Targeted management of organic resources for sustainably increasing soil organic carbon: Observations and perspectives for resource use and climate adaptations in northern Ghana

ABSTRACT

Since soil organic matter (SOM) buffers against impacts of climatic variability, the objective of this study was to assess on-farm distribution of SOM and propose realistic options for increasing SOM and thus the adaptation of smallholder farmers to climate change and variability in the interior northern savannah of Ghana. Data and information on spatial distribution of soil organic carbon (SOC), current practices that could enhance climate adaptation including management of organic resources were collected through biophysical assessments and snap community surveys. Even though homestead fields were more frequently cultivated, higher amounts of SOC (15 ± 2 g kg⁻¹) were observed in homesteads when compared to the periphery cropped sections in bushes (SOC = 9 ± 1 g kg⁻¹). Possibly, a combination of household wastes, droppings of domestic animals that are mostly reared in a free-range system, manures applied to crops and cultural norms of chieftaincy, which cause short-term fallowing of homestead fields could account for the differences in SOC. Use of organic resources for soil amendment among farmers was low (31% of interviewed farmers) due largely to ignorance of fertilizer values of manures and residues, traditions for bush-burning and competing use of organic resources for fuels. Our findings suggest a need for effective management practices, training and awareness aimed at improving management of organic resources and, consequently, increasing SOC and resilience to climate-change-induced risks.

KEYWORDS:

• Climate adaptation
• climate variability
• soil management
• organic resources
• resilience
• spatial targeting

Introduction

Climatic variability remains a major challenge for farmers in the tropics (Rowhani et al. 2011; Mubaya et al. 2012; Nutsukpo et al. 2012). In the interior northern savannah of Ghana, low and erratic rainfall patterns negatively impact on the timing of farming activities and consequently limit crop productivity. Also, soils in northern Ghana are generally low in nutrients and have limited nutrient-holding capacity to support crop production (Ziblim et al. 2012). Increasing soil organic carbon (SOC) in these tropical soils will enhance water and nutrient retention as well as their availability, and consequently improve the productivity of these soils (Batjes 2001; Moebius-Clune et al. 2011). In addition, fields with higher SOC are potentially more resilient to climate-change-induced risks (Adiku et al. 2009; Pan et al. 2009; Kong et al. 2012), and offer other multiple benefits within a climate policy context (Kahiluoto et al. 2014).

Climatic conditions in the northern savannah of Ghana are characterized by high temperatures and low rainfall during most of the year. These climatic conditions limit crop productivity, biomass accumulation and consequently lead to low soil cover and increased frequency of soil exposure to wind, runoff and erosion, which, in turn, reduce topsoil depth. This combination of factors expose the low carbon and low nutrient subsoil for cultivation, thus further constraining crop productivity. To simultaneously reduce soil erosion and increase crop productivity, there is a need to increase soil organic matter (SOM) and maintain soil cover (Ontl & Schulte 2012).

Presently, farmers in the northern savannah of Ghana pursue few options to improve SOC content in their fields. Instead, these farmers largely rely on mineral fertilizers to sustain crop nutrient supply. Continued use of mineral fertilizers without liming has led to topsoil acidification with negative impacts on crop productivity (Fageria & Baligar 2008). Moreover, injudicious use of mineral fertilizers may result in priming of SOM decomposition leading to further reduction in SOC stocks (Kuzyakov et al. 2000). On the other hand, low nitrogen and phosphorus levels may also limit biomass accumulation and subsequently constrain SOC build-up from crop residues (Kirkby et al. 2013). Under such conditions, improving soil fertility through balanced fertilization and organic matter addition will be necessary to increase crop productivity and enhance resilience to harsh climatic conditions and climate change (Zingore et al. 2007).

To improve targeting of management practices for effective utilization of already limited and/or temporarily available organic resources, information regarding spatial distribution of SOC and other soil properties within farms is crucial because different practices across fields influence soil fertility and SOM contents. Moreover, this information will enhance the effectiveness of management practices in improving soil fertility, climate adaptation and crop yield. On the other hand, to better target interventions aimed at increasing soil C, there is a need to understand farmer traditions and cultural norms and practices and how they influence C accumulation. Therefore, the objectives of this study were to investigate the spatial distribution of SOC, identify potential organic matter management and cultural constraints and review options for improving organic matter management within farms in the interior northern savannah of Ghana.

