Effects of soil management on aggregation and organic matter dynamics in sub-Saharan Africa.
Soil aggregate stability, that is the ability of soil aggregates to remain intact when subjected to some stress and soil organic matter (SOM) dynamics have lately received much attention due to their role in sustainable ecosystem functioning and also because of concerns about global warming and climate change (Fonte et al., 2009; Gougoulias et al., 2014). Soil aggregates (i.e. a group of soil particles with a diameter size of less than 2 mm, that bind each other more strongly than adjacent particles), especially micro-aggregates (size diameter, 53-250 [micro]m) formed within macro-aggregates ([greater than or equal to] 250 [micro]m), protect SOM against microbial decay (Tisdall and Oades, 1982; Six et al., 2000; Bossyut et al., 2005) and can reduce surface crusting and soil erosion (Blanchart et al., 1999; Barthes and Roose, 2002; Spohn and Giani, 2011; Six and Paustian, 2014). Soil organic matter also binds mineral particles into aggregates (Tisdall and Oades, 1982) and stimulates the activities of soil biota (Six et al., 2004; Ayuke et al.,2011b). Soil C and N stabilization and consequently fertility, are mediated by the interactions between soil organic matter, soil structure and soil fauna abundance and diversity, all of which are affected by management practices (Six et al., 2004). Land use practices such as fallowing, tillage, organic and inorganic amendment application and crop rotation, have been shown to impact soil structure, which may lead to changes in SOM storage and turnover (Ayuke et al., 2011b; Paul et al., 2013). In several conceptual models, the increase of aggregate stability after addition of organic amendments to soil has been related to the decomposition dynamics of cauliflower green manure, wheat straw and cattle manure inputs (Abiven et al., 2009). The loss of SOM and subsequent deterioration of soil physical, chemical and biological soil quality due to continuous cropping, along with sub-optimal fertilizer use, frequently result in a decline in biomass productivity and crop yields, presenting great challenges to many farmers in sub-Saharan Africa (Sanchez et al., 1997). Despite the potential significant benefits of soil aggregation and increased SOM and related soil processes on soil quality, there is a general lack of knowledge about how these soil quality parameters are affected by management practices of varying intensities, and associated soil disturbance arising from agricultural activities. Due to the soil's capacity to sequester large amounts of organic C, an understanding of soil aggregation and SOM dynamics, and their influencing factors are important in addressing climate change and greenhouse gas mitigation efforts (Lal, 2011).
This study, therefore, investigated the effect of land use practices and management intensity (fallowing and organic inputs) on soil structure and SOM dynamics in long-term field trials across eastern (Kenya and Malawi) and western (Nigeria, Ghana, Burkina Faso and Niger) Africa. Specifically, the study sought to assess the effects of management practices on soil aggregation, and C and N stabilization in whole soil and aggregate fractions.
Materials and Methods
Study sites and sampling strategy
The study was conducted on 12 long-term field trials across the sub-humid to semi-arid tropical zones of eastern Africa (Embu, Kabete, Impala and Nyabeda in Kenya, and Chitala in Malawi) and western Africa (Tamale in Ghana, Ibadan in Nigeria, Sadore in Niger and Farakoba, Saria I, II and III in Burkina Faso) (Figure 1). A general characterization of the sites, including climate and soils, is presented in Table 1. The long-term trials were established between 1960 and 2003, and aimed at testing different management options for arable crop production such as organic versus mineral inputs, crop rotation, and tillage. All experiments in the selected sites were laid down in completely randomized block designs in three to four replications. For the present study, only three treatment blocks were selected and sampled. In our sampling scheme, only the arable treatments that according to previously available data had resulted in the highest C and lowest soil organic carbon C contents were included in the analysis (Table 2). At each site, a long-term fallow representing a relatively undisturbed reference was sampled. Depending on the site, the fallows consisted of grass fallow, forest or shrub land for at least 10 years before the time of sampling.
Soil sampling, pretreatment and analysis
One soil monolith measuring 25 cm long x 25 cm wide x 30 cm deep, was randomly sampled from each replicate plot (n = 3) between six to eight weeks after planting (July-September 2006 in the West African sites and February-July 2007 in the East African sites). The excavated soil was initially hand-sorted for macro-fauna separately at 0-15 and 15-30 cm soil depths as described in Ayuke et al. (2011a).
A representative subsample (about 500g) of the 0-15 and 15-30 cm soil depth layers of the monolith was gently passed through a 10 mm sieve by breaking up the soil along natural planes of weakness, air-dried and stored at room temperature. The soil was then separated into four water stable aggregate size fractions: (i) large macro-aggregates (size diameter > 2000 [micro]m), (ii) small macro-aggregates (250 - 2000 [micro]m), (iii) micro-aggregates (53-250 [micro]m), and (iv)silt + clay sized particles (< 53 [micro]m), using the method described by Elliott (1986). Briefly, 80g of air-dried soil was transferred to a 2 mm sieve, placed in a receptacle filled with deionized water, and left to slake for 5 min, after which the 2 mm sieve was manually moved up and down 50 times in 2 minutes. The procedure was repeated using the material that passed through the 2 mm sieve, using a 250 [micro]m sieve and subsequently a 53 [micro]m sieve. A representative 250 ml subsample was taken from the suspension containing the <53 [micro]m silt and clay sized particles to determine the weight of the smallest fraction. Soil aggregates retained on each sieve were backwashed into pre-weighed containers, oven-dried at 105[degrees]C over-night and weighed.
