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Population pressure in Pakistan
Geoforum, V0110, pp. 183-194,1979. Pergamon Press Ltd. Printed in Great Britain.
Population
Pressure in Pakistan
AKHTAR HUSIAN SIDDIQI ,* Terre Haute, U.S.A.
Abstract: This study attempts to determine the effective population-carrying capacity of land in Pakistan under the existing socio-economic system. Statistical analysis provides the structural framework in which agricultural activities influence the concentration of population in Pakistan. Regression techniques have been used to show which factors are significant in determining the pressure of population in the country, and to present area1 variations between the observed and predicted values of population density.
Taeuber argues that ‘population pressure’ is a simple phrase to be used descriptively when density of settlement occurs alongside economic and social deprivation, but the definition of pressure as a demographic variable is difficult (TAEBUR, 1970). Since population is in part a reflection of the social and physical environment, population pressure may be defined meaningfully in the context of national the organization of society, the resources, methods of production, the standard of living and many other variables that provide logical structuring of man-land-resources relationships (STEEL, 1972). Population pressure also indicated existing and changing relationships of population and resources, and reflects an aspect of the process that may be called modernization (UNITED NATIONS, 1953). Thus, population pressure is a more specific concept than underpopulation, overpopulation or optimum population. In the light of the above statements, the aim of the present study is to determine the effective populationcarrying capacity of land in Pakistan under the country’s existing socio-economic system.
of population densities and distribution may find meaningful expression in the and ‘underconcepts of ‘overpopulation’ population’ based on socio-economic factors as well as the number of people per unit of land area. Although it seems logical to use population densities as the basis for deteroptimum population, economists’ mining efforts to generate a scientifically acceptable theory of optimum population have met with little success (BROWNING, 1970; SPENGLER, 1969). Estimates
There is little doubt that the approach to establishing optimum population size relative to resources is sound in principle. Also necessary is the determination of a desirable standard of living and the establishment of how many people can be maintained at that standard in a given area. This suggests that the size of the human population must be brought under rational control. Thus, the ideal of an optimum population size must be a dynamic one, in which changes in population size may be regulated in response to total human needs. It becomes evident that measurement of any such optimum in the developing countries is neither a practical nor a feasible proposition. In view of such difficulties, the densities and distribution of population, especially in relation to resources, may be referred to as population pressures. *Professor of Geography, Geology, Indiana State Indiana, U.S.A.
Department University,
The fundamental problem facing the developing countries is the rapidly increasing pressure of population on physical resources, especially on resources of land (STAMP, 1969). If population is measured against food needs and production, Pakistan already must be conssidered overpopulated. If Pakistan is to avoid some of the serious social problems that have already affected other developing countries, socio-economic planning must consider the nature of population problems as they vary
of GeographyTerre Haute,
183
184
Geoforum/Volume lo/Number 2/1979
from area to area and from one land occupancy type to another. Since a high proportion of people in Pakistan are dependent on agriculture, low agricultural productivity not only affects the country’s economic health, but also reduces the economic system’s effectiveness. The essential response to the problem should be to determine a more sustainable relationship between population and natural resources. Although continued activities aimed at limiting the rate of population growth are highly desirable, population policies must also consider the geographical distribution of people in order to limit excessively high concentrations in a few areas. Population
Growth
Rapid population growth has augmented Pakistan’s economic problems, which, in the past, were invariably attributed to such factors as physical disadvantages, social structure and disparities in land use. A crucial problem in recent years (195 1-1972) is that in Pakistan, as in other developing countries, it is becoming extremely difficult for economic growth to keep pace with the rate of population increase. Population data vary in character and quality in time and space, but the magnitude of change is clearly apparent. According to the census for 1901, the population of those areas that now constitute Pakistan was estimated at 16.6 million (RASHEED, 1961); the last census, taken in 1972, revealed that the total population of Pakistan had risen to 64.9 million (GOVERNMENT
OF PAKISTAN,
1972). The
census figures of 1901 and 1972 indicate that the population of Pakistan has quadrupled during the intervening 71 yr, recording a net increase of 291%. The rate of population growth for those areas now incorporated in Pakistan has varied substantially between 1901 and 1972. Between 1901 and 1921, the growth rate was slowest, partly because of high mortality rates due to widespread famines and the outbreak of epidemics in 1911 and 1921 over the Indian subcontinent. In the 1901-1921 period, these areas also recorded poor agricultural performance because of the lack of irrigation facilities over the large part of the region. The first great increase in the region’s population was observed during the 1930s and high popu-
lation growth has been recorded in Pakistan in each decade since then (Table 1). A closer look at the gross population change between 1901 and 1972 shows that about 79% of the net increase was added during the 19.5 l1972 period. The increase is the result of many factors, including better census coverage of the area during these decades. Between 1921 and 193 1, the provision of irrigation facilities and improvements in the traditional economic structure of the Punjab and Sind areas attracted the ‘unsettled’ population to sedentary agriculture and helped the settlement of the canalirrigated areas of the Indus Plain. After independence, most of the government’s efforts were concentrated on increasing the cropped area and irrigation facilities, resulting in high growth rates in cropping in the Indus Basin. Annual growth rates of agricultural production over the 196 1- 1970 period, indicate that the rate of expansion, which had stagnated in the early years, picked up considerably. The high growth rates in agricultural productivity are also the result of institutional changes, increased use of agricultural inputs and the extension of irrigation facilities during the 196 l-l 972 period. Since Pakistan’s economic structure is primarily based on agricultural production, the country is experiencing great population pressure in many agriculturally productive areas, and population gains are outstripping food surpluses. Table 2 shows a comparison of the net variations in population and cultivated area between 1961 and 1972. The data reveal that the population increased at a faster rate than the increase in cultivated acreage. Dry and upland areas have relatively limited physical resources, and further increase in the arable land in those areas will be costly. It seems essential that any further population growth in such areas must be supported by increasing the yield per acre. Rural Stagnation
A significant feature of Pakistan’s population is its primarily rural character. At the last census (1972), the rural population constituted 74% of the total. Over 48 million people were living in about 37,000 rural settelements. The size of the villages varied from 200 people to over 2000 people, but averaged about 900 in-
22.0
9.1
3.0
0.5
51.3
27.1
30.2
21.7
16.4
3.0
7.1
Net percentage change
3.5
2.4
1.8
1.9
1.1
0.8
1.6
Annual growth rate (%)*
86.8
36.9
Increase in gross national product over the previous date (%)
and economic variations (190 l-l 972)
*Pakistan: A demographic
report, Popul. Bull. 29 (4) 7.
