Indigenous knowledge of soil fertility management in southwest...

Indigenous knowledge of soil fertility

management in southwest Niger

Henny Osbahra,*, Christie Allanb

aTyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia,

Norwich NR4 7TJ, UKbDepartment of Social and Life Sciences, University of Surrey Roehampton, West Hill, London SW15 3SN, UK

Abstract

Agriculture in Niger is a complex and challenging operation. Farmers are faced with low-fertility

sandy soils, variable rainfall, changing social and political situations and an unfavourable economic

environment. Concerns about sustaining soil fertility have been voiced by agricultural scientists, who

view agriculture as the maintenance of soil nutrient capital. Many of the biological and economic

attributes of these farming systems have been documented, and are becoming better understood

through the growing body of agroecological literature. Although agroecology recognises social,

political and cultural interactions, much less is known about the specific details of farmers’ physical

and biological knowledge and how this knowledge is used tomakemanagement decisions. Research in

Fandou Beri village identified a local ethnopedological framework that had fundamental differences

from scientific systems. Farmers’ defined soils according to location, potential for production and

interaction with the wider ecological framework. They drew on varied ecological knowledge and

experiences to make complex and dynamic farm decisions, as at other Sahelian villages. Local soil

fertility management depends on individuals’ capabilities, perceptions of constraints and

opportunities, and their ability to mediate access to different types of resources. This research

suggests that there is a need to maximise the benefits of indigenous knowledge by integrating social

and natural science, for example to help ‘precision farming’, and to use it to understand diversity.

D 2002 Elsevier Science B.V. All rights reserved.

Keywords: Soil fertility; Ethnopedology; Indigenous knowledge; Niger; West Africa

1. Introduction

The Republic of Niger is a land-locked country in the West-African Sahel. It is one of

the world’s poorest countries in the UNDP indices on several accounts. The agricultural

0016-7061/02/$ - see front matter D 2002 Elsevier Science B.V. All rights reserved.

PII: S0016 -7061 (02 )00277 -X

* Corresponding author. Tel.: +44-1603-593904; fax: +44-1603-593901.

E-mail address: [email protected] (H. Osbahr).

www.elsevier.com/locate/geoderma

Geoderma 111 (2003) 457–479

sector is the mainstay of the economy and farmers still rely largely on traditional farming

methods. Unreliable rainfall and poor soils create an unpredictable and harsh environment.

Niger suffered major droughts in the 1970s and 1980s and low rainfall years persisted into

the mid-1990s. Economic restructuring in 1994 pushed up prices for farming products and

cut subsidies for fertilisers; turbulent political and social conditions have created a sense of

insecurity. However, despite these and similar constraints elsewhere in the Sahel, more

people make a livelihood and with greater livestock densities than before the droughts in

the 1970s. This suggests that there is much to be learned from a better understanding of

Sahelian production systems.

This paper compares local and scientific understandings of soils in one village in Niger.

Firstly, Sahelian agriculture and the role of indigenous knowledge are outlined, and

secondly, local soil frameworks are analysed. Finally, local perceptions of soil fertility

change and the application of farmers’ agroecological knowledge to the management of

soil fertility are discussed.

1.1. Sahelian agriculture

Agriculture in dry Africa is undoubtedly suffering some serious environmental, socio-

economic and political problems (Benneh et al., 1996; Commins et al., 1996; Eswaran et

al., 1997; Raynaut, 1997; Barbier, 2000). Changes in soil fertility have been associated

with population growth, low inherent biological productivity, long-term rainfall decline,

inadequate infrastructure, inappropriate agricultural policies, unsustainable intensification,

international debt and unfavourable global market trends (Vierich and Stoop, 1990;

Sivakumar, 1992; Spath and Francis, 1994; Reenberg and Paarup-Laursen, 1996; Reardon

et al., 1997; Adedeji, 1999; Breman and Sissiko, 2000).

Much concern has been raised over low and declining nutrient capital (Stoorvogel and

Smaling, 1990; Smaling and Braun, 1996; Drechsel et al., 2001). Nutrient capital can be

defined as the stock of nitrogen, phosphorus and other essential elements that becomes

available to plants. All soils suffer depletion of that capital when brought into cultivation

as nutrients are removed in crops or lost through leaching, erosion, etc. Sandy low-fertility

soils, common throughout the drylands, are inherently more prone to this problem

(Buerkert and Hiernaux, 1998). Penning de Vries and Djiteye (1992) concluded that

nutrients were limiting in most of the agricultural areas of West Africa that had average

annual rainfalls of above 250 mm. However, the nutrient stocks of individual plots, within

farms and village territories, can differ considerably from the average, depending on

differences in soil texture, land use histories, rainfall variability and the individual

capabilities of the farmers involved.

The agronomic literature on soil fertility under such conditions in the Sahel is

extensive. Fertility is related to productivity and nutrient capital, and must include

reference to the chemical, biological and physical properties of the soil. It is also generally

agreed that fertility must be defined as the ability of the land to produce and reproduce; its

capacity to support the growth of plants over time, under given climate and other relevant

conditions (Ingram, 1990). Agronomic indicators of soil fertility include organic matter

content, microbial activity, soil air and water balance (which is related to soil depth,

texture and structure), and the availability of the most important nutrients (Finck, 1995;

H. Osbahr, C. Allan / Geoderma 111 (2003) 457–479458

Lal, 2000). The main sources of plant-available phosphorus, which is generally the

limiting nutrient in the Sahel (Bationo and Mokwunye, 1991; Mahamane et al., 1996), are

from the weathering of soil minerals, the mineralisation of soil organic matter, fertiliser

applications and organic inputs.

