Abstract
Climate change adversely impacts food and feed production, depletes water, and increases the vulnerability of the people living within arid and semi-arid areas. The current study aims to assess crop–livestock water productivity within such drought-recurrent or water-stressed regions. This was done through secondary data collection and interviews from 589 households across the Sudan, Sudan–Sahel, and Sahel climatic zones of Burkina Faso. The findings confirm that the feeding strategies of livestock were based essentially on natural pasture, crop residues, and agricultural by-products. Moreover, crop–livestock total water productivity (TWP) was found generally higher in the Sudan zone (0.29 ± 0.02 $US/m3) characterized by more favorable climatic conditions than the Sudan–Sahel and Sahel regions that experienced a similar TWP (0.21 ± 0.01 $US/m3). The research gives insight into the valuation of virtual water contained in livestock feeds. Improving the accessibility in quantity and quality of such feeds through informed policy actions could enhance returns on transpired water. Additionally, other water harvesting and conservation methods are also essential to sustain more productive crop–livestock systems within water-stressed regions like Burkina Faso.
HIGHLIGHTS
Water productivity in the mixed-crop–livestock system varied with the climatic gradient from the Sudanian zone to the Sahelian zone.
Appropriate use of virtual water contained in crop residues contributes to better-transpired water productivity.
Policy actions must support accessibility in quantity and quality to animal feed to ensure more yields per drop of water.
INTRODUCTION
Water availability in West Africa varies due to factors like climate change, population growth, and infrastructure development, impacting regional development efforts. Agriculture, the region's largest economic sector, heavily depends on rainfall and surface water sources (Rameshwaran et al. 2021). However, rainfall patterns and climate change affects water availability levels during the dry season (Yira et al. 2016). The uneven distribution of water, the impacts of climate change, and the consequences of higher temperatures are limiting factors for water availability for crop production within the study area.
Climate change significantly impacts sustainable development globally, particularly affecting agriculture (Heubes et al. 2013; Nelson et al. 2018; Sanou et al. 2023), water accessibility, and livelihoods (Jones & Thornton 2009) in West Africa, including Burkina Faso. These changes could lead to agricultural yield losses (El Bilali 2021) and alter rainfall patterns, posing challenges to water availability, and threatening regional food security.
West Africa's economic value stems from its abundant natural resources, strategic geographical location, and vibrant demographic. The region is rich in resources (oil, gold, diamonds, cocoa, and coffee) which drive its economy. Its proximity to the Atlantic Ocean enables access to global markets, fostering growth in industries. With a large and youthful population, West Africa benefits from a significant labor force that propels its economic expansion. This population confronts challenges stemming from political instability, insecurity, and displacement. Simultaneously, they also reap the benefits of a rich cultural heritage, economic opportunities, and efforts toward regional cooperation. Thus, the socio-economic landscape of the region presents both challenges and opportunities, shaping the overall well-being and progression of its population.
Agriculture in the Sahelian region remains highly vulnerable to climate change and variability that adversely reduces the availability of suitable land for food production or grazing, depletes water, and increases the vulnerability of the people living in the region (Amole et al. 2021). Most climatic impacts are expected to result from changes in the water cycle. Therefore, rainfall variability and the subsequent increase in the frequency of extreme weather events, combined with an accelerated water cycle through high evapotranspiration (ET), will affect the following element in agricultural ecosystems: crops, livestock, trees, fish, rural communities, and physical infrastructure (Palombi & Sessa 2013). For this reason, climate change adaptation strategies for agriculture will need to be viewed through a ‘water lens’ (Palombi & Sessa 2013).
Despite its importance, water resource has been exposed to an unprecedented depletion and degradation worldwide. This is due to the highly diversified (Molden et al. 2007) and increased amount of water use (Descheemaeker et al. 2010). Indeed, water is the object of high competition between agricultural, industrial, household, and environmental uses. The demand for water is increasing with abstraction exceeding the natural recharge over extensive areas; and over a long period of time, groundwater is being depleted (Wada et al. 2010) and other water bodies are affected by pollution from agriculture, cities, and industries, thus reducing the amount of water available for use (Mekuria et al. 2021).
