Influence Of Soil Amendments On Forage Yieldand Greenhouse Gasemissions In Agropastoral Systems Of Makueni County, Kenya

Rangelands forms the largest land cover globally, covering more than one-quarter of the world’s land mass and storing about one-third of the world’s terrestrial C in soils and vegetation (White et al.2000, Asner et al. 2004). The primary economic activity of rangelands is livestock production, supplying meat, dairy products, leather, and wool (Herrero et al. 2009).

The productivity and profitability of rangelands is entirely a function of forage quality and quantity (Briskeet al. 2011). On the other hand, these ecosystems have, to varying extent, experienced degradation of vegetation and soils because of overgrazing, plant invasions, and climate change(Asner et al.

2004, Schipper et al. 2007, Bai et al. 2008).Thus, soil amendments practices aimed at promoting plant production may have considerable potential to restore or increase grassland C storage and feedback on the global C cycle (Schimel et al. 1990, Conant et al. 2001 Follett 2001, Schuman et al. 2002, Derner and Schuman2007).Amendment practices can affect grassland C storage or loss by altering soil chemical or physical characteristics (Cambardella and Elliott 1992, Paustian et al.

1997, Janzen et al. 1998), plant morphology or growth, soil moisture, or rates of microbial activity (Strombergand Griffin 1996, Steenwerth et al. 2002, Jones and Donnelly 2004).

Amending soils with organic and inorganic material normally increases nutrient availability, and thus is common practice used in cropping systems to enhance pasture productivity (Classman et al. 2002, Blair et al. 2006) and in some land reclamation sites to facilitate soil amelioration and plant establishment (Larne and Angers 2012). Animal manure, organic and inorganic fertilizers, crop residues and composted waste are common forms soil amendment.

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The application of organic matter to rangelands has been proposed as an approach for increasing plant productivity, as a waste management strategy, and for climate change mitigation (Hall and Sullivan 2001, Cabrera et al. 2009). Organic and inorganic matter additions to rangeland soils increase soil C and N pools directly and have the potential to indirectly increase ecosystem C storage by stimulating plant growth. Organic matter additions to rangelands can also provide a pathway to divert organic waste from landfills or for manure management from nearby dairies, thereby reducing greenhouse gas emissions from traditional waste management. Carbon benefits of enhanced pasture yields due to soil amendments may be offset from a global warming perspective by the stimulation of soil greenhouse gas emissions.

Organic and inorganic matter amendments increase soil C and nitrogen (N) pools and may alter soil environmental conditions (e.g., moisture, temperature, and pH), thereby increasing the potential for carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) emissions (Gregorich et al. 2005). The extent of management influence on soil greenhouse gas emissions is a large source of uncertainty in grasslands (Sousana et al. 2004). Manure amendment can increaseCO2 and N2O fluxes (Chadwick et al. 2000, Dalai et al.2003, Mosier et al. 2004, Davidson 2009); compostedanimalwaste and plant matter tends to result in lowergreenhouse gas emissions relative to green manures or synthetic fertilizers (Vallejo et al. 2006, Alluvione et al.2010). However, the effects of soil amendments on greenhouse gas dynamics in rangelands are largely unstudied (Lynch et al. 2005, Cabrera et al. 2009).

The purpose of this study is to examine the immediate and residual effects of soil amendments by use of organic and inorganic materials on forage production and greenhouse gas emissions in production of Brachiara xaraes,chloris gayana and Pennisetum purpureum. It is hypothesized that the application of composted organic and inorganic matter to rangeland soils would increase the above- and belowground biomass for at least one year, and that these increases in ecosystem C inputs would be partially or wholly offset by elevated rates of soil greenhouse gas emissions (CO2, N2O, and CH4).

Greenhouse gas fluxes in Africa play a vital role in the global GHG budget (Thompson et al., 2014; Hickman et al., 2014; Valentini et al., 2014; Ciais et al., 2011; Bombelli et al., 2009). Nitrous oxide emissions in sub-Saharan Africa account between 6 and 19 % of the global total, and changes in soil N2O fluxes in sub-Saharan Africa drive large inter annual variations in a tropical and subtropical N2O sources (Thompson et al., 2014; Hickman et al., 2011). Use of synthetic fertilizers such as urea has increased in the last four decades, as has the number of livestock (and their manure and urine products) in Africa (Bouwman et al., 2009, 2013). The increasing trend in N application rates is expected to cause a 2-fold increase in agricultural N2O emissions in the continent by 2050 (from 2000; Hickman et al., 2011).