Materials and methods

Description of the study area

The study was conducted in farming villages located in two districts, Tolon/Kumbungu and Savelugu/Nanton in the Northern Region of Ghana: details are presented in Figures 1 and 2. Weather data (1980–2012) obtained from Ghana Meteorological Department showed that annual rainfall ranges from 800 to 1100 mm (Figure 3) and its pattern is unimodal with a peak in August–September (Figure 4). The mean daily temperature (ca. 28°C) shows only a small annual variation with the highest temperatures observed during the long dry period from February to March. The lowest temperatures (26.8–27.5°C) were observed during the short rainy period from July to September.

Figure 1. Locations of the rural communities and weather stations in the study area of the northern region of Ghana: A  =  Tamale Airport, D = Daboya, N = Nyamkpala, P = Pong Tamale, S = Savelugu, DN = Dimabi-Nayili, DK = Dimabi-Yakura, DY = Dimabi-Yapali, Z = Zoggu, Y = Yong, L = Langa, Ny = Nyeko and Ch = Challam; sister villages: DN-DY.

Figure 2. Structure of a study community formed by a single village (in case 1) or by sister villages having different names (in case 2). Contiguous cropped areas surround houses and scattered cropped areas in the periphery of homestead. Domestic animals (fowls, goats, sheep and few cattle (2–5 heads)) are kept within homesteads.

Figure 3. Boxplot of annual rainfall data from 1980 to 2012 for each of the five weather stations in the region of northern Ghana.

Figure 4. Mean monthly rainfall and mean temperature as average of weather data (from 1980 to 2012) obtained daily at five stations in northern Ghana.

Soils in the study areas have high haematite and illite contents with high internal drainage (Nartey et al. 1997b), which together with high temperatures increase organic matter decomposition rates and nutrient leaching leading to low SOM contents (Abubakari et al. 2012). The soils are porous, gravelly and concretionary (Dedzoe et al. 2001) and have low available P (MacCarthy et al. 2009; Obiri-Nyarko 2012) due to the extremely low content of P-bearing parent materials (Nartey et al. 1997a) and high fixation of available P (Owusu-Bennoah & Acquaye 1989; Abekoe & Tiessen 1998).

The natural vegetation, in the study region, is mainly characterized by short grasses (i.e. Heteropogon spp., Panicum spp., Paspalum spp., Digitaria horizontalis (Willd.), and Pennisetum spp.) and trees such as shea butter trees (Vitellaria paradoxa L.) and Acasia spp. The principal land use is small-scale rain-fed crop production. The study area falls in the northern Guinea savannah of Ghana, between latitudes 8°N and 10°N, where yields of rain-fed crops such as maize (Zea mays L.), the most commonly produced crop in all the four agro-ecological zones of Ghana, is ca. 30% lower compared with the national average yield (Quiñones & Diao 2011; SRID 2007, 2013).

Cropping is more concentrated within fields around houses (Figure 2). The common crops grown in homesteads are cereals (typically maize, sorghum (Sorghum bicolor L., Moench)) and millet (Pennisetum glaucum L.), grain legumes (mainly groundnut (Arachis hygogaea L.) and soybean (Glycine max L., Merr.)), yam (Discorea spp.) and high-value vegetable crops (okra (Abelmoschus esculentus L., Moench)) and pepper (Capsicum spp.). Farmers more often grow high-value crops with manure application in homesteads, whereas periphery areas are more extensively cultivated (CSIR-SARI, personal communication). However, traditional leadership in northern Ghana has a strong influence on cropping within homesteads. In communities, homestead fields are fallowed according to the widespread traditional beliefs and taboos of newly inskinned chiefs. Inskinment means the installation of traditional leaders or chiefs in northern sector of Ghana because they sit on hides or skins of wild animals signifying their royal power (Dr L. Alhassan of SARI-CSIR, personal communication).

Description of cropped fields (farms) where soil samples were collected

Figure 2 presents the structure of a study community formed by a single village (in case 1) or by two sister villages having different names (in case 2), also with details in Figure 1. Cropped areas (farms) belonging to individual farmers in homesteads were contiguous from the reference O (closest point to residential area or houses) but cropped sections in bushes in the outskirt of homesteads were sparsely scattered. We refer to the cropped areas around houses as homestead fields (MacCarthy et al. 2009) and the cropped areas in the outskirt of homestead fields as periphery fields. In each community, soil samples were taken from the homestead and the periphery fields as described below. Samples taken from sister villages forming a community were not separated but analysed in the same way as samples taken from a community formed by a single village.

