Human geo-ecological interactions in Kuh Daman, a South Asian mountain valley

Applied Geography

(1985). 5, E-27

Human geo-ecological interactions in Kuh Daman, a South Asian mountain valley Nigel J.R. Allan Department of Geography University, Baton Rouge,

and Anthropology, Louisiana LA 70803-4105, USA

State

Abstract A meso-scale methodology for obtaining and analysing primary data from an isolated mountain environment is described. By combining villag_e cropping data with irrigation water supply and tribal affiliation, the systemic relationships between these features are delineated for 4iO villages in a Hindukush mountain valley. The emergent highly variable cropping systems indicate congruity with tribal affiliation and also with agronomy. This inclusion of cultural factors in regional mountain research appears to be a necessary precondition for microscale geo-ecological research.

Introduction Recent field research on mountain land use has focused on the systemic relations between physical and biological phenomena of the natural world. As originally conceived by the German biogeographer Carl Troll (1939). these interrelationships between organisms and their environmental factors had both a geographical and biological component. Troll, who applied his holistic viewpoint-which he later termed geo-ecology (Troll 1966)-to the examination of mountains around the world, included the study of humans as manipulators in the geo-ecology of mountain landscapes only at the end of his career (Troll 1972). Uhlig (1976. 1978) successfully applied the concept of geo-ecology to the highly variable cuItivation of rice in the tropics and subtropics. Bishop (1978) introduced cultural variables into the traditional framework of mountain geo-ecology. As applied to the study of mountain land use in relatively remote and undocumented areas, geo-ecology is a suitable conceptual framework for field research (Ives 1981). Its Iimitation thus far has been the difficulty of integrating cuItura1 variables with suitably scaled mountain land use data, and then positing the systemic relationships which may exist. This study surmounts the difficulties by documenting a methodology for meso-scale geo-ecology field research in mountains and by examining the interrelationships between agriculturalists and the crops they choose to plant in a mountain valley located in the extreme northwestern area of the HimalayaHindukush (Fig. 1). Mountain geo-ecology Much of the early emphasis in mountain geo-ecology fell by the International Geographical Union Commission ecology. These tasks recommended studies of various geographically in different climatic regions of the world 01~~228/85/01001~1~

$03.00 Q 1985 Butterworth

within the tasks outlined on High Altitude Geophenomena distributed and synthetic studies of

& Co (Publishers) Ltd

14

Hllman geo-ecological

inrerncriotu in (I Sods Asirm vczl1e.v

AFGHANISTAh I

Figure 1. Mean annual precipitation.

Kohestan,

Northwestern

South Asia.

horizontal and vertical arrangements of landscape types (Troll 1972:-I). As the concept of geo-ecology evolved, two research themes became apparent: one was the move away from purely geomorphological-biogeographical-climataiogical studies to those which included altitudinally-related human use of mountain land (Grdtzbach 1973, Uhlig 1978). Another effort was directed at introducing the concept of ecosystems. an idea which later received support by UNESCO’s Man and the Biosphere Project 6 programme. Because of the inherent logistical difficulties of mountain research, most studies continued to focus on single villages and small populations (Moser 1975; Alirol 1977; Moser and Peterson 1951). As the Alps had been the scene of intensive field research for two centuries. a great amount of information had been gathered on ecclesiastical censuses and land tenure; hence the best mountain land use studies are found there. Obergurgl. Austria (Himamowa 1975) and Grindelwald. Switzerland (Ape1 1952) are good examples which relate human use of mountain land with systemic analysis of physical and biological variables at the micro-scale level. These village studies fulfil the second component of Troll’s concept of geo-ecology, the micro-scale single site however. the geographical. spatial, or biological study. The first component, regional perspective. is absent. The principal difficulties in conducting regional research in mountains. especially in the non-Western mountain world, are the paucity of suitable field data and the logistical problems in gathering such data. Apart from the fragmentary tenure and agricultural data available for Indian Himalaya (Pant 1935; Atkinson 19SO; Shah 1981). systematic data collection from the Htmalaya-Hindukush has been almost non-existent. Lacking appropriate field data, research on geo-ecology-related topics has focused on micro-scale village studies (Caplan 1970: Snoy 1975; Messerschmidt 1976; Hoffpauir 1978; Frank 1982). The inherent problem m these studies is that the researcher cannot determine how well these villages represent the region. Consequently. a regional multifactor perspective of a mountain valley or watershed, combining human and land use data, is rare (Rathjens el al. 1973). As

