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Changes in soil organic carbon and other physical soil properties along adjacent Mediterranean forest, grassland, and cropland ecosystems in Turkey
ARTICLE IN PRESS Journal of Arid Environments Journal of Arid Environments 59 (2004) 743–752 www.elsevier.com/locate/jnlabr/yjare
Changes in soil organic carbon and other physical soil properties along adjacent Mediterranean forest, grassland, and cropland ecosystems in Turkey F. Evrendileka,*, I. Celikb, S. Kilicc a
Department of Landscape Architecture, Faculty of Agriculture, Mustafa Kemal University, Antakya-Hatay 31034, Turkey b Department of Soil Science, C - ukurova University, Balcali-Adana 01330, Turkey c Department of Soil Science, Mustafa Kemal University, Antakya-Hatay 31034, Turkey
Received 16 July 2003; received in revised form 6 February 2004; accepted 5 March 2004
Abstract Cultivation, overgrazing, and overharvesting are seriously degrading forest and grassland ecosystems in the Taurus Mountains of the southern Mediterranean region of Turkey. This study investigated the effects of changes on soil organic carbon (SOC) content and other physical soil properties over a 12-year period in three adjacent ecosystems in a Mediterranean plateau. The ecosystems were cropland (converted from grasslands in 1990), open forest, and grassland. Soil samples from two depths, 0–10 and 10–20 cm, were collected for chemical and physical analyses at each of cropland, open forest, and grassland ecosystems. SOC pools at the 0–20 cm depth of cropland, forest, and grassland ecosystems were estimated at 32,636, 56,480, and 57,317 kg ha1, respectively. Conversion of grassland into cropland during the 12-year period increased the bulk density by 10.5% and soil erodibility by 46.2%; it decreased SOM by 48.8%, SOC content by 43%, available water capacity (AWC) by 30.5%, and total porosity by 9.1% for the 0–20 cm soil depth (po0:001). The correlation matrix revealed that SOC content was positively correlated with AWC, total porosity, mean weight diameter (MWD), forest, and grassland, and negatively with bulk density, pH, soil erodibility factor, and cropland. The
*Corresponding author. Tel.: +90-326-245-5735; fax: +90-326-245-5832. E-mail address: [email protected] (F. Evrendilek). 0140-1963/$ - see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.jaridenv.2004.03.002
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multiple regression (MLR) models indicated that any two of the three ecosystems and one of the two soil depths accounted for 86.5% of variation in mean SOC values ((po0:001). r 2004 Elsevier Ltd. All rights reserved. Keywords: Land use; Land cover; Soil organic carbon; Mediterranean plateau; Environmental degradation
1. Introduction Carbon (C) sinks and sources in ecosystems are a dynamic function of net primary and secondary productivity, humification, decomposition and mineralization of soil organic matter (SOM), and human and natural disturbances. Globally, soils, vegetation, and the atmosphere contain about 17507250, 5507100, and 760 Pg C (1 Pg C=1015 g of C), respectively (IPCC, 2001). On an annual basis, global ecosystems remove about 120 Pg C by primary productivity from the atmosphere and return about 60 Pg C by plant respiration, 55 Pg C by soil respiration, and 4 Pg C by biomass burning to the atmosphere (Schlesinger, 1995). Local and regional human-induced disturbances of C fluxes and stocks are associated with increases in atmospheric CO2 concentration, air temperature, and extreme climatic events at the global scale (Melillo et al., 1993). These disturbances result primarily from changes in land use and land cover (LULC), and from combustion of fossil fuels and biomass. These disturbances have important consequences for the sustenance of ecological goods and services regionally and globally (Evrendilek and Doygun, 2000; Evrendilek and Wali, 2001). Globally, over the past 250 yr about 200 Pg C were released to the atmosphere as a result of changes in LULCs (Scholes and Noble, 2001). The global average conversion rate of forests to cropland during the 1990s was estimated at 12 Mha yr1 (Bouwman and Leemans, 1995). Approximately 1.7 and 0.1 Pg C yr1 are being lost to the atmosphere by deforestation and erosion, respectively (Bruce et al., 1999). Local changes in LULCs and in agricultural, grassland, and forestry practices can help to reduce the global rise of CO2 emissions in the atmosphere (Wali et al., 1999; Evrendilek and Ertekin, 2002). Currently, terrestrial vegetation and soils have a net sequestration of about 1.5 Pg C yr1 (ca. 23% of the global CO2 emissions from fossil fuels) (e.g. Melillo et al., 1993; Houghton, 2000). Political factors, socio-economic factors, and different sequestration capacities of management options increase uncertainty in estimates of terrestrial C sinks. However, the IPCC estimated a total sequestration potential of between 1.53 and 2.47 Pg C yr1 between 2000 and 2050 globally by agricultural management (33%), tropical regeneration (18%), topical forestation (15%), slowing deforestation (14%), temperate forestation (13%), tropical agroforestry (6%), and temperate agroforestry (1%) (IPCC, 1996, 2001). Ecosystems of Turkey at elevations of 1500 m and higher and slope range of 15% to 40% account for about 26% and 34% of the total land area of 759,978 km2, respectively (Atalay, 1997). Overgrazing, deforestation, and increase in agricultural activity have intensified pressures on high-altitude fragile ecosystems. Degradation
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of vegetation and soil leads to irreversible loss of biological productivity, thus diminishing well-being of highland communities and ecosystems (Nardi et al., 1996; Islam et al., 1999). The objective of this study was to quantify effects of changes in three adjacent ecosystems (forest, grassland, and cropland) in a high-altitude Mediterranean plateau on soil organic carbon (SOC) and other physical soil properties.