After wet sieving, oven drying and weighing, the large and small macro-aggregates retained were combined according to their relative weight or proportions to obtain total macro-aggregates. The total macro-aggregates were then used for the separation of micro-aggregates within macro-aggregates as follows: Micro-aggregates (53-250 [micro]m) occluded within macro-aggregates were isolated using a device described by Six et al. (2000), which completely breaks up macro-aggregates with minimal disruption of micro-aggregates. About 5 g of the macro-aggregates were transferred to the device holding a 250 [micro]m mesh screen and shaken with 50 glass beads (diameter 4 mm) to break the macro-aggregates. The micro-aggregates released were immediately flushed through the 250 [micro]m sieve and deposited onto a 53-[micro]m sieve by a continuous flow of water through the device. The material on the 53 [micro]m sieve was then wet-sieved as described above, 50 times in 2 minutes, to isolate the stable micro-aggregates from the silt and clay. The micro-aggregate fractions (53-250 [micro]m) were oven-dried (60[degrees]C) for 48 hours and weighed. Sand and coarse particulate organic matter retained on the 250 [micro]m mesh screen were washed off, oven-dried, and weighed. The silt and clay, and silt and clay within macro-aggregates were calculated from the total volume of the suspension and the volume of the subsample. Mean weight diameter was determined as the sum of the weighted mean diameters of all fraction classes.
For measurement of total soil organic C and N content, 1-2 g of the whole soil (before fractionation) and aggregate fraction soil samples were taken and ground. About 30 mg of the samples were weighed out in aluminium capsules and sent to the University of California at Davis, USA for analyses of total carbon and nitrogen. These were determined using the Dumas combustion method with a PDZ Europa ANCA-GSL elemental analyzer interfaced to a PDZ Europa 20-20 Integra C-N isotope ratio mass spectrometer (Sercon LTD, Cheshire, United Kingdom).
The data obtained on soil aggregate fractions, and soil C and N were subjected to analysis of variance with R Studio Version 0.97.449 (R Core Team, 2013). The Linear Mixed Model was fitted by Restricted Maximum Likelihood (RELM) procedure using the ImerTest package (Kuznetsova et al., 2014). This procedure allows for inclusion of both fixed- and random-effects terms in the model such that profiled deviance of RELM criterion is optimized for the parameter estimates (Bates et al., 2015). Site and treatment, and their interactions were included in the model as fixed factors, whereas block was defined as a random factor. However, only overall treatment effects are presented in the results. Aggregate fractions, whole soil and aggregate-associated Soil C and N were analyzed independently for two soil depths (0-15 cm and 15-30 cm). The statistical significance was determined at p [less than or equal to] 0.05 and where statistical differences were detected, Tukey's post hoc multiple comparisons tests were performed.
Water stable aggregate indices
Management practices and intensity had significant influences on water stable aggregates at both 0-15 and 15-30 cm depths. The differences in aggregate size distribution were reflected in mean weight diameter, which were consistently lower in the arable (high carbon and low carbon) treatments compared to fallow treatment (Table 3). At 0-15 cm soil depth, the proportion of large macro-aggregates was significantly higher in fallow than in the arable (high carbon and low carbon) treatments, but the difference between high carbon and low carbon treatments was not statistically significant (Table 3). Differences in the proportions of micro-aggregates within macro-aggregates and silt and clay within macro-aggregates showed the same pattern as differences in large macro-aggregates. The proportion of small macro-aggregates was significantly higher in the fallow (45.72 g 100 [g.sup.-1] total soil) than in high carbon treatment (42.48 g 100 [g.sup.-1] total soil), which, in turn, small macro-aggregates was significantly higher than in the low carbon (38.32 g 100 [g.sup.-1] total soil) treatment. However, a reverse trend was observed for the proportions of micro-aggregates, silt and clay and coarse particulate organic matter, and these followed the order low carbon > high carbon > fallow treatments (Table 3). At 15-30 cm soil depth, the proportion of the aggregate fractions was highly variable across treatments. The proportion of small macro-aggregates was significantly higher in the fallow than in the arable (high carbon and low carbon) treatments, whereas the proportion of micro-aggregates was significantly higher in the arable (high carbon and low carbon) treatments than in the fallow treatment (Table 3). Differences in the proportion of silt and clay showed the same pattern as observed for micro-aggregates at the 0-15 cm depth, as it followed the order low carbon > high carbon > fallow treatments. Management practices, however, had no significant effects in the proportions of large macro-aggregates, coarse particulate organic matter, micro-aggregates within macro-aggregates, silt and clay within macro-aggregates and the mean weight diameter at 15-30 cm soil depth.
Whole soil and aggregate-associated carbon
Management practices and intensity affected the concentration of carbon in whole soil, as well as in the aggregate fractions. The concentration of C for the micro-aggregates within macro-aggregates fraction, followed the order high carbon > fallow treatments > low carbon, whereas for coarse particulate organic matter and silt and clay within macro-aggregates the concentration of C did not differ between treatments. However, the levels of C in whole soil, and in all the other aggregate fractions, were significantly higher in the fallow than in high carbon treatments, which in turn, were significantly higher than in the low carbon treatments at 0-15 cm soil depth (Table 4). At 15-30 cm, the concentration of C in small macro-aggregates fraction was significantly higher in the fallow treatment than in the arable (High carbon and low carbon) treatments, whereas, the concentration of C in the micro-aggregates within macro-aggregates fraction was significantly lower in low carbon (12.95 g C 100 [g.sup.-1] total soil) treatments than in fallow (15.17 g C 100 [g.sup.-1] total soil) and high carbon (14.72 g C 100 [g.sup.-1] total soil) treatments. The concentration of C in micro-aggregates was significantly higher in fallow than in low carbon treatment, although the concentration in high carbon did not differ from either fallow or low carbon treatments. However, the concentration of C in whole soil and in all the other aggregate fractions (large macro-aggregates, silt and clay, coarse particulate organic matter and silt and clay within macro-aggregates) did not differ between the treatments and hence were not affected by management practices (Table 4).