Based on: Census of Pakistan, Vol. I, Pakistan Population, 1961, pp. 11-54-59; Population Census of Pakistan, 1972; 25 Years of Pakistan in Statistics; and Pakistan Survey, 1971-1972, Statistical section.
Computed by the author.
64.9
1972
7.8
1941
33.7
25.9
1931
42.9
21.3
1921
1951
18.3
1911
1961
4.6
17.8
1901 1.2
16.6
Year
Net total variation (million)
Total population (million)
Table 1. Population
53.6
21.3
Increase in agricultural production over previous date (%)
49.6
8.5
Increase in per capita income (%)
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Table 2. Percentage of the total area affected by the relative annual increases in population and cultivated land in Pakistan (1961-1972) Annual growth in cultivated land Annual growth in population
1.00
l.OO1.99
2.002.99
3.003.99
4.004.99
1.71
2.96
4.00-4.99
1.68
1.42
3.00-3.99
4.37
4.81
2.00-2.99
11.76
6.43
1.00-l .99
3.19
1 .oo
1.01
5.14
23.72
17.80
Total area (%) Source: Computed
2.66
7.007.99
8.00-
Loss
2.21
2.44
Total area (%)
6.88 5.16
3.62
2.76 1.46
4.61
3.61
13.36 3.42
18.98
13.14
37.40
7.34
14.14
3.09 6.27
5.53
9.24 6.58
2.76
1.46
2.21
9.77
23.90
100.00
by the author.
habitants. About 68% of the villages had between 500 and 1000 inhabitants and 69% of the total rural population, whereas about 5% of the villages had over 1500 people amounting to about 10% of the rural population, as shown in Table 3. One of the most crucial problems of Pakistan is that it is extremely difficult to force the rural economy to grow. Rural areas lack the basic facilities to utilize their resources. Only 68% of villages in Pakistan claimed a metalled road within 5 miles (GOVERNMENT OF PAKISTAN, 1971), although villages lying in the irrigated areas of the Indus Plain are relatively better served by roads. A very small percentage of the villages throughout Pakistan
Table 3. Rural population
200-500 501-1000 1000-1500 1501-2000 2001 and over
6.006.99
(%)
5 .oo-5.99
Village size (inhabitants)
% 5.005.99
by village size (1972)
Percentage of settlement
Percentage of rural population
13.22 68.26 13.86 3.77 0.89
6.35 68.60 15.17 7.40 2.48
is served by railways. Besides the lack of mobility, only a small percentage of rural areas have facilities such as grain markets and fertilizer depots. In the past, very little capital investment had been made in land development to improve the social and economic conditions of the rural population. Thus, rural stagnation has been due partly to the influence of the social structure and partly to lack of facilities and opportunities. Although seasonal agricultural labour migrations exist in many areas of Pakistan, they involve rural-rural migrants moving between neighboring villages and districts. In recent years, some migration has been generated by growing inter-regional differences in the rate of economic development. Since the development of commerce, trade and industrial plants have generated a new demand for labour in the growth centers of the country, and people have gone to those areas in search of employment or better social and economic opportunities. Otherwise immobility characterizes the rural population. Pakistan’s rural areas contrast greatly, and there are dangers in broad generalizations that treat the country as a whole. Keeping in mind the pluralistic social and economic character of the country, and also the economic back-
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187
wardness of many rural areas, Pakistan’s villages are characterized by subsistence living. Two components of this characteristic are the low income of villagers and the low level of productivity of village land. This low-income level does not necessarily indicate that the Pakistani villagers are starving, but it means that after providing for daily needs and meeting social obligations, the villagers have little left to ensure that their income will grow substantially. Density of Population
Pakistan’s population distribution and density exhibit complexity (Figure 1). Most sparsely populated are the arid and semi-arid areas of the uplands and the vast tracts of the Indus Basin, where unreliable rainfall deter dense human population. These areas show signs of over-cropping, over-stocking and soil erosion, and the average density of population is much lower than the national average. On the other hand, a large percentage of Pakistan’s total population is concentrated in the Indus Plain, and the average densities of population in these areas far exceed the national average. Thus, about 44% of the total population of Pakistan inhabits about 36% of the land area, occupying about 52% of the total arable land, whereas 7% of the total population lives on 40% of the land area, having 15% of the total arable land (Table 4). Table 4. Distribution
Population density per arable square mile 24,094
2276-1080 1060- 660 654- 534 502- 232 Unspecified Computed Source:
It becomes evident from the above discussion that in most cases density alone is not an important measure of population pressure. Much more crucial is the distribution of population in relation to available resources. Statistical
Analysis
Many variables affect population pressures on land. For practical purposes, however, it is necessary to limit the number of variables to be analysed. Using selected variables permits a better understanding of the problem and interpretation of the results. The variables used to explain the spatial distribution of population in Pakistan are: (a) population density per arable land unit, (b) ratio of irrigated land to total arable land, (c) mean annual temperature, (d) annual rainfall, (e) productivity of food grains per unit of arable land, (f) extension of irrigation, (g) changes in arable land and (h) population per unit of arable land. For statistical purposes some of these variable have been expressed in logarithmic form (a), (d) and (h). Since irrigated agriculture provides the indispensable economic resource-base in Pakistan, these variables are considered to be major determinants of population pressure on the land resources of the country. Since the resources and their productive function vary from area to area, the distri-
of population
and arable land
As percentage of the total area
As percentage of the total population
As percentage of the total arable land
0.4 14.5 18.4 17.8 40.3 8.6
5.5 34.4 23.9 19.6 7.7 8.9
0.2 22.8 28.2 24.1 15.0 9.7
Average density per square mile
Arable land per CQpitU (acre)
2623 497 272 229 41
0.02 0.37 0.66 0.68 1.10
by the author.
