Despite the various knowledge gaps about the specific biophysical processes that transport nutrients from land to streams in small upland catchments in Ghana, the logical sequence of events using the DPCER framework illustrates the significant variations that occur as land-use activities intensify. The catchments were categorized by the VINVAL project based on the percentage of natural to agricultural lands. The results showed that increasing fertilizer use with agricultural intensification, the basis for higher levels of in-stream nutrients in this study, was influenced mainly by access to credit and institutional facilities that provide support to farmers. Fertilizer use, generally, was minimal but there were significant differences in various socio-economic factors (e.g., age, education, external income, pesticide use, livestock ownership, proximity to markets, access to facilities, migration, etc.) between catchments that could influence a farmer’s incentive to increase agricultural output. Total nutrient loads/yields varied between catchments and were determined mainly by stream discharge volumes, or water yield. Although the hydrographs showed different patterns of flow, the percentage runoff from total precipitation was similar between catchments., and comparable to the estimated 5% runoff observed within the Volta basin.
Nutrient ion concentrations co-related with land-use intensity (i.e., increasing concentration with increasing intensity) and showed significant differences between catchments, with the exception of nitrogenous compounds. Water quality evaluation based on the Ghana Target Water Quality Ranges (TWQRs) for domestic use and aquatic ecosystem health requirements showed that nutrient concentrations were mainly within limits. The ecological state, described by macroinvertebrate taxa distribution in response to abiotic parameters, indicates habitats of slight to moderate levels of disturbance; however, further research is needed to develop local taxonomic descriptions to effectively describe stream health. The upland catchments are significantly different from each other, compared to the mid- and downstream sites. The direct causes, sources, and transport rates of nutrients into streams still require further research, but for the purposes of this study, increasing stream nutrient ion concentrations were observed to positively correlate with increasing land-use intensity.
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The aim of the DPCER framework in this study was mainly to establish a basic environmental descriptive cause-effect model, since an understanding of the links between land-use and in-stream nutrient concentration/loads in Ghana is currently limited. The inclusion of a comparative catchment component reduced the influence of natural variability and provided valuable information about how the cause-effect relationship changed with increasing land-use intensity. The measured values for the selected indicators represent a quality or state of each element within the framework. These values were compared to standards available from literature sources and compared across catchments to evaluate each parameter changed with intensification. Assumptions were made that (i) estimated nutrient loads and measured ion concentrations reflected agricultural activities, although there may be other unmeasured or minor inputs from domestic, wild animal or atmospheric sources, for example, and (ii) factors such as soil properties, nutrient transport mechanisms, in-stream nutrient dynamics, etc., are similar, although land-cover differences could influence nutrient ion behavior and transport in various ways. Different models have been suggested that link the flow of information in a balanced way to account for the uncertainties within each element and the interlinkages (Rekolainen et al. 2003). For this study, however, the detailed and extensive datasets required to run models were not available. Simple mathematical tools proved adequate to measure and compare each of the defined DPCER elements. Despite the above assumptions, the performance of indicators clearly illustrates significant differences that generally follow the gradient of land-use intensity. Generalizations and assumptions to explain the complexity of human-environment interactions has been one of the main criticisms of the traditional DPSIR method, on which the DPCER is based. However, the latter’s conceptual structure has still been useful for establishing environmental cause-effect relationships for policy-supporting research, and when needed, as was done for this study, innovations can be included to expand its applicability (e.g., Scheren et al. 2000; Scheren et al. 2004).
In the selection of indicators, the scale of investigation is important for defining the boundary of impacts (e.g., local or national impacts) or the scale of driving forces and responses that can influence a system (e.g., how global agreements impact local markets).