Whole soil and aggregate-associated nitrogen
Nitrogen concentrations in whole soil and aggregates showed similar trends to C at 0-15 cm depth. Although no treatment differences were observed for both coarse particulate organic matter and silt and clay within macro-aggregates, the concentration of N in micro-aggregates within macro-aggregates fraction followed the order high carbon > fallow > low carbon treatments. However, the concentrations of N for all the other fractions were significantly higher in fallow > high carbon > low carbon treatments (Table 5). At 15-30 cm, no significant differences in concentrations of N were observed for coarse particulate organic matter and silt and clay within macro-aggregates, although the level of N in micro-aggregates within macro-aggregates fraction was significantly higher in fallow > high carbon > low carbon treatments. Fallow, on the other hand had higher N in the small macro-aggregates fraction than in the arable treatments, but the concentrations of N in micro-aggregates and silt and clay were significantly lower in low carbon treatments than in either fallow or high carbon treatments. The concentrations of N in whole soil and large macro-aggregates fraction were significantly higher in fallow than in low carbon treatment, but high carbon did not differ from them (Table 5).
At most sites, management comparisons of fallow, high C and low C arable systems were not uniform, and not all of the treatments involved addition of organic residues. In view of the large variability in the data, results can be considered robust whenever differences in aggregation and SOM between treatments were significant.
Fallowing, and long-term application of organic inputs resulted in a buildup of soil organic matter, and this significantly enhanced aggregate stability and C and N pools especially at top (0-15 cm) and at subsoil (15-30 cm) depths for some soil fractions (Table 4). Our study has shown that long-term application of organic inputs such as crop residues, leaf litter and cattle manure resulted in higher stable aggregation, but not to the extent of the fallow, which is attributed to absence of soil disturbance and higher accumulations of organic matter in the fallow compared to arable systems. Our results corroborate findings by Ayuke et al. (2011b) who showed higher aggregate stability under fallow compared to the arable system. Higher proportions of aggregate fractions < 250 [micro]m in arable systems compared to fallow could be due to the effect of tillage practices which result in breakup of the macro-aggregates into smaller fraction aggregates such as micro-aggregates as well as silt and clay. Soil tillage indirectly affects soil aggregate stability, mainly through its influence on soil fauna, soil moisture, and on the redistribution of SOM (Tisdall and Oades, 1982; Paul et al, 2013). Tillage also breaks down aggregates and exposes organic matter to microbial attack, thus stimulating C and N oxidation and the loss of labile organic matter which binds micro-aggregates into macro-aggregates (Kushwaha et al., 2001).
The relatively higher proportion of small macro-aggregates in arable systems under high C inputs than under low C inputs can be attributed to regular addition of organic matter through crop residues, leaf litter and pruning, manure and additional root biomass added to soil due to fertilizer-enhanced plant growth. This results in greater C availability and enhanced microbial and macro-faunal activity which lead to the formation of aggregates (Six et al, 2004; Kibunja et al., 2010;. Ayuke et al, 2011b). Probably, when organic resources are incorporated into the soil, organic matter gradually decomposes to produce humic substances and bacterial biomass, which in turn releases polysaccharides which serve as binding agents, and fungal mycelia binding soil particles into aggregates (Bossuyt et al., 2005; Aoyama et al., 1999). Lack of organically generated binding agents, possibly explain why significantly higher proportions of aggregate fractions < 250 [micro]m (e.g. micro-aggregates, silt and clay, and coarse particulate organic matter), were found under low C input systems compared to high C input systems. Singh et al. (2007) have similarly shown that addition of animal manure with mineral fertilizers in rice-wheat-cowpea rotation systems, improved the aggregation of soil particles.
Whole soil and aggregate-associated carbon and nitrogen
Highest C and N were recorded in the fallow sites, and the high carbon input arable systems had higher C and N than low carbon input arable systems. High carbon inputs through organic amendment applications increased the C and N content of whole soil and in most of the fractions, especially at the 0-15cm depth. Higher C and N in the fallow land could be attributed to the accumulation of organic matter which upon decomposition, mineralize and release nutrients that are then added to the soil. Incorporation of organic resources facilitates decomposition processes of organic matter such that the free primary particles are cemented together into micro-aggregates by persistent binding agents such as roots, fungal hyphae and polysaccharides). As such, humification of organic matter stimulates the accumulation of C and N in aggregates. The micro-aggregates further bind to form SOM rich macro-aggregates, so the SOM can then be physically protected within the macro-aggregates. This explains why the highest micro-aggregates within macro-aggregates fraction C and N was recorded under high carbon input systems compared to fallow and low carbon input system, and these results indicate that macro-aggregates are important in C and N stabilization in soil as also observed by Sodhi et al. (2009) and Ayuke et al. (2011b). Among the soil management practices studied, C and N concentrations were generally higher in the silt and clay fractions, especially silt and clay within macro-aggregates, compared to all other fractions. Soils high in clay, and iron and aluminum oxides, such as the Nitisols of some of our study sites (for example, Embu and Kabete in Kenya), have been shown to respond positively to organic inputs in that they have a high C and N stabilization in aggregate fractions (Gentile et al., 2010; Ayuke et al., 2011b). Results on total C and N in whole soil in fallow and high carbon input practices compared to low carbon input practice is an indicator of C and N build-up as a result of the persistent addition of organic resources and cumulative soil organic matter. Rapid decomposition of organic resources and resultant conversion of the organic C into recalcitrant or resistant forms (Dick and Gregorich, 2004), and cumulative addition of N through mineral fertilizers (Sodhi et al., 2009) promotes sequestration of C and N, respectively, into the soil.
