Assessing potential of Perennial Forages on Soil Carbon Sequestration Across Agroecological Zones with Varying Management Practices in Meru County

doi:10.21203/rs.3.rs-4963470/v1

The decline in soil organic carbon (SOC) due to continuous cultivation practices threatens soil productivity and compromises climate change mitigation efforts. This study investigates the effect of agro-ecological zones (AZ), management practices (MP), and specific forages on SOC and its related fractions: particulate organic carbon (POC) and mineral-associated organic carbon (MAOC). Conducted in Meru County, Eastern Kenya in 2021. Thirty-five predetermined perennial forage fields with Brachiaria (B), Panicum (Panicum maximum) (P), Napier grass (P.P. Schumach) (N), paired with maize (Zea mays) (M) growers, and with two management practices (FYM and inorganic fertilizer application) were selected per agro-ecological zone. A factorial plot design was employed, with zones as the main plots, the management practices as split plots, and the forages as split-split plots. Soil samples were collected from 1 m-by-1 m plots across 35 farms at depths of 0–50 cm, and analyzed for pH, bulk density, SOC content, POC, MAOC, and other micronutrients. Soil samples were statistically analyzed using two-way ANOVA. Bulk density ranged from 1.07 to 1.19 g cm^-3, with the highest values under inorganic fertilizers and the lowest under farmyard manure, showing significant differences between paired plots (p = 0.0011). Soil pH ranged from 5.13 to 5.36, and management practices significantly affected all micronutrients, with FYM combined with Panicum having the highest cation exchange capacity (19.45 cmol/kg) and manganese (96.30 ppm), and FYM combined with maize showing the highest available phosphorus (54.08 cmol/kg). Results showed no significant differences in mean values of POC and MAOC across zones, though the Lower Zone (LZ) had higher POC (6.63 g C kg^-1) and MAOC (7.24 g C kg^-1) compared to the Mid Zone (MZ) and Upper Zone (UZ). Different forages exhibited varying levels of MAOC, POC, and SOCs, with Brachiaria showing the highest SOC (15.69 g C kg^-1) and Panicum the lowest (14.84 g C kg^-1). Particulate organic carbon and MAOC content were significantly different across forages and maize (p < 0.05), with Brachiaria having higher MAOC (5.37 g C kg^-1) and POC (5.97 g C kg^-1). FYM combined with Brachiaria resulted in the highest POC (6.09 g C kg^-1) and MAOC (5.44 g C kg^-1). POC and MAOC concentrations varied significantly with soil depth, showing higher values in the top 10 cm. The Mid Zone recorded significantly higher SOC, POC, and MAOC than the UZ and LZ. This study concludes that agro-ecological zones and management practices substantially influence SOC sequestration, with FYM and Brachiaria being most effective in LZ.

agro ecological zones

brachiaria

Forages

panicum

soil organic carbon fractions

In many developing countries, agriculture serves as the cornerstone of the economy, supporting livelihoods and food security for millions of people (Arias et al., 2013). Smallholder farming systems, which integrate crops and livestock and rely largely on rain-fed agriculture, are particularly prevalent in Sub-Saharan Africa (SSA) (Rao et al., 2011). These systems are essential, contributing up to 80% of total food consumption in the region (Arias et al., 2013). However, they face numerous challenges exacerbated by climate change, including soil degradation, nutrient depletion, and reduced agricultural productivity (Rao et al., 2011). Forage-based livestock production dominates over 70% of agricultural land in tropical regions, playing a critical role in food production and income generation (Rao et al., 2011). Yet, the resilience of these systems is increasingly tested by climate change-related factors such as altered rainfall patterns, increased incidence of pests and diseases, and more frequent extreme weather events (Rao et al., 2011). These challenges not only threaten agricultural productivity but also exacerbate land degradation, which in turn impacts ecosystem services crucial for maintaining soil fertility and productivity (CBD, 2011).

In Kenya, for instance, significant portions of land—more than 20%—have been severely degraded due to a combination of factors like weak soil structure, overgrazing, compaction from heavy machinery, and inadequate land management practices (Gicheru et al., 2021). These practices contribute to the loss of soil organic carbon (SOC), a vital component for soil health and agricultural sustainability (Gicheru et al., 2021). SOC plays a crucial role in soil structure, water retention, nutrient cycling, and carbon sequestration, thereby influencing both agricultural productivity and climate change mitigation efforts (Lal, 2018). Effective management strategies to preserve SOC in tropical cropping systems include reduced tillage, application of organic inputs like manure and crop residues, and erosion control measures (Sommer et al., 2018). These practices help to slow down the rate of SOC loss and maintain soil fertility over time (Sommer et al., 2018). Understanding the dynamics of SOC, including its fractions such as particulate organic matter (POM) and mineral-associated organic matter (MAOM), is essential for developing targeted soil management practices that enhance carbon sequestration and agricultural sustainability (Six et al., 2020).

Introducing and promoting the cultivation of forage species like Brachiaria spp. represents a promising strategy for enhancing SOC levels in SSA (Cheruiyot et al., 2020; Maass et al., 2015). Brachiaria spp., known for its deep rooting system, high biomass production, and adaptation to low fertility and drought-prone conditions, has shown significant potential in improving soil organic carbon stocks and enhancing livestock productivity (Cheruiyot et al., 2020; Maass et al., 2015). These forages not only contribute organic matter to the soil but also improve soil structure, reduce erosion, and increase soil water holding capacity, thereby enhancing overall soil health and resilience to climate variability. In contrast, traditional annual crops like maize (Zea mays) typically have shorter growing periods and lower biomass production compared to perennial forages (Das et al., 2017). Moreover, maize cultivation often involves intensive tillage practices that can accelerate SOC decomposition and reduce soil carbon stocks, particularly in fragile and erosion-prone soils (Das et al., 2017).