The increasing demands for food of a growing population lead to more stress on natural resources including stress on water resources (Wright 2013) to provide necessary goods and services to meet human needs, in an already water-stressed environment (Amole et al. 2021). These pressures are likely to be exacerbated in the context of climate change leading to more harsh environmental conditions in the tropics. This has to do with drier conditions for the production of rain-fed agriculture and grazing lands. In such conditions, there is an urgent necessity worldwide to better manage water resources (Gebreselassie et al. 2009) and improve water productivity in a sustainable manner (Delgado et al. 2001), especially in the agriculture sector. Water productivity is a concept developed since the mid-1990s around the slogan of ‘crop per drop’ (Zoebl 2006) and still remains at the centre of research interest worldwide, due to the key role played by water in the production systems, especially within Sahelian ecosystems. Water productivity is the amount of beneficial output per unit of water depleted expressed as a ratio of livestock products and services (meat, milk, traction, hides, manure) to the amount of water depleted in producing them (Amede et al. 2009). In its broadest sense, it reflects the objectives of producing more food, and the associated income, livelihood, and ecological benefits, at a lower social and environmental cost per unit of water used (Molden et al. 2007). Improving water productivity means producing more per drop of water and this is of great interest for areas with recurrent drought like most of the Sub-Saharan African (SSA) countries characterized by arid and semi-arid areas, where climate change is adding more burden on already stressed water resources (Nkiaka et al. 2021). In a perspective of coping with and minimizing the impact of water scarcity, adequate actions are necessary from both farmers and policymakers. For FAO (2012) 1, options to cope with water scarcity in agriculture can be seen as running a spectrum from the source of water to end users, and beyond, to consumers of agricultural goods. These options, whether technical, managerial, legal, and/or investment must be combined to help farmers to produce more from less water (Palombi & Sessa 2013). Water management must, therefore, be at the heart of climate change adaptation options, particularly in rural areas and in agriculture where the role of water is critical to crop–livestock production.
Such options could consist of a set of agricultural practices aiming at reducing water losses through evaporation; increasing agricultural soil water-holding capacities, maintaining and replenishing soil fertility, and valuation of virtual water contained in crop residues and hay through livestock grazing. All these actions can contribute to the improvement of crop and livestock water productivity (LWP) within drier mixed-farming systems which is of interest to the current research. Water-saving actions within drought-prone regions include the technologies of Zaï; half-moons (demi lunes), assisted natural regeneration, organic fertilization, etc. All these technologies contribute to increasing soil water retention and agricultural land fertility and definitely in improving production and water productivity.
In Burkina Faso, studies have been conducted on water productivity (Bama et al. 2020; Kima et al. 2020; Amole et al. 2021), but few were conducted on water productivity within a mixed-crop–livestock system across the three climatic zones of Burkina Faso (Sudan, Sudan–Sahel, and Sahel). Furthermore, limited information is available on both livestock and crop water productivity (LWP, CWP) within these zones and globally across West Africa. From this perspective, the study aimed to quantify CWP and LWP across the three climatic zones. At first instance, the study gave a brief description of crop–livestock farming households. Secondly, it addressed, the feeding strategies of livestock and crop and livestock outputs from the farming system; and finally, we quantify water depleted in the system, and water productivity of both crop and livestock.
While expecting variability in water productivity in mixed-crop–livestock systems under different climatic conditions, it is also expected that the findings give information on the needed actions to be undertaken in order to enhance the water productivity to the benefit of small farmers within a water-stressed region such as Burkina Faso and SSA in general.
STUDY METHODS
Study area
Data collection
Crop and LWP required major data sets including household land holding, crop type cultivated and land use, livestock feed sources, grazing lands, and other socio-economic information. Data also included: (i) livestock holding and herd composition, (ii) crop yield per crop type, (iii) livestock productions (milk, sales of live animals as flock offtake), and services (transport, draft power, and manure). These data were both collected empirically and through secondary data. Primary data were generated through interviews, field observations, and discussions with key informants. The collected information on crop and livestock production covers a period of 12 months given the inability of farmers to give detailed and reliable information beyond a period of one year.
Sampling method
A sampling of surveyed villages was first done with the assistance of state extension services within each municipality. The villages of each municipality were first classified by order of importance (low, medium, high) of Crop-livestock integration activities in practice in the village. Also, a purposely random sampling was done to select a set of six villages in each municipality where at least 30 individual farmers were interviewed about the crop–livestock farming systems. The total population involved in the study was 589 households made up of 195, 203, and 191 households in the Dano, Niou, and Dori municipalities, respectively.
Data analysis
Farming households across climatic zones
Farming households were studied by analyzing their structural and functional characteristics assessed through (i) their size and workforce they possess; (ii) their cultivated areas; (iii) the age of household heads; (iv) their major farming equipment; and (v) their herd ownership.