However, this scientific approach to soil fertility management fails to include the

complexity of agricultural practice. First, while technical appraisal does emphasise the role

of rainfall and bioproductivity constraints, analysis tends to use ‘typical’ models of

farmers’ responses, and, in the varied cultural and natural environment of the Sahel, it has

been claimed that this is inadequate (Guyer and Peters, 1987; Vierich and Stoop, 1990).

For example, negative nutrient balances do not always justify recommendations to farmers

for the immediate use of mineral fertilisers. This is because farm households very often

have short-term objectives that run counter to that advice, but which fit prevalent socio-

economic, ecological, public policy and international agricultural circumstances. Cases of

these circumstances are well-documented (Sikana, 1993; McIntire and Powell, 1995;

Scoones and Toulmin, 1999a). Second, scientific systems attempt to be generic in nature,

whereas indigenous knowledge systems are specific, interactive and allow heterogeneity

(Tabor, 1990; Davis, 1996). There needs to be greater integration between social and

natural science discourse and farming practice.

1.2. Changes in agroecological thought and the role of farmer knowledge

The notion of progressive decline in dryland agricultural production, which is

prevalent in the agronomic community (Powell et al., 1999; Breman et al., 2001) is

being challenged (Howorth and O’Keefe, 1999; Mazzucato and Niemeijer, 2000;

Mortimore and Adams, 2001). Soil fertility is no longer merely seen as just a physical

or environmental process. There is a greater appreciation of the multiplicity of

situations and complex interactions between society and nature, making generalisations

inappropriate (Raynaut, 1997).

To deal with the emerging complexity, research approaches have evolved, shifting from

farming systems research into production research and currently focusing the broad notion

of sustainable production. While many hailed ‘Farmer First’ thinking as a step in the right

direction, the ‘Populist’ strategies it promoted have now been said to fail to integrate fully

with local systems, or to translate the socio-cultural and political economic dimensions of

knowledge creation, transmission and use into a usable framework (Scoones and

Thompson, 1993; Chambers, 1997; Neefjes, 2000). The challenge is to listen and learn

from farmers’ own knowledge, and this is not easy. There is still a concern about the

analytical dichotomy between scientific and indigenous knowledge systems in relation to

West African farming (Richards, 1985; Leach and Fairhead, 2000). Simpson (1999)

pointed out that while many of the biological and economic attributes of traditional

farming systems have been documented (Brokensha et al., 1980; Warren et al., 1995), and

are becoming better understood through the growing body of agroecological literature

(Altieri, 1998), much less is known about the specific details of farmers’ physical and

biological knowledge and how this knowledge is used in making key management

decisions. Raynaut (1997) contended that a full understanding of the complexities

demanded a closer engagement at the microscale than most studies had achieved.

H. Osbahr, C. Allan / Geoderma 111 (2003) 457–479 459

Mortimore and Adams (1999) also believed that the major deficiency in the dominant

international research discourse was its lack of concern for the local.

Agroecological approaches to understanding local-level farming systems have had a

large influence in the debate. Agroecology is a combination of agricultural science,

ecology and elements of anthropology (Hecht, 1998). As well as the agroecology

itself, it addresses the social system within which farmers work and legitimates

farmers’ knowledge. The underlying analytic framework owes much to theoretical

and practical attempts to integrate the numerous factors that affect agriculture,

including indigenous ethnoecology (McCorkle, 1994; Gray, 1997; Rain, 1999; Maz-

zucato and Niemeijer, 2000). Using this approach, specific management decisions

cannot be divorced from economy or culture and are embedded in this wholeness or

integrity (Reenberg, 1996).

Part of the agroecological approach has been greater attention to local soil knowledge

(Tabor, 1990; Osunade, 1992; and as reflected in the papers in this collection). There have

been several studies in the Sahel, which have examined ethnopedologies as part of wider

investigations into local land management (Dialla, 1993; Reenberg, 1996; Hopkins et al.,

1995; Baidu-Forson, 1999). Studies of the ethnopedologies of the Djerma (Taylor-Powell

et al., 1991; Manu et al., 1991, 1996; de Groot, 1995; Allan, 1997) and Fulani (Lamers and

Feil, 1995; Krogh and Paarup-Laursen, 1997) have found many common terms within the

separate traditions (not common to both).

Following a focus on indigenous knowledge, many researchers have shown the

ability of smallholders to adapt (Harris, 1999; Ellis, 2000; Abdoulaye and Lowenberg-

DeBoer, 2000; Mortimore and Adams, 2001), while others have demonstrated the

importance of understanding the strategies of differentiated social actors in soil

management (Osbahr, 2001; Scoones, 2001; Scoones and Wolmer, 2002). The themes

from new agroecological thought, in relation to soil fertility management and local

ethnopedological knowledge, are explored further using the following Sahelian village

as a case study.