Soil sampling in the homestead fields

Soil sampling (0–20 cm depth) was done at sampling points along the direction O to A, but varied to the east, west, south and north among the study communities (Figure 2), and the distances between O and sampling points were assigned PD₀. Soil samples were then taken at points PD₀= 0, 50, 100, 150 and 200 m. Three sub-samples were taken to constitute a composite sample at each sampling point, PD₀.

Soil sampling in periphery fields

Periphery cropped areas in the bushes were randomly selected in each community by picking ballots in such a way that at least a cropped piece of farmland was chosen in the east, west, south and north of each community and five different soil samples were randomly taken, at depth 0–20 cm, at different points (spots) in each periphery cropped section (Figure 2). All soil samples from the periphery fields in bushes were assigned distances to be at PD₀ > 300 m because we observed that the contiguous cropped fields around houses (i.e. homestead fields) ended at distances between 200 and 300 m, with reference from O, and varied among the communities.

Survey and collection of information

The number of times pieces of farmland had been cultivated in the last five years (reference year = 2013) was assessed along the direction O to B, which varied to the east, west, south and north among the communities (Figure 2), by interviewing the farmland holders. Based on these interviews, the frequency of cultivation of pieces of land or plots was recorded for the intervals (or distances), PD₀ = 0–100, 100–200, 300–400, 400–500, 500–600, 600–700, 700–800, 800–900 and 900–1000 m.

Also, 160 farmers were randomly selected and interviewed in the villages to obtain detailed information regarding farming traditions and extension services. Specifically, this included information on farming systems, major crops cultivated, mineral fertilizers largely used over the last 15 years prior to 2013, farmer training programmes conducted in the study areas, farmland holdings, planting periods as an adaptation to the erratic rainfall pattern and management of organic resources for low-input crop production. Additional information was obtained from the District Agricultural Officers and CSIR-SARI (Savannah Agricultural Research Institute, Tamale, Ghana).

Soil analysis

The Bouyoucos hydrometer method modified by Day (1965) was used for particle size analysis. Soil pH was determined in distilled water in the ratio 1:1 of soil to water, as used by Miller and Kissel (2009). SOC was determined by the Walkley and Black (1934) method based on the reduction of K₂Cr₂O₇ by organic carbon (OC) and the unreduced K₂Cr₂O₇ measured by titration with ammonium ferrous sulphate. Soil total nitrogen (N) was determined by the modified Kjeldahl method (Bremmer 1960; Pocknee & Sumner 1997) based on digestion of total N by concentrated H₂SO₄ in the presence of a digestion accelerator mixture (10 g of K₂SO₄ + 1 g of CuSO₄ + 0.1 g of Se). The extractable K was determined by the ammonium acetate method reported by Lakanen and Ervio (1971). The Bray 1 method of Bray and Kurtz (1945) was used to determine the available P because of the low pH value of the soil samples. Mineral N ( and ) was analysed by the methods of Harper (1924a, 1924b), which involved samples with 50 ml of 2 M KCl and 0.2 g of MgO in the Kjeldahl distillation method of Bremmer (1960), and back titrations were performed against 0.01 M HCl to purplish end-points of methyl red–methylene blue indicator mixture after adding 1 ml of H₂SO₄ and 0.2 g of Devarda's alloy.

Data analysis

The IBM SPSS version 22.0 was used to analyse the data. Least significance difference (LSD) and the p-values according to the Duncan-test were tested at p < .05 to compare means of the observed variables. Pearson correlation coefficients were used to determine the relationships among the soil properties. Variables obtained through survey were tested against assumed (expected) proportions using the χ² tests (Yate's correction factors for degree of freedom (df) ≤ 5).

Results

Spatial distribution of soil properties within cultivated fields

Our results showed that SOC, pH, available P, K and total N in the cropped fields within homesteads were significantly higher (p < .05) compared to periphery fields (Tables 1 and 2). Mineral N and particle size distribution (sand, silt and clay) were the same in both homestead and periphery fields. However, the periphery fields in the study rural communities of Savelugu/Nanton District had more clay and SOC contents compared with those in the Tolon/Kumbungu District (Table 2).

Table 1. Selected properties of soils from fields located in homestead and in the periphery.

