AnalysisA curse or a blessing? Population pressure and soil quality in Sub-Saharan Africa: Evidence from rural Uganda
Introduction
Agriculture has long been recognised as the backbone of the economies of many countries of Sub-Saharan African (SSA). It is partly because about two-thirds of the region's population lives in rural areas and greatly rely on land and agriculture for their livelihoods (World Bank, 2016).1 Therefore, boosting the performance of the agricultural sector is indispensable in the war against poverty and hunger. Moreover, agricultural productivity growth plays a vital role in stimulating growth in other economic sectors. That is why scholars have continued to pay close attention to agricultural productivity (Adamopoulos and Restuccia, 2014; Gollin et al., 2014; Van Ittersum et al., 2016). Despite this reality, the performance of the agricultural sector in the region remains the poorest in the world (Binswanger and Townsend, 2000; Sanchez, 2002; Otsuka and Larson, 2016; Senbet and Simbanegavi, 2017).2 Due to the sector's poor performance, it is unsurprising to learn that most SSA countries have remained net food importers (FAO, 2009; Rakotoarisoa et al., 2012; Senbet and Simbanegavi, 2017). Low agricultural productivity affects SSA countries in distinct ways. It exacerbates rural poverty and food insecurity and hunger (Minten and Barrett, 2008; World Bank, 2008; De Janvry, 2010; FAO, 2015a; Otsuka and Place, 2015). Soil degradation is one of the key factors undermining the performance of the agricultural sector in SSA (Drechsel et al., 2001; Sanchez, 2002; Stocking, 2003) and may severely curtail agricultural productivity and push rural households into abject poverty. Studies have suggested that rural population pressure is the core driver of soil degradation in SSA (Mortimore, 1993; Grepperud, 1996; Shiferaw and Holden, 1998; Drechsel et al., 2001; Tully et al., 2015). Indeed, due to high population growth rates, arable land per person has continued to decrease (Jayne et al., 2003, Jayne et al., 2012; Otsuka and Place, 2015), thus increasing scarcity of arable land.
In this paper, we examine the relationship between rural population pressure and soil quality. We also explore the relationship between population pressure and agricultural intensification. Because population pressure is believed to be the core driver of soil depletion, it is important to empirically analyse whether and how it relates to soil quality. It is equally important to empirically examine whether population pressure induces agricultural intensification; if it does, its effect on soil depletion may be neutralised. Both issues have important policy implications. We use unique panel data from Research on Poverty, Environment and Agricultural Technology (RePEAT)—a data set containing six lab-tested soil variables–carbon, nitrogen, phosphorus, potassium, calcium, and soil pH.3 The unique aspect and contribution of this paper is the use of actual panel soil information—with lab-tested soil quality measures—that follow specific sites in a decade. Our paper is closely related to Mugizi and Matsumoto (2020)’s study on Kenya. The unique data we use in this paper provides the most reliable data on changes in soil quality over a decade. Related studies, except for Mugizi and Matsumoto (2020), have either used cross-section data and (or) self-reported measures of soil quality. By using a decade-long panel data, we use a more rigorous estimation methodology−the household fixed effects model controlling for region-specific time effects. The former affords control of unobservable household or parcel specific time-invariant characteristics that could cause bias of parameter estimates; the latter helps to clean our estimates of time trends or regional bias. The estimation strategy gives our findings more of “a causal flavour” than they would otherwise have. In our main results, we find that population density is strongly and negatively correlated with soil quality in rural Uganda. However, we do find no strong evidence concerning whether population pressure induces agricultural intensification. On the whole, the findings indicate that farmers in Uganda have yet to change their farming practices to respond to increasing land scarcity resulting from population growth.
