Rainfall, biomass and the pastoral economy of Niger: assessing the impact of drought

Journalof Arid Environmenls (1990) 18, 97-107

Rainfall, biomass and the pastoral economy of Niger: assessing the impact of drought Albert E. Sollod* Accepted 6 January 1989 Ground-based biomass measurements, systematic aerial reconnaissance and NOAA AVHRRand Landsat data were used to define the geographic limitsof dry season pasture in the southern part of the pastoralzone of Niger. This dry season pasture, referred to as the pastoral habitat, was of such overwhelming importance to the well-being ofthe pastoralsystemthat it couldbe usedtodefine the sample frame for a meso-scale drought early warning system. Normalized rainfall departures for 1957 to 1987 from multiple sites in the pastoral habitat inferred the common perceptions of recent interannual climatic variations in Niger and their impactson the pastoral economy.

Introduction

During a 1983 reconnaissance of the pastoral zone of Niger, Twareg and Wodaabe herders from various camps were asked for an opinion about the state of the pasture and the condition of pastoral life. It was late January and the 1982 rainy season had ended 4 months before this field trip. The preconception of the reconnaissance group was that 1982 had been a poor rainfall year, an opinion shared by many people in the southern agricultural and urban areas. It was assumed that many herders would soon find themselves in trouble, trying to nourish their herds on inadequate pasture. The 1983 rainy season, which might bring relief, was still 6 months away. Contrary to expectation, herders were unanimous in their opinion of the reasonably good quality of the pasture and the lack of potential problems for the survival of their herds. The last major drought occurred in 1973, and although the rains had not fully returned and, according to the herders, each of the past few years had been a little drier than the last, this dry season would be routine. The dry season progressed as the herders had predicted. Animals in the pastoral zone did not starve and signs of impending famine, like the mass dislocation of people in search offood, were not to be seen. The prescience ofthe herders was not unexpected; they were experienced in the biological and economic e~vironments of the pastoral zone, and the dramatic climatic shifts of the past two decades had amplified their ability to judge the impact of any given rainy season. This anecdote and others like it are sometimes cited as evidence that an information system to assess the short-term impact of rainfall would not contribute to the social and economic security of herders. A drought early warning system (EWS) , it is said, would be

'Tufts University School of Veterinary Medicine, North Grafton, MA 01536, U.S.A. 0140-1963/90/010097

+ 11 $03'00

© 1990 Academic

Press Limited

98

A. E. SOLLOD

of little value since herders are already capable of judging the effects of the rainy season. Also, an EWS would not, in itself, increase a government's ability to respond to a crisis (McIntyre, 1987). While these arguments acknowledge several obvious points, they also neglect a fundamental question: are herders better off in the long run if the government is unable to evaluate the impact of rainfall on the pastoral economy? In Niger and probably most of the Sahel, pastoral herders have become progressively more dependent on governments to provide assistance in times of drought (Sollod et al., 1987). The colonial conquest of West Africa reduced the economic diversity of pastoral people, who consequently came to rely less on caravan trade (and raiding and local taxation) and more on the extensive herding of cattle, sheep, goats, camels and donkeys (Starr, 1987). This increased the sensitivity of the pastoral economy to climatic variation, since the means of production, the animals, could be irrevocably lost during drought. The only relief possible would come as emergency aid from local governments and international donors of food and medicine. Given that this economic dependence on animal agriculture will exist for the foreseeable future, it would seem to be in the herders' interest to be supported by governments that are knowledgeable about conditions in the pastoral zone. At first thought it seems that a pastoral drought EWS could be predicated on what the herders know. There are, however, several good arguments for the development of an EWS that is independent of the herders' evaluations. The objections are based on the great complexity of the variables that herders consider, on the qualitative nature of the assessment which they articulate, and on the difficulty of obtaining unbiased reports from people who understand the potential for obtaining free aid by manipulating the information. First, the variables on which the herders assess drought impact are too numerous and interdependent to be readily measured and evaluated in a practical EWS. The herders' evaluations are derived from their perceptions of recent rainfall and consequent biomass, the condition of the herds, the quality of pasture and water points, the state of the markets in which they buy and sell, their current resource-use rights, and many other factors. Their judgments are personal and are influenced by the current economic and political conditions of the societal unit to which each herder belongs. It would be difficult for an outside agency to generalize these complex analyses to the pastoral population as a whole, in order to assess the need for drought relief on a large scale. Second, the herders produce a qualitative assessment of drought impact that would be difficult to act upon with any degree of precision. The national and international responses to drought are always quantified, even if the results often seem haphazard. Governments offer fixed quantities of grain to be delivered by a known number of lorries that will consume a specified quantity of fuel and require so many spares and repairs. In agricultural areas where food crops are grown, the estimated harvest (or the shortfall from normal production) is usually accepted by governments as the quantified indicator of the need for food relief. An analogous indicator for pasture or animal production could not be obtained from the herders themselves, and bureaucratic agencies would not accept the subjective, unconfirmed evaluations. Third, it would be a hard task to obtain unbiased information from the herders. While herders often seem eager to give honest information to strangers who show an interest in their activities, they would eventually perceive that pessimistic assessments were more likely than optimistic ones to bring in food aid. Discounting that a few may simply fabricate, for the majority it would become difficult not to let this element bias the reporting. Worse still, control of the information collection network might be usurped by local elites, who could then manipulate the data in order to bring free food to their supporters. Accepting that a pastoral drought EWS should be immune to manipulation and based on a relatively simple external assessment using quantifiable indicators, what should be its objectives?