Applications of the traditional DPSIR framework are usually large scale, mainly for
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national or regional water systems that have different dominant types of land-use activities and a variety of impacts (e.g., Borja et al. 2006; Jago-on et al. 2009). For this reason, there have been criticisms that driving forces are usually defined by the prevailing external parameters, whereas socio-economic drivers at the household level that affect its characteristics and choices are rarely assessed, even though these are critical to the decision-making process of land use (Svarstad et al. 2008). The assessment of small upland catchments in this study provided a suitable platform to assess how the cause-effect system operates, with added advantages of evaluating household level parameters and providing more accurate hydrological estimates than would have been obtained for larger systems.
7.1.1 Drivers of land-use intensification
Factors driving a farmer’s decision to manage soil fertility towards increased productivity have been the focus of regional studies (e.g., Barbier 1998; Omamo et al. 2002; Place et al.
2003; Giller et al. 2006). Agricultural intensification in sub-Saharan Africa has been described as either labor-led or capital-led or a combination of both (Aune and Bariono 2008). Labor-led intensification requires more use of labor per unit of land for preparation, weeding, manure application and harvesting, while capital-led intensification implies more use of inputs such as fertilizers, pesticides, and agricultural equipment. In assessing the factors influencing increased production in the southwestern parts of Ghana, Drechsel et al.
(2005) found weak links between agricultural intensification and increased inputs, as farmers were predisposed mostly to low external inputs with minimal investments. In most cases, farmers preferred fallow periods for as long as possible, with slash-and-burn techniques providing the required nutrients. Farmers were more likely to look for land in remote areas (extensification) or invest in off-farm activities (income diversification) where land is scarce, population pressure was increased and fallow periods reduced, than invest into increased productivity per unit area of land. This phenomenon is supported by long-term projections of bioeconomic models that illustrate that intensification per hectare is more expensive for the farmer than the fallow system, due to the poor economic conditions of farmers in sub-Saharan Africa (Barbier 1998). The tendency for increased nutrient input was found only among a few rich rural farmers with high-value crops and urban farmers
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with closer proximity to the city markets, indicating that decisions for investment are largely determined by market access and financial returns (Drechsel and Zimmerman 2005;
Kelly 2006). Studies explaining the adoption of agricultural innovations for hybrid cocoa in Ghana, for example, also show that the support small-scale farmers obtain via their social networks, which provide resources such as cooperative labor and network information, was more relevant than the advantages of the large farm size of large-scale farmers, who benefited more by access to bank loans (Boahene et al. 1999). Contacts with extension officers and the availability of hired labor had positive effects on the adoption of innovations, in addition to the indirect benefits of social status, i.e., farmers with higher social status are more likely to obtain a bank loan.
One assumption for this study is that increased stream nutrient ion concentrations and loads due to increasing land-use intensity are the result of increased fertilizer use.
Estimated rates of fertilizer application in Ghana are low, and are only up by 20% of the farmers in the high intensity land-use catchment. Factors explaining fertilizer use were mainly access to credit, access to agricultural extension services, migration and land ownership (i.e., property rights). In addition, farmers who used pesticides were more likely to apply fertilizers. This corresponds to the above discussions as well as results of other studies (e.g., Erenstein 2006; Kelly 2006; Oduro and Osei-Akoto 2008) that increasing fertilizer use or the adoption of new agricultural techniques are not significantly influenced by access to land, income levels, and education, but rather by factors that influence incentives and associated costs (i.e., profits), such as agricultural extension support services, access to informal or formal credit systems, and proximity to markets.
The suitability of each catchment for agriculture is a significant determinant of the drivers of land-use intensity. Compared to the other catchments, Nyamebekyere for example, has poorer access and less proximity to the markets. It’s location in a national forest reserve restricted farming options and strongly influenced farmers’ choices, with farming mostly for subsistence. The diversity of livelihoods was highest in Nyamebekyere, where there is minimal settler farming, and most of the respondents are long-term residents.
