Forest floor parameters under the
Forestry has been recommended for carbon cycle management since it promotes carbon accumulation in soils and vegetation. Soil organic carbon (SOC) is fundamental to fertility and crop production in tropical soils and its conservation is critical to sustainable land management of neotropical savannas. Thirty to forty years of Eucalyptus and Pinus forestry in original Brazilian wooded-savanna affected forest floor layers, SOC and organic matter (OM) quality. Eucalyptus and Pinus showed higher forest floor carbon stocks than natural forest plots. On the surface soil layer, plantation effects on SOC were mediated by site-dependent factors. Below 10 cm, both plantations showed lower SOC than the native forest. The relationship between carbon and clay contents was significant in subsurface soil layers, suggesting that the particulate OM pool had been depleted by plantation activities. Plantations lead to soil OM replacement to a depth of 5 cm within 30 years. The new litter and OM in the plantations had lower quality (higher C:N ratios) than in natural forests. Our results indicate that particular care must be taken when choosing forest management practices in tropical-weathered soils because they can oxidize a significant part of the SOC pool with negative consequences to soil fertility and aggregate stability.
- carbon stocks
- organic matter
- forest floor
- subtropical forest
Forest management is an available option for climatic change mitigation through carbon cycle management [1, 2, 3]. In that context, soil carbon is decisive in the long term  because soils contain two to three times the amount of carbon in vegetation  in chemical forms that are much more stable than in biomass, with residence times extending from decades to millions of years  (Figure 1). Soil organic carbon (SOC) is defined by climate, soil type, plant cover, decomposer activity, perturbations and management . Vegetation affects SOC because, through root and leaf production, it determines soil organic input quantity and quality, which are major decomposition control factors . Soil type affects SOC decomposition and stabilization through drainage, structure, texture , the presence and type of clays, sesquioxides and other stabilizers . Management practices affect disruption and aggregation of organic matter (OM), and thus, their influence on SOC is determinant  (Figure 1).
SOC is fundamental to fertility and crop production in tropical soils. In tropical savannas, most soils have a predominance of highly weathered clays; thus, they are acidic, low-fertility soils characterized by a low cation exchange capacity, low base saturation and high Al toxicity. Because the mineral fraction is dominated by low-activity clays, SOC is especially important in these soils, where OM is the main nutrient source for plants, soil fauna and microorganisms [11, 12]. SOC also plays a fundamental role in soil aggregation, and thus, it is essential for water supply and soil structure maintenance . Hence, the conservation of SOC is critical to sustainable land management of neotropical savannas .
The Brazilian wooded-savanna’s ecological complex (
Despite the importance of SOC to forest sustainable management in neotropical savannas, literature on the subject is scarce, and it mostly remains in thesis and regional papers where it is difficult to be consulted. Furthermore, available research papers conclude either that there is no effect or that contradictory effects are shown , as it has been recently appointed in a review of intensive logging effects on SOC . The effects of
Given the wide occurrence of forest plantations in tropical soils and the importance of SOC conservation to soil fertility, crop production and sustainable land management of neotropical savannas, we aimed to assess alterations in SOC content produced after 30 years of intensive management of
2. Material and methods
2.1. Site description
We collected samples at four locations in the State of Sao Paulo, SE Brazil. They are approximately 100 km apart, located in the Luiz Antônio (21°61′S;47°75′W) (LZ), Mogi Guaçú (22°24′S;47°15′W) (MG), Pederneiras (22°34′S;48°89′W) (PD) and Itirapina (22°19′S;47°94′W) (IT) districts. At each location, we studied
Climate is characterized as tropical type II . Climatic conditions are homogeneous among sites, with temperatures ranging between 19 and 22°C (mean annual T = 20°C) and with an annual mean precipitation of approximately 1200 mm year−1. Rainfall is concentrated from October to March, and thus, there is a dry winter season between June and September when water demand exceeds water availability and soil moisture limits plant growth, biomass production, SOC decomposition and other ecosystem process.