Future research should focus on conducting long-term field studies to monitor SOC dynamics under different cropping systems and management practices (Sommer et al., 2018). Evaluating the impacts of Brachiaria spp. and maize cultivation on SOC dynamics, including POM and MAOM fractions, will provide valuable insights into sustainable agricultural practices that enhance soil health and resilience to climate change impacts (Six et al., 2020). Furthermore, incorporating socio-economic factors and farmer perceptions into research and development initiatives can help to ensure the adoption and scalability of these practices among smallholder farmers in SSA.

In conclusion, effective management of soil organic carbon is critical for achieving sustainable agricultural development, enhancing food security, and mitigating climate change impacts in tropical farming systems (Lal, 2018). By promoting practices that preserve and enhance SOC levels, such as integrating forage species like Brachiaria spp., SSA countries can improve soil fertility, increase agricultural productivity, and contribute to global efforts towards climate change adaptation and mitigation. These strategies are particularly relevant in regions like Meru County, Kenya, where smallholder farming dominates and faces challenges from climate variability and land degradation, highlighting the urgent need for sustainable soil management practices.

Study area

The study was conducted in August 2021 in Meru County. The altitude of this area is 1526 m above sea level and is located on the Eastern slopes of Mt. Kenya. The county has a bi-modal rainfall pattern, with the long rains running from March to June, and the short rains start in October and end in December. The area has an annual rainfall of between 1200 mm to 1400 mm (Ngetich et al., 2014) and an average yearly temperature of 20^oC (Nderi et al., 2015). The soil type at the experimental field is humic Nitisol (IUSS WG WRB, 2015). It is well weathered with moderate to high inherent fertility, clay textured (Omenda et al., 2021), and highly acidic with high iron oxide content favoring P-sorption with moderately low cation exchange capacity (CEC).

The main economic activities are agriculture; livestock keeping, and farming of food crops such as bananas (Musa acuminate), corn (Zea mays)), beans (Phaseolus vulgaris), sweet potatoes (Ipomoea batatas), yams (Dioscorea alata), cassava (Manihot esculenta) and Irish potatoes (Solanum tuberosum) while cash crops include tea (Camellia sinensis), coffee (Coffea arabica), tobacco (Nicotiana tabacum) and butternut (Cucurbita moschata) (Njue et al., 2020).

Map 1: Meru County Source: Kenya National Bureau of Statistics

Paired plots sites selection

The study was carried out in the Meru County, Eastern part of Kenya. The main economic activity in these two regions is agricultural production with more than 50% doing intensive mixed farming and dairy farming. Rainfall pattern is bi-modal, long rain seasons from March to August and the short season is from October to January. Thirty-five perennial forage grass growers from each region were selected to participate in the research. This was done by generating a checklist of all farmers from three zones (upper, Mid and lower zone) who grow Brachiaria spp, Panicum (Panicum maximum), Napier grass (P.P. Schumach) Rhodes paired with corn (Zea mays) field with help of a frontline extension staff. A semi-structured questionnaire was used to determine the forage years of production with a target of < 3 years, 3 years and > 3 years for the selected perennial forages Panicum (Panicum maximum) (P), (Bracharia (B) and Nappier (N) in addition data on soil management practices and previous land uses were captured in the questionnaire.

Research design and Soil sampling

A factorial plot design was employed, with zones as the main plots, the management practices as split plots, and the forages as split-split plots. Soil samples were collected from 1 m-by-1 m plots across 35 farms at depths of 0–50 cm, and analyzed for pH, bulk density, SOC content, POC, MAOC, and other micronutrients

Bulk Density determination

Coring rings of known volume were used to collect the samples. Sampling was done carefully by driving the coring ring into the soil using hand sledge and a block of wood. Analysis of soil bulk density was done using the methodology described by Cresswell and Hamilton (2002). Oven proof containers were weighed first before the soil is transferred. The soil and the container were oven dried at 105^o C for 24 hours. The soil and container were then removed from the oven and left to cool in a desiccator then weighed and recorded.

Soil bulk density (g cm-³) was then be calculated as shown (Eq. 1):

Where;

BD Sample is the bulk density (g cm-³) of the soil sample, ODW Sample the mass (g) of oven dried soil core and CV Sample core volume (cm³) of the soil sample.

Soil reaction (pH) determination

The pH was measured with a glass electrode pH meter on 1: 2.5 (^w/_v) suspension of soil in water, in all cases after shaking for 30 minutes (Okalebo et al., 2002).

Soil organic carbon Determination-Soil organic carbon (SOC) was determined using the Walkley black method

Soil organic carbon stock calculations

SOC stock (Mgha^− 1=SOC (%) X Bulk density (gcm³) x soil depth (cm) x cf

Where: SOC- concentration of soil organic carbon (%); BD– bulk density (g/cm³); SD – topsoil depth (cm). cf is the conversion factor = (kg cm^− 3) × (10,000 cm² m^− 2) × (10,000 m² ha ¹).