2. Fandou Beri

The case study is of Fandou Beri (13j31.8039N, 2j33.4486E) (Fig. 1), already the

focus of various scientific and development projects.1 It is a small (population of

about 750–800), but regionally important settlement in the hinterland of Niamey in

1 1996–1998 Project Social and Environmental Relations in Dryland Agriculture (SERIDA), a collaboration

between University College London, the International Institute for Crop Research in Semi-Arid Tropics

(ICRISAT-Niger), the Institute of Hydrology and Brunel University (Batterbury et al., 1999; Warren et al.,

2001a,b). Additional research has been carried out in the village on ecology, indigenous knowledge, hydrology,

erosion and gender (Chappell, 1995; Longbottom, 1996; Osbahr, 1997; Allan, 1997; Piper, 1998; Matthews,

1998). The study village is in the IGPB-SALT site and ‘East-Central’ site of HAPEX-Sahel (The NASA

Hydrologic–Atmospheric Pilot Experiment) (Goutorbe et al., 1997), and soil maps are available (Legger, 1993;

Manu et al., 1991). The nearby village of Banizoumbou has been intensively monitored as part of the HAPEX and

ORSTOM programmes for several years and, along with another nearby site, is currently being used by the

international centres of ICRISAT and ILRI.


southwest Niger. The village territory is approximately 37 km2. The landscape is an

open savanna parkland mosaic of farmland, degraded land, and rangeland. Most of the

arable land is in a wide, shallow valley, filled with now stabilised Late-Pleistocene

dune sands, which thin out northward onto an uncultivable, ferricrete plateau, used

only for grazing and wood fuel. The sandy soils of the valley are poor and acidic, and

as such, are susceptible to rapid leaching, P-fixation and contain free Al. Some of

these sandy acid soils have complex patterns of erosion, exposed hardpans and are

dissected with dry abandoned channels, in which there are soils with higher clay

content. The rains come in a well-defined season from April to September, giving a

mean annual rainfall of about 550 mm. Early-season storms bring high intensity rains

and high winds, which cause erosion and consequent dust storms. There is an

appreciable input to soils of far-travelled dust in the Harmattan season between

November and February, and this appears to replace the calcium and potassium

removed by crops, but not phosphorus (Warren et al., this collection). Villagers come

from Djerma and Fulani ethnic groups and are mostly farmers who practice rainfed

subsistence agriculture and rear small ruminants. The Fulani families farm loaned

fields, but some remain almost wholly pastoral. The agricultural system is focused on

cereals such as millet and sorghum that are intercropped with cowpea, groundnut and

hibiscus in low-density patterns. Farmers have only basic equipment (using hoes rather

than ploughs), rarely use mineral fertiliser because of its expense and apply only

limited amounts of organic fertilisers, relying on short-fallow rotation (averaging 3

years) for nutrient replacement. Many rely on off-farm income to supplement their

household cash flow, made easier by the good access to roads and the capital. There

Fig. 1. Location of study village.


are four primary constraints for the farming community: the unreliable rainfall (above

all), low soil bioproductivity, limited capital and limited labour.

Most farms are dependent on family labour, but farming suffers a shortage of

labour, even at a population density of about 20 people per square km. Nevertheless,

the area of cultivation increased from 11% in 1950 to 23% in 1992 (Batterbury et al.,

1999). This kind of extensification is shared with villages elsewhere in the region

(Heasley and Delehanty, 1996; Amissah-Arthur et al., 2000) and can be partly

attributed to changes in tenure law (Lund, 1998). There have been changes in the

crops grown. Cotton has not been grown since the droughts of the 1980s and farmers

have had to look to the sale of the remaining crops for additional income. The loss of

vegetation on common land and increased harvest of crop residues for household use

appears to have been one of the factors behind the reduction in the numbers of herds

passing through the village, once important sources of manure.

3. Methods

Studying farmers’ knowledge of soil is methodologically demanding because of the high

variability in ecological, cultural and socio-economic factors. The study used a multi-

disciplinary approach, incorporating Grounded Theory (Strauss and Corbin, 1990), partic-

ipatory methods (Guijt and van Veldhuizen, 1998) and soil science to build an understanding

of soil knowledge andmanagement on 20 farms (households were selected through stratified

proportional sampling). The research was conducted during the 1997 and 1998 agricultural

seasons (April–August). The rainy season was chosen because migrant workers have

returned to their farms by April and make the most farm management decisions during this

time. Trained Djerma and Fulfude translators were used to conduct focus groups, transect

walks, farm visits, qualitative interviews and semi-structured questionnaires (including the

household heads, male village elders andwomen). Through a process of participatory review

and repeat visits, information was cross-checked and organised at three scales: field, farm

and village territory.

3.1. Developing local narrative through visualisation

Visualisation techniques were used to develop soil maps of the village territory. Each

member of the group was asked to indicate and describe the location and soil type of their

current fields. After discussing the soil types found in the territory, the group was asked to

draw a map showing the distribution of the soil types. Individuals and groups were

presented with photographs and samples of the different soil types and asked to identify the

soil type. This gave insights into the role of intrinsic physical characteristics and spatial

locations in the classification framework. Farmers were asked about perceived changes in

soils, soil management, and the meanings of the soil and land use terms recorded by

previous studies (Taylor-Powell et al., 1991; de Groot, 1995). Individuals were also asked

to create network diagrams to convey everyday experiences, common knowledge and

practice by representing their individual perceptions of the choices and priorities that

influence resource allocation and investment.