Crop and LWP
Water productivity is a function of the depleted water (representing the amount of water that is lost through ET) and the beneficial outputs from crops and livestock (Peden et al. 2007). Indeed, CWP consists of a ratio of crop yield (physical productivity) or its financial value (financial productivity) to the amount of water depleted to produce crop grain (Haileslassie et al. 2009a, 2009b). Similarly, LWP is the ratio of net livestock-related benefits, including both products and services, to the water depleted and degraded in producing these products (Gebreselassie et al. 2009; Haileslassie et al. 2009a, 2009b).
Depleted water estimation in mixed-crop–livestock farming
The estimation of the depleted water in crop and livestock production was a function of water lost through ET during production processes. The computation of ET used crop coefficient (Kc) for different stages of development for each crop type using Equation (4) (Amole et al. 2021).
The reference evapotranspiration (ETo) values were computed for each climatic zone using the Penman–Monteith method as a standard method of computation (FAO 1998). The data needed include temperature, relative humidity, wind speed, and solar radiation (Mekonnen et al. 2011).
Assumptions and Secondary Data Sourcing
Following assumptions were made in the water productivity estimation:
(i) The depleted water (ET) for purchased feeds was not considered in the current study, as suggested by Houenou et al. (2012). Indeed, as indicated by Amole et al. (2021), there is not enough credible information on the quantity, type, and frequency of purchase of feeds. (ii) The factor of tropical livestock unit per hectare (TLU/ha) was used to allocate the share of each household's livestock owner from the communal grazing areas (Haileslassie et al. 2009a). This was done assuming equal access to feed available from communal grazing areas per household (Amole et al. 2021). A total livestock density of 0.2TLU/ha was considered to be an average livestock density for Sahel and Sudan–Sahel zones, while 0.4TLU/ha was considered to be an average density for the Sudan zone (Ouédraogo 2011). (iii) Grazing land feed use factor of 45% was assumed as an average of the value of available dry matter (DM) accessible by livestock during the wet and dry seasons for grazing lands in similar agro-ecological conditions (Amole et al. 2021).
Estimation of crops beneficial outputs
Information on 2020/2021 average yields (kg/ha/year) for the major crops cultivated in each studied zone were obtained from the heads of farming household. The crop types were maize, millet, sorghum, groundnut, cowpea, and sesame. The market values of each crop were estimated based on the current local market price of each crop (USD/kg).
Estimation of livestock beneficial outputs and services
Livestock beneficial outputs were products (milk, meat, and manure) and services (traction and transportation). All the estimations of livestock output were done on a yearly basis, especially for the campaign 2020–2021.
The following approach was adopted in the estimation of livestock beneficial outputs:
- (i)
Manure production and its fertilizer values: Livestock holdings were converted to the equivalent Tropical Livestock Unit (TLU) using a conversion factor of 0.70 TLU/head for cattle and donkeys and 0.10 TLU/head for sheep and goats (FAO 2003). Dry weight daily dung production of 1.03, 1.76, and 1.85 kg/d/TLU was used for cattle, sheep, and goats, respectively (Fofana et al. 2011). The total annual dung produced was, therefore, estimated for the different farming systems.
Livestock's dung nutrient contents (N, P, K) were estimated based on the average chemical composition of cattle manure (9.0–20 g N/kg, 4.0–10.0 g P/kg, and 22.0–56.0 g K/kg) (Bidjokazo et al. 2012; Gomgnimbou et al. 2014) and sheep and goat manure (14.0 g N/kg, 4.0 g P/kg, and 54.0 g K/kg) in Burkina Faso (Bidjokazo et al. 2012). To determine these nutrient values, each nutrient (N, P, K) quantity was converted to fertilizer equivalent monetary value using the current local market price of chemical fertilizer (i.e., the price of 50 kg bag of NPK; 50 kg bag of urea, and 50 kg bag of phosphate). The local market prices, including handling and transportation costs of 50 kg/bag of N14P23K14 fertilizers (14% N, 23% P and 14% K) were 32.0 USD, 32.9 USD, and 38.0 USD, in the Sudan–Sahel (Niou), Sudan (Dano), and Sahel (Dori), respectively. The beneficial value of urine was not considered in this research due to the lack of reliable data on the volume of production and nutrient concentration.