2. Material and methods 2.1. Study area The study area is located in the central Taurus mountains of the southern Mediterranean region of Turkey at an altitude of about 1400 m above sea level (37 110 N, 34 380 E). The study area is a plateau lying in east to west and covers 240 ha of which open forest occupies 90 ha, grassland 80 ha, and cropland 70 ha. The prevailing climate of the study area is a typical Mediterranean climate with the longterm mean annual temperature and precipitation of 14 C and 850 mm, respectively. About 70% of precipitation falls during the winter and spring (November–May). Dominant soils in the study area are Typic Haploxeroll (Soil Survey Staff, 1998). On average, the soil depth is 45–55 cm with a slope ranging from 8% to 10%. The soil at the experimental site was very shallow and silty clay composed of 19.6% sand, 40.1% silt, and 40.3% clay. No salinity and drainage problems exist, and soil pH, CaCO3 and soluble total salt concentration were 7.4, 210 and 5 g kg1, respectively. Dominant tree species in the forests are Pinus nigra, P. brutia, and Cedrus libani which are replaced by Juniperus excelsa in the process of human-induced regressive succession. Plant cover of the grassland ranges from 90% to 60% depending on the severity of grazing. Dominant grass species include Chrysopogon gryllus, Festuca ovina, Bothriochloa ischaemum, Globularia trichosantha, Plantago lagopus, Lotus corniculatus, and Teucrium polium. Some grasslands have been converted to continuous barley (Hordeum vulgare L.) and wheat (Triticum aestivum L.) in a rotational manner since 1990. 2.2. Soil sampling and analyses In August 2002, soil samples were collected from four sites under each of the three adjacent ecosystems: (1) open forest, (2) grassland, and (3) cropland. For each site, four soil samples were randomly taken for chemical analysis, and four soil samples for physical analysis. This procedure was repeated for each of the depth ranges of 0– 10 and 10–20 cm, with a total of eight soil samples per one depth. For aggregate analysis, soil samples of approximately 3 kg were taken. The samples were air-dried and sieved through 8 mm sieves. Soil samples for analysis of soil bulk density were taken by using a steel cylinder of a 100-cm3 volume (5 cm in diameter, and 5 cm in height). The soil samples were sieved through a 2 mm meshed sieve for chemical analyses. Bulk density was determined by the core method (Blake and Hartge, 1986),
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particle size distribution by the hydrometer method (Gee and Bauder, 1986), soil organic matter by the Walkey Black method (Schnitzer, 1982), soil pH according to Page et al. (1982), and soil erodibility (USLE K factor) according to Wischmeier and Smith (1978) as follows: K ¼ 2:8M 1:14 ð107 Þð12-OMÞ þ 4:3ð103 ÞðS 2Þ þ 3:3ð103 ÞðP 3Þ;
ð1Þ
where M is the particle size parameter calculated as (silt, %+very fine sand, %) (100-clay, %), OM organic matter (%); S soil structure code (1=very fine granular, 2=fine granular, 3=medium or coarse granular, 4=block, platy, or massive); and P the profile-permeability class (1=rapid, 2=moderate to rapid, 3=moderate, 4=low to moderate, 5=slow, 6=very slow). Water retention capacity at 33 kPa (field capacity) was measured in the soil samples taken for analysis of bulk density and at 1500 kPa (permanent wilting point) in the soil samples taken for analyses of other physical and chemical properties. Available water capacity (AWC) was determined as the difference between field capacity and permanent wilting point (Klute and Dirksen, 1986). Total porosity was calculated in the water-saturated samples of 100 cm3 assuming no air trapped in the pores and validated using dry bulk density and a particle density of 2.65 g cm3 (Danielson and Sutherland, 1986). A wet sieving method was used to determine the mean weight diameter (MWD) as indices of the soil aggregation. The wet sieving method of Kemper and Rosenau (1986) was used with a set of sieves of 4, 2, 1, and 0.5 mm in diameter. After the soil samples were passed through an 8 mm sieve, approximately 50 g of the soil was put on the first sieve and gently moistened to avoid a sudden rupture of aggregates. After the soil had been moistened, the set was sieved in distilled water at 30 oscillations per minute. After 10 min of oscillation, the soil remaining on each sieve was dried, and then sand and aggregates were separated (Gee and Bauder, 1986). The MWD was calculated as follows: n X MWD ¼ Xi Wi ; ð2Þ i¼1
where Xi is the mean diameter of each size fraction (mm), and Wi the proportion of the total sample mass in the corresponding size fraction after deducting the mass of stones (upon dispersion and passing through the same sieve) as indicated above. SOC content for the soil depths of 0–10 and 10–20 cm was calculated for each of the ecosystems, based on SOC=0.58 SOM as follows: SOCðkg ha1 Þ ¼ ð%SOC=100Þ soil massðkg ha1 Þ; 1
where soil mass (kg ha )=depth 10,000 m2 ha1 1000 kg Mg1.