Data on GHG stocks in pastoral ecosystems is important for assessing their contribution for offsetting emissions. Real and accurate greenhouse gases data is scarce. Limited understanding about the amount of greenhouse gases emissions in pastoral ecosystems thus results from a failure to consider spatial and temporal environmental dynamics. This poses challenges for policy development to promote, manage or protect pastoralism to safeguard the atmospheric environment from GHG emissions, in addition to providing local pastoralists with a reasonable livelihood. Consequently, there has been a general development of replacing pastoralism with other land uses without looking at associated environmental implications (Behnke and Karen 2013).

The understanding soil amendments effects on GHG emissions, carbon stocks and Nitrogen cycling are important to provide effective management options in the rangelands. This may contribute to improving productivity as well as managing the impacts of climate change. There is need to identify the appropriate soil amendments practices that will increase rangeland productivity while offsetting greenhouse gas emissions. The present study findings will contribute towards guiding policy formulations for sustainable rangeland management at both county and national levels of governance.

To contribute to sustainable rangeland management through assessment of soil amendment practices on pasture yields, organic carbon stocks, Nitrogen cycling and GHG emissions in different agro pastoral systems for climate change mitigation.

1. To evaluate the influence of soil amendment practices on pasture yields

2. To determine the influence of soil amendment practices on Methane, Nitrous oxide and Carbon dioxide emissions

3. To determine the influence of soil amendment practices on soil organic carbon stocks

4. To determine the influence of soil amendment practices on Nitrogen cycling

Q1: Which organic or mineral fertilizer and soil amendment produces the highest pasture yields?

Q2: How do different fertilizers affect soil emissions of CO2, CH4 and N2O intensities?

Q3: How do different organic and mineral fertilizers influence soil C concentrations and Nitrogen cycling?

Q4: How do different organic and mineral fertilizers influence Nitrogen cycling?

H1: Organic amendments (FYM, FYM-BC and BSL) contain N but also other nutrients that are relevant for plant growth, especially phosphorus (P) which is often lacking in highly-weathered acidic tropical soils. Therefore, they will produce higher yields than controls or Lab Lab intercropping.

H2: Soil emissions of CO2 and CH4 will be higher in plots fertilized with FYM, FYM-BC and BSL because of additional C input. All fertilizer treatments will increase soil N2O emissions compared to control, but bio char will reduce N2O emissions from plots fertilized with FYM.

H3: In the long term (>1 year), organic fertilizers (FYM, FYM-BC, BSL, LAB LAB) will increase soil organic C (SOC) compared to controls and NPK because of additional C input directly during application of the amendment (FYM, FYM-BC, BSL) or due to additional root growth (LAB).

H4: Concentrations of mineral N (i.e. NH4+ and NO3-) will fluctuate over time depending on plant growth and N uptake as well as decomposition of organic fertilizers

Study site

The study will be conducted at KALRO- Kiboko in Makueni County located in the southern parts of Kenya, which is classified as ASAL. Makueni County lies between Latitude 1º 35´ and 30º 00’South and Longitude 37º 10’and 38º 30’east occupying an area of 7965.8km2. Makueni is predominantly agro-pastoral. The area experience bimodal rainfall patterns with long rains occurring between March and May, while short rains are experienced from October to December. It receives annual rainfall ranging from 300mm to 1250mm per year (Moss, 2001; Makueni CIDP, 2013). The temperatures in ranges between 12 °C and 35 °C, depending on the season and topography of a location (Berger, 1993; Makueni CIDP, 2013). The vegetation in this County generally exhibits semi-arid characteristics with some diversities arising from heterogeneity of soil types and rainfall patterns and amounts (Kidake et al., 2016) People of this area are small-holder subsistence farmers and/or livestock keepers who depend on rainfall for their livelihood (Amwata et al., 2015). Makueni County had a human population of 884,527 in 2009 with an annual growth rate of 2.8% (CBS, 2009). The County has potential in horticulture and dairy farming especially the hilly parts. The lowlands are used for livestock keeping, cotton and fruit production, and the main fruits grown include mangoes, pawpaw and oranges. The main food crops produced in the County are; Maize, Green grams, pigeon peas and sorghum.