- (ii)
Milk production: yearly annual milk production was estimated as a function of the number of lactating cows, lactation period, and daily milk production (l/d/cow) in the study area. The monetary value of the estimated milk quantity was determined based on the current local market price of fresh milk (USD/l) in the study area (Table S1).
- (iii)
Offtake rate and meat value: the estimation was done based on the offtake rate assuming carcass weight of 52% for bovines and 46% for ‘shoats’ (sheep and goats) (FAO 1999) and the age of maturity was taken as five years, 5.5 years, and 1.5 years for cattle, donkey, and goat/sheep, respectively (Houenou et al. 2012). To avoid an overestimation of LWP (given that yearly water depleted to produce feed cannot solely account for the carcass weight) and ensure that productivity computed reflected that of the considered period (2020–2021), the monetary value of the meat produced by each livestock was divided by its maturity age (Houenou et al. 2012). This allowed for estimating the annual meat and other livestock output values in the calculation of LWP as a ratio of yearly output to the yearly water depleted.
In this study, the values of hides and skins were not considered because the assumption made considered only the potential offtake of livestock (no slaughter) from the farmers' households (Amole et al. 2021).
- (iv)
Value of livestock services: within the three study zones, animal draft power constitutes a key beneficial output to farm households. The livestock service also includes the transportation of crop residues from farms to homesteads and organic fertilizers (compost, dung, and household waste) from homesteads to cropped fields. The evaluation of these livestock services was done by multiplying the daily hiring cost (USD/d) of draft animals (oxen and equines) by their respective number of working days per year spent in transportation or cropping (ploughing, weeding) for each household (Otte & Chilonda 2002).
Statistical analysis
Data from the survey and relevant secondary data were organized, summarized, and analyzed using R Software, a language and environment for statistical computing and cited in the manuscript (R Core Team 2022). Data were statistically checked for meeting the assumptions of normality (Shapiro-Wilk test) and variance homogeneity (Levene test). Barplots were built to visualize water productivity across the three climatic zones. To compare the obtained results between the three climatic zones, we performed a one-way analysis of variance (AVOVA). The Tukey's Honest Significant Difference (Tukey HSD) analysis (Tukey 1949) was afterwards performed when significant differences were detected. Alternative non-parametric tests (Kruskal–Wallis and Pairwise Wilcoxon Rank Sum Tests) were carried out when the assumptions of normality and equality of variance of data were not met.
RESULTS AND DISCUSSION
Household characteristics
Sedentary-extensive farmers were interviewed and were characterized based on different factors such as by the age of the household head, the available workforce, the number of members, the residence status, the marital status, the gender, and the ethnic group. Farmers’ age and their workforce did not differ significantly between the Sudan (45 ± 11 years and 6 ± 4 workers) and Sahel (47 ± 13 years and 5 ± 3 workers) zones but they differed significantly from those of the Sudan–Sahel zone that distinguished itself by older farmers (49 ± 11 years) and the available workforce (6 ± 3 workers) (p < 0.05) (Table 1). Household size was significantly different from the Sudan zone (10 ± 6 persons) through the Sudan–Sahel (13 ± 6 persons) to the Sahel zone (11 ± 5 persons). The majority of interviewed households are native to each study site (186, 201, and 191 in Dano, Niou, and Dori, respectively) and the majority are married (193, 198, and 184 in Dano, Niou, and Dori, respectively). Households' heads are male in general and the main ethnic groups are Dagara (190), Mossi (200), and Fulani (191) as we move from Dano to Dori (Table 1).