3.2. Methods for eliciting understandings of soil fertility

Farmers were asked to rank the soil types by texture, colour and fertility and to rank

their fields by fertility for 1996 and 1997. Fertility was ranked for both ‘good rain’ years

and ‘poor rain’ years (locally defined). Since not all groups used the same number of soil

types, rankings were scaled by dividing by the total number of soil types ranked. A

modified proportional piling technique was used to quantify the fertility differences

between soil classes. Farmers were asked to use the local boko measure (bundle of millet)

to indicate comparative yields for the different soil classes and fields represented by

identical circles. For comparison, the field with the most fertile soil (as identified by each

group) was said to be producing 100 boko.

3.3. Comparative soil sampling and laboratory analysis

Available ammonium and nitrate in the four locally defined soil types of five fallow

fields was measured from nine duplicate soil samples in each site (10 g of each soil was

shaken in 25 ml 1 M KCl for 1 h, the sediment allowed to settle and the supernatant

decanted). The nutrient content was determined using standard methods described for

ammonium (Rowland, 1983; Gentry and Willis, 1988), nitrate (Dorich and Nelson, 1983;

Tel and Heseltine, 1990), phosphate (Bray and Kurtz, 1945) and organic matter content

(Tiessen et al., 1991). Soil pH (H2O) was measured with a pH meter in a 1:1 solution.

Grain size was measured using a set of soil sieves of 1000, 500, 250 and 45 Am mesh size.

4. Ethnopedological framework

Table 1 gives the local classification for soils in Fandou Beri. The seven groups of

farmers consistently divided the soils into two major soil classes, hard soils (locally known

as botogo and gangani) and sandy soils (tassi). The hard soils were further divided by

perceived fertility, the botogo soils being considered more fertile than the gangani. A

fourth type of soil (korabanda) was identified by a characteristic black surface. Farmers’

opinions differed as to whether korabanda occurred only on hard or sandy soils (it was

observed on both during the survey) and approximately one-third of farmers interviewed

Table 1

The main soil types identified by farmers in Fandou Beri and their distinguishing characteristics (from: Allan,

1997)

Soil name Texture Colour Fertility

Botogo hard; compacted and heavy to work dark brown most fertile but dependent on rain

Gangani hard; highly compacted, needs

animal traction for cultivation

red fertile but dependent on rain

Tassi loose and sandy red, white or black least fertile but still productive in

low rainfall years

Korabanda skin on hard or sandy soil black skin over

any colour soil

fertile in low and high rain years


did not describe korabanda as a separate soil type, whereas all groups described the other

three soil types as distinctly different.

This summary gives a conceptual framework. The division is primarily texture-based

and has two exclusive classes. There is a secondary division in one of these classes based

on fertility, this being characterised by a colour difference. Here again there are two

exclusive classes. Thus, there are a total of three distinct classes of soil (tassi, botogo and

gangani) and a floating class defined by a soil crust (korabanda) that can occur on any of

the other three soils.

4.1. Comparing soil identification characteristics

Despite giving texture and colour as important identifying characteristics, farmers were

unable to distinguish each soil type by these characters alone. When presented with

photographs of each soil type, most farmers could identify the korabanda soils from the

distinctive black surface markings, but were unable to identify, or frequently wrongly

identified the others; this was despite relatively good photographic reproduction. Farmers

invariably asked where they had come from, suggesting the need to use a spatial reference

as the primary method of soil identification.

The mapping exercises were used both to elicit a range of information about the local

ethnopedology and for triangulation, whereby the descriptions of the soil types and

location of the fields farmed by each informant were compared to the soil distribution map

drawn up by each informant at the start of the session. The high degree of agreement

created a local soil distribution map (Fig. 2), although two fields of korabanda soil were

located outside the ‘korabanda area’.

These exercises highlight an important difference between how soils are identified

and differentiated in the local ethnopedological framework and a scientific framework.

Fig. 2. Farmers’ map of soil types (from: Allan, 1997).


Indigenous soil knowledge contained a wealth of information, and direct comparison

with scientific soil classifications is not always straightforward. In common with other

ethnopedologies (Osunade, 1992), colour and texture were used as the primary

characteristics. However, they could not be used to identify soil samples removed

from their physical location with the history attached to that piece of land. In contrast,

a soil scientist often identifies soils from samples far removed from their site and uses

characteristics, including colour and texture, intrinsic to the soil samples to differ-

entiate them. The scientific study of the soils in the territory, conducted during the

NASA HAPEX-Sahel experiment (Legger, 1993), roughly correspond to the three

zones described by the farmers. However, in the scientific survey they are categorised

into units, such as Arenosols or Podzols, that can be separated out from context and

still retain distinguishing characteristics. This is not the case with the local soil

framework.

4.2. Comparing soil fertility

The relative fertility of the different soil types was perceived by the farmers in terms of

crop production. In a year with adequate and evenly distributed rainfall (a ‘good’ rain

year), the groups consistently ranked hard soils (botogo and gangani) as more fertile than

the sandy soils, and all but one group ranked botogo as more fertile than gangani (Table

2). The modified proportional piling exercise was used to produce values that were

comparable for both rainfall regimes. The number (N) is given for each average value in

Fig. 3. Notwithstanding, Fig. 3 does suggest a picture of the relative productivity of the

soil types as perceived by the farmer groups.