Properties	Location of fields	Sample size (n)	Mean ± SE	Minimum	Maximum
pH (H2O)1:1^#	Homestead	75	6.0 ± 0.2 a	4.9	8.4
	Periphery	125	5.4 ± 0.1 b	4.4	6.6
SOC^γ (g kg^−1)	Homestead	75	15 ± 2 a	5	40
	Periphery	125	9 ± 1 b	4	25
Total N (g kg^−1)	Homestead	75	1.37 ± 0.71 a	0.7	4.0
	Periphery	125	0.91 ± 0.23 b	0.5	1.5
Available P (mg kg^−1)	Homestead	75	16.1 ± 3.8 a	3.0	74.9
	Periphery	125	5.8 ± 1.0 b	2.2	25.3
Mineral N^λ (mg kg^−1)	Homestead	75	227 ± 31 a	70	592
	Periphery	125	185 ± 25 a	67	560
Extractable K (mg kg^−1)	Homestead	75	293 ± 66 a	70.2	1532.7
	Periphery	125	126 ± 18 b	27.3	378.3
Sand (%)	Homestead	75	66.4 ± 2.1 a	32.0	76.5
	Periphery	125	71.0 ± 1.7 a	55.5	82.7
Silt (%)	Homestead	75	16.0 ± 1.3 a	6.6	27.7
	Periphery	125	15.0 ± 1.2 a	4.9	27.0
Clay (%)	Homestead	75	17.7 ± 1.4 a	10.0	42.5
	Periphery	125	14.0 ± 1.0 a	5.0	22.5

Notes: γ: SOC; ; SE: standard error. Different letters against values are significantly different according to Duncan-test at p < .05.

^#Soil pH in a ratio 1:1 of soil and water.

Table 2. Selected soil properties in fields located in homesteads and in the peripheries of communities for the two study districts.

Soil property	Savelugu/Nanton District		Tolon/Kumbungu District		LSD(p  < .05)
	Periphery (mean ± SE)	Homestead (mean ± SE)	Periphery (mean ± SE)	Homestead (mean ± SE)
	n = 75	n = 45	n = 50	n = 30
pH (H2O)1:1^#	5.4 ± 0.1	6.1 ± 0.4	5.4 ± 0.2	6.0 ± 0.2	0.23
Total N (g kg^−1)	0.93 ± 0.1	1.94 ± 0.3	0.89 ± 0.1	1.41 ± 0.1	0.2
SOC^γ (g kg^−1)	10 ± 1	15 ± 4	7 ± 1	15 ± 2	2.3
Mineral N^λ (mg kg^−1)	195 ± 33	203 ± 52	171 ± 41	244 ± 38	40
Available P (mg kg^−1)	6.5 ± 1.7	12.2 ± 4.2	4.8 ± 0.8	18.9 ± 5.7	4.1
Extractable K (mg kg^−1)	145.9 ± 34.2	232.4 ± 74.7	112.3 ± 20.9	335.4 ± 99.8	70.4
Sand (%)	69.8 ± 2.6	63.6 ± 2.7	72.8 ± 1.4	68.3 ± 3.0	2.7
Silt (%)	15.0 ± 1.8	18.2 ± 2.2	15.0 ± 1.3	14.4 ± 1.4	1.7
Clay (%)	15.2 ± 1.5	18.3 ± 1.6	12.3 ± 1.3	17.3 ± 2.1	1.8

γ: SOC; λ: also, ; SE: standard error; LSD_{(p  < .05)}: least significance difference at p < .05; n = sample size.

^#Soil pH in a ratio 1:1 of soil and water.

SOC, pH, K, available N and available P tended to decrease with increasing distance (PD₀) of sampling points further away from the homestead (reference O) (Figure 5). The SOC contents, pH, available K and available P were the highest in samples taken at sampling point O (PD₀ = 0). Mineral N remained high over distances until PD₀ = 50 m beyond which it decreased. SOC contents at sampling points (PD₀ = 50, 100, 150, 200 and >300 m) were significantly lower than SOC contents of soil samples taken at point O (results of statistical analysis not shown). The lowest SOC content was observed at PD₀ > 300 m. Similarly, available K decreased with increasing distances (or sampling points further away) when compared with amounts of available K at reference O. Observed values of both pH and available P at distances PD₀ > 100 m were lower than those obtained from samples taken at PD₀ = 100 m or at PD₀ = 0. The distance of sampling points (PD₀) was negatively correlated with soil pH (p < .001), total N (p < .05), SOC (p < .05), available P (p < .05) and K (p < .05). Soil pH was positively correlated with SOC (p < .001), total N (p < .01), available P (p < .01) and K (p < .001). Available P was positively correlated with K (p < .001), which also was positively correlated with total N (p < .05) and available N (p < .01).