THE IMPACT OF DROUGHT ON NIGER

99

Objectives ofa pastoral early warning system There is no reliable way to predict drought, that is, to detect its approach in advance (Wilhite & Glantz, 1985). The simplest objective of a drought EWS is to identify the occurrence of a drought as early as possible after its start. Since drought is a creeping phenomenon, whose onset and end are often indefinite, EWS information is not very useful in identifying the time-boundaries of a drought, except perhaps in retrospect (Wilhite & Glantz, 1985). However, current research into medium-range climatological forecasting may one day make possible these potentially important predictive capabilities. An operational EWS for disaster readiness may also attempt to assess the future impacts of a drought. A quantified measure of a shortfall in the harvest may be used to determine the amount of food relief that will be needed. The spontaneous dislocation of people into camps may be a red flag that cholera vaccine will be required. Like any drought EWS, a pastoral EWS is useful only if it is designed around a specific objective or set of objectives for a defined geographical area. In general, the features of an EWS-which and how many variables are considered, how these are measured, what analyses are undertaken, and who receives the results-depend on the unique objectives of each EWS. In systems that measure crop production, rainfall is often measured during the growing season to estimate probable yields before the harvest. For the development of a pastoral EWS, there is a growing interest in rainfall-biomass models and satellite reflectance data that correlate with pasture biomass at the end of the rainy season (Tucker et al., 1985; Hiernaux & Justice, 1986; Justice & Hiernaux, 1986). In order to formulate useful objectives for an EWS, an understanding of the target area is required. The northern, or pastoral, zone of the West African Sahel is an irregular, 200 km-wide strip of sand dune grassland and wooded savanna that merges into the of the Sahara Desert. It is a bioclimatic region delimited by 150 and southern frin~~ 25r---------------------,

20

z

Rainy ""-l...------,tL--seasan ;razln;

..,'" .a ~

...J

10

5

Northern limit of extensive cultivation

0

5

10

15

20

Longitude E

Figure 1. Mapof Nigerwithlocations ofstudyarea, pastoral habitatand the meteorological stations used in this analysis. I, Tahoua;2, Tchintabaraden; 3, Ingal1; 4, Agadez; 5, Abalak; 6, Dakoro: 7 Tanout; 8, Goure; 9, N'guigmi,

' ,

100

A. E. SOLLOD

Figure 2. Relationships of rainfall to biological and economic variables.