Our results showed that fallowing and long-term application of organic resources alone or in combination with mineral fertilizers observed at study sites, enhanced C and N stabilization with the benefits of improving soil physical and chemical properties. Due to the capacity of soils to sequester large amounts of organic carbon, an understanding of soil aggregation and soil organic matter dynamics, and their influencing factors are important in addressing climate change and greenhouse gas mitigation efforts. Arable land in sub-Saharan Africa faces numerous challenges and among them, an increasing population, dwindling household land acreage, and reduced or abandoned fallow practices. These results show the importance of soil conservation practices for sustaining soil quality, and the importance of fallowing as an integral part of sustainable management strategies in these regions.
Fallowing and high carbon inputs in arable soils significantly improved aggregate stability and C and N stabilization in the top (0-15 cm) of arable soils. In contrast, no significant improvements in soil aggregation and C and N stabilization were found when organic inputs were applied in low quantities as observed in the low carbon input soils. This study has shown that fallowing and long-term application of organic amendments are the best among the soil improving management practices tested in this study, for enhanced C and N stabilization with the benefits of improving soil physical and chemical properties.
This study was supported by Science for Global Development/WOTRO through Wageningen University and Norman Borlaug LEAP Fellowship Program through UC-Davis. We thank our partners, especially the scientists and field technicians of the Tropical Soil Biology and Fertility Institute of the International Centre for Tropical Agriculture (TSBF-CIAT, Kenya), Kenya Agricultural Research Institute (KARI), Kenya Forestry Research Institute (KEFRI), Kenyatta University, Kenya, International Institute of Tropical Agriculture (IITA, Nigeria), International Fertilizer Development Centre (IFDC, Burkina Faso), Institute of Natural Environmental and Agricultural Research (INERA, Burkina Faso), Savanna Agricultural Research Institute (SARI, Ghana), Chitedze Agricultural Research Station (Malawi), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT, Niger) and Natural History Museums (Hungary), who agreed to work with us and have allowed us to use their experimental sites for this study. We sincerely thank David Lelei who helped with laboratory extraction of aggregate fractions.
Abiven S., Menasseri S., Chenu C. (2009) The effects of organic inputs over time on soil aggregate stability--a literature analysis. Soil Biology and Biochemistry. 41, 1-12.
Aoyama M., Angers D.A., N'Dayegamiye A. (1999) Particulate and mineral associated organic matter in water stable aggregates as affected by mineral fertilizer and manure applications. Canadian Journal of Soil Science. 79, 295-302.
Ayuke F.O., Pulleman M.M., Vanlauwe B., de Goede R.G.M., Six J., Csuzdi C., Brussaard L. (2011a) Agricultural management affects earthworm and termite diversity across humid to semi-arid tropical zones. Agriculture Ecosystems and Environment. 148, 148-154.
Ayuke F.O., Brussaard L., Vanlauwe B., Six J., Lelei D.K., Kibunja C., Pulleman M.M. (2011b) Soil fertility management: impacts on soil macrofauna, soil aggregation and soil organic matter allocation. Applied Soil Ecology. 48, 53-62.
Bates D., Machler M., Bolker B.M., Walker S.C. (2015) Fitting Linean Mixed Effects Models using Ime4. Journal Statistical Software. 67(1), 1-48.
Barthes B., Roose E. (2002) Aggregate stability as an indicator of soil susceptibility to runoff and erosion: validation at several levels. CATENA. 47, 133-149.
Blanchart E., Albretch A., Alegre J., Duboisset A., Gilot C., Pashanasi B., Lavelle P., Brussaard L. (1999) Effects of earthworms on soil structure and physical properties. In: Lavelle P., Brussaard L., Hendrix P. eds. Earthworm management in Tropical Agroecosystems. CABI publishing, pp. 149-172.
Bossuyt H., Six J., Hendrix P.F. (2005) Protection of soil carbon by micro-aggregates within earthworm casts. Soil Biology and Biochemistry. 37, 251-258.
Dick W.A., Gregorich E.G. (2004) Developing and maintaining soil organic matter levels. In: Schjonning P., Elmholt S., Christensen B.T. eds, Managing soil quality: Challenges in Modern Agriculture. CABI publishing, Oxon, UK, pp. 103-120.
Elliott E. T. (1986) Aggregate structure and carbon, nitrogen and phosphorus in native and cultivated soils. Soil Science Society of American Journal. 50, 627-633.
Fonte S.J., Winsome T., Six J. (2009) Earthworm populations in relation to soil organic matter and management in California tomato cropping systems. Applied Soil Ecology 41, 206-214.