Integration variables . | Sudan (Dano) . | Sudan–Sahel (Niou) . | Sahel (Dori) . | |
---|---|---|---|---|
Household head age (year) | 45 ± 11a** | 49 ± 11b** | 47 ± 13a** | |
Workforce (worker) | 6 ± 4a* | 6 ± 3b* | 5 ± 3a* | |
Household size (person) | 10 ± 6a** | 13 ± 6b** | 11 ± 5c** | |
Residence status | Native | 186a* | 201b* | 191c* |
Non-native | 9a* | 2b* | 0c* | |
Marital status | Married | 193a* | 198b* | 184c* |
Single/Widow | 2a* | 5b* | 7c* | |
Gender | Male | 194a* | 200b* | 180c* |
Female | 1a* | 3b* | 1a* | |
Ethnic group | Dagara | 190a* | 1b* | 0c* |
Mossi | 2a* | 200b* | 0c* | |
Fulani | 3a* | 2b* | 191c* |
Integration variables . | Sudan (Dano) . | Sudan–Sahel (Niou) . | Sahel (Dori) . | |
---|---|---|---|---|
Household head age (year) | 45 ± 11a** | 49 ± 11b** | 47 ± 13a** | |
Workforce (worker) | 6 ± 4a* | 6 ± 3b* | 5 ± 3a* | |
Household size (person) | 10 ± 6a** | 13 ± 6b** | 11 ± 5c** | |
Residence status | Native | 186a* | 201b* | 191c* |
Non-native | 9a* | 2b* | 0c* | |
Marital status | Married | 193a* | 198b* | 184c* |
Single/Widow | 2a* | 5b* | 7c* | |
Gender | Male | 194a* | 200b* | 180c* |
Female | 1a* | 3b* | 1a* | |
Ethnic group | Dagara | 190a* | 1b* | 0c* |
Mossi | 2a* | 200b* | 0c* | |
Fulani | 3a* | 2b* | 191c* |
Mean ±SD with different superscripts along the lines differ significantly. Significant codes: 0 ‘***’; 0.001 ‘**’; 0.01 ‘*’; 0.05 ‘.’; 0.1 ‘ ’; 1.
Farm size differed significantly between climatic zones and was comparatively bigger (5.7 ± 4.1 ha) in the Sudan zone compared to the Sudan–Sahel (4.2 ± 2.2 ha) and Sahel zone (3.9 ± 2.4 ha) (p < 0.05). Herd size (4.8 ± 4.6 TLU for ruminants, 5.5 ± 4.7 for swine, 2.0 ± 1.0 for donkey) was similarly bigger in the Sudan zone. The Sahel (2.8 ± 2.7 TLU) and Sudan–Sahel (2.4 ± 2.4 TLU) zones had similar ruminant herd sizes that differed significantly from that of the Sudan zone (P < 0.05). Herd size obtained for sedentary-extensive farmers in Niou (Sudan–Sahel) is bigger than that obtained (1.9 TLU) in the same zone (Amole et al. 2021). However, these authors in the Sahel zone found a higher herd size (5.3 TLU) than that of the current study. Overall, farming equipment (cart, plough, hoe, and compost pit) was found significantly different between zones. Sudan and Sudan–Sahel zones seem to have more cropping equipment than the Sahel zone (Table 2). This confirms the nature of cropping-oriented farmers than livestock rearing-oriented farmers in these zones compared to the Sahel zone.
Integration variables . | Sudan (Dano) . | Sudan–Sahel (Niou) . | Sahel (Dori) . |
---|---|---|---|
Farm size (ha) | 5.7 ± 4.1a** | 4.2 ± 2.2b** | 3.9 ± 2.4c** |
Ruminant (TLU) | 4.8 ± 4.6a*** | 2.4 ± 2.4b*** | 2.8 ± 2.7b*** |
Donkey (nb) | 2.0 ± 1.0a* | 2.0 ± 2.0a* | 1.0 ± 0.0b* |
Swine (nb) | 5.5 ± 4.7a** | 4.8 ± 4.1b** | – |
Cart (nb) | < 1a* | < 1b* | < 1c* |
Plough (nb) | 1 ± 1a* | 1 ± 1b* | – |
Hoe (nb) | 9 ± 8a** | 7 ± 3b** | 4 ± 2c** |
Compost pit | < 1a* | < 1a* | – |
Integration variables . | Sudan (Dano) . | Sudan–Sahel (Niou) . | Sahel (Dori) . |
---|---|---|---|
Farm size (ha) | 5.7 ± 4.1a** | 4.2 ± 2.2b** | 3.9 ± 2.4c** |
Ruminant (TLU) | 4.8 ± 4.6a*** | 2.4 ± 2.4b*** | 2.8 ± 2.7b*** |
Donkey (nb) | 2.0 ± 1.0a* | 2.0 ± 2.0a* | 1.0 ± 0.0b* |
Swine (nb) | 5.5 ± 4.7a** | 4.8 ± 4.1b** | – |
Cart (nb) | < 1a* | < 1b* | < 1c* |
Plough (nb) | 1 ± 1a* | 1 ± 1b* | – |
Hoe (nb) | 9 ± 8a** | 7 ± 3b** | 4 ± 2c** |
Compost pit | < 1a* | < 1a* | – |
Mean ±SD with different superscripts along the lines differ significantly. Significant codes: 0 ‘***’; 0.001 ‘**’; 0.01 ‘*’; 0.05 ‘.’; 0.1 ‘ ’; 1.
nb, number; <, less than.