Fertility was related both to intrinsic soil properties and critically the amount of

rainfall in a given year (Table 2 and Fig. 3). Few groups ranked the fertility of

korabanda, but of those that did, half ranked it higher in fertility than gangani and

half ranked it lower. This resulted in a similar average fertility rank for the two

classes. In years when rainfall was low or poorly distributed (temporally or spatially)

(a ‘bad’ rain year), tassi soils were given the highest fertility rank (although still only

attaining 70% of hard soil fertility levels in ‘good’ rain years, Fig. 3), while botogo

and gangani were equally low; notably, korabanda retained its relatively high position

in the rankings in these years (Table 2 and Fig. 3). Gangani soils were believed to be

unproductive in a ‘bad rain year’. The pattern of ranks for the sample fields in the

years of survey most closely resembled the ‘good rain year’ ranking pattern. It is clear

from the fertility rankings that soil fertility is not perceived as an intrinsic property of

Table 2

Average scaled soil rank (number of groups who ranked each type given in square brackets) (from: Allan, 1997)

Soil types Good rain year Bad rain year Sample fields

Botogo 0.98 [7] 0.46 [7] 1.00 [7]

Gangani 0.66 [7] 0.43 [7] 0.80 [7]

Korabanda 0.62 [5] 0.79 [5] 0.53 [7]

Tassi 0.28 [7] 0.98 [7] 0.33 [7]


the soil, but rather as an interaction between a combination of soil characteristics

(encompassing nutrient content and texture) and rainfall.

Discussion with the groups provided qualitative evidence to support the relationships

represented in Fig. 3. Farmers described a complex situation, one in which the productivity

of any given field in any given year is difficult to predict with high spatial variability in

rainfall. In previous studies of both Djerma and Fulani, rainfall was also found to be central

to local perceptions of soil productivity (Manu et al., 1991; Krogh and Paarup-Laursen,

1997). Manu et al. (1991) reported that in ‘good’ rain years, crops would be sufficient

regardless of soil nutrients, while in years of lower or more erratic rainfall, low soil fertility

became the more important limiting factor. This study found that it was both the temporal

and spatial (on a field-by-field scale) distribution of rainfall during the growing season that

determined the relative productivity of the soils. It is the soil characteristics that affect

productivity in relation to rainfall that are most important in the local division of soil types.

The ethnopedological framework is evidently based around perceptions of how soil qualities

interact with rainfall to affect productivity, and this suggests that farmers seek to manage

ecological uncertainties to maintain yield even in ‘bad’ rain years.

4.3. Results of laboratory tests

The levels of nutrients measured in all the soils were low and variation between soil

samples within and between grids was high, making patterns of inter-soil type nutrient

availability difficult to distinguish (Table 3). However, tassi soils did have discernibly lower

nitrate values, while botogo, korabanda and gangani had similar values for ammonium. The

highest values of available phosphate and nitrate were found in soil from korabanda.

Inter-site patterns of soil organic matter content and pH did not correspond to observed

patterns in nutrient availability, but grain size did differ slightly between the soil types

(Table 3). Organic matter levels were extremely low in all soil types, not one site having

levels exceeding 0.8%, and inter-soil type differences showed no clear pattern. Average

soil pH was between 5.2 and 5.5. The soils were sandy with generally very low silt

Fig. 3. Comparative expected yields (average number of boko or bundles of millet estimated by each group)—N

for each average is given in square brackets under each soil type in the form [N ‘good’ rain year, N ‘bad’ rain

year] (from: Allan, 1997).


Table 3

Results of scientific soil analysis (from: Allan, 1997)

Code Soil type Fallow age

(years)

NH4–N

(Ag/g) averageNO3–N

(Ag/g) averagePO4–P

(Ag/g) averageOrganic matter

(% dry weight)

pH (H2O)

average S.E.

Grain size

(% dry weight in each size class)

(S.E.) (N= 9) (S.E.) (N= 9) (S.E.) (N = 9) average (S.E.)

(N= 9)