Gentile R., Vanlauwe B., Chivenge P., Six J. (2010) Trade-offs between the short- and long-term effects of residue quality on soil C and N dynamics. Plant and Soil Journal. 338, 159-169.
Gougoulias C., Clark J.M., Shaw L.J. (2014) The role of soil microbes in the global carbon cycle: tracking the below-ground microbial processing of plant-derived carbon for manipulating carbon dynamics in agricultural systems. Journal of Science Food Agriculture. 94(12), 2362-2371.
Kibunja C.N., Mwaura F.B., Mugendi D.N. (2010) Long-term land management effects on soil properties and microbial populations in maize-bean rotation at Kabete, Kenya. African Journal of Agricultural Research. 5 (2), 108-113.
Kushwaha C.P., Tripathi S.K., Singh K.P. (2001) Soil organic matter and water-stable aggregates under different tillage and residue conditions in a tropical dryland agroecosystem, Applied Soil Ecology 16, 229-241.
Kuznetsova A., Brockhoff P.B., Christensen R.H.B. (2014) lmerTest: Tests for random and fixed effects for linear mixed effect models (lmer objects of lme4 package). R package version 2.0-6. http://CRAN.R-project.org/package=lmerTest. (Accessed September 2017)
Lal R. (2011) Sequestering carbon in soils of agroecosystems. Food policy. 36, 33-39.
Paul B.K., Vanlauwe B., Ayuke F.O., Gassnerc A., Hoogmoed M., Hurissoa T.T., Koala S., Lelei D., Ndabamenyea T., Six J., Pulleman M.M. 2013. Medium-term impact of tillage and residue management on soil aggregate stability, soil carbon and crop productivity. Agriculture Ecosystems Environment. 164, 14-22.
R Core Team. (2013) R: A language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/. (Accessed September 2017)
Sanchez P.A., Shepherd K.D., Soule M.J., Place F.M., Buresh R.J., Anne-Marie N.I., Mokwunye A.U., Kwesiga F.R., Ndiritu C.G., Woomer P.L. (1997) Soil fertility replenishment: An investment in Natural Resource Capital. In: Buresh, R.J., Sanchez, P.A., F. Calhoun, F. eds. Replenishing Soil Fertility in Africa. Soil Science Society of America. (SSSA). Special publication No 51, USA.
Singh G., Jalota S.K., Singh Y. (2007) Manuring and residue management effects on physical properties of a soil under the rice-wheat system in Punjab, India. Soil Tillage Research. 94, 229-238.
Six J., Paustian K. (2014) Aggregate-associated soil organic matter as an ecosystem property and a measurement tool. Soil Biology and Biochemistry. 68, 4-9.
Six J., Bossuyt H., Degryze S., Denef K. (2004) A history of research on the link between (micro) aggregates, soil biota, and soil organic matter dynamics. Soil and Tillage Research. 79, 7-31.
Six J., Elliot E.T., Paustian K. (2000) Soil macro-aggregate turnover and micro-aggregate formation: a mechanism for C sequestration under no-tillage systems, Soil Biology and Biochemistry. 32, 2099-2103.
Spohn M., Giani L. (2011) Impacts of land use change on soil aggregation and aggregate stabilizing compounds as dependent on time. Soil Biology and Biochemistry. 43, 1081-1088.
Sodhi G.P.S., Beri D.K., Benbi D.K. (2009) Soil aggregation and distribution of carbon and nitrogen in different fractions under long-term application of compost in rice/wheat system. Soil and Tillage Research. 103, 412-418.
Tisdall J.M., Oades J.M. (1982) Organic matter and water-stable aggregates in soils Journal of Soil Science. 33, 141-163.
WRB. (2015) World Reference Base for Soil Resources. International soil classification system for naming soils and creating legends for soil maps. World Soil Resources Reports No. 106. FAO, Rome, 203p.