300 mm isohyets and producing 250 to 1000 kg of herbaceous biomass per hectare per year (Justice & Hiernaux, 1986). Extensive transhumant herding is the predominant mode of agricultural exploitation. The present study area (Fig. l~ forms the boundaries of a pastoral livestock development project. It is an 82,000 km rectangle in central Niger located between about 15-17° Nand 5-8° E (Milligan, 1982; Justice & Hiernaux, 1986; Sollod et al., 1987). In this paper the pastoral zone is subdivided into a northern area of rainy season grazing and a southern area called the pastoral habitat. The study area includes a cross-section of the pastoral zone and extends slightly beyond it, both north and south. Herders in the study area, like those in most of the northern Sahel, produce animals for milk, meat and other subsistence purposes. At least as important, they market live animals in order to purchase cereal grains for family consumption. The normally higher value of animals relative to cereals permits herders to purchase more food calories than they sell. The ratio between the selling price per kg of animal and that of millet or sorghum reflects this commercial relationship. When this terms-of-trade ratio is high, the herders' purchasing power is sufficient to sustain the pastoral economy; when it falls, pastoral production may become uneconomic (Sutter, 1982). Figure 2 is a simplified flow chart of the linkages between rainfall and the major intermediary determinants of the pastoral economy. Annual rainfall usually begins in Mayor June, concurrent with the northward penetration of the intertropical convergence zone (ITCZ) into the desert fringe, and ends in September. In the above model, rainfall is the first variable to affect the system. The next determinant is the production of natural vegetation (pasture); this directly determines the energy available for animal production during the next 8 to 9 months. Millet production, which takes place south of the pastoral zone, is determined at about the same time, but its influence on the economy comes later, at the market level. In general, when drought occurs, the pasture grows poorly and the potential for animal production declines. Animals grow more slowly, they reproduce less frequently, and give less milk. Their value declines as they lose condition. The market collapses when herders attempt to dump animals they can no longer feed, and for which there is little demand. If the drought is

THE IMPACT OF DROUGHT ON NIGER

101

widespread, millet production south of the pastoral zone also declines, but millet grain prices rise because of scarcity. Since their incomes drop while the price of millet is rising, herders become a disadvantaged population in relation to crop farmers. Aerial estimates of animal populations in the study area (Milligan, 1982) and estimates of annual residual biomass indicate that there is sufficient carrying capacity to sustain animal production except after 2 consecutive years of severe drought (Greenwood & de Leeuw, 1983). After 2 years the entire system crosses a threshold and collapses; there is massive animal mortality, herders gather spontaneously into camps to seek relief, and famine ensues if relief is not prompt. From this simplified discussion of the linkages in the pastoral economy, and given the predictive limitations of available technology, the following are realistic objectives for a pastoral drought EWS: (1) to provide an index at the end of the rainy season (midSeptember) of the potential for animal production during the next eight to nine months; (2) to provide a red flag alert when drought in one year is so severe that continuation into a second year would result in a collapse of the pastoral economy; (3) to indicate whether the second, catastrophic drought year has occurred; and (4) to provide an annual index for long-term monitoring of the pastoral zone.

The selection of indicators The two obvious variables that may be capable of fulfilling these objectives are rainfall and pasture biomass production. The pasture in the study area has been monitored each year from 1984 to 1987 by ground sampling and by National Oceanographic and Atmospheric Administration (NOAA) satellite with data from the advanced very high resolution radiometer (AVHRR). Correlations were made for 2 years between ground biomass samples and satellite-derived normalized difference vegetation index (NDVI) (Wylie et al., 1987, 1988). In the present analysis, before examining the relative contributions of rainfall and NDVI, certain assumptions were laid out to serve as markers of the 'fit' with historic data. Below are some commonly held perceptions of herders, government officials, and development workers about the study zone. Rather than referring to the calendar year, the assumptions apply to the period from about I July of the cited year, when the seasonal rainfall begins to impact on the pastoral environment, to about 30 June of the next: (1)

c: '"

.s

0

..

<; 0;; "0 "0

(;

"0

~

en

-I

Year

Figure 3. Normalized annual rainfall departures from 14-20 stations located from 11-18° N and west of 10° E; Lamb et at. (1986, personal communication: 1986 and 1987). Base period is 19411986.

102

A. E. SOLLOD

Table 1. Populations, carrying capacities and rain useeffUiency in the 82,000 km2 study area ofcentral Nigerl Year

Cattle population Total animal population'

Human populations non-sedentary sedentary]: total pastoral

1981

1982

1984 1985 1986 in thousands of units

380

330

45

535

540

100

1987

110 70 180

Carrying capacity (standing herbage):j: northern half mm rainfall (two stations) rain use efficiency§ southern half mm rainfall (seven stations) rain use efficiency total carrying capacity

0(8) 25'1 0·32 0(32) 159'4 0·2 0

0(290) 107·5 2·7 610 (767) 229 3-35 610'00

180 (523) 130'5 4·0 465 (921) 237-4 3-88 645'00

0(144) 101'5 1·42 500 (613) 184'1 3-33 500'00

Source: Niger Integrated Livestock Production Project and Niger Range and Livestock Project reports. 1. Census by low altitude systematic aerial reconnaissance during September-October. 'Cattle, sheep, goats, camels, and donkeys in tropical livestock units (TLU) = cattle equivalent-weight units. t Excludes all village and urban population centers. :j:Satellite and ground data, 1985 & 1987; ground data only, 1984 & 1986; in 1000 TLU/41,OOO km 2 (kg standing herbageJhectare). §kg standing dry herbage/(hectare x mm rainfall).