these areas come under the control of central governments which are equipped to collect census data on mountain land use. more geo-ecological studies at the meso-scale level will be possible. The study reported here demonstrates a methodology for examining unsophisticated field data and explains the systemic relationshlps in land use found in one mountain valley. The study area In Troll’s (1967) climatic ecologicat regionalization of the Himalaya-Hindukush. four types of cultivation systems were proposed. The westernmost agricultural type characterized by irrigation of all crops in small fields, was located in the Hindukush, Indus Himalaya, and Karakorarn mount~lins. The study area. the Kuh Daman Valley, lies in this region in the upper reaches of the Kabul River, a tributary of the Indus, north of the city of Kabul and south of the main Hindukush massif This entire area from the Indus gorge in Pakistan to Kabul, Afghanistan. is called Kohestan, meaning ‘land of mountains’. Precipitation is only 346 mm yr-‘: therefore, irrigation water obtained from the 5000-6000-m-high mountain snowfields and glaciers is essential for agriculture. This location in an intermontane valley has a climate characterized by very warm summers and foehn-like effects (katabatic winds) from the main Hindukush range to the north, while the high mountains all around prevent summer monsoon rain and cloud cover reaching this 25 km-wide and 70 km-long valley. Consequently. bright sunshine, warmth, and high radiation level are conducive to crop grotvth. As is typical of mountains in this area, no cadastral survey or land registration exists. making data on agricultural area and yield non-existent. The only tax paid on agricultural produce is a nominal fee on commodities sold at periodic markets and on fresh grapes which are exported from the valley. Characterizing the agricultural system in the valley is very difficult because of the circumstance which did not escape the many crops grown in Kuh Daman-a famous Russian agricultural scientist Vavilov many years ago (Vavilov and in the villages within the ten hlinor Civil Bukinich 1929). Croppin, 0 variation Divisions (MCD) of the valley (Fig. 2) is particularly noticeable (Table 1). For example, most villages in all ten MCDs grow wheat as a basic subsistence food crop yet maize is only grown by 50 per cent of the villages in five MCDs. All villages in two MCDs grow wheat, maize, and barley, but no potatoes are gron-n in these viltages. As local relief is slight in this intermontane valley and soil quality is relativeiy uniform, these cropping patterns are the product of unkno~vn factors. The cuitivators in this valley come from four different ethnic or tribal groups. with each one considering itself to be quite distinct from the others. The occupants of most villages are called Kuhestanis, which means, quite literally. mountaineers or highlanders. Two related tribes who have filtered into the area during the last few centuries are the Pakhtun-the well known Pathan-and the Pashtun. Aside from speaking a different dialect of the same language. Pashto. these tribes have had different traditional occupations. Pakhtun are sedentary cultivators concentrated in the Indus watershed and Pashtun are former nomads from the middle and lower Indus river plains and adjacent Pakistan. A fourth group, Safi. declare themselves to be quite different from the others. but there is evidence to suggest that they are Kuhestanis who are the most recent converts from paganism to Islam (Markham 1879; Jettmar 1975; Wutt 1981). Because of the absence of census data, estimates on the number of inhabitants vary widely from 150 000 to 200 000 (Allan 1978). Other than grape or raisin production, agriculture is of a subsistence nature

16

Human

geo-ecological

interactions

in a South Asian

valley

KARUL K4LAKAI

Figure 2. Kabul Kohestan,

KOHESTAN M,rnlC,..,D,..,,on*o

Afghanistan.

with small amounts of surplus perishable produce, principally vegetables and fruits sold in the several small periodic bazaars located in some of the villages. Despite the relative proximity of Kabul, many villages in the southern section of the valley reported only occasional trips to this city. The purchase of petty bazaar goods such as cloth, mirrors and nostrums, was given as the prime reason for these trips outside of the valley. Fieldwork and herding of cows, sheep, and goats occupied the bulk of the villagers’ time. Occasionally some attempt was made at planting wheat or barley on lalmi or unirrigated land, in the hope that sporadic summer rainfall would permit additional grain production. Irrigation water was allocated according to traditional rights from small rivers, streams, irrigation canals and leats. Methods An examination of an unpublished United Organization agricultural census originally taken have highly varied cropping in sample villages. associated with the number of irrigation water (United Nations Special Fund 1968). Later field that cultivators attributed this cropping pattern

Nations Food and Agriculture in 1967 showed Kuh Daman to This variation was thought to be sources available to the villages inquiries by the author indicated to food preferences by different

Nipi J.R. AlIan Table 1.