Mineral-associated organic carbon (MAOC) and particulate organic carbon (POC) determination

SOM were separated into mineral-associated organic carbon (MAOC) and particulate organic matter (POC) using size fractionation procedure (Cambardella and Elliott 1992) as modified by Brad-ford et al. (2008). 10 g of air-dried soil were extracted with 30 mL Sodium hexametaphosphate solution (5 g L − 1) in 100 mL sampling bottles and shaken horizontally for 18 h. After 18 h, the sample were then be passed through a 0.053 mm sieve. The fraction retained on the sieve as POC while the finer, clay and silt fraction that were pass through the sieve as MAOM.

Statistical analysis

Effects of planted forages and corn (Zea mays) plantations on total SOC, SOC fractions, and the interactions were analyzed by two-way analysis of variance (ANOVA) using Genstat 15thedition. Means were separated using Fischer’s protected least significant difference (LSD) test at P ≤ 0.05. A simple linear regression analysis was used to reveal the relationship between SOC and its fractions and Perennial forages and corn (Zea mays) plots.

Interactive effects of zone and forages on soil BD, pH and soil micronutrients

Bulk density for the interaction of Mgt*F/C ranged from 1.07 and 1.19 g cm^− 3 with the highest mean of 1.19 g cm^− 3 under IF*N and 1.19 g cm^− 3 at IF*M while that in the FYM plots were the lowest as compared to IF though not significantly (p < 0.05) different with 1.12 g cm^− 3 under FYM*N and 1.07 g cm^− 3 at FYM*M. There were significant differences in the bulk density between the paired plots (p = 0.0011). Soil pH of the study sites ranged from 5.13 to 5.36. Results showed that the management had a significant (p < 0.05) effect on all the micronutrients. For instance, the FYM*P had the highest cation exchange (19.45 cmol/kg), Manganese (96.30 ppm), FYM*M-available Phosphorous (54.08 cmol/kg) (Table 1).

Table 1

Interactive effects of zone and forages on soil pH and soil micronutrients
Mgt	F/c	BD g cm-3	pH (H₂O)	Mn_ ppm	Zn_ ppm	cmol_ kg_CEC	ppm_ Cu	ppm_ Fe	ppm_ P
IF	N	1.19a	5.13^a	88.65^b	9.47^bc	21.39^b	2.698^ab	55.84^a	39.15^b
	BR	1.12a	5.25^a	86.54^a	7.82^a	19.37^a	2.411^ab	63.51^c	34.41^a
	M	1.18a	5.27^a	94.93^c	11.21^e	22.50^b	2.311^a	55.47^a	53.73^d
	P	1.14a	5.19^a	95.93^cd	11.10^de	19.10^a	2.502^ab	60.48^b	41.84^c
FYM	N	1.12a	5.23^a	89.02^b	9.84^cd	21.74^b	2.747^b	56.21^a	39.50^b
	BR	1.13a	5.33^a	86.91^a	8.19^ab	19.72^a	2.460^ab	63.88^c	34.76^a
	M	1.07a	5.36^a	95.30^cd	11.58^e	22.84^b	2.360^ab	55.84^a	54.08^d
	P	1.07a	5.32^a	96.30^d	11.47^e	19.45^a	2.551^ab	60.85^b	42.19^c

F/C-Forage/crop MGT-Management BR-Brachiaria spp M-Maize (Zea mays) N-Napier P-Panicum (Panicum maximum)

Means followed by the same superscript letter (within a column of each parameter) are not significantly (p < 0.05) different (p ≤ 0.05) by Tukey’s HSD test.

Effects of Forages and Maize (Zea mays) and depth on Particulate organic carbon (POC) and Mineral Associated Organic Carbon (MAOC) content

Particulate organic carbon and Mineral Associated Organic Carbon content for the for the three forages and Maize (Zea mays) were significantly (p < 0.05) different. The average MAOC concentration ranged from 4.39 g C kg^− 1 to (5.37 g C kg^− 1) (Table 3). With Brachiaria spp being higher (5.37(g C kg^− 1) than those of Maize (Zea mays) (4.45 (g C kg^− 1), Napier grass (P.P. Schumach) (4.63 C kg^− 1) and Panicum (Panicum maximum) (4.39 (g C kg^− 1). The same was observed for Particulate organic carbon. It was significantly (p < 0.05) higher under Brachiaria spp (5.97g C kg^− 1 ) as compared to Panicum (Panicum maximum) (5.38g C kg^− 1), Maize (Zea mays) 5.86g C kg^− 1 and Napier grass (P.P. Schumach) (5.42 g C kg^− 1) (Table 3).The results from this study showed that the mean values of POC at different depths were not significantly (p < 0.05). However, 0–10) had higher POC (5.72 g C kg^− 1) than 11–20 (5.65 g C kg^− 1), and 21–50 (5.61 g C kg^− 1). Whereas for the MAOC there were significantly (p < 0.05) different at all the depths with highest recorded in 0–10 (4.84 g C kg^− 1) followed by lower11-20 and 21–50 with 4.77 and 4.53 g C kg^− 1) respectively.

Table 2: Soil Organic Carbon stocks, Soil Organic Nitrogen stocks and CN ratio under different forages

Forage/crop	SOCs Mg/ha	SONS (Mg/Kg)	CN ratio
BR	18.28^c	3.34^a	5.5
M	15.61^b	3.39^a	4.6
N	11.10^a	3.40^a	3.3
P	20.50^d	3.85a^b	5.3

Means followed by the same superscript letter (within a column of each parameter) are not significantly (p<0.05) different by Tukey’s HSD test.