(N= 9)< 0.25

mm

0.5–0.25

mm

>0.5

mm

F13 B Botogo 4 7.7 (1.0) 2.1 (0.9) 2.4 (1.1) 0.1 (0.1) 5.4 (0.1) 40.9 47.0 12.1

F7 2A Gangani 2 8.2 (2.3) 2.3 (1.6) 3.6 (1.2) 0.1 (0.1) 5.5 (0.1) 50.0 37.3 12.7

F7 2B Gangani 2 7.2 (1.6) 1.5 (0.8) 2.5 (0.8) 0.5 (0.1) 5.2 (0.1) 42.3 48.4 9.3

F7 4A Gangani 4 7.5 (1.0) 1.4 (0.7) 3.8 (1.9) 0.7 (0.1) 5.4 (0.1) 56.4 36.1 7.5

F7 4B Gangani 4 9.4 (2.0) 3.5 (1.5) 2.7 (0.5) 0.3 (0.2) 5.4 (0.1) 57.0 34.6 8.3

F1 A2 Korabanda–

tassi

6 9.1 (1.6) 5.3 (0.4) 10.9 (2.1) 0.2 (0.2) 5.4 (0.1) 45.8 41.7 11.8

F1 A3 Korabanda–

tassi

6 7.8 (3.4) 1.5 (0.5) 3.6 (1.3) 0.7 (0.1) 5.3 (0.1) 41.6 48.9 9.5

F5 A Tassi 1 6.5 (1.6) 1.7 (0.3) 4.0 (1.7) 0.3 (0.3) 5.5 (0.1) 34.0 58.7 7.3

F5 B Tassi 1 6.8 (2.0) 3.1 (0.9) 2.9 (1.6) 0.3 (0.2) 5.5 (0.1) 35.7 56.9 7.4

F8 2B Tassi 2 5.4 (0.5) 1.9 (1.2) 4.2 (1.9) 0.7 (0.1) 5.3 (0.1) 29.5 65.4 5.2

H.Osbahr,C.Alla

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(2003)457–479

467

contents. The hard (botogo and gangani) soils had a higher percentage of the finest grains

( < 0.25 mm), which included clay. The tassi soils (including korabanda on tassi) had a

correspondingly higher percentage of the medium sized grains (0.5–0.25 mm).

Of all the factors measured, grain size had the closest correlation to local divisions of

soil types, indicating the importance of water-holding capacity on soil productivity.

Available moisture increases with increasing proportion of fines, sandy soil having the

lowest water holding capacity. Thus, botogo and gangani would be expected to have the

highest available moisture when there is sufficient rain. However, these soils also have the

highest clay content. Although clay was not measured in this study, Taylor-Powell et al.

(1991) recorded clay contents of 2–8%, with the highest values in the soils near the

plateau (i.e. botogo and gangani) and the lowest values in the valley soils (i.e. tassi). Even

small differences in clay content can make a great difference to the hard-setting tendency,

which affects workability, especially under hoe cultivation. It is possible that in bad rain

years or during intense rainfall events, the rain falling on the higher altitude areas of

botogo and gangani would run off towards the tassi areas. This has two effects: erosion

and the transport of water towards the higher tassi soils.

The farmers’ perceptions of fertility were based around an interaction between soil

characteristics and climatic factors, which produced a distinctive pattern of soil fertility

that the scientific soil tests used in this study, were unable to discern. A study that

measured available nutrients over several entire growing seasons may better detect the

patterns perceived by the farmers. However, since intrinsic soil characteristics composed

only part of farmers’ perceptions of fertility, there may be no direct relationship between

measurable soil characteristics and local fertility ratings. The farmers’ ethnopedological

framework relates to a complex management system that incorporates social and cultural

as well as environmental considerations and it is these factors in combination which

dictate the productivity of the land, not soil characteristics alone.

5. Perceptions of change in soil fertility

The majority of the farmers (80%) reported declining soil fertility and crop yields on

sandy soils. They had noticed a lighter colour and coarser texture for soils near the village,

indicating a decrease in organic matter. Farmers attributed these changes to the increase in

the area of permanent cultivation, the decrease in the area of long-term fallow (over 3

years), the limited inputs of manure from livestock, and to low rainfall. Elders believed

that there were fewer areas of black sandy soils (tassi biri), that is those soils with high

organic matter content, and more areas of red or white sandy soils (tassi kirey and tassi

kware), which have lower organic matter contents. This is consistent with previous studies

in the village (Batterbury et al., 1999). Only 10% of the farmers felt that there had been a

decline in fertility of the hard soils and all of them believed that the restricted areas of

tombo had lost little fertility (these soils gain their fertility from inputs near or on

household compounds). In contrast to the beliefs of the Djerma, the Fulani groups reported

no such declines in soil fertility on their fields, which they attributed to their constantly

high inputs. The process of declining soil fertility during cultivation was reflected in the

naming of stages of the rotation system. Farmers describe how one piece of land


progresses from fertile cleared sacara in the first year of cultivation to lalibanda the year

after, to kwar kwari (white sand with less organic matter) in the third season and finally to

boulouga (degraded land) after 5 years. After cropping for 5 years, farmers observe that

some of the field will need to be rested as fallow (farezenon), or nutrients have to be added

or, if particularly degraded, abandoned to long-term bush until the farmer has the ability to

add enough inputs. Under farezenon farmers noticed the development of darker soil

colours and korobanda.

6. Using local knowledge to manage soil fertility

Farmers hold complex ecological knowledge or berey (local knowledge), as the

ethnopedological framework presented in this paper has shown. There is great variation

in the kinds and depth of such knowledge. The choices made by individual farmers

depends on their capacity to enact successful agricultural performances and to exploit an

evolving range of opportunities, and these in turn are based on the use of their local

knowledge, as well as on their communication and creative capacities. The knowledge,

here as elsewhere (Pawluk et al., 1992; Stoller, 1989), becomes intertwined with the belief

and value systems that underlie culture (for example, in the use of metaphoric linkages).

On an individual basis, knowledge is acquired through personal experiences and over-

lapping communication pathways, both of which are influenced by social factors,

including age, gender and family ties. Uncertainties arise because any one farmer’s

knowledge is incomplete and incapable of dealing with risks outside of their partial

perspective and this creates a plurality of perspectives (as discussed by Mehta et al., 1999).