Figure 5. Variation in OC, pH_1:1, mineral N, available P and K with distance (PD₀) from reference O within homestead described in Figure 2.

Adaptations to soil infertility and climatic conditions in smallholder systems

In the study areas, fields under cereal cultivation were up to 3 ha per farmer followed by legumes (up to 1 ha per farmer) (Table 3); these crops are grown as staple crops to sustain local food supply. As supplemental crops, yam and vegetable field sizes per farmer were ≤0.1 and ≤0.5 ha, respectively. Crops were grown as rain fed, usually from May to October each year. The majority of farmers (83–93%) indicated that they plant crops in May, a period which coincides with the onset of the rainy season (Table 3 and Figure 4). Late planting is possible in June with higher risk of insufficient rainfall in the latter part of the crop-growing period.

Table 3. Some major practices of farmers interviewed (sample size, n = 160) in the study rural communities.

Details	Area, months and rates	Crops
		Cereals^a	Legumes	Vegetables	Yam
Pieces of farmland holdings under cultivation
Cultivated field size per farmer^b	Hectare (ha)	≤3	≤1	≤0.5	≤0.13
Climate adaptation practices
Planting time^c	April	17%	5%	–	71%
	May	83%	89%	93%	29%
	June	–	3%	7%	–
	July	–	3%	–	–
Application of mineral fertilizers
AS	125 kg ha^−1^d	96%	–	7%	–
	250 kg ha^−1	4%	–	–	–
	>250 kg ha^−1	–	–	–	–
NPK^e mineral fertilizers	125 kg ha^−1^d	39%	–	4%	–
	250 kg ha^−1	60%	–	–	–
	>250 kg ha^−1	1%	–	–	–

^aMaize, millet and sorghum.

^bThese are ranges of cultivated field sizes obtained through interviewing farmers.

^cRainfall pattern determines and limits crop planting period (mid-May–early June) for most crops.

^dFarmers’ own application rate in the last 15 years prior to 2013 (i.e. 50 kg per acre = 125 kg ha⁻¹).

^eThe various kinds of NPK mineral fertilizers available and receive the same application rates were 15–15–15, 23–10–5, 20–10–5, 23–10–10, 21–10–10, etc.

Farmers apply mineral fertilizers to crops, especially cereals (maize, millet and sorghum), which are the major staple food crops, in all fields regardless of whether they are located in homestead or periphery. The most commonly used mineral fertilizers in the study communities were ammonium sulphate (AS), which was applied at a rate of 125 kg ha⁻¹ (indicated by 96% of farmers) and NPK (15–15–15, 20–10–10, 21–10–10, 23–10–5, etc.), which was applied at a rate of either 125 kg ha⁻¹ (indicated by 39% of farmers) or 250 kg ha⁻¹ (indicated by 60% of interviewed farmers) (Table 3). AS was applied for “top-dressing”, whereas NPKs were applied as basal fertilizers, but the application rates for the different NPKs were independent of the different formulations available. By this normal practice, the annual supply of nutrients from these mineral fertilizers to cultivated fields, irrespective of farm location, was estimated to be 50–89 N kg ha⁻¹, 5–16 P kg ha⁻¹ and 5–21 K kg ha⁻¹. However, it was difficult to determine whether these nutrient application rates were sufficient for short season rain-fed cropping or for having impact on SOC contents.

The cropping frequency of farmland was higher in homesteads than in periphery fields (Figure 6). Farmland use for various crops, over the last five years (i.e. reference year = 2013), decreased with increasing distance from the homestead reference point (PD₀) along the direction O to B (Figure 2). Pieces of farmland (i.e. homestead fields) up to PD₀ = 400 m from reference O seemed to be more cultivated yearly than pieces of land further away. However, pieces of farmland within the locations (positions) 0 ≤ PD₀ < 500 m in the Zoggu community had been fallowed over the three years prior to 2013.

Figure 6. The relationship between the frequency of field cultivation over the last five years (reference period = 2008–2013) and the distance of fields from homesteads.

Organic matter management in smallholder system and extension services

During field preparation, all farmers incorporate remaining residues (or organic matter) into the soil. However, in this study, only 31% of interviewed farmers indicated that they apply organic manure from refuse dumps, compost, crop residues and animal droppings in cultivated fields (both homestead and periphery) (Table 4). Fifty-seven percent out of the 31% of farmers apply and incorporate animal droppings and left-over plant residues in fields, whereas 36% (of 31% farmers) apply naturally composted organic resources from refuse dumps. Making composted organic manures for use is rare (i.e. only 7% of 31% farmers, when compared to assumed proportion). Similarly, observed proportions of farmers that use manures from both refuse dumps and gathering animal manure and left overs are significantly lower than assumed proportion of farmers (75%), suggesting that organic resources are under-utilized in the study areas.