Population Census of Pakistan, 1972; Agricultural Statistics of Northwestern Frontier Province, 1945-1970; Development Statistics of Sind, 1972; and The Development Statistics of the ~njab , 1972.
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188
PAKISTAN POPULATION DENSITY 1972 PERSONS
PER
ARABLE
SQUARE
232-502 634-es6 680 - 1.caJ l.CXX.
2.276
24‘oM
Figure 1. Population
density.
MILE
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bution of population is expected to vary in approximately the same way. It is assumed that the pressure of population in Pakistan is directly influenced by the productiveness of agricultural land (the most important resource) and the prevailing climatic conditions. In order to test this model and, therefore, the hypothesis, it is necessary to estimate the manner in which each variable affects the density of population on arable land. Given such a set of data, it appeared that multivariate statistical analysis could provide some insight into the effective populationcarrying capacity of resources in Pakistan and the study presents two interrelated aspects of such an analysis. It was considered that the two statistical approaches selected could best provide output that would prove useful for those involved in population studies and determining man-land-resource relationships. Factor analysiswasusedtofocus the underlying causative processes that produce regional population pressure differentiation, as well as to identify the independent populationresource variables in the data. Stepwise multiple regression was used to study the relationship between the independent variables identified by the factor analysis and the population density per square miles of arable land as dependent variable. In completing the analysis a number of computer programs were used. Details are not given in this paper but, upon request, the author would be pleased to provide information concerning the programs used. Table 5.
density
4. Log rainfall 5. Productivity
The factor analysis has revealed that there appear to be three underlying factors as noted in Table 5. These factors accounted for 70.6% of the total variance in the original variables. Factor I accounted for 28.4% of the total variance. The associated variables with high loadings (+ 0.6 and above) were irrigated ratio (0.86), productivity of grains (0.73) and extension of irrigation (0.66). Inspection of the first factor loadings show that Factor I emerges as a general factor with high loadings related to use of technology and the related output of the arable land. Factors II and III were bipolar. Accounting for 24.5% of the total variance, the second factor showed change in population (0.91) at one pole and change in the productive land (-0.80) at the other. The explanation is that these two attributes are not in fact independent but may be thought of as two extreme situations, suggesting the possible existence of an underlying variable tending to act in opposite directions. Thus,
Rotated factor matrix h2
1. Log population 2. Irrigation ratio 3. Temperature
In order to fit the concept of population pressure into a spatial framework, it is necessary to explain the structure in which the above variables mutually associate. The factor analytic technique was used to account for the behaviour of the eight variables in terms of the relatively few basic dimensions related to population and resource-carrying capacity. The available program for general factor analysis was used to perform a principal component analysis and those orthogonal or uncorrelated factors with eigenvalues greater than unity were rotated to varimax solution.
0.77 0.78 0.62
Factor
Factor
-0.62 0.88 0.74
6. Change in productive land 7. Extension of irrigated land
0.71 0.44
0.66
8. Log change in population Percentage of variance Cumulative variance (%)
0.85
Computed
by the author.
Factor 0.64
0.78 of grains
II
0.86
0.70
Source:
I
-0.80
28.4 28.4
0.91 24.5 52.9
17.7 70.6
III
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190
the factor population productive
reveals that there is a tendency for to increase in areas where more land is available.
Finally, Factor III, which accounted for 17.1% of the total variance, projected the dimension of climatic conditions. Positive loadings are associated with the annual rainfall (0.88) and the density of population (0.64), whereas negative loading appears to be associated with mean temperature (-0.62). This factor appears to identify some aspect of the population density as associated with environmental conditions in Pakistan. Examination of the high positive scores of the factor identify the rainfall subsistence farming areas located in the north and north-western sections of Pakistan, whereas the high negative scores identify the areas (Trans-Indus Plain and the Plateau of Baluchistan) where, because the rainfall is light and erratic, cropping and pasturing are closely linked to flood water availability. Other groups reflect low rainfall areas of the Indus Plain, where irrigation has provided farmers with means to practice irrigated agriculture. In fact, a large concentration of population is found in these areas. In short, the factor analytic technique identified the closely related variables and partitioned the eight variables into three unrelated factors-namely organizational, transformational and environmental factors--providing a structural framework of population-resource relationships (Figure 2).