Table 3

Effects of Forages and Maize (Zea mays) and depth on Particulate organic carbon (POC) and Mineral Associated Organic Carbon (MAOC) content
Forage	Panicum	Napier	Maize	Brachiaria
MAOC_ g C kg^− 1	4.45^a	4.63^b	4.39^a	5.37^c
POC_g_C_kg_1	5.86 ^b	5.42 ^a	5.38 ^a	5.97^b
Depth	0–10	11–20	21–50
MAOC_g_C_kg_1	4.84^b	4.77^b	4.53^a
POC_g_C_kg_1	5.71^a	5.65^a	5.61^a

Means followed by the same superscript letter (within a row of each parameter) are not significantly (p < 0.05) different by Tukey’s HSD test.

Interactive effects of management and forage/crop on Particulate organic carbon (POC) and Mineral Associated Organic Carbon (MAOC) content

The results from this study showed that the interactive (Mgt*F/C) mean values of POC and MAOC were significantly (p < 0.05) different. Thus, FYM*Br had significantly (p < 0.05) higher POC (6.09 g C kg^− 1) than FYM*P (5.49 g C kg^− 1) and FYM*N (5.53 g C kg^− 1) but not significantly (p < 0.05) different from FYM*M (5.98 g C kg^− 1). There was also a significant difference for MAOC for different interaction of Mgt*FC with highest recorded in FYM*Br (5.44 g C kg^− 1) than other interactions but not significantly (p < 0.05) different from IF*Br (5.29 g C kg^− 1) (Table 4).

Table 4

Interactive effects of management and forage/crop on Particulate organic carbon (POC) and Mineral Associated Organic Carbon (MAOC) content
Management	FORAGE/CROP	POC_g_C_kg_1	MAOC_g_C_kg_1
Inorganic Fertilizer	Napier	5.304^ab	4.557^ab
	Brachiaria	5.859^de	5.293^c
	panicum	5.746^cd	4.379^a
	Maize	5.264^a	4.318^a
Farmyard Manure	Napier	5.534^bc	4.704^b
	Brachiaria	6.089^e	5.439^c
	panicum	5.976^de	4.526^ab
	Maize	5.494^abc	4.465^ab

Means followed by the same superscript letter (within a column of each parameter) are not significantly (p < 0.05) different by Tukey’s HSD test.

Effects of zone on Particulate organic carbon (POC) and Mineral Associated Organic Carbon (MAOC) content

The result from this study shows that the mean values of POC and MAOC were not significantly (p < 0.05) different in the three zones. Thus, mid zone has significantly (p < 0.05) higher POC (3.32 g C kg^− 1) than upper zone (2.97 g C kg^− 1) and lower zone (2.83 g C kg^− 1). Whereas for the MAOC there were not significantly (p < 0.05) difference at the three zones with highest recorded in upper zone (3.49 g C kg^− 1) followed by Mid and lower zone with 3.46 ¹ and 3.31 g C kg^− 1 respectively (Fig. 3).

Soil Organic Carbon stocks, Soil Organic Nitrogen stocks CN ratio under different forages

Soil organic carbon fractions, SOC and SON stocks varied with different forages/crop. Higher mean SOC stock (20.50 Mg/ha) was observed in the Panicum (Panicum maximum) than in Brachiaria spp and maize (P.P. Schumach) (18.28 and 15.30 Mg/ha) respectively. SOCs in maize was significantly (p < 0.05) different from the three forages Panicum (Panicum maximum), Brachiaria spp and Napier grass. The results also indicated that Soil Organic Nitrogen stocks were no significantly (p < 0.05) different for all the forages and Maize (Zea mays) with Panicum recording the highest 3.85 Mg/ha than the other forages and maize. CN ratio ranged from 3.3–5.5 (Table 2).

Interactive eeffects of zone and forage/maize on soil organic carbon stocks (SOC), Particulate organic carbon (POC) and Mineral Associated Organic Carbon (MAOC) content

The results from this study shows that the mean values of SOCs, POC and MAOC are were significantly (p < 0.05) different in the three zones. Thus, mid zone has significantly (p < 0.05) higher SOCs and POC (24.92 and 12.1 Mg/ha) than upper zone (21.52 and 9.65 Mg/ha) and lower zone (15.05 and 7.1 Mg/ha) respectively in panicum forage. Whereas for the MAOC there were no significantly (p < 0.05) difference at the three zones with highest recorded in Mid-zone (11.77 Mg/ha) followed by upper zone and lower zone with 10.81 and 6.54 Mg/ha respectively (Fig. 3).

Regression analysis

Mid zone and upper zone were inversely correlated (r = -2.03E + 00 and r = -2.35E + 00; p < 0.001) to soil POC (Table …). Among the forages maize and Napier showed inverse correlation r =-1.75E + 00 and r =-2.23E + 00; p < 0.05). For the interaction of zone and forages (MZ*M r = 2.62E + 00, MZ*N r = 3.53E + 00, MZ*P r = 1.87E + 00 and UZ*P r = 3.16E + 00) showed positive correlations (p < 0.001). UZ*N*D also showed a positive correlation with soil POC at p < 0.01.