Table 4. Responses of interviewed farmers (sample size, n = 160) to questions on management practices.

Practices and observations of farmers	Frequency		χ^2-value^a
	Assumed	Observed
Farming system
Following crop rotation plans correctly	75%	34%	32.26**
Organic matter management
Managing OM in fields	75%	31%	37.11**
^bSources of OM applied
Collecting and applying residues and animal droppings	75%	57%	6.44*
Obtaining decaying OM from refuse dumps	75%	36%	29.23**
Preparing own composts	75%	7%	92.79****
^bBenefits of OM management realized
Less mineral fertilizers applied	0%	86%	147.39****
Normal crop growth	0%	90%	160.02****
Problems associated with OM for soil amendment
Bushfire burning residues in long dry seasons	0%	83%	138.48****
Problems of transporting OM to fields	5%	10%	1.15^NS
FBO members not sharing ideas	0%	46%	57.17***
Lack of awareness and confidence in OM value	0%	90%	160.02****

Notes: OM: organic matter; FBO: farmer-based organizations. NS denotes that the difference between observed and assumed frequencies is not significant at p < .05.

^aYate's correction factor for degrees of freedom (df) equal to one.

^bProportions of the small proportion, 31% of farmers, who applied organic resources.

*Difference between assumed (expected) and observed frequencies is significant at p < .05.

**Difference between assumed (expected) and observed frequencies is significant at p < .01.

***Difference between assumed (expected) and observed frequencies is significant at p < .001.

****Difference between assumed (expected) and observed frequencies is significant at p < .0001.

The Ministry of Food and Agriculture (MoFA in Ghana) contributes to develop capacity of the largest proportion of farmers in interior northern savannah (Table 5). Observed proportions of farmers trained by MoFA, Non-Governmental Organizations (NGOs) and Research Institutes (RIs), when compared to our assumed (expected) proportions, have shown that almost all farmers were trained in good agricultural practices. However, some specific expectations of larger proportions of farmers (70% compared with assumed 80%) towards receiving trainings in use of organic resources have shown that it is likely that previous trainings might not have covered the fertilizer value of manures and residues. Also, it seems that timing of previous trainings conflicted with rain-fed farming season, as indicated by recommendations of 67% of farmers (compared with expected 75%).

Table 5. Responses of interviewed farmers (sample size, n = 160) to questions related to farmer trainings.

Practices and observations of farmers	Frequency		χ^2-value^a
	Assumed	Observed
Farmers being trained annually by
MoFA-Ghana	60%	50%	1.64^NS
NGOs	10%	7%	0.38^NS
RIs	15%	9%	1.18^NS
MoFA-Ghana with NGOs or RIs for joint trainings	30%	21%	1.68^NS
None^b	5%	13%	2.99^NS
Social impact of trainings
FBO membership	80%	75%	0.46^NS
Expectations of farmers seeking specific trainings
Organic matter management	80%	70%	2.16^NS
High-yielding and drought-tolerant crops	80%	82%	0.03^NS
Soil water conservation and fertility management	80%	31%	46.64***
Crop protection	80%	3%	118.96****
Rearing farm animals	80%	3%	118.96****
Preferred timing of trainings
Before the onset of rainfall	75%	67%	1.19^NS
Throughout a rainy season	75%	21%	56.27***
Throughout a year	75%	12%	78.2***

Note: NS denotes that the difference between observed and assumed frequencies is not significant at p < .05.

^aYate's correction factor for degrees of freedom (df) ≤ 5.

^bInterviewed farmers who had never participated in training programmes; FBO: farmer-based organizations.