F. O. Ayuke (1*), Z. Zida (2) and D. Lelei (3)
(*) Lead author email: firstname.lastname@example.org , email@example.com
(1) Department of Land Resource Management and Agriculture Technology (LARMAT), Faculty of Agriculture and Veterinary Sciences, University of Nairobi, P.O Box 29053-00625, Nairobi, Kenya
(2) Alliance for Green Revolution in Africa (AGRA), PMB KIA 114, Accra, Ghana
(3) World Agroforestry Centre (ICRAF), P.O Box 30677-00100, Nairobi, Kenya
Table 1: Location and characteristics of the study sites Sites Embu, Kabete, Kenya Kenya Environmental Parameters Altitude asl. (m) 1480 1700 Latitude and 0[degrees] 30' S; 1[degrees] 15' S; Longitude 37[degrees] 30' E 36[degrees] 41' E Mean Annual 20 18 temp ([degrees]C) Mean annual 1450 1000 rainfall (mm) Bimodal Bimodal Climate (FAO) Sub-humid Sub-humid Soil type (WRB, HUMIC HUMIC 2015) NITISOL NITISOL Texture Clay Clay sand, silt, clay 3, 22, 75 11, 22, 67 (%) Sites Impala, Nyabeda, Kenya Kenya Environmental Parameters Altitude asl. (m) 1337 1420 Latitude and 0[degrees] 08' N; 0[degrees] 06' N; Longitude 34[degrees] 25' E 34[degrees] 36' E Mean Annual 23 23 temp ([degrees]C) Mean annual 1800 1800 rainfall (mm) Bimodal Bimodal Climate (FAO) Humid Humid Soil type (WRB, HUMIC HUMIC 2015) FERRALSOL FERRALSOL Texture Clay Clay sand, silt, clay 13, 17, 70 9, 21, 70 (%) Sites Chitala, Ibadan, Malawi Nigeria Environmental Parameters Altitude asl. (m) 606 200 Latitude and 13[degrees] 40' S; 7[degrees] 30' N; Longitude 34[degrees] 15' E 3[degrees] 54' E Mean Annual 22 27 temp ([degrees]C) Mean annual 800 1200 rainfall (mm) Unimodal Bimodal Climate (FAO) Sub-humid Humid Soil type (WRB, TYPIC DYSTRIC 2015) FERRALSOL REGOSOL Texture Sandy clay Sandy sand, silt, clay 60, 5, 35 87, 6, 7 (%) Sites Tamale, Sadore, Ghana Niger Environmental Parameters Altitude asl. (m) 185 250 Latitude and 9[degrees] 25' N; 13[degrees] 15' N; Longitude 1[degrees] 00' W 2[degrees] 17' E Mean Annual 29 33 temp ([degrees]C) Mean annual 1200 550 rainfall (mm) Unimodal Unimodal Climate (FAO) Semi-arid Semi-arid Soil type (WRB, FERRIC FERRALIC 2015) LUVISOL ARENOSOL Texture Sandy Sandy sand, silt, clay 90, 4, 6 92, 3, 5 (%) Sites Farakoba, Saria I, II, III, Burkina Faso Burkina Faso Environmental Parameters Altitude asl. (m) 405 300 Latitude and 11[degrees] 06' N; 12[degrees] 16' N; Longitude 4[degrees] 20' W 2[degrees] 09' E Mean Annual 28 33 temp ([degrees]C) Mean annual 850 800 rainfall (mm) Unimodal Unimodal Climate (FAO) Sudano-Sahelian North-Sudanian Soil type (WRB, FERRIC FERRIC 2015) LUVISOL LIXISOL Texture Loamy sand Sandy loam sand, silt, clay 74, 19, 7 53, 36, 11 (%) Table 2: Description of selected sites. # refers to management treatments: 1 = crop rotation, 2 = tillage, 3 = organic inputs, 4 = inorganic fertilizer HC = high carbon; LC = low carbon Trial site Year Treatments established Fallow Embu Fallow-woodland/shrubland since 1993 1993 Kabete 1976 Fallow-Bushland since trial establishment in 1976 Impala 2000 Fallow-shrubland nearby since trial establishment in 2000 Nyabeda 2003 Fallow-shrubland nearby since trial establishment in 2003 Chitala 1995 Grass fallow since trial establishment in 1995 Ibadan 1996 Bushland fallow since 1986 adjacent to the experimental plots Tamale 1996 Grass fallow strip since 1996 Sadore 1986 Fallow-shrubland within the experimental site since 1986 Farakoba 1993 Grass fallow within the experimental site since trial; establishment in 1993 Saria I 1960 Grass- fallow since trial establishment in 1959 (Common for all the Sarias) Saria II 1980 See Saria I Saria III 1990 See Saria I Trial site Arable- HC Embu #1=Cont. maize, 2=Hand hoeing, 3=Leucaena leucocephala (5 Mg [ha.sup.-1]), 4=no fertilizer Kabete #1=Maize-bean rotation, 2=Hand hoeing, 3=10 Mg [ha.sup.-1] manure, 4=CAN (120 kg N [ha.sup.-1]) and TSP (52.8 kg P [ha.sup.-1]) fertilizers Impala #1=Maize-Tephrosia candida relay/rotation, 2=Hand hoeing, 3=T. candida residues (5 Mg [ha.sup.