Figure 2. Structural
framework.
1O~Number 211979
Structural Framework It is increasingly recognized that technology and organization mediate between population and resources. Assuming that a farming system could be viewed as an organizational factor, the first factor (which identifies irrigated land, productivity of food grains and extension of irrigated land) is indicative of organization. The second factor, representing changes in population and productive land, may be considered a transformative factor and reflects the fundamental structural changes in resource use as well as in the social structure of the country. Another major means of adaptation, described by the third factor, is the seasonal character of Pakistan, which identifies basic relationships between climate and population distribution. Regression Analysis Since the general purpose of factor analysis is to find relationships between clusters of variables (variables sharing similar characteristics) in order to determine the structure of sets of independent variables, principal component analysis was repeated only on seven original variables, eliminating thevariable of population density from the analysis. This operation was undertaken to remove the effect of the variable on other variables, ensuring that the common underlying dimensions are extracted with clusters of related variables that are relatively independent of other clusters, as well as of density of population. An orthogonal varimax rotation again extracted three factors, keeping the same major dimensions, and explained 72.6% of the total variance. The slight alteration of the individual factor loadings did not disturb the measurement of the underlying dimensions of the structural framework identitied above. The statistical relationship between resource structure and population density was developed using regression analysis. The factor scores for the 45 districts of Pakistan derived in the factor analysis were used as independent variables. The logarithmic values of the density of population were fed as dependent variables into the analysis to measure the function. regression technique added one Stepwise variable at a time until the complete equation was finallycalibrated.The order of independent
191
Ceoforum/Volume 1O/Number 2/l 979
variables entered in the regression sequence explained their contribution to explanation of the remaining variance in the dependent variable. The order of factors entering the equation was transformation factor (Factor II), environmental factor (Factor III), and finally organizational factor (Factor I). These factors were added to the equation in an orderly way in accordance with their relative importance, explaining about 34% of the total variance in the density of population. The transformation factor (Factor II), associated with the changes in population and productive land, was the most important and explained about 16% of the total variance, whereas the environmental factor (Factor III) explained about 13% of the total variance. The organizational factor (Factor I) explained only 4% of the total variance. However, the contributions of the variable to the multiple R were not statistically significant (Table 6). In order to compute the residuals, stepwise procedure was terminated after the second and third factor, and the multiple regression equation with respect to population density
Table 6. Summary
Variable entered 1. Factor II 2. Factor III 3. Factor I
Transformational Environmental Organizational
in Pakistan
is, therefore,
log population 2.88940
density -
=
0.13382F2
+
0.12137F3
Thus, the existing economic framework in which population is found produced a correlation of 0.55, indicating that the generated resource structure can account for barely onethird of the variance in population density. The Patterns of Population
Pressure
The residual values derived from regression analysis for each district indicate how well regression predicts the population density per arable unit (as dependent variable) for that particular observation. The predicted values of population density for 45 districts were subtracted from the observed population densities. The resulting values were used to show area1 variation in the degree of fit of the regression equation. Thus, the distribution of positive residuals (districts where density is greater than expected) and distribution of negative residuals (districts where density is less than expected) show spatial differences.
of a stepwise multiple
r
0.404 0.367 0.204
0.404 0.546 0.583
correlation
analysis
R2
Increase inR2
F-value
0.163 0.298 0.340
0.163 0.235 0.042
8.595* 8.248* 2.644t
Based on Step 2: Coefficient 2.88946 -0.13382 0.12147
Variable Constant Factor II Factor III Multiple R Std. error of est. Regression Residual
0.5459 0.2837 Df 2 43
Source: Computed by the author. *Significant on the 99% level. +Not significant.
Sum of squares 1.470 3.462
St. errors 0.0423 0.0423
Mean squares 0.735 0.08 1
F-ratio 9.129*
192
As shown in Figure 3, small residuals reflect very close correspondence between the actual and predicted values. These findings predominate in the districts of Jhelum, Gujrat, and Sialkot in the northern section of the upper Indus Basin, and Nawabshah and Hyderabad in the lower Indus Valley. The actual density of population in these cases was found closest to the predicted values of the model, exhibiting a best fit of the representation of the relationship between the carrying capacity of land and the degree of concentration of population.