Table 2. Totalannualrainfall for ninemeteorological stations in thepastoral zoneof Niger, 1957-1987

Station

Latitude N

Rainy season grazing Agadez Ingall

Pastoral habitat

N'guigmi Tchintabaraden Abalak Tanout Goure Dakoro Tahoua

Standard deviation (mm)

Coefficient of variation (%)

Longitude E

Mean (mm)

16·98 16'8

7'98 6'92

121·8 176'6

57-3 73-9

47 42

14'25 15·9 15'42 14·96 13-98 14'51 14'87

13'11 5-82 6'25 8'87 10·27 6'75 5·25

202·7 206·8' 231'7" 24H 297'6 327'6 375-8

102·8 62-2 65-8 88·2 107-6 104'2 106'0

51 30 28 37 36 32 28

Source: Niger National Directorate of Meteorology. '1968-1987.

THE IMPACT OF DROUGHT ON NIGER

103

1972 was a year of extreme drought; (2) 1973 was a year of extreme drought, and the pastoral economy collapsed; (3) 1974saw an abrupt end to the drought pulse; (4) 1978was the last good year before the 1983 to 1984 drought; (5) 1980to 1982 saw a stepwise annual decline in pasture; (6) 1983 was a year of extreme drought; (7) 1984 was a year of extreme drought, and the pastoral economy collapsed; (8) 1985)saw an abrupt end to the drought pulse; (9) 1987 was a year of extreme drought. While the markers do not signify conditions over more than a few consecutive years, they should be consistent with longer term events such as the sub-Saharan drought which has been ongoing since the 1960s (Lamb et al., 1986). Therefore, if the 1972-1973 and 1983-1984 drought pulses that were experienced in the Niger study area were a part of this larger phenomenon, it should be possible to recognize some of the markers in a general rainfall index for sub-Saharan Africa. Figure 3 is an abridged version (1957-1987) of a graph that is frequently cited to depict sub-Saharan rainfall trends in West Africa over the past five decades. The numbers and question marks placed above or below the bars on the graph correspond to the assumptions listed above. A number denotes a year in which the validity of the corresponding assumption is inferred by the actual rainfall departure. A question mark indicates no apparent relationship between the rainfall departure and the perceived condition of the study area for that year. For example, in 1972 the assumption of extreme drought may be inferred by the negative rainfall departure of more than one standard deviation. Marker # 1 is therefore placed on the graph to indicate this fit. In 1973, however, the assumption of extreme drought and economic collapse is not inferred since the rainfall departure is no greater than that of several other unnotable years and, in fact, is even slightly more favorable than the 'recovery' year of 1985. A question mark, rather than marker # 2, is therefore placed above the bar. The most striking feature of the sub-Saharan rainfall index is the dissimilarity between the drought pulse ofthe 1970sand that of the 1980s. Even though most of the assumptions of the 1980s decade are inferred by the rainfall departures, if the patterns between two drought pulses can deviate this greatly, the information would not be useful for early warning. Indicators which bear a closer relationship to the pastoral zone of Niger are therefore required.

Focusing on the pastoral zone ofNiger The study area represents a cross-section of the pastoral zone. Weight measurements of annual pasture production have been taken each year from 1984-1987 at 23-25 'groundtruth' sites within the area (Wylie et aZ., 1988). The sites are representative of land management units that were identified by systematic aerial reconnaissance (Milligan, 1982). They consist of stabilized dunes, northern dunes, flood plains and rocky outcrops (Wylie etaZ., 1988). In 1985and 1987the NDVI from NOAA AVHRR data was calibrated from the ground measurements and mapped over the study area (Wagenaar & Ridder, 1987; Wylie et al., 1987). In 1987 it was mapped across the entire pastoral zone of Niger, without further biomass verification. Two readily distinguishable biological strata of the pastoral zone have become apparent from these studies, a dry season pastoral habitat in the south and a rainy season grazing area in the north. Only once, in 1986, did the northern half of the study area produce and retain sufficient biomass to support animal production during the ensuing dry season. Even in this case, it produced only 36% of the total biomass and was calculated to provide 28%of the carrying capacity of the study area (WylieetaZ., 1987; 1988). Table 1gives some population, biomass and rainfall data for the study area. Figure 1 shows the extent and location of the pastoral habitat for 1987. The northern boundary is extended across Niger using 1987 NDVI. A sharp division at this boundary can be distinguished with mapped, calibrated NDVI; virtually all of the surface area above

A. E. SOLLOD

104

2·01--

~ .£1 o

.....- - - - - - - - - - - - - - - j

4

10

3

's

'"

."