Theoretically, population pressure in farming communities can have two opposing effects on soil quality. It can reduce soil quality due to more frequent and intensive use of farmlands–hereafter population pressure hypothesis; it can also induce the transition of farming methods to more intensive farming in which more fertiliser and other inputs are used to increase the productivity of little available land (Boserup, 1965)—Boserup hypothesis. According to population pressure hypothesis, population pressure on farmland leads to soil degradation (Bilsborrow, 1987, Bilsborrow, 1992; Lele and Stone, 1989; Mortimore, 1993; Grepperud, 1996). When population density is low, households have abundant land to cultivate. At this stage, land-using extensive systems such as slash and burn are practised (Otsuka and Place, 2015). The most common method of regenerating the soil fertility is long-term fallow periods (Ruthenberg, 1971). As population pressure increases and farmlands decrease, uncultivated land is brought into cultivation since unoccupied arable land is still available. However, a further increase in population pressure leaves no idle arable land. A bunch of recent studies in SSA have found that farm sizes per smallholder farmer are declining as a result of subdividing land across generations (Jayne et al., 2003; Headey and Jayne, 2014; Josephson et al., 2014; Muyanga and Jayne, 2014; Ricker-Gilbert et al., 2014). Consequently, fallow periods have been shortened or eliminated (Drechsel et al., 2001; Headey and Jayne, 2014; Otsuka and Place, 2015; Binswanger-Mkhize and Savastano, 2017). Thus, to feed the growing population amidst increasing land scarcity, one of the plausible options available to farmers is to increase the frequency of cultivating the same land. Continuous cropping on land unaccompanied by good farming practices such as the use of supplementary biological and chemical inputs eventually leads to soil fertility loss. The effects are likely to be more harmful in areas where usage of manure and fertiliser is very low such that the nutrients returned to the soil are less than those lost.
Although descriptive studies suggest an inverse relationship between population pressure and soil quality in SSA, far too little attention has been paid to examine this relationship rigorously. Except for a very recent study by Mugizi and Matsumoto (2020) on Kenya, we know of only other few studies such as Grepperud (1996), Shiferaw and Holden (1998), Drechsel et al. (2001), and Pender et al. (2004). Grepperud (1996) found a positive relationship between population density and soil erosion in Ethiopia, while Shiferaw and Holden (1998) found a negative association between land-man ratio and soil erosion in Ethiopia.4 Pender et al. (2004) found a positive correlation between population pressure and soil erosion in the highland zones of Uganda. Similarly, Drechsel et al. (2001)’s study found an inverse relationship between population density and soil nutrient balance in 37 countries. However, their analysis was mainly by scatter plots hence providing only a bivariate relationship.
Contrary to population pressure hypothesis, Boserupian hypothesis predicts that population pressure on natural resources induces technological changes (Boserup, 1965). The main thesis is that as population density increases, agricultural land gets scarcer. Consequently, traditional methods such as fallow that are commonly used to regain soil fertility when land is abundant will no longer be used. In response to land constraint resulting from population growth, farmers gradually change their farming behaviours by switching from extensification (continuous expansion of land in order to increase output) to the intensive farming system in which more inputs such as manure and chemical fertilisers are used to offset declining soil fertility and make the small available farmland more productive.5 Hayami and Ruttan (1985)’s induced innovation theory also postulates that as land becomes scarcer, land-saving technology tends to be more developed to conserve the scarce land. The land scarcity leads to technological change in the form of use of new farm inputs such as inorganic fertilisers that may improve the quality of the land. Recently, a number of studies (see, inter alia, Josephson et al., 2014; Muyanga and Jayne, 2014; Ricker-Gilbert et al., 2014; Mugizi and Matsumoto, 2020) have found a positive relationship between population pressure and agricultural intensification in the form of input use—suggesting that farmers are changing their farming behaviour to cope with declining farm sizes. The documented positive association also suggests that population pressure may not necessarily hurt the soil. It may even improve the soil if farmers respond by using modern farming technologies to make the small available land more productive.