Geoforum/Volume 1O/Number 2/l 979
occurred from the cultivation of low-yield cereals to that of high-yield food crops, such as wheat, rice and sugar cane. The well-irrigated sections of Pakistan are supporting more people because of the quality of their soils and the.practice of suitable types of farming. Thus, there is a definite tendency for districts with deviations from the norm to cluster spatially. Postive deviations tend to cluster in irrigated tracts, and negative deviations in dry and mountainous sections. Conclusion
(i) Areas of Low Population Pressure Large areas in the northwestern and western sections of Pakistan have negative residuals, where actual densities are less than the predicted values. Small areas in the eastern and south-eastern sections of the country also show this trend. It is clear from these negative residuals that districts are distinctly grouped according to the poor population-carrying capacities of their agricultural land. These areas have the least arable land, and are devoid of irrigation or have barani (rain-fed) land. In these districts, yields of food crops remained at low levels, because fertilizer and improved seeds are not used. In the sparsely inhabited or completely uninhabited areas, very little effort has been made to increase the potential for food production, and innovations have not been introduced. (ii) Areas of High Population Pressure In the central sections of the Indus Plain, high positive residuals occur. Very high positive residuals in the districts of Karachi, Lahore, Lyallpur, Peshawar and Rawalpindi reflect urbanization. High positive values also tend to occur in districts that are relatively industrialized or have developed commercial agriculture. The mapping of the positive residuals supports the concept that the magnitude of the population concentration in the upper and lower Indus Plains, where canal and tube well irrigation is intensively used, is positively associated with an increase in land use intensity and the extension of irrigation facilities. In recent years, some of these areas have shown remarkable increases in food production through the use of fertilizer and improved seeds. In many of these districts, a shift has
The study evaluates population pressure in terms of the carrying capacity of agricultural land, as well as an overall population-resource relationship within a conceptual framework. It also suggests that national planning agencies take a population-oriented policy making approach in devising regional development plans for the country. Statistical analysis illustrates the structural framework in which agriculture operates and the ways in which it influences the distribution and concentration of population in Pakistan. The regression model identifies the spatial patterns of the population-carrying capacity of the country’s agricultural land, considering resources in the context of population changes. The predicted values of population densities may provide a rationale for the consideration of regional development plans capable of attracting and absorbing additional population, which is already stagnating in the overpopulated parts of Pakistan. Mapping of residuals reveals a clear relationship between the existing socio-economic structure and the patterns of population pressure in Pakistan. The residuals also indicate that the population pressure is positively related to the agricultural development process. Districts located in the well-irrigated tracts with relatively better agricultural practices and diversified economic structure reflect positive values, indicating underprediction. It follows that in these areas, factors other than the independent variables influence the dependent variable. On the other hand, the districts with lesser agricultural resource development show indicating overprediction. negative results, These negative residuals suggest that in these
Geoforum/Volume
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211979
18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
PAKISTAN POPULATION (BASED
ON
TWE
PRESSURE
REGRESSION
ANALYSIS)
1972 RESIDUAL
VALUES
Ly
2 t
-
P
120
- 0.w
.0?6! - 0418 On0
LOW
- -0223
ACTUAL
- -1076
LOW
w ->
-0465
s
- 27c3 _- 434,
s
IilGH
1373 _ ml.47
CLOSEST
TO
-X?l!S--19Q3 4-llGt-I
Figure 3. Population
pressure.
PREDICTED
Geoforum/Volume
194
areas the population is distributed in such a way that there are less resources available for supporting this population. The significant problem that stands in the way of agricultural development in these areas is the lack of an irrigation system to supply the needed water throughout the year. Pakistan’s agriculture has been-and to a large extent still is-dependent on weather conditions. These areas badly need effective irrigation projects. Although the cultivation of upland river valleys and adoption of improved farming methods have created patterns of settlement (in Quetta and Peshawar districts, for example), sparsely populated areas lack resources to support the population. In these areas population shifts may be encouraged either by improving agricultrual practices or developing new economic opportunities through exploitation of mineral and/or other natural resources. The correlation between density of population and organizational factors was disappointingly low (r value of 0.20), indicating that, in an overall sense, the organizational factor is not strongly related to the population density. Such a correlation is not inconsistent with our analysis of residuals. In short, it can be confirmed that a multivariate relation in which population pressure is found in Pakistan largely depends on the changes in population and agricultural inputs and environmental factors. Moreover, each district has a
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position on a development scale representing a continuum of ‘good’ to ‘bad’. References BROWNING
H. L. (1970) Some biological
consider-
ation of population pressure on resources, In:
Geography and A Crowding World, W. Zelinsky, A. Kosinski and R. H. Prothero (Eds.). Oxford University Press, New York, pp. 71-82. GOVERNMENT OF PAKISTAN, AGRICULTURAL CENSUS ORGANIZATION (197 1) Second Pakistan Census of Agriculture, Vol. III, pt. II, Village Statistics, Lahore. GOVERNMENT OF PAKISTAN, CENSUS ORGANIZATION (1973) Population Census of Pakistan, 1972. Census Bulletin No. 1, Islambad. RASHEED, (1961) Census of Pakistan Population, Vol. I. TableandReports, Government of Pakistan, Karachi, pp. 1 l-54. STAMP L. D. (1969) Land for Tomorrow: Our Developing World, Indiana University Press, Bloomington. STEEL R. W. (1970) Population pressure in tropical Africa Trans. Inst. Br. Geogr. 49, l-14. SPENGLER J. J. (1967) Population optima, In: The 99th Hour, E. 0. Price (Ed.). Chapel Hill, N. C. pp. 29-50. TAEBUR IRENE B. (1970) Population dynamics and population pressures: geographic-demographic approaches, In: Geography and a Crowding World, W. Zelinsky, L. A. Kosinski and R. M. Prothero (Eds.). Oxford University Press, New York. UNITED NATIONS, POPULATION DIVISION (1953) The determinants and consequences of population trends, Popul. Stud. 17.
Population
Pressure in Pakistan
AKHTAR HUSIAN SIDDIQI ,* Terre Haute, U.S.A.
Abstract: This study attempts to determine the effective population-carrying capacity of land in Pakistan under the existing socio-economic system. Statistical analysis provides the structural framework in which agricultural activities influence the concentration of population in Pakistan. Regression techniques have been used to show which factors are significant in determining the pressure of population in the country, and to present area1 variations between the observed and predicted values of population density.