Sites belong to the
All study stands are older than 30 years. They were planted in 1962, 1965, 1966, 1969 and 1972. Natural vegetation was first cleared, and after slash and burn of the original forest, a heavy disk plow was used to open seedling lines (~20 cm depth). Trees were planted manually. The used species were
One hundred trees per plot were measured for characterization of the vegetation. Mean basal area values ranged from 21 to 44 m2 ha−1 in the planted stands and from 23 to 43 m−2 ha−1 in the native forests. Vegetation densities (299–786 trees ha−1 in plantations and 1200–1600 trees ha−1 in native forests) and diameter distributions (70% of trees were smaller than 10-cm diameter breast height in native forest) showed structural differences between natural and planted areas. Neither planted nor natural sites had been burnt in the last three decades.
2.2. Experimental design
Thirty sampling points were randomly selected at each plot (forest type × site) for soil and litter collection. The procedure was repeated four times at different locations in order to guarantee real independence of the observations (Figure 2). Our experimental work was then carried out following a randomized block design with sampling replication within the blocks , as we collected 30 samples inside each of the three forest type treatments (
2.3. Sampling and laboratory analysis
Collection was performed in 2004 at the end of the dry season during the maximum litter accumulation period. Forest floor samples were collected using a 25-cm2 metal frame. All materials were collected, including not only litter but also fibric and humic horizons when present. Samples were oven dried to constant weight and ground for chemical analysis. C and N were determined by wet combustion  on 360 samples.
Soil samples were collected at three depths: 0–5, 10–25 and 35–50 cm. Pits were open to profile description and undisturbed soil sample collection. Undisturbed soil samples were collected using 5-cm diameter metal cores at four random replicates per plot. Then, soil bulk density was calculated as the oven-dry sample mass divided by the sampled volume for a total of 144 samples. Disturbed samples were collected with an auger at 30 sampling points per plot. After collection, soil samples were air dried and individually sieved through 2-mm mesh. SOC was determined by the Walkley & Black wet combustion method  following a tropical soil-adapted protocol  for a total of 600 samples. Since the studied soils are free of stones and gravel, corrections for those fractions were unnecessary. Texture was determined by the pipette method . Sand (<2 mm to 64 μm), silt (<64 μm to 2 μm) and clay (<2 μm) fractions were determined for 216 samples.
Soil carbon stocks (Mg ha−1) were calculated using bulk density (g cm−3) and carbon content data (g kg−1). Because we lack continuous sampling data, we used pedotransfer functions to estimate soil carbon stocks into the soil profile. Those functions, which related carbon content with soil depth or texture, can precisely calculate soil carbon stocks . SOC exponentially decays with depth; therefore, most pedotransfer functions are based on the exponential model equation [22, 31, 32]. We used its more general form, which is:
Because the Kjeldahl acid digestion method loses accuracy when analyzing acidic, N-poor soils, we used a CN analyzer (Leco CN-2000) to determine soil C and N by dry combustion and gas chromatographic separation of 36 soil surface samples to obtain the A horizon C:N values. C:N ratios were then calculated for 720 samples; 36 samples from the soil surface (A horizon, 0–5 cm depth) and 360 from the forest floor.