Crop and LWP
Contribution of different feed resources
The highest contribution of crop residues to the feeding strategies in the Sudan zone is because many of these residues are often left in the field after harvest and were freely accessible to mobile herds. The farmers leave about 80% of cereal crop residues on their fields (Andrieu et al. 2015). Inversely, in the Sudan–Sahel zone, the collection and storage of crop residues are done to supplement the natural pasture from grazing lands. The Sahel zone presents the lowest contribution of crop residues in the feeding strategies. This is due to the comparatively lower crop residue biomass produced by farming systems. In such conditions, farmers must rely additionally on agricultural by-products (bran, grain, and cotton seed cake) in their feeding strategies. In all zones, crop residues are of greatest use during the dry season when the available pasture is low in quantity and quality (Amole & Ayantunde 2019). Different feed sources sustain livestock production (meat, milk, and manure) and services, across climatic zones that are facing challenges of suitable herd feeding.
Livestock and crop beneficial outputs
The dominant livestock species in the study zones include cattle (Bos indicus and Bos taurus), sheep (Ovis aries), goats (Capra hircus), and donkey (Equus asinus). They serve multiple purposes such as the source of milk, meat, and draft power. The dominant crop species grown across zones are sorghum (Sorghum bicolor), millet (Panicum sp.), and maize (Zea mays L.) which constitute the main pillars of Burkina Faso's food security across West Africa (Waongo et al. 2015). Besides these cereal crops are groundnut (Arachis hypogaea) and cowpea (Vigna unguiculata) which play a dual role as staple and cash crop for vulnerable small-scale farmers in the zones.
Livestock beneficial output (US$/household.year−1) included livestock offtake, livestock services (traction), milk, and manure produced, while crop beneficial outputs consisted grain yield.
Both physical and financial crop outputs per household per annum were higher (2,723.3 ± 158.5 kg/household/year and 1,140.5 ± 1,056.8US$/household/year) in the Sudan zone (P < 0.05) (Table 3). Livestock financial outputs were in the range of 710.2 ± 42.8–1,228.2 ± 83.7 US$/household/year. This compared well with 679.88 ± 756–1,436.1 ± 63.7 US$/household/year reported for mixed-crop–livestock farming in Ethiopia (Abebe 2012).
Zones . | Crop output (kg/household /year) . | Crop output (US$/household /year) . | Livestock output (US$/household/year) . | Total output (US$/household/year) . |
---|---|---|---|---|
Sudan (Dano) | 2,723.3 ±158.5a*** | 1,031.3 ±71.5a*** | 1,228.2 ±83.7a*** | 2,152.3±116.5a*** |
Sudan–Sahel (Niou) | 1,406.0 ±59.5b*** | 606.7 ±27.1b*** | 820.5 ±39.8b*** | 1,429.8±56.4b*** |
Sahel (Dori) | 1,779.4 ±80.7c*** | 825.8 ±37.1c*** | 710.2 ±42.8c*** | 1,532.9±68.2c*** |
Zones . | Crop output (kg/household /year) . | Crop output (US$/household /year) . | Livestock output (US$/household/year) . | Total output (US$/household/year) . |
---|---|---|---|---|
Sudan (Dano) | 2,723.3 ±158.5a*** | 1,031.3 ±71.5a*** | 1,228.2 ±83.7a*** | 2,152.3±116.5a*** |
Sudan–Sahel (Niou) | 1,406.0 ±59.5b*** | 606.7 ±27.1b*** | 820.5 ±39.8b*** | 1,429.8±56.4b*** |
Sahel (Dori) | 1,779.4 ±80.7c*** | 825.8 ±37.1c*** | 710.2 ±42.8c*** | 1,532.9±68.2c*** |
Mean ±SD error with different superscripts along the column differ significantly. Significant codes: 0 ‘***’; 0.001 ‘**’; 0.01 ‘*’; 0.05 ‘.’; 0.1 ‘ ’; 1.