(m) bulk
ð3Þ density
3
(Mg m )
2.3. Data analysis Data analyses were carried out using Minitab (version 13.32). General linear model (GLM) was used to assess the effects of ecosystem type, soil depth, and their
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interaction on SOC. Tukey’s HSD procedure was used for multiple comparisons of mean physical and chemical properties of the soil depths (0–10, 10–20, and 0–20 cm) among the ecosystems (cropland, open forest, and grassland) at po0:05 level. Pearson’s correlation coefficients (r) were determined for the correlation matrix of all the variables (bulk density, SOC, SOM, plant-available water, clay content, USLE K soil erodibility factor, total porosity, pH, MWD, and the three ecosystems). Multiple linear regression (MLR) models were developed to relate the response variable of SOC to the indicator variables of the three ecosystems and the two depths as follows: SOC ¼b0 þ b1 Ecosystem1 þ b2 Ecosystem2 þ b3 Depth1 ;
ð4Þ
where b0 ; b1 ; b2 ; and b3 are regression coefficients of the indicator variables which estimate how much SOC will change in the presence of each ecosystem and each depth, with the other variables held constant.
3. Results The GLM showed that ecosystem type and soil depth affected the measured content of SOC (po0:001), but did not have a significant interactive effect on SOC (p > 0:05). For the soil depth of 0–20 cm, 21.1 g SOM kg1 in the cropland soil differed significantly from 38.8 g SOM kg1 in the forest soil and 41.3 g SOM kg1 in the grassland soil (po0:001), while the forest and grassland soils did not differ in SOM (p > 0:05). The mean SOM concentration of 36.6 g kg1 in the 0–10 cm layer was significantly higher than 30.9 g kg1 in the 10–20 cm layer, regardless of the differences in the ecosystems (po0:001). A multiple comparison of physical and chemical properties of the adjacent cropland, forest, and grassland soils is provided for each of the two soil depths (Table 1). The concentrations of SOM in the 0–10 and 10–20 cm layers of the cropland soil were 43.7% and 47.7% lower than those of the forest soil and 47.5% and 50.3% lower than those of the grassland soil, respectively (po0:05). The correlation matrix revealed that SOC content was correlated positively with AWC, total porosity, MWD, forest, and grassland, and negatively with bulk density, pH, USLE K factor, and cropland (Table 2). The cropland soil had a higher bulk density than the adjacent forest and grassland soils in both depths (po0:05). The grassland and forest soils did not differ in bulk density in the 0–10 cm layer but differed in the 10–20 cm layer (Table 1). On average, AWC in the 0–10 cm layer of the cropland soil was 44.4% and 35.5% less than the forest and grassland soils, respectively. In the 10–20 cm layer, the forest soil had the highest AWC of 0.156 m3 m3 and was different from AWC of 0.119 and 0.090 m3 m3 in the grassland and cropland soils, respectively (po0:05). The cropland, forest, and grassland soils had similar contents of sand, silt and clay, and pH in both depths (p > 0:05). Soil erodibility factor was greater in the cropland than in the forest site (po0:05). The cropland soil had a lower total porosity than the forest and grassland soils in both depths (po0:05). The meanweight diameter of aggregates was significantly greater in the forest and grassland
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Soil properties
3
Soil texture (%) Sand Silt Clay pH (1:2.5) USLE K factor Total porosity (m3 m3) MWD (mm)
Forest
Grassland
0–10 cm
10–20 cm
0–20 cm
0–10 cm
10–20 cm
0–20 cm
0–10 cm
10–20 cm
0–20 cm
1.3070.017a 23.4371.6a 17666716a 0.08970.007a
1.3770.021a 18.8475.2a 14970763a 0.09070.008a
1.3370.043a 21.1374.3a 326367214a 0.08970.007a
1.2470.027b 41.6173.5b 29926755b 0.16070.019b
1.27+0.024b 36.0571.0b 26554714b 0.15670.013b
1.2570.030b 38.8373.8b 564807132b 0.15870.015b
1.2370.032b 44.6071.8b 31818733b 0.13870.006b
1.1670.043c 37.9073.9b 25499797b 0.11970.009c
1.1970.050c 41.2774.5b 573177261b 0.12870.012c
20.076.3a 41.074.8a 39.077.4a 7.770.08a 0.2670.058a 0.5170.006a
19.077.2a 42.076.4a 39.077.7a 7.770.12a 0.2770.064a 0.4870.008a
20.076.3a 41.075.2a 39.077.0a 7.770.10a 0.2670.057a 0.5070.016a
19.077.6a 38.078.3a 43.0715.8a 7.170.46a 0.1170.087b 0.5370.011b
20.078.3a 36.0710.9a 44.0719.0a 7.370.65a 0.1170.099b 0.5270.009b
20.077.3a 37.079.0a 43.0716.2a 7.270.54b 0.1170.086b 0.5370.011b
18.073.6a 43.073.6a 39.073.3a 7.270.23a 0.1470.017ab 0.5470.012b
21.074.5a 41.073.3a 38.071.4a 7.570.12a 0.1470.024ab 0.5670.017c
20.074.0a 42.073.3a 38.072.3a 7.470.22ab 0.1470.020b 0.5570.019c
1.3070.3a
1.2970.5a
1.2970.4a
3.1070.5b
2.6770.7b
2.8970.6b
3.5970.8b
3.4170.8b
3.5070.7b
Means in each row followed by the same letters are not significant at po0:05 (n ¼ 4 for 0–10 cm and 10–20 cm and n ¼ 8 for 0–20 cm). S.D.: standard deviation, BD: bulk density, SOM: soil organic matter, SOC: soil organic carbon, AWC: available water capacity, K: USLE soil erodibility factor, MWD: mean weight diameter.