Table 5

Regression analysis of POC with zones, forage, and depth
	Estimate	Std. Error	t value	Pr(>\|t\|)
(Intercept)	7.79E + 00	2.63E-01	29.604	< 2e-16	*******
Zone MZ	-2.03E + 00	3.72E-01	-5.455	1.73E-07	*******
Zone UZ	-2.35E + 00	3.72E-01	-6.32	2.27E-09	*******
Forage M	-1.75E + 00	3.72E-01	-4.697	5.46E-06	*******
Forage N	-2.23E + 00	3.72E-01	-6.001	1.17E-08	*******
Forage P depth	-2.19E + 00	3.72E-01	-5.892	2.03E-08	*******
Zone MZ: Forage M	2.62E + 00	5.26E-01	4.976	1.59E-06	*******
Zone UZ: Forage M	2.73E + 00	5.26E-01	5.189	6.05E-07	*******
Zone MZ: Forage N	3.53E + 00	5.26E-01	6.712	2.82E-10	*******
Zone MZ: Forage P	1.87E + 00	5.26E-01	3.559	0.000484	*******
Zone UZ: Forage P	3.16E + 00	5.26E-01	6.012	1.11E-08	*******
Zone UZ: forage N: depth	6.71E-02	2.44E-02	2.754	0.006543	**
Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1
Residual standard error: 0.2984 on 168 degrees of freedom
Multiple R-squared: 0.9101,	Adjusted R-squared: 0.885
F-statistic: 36.21 on 47 and 168 DF, p-value: < 2.2e-16

Regression analysis of MAOC with SOC, SON, POC, zones, forage, and depth

Agro-ecological zones showed significant effects on MAOC, with the Mid Zone (MZ) coefficient of 1.045832 and Upper Zone (UZ) coefficient of 1.028316 both significantly positive (p < 0.001). The type of management practice (IF for inorganic fertilizer) did not show a significant effect on MAOC (p = 0.5198), indicating that while agro-ecological zones play a role. Forage types exhibited distinct effects on MAOC, with coefficients of -0.95347 for Maize (M), -0.52554 for Napier grass (N), and − 1.3386 for Panicum (P) compared to a reference forage type, likely Brachiaria spp (Table 6). Analysis of depth (0.010042, p = 0.31197) revealed that MAOC did not vary significantly with soil depth. Significantly, SOC (0.533876, p = 0.02292), SON (3.52735, p = 0.00537), and POC (0.262648, p = 1.11E-07) all showed positive relationships with MAOC. the regression model demonstrated a good fit (Multiple R-squared = 0.6609, Adjusted R-squared = 0.6427) and statistical significance (F-statistic = 36.15, p < 2.2e-16).

Table 6

Regression analysis of MAOC with SOC, SON, POC, zones, forage, and depth
Coefficients	:
	Estimate	Std. Error	t value	Pr (>\|t\|)
(Intercept)	1.723487	0.692327	2.489	0.0136	*
Zone MZ	1.045832	0.101064	10.348	< 2e-16	***
Zone UZ	1.028316	0.174705	5.886	1.61E-08	***
Management IF	0.058037	0.090012	0.645	0.5198
Forage M	-0.95347	0.106398	-8.961	< 2e-16	***
Forage N	-0.52554	0.111961	-4.694	4.91E-06	***
Forage P	-1.3386	0.205885	-6.502	5.99E-10	***
depth	0.010042	0.009907	1.014	0.31197
SOC	0.533876	0.232928	2.292	0.02292	*
SON	3.52735	1.253422	2.814	0.00537	**
POC	0.262648	0.047729	5.503	1.11E-07	***
Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1
Residual standard error: 0.5314 on 204 degrees of freedom
Multiple R-squared: 0.6609,	Adjusted R-squared: 0.6427
F-statistic: 36.15 on 11 and 204 DF, p-value: < 2.2e-16

Effects of zone, Forages/forages and depth on Soil Organic Carbon and Soil Organic Nitrogen concentrations

The study revealed significant variations in soil organic carbon (SOC) and soil organic nitrogen (SON) stocks among different forages and crops, underscoring the influence of different forages on soil carbon and nitrogen dynamics. Panicum maximum (Panicum) exhibited the highest mean SOC stock at 20.50 Mg/ha, followed by Brachiaria spp at 18.28 Mg/ha, and maize (Zea mays) at 15.30 Mg/ha. This variation can be attributed to several factors related to plant characteristics and litter quality.

Research supports those perennial grasses like Panicum, with their extensive root systems and high biomass production, contribute significantly to SOC sequestration. These plants enhance organic matter input into the soil, promoting SOC accumulation through root turnover and litter decomposition processes (Zimmermann et al., 2012; Maass et al., 2015). In contrast, maize, being an annual crop with different growth patterns and litter quality, may contribute less to SOC formation due to lower quality residues and less extensive root systems compared to perennial grasses (Loss et al., 2013).

Although SOC varied significantly among the forages, SON stocks showed no significant differences. This suggests that while different plants may affect SOC accumulation differently, they may have similar impacts on SON stocks, possibly due to comparable nitrogen inputs from root exudates and decomposition residues across the forages (Yadav et al., 2019). The C ratio, which ranged from 3.3 to 5.5 across the different forages and crops, indicates variations in the decomposition rates of organic matter and nitrogen mineralization potential. Lower C ratios generally imply faster decomposition and potentially higher nitrogen mineralization rates, influencing soil fertility and nutrient availability (Sarkar et al., 2018; Wang et al., 2021).