The quantity and value of milk produced (160.3 ± 13.5 l/TLU/year and 136.8 ± 122.8 US$/household/year) in the Sahel zone were the highest (P < 0.05) (Table 4). Values for manure (187.21 ± 172.06 US$/household/year), livestock services (285.2 ± 220.5 US$/household/year), and quantity and value of meat (333.1 ± 213.3 kg/household/year and 752.8 ± 672.9 US$/household/year) from the Sudan zone were higher (P < 0.05) than those from Sudan–Sahel and Sahel zones (Table 4). The values obtained in the Sahel zone for the same type of farmers (sedentary-extensive), were all comparatively higher than those indicated by Amole et al. (2021) in the same zone for milk (2.18 US$/household/year), livestock offtake (136.2 US$/household/year), manure (1.8 US$/household/year), and services (1.2 US$/household/year). Similarly, for the Sudan–Sahel zone, Amole et al. (2021) reported lower values for livestock offtake (98.2 US$/household/year), manure (2.1 US$/household/year), services (25.6 US$/household/year).
Zones . | Services (US$/household/year) . | Manure (US$/household/year) . | Milk (l/TLU/year) . | Milk (US$/household/year) . | Meat (kg/household/year) . | Meat (US$/household/year) . |
---|---|---|---|---|---|---|
Sudan (Dano) | 285.2 ±220.5a*** | 187.2±172.1 a*** | 7.2 ±3.1a*** | 12.7 ±1.8a*** | 333.1 ±213.3a*** | 752.8 ±672.9a*** |
Sudan–Sahel (Niou) | 198.4 ±133.8b*** | 111.6±98.0b*** | – | – | 206.8±126.3b*** | 498.3 ±399.9b*** |
Sahel (Dori) | 82.7 ±82.0c*** | 111.7±93.1b*** | 160.3 ±13.5b*** | 136.8 ±122.8b*** | 146.2±94.3c*** | 431.3 ±371.2c*** |
Zones . | Services (US$/household/year) . | Manure (US$/household/year) . | Milk (l/TLU/year) . | Milk (US$/household/year) . | Meat (kg/household/year) . | Meat (US$/household/year) . |
---|---|---|---|---|---|---|
Sudan (Dano) | 285.2 ±220.5a*** | 187.2±172.1 a*** | 7.2 ±3.1a*** | 12.7 ±1.8a*** | 333.1 ±213.3a*** | 752.8 ±672.9a*** |
Sudan–Sahel (Niou) | 198.4 ±133.8b*** | 111.6±98.0b*** | – | – | 206.8±126.3b*** | 498.3 ±399.9b*** |
Sahel (Dori) | 82.7 ±82.0c*** | 111.7±93.1b*** | 160.3 ±13.5b*** | 136.8 ±122.8b*** | 146.2±94.3c*** | 431.3 ±371.2c*** |
Mean ±SD error with different superscripts along the column differ significantly. Significant codes: 0 ‘***’; 0.001 ‘**’; 0.01 ‘*’; 0.05 ‘.’; 0.1 ‘ ’; 1. For manure, fertilizer values of N, P, and K are considered.
From livestock manure production, the results showed a significant difference (P < 0.05) in the amount of nitrogen (Ndung) and potassium (Kdung) made available through livestock dropping across zones. For the phosphorus (Pdung), a significant difference was found only between Sudan and the two other zones (Sudan–Sahel and Sahel) (Table 5).
Zones . | Ndung . | Pdung . | Kdung . |
---|---|---|---|
Sudan (Dano) | 6.3 ±0.1a*** | 2.5±0.0a*** | 20.0 ±0.4a*** |
Sudan–Sahel (Niou) | 7.0±0.1b*** | 2.6 ±0.0b*** | 22.5 ±0.7b*** |
Sahel (Dori) | 5.8±0.1c*** | 2.5±0.0b*** | 17.9 ±0.3c*** |
Zones . | Ndung . | Pdung . | Kdung . |
---|---|---|---|
Sudan (Dano) | 6.3 ±0.1a*** | 2.5±0.0a*** | 20.0 ±0.4a*** |
Sudan–Sahel (Niou) | 7.0±0.1b*** | 2.6 ±0.0b*** | 22.5 ±0.7b*** |
Sahel (Dori) | 5.8±0.1c*** | 2.5±0.0b*** | 17.9 ±0.3c*** |
Mean ±SD error with different superscripts along the column differ significantly. Significant codes: 0 ‘***’; 0.001 ‘**’; 0.01 ‘*’; 0.05 ‘.’; 0.1 ‘ ’; 1.
Water depleted in the mixed-crop–livestock system
The amount of water depleted for both crop and feed production is so important that its valuation can suitably be done through crop residue use in the mixed-crop–livestock farming system.
The quantification and valuation of crop and livestock beneficial outputs and their corresponding depleted water enabled the computation of crop and LWP in the following section.