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BD (Mg m ) SOM (g kg1) SOC (kg ha1) PAW (m3 m3)
Cropland
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Table 1 Comparisons of some physical and chemical properties (means7S.D.) of adjacent cropland, forest, and pasture soils for two depths of 0–10 and 10–20 cm
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Table 2 Correlation matrix of soil properties and adjacent land use and land cover types (LULCs) (Pearson’s correlation coefficients, r)
SOC BD SOM AWC Cropland Forest Grassland pH K TP
BD
SOM
0.64
0.99 0.78 0.89 0.74 0.44 0.75 0.76 0.91 0.84
AWC
Cropland Forest 0.42
Grassland pH
0.47 0.59 n.s. 0.68 n.s. n.s. 0.54 0.58 0.77 n.s. 0.50 0.50 0.50 0.53 0.50 0.46 0.46
K
TP
MWD
0.74 0.64 0.81 0.54 1.0 0.61 0.74 0.74 0.82 0.58 0.45 0.63 0.75 0.75 0.83 0.49 n.s. n.s. 0.49 0.67 n.s. n.s. 0.73 n.s. 0.54 0.59 0.61
, , and refer to pp0:05; pp0:01; and pp0:001; respectively; n.s.: not significant at pp0:05:
SOC: soil organic carbon, BD: bulk density, SOM: soil organic matter, AWC: available water capacity, K: USLE soil erodibility factor, TP: total porosity, MWD: mean weight diameter. Soil depths of 0–10 and 10– 20 cm, and soil texture were not included in the table as none of their correlations with any of the other variables were significant at pp0:05:
soils than the cultivated soils (Table 1). On average, cultivation caused a 55% decrease for the 0–10 cm layer and a 63% decrease for the 10–20 cm layer in MWD of the cropland soil relative to the forest and grassland soils, respectively (po0:05). SOC accumulations of the cropland, forest and grassland soils were estimated at 32,636, 56,480, and 57,317 kg ha1 for the soil depth of 0–20 cm, respectively. The MLR models were estimated to describe the relative importance of, and the nature of relationships among the cropland, forest, and grassland soils. The MLR models had a high F value (the model utility test) and R2 value (the coefficient of determination) (po0:001). Any one of the two soil depths and any two of the three ecosystems accounted for 86.5% of the variation in mean SOC contents. The MLR models revealed that conversions from the forest and grassland to the cropland increased the mean loss of SOC by 96.5% and 96.6%, respectively. Mean SOC accumulation for the soil depth of 0–10 cm was 12,366 kg ha1 higher in the grassland and 11,932 kg ha1 higher in the forest than in the cropland. Mean SOC was 4050 kg ha1 higher in the 0–10 cm depth and negatively associated with the increasing soil depth for all the ecosystems.
4. Discussion The findings indicated that conversion of the grassland into the cropland in the southern Taurus mountains of the Mediterranean region increased bulk density by 10.5% and soil erodibility by 46.2%, and decreased SOM by 48.8%, SOC content by 43.0%, AWC by 30.5% and total porosity by 9.1% during a 12-yr period (po0:05). Hajabbasi et al. (1997) reported that deforestation and subsequent tillage practices resulted in nearly a 20% increase in bulk density and a 50% decrease in SOM for the
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soil depth of 0–30 cm over 20 yr in the central Zagrous mountains in Iran. Cultivation of alpine grassland soils in China for 8, 16, and 41 yr decreased SOC by 25%, 39%, and 55%, respectively, thus rendering soils more susceptible to erosion (Wu and Tiessen, 2002). Increased SOM improves aggregation, water-holding capacity, nutrient-retention capacity, ion exchange capacity, and biodiversity in soils. Cultivation breaks up soil aggregates, decreases total soil porosity, and accelerates decomposition and mineralization of SOM due to exposures of previously inaccessible SOM to microbial attack (e.g. Sparling et al., 1992; Haynes, 1999; Shepherd et al., 2001). Studies have shown that the removal of vegetation, the loss of SOM, and soils with a low MWD also increased bulk density and soil erosion (e.g. Teixeira and Misra, 1997; Boix-Fayos et al., 2001; Loveland and Webb, 2003). Despite variations as a function of abiotic and biotic factors, mean losses of SOC from grassland and forest soils by conventional tillage practices are estimated to range from 20% to 50% of the initial SOC content in the zone of cultivation within the first 20 to 30 years of cultivation (Post and Mann, 1990; Davidson and Ackerman, 1993; Murty et al., 2002). These SOC losses show a rapid exponential decline in the first 20 years after which SOC levels gradually stabilize at a new steady state over the next 30 or so years. Clearance of forest and grassland for agricultural production, semi-arid climate, and inclined topography render the Mediterranean plateau ecosystems of Turkey unable to recover from some changes in land uses and land covers. Sustainability-oriented practices that assure biological productivity, biodiversity, and soil stability should be considered in management of these ecosystems.