Crop

Bagram

Percentage of villages growing crops in Kuh Daman MCDs

Charikar

Jabai OS Saraj Qarabagh

ShakarDara

Rice Maize Wheat Barley Chickpea Horsebean Cowpea Kidneybean Greenbean Blackgram Potato Onion Garlic Turnip Cottoll Squash Tomato Eggpkltlt Wenna Gape Apple Pear Apricot Cherry Plum Almond Walnut Melon Swcetmclon Mulberry Fodder

29 96 46 u 15 0 38 8 4 2 2 0 0 35 0 0 2 0 88 0 0 8 0 0 0 0 23 29 60 96

9 52 100 76 3 -is 6 36 30 6 18 39 6 3 82 9 3 27 0 9-l 36 0 1X 6 3 9 Y 0 3 82 91

20 15 15 72 l-l 52 0 66 43 1 6 36 20 0 73 0 13 15 0 II 8 0 18 0 1 7 0 16 31 72 79

0 4 92 18 29 1 0 8 I4 0 6’: 0 4 4 0 6 55 0 92 12 0 10 0 2 0 10 29 29 92 0

21 57 100 57 29 79 0 0 0 68 57 36 1 18 0 10 7 1 0 79 36 7 18 0 0 0 1s 0 U 82 96

No. of villages in MCD

52

33

85

19

2s

0

17

Estalef

Kalakan 0

Slir Bacha Kut

0 0 I8 37 15 7 0 7 -I 67 0 0 81 0

52 85 19 0 9 ll 9 0 0 2-l 23 0 0 0 0 0 9 U IS 0 0 0 I) 0 0 0 u 0 l-t 0

4 36 96 32 ‘4 20 U 48 32 0 72 SD 0 4 0 4 0 40 0 1Oil 20 0 70 0 20 -I 16 0 0 9’7 6.4

37

21

25

0 l-l SY

xl 1 l-1

0 33 0 0 11 1

0 2h 0 0 1

Kuhrstan 40

Mahmud Eraqi

Kuh Daman valley

100 loo 0 0 loo 100 0 0 0 50 0 0 100 0 0 25 75 75 I UO 0 U 0 0 0 0 0 0 75 U

100 loo 100 1UU U 36 16 20 U 0 U 96 0 0 100 U U 96 U 0 2U 0 .tO 1U 0 0 U St) IU iuct u

28 ho 91 60 6 31 12 IO 16 6 15 4-l

JO

50

410

IOU

: 48 1 i 30 7 54 24 1 I5 3 2 3 s 1Y If? 72 46

tribes. Using the old FAO Agricultural Census as a roster of villages in the valley, a master list of all possible crops in Kuh Daman was established and visits were made to 360 of 410 villages in the valley, where the presence or absence of each crop on this list was recorded. Villages not surveyed by the author had their crops verified by the village headmen and these data were integrated into the 410 x 31 village crop data matrix (Ailan 1978). Village location and tribal affiliation were recorded on I:50 000 maps. Because of the close proximity of many villages and the rapidity with which the dichotomous cropping data could be obtained, all villages were surveyed, thereby fulfilling an objective of the field research that all possible variatton in cropping habits be encompassed in the meso-scale field survey. Crops found growing in fewer than five villages were eliminated from the analysis. Thirty-one crops were found to be growing in the valley. As the variance in village cropping habits was thought to be associated with complementary agronomic conditions, a factorial ecology was performed on the data set. All the dichotomous cropping data (i.e. presence or absence) were transformed into coefficients prior to submission as input data for the R-mode factor analysis. Other similar agricultural studies have used agricultural and yield data as a primary data set (Weaver 1944; Murdock 1960; Bennett 1961; Coppock 1964; Rutherford 1966; Gould and Sparks 1969; Barker 1976; Ilbery I9Sl), and one successful study on a

18

Human

geo-ecological

interactions

in a South Asian

valle?