Application of farmyard manure (FYM) was found to increase SOC content due to its carbon content and improved soil water holding capacity, essential for soil nutrient enhancement (Lehmann et al., 2020). FYM stimulates microbial populations and enhances soil conditions, accelerating organic matter decomposition and carbon release (Huang et al., 2019; Six et al., 2020). This enhancement in microbial activity contributes significantly to the buildup of soil organic carbon, crucial for soil fertility and ecosystem health. Farmyard manure (FYM) serves as a valuable source of soil nutrients and contributes to the improvement of soil physical structure (Lehmann et al., 2020). Application of farmyard manure (FYM) is a widely adopted method to enhance soil fertility by increasing soil available nutrients (Singh et al., 2020; Singh et al., 2021). Recent studies indicate that forage crops exhibit luxury consumption of nutrients when supplemented with inorganic fertilizers, depleting soil reserves due to the immediate availability of nutrients (Khan et al., 2019; Nigussie et al., 2020). This phenomenon underscores the importance of sustainable nutrient management practices in agriculture.

Forage crops like Panicum and Brachiaria exhibit substantial carbon sequestration potential, attributed to their robust root systems and efficient nutrient uptake (Smith et al., 2019; Wang et al., 2021). These findings underscore the importance of selecting appropriate forages in agricultural systems to enhance SOC levels and overall ecosystem resilience. Root-derived carbon inputs, rapidly absorbed and preserved within soil aggregates, further contribute to particulate organic matter and humus fractions, supporting long-term soil organic matter dynamics and carbon sequestration (Fornara and Tilman, 2008; Lehmann et al., 2020).

Effects of Zone, Forages/Maize (Zea mays) and Depth on Particulate organic carbon (POC) and Mineral Associated Organic Carbon (MAOC) content.

The above-ground dry matter contributes to increase in MAOC in the top layer (0–10 cm depth) of soil depth. The same was reported by Saraiva et al. (2014), that highest carbon stocks in the soil surface (0–10 cm depth) are due to the deposition of residues from the forage/crop in addition to root system concentrated into the top layers of soil.

The results obtained in this research indicate that Brachiaria spp and Panicum (Panicum maximum) showed an increase the POC content. This is attributable to high amount of residues above-ground and also direct influence of roots as the primary source of soil carbon and particularly to POC and MAOC as reflected in panicum and Brachiaria spp. plots. Thus, the greater below ground root biomass of the Brachiaria and panicum forages led to an increase in microbial activity and hence increased POC and MOAC as compared to Napier and Maize. This concurs with findings from Loss et al. (2013), indicating that the voluminous root systems of Panicum (Panicum maximum) and Brachiaria spp. contribute significantly to soil organic matter (SOM) accumulation. Recent studies continue to support this observation, underscoring the role of extensive root systems in enhancing SOM content and carbon sequestration (Kumar et al., 2020; Wang et al., 2021). Additionally, there is a higher canopy in the panicum and brachiaria resulting to higher soil moisture content, encouraged high litter turnover and thus increased SOC from the surface. Protective cover over the soil surface has been demonstrated to reduce the impacts of wind and water erosion on surface horizons (Devagiri et al., 2013). Higher levels of mineral-associated organic carbon (MAOC) are associated with the decomposition of plant residues and nutrient mineralization (Six et al., 2020; Lehmann et al., 2020). Previous studies have reported that Brachiaria spp. positively affects particulate organic carbon (POC) due to increased organic residue inputs into the soil (Cheruiyot et al., 2020). Moreover, Lopes et al. (2010) associated the higher MAOC content in Brachiaria spp. with greater shoot dry matter production and exudate release compared to other species.

From this research it is evident that POC was higher in the mid zone than other zones. This shows that forage/crop biomass changes with the zones and this highly impacts SOC input, hydrological processes and thus the effect on Particulate organic carbon and mineralized associated organic carbon. The mid zone, as characterized by Fernández-Romero et al. (2014), experiences distinct climate conditions that affect vegetation biomass and productivity, thereby influencing the quantity of organic carbon input into the soil. Recent studies continue to highlight the variability in climate conditions across different zones and its impact on soil organic carbon dynamics (Smith et al., 2020; Wang et al., 2021)

Research supports that different agro-ecological zones can significantly influence soil carbon fractions due to varying environmental conditions and management practices. For instance, studies by Zhao et al. (2018) and Smith et al. (2020) highlight how soil carbon levels can vary across different geographical zones, influenced by factors such as climate, soil type, and vegetation cover. The mid zone's higher SOC and POC levels align with findings by Peters et al. (2012), who emphasize the role of favourable environmental conditions and plant species in promoting carbon sequestration through increased root biomass and organic matter inputs.

Regarding MAOC, although no significant differences were observed among the three zones in this study, previous research by Wang et al. (2019) and Liu et al. (2021) underscores the stability of mineral-associated organic carbon across diverse environmental gradients. This stability suggests that while particulate organic carbon may vary with management practices and environmental conditions, mineral-associated organic carbon remains relatively consistent due to its bonding with soil minerals.

Regression analysis of MAOC with SOC, SON, POC, zones, forage, and depth

The correlations observed between agro-ecological zones and different forages in relation to soil particulate organic carbon (POC) provide insights into how environmental factors and plant species interact to influence carbon dynamics in agricultural soils. The inverse correlations between the mid zone and upper zone (r = -2.03E + 00 and r = -2.35E + 00; p < 0.001) with soil POC suggest contrasting impacts of these zones on carbon accumulation. This pattern aligns with studies that highlight varying soil carbon levels across different agroecological zones and management practices (Zhao et al., 2018; Smith et al., 2020).

Among the forages, maize and Napier grass showed inverse correlations with soil POC (r = -1.75E + 00 and r = -2.23E + 00; p < 0.05), indicating that these crops may have lower contributions to particulate organic carbon compared to other forages such as Panicum maximum and Brachiaria spp. This finding is consistent with research demonstrating the differential effects of plant species on soil carbon dynamics, influenced by factors such as root biomass, litter quality, and turnover rates (Loss et al., 2013; Kumar et al., 2020).