-1]), 4= Blanket P , no N fertilizer Nyabeda #1. Maize-soybean rotatn, 2=no till, 3=Maize stover residues (2 Mg [ha.sup.-1]), 4=NPK fertilizer (60:60:60) Chitala #1=Maize-pigeon pea rotation, 2=Tractor till, 3=Crop residues: stem + leaves, 4=[(N[H.sub.4]).sub.2] S[O.sub.4] fertilizer (96 kg N [ha.sup.-1] [yr.sup.-1]) Ibadan #1=Maize-cowpea rotation, 2=Minimum tillage-light surface hoeing, 3=S. siamea (5 Mg [ha.sup.-1]), 4=fertilizer-NPK (60:30:30 kg [ha.sup.-1] [yr.sup.-1]) Tamale #1=Cont. maize, 2=Zero till-hand pulling/slashing of weeds, 3=no organic inputs, 4=no fertilizer Sadore #1=Millet-cowpea rotation, 2= Animal traction + ridging , 3=residues applied, 4=fertilizer (30kg N, 13 kg P [ha.sup.-1]) Farakoba #1. Cont. sorghum, 2=Tractor till, 3=compost (5 Mg [ha.sup.-1]), 4=PK fertilizer (25:14) Saria I #1=Sorghum-cowpea rotation, 2=Tractor till, 3=manure (5 Mg [ha.sup.-1] every 2 yrs), 4=NPK fertilizer (100 kg [ha.sup.-1]) and Urea (50 kg [ha.sup.-1]) every 2 years Saria II #1=Cont. sorghum, 2=Tractor till, 3=10 Mg [ha.sup.-1] manure, 4=fertilizer- 23kg N [ha.sup.-1] Saria III #1. Cont. sorghum, 2=Oxen plough, 3=Manure (10 Mg [ha.sup.-1]), 4=NPK fertilizer (100 kg [ha.sup.-1] [yr.sup.-1]) and Urea (50 kg [ha.sup.-1] [yr.sup.-1]) Trial site Arable-LC Embu #1=Cont. maize, 2=Hand hoeing, 3=no organic inputs, 4=no fertilizer Kabete #1. Maize-bean rotation, 2=Hand hoeing, 3= no organic inputs, 4=no fertilizer Impala #1= Cont. maize, 2=no till, 3=no organic inputs, 4=no fertilizer Nyabeda #1=Maize-soybean rotation, 2=hand hoeing, 3=no organic inputs, 4=NPK fertilizer (60:60:60) Chitala #1=Cont. maize, 2=Tractor till, 3=no organic inputs, 4=no fertilizer Ibadan #1=Maize-cowpea rotation, 2=Minimum tillage-light surface hoeing, 3=no organic inputs, 4=no fertilizer Tamale #1=Cont. maize, 2=Bullock plough-hand hoeing of weeds, 3=no organic inputs, 4=no fertilizer Sadore #1=Cont. millet, 2= Hand hoeing, no ridging, 3=residues applied, 4=fertilizer (13 kg P [ha.sup.-1]) Farakoba #1. Cont. sorghum, 2=tractor till, 3=no organic inputs Saria I #1=Cont. sorghum, 2=Tractor till, 3=manure (5 Mg [ha.sup.-1] every 2 yrs), 4=NPK fertilizer (100 kg [ha.sup.-1]) and Urea (50 kg [ha.sup.-1]) every 2 years Saria II #1=Cont. sorghum, 2=Tractor till, 3=no organic inputs, 4=no fertilizer Saria III #1=Cont. sorghum, 2=Hand hoeing (5cm depth), 3=Manure (10 Mg [ha.sup.-1]), 4=NPK fertilizer (100 kg [ha.sup.-1] [yr.sup.-1]) and Urea (50 kg [ha.sup.-1] [yr.sup.-1]) Table 3: Aggregate fraction distribution in the surface (0-15 cm) and sub-surface (15-30 cm) soil layers Aggregate fraction (g 100 [g.sup.-1] total soil) Treatment LM (>2000[micro]m) SM (250-2000[micro]m) Depth (0-15 cm) Fallow 19.03 (3.3)A 45.72 (3.5)A High-C 8.15 (1.7)B 42.48 (4.0)B Low-C 6.62 (1.5)B 38.32 (3.7)C p-value <0.001 <0.001 Depth (15-30 cm) Fallow 15.83 (2.5)A 49.46 (3.9)A High-C 13.80 (2.7)A 45.67 (3.8)B Low-C 13.14 (2.4)A 43.02 (3.9)B p-value 0.280 <0.001 Aggregate fraction (g 100 [g.sup.-1] total soil) Treatment Mi (53-250[micro]m) sc ([less than or equal to]53) Depth (0-15 cm) Fallow 30.74 (3.3)C 4.52 (0.4)C High-C 41.70 (3.5)B 7.67 (0.5)B Low-C 46.11 (3.0)A 8.95 (0.6)A p-value <0.001 <0.001 Depth (15-30 cm) Fallow 30.09 (3.3)B 4.62 (0.4)C High-C 34.79 (3.3)A 5.75 (0.5)B Low-C 37.32 (3.4)A 6.52 8.05)A p-value <0.001 <0.001 Aggregate fraction (g 100 [g.sup.-1] TM) Treatment cPOM ([greater than or equal to]250[micro]m) Depth (0-15 cm) Fallow 36.98 (6.8)C High-C 44.00 (7.4)B Low-C 46.79 (7.5)A p-value <0.001 Depth (15-30 cm) Fallow 36.30 (6.8)A High-C 39.93 (7.1)A Low-C 38.59 (7.0)A p-value 0.370 Aggregate fraction (g 100 [g.sup.-1] TM) Treatment mM (53-250[micro]m) scM ([less than or equal to]53) Depth (0-15 cm) Fallow 45.28 (4.6)A 17.73 (2.8)A High-C 42.30 (5.3)B 13.70 (1.4)B Low-C 41.00 (5.7)B 12.21 (2.2)B p-value 0.004 <0.001 Depth (15-30 cm) Fallow 46.26 (4.8)A 17.45 (2.8)A High-C 44.49 (5.5)A 12.57 (1.1)A Low-C 45.68 (5.1)A 15.58 (2.3)A p-value 0.729 0.124 Aggregate fraction (g 100 [g.sup.