Caribbean island used dichotomous data from sample sites of agricultural activity (Henshall and King 1966). An initial &factor solution was obtained. Using the ‘rule of thumb’ in evaluating each factor which accounts for a sufficiently high proportion of the variance (at least five per cent), it was found that a four-factor solution would afford greater resolution of the underlying dimensions. The high crop loadings of the four factors are shown in Table 2. To satisfy Troll’s proviso that geo-ecology include a regional or geographic dimension. the factor scores for all 410 villages on each of the four factors were obtained. These factor scores were broken down into classes based on positive and negative standard deviations from the mean and plotted on Kuh Daman maps (Figs 3, 4, 5, and 6). The hollow and solid circles in the maps represent high negative and positive values, with the small solid dots showing the median range of a village’s relationship with the four factors.

II

,-, JI

0 -1.9 --9.5 0 -9.5 -0 * 0 -.95 l

l

.95 -1.9 1.9-3.8

Figure 3. Village scores on Factor I.

ooom

Niger J.R. Allan Table 2. Crop factor Factor I Heavily irrigated field crops Cowpea Henna Apple Rice Cotton

Factor II Lightly irrigated field crops

O.S6 0.s-l 0.63 0.56 oxi

Horsebean Maize Barley Cotton Fodder Kidneybean Greengram

0.61 0.59 0.57 0.56 0.5-t 0.13 O.-t3

loadings Factor III Southern sustenance

Potato Blackgram Apple Chickpea Turnip

1 _.

0 -1.8

-

--.9

- o-.9 l

Factor IV Horticulture 0.66 0.37 0.35 0.33 0.33

0 -.9-o

l

19

.9 - 1.8 1.8 - 2.73

Figure 4. Village scores on Factor II.

Eggplant Onion Rice

0.80 0.61 0.50

20

Human

geo-ecological

interactions

0 -1.6

--.87

0 -.88

- 0

in a South Asian

valley

- O-.8 l

.9 -1.7

.

1.8 - 3.1

Figure 5. Village scores on Factor III.

Crop ecology Distinctive cropping patterns in Factor I appeared in the northeastern corner of the valley where cowpeas, rice, and cotton highlighted field cropping. Field observations verified the presence of espaliered apple trees along the southern sides of dwellings, and henna was grown and processed as beard dye and for use as a nostrum. A rather inferior type of cotton was grown and processed by hand in a cottage industry. Because these villages were located close to the perennial Panjhir river, this crop comp!ex was assumed to be associated with water supply. Factor II had high values in villages across the river from the location of prominent Factor I villages. Once again pulses, horsebean, kidney bean, and greengram were prominent. Two cereals, maize and barley, both requiring less water than rice, appeared. Cotton and fodder for livestock emerges. Since many of these villages

Niger J. R. Allan

21

o -.9-o -0-9 l

.9 - 1.8

l

1.8-2

Figure 6. Village scores on Factor IV.

loading high on Factor II were located at some distance from the river, this factor was labelled Lightly Irrigated Field Crops. Southern valley villages dominated Factor III with potato replacing the cereals which were prominent in the nothern villages, supplemented by other pulses, this time chick pea and black gram. Even less water is required for these crops. Most of the potatoes were grown in garden plots. The subsistence nature of these crops suggested that this dimension be labelled Southern Sustenance. Factor IV (Fig. 6) had rice supplemented by two vegetables, onion and eggplant. The latter is associated with the paufiz crop, which includes melons and cucurbits. This factor, characterized by Horticulture, dominated a northeast location but was also distributed throughout the valley central portion. The factorial ecology confirmed the earlier, subjective hypothesis that Kuh Daman crop ecology exhibited great regional diversify. High values of three factors

22

Human geo-ecological

interaction.s itI LISord _&inn rulley

dominated northern villages which were in close proximity to assumed superior access to water supplies, and southern villages, further removed from perennial water, were dominated by garden crops. Irrigation