***Difference between assumed (expected) and observed frequencies is significant at p < .001.

****Difference between assumed (expected) and observed frequencies is significant at p < .0001.

Discussion

SOC within cultivated fields

In all the communities, similar patterns of farmland management for crop production were observed. Specifically, farming in homesteads was observed to be more intensive than that in the periphery fields, a common practice among farmers in the northern Ghana (SARI-CSIR, personal communication), also evidenced by the fact that the chosen study's rural communities in the two districts are far apart (Figure 1) but showed similar patterns of less intensive farming in the periphery fields (Figure 6). However, SOC contents differed considerably with more SOC in homestead fields, as it was also observed by Zingore et al. (2007). As distances, further away, from the homesteads increased, SOC content tended to decrease. In contrast, Masvaya et al. (2010) reported that in extensive cultivation systems under semi-arid conditions, fields closest to homesteads were less fertile than fields further away and this was attributed to the more recent cultivation of new fields located far away from homesteads. In the current study, the difference between SOC in homestead fields and those of periphery may be due to disproportionate organic matter inputs from several factors known to increase SOC (Moebius-Clune et al. 2011; Olson et al. 2013).

High SOC within homesteads was surprising because farmers often use residues for domestic fuels (MacCarthy et al. 2009; Aniah et al. 2013). Nonetheless, high SOC contents have also been reported within house rings of farming villages in savannah areas of Senegal and Burkina-Faso (Prudencio 1993; Manlay et al. 2002b, 2004b) bearing similar cropping system and climatic conditions observed in northern Ghana. The high SOC observed in fields contiguous to the village was attributed to soil C input from crop residues, manures and household wastes spread in the house rings. In addition, land fallowing has previously been observed in improving SOC, available nutrients and active biological activities (Manlay et al. 2002a, 2002c). We also observed that though very few farmers applied organic matter in their fields, household wastes and droppings of domestic animals, largely fowls, sheep and goats kept in the free-range system (Adzitey 2013) with few housed cattle (2–5 heads) close to houses, could increase SOC. Droppings of fowls, sheep and goats are usually spread within homesteads and cannot easily be collected for application in farms. According to traditional norms of the chiefs (Nyantakyi-Frimpong 2013), owners temporarily keep their animals in cages or tether them to trees near grasses or in small fences, where they are provided feeds (or residues) to avoid damage to crops during cropping season (Agricultural Extension Agents of MoFA, personal communication). Use of plant residues as livestock feed causes loss of organic resources (Manlay et al. 2004b). However, this effect is expected mostly in peripheries of communities because homesteads are traditionally more protected than periphery fields, where large-scale rearing of cattle in the nomadic system is common.

Short-term fallowing of house (homestead) fields, whenever a new chief is inskinned (Savannah Agricultural Research Institute, personal communication), was also considered a major factor contributing to the high SOC similar to the effects of fallowing reported by Manlay et al. (2002a). By traditional beliefs, new chiefs temporarily prohibit cultivation of farmland around houses for recovery of natural vegetation and to conserve resources (National Commission on Culture 2013). The Zoggu community in Savelugu/Nanton District had a new chief in 2010, and thus crop fields around the houses were fallowed prior to this study in 2013 (Figure 5).

Causes of low organic inputs

In Ghana, the largest population of livestock (goats, sheep and cattle) is produced in the northern savannah of Ghana. Annually, estimated 2 million metric tonnes of manure are produced in north Ghana (Issaka et al. 2012) and the OC contents of these manures range from 27% to 32% (Boakye-Danquah et al. 2014). Taking the recommended application rates of manure as 4–5 tonnes per hectare (Boateng et al. 2006; Fening et al. 2011), farmers would be able to supply 1.0–1.5 tonnes of OC per hectare to crop fields. Hence, the quantity of manures produced in the northern savannah of Ghana will likely be adequate to cover 500 million hectares of crop fields in farming season. However, these manures may not be easily assessed because of nomadic behaviour of most herdsmen and the free-range system adopted by farmers rearing livestock and fowls in greater parts of the year. Transporting manures to fields create no significant challenges to farmers (Table 4) but the use of manures (mainly cow dung) and plant residues by farmers for fuels (MacCarthy et al. 2009; Aniah et al. 2013) and widespread bush burning during long dry season in the whole of northern savannah of Ghana cause temporal availability of organic resources and/or compete with SOM use for crop production.

The proportion of farmers that apply organic matter in the study communities was low (Table 4), even though these farmers indicated that applying organic matter to fields reduced the need for mineral fertilizers and supported normal crop growth. One of the main barriers to application of manure appears to be the fact that the majority of farmers (90%; Table 4) were not aware and confident of the fertilizer value of organic resources produced in their communities. This seems to be a major cause of low adoption of manure and residue application in the study areas, confirming the low use of manures for crop production in northern Ghana reported by Bellwood-Howard (2013).

