CHAPTER ONE
1.0 INTRODUCTION
The value of a soil has traditionally been measured in terms of its productivity, defined as the capacity of the soil to produce a plant or sequence of plants under a physically defined set of management practices (Soil Survey Staff, 1951). Maintenance of soil productivity depends on management practices as well as on soil and site characteristics, the major ones being soil rooting depth, topsoil thickness, available water capacity, plant nutrient storage, surface runoff, soil tilth, and soil organic matter content (McCormack et al., 1982)
Soil quality has historically been equated with agricultural productivity. Soil quality, of which soil productivity is a vital integral component, is defined by Larson and Pierce (1991) as “the capacity of a soil to function, both within its ecosystem boundaries (such as soil map unit boundaries) and within the environment external to that ecosystem (particularly relative to air and water quality)”. In other words, it is the capacity of a specific kind of soil to function, within natural or managed ecosystem boundaries, to sustain plant and animal productivity, maintain or enhance water and air quality, and support human health and habitation.
Soil productivity includes two aspects: the inherent productivity of soil and its response to management. Crop yield has been considered the best indicator of soil productivity as it integrates the inherent and managed components of soil productivity (Pierce, 1994). This is precisely why land evaluation procedures or indices relate to the potential of land to produce food and fibre, and hence must correlate to crop yield (Pierce, 1994). Crop yields are an expression of historical production, whereas productivity is a measure of potential yield (Tengberg and Stocking, 1997).
The evaluation of soil productivity using crop yields as the only indicator is inadequate and inappropriate because in addition to soil properties, crop yields are influenced by other factors extrinsic to soil such as climate, management, slope, and crop genetic make-up which are difficult to quantify. Crop yield as the measure of soil value is inappropriate because it “simplifies” the soil by treating it as a closed system in which an array of managed inputs produces a single output, crop yield (Pierce, 1994).
Soil degradation (long-term decline in soil’s productive and environmental regulatory capacity) by accelerated erosion is a serious global issue, especially in developing countries of the tropics. The soil and water resources of the tropics are under pressure and prone to degradation because of harsh environments and fragile soils in ecologically-sensitive eco-regions (Lal, 1994). Erosion ultimately reduces soil productivity. Relationship between soil properties and a soil’s capacity for producing plants or soil productivity has been the focus of a number of current research activities (National Soil Erosion-Soil Productivity Research Planning Committee, 1981). The effects of topsoil loss on soil productivity have been more widely researched in the temperate regions than in the tropical regions. At present, there are serious gaps in our knowledge about the relationships between erosion and productivity in tropical soils (Lal, 2012). Because of the many hectares of new land being brought into cultivation in the wet and dry tropics, it is imperative that research information be made available on the erosion-productivity relationship for these soils; such information is essential in planning development strategies and in selecting appropriate land use and management practices for sustaining soil productivity (Lal, 2012).
The productive capacity of a soil can be evaluated directly or indirectly (Dengiz and Saglam, 2012). Direct evaluations are carried out in the field, greenhouses or laboratory by means of some experiments under given climatic and management conditions. Indirect evaluations consist basically in developing and applying models of varying complexity. There is a need to conduct periodic soil erosion-productivity studies using soil productivity models of proven validity to ascertain the continued ability of a nation’s soil resources “to produce a plant or sequence of plants under a physically defined set of management practices” and by direct implication feed the nation’s population. These indices are calculated based on selected soil properties that are easily measurable. Several models have been developed for predicting loss in soil productivity occasioned by erosion (Laflen et al., 1985; Pierce et al., 1983; Stocking and Pain, 1983; Timlin et al., 1986; Williams et al., 1983). Most methods for evaluating erosion impacts on productivity are based on the relationship of crop yield to soil thickness (or topsoil removed) or to productivity indices that depend upon the depth and quality of the surface soil (Lal, 2012). The most commonly used methods are (a) agronomic methods, including natural erosion plots and yield records and desurfacing experiments; (b) geological measurements and rates of weathering; and (c) modelling and productivity indices (Lal, 2012). The usefulness, effectiveness and application of an index of soil erosion will certainly be limited outside the region, crop, or general use for which the index was developed (László, 2008). For this reason, there is a need to carry out field trials in specific eco-regions in order to evaluate the validity and effectiveness of selected models in quantifying soil productivity with a view to establishing a scientific basis for inclusion and/or exclusion of certain factors in order to enhance their applicability to local soil conditions in specific areas.
Relatively few studies have been undertaken to validate the usefulness/reliability of methods of evaluating the effect of soil erosion on the productivity of Nigerian soils (Mbagwu et al., 1984a; Anikwe and Obi, 1999, Ngwu et al., 2007; Nwite and Obi, 2008; Agber and Anjembe, 2012). Most of these research works on soil erosion-soil productivity relationships carried out predominantly in southeastern Nigeria, focused mainly on the use of a simple numerical index model of Neill (PI) and its modifications in quantifying the relationship between plant growth and soil properties which might be affected by soil erosion, using mostly cereals (maize and sorghum) and rarely legumes as test crops. There is, therefore, a need to investigate the effectiveness of a wide range of methods of predicting the impacts of erosion on soil productivity in southeastern Nigeria. Furthermore, a variety of local crops should be used as test crops in full cognizance of the fact that productivity is a relative term; each crop has its own soil productivity scale, which does not coincide with that of any other crop (Riquier et al., 1970). Soil productivity studies should also be carried out in different locations with contrasting climates and soil types in order to determine the influence of climate and inherent soil properties on soil productivity as affected by soil erosion. Information on the effects of varying degrees of topsoil removal is necessary to determine the relative importance of different topsoil thicknesses in relation to soil productivity. The main objective of this work was to evaluate the effectiveness of four methods of quantifying soil erosion-soil productivity relationship in Nsukka and Ekwegbe, southeastern Nigeria, using groundnut as a test crop. The methods included Neill’s (1983) productivity index (PI), Modified productivity index (MPI), Riquier’s productivity index (RI) and Desurfacing
| Project details | Contents |
|---|---|
| Number of Pages | 124 pages |
| Chapter one | Introduction |
| Chapter two | Literature review |
| Chapter three | methodology |
| Chapter four | Data analysis |
| Chapter five | Summary,discussion & recommendations |
| Reference | Reference |
| Questionnaire | Questionnaire |
| Appendix | Appendix |
| Chapter summary | 1 to 5 chapters |
| Available document | PDF and MS-word format |
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