Taeuber argues that ‘population pressure’ is a simple phrase to be used descriptively when density of settlement occurs alongside economic and social deprivation, but the definition of pressure as a demographic variable is difficult (TAEBUR, 1970). Since population is in part a reflection of the social and physical environment, population pressure may be defined meaningfully in the context of national the organization of society, the resources, methods of production, the standard of living and many other variables that provide logical structuring of man-land-resources relationships (STEEL, 1972). Population pressure also indicated existing and changing relationships of population and resources, and reflects an aspect of the process that may be called modernization (UNITED NATIONS, 1953). Thus, population pressure is a more specific concept than underpopulation, overpopulation or optimum population. In the light of the above statements, the aim of the present study is to determine the effective populationcarrying capacity of land in Pakistan under the country’s existing socio-economic system.
of population densities and distribution may find meaningful expression in the and ‘underconcepts of ‘overpopulation’ population’ based on socio-economic factors as well as the number of people per unit of land area. Although it seems logical to use population densities as the basis for deteroptimum population, economists’ mining efforts to generate a scientifically acceptable theory of optimum population have met with little success (BROWNING, 1970; SPENGLER, 1969). Estimates
There is little doubt that the approach to establishing optimum population size relative to resources is sound in principle. Also necessary is the determination of a desirable standard of living and the establishment of how many people can be maintained at that standard in a given area. This suggests that the size of the human population must be brought under rational control. Thus, the ideal of an optimum population size must be a dynamic one, in which changes in population size may be regulated in response to total human needs. It becomes evident that measurement of any such optimum in the developing countries is neither a practical nor a feasible proposition. In view of such difficulties, the densities and distribution of population, especially in relation to resources, may be referred to as population pressures. *Professor of Geography, Geology, Indiana State Indiana, U.S.A.
Department University,
The fundamental problem facing the developing countries is the rapidly increasing pressure of population on physical resources, especially on resources of land (STAMP, 1969). If population is measured against food needs and production, Pakistan already must be conssidered overpopulated. If Pakistan is to avoid some of the serious social problems that have already affected other developing countries, socio-economic planning must consider the nature of population problems as they vary
of GeographyTerre Haute,
183
184
Geoforum/Volume lo/Number 2/1979
from area to area and from one land occupancy type to another. Since a high proportion of people in Pakistan are dependent on agriculture, low agricultural productivity not only affects the country’s economic health, but also reduces the economic system’s effectiveness. The essential response to the problem should be to determine a more sustainable relationship between population and natural resources. Although continued activities aimed at limiting the rate of population growth are highly desirable, population policies must also consider the geographical distribution of people in order to limit excessively high concentrations in a few areas. Population
Growth
Rapid population growth has augmented Pakistan’s economic problems, which, in the past, were invariably attributed to such factors as physical disadvantages, social structure and disparities in land use. A crucial problem in recent years (195 1-1972) is that in Pakistan, as in other developing countries, it is becoming extremely difficult for economic growth to keep pace with the rate of population increase. Population data vary in character and quality in time and space, but the magnitude of change is clearly apparent. According to the census for 1901, the population of those areas that now constitute Pakistan was estimated at 16.6 million (RASHEED, 1961); the last census, taken in 1972, revealed that the total population of Pakistan had risen to 64.9 million (GOVERNMENT
OF PAKISTAN,
1972). The
census figures of 1901 and 1972 indicate that the population of Pakistan has quadrupled during the intervening 71 yr, recording a net increase of 291%. The rate of population growth for those areas now incorporated in Pakistan has varied substantially between 1901 and 1972. Between 1901 and 1921, the growth rate was slowest, partly because of high mortality rates due to widespread famines and the outbreak of epidemics in 1911 and 1921 over the Indian subcontinent. In the 1901-1921 period, these areas also recorded poor agricultural performance because of the lack of irrigation facilities over the large part of the region. The first great increase in the region’s population was observed during the 1930s and high popu-
lation growth has been recorded in Pakistan in each decade since then (Table 1). A closer look at the gross population change between 1901 and 1972 shows that about 79% of the net increase was added during the 19.5 l1972 period. The increase is the result of many factors, including better census coverage of the area during these decades. Between 1921 and 193 1, the provision of irrigation facilities and improvements in the traditional economic structure of the Punjab and Sind areas attracted the ‘unsettled’ population to sedentary agriculture and helped the settlement of the canalirrigated areas of the Indus Plain. After independence, most of the government’s efforts were concentrated on increasing the cropped area and irrigation facilities, resulting in high growth rates in cropping in the Indus Basin. Annual growth rates of agricultural production over the 196 1- 1970 period, indicate that the rate of expansion, which had stagnated in the early years, picked up considerably. The high growth rates in agricultural productivity are also the result of institutional changes, increased use of agricultural inputs and the extension of irrigation facilities during the 196 l-l 972 period. Since Pakistan’s economic structure is primarily based on agricultural production, the country is experiencing great population pressure in many agriculturally productive areas, and population gains are outstripping food surpluses. Table 2 shows a comparison of the net variations in population and cultivated area between 1961 and 1972. The data reveal that the population increased at a faster rate than the increase in cultivated acreage. Dry and upland areas have relatively limited physical resources, and further increase in the arable land in those areas will be costly. It seems essential that any further population growth in such areas must be supported by increasing the yield per acre. Rural Stagnation
A significant feature of Pakistan’s population is its primarily rural character. At the last census (1972), the rural population constituted 74% of the total. Over 48 million people were living in about 37,000 rural settelements. The size of the villages varied from 200 people to over 2000 people, but averaged about 900 in-
22.0
9.1
3.0
0.5
51.3
27.1
30.2
21.7
16.4
3.0
7.1
Net percentage change
3.5
2.4
1.8
1.9
1.1
0.8
1.6
Annual growth rate (%)*
86.8
36.9
Increase in gross national product over the previous date (%)
and economic variations (190 l-l 972)
*Pakistan: A demographic
report, Popul. Bull. 29 (4) 7.