"E o

0·0

." C

o

Ui -1·01---------

87

Year

Figure 4. Normalized annualrainfall departuresfromseven locations in or near the pastoral habitat of Niger.

2·00

Ul

c

.£1

0 .>

4

1·00

'"

."

~

0

-e C

0

Vi -1-00

-2·(':.)

57

59

61 63

65

6' 69

Year

Figure 5. Normalized annualrainfall departuresfortwolocations in the rainyseason grazingzoneof Niger. the northern boundary has a maximum herbaceous cover of 200 kg/ha, therefore, zero carrying capacity when allowing for residual cover and natural decomposition. The northern limit of extensive cultivation, which forms the southern boundary of the pastoral habitat, was identified with 1987 Landsat data. There are nine meteorological stations in or near the pastoral zone where data have been collected for 20 or more consecutive years. The geographic coordinates and rainfall statistics for each meteorological station appear in Table 2. The range for mean annual rainfall is from 121·8 mm in Agadez to 375·8 mm in Tahoua, therefore slightly wider than the 150-300 mm range of the northern Sahel. In view of the disproportionately greater biomass of the pastoral habitat in relation to the rainy season grazing area, rainfall data were aggregated from the seven meteorological stations located in or near the pastoral habitat (Fig. 1). Agadez and Ingall, in the rainy season grazing area, were not included in the sample frame on grounds that they represented sites that did not regularly produce or retain enough biomass to support pastoral production during the critical dry season.

THE IMPACT OF DROUGHT ON NIGER

lOS

The data are presented in Fig. 4. In all cases but 1985, the markers fit the rainfall departure patterns. The drought pulses of 1972-1973 and 1983-1984 appear similar, both having consisted of two consecutive very dry years preceded by several mediocre ones. The only inconsistent rainfall departure is for 1985 which, at -0·5 standard deviations, does not imply an abrupt end to the drought. However, NOVI and biomass measurements indicate that the carrying capacity ofthe pastoral zone was restored to 610,000 TLU, all being accounted for within the pastoral habitat (the southern zone in Table 2). The total animal population at the time was only 100,000 TLU, although the pastoral habitat of the study area could have supported more animals than were present in 1981 or 1982, before the drought. Finally, 31 years of rainfall data from Agadez and Ingall were examined for their relationship to the markers. The departure results are presented in Fig. 5. They show little resemblance to the pattern of rainfall in the pastoral habitat, and most of the markers cannot be identified from the rainfall departures. This is not surprising since the variability is very high at these low rainfall northern sites (Table 1). The lack of correlation and the relative unimportance of the northern, rainy season grazing area are adequate reasons to reject these sites from the sample frame of a pastoral EWS.

Discussion In 1982, rainfall in the pastoral zone of Niger was below average, but the herders were satisfied with the pasture. When the field reconnaissance was undertaken in late January of 1983, the herders apparently were aware that the southern zone, or pastoral habitat as it was called in this analysis, would be a sufficient resource for their herds. Quantitative data are lacking on pasture production resulting from the 1982 rains. However, the field reconnaissance group visually estimated the herbaceous biomass at 500-1000 kg/ha while traversing the study area between Tchintabaraden and Abalak (personal observation). These unsystematic observations, made while crossing the pastoral habitat, help to confirm the herders' ability to assess pastoral environmental conditions. The important points arising from the present analysis are: (1) a normalized rainfall departure based on three decades of data within the pastoral habitat is a good quantitative indicator of the state of the pastoral system; (2) the pastoral habitat, in contrast to the northern, rainy season pasture, is of such overwhelming importance to the well-being of the pastoral system that it can be used to define the geographic area from which a pastoral EWS must obtain data; (3) data can be brought together from many sources, both quantified and subjective, in order to determine a relatively simple indicator for a pastoral drought EWS. No attempt was made to compare results by varying either the time frame or number of data-collection points. The three-decade limit for rainfall data was imposed by the short period that most meteorological stations within or near the pastoral habitat of Niger have collected data. To achieve better coverage, it was considered advantageous to add two sites (Tchintabaraden and Abalak) with only two decades of data. Hiernaux (1984) also used a three-decade time frame for a rainfall-biomass model in Mali that was subsequently applied to an analysis of NDVI in the Niger study area (Justice & Hiernaux, 1986). Whether three decades is optimal is unknown; it would depend on a complex set of demographic, economic and climatic variables. Emphasis on the pastoral habitat implies that the pastoral system is dependent on the annual grasslands of the southern pastoral zone. This does not mean, however, that the northern zone is devoid of animals during the dry season. Micro-depressions with perennial brush are scattered across the north and support numerous camels and goats throughout the year (Milligan, 1982). These habitats probably have carrying capacities