The positive correlations observed between the interaction of zones and forages (Mid Zone Maize r = 2.62E + 00, Mid Zone Nappier r = 3.53E + 00, Mid Zone Panicum r = 1.87E + 00, and Upper zone Panicum r = 3.16E + 00; p < 0.001) underscore how specific combinations of agro-ecological conditions and forage types can synergistically enhance soil POC levels. This synergy reflects the combined influence of favorable environmental factors and plant characteristics that promote carbon sequestration through increased root biomass and organic matter inputs (Peters et al., 2012; Kumar et al., 2020).

Furthermore, the positive correlation between Upper Zone Nappier and soil POC (p < 0.01) suggests that specific management practices or environmental conditions in the upper zone with Napier grass may also contribute positively to POC accumulation. This aligns with studies emphasizing the role of management strategies, such as organic residue management and soil conservation practices, in enhancing soil carbon storage (Devagiri et al., 2013; Lehmann et al., 2020).

This study demonstrates that agro-ecological zones significantly influence soil organic carbon (SOC) dynamics, with the Lower Zone exhibiting higher particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) compared to other zones. Integrated nutrient management practices, particularly the use of farmyard manure (FYM) with Brachiaria forages, proved effective in enhancing SOC levels and soil nutrient content. These findings underscore the importance of soil management strategies to sustainably improve carbon sequestration and soil fertility in tropical smallholder farming systems.

Supplementary Information

Not applicable

Acknowledgements

This work was supported by CLIFF-GRADS ROUND IV

Funding Not applicable

Data availability

Upon request, the corresponding author can provide the data supporting the findings of this study.

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All authors have reviewed the manuscript and agree to its submission to this journal.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Informed consent to participate

The sampling was conducted on farmers field and permission was obtained from the farmers to sample at their field.

Compliance with Ethical Standards

The protocols for this research was approved by NACOSTI Committee in accordance with the NATIONAL COMMISSION FOR SCIENCE, TECHNOLOGY AND INNOVATION (NACOSTI)