Based on: Census of Pakistan, Vol. I, Pakistan Population, 1961, pp. 11-54-59; Population Census of Pakistan, 1972; 25 Years of Pakistan in Statistics; and Pakistan Survey, 1971-1972, Statistical section.
Computed by the author.
64.9
1972
7.8
1941
33.7
25.9
1931
42.9
21.3
1921
1951
18.3
1911
1961
4.6
17.8
1901 1.2
16.6
Year
Net total variation (million)
Total population (million)
Table 1. Population
53.6
21.3
Increase in agricultural production over previous date (%)
49.6
8.5
Increase in per capita income (%)
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Table 2. Percentage of the total area affected by the relative annual increases in population and cultivated land in Pakistan (1961-1972) Annual growth in cultivated land Annual growth in population
1.00
l.OO1.99
2.002.99
3.003.99
4.004.99
1.71
2.96
4.00-4.99
1.68
1.42
3.00-3.99
4.37
4.81
2.00-2.99
11.76
6.43
1.00-l .99
3.19
1 .oo
1.01
5.14
23.72
17.80
Total area (%) Source: Computed
2.66
7.007.99
8.00-
Loss
2.21
2.44
Total area (%)
6.88 5.16
3.62
2.76 1.46
4.61
3.61
13.36 3.42
18.98
13.14
37.40
7.34
14.14
3.09 6.27
5.53
9.24 6.58
2.76
1.46
2.21
9.77
23.90
100.00
by the author.
habitants. About 68% of the villages had between 500 and 1000 inhabitants and 69% of the total rural population, whereas about 5% of the villages had over 1500 people amounting to about 10% of the rural population, as shown in Table 3. One of the most crucial problems of Pakistan is that it is extremely difficult to force the rural economy to grow. Rural areas lack the basic facilities to utilize their resources. Only 68% of villages in Pakistan claimed a metalled road within 5 miles (GOVERNMENT OF PAKISTAN, 1971), although villages lying in the irrigated areas of the Indus Plain are relatively better served by roads. A very small percentage of the villages throughout Pakistan
Table 3. Rural population
200-500 501-1000 1000-1500 1501-2000 2001 and over
6.006.99
(%)
5 .oo-5.99
Village size (inhabitants)
% 5.005.99
by village size (1972)
Percentage of settlement
Percentage of rural population
13.22 68.26 13.86 3.77 0.89
6.35 68.60 15.17 7.40 2.48
is served by railways. Besides the lack of mobility, only a small percentage of rural areas have facilities such as grain markets and fertilizer depots. In the past, very little capital investment had been made in land development to improve the social and economic conditions of the rural population. Thus, rural stagnation has been due partly to the influence of the social structure and partly to lack of facilities and opportunities. Although seasonal agricultural labour migrations exist in many areas of Pakistan, they involve rural-rural migrants moving between neighboring villages and districts. In recent years, some migration has been generated by growing inter-regional differences in the rate of economic development. Since the development of commerce, trade and industrial plants have generated a new demand for labour in the growth centers of the country, and people have gone to those areas in search of employment or better social and economic opportunities. Otherwise immobility characterizes the rural population. Pakistan’s rural areas contrast greatly, and there are dangers in broad generalizations that treat the country as a whole. Keeping in mind the pluralistic social and economic character of the country, and also the economic back-
1O/Number211979
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187
wardness of many rural areas, Pakistan’s villages are characterized by subsistence living. Two components of this characteristic are the low income of villagers and the low level of productivity of village land. This low-income level does not necessarily indicate that the Pakistani villagers are starving, but it means that after providing for daily needs and meeting social obligations, the villagers have little left to ensure that their income will grow substantially. Density of Population
Pakistan’s population distribution and density exhibit complexity (Figure 1). Most sparsely populated are the arid and semi-arid areas of the uplands and the vast tracts of the Indus Basin, where unreliable rainfall deter dense human population. These areas show signs of over-cropping, over-stocking and soil erosion, and the average density of population is much lower than the national average. On the other hand, a large percentage of Pakistan’s total population is concentrated in the Indus Plain, and the average densities of population in these areas far exceed the national average. Thus, about 44% of the total population of Pakistan inhabits about 36% of the land area, occupying about 52% of the total arable land, whereas 7% of the total population lives on 40% of the land area, having 15% of the total arable land (Table 4). Table 4. Distribution
Population density per arable square mile 24,094
2276-1080 1060- 660 654- 534 502- 232 Unspecified Computed Source:
It becomes evident from the above discussion that in most cases density alone is not an important measure of population pressure. Much more crucial is the distribution of population in relation to available resources. Statistical
Analysis
Many variables affect population pressures on land. For practical purposes, however, it is necessary to limit the number of variables to be analysed. Using selected variables permits a better understanding of the problem and interpretation of the results. The variables used to explain the spatial distribution of population in Pakistan are: (a) population density per arable land unit, (b) ratio of irrigated land to total arable land, (c) mean annual temperature, (d) annual rainfall, (e) productivity of food grains per unit of arable land, (f) extension of irrigation, (g) changes in arable land and (h) population per unit of arable land. For statistical purposes some of these variable have been expressed in logarithmic form (a), (d) and (h). Since irrigated agriculture provides the indispensable economic resource-base in Pakistan, these variables are considered to be major determinants of population pressure on the land resources of the country. Since the resources and their productive function vary from area to area, the distri-
of population
and arable land
As percentage of the total area
As percentage of the total population
As percentage of the total arable land
0.4 14.5 18.4 17.8 40.3 8.6
5.5 34.4 23.9 19.6 7.7 8.9
0.2 22.8 28.2 24.1 15.0 9.7
Average density per square mile
Arable land per CQpitU (acre)
2623 497 272 229 41
0.02 0.37 0.66 0.68 1.10
by the author.