After eliciting the distinctive regional crop ecologies in the valley, the next logical step was to probe for a possible relationship between distinctive crop ecologies and access to water supplies. The earlier FAO survey had been concerned with irrigation and had enumerated the number and type of water supply sources to each village. Water sources were of two types: h-e.2 were artificial water sources obtained from subterranean aqueducts, and the natural water sources consisted of intermittent and perennial streams and irrigation leats and canals, which dominated field supplies. Because the crop ecologies were presumed to be associated with irrigation supply, this relationship ought to be reflected in the villages with high factor scores on the supposed irrigation dimensions. Visual inspection of the histograms of factor scores does not confirm this assumption (Fig. 7). The factor scores which load high on the irrigated field crops (Factors I and II) should be positively skewed to reflect their access to one or two natural water sources. In fact they exhibit a normal distribution. Of the twelve histograms presented. only one might suggest that accessibility to water sources is implicated in crop distributions: on Factor II the percentage of villages with no natural water sources has a negatively skewed distribution. Given the simplicity of the available data, the relationship between village cropping and access to water could not be confirmed. FACTOR

FACTOR

I

II

FACTOR

III

FACTOR

IV

!,i ~~~~ -2

0

+2

Factor Score

Figure 7. Frequency

-2

0

+2

Factor Score

distribution

Factor Score

Factor Score

of villages’ natural water sources on villages’ factor scores.

Tribal cropping

Integrating cultural variables into mountain geo-ecological

research in this Muslim

Nigel J. R. Allan

23

area is fraught with difficulties.

Unlike Bishop’s study (f978) in Hindu-Buddhist western Nepal where cultivators were forthcoming with social information, cultivators are reluctant to divulge personal information in the Indus HimalayaHindukush. Reasons for this reticence include the typical mountaineer xenophobia of city dwellers and foreigners, a reluctance to disclose information on agricultural production because it could lead to land registration and taxation, and a desire to preserve Islamic values, especially as they relate to the household. Notwithstanding these difficulties, the tribal affiliation of all villages was obtained, thereby adding a social dimension to the geo-ecological information obtained in the field survey. Cropping habits of tribal villages demonstrate a marked preference for some crops over others (Table 3). Consequently, the third step in investigating the systemic Table 3. Percentage of ethnic villages growing crops Crop Rice Maize Wheat Barley Chickpea

Horsebean COWp~a

Kidneybean Greengram Blackgram Potato Onion Garlic Turnip Cotton Squash Tomato Eggplant Henna Grapes Apple Pear Apricot Cherry Plum Almond Walnut Melon Sweetmefon Mulberry Fodder

Kuhestani

Pathan

22 _-

7

:; 57 6 63 15

;: 33 3 9 3 23 0 7 27

44 17 6 17 59 5 4 46

2 28 2 12

;: 13 10 0 3 27 0 50 20 3 20

3 3 10 7 12 68 50

30 3 23 17 13 70 23

: 22

Safi 74 97 97 95 2 20 8 48 21 0 5 27 8 0 98 0 5 68 0 3 16 0 27 16 0 3 0 68 26 92 35

Pashtun 16 42 100 44 14 7 0 14 8 11 14 7 0 0 17 3 0 28 0 72 11 0 11 0 3 0 0 :: 72 60

relationships in village cropping patterns was accomplished by computing measures of association between tribes and crops. This was achieved by employing a coefficient of association for dichotomous variables, Yule’s Q, which has the required properties for three variable analysis (Goodman 1965). It has a very intuitive interpretation in that it is the number of concordant pairs (P) minus the number of discordant pairs (Q) divided by the total number of united pairs (P-f-Q},