Acknowledgements We thank Prof. M.K. Wali and an anonymous reviewer for valuable comments on a previous version of the manuscript. This research was supported by a research - ukurova University. project grant of C
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Changes in soil organic carbon and other physical soil properties along adjacent Mediterranean forest, grassland, and cropland ecosystems in Turkey F. Evrendileka,*, I. Celikb, S. Kilicc a
Department of Landscape Architecture, Faculty of Agriculture, Mustafa Kemal University, Antakya-Hatay 31034, Turkey b Department of Soil Science, C - ukurova University, Balcali-Adana 01330, Turkey c Department of Soil Science, Mustafa Kemal University, Antakya-Hatay 31034, Turkey
Received 16 July 2003; received in revised form 6 February 2004; accepted 5 March 2004
Abstract Cultivation, overgrazing, and overharvesting are seriously degrading forest and grassland ecosystems in the Taurus Mountains of the southern Mediterranean region of Turkey. This study investigated the effects of changes on soil organic carbon (SOC) content and other physical soil properties over a 12-year period in three adjacent ecosystems in a Mediterranean plateau. The ecosystems were cropland (converted from grasslands in 1990), open forest, and grassland. Soil samples from two depths, 0–10 and 10–20 cm, were collected for chemical and physical analyses at each of cropland, open forest, and grassland ecosystems. SOC pools at the 0–20 cm depth of cropland, forest, and grassland ecosystems were estimated at 32,636, 56,480, and 57,317 kg ha1, respectively. Conversion of grassland into cropland during the 12-year period increased the bulk density by 10.5% and soil erodibility by 46.2%; it decreased SOM by 48.8%, SOC content by 43%, available water capacity (AWC) by 30.5%, and total porosity by 9.1% for the 0–20 cm soil depth (po0:001). The correlation matrix revealed that SOC content was positively correlated with AWC, total porosity, mean weight diameter (MWD), forest, and grassland, and negatively with bulk density, pH, soil erodibility factor, and cropland. The
*Corresponding author. Tel.: +90-326-245-5735; fax: +90-326-245-5832. E-mail address: [email protected] (F. Evrendilek). 0140-1963/$ - see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.jaridenv.2004.03.002
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multiple regression (MLR) models indicated that any two of the three ecosystems and one of the two soil depths accounted for 86.5% of variation in mean SOC values ((po0:001). r 2004 Elsevier Ltd. All rights reserved. Keywords: Land use; Land cover; Soil organic carbon; Mediterranean plateau; Environmental degradation
1. Introduction Carbon (C) sinks and sources in ecosystems are a dynamic function of net primary and secondary productivity, humification, decomposition and mineralization of soil organic matter (SOM), and human and natural disturbances. Globally, soils, vegetation, and the atmosphere contain about 17507250, 5507100, and 760 Pg C (1 Pg C=1015 g of C), respectively (IPCC, 2001). On an annual basis, global ecosystems remove about 120 Pg C by primary productivity from the atmosphere and return about 60 Pg C by plant respiration, 55 Pg C by soil respiration, and 4 Pg C by biomass burning to the atmosphere (Schlesinger, 1995). Local and regional human-induced disturbances of C fluxes and stocks are associated with increases in atmospheric CO2 concentration, air temperature, and extreme climatic events at the global scale (Melillo et al., 1993). These disturbances result primarily from changes in land use and land cover (LULC), and from combustion of fossil fuels and biomass. These disturbances have important consequences for the sustenance of ecological goods and services regionally and globally (Evrendilek and Doygun, 2000; Evrendilek and Wali, 2001). Globally, over the past 250 yr about 200 Pg C were released to the atmosphere as a result of changes in LULCs (Scholes and Noble, 2001). The global average conversion rate of forests to cropland during the 1990s was estimated at 12 Mha yr1 (Bouwman and Leemans, 1995). Approximately 1.7 and 0.1 Pg C yr1 are being lost to the atmosphere by deforestation and erosion, respectively (Bruce et al., 1999). Local changes in LULCs and in agricultural, grassland, and forestry practices can help to reduce the global rise of CO2 emissions in the atmosphere (Wali et al., 1999; Evrendilek and Ertekin, 2002). Currently, terrestrial vegetation and soils have a net sequestration of about 1.5 Pg C yr1 (ca. 23% of the global CO2 emissions from fossil fuels) (e.g. Melillo et al., 1993; Houghton, 2000). Political factors, socio-economic factors, and different sequestration capacities of management options increase uncertainty in estimates of terrestrial C sinks. However, the IPCC estimated a total sequestration potential of between 1.53 and 2.47 Pg C yr1 between 2000 and 2050 globally by agricultural management (33%), tropical regeneration (18%), topical forestation (15%), slowing deforestation (14%), temperate forestation (13%), tropical agroforestry (6%), and temperate agroforestry (1%) (IPCC, 1996, 2001). Ecosystems of Turkey at elevations of 1500 m and higher and slope range of 15% to 40% account for about 26% and 34% of the total land area of 759,978 km2, respectively (Atalay, 1997). Overgrazing, deforestation, and increase in agricultural activity have intensified pressures on high-altitude fragile ecosystems. Degradation
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of vegetation and soil leads to irreversible loss of biological productivity, thus diminishing well-being of highland communities and ecosystems (Nardi et al., 1996; Islam et al., 1999). The objective of this study was to quantify effects of changes in three adjacent ecosystems (forest, grassland, and cropland) in a high-altitude Mediterranean plateau on soil organic carbon (SOC) and other physical soil properties.