2.4. Statistical analysis
We used general linear models to test the SOC content (g kg−1) and C:N ratio responses to the three forest treatments (
3. Results and discussion
3.1. Forest floor
Forest floor layers under the native
Forest floor organic carbon stocks were one to two times larger under the
|Mass (Mg ha−1)||OC (g kg−1)||OC (Mg ha−1)||C:N||C:N|
|Ce||LZ||8.194 (2.405)||416.1 (28.7)||3.523 (1.04)||33 (3.91)||15 (0.27)|
|Eu||LZ||10.014 (3.129)||440.2 (11.4)||4.340 (1.39)||84 (12.93)||21 (1.13)|
|Pi||LZ||10.322 (4.023)||453.0 (14.2)||4.697 (1.84)||66 11.96)||21 (0.63)|
|Ce||MG||8.025 (2.699)||429.8 (15.6)||3.366 (1.20)||43 (6.23)||15 (0.60)|
|Eu||MG||5.411 (1.664)||438.5 (13.7)||2.347 (0.75)||61 4.40)||18 (0.70)|
|Pi||MG||8.666 (3.855)||439.2 (25.2)||3.948 (1.78)||65 (9.20)||23 (1.07)|
|Ce||PD||8.146 (2.143)||399.8 (26.7)||3.158 (0.94)||33 (3.81)||17 (1.50)|
|Eu||PD||11.583 (3.183)||428.7 (30.9)||5.010 (1.48)||71 (12.08)||18 (0.35)|
|Pi||PD||11.862 (4.027)||450.9 (11.1)||5.318 (1.84)||94 (12.57)||21 (3.20)|
|Ce||IT||10.706 (2.981)||439.2 (15.3)||4.731 (1.32)||36 (4.93)||18 (1.61)|
|Eu*||IT||19.160 (3.334)||474.9 (2.8)||9.049 (1.58)||68 (4.78)||26 (0.83)|
|Pi||IT||16.328 (4.298)||420.0 (39.6)||6.339 (1.86)||64 (12.64)||21 (1.18)|
Forest floor accumulation depends on the input/output balance, which is controlled by litter production and decomposition . It is known that
3.2. Soil organic carbon
Our results show that soil carbon is related to forest type, soil depth and texture.
SOC distribution is heterogeneous in the soil profile. SOC fitted a lognormal distribution, as expected from the literature [43, 44]. SOC heterogeneity decreased from surface to subsurface soil layers. We found variation coefficients from 18 to 58% at the 0–5-cm soil layer and from 5 to 26% in layers below 10-cm soil depth. Standard deviations increased between 10 and 25 cm and 35–50 cm layers in four sites (
|Treatment||Soil organic carbon (g kg−1)||Total SOC (Mg ha−1)|
|0–5 cma||10–25 cmb||35–50 cmb||0–30 cmc||R2|
|Ce||LZ||28.41 (06.12)||14.59 (1.27)||12.73 (1.04)||55.8||0.64|
|Eu||LZ||34.61 (06.33)||13.31 (1.27)||11.40 (1.56)||68.3||0.83|
|Pi||LZ||43.14 (17.01)||11.8 (0.55)||10.64 (0.78)||56.3||0.50|
|Ce||MG||24.67 (06.18)||13.2 (2.66)||10.93 (2.83)||56.9||0.51|
|Eu||MG||11.65 (02.79)||9.65 (2.14)||9.13 (2.21)||40.8||0.16|
|Pi||MG||35.45 (14.73)||8.90 (1.20)||7.79 (0.56)||54.3||0.66|
|Ce||PD||30.48 (15.31)||8.08 (1.01)||6.34 (0.70)||59.7||0.64|
|Eu||PD||10.83 (01.91)||6.92 (0.97)||6.10 (0.79)||39.6||0.53|
|Pi||PD||12.26 (03.88)||5.64 (0.73)||5.58 (0.56)||36.0||0.47|
|Ce||IT||36.86 (19.66)||8.43 (1.20)||6.63 (0.62)||54.4||0.53|
|Eu*||IT||65.99 (38.28)||7.56 (1.81)||6.40 (1.16)||85.7||0.76|
|Pi||IT||15.58 (06.18)||5.41 (1.16)||5.06 (0.87)||33.7||0.40|
SOC content decreased as the depth increased in the soil profile (Table 2); 81–78% of the SOC contained 50 cm depth was concentrated on the surface soil layer (data not shown). More SOC content on the surface than on deeper layers is due to soil organic inputs being mostly superficial. Furthermore, literature reports that SOC distribution in the soil profile is well explained by indirect exponential functions in temperate  and tropical forest soils . In this study, pedotransfer functions based on the exponential model properly fitted the observed data, with coefficients varying between 0.40 and 0.83. Similar pedotransfer function coefficients, from 0.54 to 0.73, were reported in oxisols of the Western Brazilian Amazon . These results reinforce the idea that exponential models are useful for carbon stock estimations [22, 30, 31, 32]. Even continuous sampling with volumetric cores could improve the models’ fit, collection at three depths is considered appropriate to SOC stocks estimation  and it demands significantly less field effort. The estimated SOC stocks (Table 2) match the values reported for