For example, an overlapping set of influences affects knowledge distribution and

communication. One of this set is familial status, based on lineage and traditional

divisions. Family ties can allow access to specialised spheres of knowledge and sources

of income. The traditional belief system and its associated practices is not equally spread,

and appears to be eroding in importance in many locations, especially amongst the young

who chose to enter new professions.

Network mapping can capture some of the farmers’ everyday experiences and

‘common’ knowledge (assumed knowledge held within a culture). Such diagrams

identify the links that exist in soil fertility maintenance practices and the conceptual

arrangement of knowledge or differences in management between individuals. The

varying levels of complexity in the diagrams represent the opportunities and constraints

for individuals. These opportunities and constraints are defined by the household’s

livelihood portfolio or predominance of particular types of ‘capital assets’ (see Carney,

1998; Scoones, 1998; Bebbington, 1999). Hence, the conceptual importance attached to

soil fertility investment for farmers with poor soils and little access to livestock or labour

is defined by constraints, whereas for farmers with exogenous knowledge or with higher

social status, it is defined by opportunities. Thus, each ‘map’ becomes a statement about

the way each individual views farm management, but also a reflection of their status,

power, skills, identity and fears. The example given in Fig. 4 reflects the social and

financial ‘asset’ opportunities open to a Djerma farmer with status in the village (a

marabout and old family lineage).


Furthermore, at the local level, the inherent temporal and spatial heterogeneity of

natural resources is paralleled by equally variable household productive capacity (includ-

ing knowledge, family labour and social networks, livestock, tenure, cash, and ability to

Fig. 4. Conceptual network diagram of soil fertility management (from: Osbahr, 2001).

Table 4

Soil fertility practices used in 1998 (from: Osbahr, 2001)

Soil fertility practice 1998

% Farmers,

n= 20

% Fields,

n= 58

% Tassia,

n= 41

% Gangania,

n= 8

% Botogoa,

n= 9

Fallow: 85 48 60 13 30

(a) Short (1–3 years) 80 38 50 13 0

(b) Long (4 years+) 30 10 10 0 30

Inputs from livestock: 80 34 38 13 30

(a) Corralling or grazing 55 19 25 0 10

(b) Manure transported

from homestead

65 24 30 13 30

Mineral fertilisers 0 0 0 0 0

Nitrogen-fixing crops 100 72 85 38 40

Ash from burning 40 19 23 0 20

Protecting trees 80 69 75 50 80

Laying of millet stalks 100 100 100 100 100

Recycling and

composting organic

materials

90 84 90 70 52

a Although the local soil type is variable with all fields, values are given for the primary soil type found in the

field.


enact resource entitlements) (Osbahr, 2001). There are many constraints to productive

capacity for farmers in Fandou Beri. Table 4 shows that only 21% of the survey

households used labour intensive methods (such as compost or hand-distributed applica-

tions of inputs), while most farmers were dependent on fallow rotation and a variety of low

labour intensive methods. In other circumstances, farmers relied on their local knowledge

of soil characteristics and plant indicators to focus effort in ‘precision farming’ methods, in

which they target their planting strategies and additions of nutrients to specific places and

soil types, with the aim of maximising nutrient recycling (Osbahr, 1997). For example,

farmers value fertile niches around Faidherbia albida, termite mounds, old livestock pens

Box 1. One farmer’s agricultural season in 1998 (from Osbahr, 2001).

Amadou Abdoullaye2 is a middle-aged Djerma farmer. He had inherited three

fields of different soil types but considered the largest, nearest to the homestead, to

have low soil fertility because it had been cultivated continuously for over 50 years.

Below-average annual income meant he relied on help from his family to run the

farm. His family needed to produce an annual minimum of 330 boko for subsistence.

However, in 1997 grasshopper swarms caused much of the farm to be abandoned,

producing a harvest of 146 boko, and presenting him with constraints in essential

resources, such as seed, manure and labour for 1998. Mr. Abdoullaye worked as a

migrant farm labourer in the Ivory Coast from November to February to earn cash to

buy seed. With the lack of early 1998 rains, experience told him that the sandy soils

would be more productive and he decided to clear a 3-year fallow on his large tassi

field and mulch and burn the other fields. He put his household animals on the

closest field but carried manure to the distant gangani field because he had not been

able to pay local Fulani for grazing (7000 F CFA for 2 months). He and his family

planted the millet seed on the tassi parts of the large field 3 days after the first rains at

the end of April. Unfortunately, he misjudged his labour management as the result of

a conflict with neighbours and missed seeding after the next rains, forcing him to

plant a fast growing cultivar. Different crops were planted on the different soils

reflecting the fertility and moisture-retention capability (Fig. 5). He partitioned his

mid-season labour, preferentially weeding the tassi plots. Improved late-season rains

allowed him to redirect work to botogo and gangani areas, which were additionally

able to support sorghum, sorrel and hibiscus (planted at the same time as the millet)

and he planted peanut on these soils 15 days later. However, much of the farm’s

botogo soils had not been prepared and he was restricted to cultivating only those

parts ready. High levels of weed growth, including Striga varieties, developed with

the better rains and several parts were abandoned. Overall, 1998 brought more

sustained late-season rains but his limited labour resources made prioritising action

for soil fertility management and farm tasks especially difficult, making him

vulnerable to unpredictable rainfall patterns (Fig. 6).

2 Name has been changed.


Fig. 5. Seeding pattern used in 1998 (from: Osbahr, 2001).