2. Material and methods 2.1. Study area The study area is located in the central Taurus mountains of the southern Mediterranean region of Turkey at an altitude of about 1400 m above sea level (37 110 N, 34 380 E). The study area is a plateau lying in east to west and covers 240 ha of which open forest occupies 90 ha, grassland 80 ha, and cropland 70 ha. The prevailing climate of the study area is a typical Mediterranean climate with the longterm mean annual temperature and precipitation of 14 C and 850 mm, respectively. About 70% of precipitation falls during the winter and spring (November–May). Dominant soils in the study area are Typic Haploxeroll (Soil Survey Staff, 1998). On average, the soil depth is 45–55 cm with a slope ranging from 8% to 10%. The soil at the experimental site was very shallow and silty clay composed of 19.6% sand, 40.1% silt, and 40.3% clay. No salinity and drainage problems exist, and soil pH, CaCO3 and soluble total salt concentration were 7.4, 210 and 5 g kg1, respectively. Dominant tree species in the forests are Pinus nigra, P. brutia, and Cedrus libani which are replaced by Juniperus excelsa in the process of human-induced regressive succession. Plant cover of the grassland ranges from 90% to 60% depending on the severity of grazing. Dominant grass species include Chrysopogon gryllus, Festuca ovina, Bothriochloa ischaemum, Globularia trichosantha, Plantago lagopus, Lotus corniculatus, and Teucrium polium. Some grasslands have been converted to continuous barley (Hordeum vulgare L.) and wheat (Triticum aestivum L.) in a rotational manner since 1990. 2.2. Soil sampling and analyses In August 2002, soil samples were collected from four sites under each of the three adjacent ecosystems: (1) open forest, (2) grassland, and (3) cropland. For each site, four soil samples were randomly taken for chemical analysis, and four soil samples for physical analysis. This procedure was repeated for each of the depth ranges of 0– 10 and 10–20 cm, with a total of eight soil samples per one depth. For aggregate analysis, soil samples of approximately 3 kg were taken. The samples were air-dried and sieved through 8 mm sieves. Soil samples for analysis of soil bulk density were taken by using a steel cylinder of a 100-cm3 volume (5 cm in diameter, and 5 cm in height). The soil samples were sieved through a 2 mm meshed sieve for chemical analyses. Bulk density was determined by the core method (Blake and Hartge, 1986),
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particle size distribution by the hydrometer method (Gee and Bauder, 1986), soil organic matter by the Walkey Black method (Schnitzer, 1982), soil pH according to Page et al. (1982), and soil erodibility (USLE K factor) according to Wischmeier and Smith (1978) as follows: K ¼ 2:8M 1:14 ð107 Þð12-OMÞ þ 4:3ð103 ÞðS 2Þ þ 3:3ð103 ÞðP 3Þ;
ð1Þ
where M is the particle size parameter calculated as (silt, %+very fine sand, %) (100-clay, %), OM organic matter (%); S soil structure code (1=very fine granular, 2=fine granular, 3=medium or coarse granular, 4=block, platy, or massive); and P the profile-permeability class (1=rapid, 2=moderate to rapid, 3=moderate, 4=low to moderate, 5=slow, 6=very slow). Water retention capacity at 33 kPa (field capacity) was measured in the soil samples taken for analysis of bulk density and at 1500 kPa (permanent wilting point) in the soil samples taken for analyses of other physical and chemical properties. Available water capacity (AWC) was determined as the difference between field capacity and permanent wilting point (Klute and Dirksen, 1986). Total porosity was calculated in the water-saturated samples of 100 cm3 assuming no air trapped in the pores and validated using dry bulk density and a particle density of 2.65 g cm3 (Danielson and Sutherland, 1986). A wet sieving method was used to determine the mean weight diameter (MWD) as indices of the soil aggregation. The wet sieving method of Kemper and Rosenau (1986) was used with a set of sieves of 4, 2, 1, and 0.5 mm in diameter. After the soil samples were passed through an 8 mm sieve, approximately 50 g of the soil was put on the first sieve and gently moistened to avoid a sudden rupture of aggregates. After the soil had been moistened, the set was sieved in distilled water at 30 oscillations per minute. After 10 min of oscillation, the soil remaining on each sieve was dried, and then sand and aggregates were separated (Gee and Bauder, 1986). The MWD was calculated as follows: n X MWD ¼ Xi Wi ; ð2Þ i¼1
where Xi is the mean diameter of each size fraction (mm), and Wi the proportion of the total sample mass in the corresponding size fraction after deducting the mass of stones (upon dispersion and passing through the same sieve) as indicated above. SOC content for the soil depths of 0–10 and 10–20 cm was calculated for each of the ecosystems, based on SOC=0.58 SOM as follows: SOCðkg ha1 Þ ¼ ð%SOC=100Þ soil massðkg ha1 Þ; 1
where soil mass (kg ha )=depth 10,000 m2 ha1 1000 kg Mg1.