106

A. E. SOLLOD

that are less sensitive than the annual grasslands to seasonal rainfall and, therefore, protect some herders from the impacts of drought. The pastoral zone was analyzed at the meso-scale for several reasons. First, a minimum scale must be reached in order to justify national or international response to drought. Local level distress is best relieved by local response, in which case an external EWS should not be required. Second, the pastoral habitat is treated as a uniform 'agroecological' zone that is subject to a normative drought process. Third, the diverse types of data that have been collected since 1981and used in this analysis are most easily reconciled at the meso-scale. When analyzed together, studies from the pastoral zone of Niger (Justice & Hiernaux, 1986; Milligan, 1982; Wagenaar & de Ridder, 1987; Wylie et al., 1987,1988) suggest why herbaceous residue in the north is commonly absent or minimum. Justice & Hiernaux (1986) discuss various reasons for poor rainfall-NOVI correlations under conditions oflow biomass. These include surface runoff, overgrazing during the past year or years, and grazing during the rainy season. The abrupt dividing line between the northern and southern pastures intersects uniform areas of both stabilized dunes and wooded Sahel savanna, and lies approximately 100 km south ofthe region's major flood plains (Milligan, 1982). Thus, although localized runoff may account for some of the variability in biomass, meso-scale surface phenomena do not explain the major north-south difference. A reduction in annual grass seed from prior overgrazing may occur in some years. However, this does not explain the division either, since strategic grazing control is not practiced in Niger's pastoral zone. It seems highly improbable that a deficit of seed would occur along a uniform boundary through herding practices characterized by decentralized management. Considering the above, and the fact that the area supports rainy season transhumant grazing almost every year, it is suggested that the north-south difference is the result of a complex vegetation response to rainy season grazing when rainfall is lower than a certain threshold. A comparison of interannual changes in the rain use efficiency (RUE) (Table 1) suggests that the vegetation response becomes volatile when total rainfall is below 130 mm in the north and 180 mm in the south. Le Houerou (1984) discusses the factors that influence RUE, including aridity, soil conditions and vegetation-livestock interactions, and emphasized that it is this latter dynamic status on which RUE is most dependent. In contrast to the volatility of RUE in the northern grazing area, RUE in the pastoral habitat of Niger is relatively insensitive to rainfall variability. For example, during the 1987 drought year RUE in the northern grazing area dropped to 1·42 kg/mm, whereas it was 3·33 kg/mm in the pastoral habitat (Table 1). Only in 1984, after 2 years of extreme drought, was RUE in the pastoral habitat of Niger extremely low. From 1985-1987, it was greater than the 2'5 kg/mm reported for the Sahel (Le Houerou & Hoste, 1977) but lower than the worldwide mean of 4·03 kg/mm reported for 77 arid lands data sets (Le Houerou et al., 1988). Rainfall is the first variable to influence conditions along the pathway from drought to famine (Fig. 2). In the present paper, normalized departure data from the pastoral habitat best reflected some common perceptions of historical conditions in the pastoral zone of Niger. Although the analysis demonstrated the potential usefulness of rainfall data, biomass measurements were necessary to identify the pastoral habitat and thus to select the most applicable geographic area for sampling. Since biomass is an early responding rainfall-dependent variable, further research on satellite-derived NOVI should be undertaken with a view to incorporating such data into an operational EWS. In addition cumulative rainfall before the end of the rainy season should be analyzed in order t~ improve the potential for real-time reporting of conditions in the pastoral zone. I wish to thank Abdou Nababaand Bagoudou Maidagi, Director and Coordinator,respectively, of the IntegratedLivestock Production(ILP) Project,NigerMinistryof Animal and Water Resources,

THE IMPACT OF DROUGHT ON NIGER

107

for supporting the activities on which this analysis is based. John Harrington Jr, reviewed the manuscript and provided many helpful comments. Partial funding was provided by Grant 683-0242 from the United States Agency for International Development to the Government of the Republic of Niger.