Our soil bulk density values (Table 3) also fit the ranges reported in other studies conducted at Brazil [17, 22, 24, 47]. We found soil bulk density increments in plantations compared with natural
|Treatment||Bulk density (g cm−3)|
|0–5 cma||10–25 cmb||35–50 cmb|
|Ce||LZ||0.93 (0.02)||0.85 (0.03)||0.94 (0.09)|
|Eu||LZ||1.20 (0.04)||1.00 (0.06)||0.96 (0.05)|
|Pi||LZ||0.89 (0.05)||1.01 (0.06)||0.95 (0.03)|
|Ce||MG||1.03 (0.09)||1.23 (0.06)||1.12 (0.09)|
|Eu||MG||1.27 (0.06)||1.32 (0.06)||1.30 (0.05)|
|Pi||MG||1.15 (0.05)||1.10 (0.13)||1.03 (0.12)|
|Ce||PD||1.22 (0.02)||1.40 (0.04)||1.41 (0.02)|
|Eu||PD||1.28 (0.03)||1.41 (0.04)||1.44 (0.03)|
|Pi||PD||1.28 (0.06)||1.49 (0.02)||1.40 (0.08)|
|Ce||IT||0.86 (0.07)||1.30 (0.11)||1.36 (0.01)|
|Eu*||IT||1.00 (0.16)||1.46 (0.07)||1.38 (0.05)|
|Pi||IT||1.15 (0.10)||1.42 (0.04)||1.42 (0.06)|
We found gains as well as losses of carbon stocks into the upper 0–30-cm depth mineral soil layer working on a soil volume basis. Under
Our SOC results fit the literature-reported values [17, 24]. As expected, forest type had significant effects on SOC concentration; however, responses to forest type cannot be described straightforwardly because they were dependent on soil depth and site (Table 4). There were strong SOC differences according to forest type at the soil surface layer, but the net effect varied between sites, including losses, gains and even no significant changes compared to the reference native forest (Figure 3). These results suggest that there are site-dependent determinant factors affecting surface layer SOC. At deeper layers, we found the same pattern in all studied stands: SOC concentration decreased under plantations and SOC levels were lower in the
|Site × forest type||6||1.968||ns|
|Site × forest type||6||1.626||ns|
|0–5 cm||10–25 cm||35–50 cm|
|LZ (59%)||MG (25%)||PD (15%)||IT (11%)||All sites||All sites|
Meta-analysis results support our findings; soil carbon stocks decline about 13% after natural forests to plantation conversion . Nevertheless, the net effect depends on the type of planted species; broad tree plantation placed onto prior native forests or pastures did not affect the SOC stock, whereas pine plantations reduced SOC stocks about 12–15% . Moreover, most of the soil carbon was lost under softwoods plantations (particularly
Our results suggest that clay content regulates SOC responses to forest management. Surface SOC concentration changes in
Our contrasting surface SOC results could be explained by tillage and/or soil preparation differences between sites at the initial plantation time, as no evident differences exist in climate, main soil formation processes, stand age and management practices, and differences in clay content are not related to SOC in the surface layer (see Section 3.3). Small differences in soil tillage and management practices at soil preparation time can generate significant losses of SOC, and the patterns of loss and accumulation of SOC strongly vary according to location . More than 30% of the forestland and 50% of the grassland surface SOC pool variation were attributed to site variables in Ohio in the Great Lakes region of the USA . Different patterns of surface SOC dynamics at each study site in
Site preparation activities could be responsible for SOC losses at our sites. At plantation time, burning harvest residue for site preparation was the common practice and then, the SOC decreases founded in planted stands below 10-cm soil depth may be related to enhance SOC oxidation at plantation time. Activities carried out during site preparation, such as natural vegetation clearing and plowing (up to ~20-cm depth) probably lead to net SOC losses because they increase aggregates disruption and aeration as well as increase the availability of native labile organic carbon for decomposers. The particulate SOC pool, which is very sensitive to management , could be easily oxidized at plantation time due to soil preparation activities. The SOC pool associated with clays, which is more resistant to disruption, could be retained in the mineral soil, forming 60–70% of the actual carbon pool in the studied soils (see Section 3.3). Species richness itself could partially explain higher carbon contents in the subsoil of