24

Human geo-ecological interacrions in a South .&km valley

i.e., Yule’s Q==P--Q/p+Q. This form of contingency table analysis is idea! for examining relationships between tribal villages and the crops grown in them. So-called zero-order Yule’s Q simply measures the relationship between two variables, and a partial-order Yule’s Q refers to three-variable analysis controlling for one or more variables. The utility and geographical application of this technique (Johnston 1971; Mercer 1975) is discussed in a monograph by Davidson (1976). Yule’s Q is analogous to the commonest correlation measure, Pearson’s product moment coefficient for interval data. As ail tribal villages did not grow the same set of crops the analysis is limited to tribes which grew identical cereals and complementary crops. Cereals and pulses (peas and beans) are the major components in the diets of Kuh Daman villagers. Cropping patterns could reflect Dr Johnson’s opinion about oats, ‘a grain, which in England is generally given to horses, but in Scotland supports the people’: that is, food preferences can influence cropping patterns. During the field survey vilfagers voiced opinions on good foods (i.e.. status foods such as rice, and poor man’s foods like barley). The Safi tribe assert that their name is derived from Snf=(Pashto) pure, that they are the elite of tribes and prefer to eat and cultivate the ‘best’ cereal, rice. This is, indeed, evident as there is a high positive measure between Safi tribal villages and rice growing, since Q=O.S3. To test whether this is a true or spurious relationship, a third variable, horsebean, was inserted into the comparison. A partial-order &=0.89 was obtained thereby sustaining the initial observation that Safi tribal villages were correlated with rice cultivation. In Factor IV the variation in eggplant cultivation covaried with rice. When eggplant as the control variable is introduced into the Safi-rice pairing the strength of the relationship is slightly diluted as partial-order Q=0.67. Nevertheless, the association of Safi tribal villages with rice, horsebean. and eggplant growing is strong and it can be assumed that geo-ecological systemic relationships exist between these components. (Micro-scale field research at the village and field level could at this point proceed to elicit causal links between agronomic and human variables.) Pejorative statements (of the same genre as Dr Johnson’s remarks) are made by the elitist Safi that Kuhestani, the ‘wild mountaineers’. lack sufficient skills to grow rice. There is indeed a negative relationship between Kuhestani and rice, Q=-0.37, but this becomes weaker when the control variable of eggplant (also used in the Safi comparison) was introduced, as Q=O*Ol, thereby demonstrating that the negative association disappears. The variation in eggplant explains the existence of the Kuhestani-rice relationship. Hence Factor IV crops, rice and eggplant, co-vary with Safi tribaf villages, and can be regarded as part of a tribal crop complex. When another p&se, horsebean, is introduced in a Kuhestani-maize pairing, the association becomes weaker as zero-order Q=-0.20 changed to partial-order QzO.16. This suggests that, unlike the Safi village cropping relationships, there are no demonstrated links between Kuhestani villages and components of Factor II, maize and horsebean; however, these two crops are linked as the factorial ecology indicated. In evaluating these associations between tribes and the crops grown in their villages, it is useful to heed Uhlig’s (1978: 527) observation that crop growing ‘under drier cIimatic-ecoIogica~ conditions enforces irrigation for ail kinds of permanent agricultural activity’. Given this latitude in choice of irrigated crop growing, it follows that geo-ecological physical controls may dominate a cropping system based on monoculture; for example, rice in rain-fed mountains of South and Southeast Asia, but in areas of irrigation agriculture there is a greater propensity

Nigel J. R. Allan

for choice to affect the cropping system. distinct preference for certain crops.

In the Kuh Daman

25

case. one tribe had a

Conclusion Geo-ecological research on the human-modified mountain landscape has demonstrated considerable variation in crop growing. Although it may appear that one crop dominates the agricultural landscape, other crops share spatial variance in similar climatic-ecological conditions. By sampling, or better still. obtaining rapidly collected unsophisticated field data from an entire population of settlements, the geographically idiosyncratic crop complexes can be revealed. A factorial ecology of crops as a descriptive method for defining cropping systems should be augmented by complementary data on meso-level agronomic conditions such as water availability, and social data which distinguish the varied nature of the local population. A comparison of the uniqueness of cropping systems with other criteria is necessary to generate hypotheses of causal links between the human and physical components in agriculture. Heretofore, studies of single villages or of a small group of villages have dominated mountain geo-ecological research. No estimates of their representativeness at the meso or macro (regional) scale is given in these studies. By eliciting meso-scale geographic variation, as demonstrated by the factorial ecology of Kuh Daman, and by relating this variation to available physical and human data. systemic relationships can be verified or rejected. This screening, or filtering method of meso-scale investigation, is a necessary precursor for further hypothesis testing which can then be executed in villages and fields, selected according to the geo-ecological criteria revealed in the meso-scale investigation. Acknowledgements Financial support for field research was underwritten by the American Institute Pakistan Studies, the National Geographic Society, and the US Office Education.

of of

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