References Greenwood, G. & de Leeuw, P. (1983). Annex 10: Natural resources management. The Niger Integrated Livestock Production Project Paper. MA, North Grafton: Tufts University. 36 pp. Hiernaux, P. H. Y. (1984), Distribution des pluies et production herbacee au Sahel: une methode empirique pour characteriser las distribution des precipitations iournalieres et ses effets sur la production herbacee, Document de Programme AZ 98, CIPEA, Mali. Hiernaux, P. H. Y. & Justice, C. O. (1986). Suivi du developpement vegetal au cours de l'ete 1984 dans Ie Sahel Malien. InternationalJoumal of RemoteSensing, 7: 1515-1531. Justice, C. O. & Hiernaux, P. H. Y. (1986). Monitoring the grasslands of the Sahel using NOAA AVHRR data: Niger 1983. InternationalJournal of RemoteSensing, 7: 1475-1497. Lamb, P. J., Peppler, R. A. & Haspenrath, S. (1986). Interannual variability in the tropical Atlantic. Nature, 322: 238-240. Le Houerou, H. N. (1984). Rain use efficiency: a unifying concept in arid-land ecology. Joumal of Arid Environments, 7: 213-247. Le Houerou, H. N., Bingham, R. L. & Skerbek, W. (1988). Relationship between the variability of primary production and the variability of annual precipitation in world arid lands. Journal of Arid Environments, 15: 1-18. Le Houerou, H. N. & Hoste, C. H. (1977). Rangeland production and annual rainfall relations in the Mediterranean Basin and in the African Sahelian and Sudanian Zones. Joumal of Range Aianagement. 30: 181-189. McIntyre, J. (1987). Would better information from an early warning system improve African food security? In: Easterling, W. E. & Wood, D. A. (Eds), PlanningforDrought. Toward a Reduction of Societal Vulnerability, pp. 283-293. Boulder: Westview Press. 597 pp, Milligan, K. (1982). Aerial Survey of Human, Livestock and Environmental Conditions in a Central Region of the Pastoral Zone of Niger. Final Report for USAIDlNiger. International Livestock Centre for Africa, Kaduna, Nigeria. 105 pp. Sollod, A. E., Cord, L., Nababa, A., Maidagi, B. & Mani, Y. (1987). Livestock Development Strategy for the Drought-Prone Ecology of Niger. Report of the Integrated Livestock Production Project. Government of Niger/Tufts University/USAID. 40 pp. Starr, M. (1987). Risk, environmental variability, and drought-induced impoverishment: the pastoral economy of central Niger. Africa, 57: 29-50. Sutter, J. W. (1982). Commercial strategies, drought, and monetary pressure: Wo'Daa'Be nomads of Tanout Arrondissement, Niger. Nomadic Peoples, No. 11: 26-60. Tucker, C. J., Vanpraet, C. L., Sharman, M. J. & Van Ittersum, G. (1985). Satellite remote sensing of total herbaceous biomass production in the Senegalese Sahel: 1980-1984. RemoteSensing of the Environment, 17: 223-249. Wagenaar, K. T. & Ridder, H. de (1987). Estimates ofBiomass Production andDistribution in theILP Project Zonein 1985, BasedonSatelliteNDVI Values. Plant science division working paper no. C1. International Livestock Centre for Africa, Addis Ababa. 43 pp. Wilhite, D. A. & Glantz, M. H. (1985). Understanding the drought phenomenon: the role of definitions. WaterInternational, 10: 111-120. Wylie, B., Maidagi, B., Harrington, J. & Denda, I. (1987). Early Waming System Preliminary Report. Report of the Niger Integrated Livestock Production Project, Government of NigerlNew Mexico State UniversitylUSAID. 29 pp. Wylie, B., Maman, A. , Harrington, J., Denda, I. & Pieper, R. (1988). 1987Pasture Assessment Early Warning System,Research onSatellite-Based Pasture Assessment Implementation Techniques. Report of the Niger Integrated Livestock Production Project, Government of NigerlNew Mexico State UniversitylUSAID. 32 pp.