tilman 2000), especially because initial soil properties are often unknown. Several cultivation history studies (Rumpel et al. 1999; Maharaj et al. 2007; Shrestha and Lal 2010) have reported accumulation of SOC stock over time in cultivated soils. However, ecosystem processes and the long-term changes in SOC stock in cultivated soil land-uses are poorly understood. Shrestha and Lal (2010) found an increase in SOC stock with increase in the cultivated history in forest and pasture ecosystems. Some studies carried out in Europe indicated an increase of SOC stock with increasing cultivation history (see Nieder and Richter 2000). Increase in SOC content as well as SOC stock with cultivation history may be due to increase in soil microbial biomass (Sourkova et al. 2005), accumulation and incorporation of the aboveground biomass, litter and roots (Shrestha and Lal 2010).

Regional variations in SOC stocks could be related to a number of natural factors (climate, parent material, landscape position and elevation, site-specific conditions such as soil texture, soil mineralogy, pH and drainage; Tan et al. 2004; Leifeld et al. 2005; von Lützow et al. 2006; Yu et al. 2007) and human activities (land-use type, management intensity; Somaratne et al. 2005). Considering the entire soil profile (0–120 cm), the range SOC stock in the north Nile Delta crop land was 5.5–7.5 kg C m−2 which compared to the range reported for crop land soils from China (Table 3). In contrast, it is higher than those reported for tropical and subtropical crop land soils from India and for subtropical crop land from USA. In addition, it is lower than those reported for temperate crop land soils from Europe. The highest SOC stock in temperate climates in Europe may be attributed to the low soil temperature that probably supported high vegetative growth and rapid root proliferation (Singh et al. 2011). In addition, Chiti et al. (2012) reported a decrease of the SOC stock from the temperate regions toward the Mediterranean ones. The lowest SOC stock in tropical and subtropical climates may be attributed to the greater decomposition due to high temperature (Eid et al. 2014). Worldwide, SOC stocks generally increase as mean annual temperature decreases (Post et al. 1982).

Table 3 Soil organic carbon (SOC) stock (kg C m−2) in the crop land soil of north Nile Delta, Egypt, compared with those reported in other studies
Full size table

Our study calculated an SOC accumulation rate of about 62 g C m−2 year−1 in the 120 cm for 50 years of cultivation; this finding supports previous results such as those by Yu et al. (2009) who suggested a large potential for organic carbon sequestration in the cultivated soils. The previous results (Table 4) reflect a high variability in SOC accumulation rates, which depend on several factors such as the climate zone, crop species, biomass accumulation rates, cultivation history, time of restoration and soil type (Post and Kwon 2000; Guo and Gifford 2002).

Table 4 Soil organic carbon (SOC) accumulation rate (g C m−2 year−1) in the soil of north Nile Delta, Egypt, compared with those reported in other studies
Full size table

5 Conclusion

The aims of the present study are: (1) to quantify the vertical distribution of the soil bulk density (SBD) and SOC content in the soil of north Nile Delta, Egypt, under different types of land-use; (2) to provide estimates of the carbon sequestration rate (CSR) of those soils under different types of land-use; and (3) to establish a baseline data on SOC stocks for future studies on SOC dynamics. Effect of crop type was significant on SBD, SOC content, and SOC stock. Soil bulk density decreases as soil organic carbon content increases. SOC stock under crop land and fish farm were 1.6 and 1.5 times as that of virgin land. SOC stock increases as the number of years of cultivation increases. Rice was the crop with less SBD and more soil organic carbon stock. Conversion of virgin land into crop land or fish farm contributed to SOC sequestration. In conclusion, crop lands may be the optimal choice for SOC sequestration in the north Nile Delta. Crop land with rice and clover are also recommended for their great contribution to SOC storage in the area.