The concentration of CO2, N2O and CH4 will be measured using the static greenhouse gaschamber approach (Pelster et al., 2015). In each plot, one sampling point will be randomly selected and a chamber will be installed for gas sampling. The, chambers consists of a collar (0.27m×0.372m×0.1m) and a lid(27×37.2×12.5cm) made of plastic. The collars will be inserted up to 10cm into the ground. The lids will be equipped with 50cm long (2.5cm diameter) vent tubes, thermometers to measure internal temperature, fan and a gas sampling ports. During measurements, the lid will be placed on the collar and both increments will be tied with clamps with a gasket between the lid and the collar for airtight seal. Chamber bases will be inserted at least one week prior to the first greenhouse gas concentration measurements and will remain in place throughout the sampling period. During each sampling event, chambers will be closed for 30 min and thereafter, four samples taken at 10 min intervals (0,10, 20, and 30 min) from each individual chamber. A gas pooling technique will be employedwhere 30 ml of gas will be sampled in each of the four chambers within a sampling point. This will be done using a 60ml propylene syringe with Luerlocks and immediately transferred into 30ml glass vials fitted with crimp seals (Butterbach-Bahl et al., 2016). Samples will be analyzed within36 hours after every sampling period.

Forage yields

Forages will be harvested at the end of each growing season and subsequently weighed, dried in the laboratory for each forage species.

Soil sampling

Soil will be sampled at intervals of 0–10, 10-20, 20-30, 30-60, 60-90 and 90-120 cm depth using a soil auger. Soils will have sampled at intervals within the plots: before planting, at germination time, at maturity and harvesting time. Within each sampling point, two soil samples will be mixed to form a composite soil sample per respective depths. The composited samples will be packed in a well labeled polythene bags for transportation to ILRI Mazingira Centre for soil organic carbon analysis. In addition, undisturbed soil samples for each depth will be collected using core rings with a defined volume (100 cm3) from each sampling plot for bulk density determination.

Determination of available mineral N

Harvesting of soil cores (0-10 cm) will be done following seeding/transplanting and/or fertilizer addition, and then after every 15 days.

[bookmark: _Toc533844313]Data analysis

Flux analysis

Concentrations of CO2, N2O, and CH4 will be analyzed using a gas chromatograph (model 8610C; SRI) equipped with two detectors; a flame ionization detector (FI) comprising of a Platinum catalyzed methanizer for catalytic conversion of CO2 to CH4 and for subsequent detection of CH4 and CO2 and an electron capture detector (ECD) to detect N2O. A mixture of CO2 and N2 pre-mixed in the ratio of 5:95 will be used as the ECD Make-up gas to improve on the detector sensitivity.

The analytes will be separated on (3m, 1/8″) chromatographic columns packed with Hayesep D stationary phase at an isocratic oven temperature program of 70°C. ECD and FID detectors temperatures will be set at 350°C. 99.999%. White spot Nitrogen will be used as carrier gas at flow rates of 25ml min-1 on both FID and ECD lines. Gas concentrations of samples will be calculated based on the peak areas measured by the gas chromatograph relative to the peak areas measured from calibration gases run at two calibration levels. This will be done four times each day. Calibration gases ranges from (4.28-8.3097 ppm) for CH4, (400-810.5 ppm) for CO2 and (0.36 0.7606 ppp) for N2O. Concentrations will then be converted to mass per volume using the Ideal Gas Law (pV = nRT) and measured chamber volume, internal chamber air temperature, and atmospheric pressure determined during sampling. GHG fluxes will be calculated using linear regression of gas concentrations versus chamber closure time.

Gas flux data will be subjected to analysis of variance (ANOVA) using GenStat Discovery 15thedition statistical software.

Soil analysis

The soil samples will be air-dried and passed through a 2 mm sieve. In order to determine soil total C and N content, 20 g of sieved soils will be dried at 40°C for 48hrs and thereafter ground with a hammer mill (RetschMM400Mixer Mill, Retsch GmbH, Germany). A 20g subsample will then be analysed for C content using a high-temperature oxidative combustion system (Elementar Vario Max Cube). The bulk density for each depth was estimated by core ring method (Blake, 1965). Soil carbon stocks will be calculated using the following equation 1:

SOC Stock=c × BD × D

Where SOC is the soil organic carbon stock (Mg C ha-1) (Were, 2015). c represents the carbon concentration (%), BD bulk density (gcm-3) and D the respective soil depth (m).

Mineral N analysis

Subsequent extraction of the sampled soil with 2 M KCl and colorimetric determination of mineral nitrogen (NH4+ and NO3 will be conducted.

Forage quantity and quality

Forages will be harvested at the end of each growing season and subsequently weighed, dried and analysed in the laboratory for crude protein content, ADF, NDF, fibre content and gross energy.

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Influence Of Soil Amendments On Forage Yieldand Greenhouse Gasemissions In Agropastoral Systems Of Makueni County, Kenya. (2022, Jul 14). Retrieved from

Influence Of Soil Amendments On Forage Yieldand Greenhouse Gasemissions In Agropastoral Systems Of Makueni County, Kenya
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