The proximity of Attakrom and Dunyankwanta to markets had a significant impact on the prevailing agricultural practices, and both catchment communities had the same access to
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extension services and bank loans; however, farming in Attakrom was observed to be more orientated towards cash crops. Respondents in Attakrom were characterized by their (i) lack of secondary livelihoods, (ii) low educational standards, (iii) low livestock ownership, and (iv) high percentage of external income compared to the other catchments. The first three characteristics are important factors in occupation and wealth diversification, which are strategic options for reducing risk factors associated with diminishing returns or high costs (Barrett et al. 2001).
Land-use intensity in the study catchments was assessed by comparing the relative proportion of cultivated to natural lands (including fallowed fields) (Meijerink et al.
2003; Verzandvoort et al. 2005). The results show that there is minimal fertilizer application in the catchments and extensification/labor led intensification is still the main strategy for increasing agricultural productivity. With the subsidization of fertilizers, the local conditions that influence a farmers’ decision to invest in fertilizers can, however, eventually change (Lambin and Geist 2001).
7.1.2 Pressure – nutrient loading
Total nutrient yield for the catchments did not follow the trend of land-use, but was in the order Dunyankwanta>Nyamebekyere>Attakrom for all nutrients except sodium, where loads/yields in Attakrom were higher than in Nyamebekyere. The magnitude of nutrient loads/yields correlated with total water yield, as nutrient dynamics are closely linked to the hydrology of a catchment or basin (Lewis Jr. et al. 1999; Poor and McDonnel 2007). Long-term studies required to establish the catchment hydrology as a function of geology, soil, and land-use (Shrestha et al. 2008) were not available for this study. However, the measured annual water yield for each catchment was used to calculate nutrient loads and yields.
Hydrology
The water yield of a stream draining any given catchment is an important determinant of the exported total nutrient loads/yields. In the tropics, evapotranspiration and surface infiltration are the main factors that influence the flow regime (Brown et al. 2005).
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Diminishing tropical forests, as a result of deforestation and conversion to other land-use types affect the catchment water balance (Calder 1998; Bruijnzeel 2004). The detailed data needed to determine evapotranspiration, i.e., weather, crop factors and environmental conditions, were beyond the scope of work of this study based on the specific objectives and research boundaries presented. Potential evapotranspiration (ET0) was estimated by the FAO Penman-Monteith equation and actual evapotranspiration (ETa) by simple calculations of the difference between annual ET0 and stream water yield. The total annual water yield varied between catchments and was highest in Dunyankwanta (79.9 mm yr-1), followed by Nyamebekyere (52.5 mm yr-1) and Attakrom (16.4 mm yr-1). Although there were missing stream-flow data between September and December 2006 for Nyamebekyere, the estimated percentage runoff (2.3%) was similar to that of Attakrom (2.7%), and both were lower than estimated for Dunyankwanta (6.2%). Despite these variations, the fraction of rainfall that becomes stream discharge is comparable to the estimated 4.9-5.0% runoff fraction in studies carried out in the Volta Basin (Andreini et al. 2000; Ajayi 2004).
Field studies involving the use of two catchments with similar characteristics (in terms of slope, aspect, soils, area, climate and vegetation located adjacent to or in close proximity to each other) have been effective at describing the changes in the magnitude of water yield resulting from changes in vegetation (Brown et al. 2005). One catchment usually serves as a control as the other is subjected to various types of ‘treatment’ involving some change in vegetation, e.g., afforestation, re-growth, deforestation, or conversion.
Experimental studies are available that assess how the conversion of forests and natural vegetation to agricultural land impacts water yields in small upland catchments in the region. In Benin, for example, the reduced activity of macrofauna (mainly earthworms) in cultivated soils reduced the soil macroporosity and resulted in lower infiltration capacity and higher surface runoff (Giertz and Diekkrüger 2003; Giertz et al. 2005).
Increasing land-use intensity is generally associated with soils of higher bulk density, lower macroporosity and higher microporosity (Ungaro et al. 2004). Water retention properties are significantly influenced by increasing land-use intensity, as air entry pressures are higher and available water content, i.e., the difference between water content at field capacity (-100 cm) and water content at wilting point (-15000 cm), lower.