H.Osbahr,C.Alla

n/Geoderm

a111

(2003)457–479

472

and target applications of green manures, livestock grazing and burning. The importance

of these practices has been widely qualified in numerous scientific studies (Juo and Manu,

1996; Brouwer and Bouma, 1997; Payne et al., 1998; Hiernaux et al., 1999; Wezel et al.,

2000; Esse et al., 2001).

To work with environmental microdiversity, farmers have developed an understanding

that allows them to manage dynamic social, economic and environmental resources, and

this knowledge may often appear to run counter to the understandings of conventional

agricultural science. Their perspective essentially incorporates the ephemerality of soil

status, the historical dynamics of soil fertility and the need for soil fertility maintenance to

reflect natural variability. In the context of annual crop production, the convergence of

these physical and social forces is possibly best conceived as a dynamic performance

(Richards, 1989). It is more accurately a set of linked performances, through which

individuals respond to the evolving set of physical and social conditions within each year,

and from one year to the next (Box 1, Figs. 5 and 6). The general nature of these

performances, as summarised by Moris (1991), applies very well to the situation at

Fandou Beri. Risk and uncertainty dominate farmers’ lives; they must respond to an

unfolding scenario of opportunities and constraints (for example, wet or dry years, early

or late onset of the rains, pest outbreaks in a particular crop, unplanned labour shortages,

and so forth). Farmers are able to bring to their farming an accustomed ‘script’, modified

as the season develops. This does not preclude strategic natural resource management

plans and indeed the process in adaptive strategies operating at different scales and over

different timeframes has been well documented (Reij et al., 1996). Thus, local soil fertility

management is the result of a combination of responses to unforeseen events, planned

management, land use history and the farmer’s own particular knowledge. These form the

basis of a household’s strategy at a particular time, in a specific place, whereby local

knowledge is employed in an array of methods to manage soil fertility depending on

labour and capital.

Fig. 6. Household farm labour and rainfall in 1998 (from: Osbahr, 2001).


7. Conclusions

Our findings show that the local framework for understanding soil types was part of a

wider conceptualisation of the local ecology. The soil classification was based on an

understanding of the interactions of different environmental and social factors, as they

affect the productivity of a particular field. The awareness of differing soil potentials under

variable rainfall or anthropogenic inputs supported an essentially flexible and responsive

management strategy, which may well be better at coping with the inherent and increasing

variability in Sahelian systems than those suggested by orthodox agricultural science. It is

clearly important for research into ethnopedologies to avoid easy comparisons of super-

ficial similarities that may overlay a deeper divergence of perspectives.

The comparison of agricultural science and local knowledge is not straightforward. The

results of the soil chemical analysis, which showed low nutrients levels in all soil types,

indicate that orthodox soil analysis may not distinguish the subtle differences in soil

productivity represented in the local ethnopedology (although more thorough analysis

might detect these). There were fundamental differences between local and scientific

systems for defining and describing soil properties. Whereas scientific frameworks tend to

be based on intrinsic soil characteristics that can be quantified independently of the

context, the local framework defines the important distinguishing characteristics of soils in

terms of factors such as location, potential and interaction in the wider ecology and history.

Risk-aversion and dynamic soil use (responsive to rainfall, household labour, capital and

ability to increase nutrient inputs) are more important in the local framework than are

absolute soil fertility and crop production. Critically, the local knowledge is pluralistic,

locally and historically embedded and socially constructed, factors that are not included in

scientific soil frameworks.

The local ethnopedological framework only represents one part of the farmers’

strategy for managing soil fertility. They draw upon varied ecological knowledge to

make complex and dynamic management decisions. This research has shown that as well

as biophysical, economic and social variability, local perceptions of the environment

heavily influence soil fertility management. The local approach, incorporates measure-

ments of crop yield, integrates complex soil–water relations and allows for inter-annual

rainfall variability. Each household responds to these influences according to its

capabilities, constraints and opportunities and ability to mediate access to resources.

The strategies at Fandou Beri are similar to patterns in other Sahelian villages (Reenberg

and Paarup-Laursen, 1996; Scoones and Toulmin, 1999b; Mortimore and Adams, 1999;

Scoones, 2001).

There is an urgent need for further studies to discover, develop and maximise the

benefits of indigenous knowledge, such as is used in ‘precision farming’ techniques.

They are particularly important where labour and capital are constraining. However,

despite the local capabilities, it is acknowledged that many of the constraints on the use

of technologies to improve soil fertility, such as the scarcity of inputs, labour, land,

capital, and to some extent knowledge, can only be overcome by intervention at the

policy level. In particular, there needs to be greater access to credit and economic

rewards for farmers before investment in soil fertility matches local aspirations and

knowledge.


Acknowledgements

This paper draws on separate research carried out in Niger by the authors during the

1997 and 1998 agricultural seasons. It was funded by awards from the Economic and

Social Research Council and Natural Environment Research Council, Royal Geographical

Society, University College London Research and Travel Committee and the Eric Brown

Geographical Trust. We would like to extend our thanks to the villagers of Fandou Beri, to

our research assistants and local collaborators, and the SERIDA Project. We are grateful

for comments from Katherine Homewood, Andrew Warren, John Pearson, Simon

Batterbury and two referees.

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