The two perspectives highlighted above suggest that population pressure may have two opposing effects on soil quality. Population pressure may increase cropping intensity and thus soil nutrient mining, but it may also catalyse increased input intensity (i.e., increased use of fertiliser, compost or manure). The net effect on soil nutrient concentration depends on the relative effects of increased soil nutrient mining vs. increased input intensity. In most SSA countries, however, the net effect is likely to be negative due to limited use of fertiliser—both organic and inorganic fertilisers and other modern agricultural inputs (Sommer et al., 2013; FAO, 2015b; Binswanger-Mkhize and Savastano, 2017).67 For example, while fertiliser use intensity in SSA is only 14.9 kg/ha, the world average is 124 kg/ha, and that of East Asia and the Pacific is 322 kg/ha (FAO, 2015b).8 At the same time, although no enough rigorous evidence that does exist for nutrient mining and soil degradation, the few available evidences suggest that the rate at which soil fertility depletion is taking place in the region is high (Smaling et al., 1997; Sanchez, 2002; Henao and Baanante, 2006; Sommer et al., 2013). For example, Sommer et al. (2013) document that the average combined depletion rate of NPK for all SSA is 54 kg/ha per year. Therefore, a study on how population pressure relates to soil quality on the one hand, and how it connects with agricultural intensification, on the other hand, is not only important but also an interesting one.
Uganda provides an ideal case for this study for three reasons. First, it used to be one of the countries with most fertile soils in the tropics (Chenery, 1960), but since the past one decade, it is considered to be one of the countries in Africa with highest soil nutrient depletion (Henao and Baanante, 2006). Yet its current fertiliser use intensity of 1.3 kg/ha is one of the lowest in SSA (FAO, 2015).9 Second, over 80% of its population is employed in agriculture—a land-based sector; soil quality exhaustion is likely to have detrimental effects on the livelihoods of this population. Third, Uganda's population growth rate is among the highest.10 The growth rate is likely to be higher in rural areas, thus leading to more population pressure on farmland. Deducing from the above, we hypothesise that in countries with limited use of fertilisers such as Uganda, population pressure on a farm reduces soil nutrients and soil quality; it also induces agricultural intensification in terms of use of more intensive inputs in responding to soil degradation.
The paper proceeds as follows. Section 2 covers the data. Section 3 lays out the estimation strategy. Section 4 presents and discusses the results. Section 5 concludes and provides policy recommendations.
Section snippets
Data
The main source of data is the Research on Poverty, Environment and Agricultural Technologies (RePEAT) project. The RePEAT surveys were conducted by the National Graduate Institute for Policy Studies (GRIPS) of Japan in collaboration with the Makerere University of Uganda. The questionnaires are detailed with a wide range of information on demographic, farm input use, land ownership and other land issues, and community characteristics, among others. Population density—one of the key variables
Estimation strategies
Examining the drivers of soil quality changes can be empirically challenging because most soil properties are shaped after a long period of time. Therefore measuring changes in soil quality requires a study over a long time horizon (Tully et al., 2015). Fortunately, we have a decade-long panel data. Although one decade may not necessarily be enough, we believe this interval may help to shed light on soil quality dynamics.
Building on soil formation literature, an ideal structural equation to
Empirical results
The estimation results of Eq. (3) are shown in Table 3. We use full soil sample—we include all households with panel soil data. The outcome variables are the seven different measures of soil quality index. In column 1, we use the soil quality index constructed by using all the six soil variables. We find that soil quality is significantly negatively correlated with population density. To check the robustness of the results, in column 2, we use the soil quality index created by using five soil
Conclusion and policy implications
Descriptive studies suggest that population pressure on farmland is the core driver of soil degradation in SSA. However, population pressure may have two opposing effects on soil quality. It can reduce soil quality if it leads to unsustainable agricultural intensification; it can improve the fertility of the soil if the intensification is sustainable. Nonetheless, little attention has been paid to examine how population pressure relates to soil quality, partly because soil quality is shaped
Declaration of competing interest
None.
Acknowledgments
The authors would like to thank for their comments; Prof. Yoko Kijima, Prof. Yamauchi Chikako, Prof. Leah E. M. Bevis, the Journal Editor, and two other anonymous reviewers. We are also thankful to the participants of the GRIPS Policy Analysis workshops, Economic Policy Research Centre workshop (Kampala), as well as the 93rd WEAI (June 2018, British Columbia, Canada) and the 94th WEAI (June 2019, San Francisco, USA) conferences. Finally, we are grateful to the Japan's Ministry of Education,
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