-1] TM) Treatment MWD (mm) Depth (0-15 cm) Fallow 1.51 (0.1)A High-C 0.95 (0.1)B Low-C 0.83 (0.1)B p-value <0.001 Depth (15-30 cm) Fallow 1.40 (0.1)A High-C 1.26 (0.1)A Low-C 1.20 (0.1)A p-value 0.062 Table 4: Whole soil C (g kg-1 soil) and aggregate fraction C (g 100 [g.sup.-1] total soil) LM (>2000[micro]m) Treatment WS (g kg-1 soil) Depth (0-15 cm) Fallow 18.34 (2.6)A 19.33 (3.3)A High-C 15.53 (2.1)B 15.61 (2.5)B Low-C 12.94 (1.8)C 11.49 (2.0)C p-value <0.001 <0.001 Depth (15-30 cm) Fallow 12.75 (1.9)A 13.66 (2.3)A High-C 12.61 (1.8)A 13.16 (2.2)A Low-C 11.95 (1.7)A 12.13 (1.9)A p-value 0.170 0.146 SM (250-2000[micro]m) Mi (53-250[micro]m) Treatment Depth (0-15 cm) Fallow 16.55 (2.7)A 19.21 (2.7)A High-C 14.38 (2.2)B 15.82 (2.0)B Low-C 11.76 (1.9)C 13.58 (1.7)C p-value <0.001 <0.001 Depth (15-30 cm) Fallow 13.94 (1.9)A 13.60 (1.9)A High-C 12.40 (1.8)B 13.23 (1.8)AB Low-C 12.22 (1.7)B 12.26 (1.7)B p-value 0.004 0.041 sc ([less than or equal to]53) Treatment (g 100 g-1 total soil) Depth (0-15 cm) Fallow 26.70 (2.7)A High-C 22.14 (2.0)B Low-C 19.41 (1.6)C p-value <0.001 Depth (15-30 cm) Fallow 20.24 (2.0)A High-C 19.77 (1.9)A Low-C 18.34 (1.8)A p-value 0.121 cPOM ([greater than or equal to]250[micro]m) Treatment Depth (0-15 cm) Fallow 12.88 (2.6)A High-C 11.08 (2.3)A Low-C 15.17 (3.3)A p-value 0.366 Depth (15-30 cm) Fallow 11.16 (1.9)A High-C 11.81 (2.4)A Low-C 9.84 (1.7)A p-value 0.105 mM (53-250[micro]m) scM ([less than or equal to]53) Treatment Depth (0-15 cm) Fallow 15.71 (1.9)B 24.38 (2.1)A High-C 17.53 (2.5)A 25.39 (2.6)A Low-C 13.77 (1.9)C 24.24 (1.8)A p-value <0.001 0.605 Depth (15-30 cm) Fallow 15.17 (1.8)A 23.52 (1.8)A High-C 14.72 (2.2)A 22.17 (1.9)A Low-C 12.95 (1.7)B 21.15 (1.6)A p-value 0.008 0.170 Table 5: Whole soil N (g kg-1 soil) and aggregate fraction N (g 100 [g.sup.-1] total soil) LM (>2000[micro]m) Treatment WS (g kg-1 soil) Depth (0-15 cm) Fallow 1.59 (0.2)A 1.58 (0.3)A High-C 1.35 (0.2)B 1.25 (0.2)B Low-C 1.10 (0.2)C 0.96 (0.2)C p-value <0.001 <0.001 Depth (15-30 cm) Fallow 1.13 (0.2)A 1.14 (0.2)A High-C 1.09 (0.2)AB 1.01 (0.2)AB Low-C 1.03 (0.2)B 0.94 (0.2)B p-value 0.026 0.002 SM (250-2000[micro]m) Mi (53-250[micro]m) Treatment (g 100 g-1 total soil) Depth (0-15 cm) Fallow 1.44 (0.2)A 1.62 (0.2)A High-C 1.18 (0.2)B 1.29 (0.2)B Low-C 0.96 (0.2)C 1.10 (0.1)C p-value <0.001 <0.001 Depth (15-30 cm) Fallow 1.17 (0.2)A 1.15 (0.2)A High-C 1.02 (0.2)B 1.09 (0.2)A Low-C 0.99 (0.1)B 1.02 (0.1)B p-value <0.001 0.003 sc ([less than or equal to]53) Treatment Depth (0-15 cm) Fallow 2.36 (0.3)A High-C 1.92 (0.2)B Low-C 1.63 (0.1)C p-value <0.001 Depth (15-30 cm) Fallow 1.77 (0.2)A High-C 1.70 (0.2)A Low-C 1.54 (0.1)B p-value 0.008 cPOM ([greater than or equal to]250[micro]m) Treatment Depth (0-15 cm) Fallow 0.81 (0.2)A High-C 0.75 (0.2)A Low-C 1.01 (0.2)A p-value 0.378 Depth (15-30 cm) Fallow 0.75 (0.1)A High-C 0.72 (0.2)A Low-C 0.64 (0.1)A p-value 0.184 mM (53-250[micro]m) scM ([less than or equal to]53) Treatment Depth (0-15 cm) Fallow 1.25 (0.2)B 2.24 (0.2)A High-C 1.39 (0.2)A 2.28 (0.2)A Low-C 1.08 (0.1)C 2.34 (0.2)A p-value <0.001 0.728 Depth (15-30 cm) Fallow 1.20 80.1)A 2.20 (0.2)A High-C 1.17 (0.2)B 2.05 (0.2)A Low-C 1.03 (0.1)C 2.01 (0.1)A p-value 0.007 0.164
|Printer friendly Cite/link Email Feedback|
|Title Annotation:||Borlaug LEAP Paper|
|Author:||Ayuke, F.O.; Zida, Z.; Lelei, D.|
|Publication:||African Journal of Food, Agriculture, Nutrition and Development|
|Date:||Jan 1, 2019|
|Previous Article:||Effects of Organic and Inorganic Fertilizers on the Soil Carbon Sequestration Influence of Mavuno and Manure Fertilization on Soil Carbon Fractions.|
|Next Article:||Climate Change Effects on Crop Production in Yatta sub-County: Farmer Perceptions and Adaptation Strategies.|