Arias, P., Arce, A., Pineda, H., & Alvarado, G. (2013). The importance of smallholder farms for food security in sub-Saharan Africa. *Revista de Ciencias Sociales, 136*, 49-62.
Arias, P., Martínez-Casasnovas, J. A., & Lloveras, J. (2013). Factors affecting land use in small Mediterranean catchments under extensive agriculture. *Land Degradation & Development, 24*(6), 537-551.
Arias, P., Hallam, D., Krivonos, E., & Morrison, J. (2013). *Smallholder Integration in Changing Food Markets*. Food and Agriculture Organization of the United Nations: Rome, Italy.
Bradford, M. A., Keiser, A. D., Davies, C., et al. (2013). Empirical evidence that soil carbon formation from plant inputs is positively related to microbial growth. *Biogeochemistry, 113*, 271–281.
Camberdella, C. A., & Elliott, E. T. (1992). Particulate soil organic-matter changes across a grassland cultivation sequence. *Soil Science Society of America Journal, 56*(3), 777–783.
CBD (2011). *Climate Change and Biodiversity*. CBD Technical Series No. 58, Montreal, Canada.
Cheruiyot, E. K., Njarui, D. M., Mukisira, E. A., & Gichangi, E. M. (2020). Forage options for sustainable intensification of crop-livestock systems in Sub-Saharan Africa. *Agriculture, Ecosystems & Environment, 287*, 106690.
Das, A., Ghosh, P. K., Lal, R., Saha, R., & Ngachan, S. (2017). Soil quality effect of conservation practices in maize–rapeseed cropping system in Eastern Himalaya. *Land Degradation & Development, 28*(6), 1862-1874.
Das, A., Ghosh, P. K., Manna, M. C., Bandyopadhyay, K. K., & Mandal, B. (2016). Soil organic carbon sequestration potential of maize–legume intercropping systems in relation to nutrient-use efficiencies using 13C natural abundance technique. *European Journal of Agronomy, 72*, 91-102.
Das, S., Saha, R., & Senapati, N. (2017). Effect of tillage and crop establishment methods on soil organic carbon sequestration and agronomic performance of rice (Oryza sativa L.) in Eastern Himalayas. *Agricultural Research, 6*(3), 330-338.
Devagiri, G. M., Nagaraju, M. S. S., & Vinay, B. (2013). Effect of protective tillage on soil properties and yield of maize (Zea mays L.). *Karnataka Journal of Agricultural Sciences, 26*(3), 325-328.
Duncan Cheruiyot, Charles A. O., Midega, J. O., Pittchar, J. O., Pickett, J. A., & Khan, Z. R. (2020). Farmers’ Perception and Evaluation of Brachiaria spp Grass (Brachiaria spp.) Genotypes for Smallholder Cereal-Livestock Production in East Africa. *Agriculture, 10*, 268.
Fernández-Romero, M. L., Lozano-García, B., & Parras-Alcántara, L. (2014). Topography and land use change effects on the soil organic carbon stock of forest soils in Mediterranean natural areas. *Agriculture, Ecosystems & Environment, 195*, 1–9.
Gicheru, P. T., Ngetich, K. F., & Kamau, P. W. (2021). Land degradation assessment using remote sensing and geographic information systems in Kajiado County, Kenya. *Journal of Arid Environments, 186*, 104435.
Herrero, M., Thornton, P. K., Power, B., Bogard, J. R., Remans, R., Fritz, S., & Gerber, J. S. (2020). Farming and the geography of nutrient production for human use: a transdisciplinary analysis. *The Lancet Planetary Health, 4*(10), e438-e444.
Rao, I., Ishitani, M., Miles, J., Peters, M., Tohme, J. O. E., & Martens, S. G. V. (2014). Climate-smart crop-livestock systems for smallholders in the tropics: Integration of new forage hybrids to intensify agriculture and to mitigate climate change through regulation of nitrification in soil. *Tropical Grasslands – Forrajes Tropicales, 2*, 130-132.
Lal, R. (2018). Digging deeper: A holistic perspective of factors affecting soil organic carbon sequestration in agroecosystems. *Global Change Biology, 24*(8), 3285-3301.
Lopes, A. S., Barioni, L. G., Pereira, O. G., Queiroz, A. C., & Berchielli, T. T. (2010). Evaluation of the degradation potential of brachiaria brizantha cv. marandu under different cutting management. *Scientia Agricola, 67*(2), 202-207.
Loss, A., Pereira, M. G., Carvalho, J. L. N., & Fagundes, G. R. (2013). Soil physical quality under different management systems in the Amazon region of Brazil. *Soil and Tillage Research, 126*, 177-184.
Maass, B. L., Muschler, R. G., & Hussein, A. (2015). Past, present, and future roles of Brachiaria grasses in tropical pastures. *Tropical Grasslands-Forrajes Tropicales, 3*(1), 1-21.
Nyambati, E. M., Muasya, R. M., Nyangito, M. M., & Oyier, M. O. (2016). Evaluating the potential of napier grass (Pennisetum purpureum) in restoring degraded lands: A case study of Gachoka Division, Kenya. *Journal of Environmental Science and Technology, 9*(4), 307-315.
Peters, M., Hempel, C., Miettinen, A., & Lehmann, J. (2012). A conceptual framework for root research in ecosystems. *Ecology, 93*(1), 166-176.
Rao, I. M., Miles, J. W., & Beebe, S. E. (2011). Forage in crop-livestock systems in the tropics. *Tropical Grasslands-Forrajes Tropicales, 3*(1), 59-82.
Rao, M. R., Sajjala, S., Kadiyala, M. D. M., & Reddy, B. S. (2011). Agro-ecological regions and their delineation in Andhra Pradesh. *Indian Journal of Agricultural Economics, 66*(1), 124-135.
Rossi, F., Bonanomi, G., Giannino, F., Mingo, A., & Rutigliano, F. A. (2012). Changes in humic substances along a gradient of soil degradation. *Soil Biology and Biochemistry, 51*, 85-93.
Sarkar, D., Meitei, C. B., Das, A., Ghosh, P. K., & Mandal, B. (2018). Changes in soil organic carbon pools in a long-term trial with perennial fodder crops in acid soils of north-east India. *Grass and Forage Science, 73*(2), 473-481.
Sarkar, B., Mandal, B., Kundu, M. C., & Sarkar, S. K. (2018). Soil organic carbon pools and productivity under different land uses in the humid tropics of northeast India. *Agroforestry Systems, 92*(6), 1523-1535.
Six, J., Bossuyt, H., Degryze, S., & Denef, K. (2020). A history of research on the link between (micro)aggregates, soil biota, and soil organic matter dynamics. *Soil and Tillage Research, 202*, 104669.
Sommer, R., Bossio, D., Desta, L. T., & De Deyn, G. B. (2018). Soil carbon sequestration and agricultural resilience. In S. S. Verma, D. L. Sparks, & B. R. Singh (Eds.), *Soil health and climate change* (pp. 213-243). Academic Press.
Wang, Y., Lu, W., Li, Y., Wu, J., & Wu, Z. (2021). Spatial variation of soil organic carbon and its influencing factors in agro ecosystems: A case study in eastern China. *Catena, 196*, 104887.
Yadav, G. S., Lal, R., Meena, R. S., Babu, S., Das, A., Bhowmik, S. N., Datta, M., Layak, J., & Saha, P. (2017). Conservation tillage and nutrient management effects on productivity and soil carbon sequestration under

Map 1 is available in the Supplementary Files section.

No competing interests reported.

Map.png
Map 1: Meru County Source: Kenya National Bureau of Statistics

Assessing potential of Perennial Forages on Soil Carbon Sequestration Across Agroecological Zones with Varying Management Practices in Meru County

Status:

Version 1

Abstract

Figures

Introduction

Materials and methods

Study area

Map 1: Meru County Source: Kenya National Bureau of Statistics

Paired plots sites selection

Research design and Soil sampling

Bulk Density determination

Soil reaction (pH) determination

Soil organic carbon stock calculations

Mineral-associated organic carbon (MAOC) and particulate organic carbon (POC) determination

Statistical analysis

Results and discussion

Interactive effects of zone and forages on soil BD, pH and soil micronutrients

Effects of zone on Particulate organic carbon (POC) and Mineral Associated Organic Carbon (MAOC) content

Soil Organic Carbon stocks, Soil Organic Nitrogen stocks CN ratio under different forages

Regression analysis

Regression analysis of MAOC with SOC, SON, POC, zones, forage, and depth

Discussion

Effects of zone, Forages/forages and depth on Soil Organic Carbon and Soil Organic Nitrogen concentrations

Regression analysis of MAOC with SOC, SON, POC, zones, forage, and depth

Conclusion

Declarations

References

Map 1

Additional Declarations

Supplementary Files

Status:

Version 1