3.3. SOC-clay relationship
The SOC-clay equations fitted linear regression models; however, the relationship differed with soil depth. Clay content explained 62% of the SOC content at the 10–25 cm depth and 75% at the 35–50 cm depth, but clay and SOC levels were not related at the surface layer (0–5 cm depth) (Table 6). The SOC-clay direct relationship can be explained by SOC stabilization. Carbon is adsorbed on clay surface exchange sites, where it is protected from decomposition, lixiviation and water transport losses. Mineral fractions <20 μm are responsible for SOC physical protection because of its occlusion into microaggregates . Thus, the more abundant the clay, the more protected the SOC.
|Soil layer||Linear regression analysis|
In Brazilian oxisols, clay content is considered as a major controlling factor of slow SOC cycling  and SOC accumulation is often higher in clay than in sandy soils [17, 60]. Therefore, clay content has a strong influence on soil carbon dynamics and storage in this type of soils. Although experimental results do not always confirm the linear relationship between carbon and fine soil mineral particles [61, 62], several studies support significant relationships either with clay [8, 20] or with clay + silt [9, 30, 43, 57]. The linear relationship is related to the number of adsorption sites on the clay mineral surface per unit soil weight or volume. This linear relationship has been also reported in soils dominated by low activity clays . Other authors found strong texture effects on SOC in shallow and deep soil layers but not at the surface layer [30, 57, 63]. The unclear textural effect at the surface layer found in the
The SOC differences between the surface and the lower layers may be due to the surface SOC pool mostly containing labile forms that originated from particulate OM, which is composed of organic fragments up to 20–50 μm . Below a 10-cm soil depth, the SOC pool may contain more stable forms of 20 μm or smaller in size that could be stabilized through clay association. However, the relationship between physical protection and chemical quality is not as simple. SOC recalcitrance decreases with depth have been found in Mediterranean forest soils . The authors found that recognizable plant fragments constituting the free-light SOC fraction were not necessarily the youngest fraction and that the nondecomposed fraction of SOC presented intermediate degrees of recalcitrance .
3.4. Organic matter quality: C:N ratios
We found higher C:N ratios in
Our results indicate that SOC replacement occurred in 30 years in the A horizon to a depth of 5 cm in
According to our results, forest management practices may have strong implications for SOC pools that may offset the carbon biomass accumulation potential of plantations of fast-growing species, thus limiting their role in C sequestration and climate change mitigation. These implications are particularly critical in the case of the substitution of native forests by artificial plantations considering the possible negative consequences for biodiversity conservation.
We thank the FAPESP Foundation (Research Foundation of the State of São Paulo, Brazil) and the AECI Agency (Spanish International Cooperation Agency) for the financial support. We thank the Florestal Institute and the Botanical Institute of the State of Sao Paulo for the field support and infrastructure and the laboratory CENA (USP) staff for the support with chemical analysis. We thank Dr. Prado and Dr. Oliveira (University of Sao Paulo, Ecology Dep.) for the aid with analyses using R language. Finally, we thank Dr. Vallejo (Barcelona University, Vegetal Biology Dep.) for his useful comments.