(m) bulk
ð3Þ density
3
(Mg m )
2.3. Data analysis Data analyses were carried out using Minitab (version 13.32). General linear model (GLM) was used to assess the effects of ecosystem type, soil depth, and their
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interaction on SOC. Tukey’s HSD procedure was used for multiple comparisons of mean physical and chemical properties of the soil depths (0–10, 10–20, and 0–20 cm) among the ecosystems (cropland, open forest, and grassland) at po0:05 level. Pearson’s correlation coefficients (r) were determined for the correlation matrix of all the variables (bulk density, SOC, SOM, plant-available water, clay content, USLE K soil erodibility factor, total porosity, pH, MWD, and the three ecosystems). Multiple linear regression (MLR) models were developed to relate the response variable of SOC to the indicator variables of the three ecosystems and the two depths as follows: SOC ¼b0 þ b1 Ecosystem1 þ b2 Ecosystem2 þ b3 Depth1 ;
ð4Þ
where b0 ; b1 ; b2 ; and b3 are regression coefficients of the indicator variables which estimate how much SOC will change in the presence of each ecosystem and each depth, with the other variables held constant.
3. Results The GLM showed that ecosystem type and soil depth affected the measured content of SOC (po0:001), but did not have a significant interactive effect on SOC (p > 0:05). For the soil depth of 0–20 cm, 21.1 g SOM kg1 in the cropland soil differed significantly from 38.8 g SOM kg1 in the forest soil and 41.3 g SOM kg1 in the grassland soil (po0:001), while the forest and grassland soils did not differ in SOM (p > 0:05). The mean SOM concentration of 36.6 g kg1 in the 0–10 cm layer was significantly higher than 30.9 g kg1 in the 10–20 cm layer, regardless of the differences in the ecosystems (po0:001). A multiple comparison of physical and chemical properties of the adjacent cropland, forest, and grassland soils is provided for each of the two soil depths (Table 1). The concentrations of SOM in the 0–10 and 10–20 cm layers of the cropland soil were 43.7% and 47.7% lower than those of the forest soil and 47.5% and 50.3% lower than those of the grassland soil, respectively (po0:05). The correlation matrix revealed that SOC content was correlated positively with AWC, total porosity, MWD, forest, and grassland, and negatively with bulk density, pH, USLE K factor, and cropland (Table 2). The cropland soil had a higher bulk density than the adjacent forest and grassland soils in both depths (po0:05). The grassland and forest soils did not differ in bulk density in the 0–10 cm layer but differed in the 10–20 cm layer (Table 1). On average, AWC in the 0–10 cm layer of the cropland soil was 44.4% and 35.5% less than the forest and grassland soils, respectively. In the 10–20 cm layer, the forest soil had the highest AWC of 0.156 m3 m3 and was different from AWC of 0.119 and 0.090 m3 m3 in the grassland and cropland soils, respectively (po0:05). The cropland, forest, and grassland soils had similar contents of sand, silt and clay, and pH in both depths (p > 0:05). Soil erodibility factor was greater in the cropland than in the forest site (po0:05). The cropland soil had a lower total porosity than the forest and grassland soils in both depths (po0:05). The meanweight diameter of aggregates was significantly greater in the forest and grassland
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Soil properties
3
Soil texture (%) Sand Silt Clay pH (1:2.5) USLE K factor Total porosity (m3 m3) MWD (mm)
Forest
Grassland
0–10 cm
10–20 cm
0–20 cm
0–10 cm
10–20 cm
0–20 cm
0–10 cm
10–20 cm
0–20 cm
1.3070.017a 23.4371.6a 17666716a 0.08970.007a
1.3770.021a 18.8475.2a 14970763a 0.09070.008a
1.3370.043a 21.1374.3a 326367214a 0.08970.007a
1.2470.027b 41.6173.5b 29926755b 0.16070.019b
1.27+0.024b 36.0571.0b 26554714b 0.15670.013b
1.2570.030b 38.8373.8b 564807132b 0.15870.015b
1.2370.032b 44.6071.8b 31818733b 0.13870.006b
1.1670.043c 37.9073.9b 25499797b 0.11970.009c
1.1970.050c 41.2774.5b 573177261b 0.12870.012c
20.076.3a 41.074.8a 39.077.4a 7.770.08a 0.2670.058a 0.5170.006a
19.077.2a 42.076.4a 39.077.7a 7.770.12a 0.2770.064a 0.4870.008a
20.076.3a 41.075.2a 39.077.0a 7.770.10a 0.2670.057a 0.5070.016a
19.077.6a 38.078.3a 43.0715.8a 7.170.46a 0.1170.087b 0.5370.011b
20.078.3a 36.0710.9a 44.0719.0a 7.370.65a 0.1170.099b 0.5270.009b
20.077.3a 37.079.0a 43.0716.2a 7.270.54b 0.1170.086b 0.5370.011b
18.073.6a 43.073.6a 39.073.3a 7.270.23a 0.1470.017ab 0.5470.012b
21.074.5a 41.073.3a 38.071.4a 7.570.12a 0.1470.024ab 0.5670.017c
20.074.0a 42.073.3a 38.072.3a 7.470.22ab 0.1470.020b 0.5570.019c
1.3070.3a
1.2970.5a
1.2970.4a
3.1070.5b
2.6770.7b
2.8970.6b
3.5970.8b
3.4170.8b
3.5070.7b
Means in each row followed by the same letters are not significant at po0:05 (n ¼ 4 for 0–10 cm and 10–20 cm and n ¼ 8 for 0–20 cm). S.D.: standard deviation, BD: bulk density, SOM: soil organic matter, SOC: soil organic carbon, AWC: available water capacity, K: USLE soil erodibility factor, MWD: mean weight diameter.