Crop–LWP
The findings on crop–LWP compared well with those of previous literature. Indeed, LWP experienced across climatic zones revealed an increasing trend (0.06 ±0.01 US$/m3 to 0.17±0.01 US$/m3) from the Sahel to the Sudan zone. These values in the Sudan–Sahel and Sahel zones were similar to those of 0.06–0.08 US$/m3 reported by Mekonnen et al. (2011) in Ethiopia and 0.01–0.11 US$/m3 reported by Amole et al. (2021) across the same zones of Burkina Faso. Also, the LWP obtained in the Sudan zone (0.17±0.01US$/m3) was quite similar to the average value (0.16 ±0.01 US$/m3) indicated by Abebe (2012) and within the range (0.1 and 0.6 US$/m3) indicated by Haileslassie et al. (2009a) and Haileslassie et al. (2009b) in Ethiopia.
Financial CWP (0.13 ±0.01 to 0.16±0.01US$/m3) was found to be lower than those reported in Ethiopia by Haileslassie et al. (2009b) (0.24–0.38 US$/m3) and Haileslassie et al. (2009a) (0.2–0.5 US$/m3). Likewise, the physical CWP (0.29 ±0.01 to 0.40±0.02 kg/m3) across climatic zones was quite similar to the findings 0.24–0.38 kg/m3 by Haileslassie et al. (2009b) and 0.3–0.5 kg/m3 by Haileslassie et al. (2009a). Kima et al. (2020) and Bama et al. (2020), respectively, reported higher CWP values of 0.41 and 0.85 kg/m3 within rice-based systems in Burkina Faso. There are possibilities to improve CWP across the three climatic zones of Burkina Faso. Increasing CWP means improving the LWP of the mixed-crop–livestock farming systems across zones through increased availability of crop-feeds (straw and by-products) for livestock use. Well-fed livestock will have higher output (milk and meat, manure, traction) through higher use efficiency of transpired water.
Milk water productivity varied from 0.004 ±0.004 to 0.02±0.01 L/m3 within the Sudan and Sahel zones, respectively. Meat water productivity amounted to 0.04±0.03 kg/m3 in the Sudan zone, 0.02±0.01 kg/m3 in the Sudan–Sahel zone, and 0.01±0.01 kg/m3 in the Sahel zone (Figure 4). Milk and meat water productivity across climatic zones were all lower than those (1.0 L/m3, 0.09 kg/m3) reported by Gebreselassie et al. (2009) in Ethiopia.
CONCLUSION
Feeding strategies of livestock within the Sudan zone differed globally from those of Sudan–Sahel and Sahel zones. Crop residues are generally available to livestock throughout the year in the Sudan zone, unlike the two other zones. However, crop residues occupied a more central role in feeding strategies of livestock in Sudan–Sahel especially during the hot and dry season. The feeding strategies of the Sahel zone relied mainly both on crop residues and agricultural by-products. Across all the zones, livestock feeding relied mainly on natural pasture during the rainy season and this was more pronounced in the Sudan–Sahel zone. Cropping and livestock feeding implies depleting water to produce meat, milk, cereals, and other crop products within all the zones. Crop and livestock production and the amount of water depleted to sustain such productions within each climatic zone differed significantly across climatic zones. Generally, the highest crop and LWP was experienced by farmers in the Sudan zone compared with the Sudan–Sahel and Sahel zones which are characterized by a harsher environment with comparatively less rain and higher temperature and ET.
The current level of crop and LWP can be improved through adequate actions aiming to enhance both livestock and crop beneficial outputs across the climatic zones of Burkina Faso. The improvement could also be done through increased livestock feeding of high-quality crop residues collected and stored in good conditions that prevent the deterioration of their nutritional quality. Additionally, in-situ field water harvesting techniques such as demi lunes (half-moons) and Zaï can improve the quantity and quality of crop residues.
ACKNOWLEDGEMENTS
We are grateful to the German Federal Ministry of Education and Research (BMBF), which funded this work through the West Africa Science Centre of Climate Change and Adapted Land Use (WASCAL). We also appreciate the Meteorological Agency and the Ministry of Agriculture of Burkina Faso for providing the data.
FAO: Food and Agriculture Organization.
DATA AVAILABILITY STATEMENT
Data cannot be made publicly available; readers should contact the corresponding author for details.
CONFLICT OF INTEREST
The authors declare there is no conflict.