A large proportion of interviewed farmers (75%) belong to different farmer-based organizations (FBOs). But many of these farmers (46% in Table 4) do not share innovative ideas among themselves. Capacity development programmes will need to target and relate salient social aspects, within farmer-based groups, to SOC improvement for sustainability of any improved farming systems against existing harsh climatic risks. The current (lack of) knowledge among farmers may be a considerable obstacle, as 70% of the farmers indicated that trainings should focus more on organic matter management. Also, it seems that timing for training programmes negatively affect farmers, as the majority of farmers suggested that training programmes should be done before the onset of rainfall because the annual weather cycle (Figure 4) constrains farmers to do their yearly crop planting in mid-May to early June (Table 3). Participation of farmers in important capacity development programmes organized during the limited rainfall season (May–September) can be low. Farmers who will attend training programmes during active cropping period may generally not share experiences with others in the communities and the effect is likely a low adoption of new farming technologies and techniques (Akudugu et al. 2012).

Future directions for sustainable SOM management

Previous studies have demonstrated that soil organic resources generally improve soil water availability and nutrient supply leading to an increase in crop productivity and buffering against dry weather conditions (Bot & Benites 2005; Adiku et al. 2009; Tittonell et al. 2010). In this study, we observed that in fields where SOC was high, other soil properties such as P, K, total N and pH were also high. However, the SOC contents across cultivated fields were generally too low (ca. 13 g kg⁻¹) to provide sufficient resilience against adverse climatic conditions and nutrient improvement. This may mainly be due to the fact that the potential of savannah soils to sequester C is generally very low (Manlay et al. 2002c). Additionally, most of the current practices in the study communities do not increase SOC, as competing alternative uses of organic resources result in limited retention of residual biomass (Manlay et al. 2004a). Also, the widespread use of bush burning, during the long dry season, in addition to the use of plant residues and manures for fuel lead to a reduction in the availability of organic resources that could boost SOC content.

Cover cropping with selected legumes increases SOC as well as soil nitrogen and crop yields (Adiku et al. 2009). Farmers practising crop rotation (Table 4) could be encouraged to include leguminous plants in their crop rotation plans to enhance soil productivity. Farmers in the study region will need to keep their domestic animals in confinements for effective collection of droppings. Additionally, gathering of household wastes and plant residues as well as awareness on the effects of bushfire on organic resources for low-input cropping systems will increase the availability of organic resources. The collected organic materials can be composted during the long dry season for application to crops in the rain-fed farming period. However, further research is required to investigate optimum timing for composting organic resources to coincide with rainy season and application rates to field crops.

Alternative renewable energy technologies to the current use of manures and plant residues for fuel in the study communities will have significant impacts on SOC. A biogas system can be developed to digest manures/cow dung and plant residues into composts and gas. In this way, the farmers can then use the biogas for fuel and apply the digestate to the fields to improve and maintain SOC (Thomsen et al. 2013). Such technologies will, however, require investments in both equipment and skills for operation and maintenance. Adoption of such possibilities therefore requires the active participation of government and support from development agencies.

Also, long-term SOM input improvement will be important to replenish depletion of SOM in tropical savannah (Lal 2004). For instance, technologies with multiple benefits such as fallowing and agroforestry practices should be supported in cultivated fields for regrowth of vegetation, improvement of soil cover and enhancement of soil C sequestration (Henry et al. 2009; Kong et al. 2012).

Cultural norms have a strong influence on SOM contents. Integrating cultural beliefs, which have been causing fallowing on wider scale, into participatory farmer training programmes targeted at improving management of organic resources must be a core aspect of planning. Timing for implementation of training programmes should eliminate conflicts between off-season period and rain-fed farming period (Table 5) to ensure full participation of farmers.

Acknowledgements

The views expressed in the document cannot be taken to reflect the official opinions of CGIAR, Future Earth or donors. We would like to thank the technicians of Soil Science Department, University of Ghana for their valuable laboratory work and support. We appreciate the useful technical advice, support and additional information from Dr L. Alhassan of SARI-CSIR in Nyampkala-Tamale, Ghana and the Agricultural Extension Agents of the Ministry of Food and Agriculture (MoFA) in the study communities.

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

This work was undertaken as part of the CGIAR and IEA (Ghana) Research Programs on Climate Change, Agriculture and Food Security (CCAFS), which is a strategic partnership of CGIAR, Future Earth and IEA (Ghana), with support from the European Union (EU) and the International Fund for Agricultural Development (IFAD).

ORCID

Jørgen E. Olesen http://orcid.org/0000-0002-6639-1273