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BD (Mg m ) SOM (g kg1) SOC (kg ha1) PAW (m3 m3)
Cropland
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Table 1 Comparisons of some physical and chemical properties (means7S.D.) of adjacent cropland, forest, and pasture soils for two depths of 0–10 and 10–20 cm
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Table 2 Correlation matrix of soil properties and adjacent land use and land cover types (LULCs) (Pearson’s correlation coefficients, r)
SOC BD SOM AWC Cropland Forest Grassland pH K TP
BD
SOM
0.64
0.99 0.78 0.89 0.74 0.44 0.75 0.76 0.91 0.84
AWC
Cropland Forest 0.42
Grassland pH
0.47 0.59 n.s. 0.68 n.s. n.s. 0.54 0.58 0.77 n.s. 0.50 0.50 0.50 0.53 0.50 0.46 0.46
K
TP
MWD
0.74 0.64 0.81 0.54 1.0 0.61 0.74 0.74 0.82 0.58 0.45 0.63 0.75 0.75 0.83 0.49 n.s. n.s. 0.49 0.67 n.s. n.s. 0.73 n.s. 0.54 0.59 0.61
, , and refer to pp0:05; pp0:01; and pp0:001; respectively; n.s.: not significant at pp0:05:
SOC: soil organic carbon, BD: bulk density, SOM: soil organic matter, AWC: available water capacity, K: USLE soil erodibility factor, TP: total porosity, MWD: mean weight diameter. Soil depths of 0–10 and 10– 20 cm, and soil texture were not included in the table as none of their correlations with any of the other variables were significant at pp0:05:
soils than the cultivated soils (Table 1). On average, cultivation caused a 55% decrease for the 0–10 cm layer and a 63% decrease for the 10–20 cm layer in MWD of the cropland soil relative to the forest and grassland soils, respectively (po0:05). SOC accumulations of the cropland, forest and grassland soils were estimated at 32,636, 56,480, and 57,317 kg ha1 for the soil depth of 0–20 cm, respectively. The MLR models were estimated to describe the relative importance of, and the nature of relationships among the cropland, forest, and grassland soils. The MLR models had a high F value (the model utility test) and R2 value (the coefficient of determination) (po0:001). Any one of the two soil depths and any two of the three ecosystems accounted for 86.5% of the variation in mean SOC contents. The MLR models revealed that conversions from the forest and grassland to the cropland increased the mean loss of SOC by 96.5% and 96.6%, respectively. Mean SOC accumulation for the soil depth of 0–10 cm was 12,366 kg ha1 higher in the grassland and 11,932 kg ha1 higher in the forest than in the cropland. Mean SOC was 4050 kg ha1 higher in the 0–10 cm depth and negatively associated with the increasing soil depth for all the ecosystems.
4. Discussion The findings indicated that conversion of the grassland into the cropland in the southern Taurus mountains of the Mediterranean region increased bulk density by 10.5% and soil erodibility by 46.2%, and decreased SOM by 48.8%, SOC content by 43.0%, AWC by 30.5% and total porosity by 9.1% during a 12-yr period (po0:05). Hajabbasi et al. (1997) reported that deforestation and subsequent tillage practices resulted in nearly a 20% increase in bulk density and a 50% decrease in SOM for the
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soil depth of 0–30 cm over 20 yr in the central Zagrous mountains in Iran. Cultivation of alpine grassland soils in China for 8, 16, and 41 yr decreased SOC by 25%, 39%, and 55%, respectively, thus rendering soils more susceptible to erosion (Wu and Tiessen, 2002). Increased SOM improves aggregation, water-holding capacity, nutrient-retention capacity, ion exchange capacity, and biodiversity in soils. Cultivation breaks up soil aggregates, decreases total soil porosity, and accelerates decomposition and mineralization of SOM due to exposures of previously inaccessible SOM to microbial attack (e.g. Sparling et al., 1992; Haynes, 1999; Shepherd et al., 2001). Studies have shown that the removal of vegetation, the loss of SOM, and soils with a low MWD also increased bulk density and soil erosion (e.g. Teixeira and Misra, 1997; Boix-Fayos et al., 2001; Loveland and Webb, 2003). Despite variations as a function of abiotic and biotic factors, mean losses of SOC from grassland and forest soils by conventional tillage practices are estimated to range from 20% to 50% of the initial SOC content in the zone of cultivation within the first 20 to 30 years of cultivation (Post and Mann, 1990; Davidson and Ackerman, 1993; Murty et al., 2002). These SOC losses show a rapid exponential decline in the first 20 years after which SOC levels gradually stabilize at a new steady state over the next 30 or so years. Clearance of forest and grassland for agricultural production, semi-arid climate, and inclined topography render the Mediterranean plateau ecosystems of Turkey unable to recover from some changes in land uses and land covers. Sustainability-oriented practices that assure biological productivity, biodiversity, and soil stability should be considered in management of these ecosystems.
Acknowledgements We thank Prof. M.K. Wali and an anonymous reviewer for valuable comments on a previous version of the manuscript. This research was supported by a research - ukurova University. project grant of C
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