Population Census of Pakistan, 1972; Agricultural Statistics of Northwestern Frontier Province, 1945-1970; Development Statistics of Sind, 1972; and The Development Statistics of the ~njab , 1972.
~oforumlVolume
188
PAKISTAN POPULATION DENSITY 1972 PERSONS
PER
ARABLE
SQUARE
232-502 634-es6 680 - 1.caJ l.CXX.
2.276
24‘oM
Figure 1. Population
density.
MILE
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189
bution of population is expected to vary in approximately the same way. It is assumed that the pressure of population in Pakistan is directly influenced by the productiveness of agricultural land (the most important resource) and the prevailing climatic conditions. In order to test this model and, therefore, the hypothesis, it is necessary to estimate the manner in which each variable affects the density of population on arable land. Given such a set of data, it appeared that multivariate statistical analysis could provide some insight into the effective populationcarrying capacity of resources in Pakistan and the study presents two interrelated aspects of such an analysis. It was considered that the two statistical approaches selected could best provide output that would prove useful for those involved in population studies and determining man-land-resource relationships. Factor analysiswasusedtofocus the underlying causative processes that produce regional population pressure differentiation, as well as to identify the independent populationresource variables in the data. Stepwise multiple regression was used to study the relationship between the independent variables identified by the factor analysis and the population density per square miles of arable land as dependent variable. In completing the analysis a number of computer programs were used. Details are not given in this paper but, upon request, the author would be pleased to provide information concerning the programs used. Table 5.
density
4. Log rainfall 5. Productivity
The factor analysis has revealed that there appear to be three underlying factors as noted in Table 5. These factors accounted for 70.6% of the total variance in the original variables. Factor I accounted for 28.4% of the total variance. The associated variables with high loadings (+ 0.6 and above) were irrigated ratio (0.86), productivity of grains (0.73) and extension of irrigation (0.66). Inspection of the first factor loadings show that Factor I emerges as a general factor with high loadings related to use of technology and the related output of the arable land. Factors II and III were bipolar. Accounting for 24.5% of the total variance, the second factor showed change in population (0.91) at one pole and change in the productive land (-0.80) at the other. The explanation is that these two attributes are not in fact independent but may be thought of as two extreme situations, suggesting the possible existence of an underlying variable tending to act in opposite directions. Thus,
Rotated factor matrix h2
1. Log population 2. Irrigation ratio 3. Temperature
In order to fit the concept of population pressure into a spatial framework, it is necessary to explain the structure in which the above variables mutually associate. The factor analytic technique was used to account for the behaviour of the eight variables in terms of the relatively few basic dimensions related to population and resource-carrying capacity. The available program for general factor analysis was used to perform a principal component analysis and those orthogonal or uncorrelated factors with eigenvalues greater than unity were rotated to varimax solution.
0.77 0.78 0.62
Factor
Factor
-0.62 0.88 0.74
6. Change in productive land 7. Extension of irrigated land
0.71 0.44
0.66
8. Log change in population Percentage of variance Cumulative variance (%)
0.85
Computed
by the author.
Factor 0.64
0.78 of grains
II
0.86
0.70
Source:
I
-0.80
28.4 28.4
0.91 24.5 52.9
17.7 70.6
III
~ofo~mlVol~me
190
the factor population productive
reveals that there is a tendency for to increase in areas where more land is available.
Finally, Factor III, which accounted for 17.1% of the total variance, projected the dimension of climatic conditions. Positive loadings are associated with the annual rainfall (0.88) and the density of population (0.64), whereas negative loading appears to be associated with mean temperature (-0.62). This factor appears to identify some aspect of the population density as associated with environmental conditions in Pakistan. Examination of the high positive scores of the factor identify the rainfall subsistence farming areas located in the north and north-western sections of Pakistan, whereas the high negative scores identify the areas (Trans-Indus Plain and the Plateau of Baluchistan) where, because the rainfall is light and erratic, cropping and pasturing are closely linked to flood water availability. Other groups reflect low rainfall areas of the Indus Plain, where irrigation has provided farmers with means to practice irrigated agriculture. In fact, a large concentration of population is found in these areas. In short, the factor analytic technique identified the closely related variables and partitioned the eight variables into three unrelated factors-namely organizational, transformational and environmental factors--providing a structural framework of population-resource relationships (Figure 2).
Figure 2. Structural
framework.
1O~Number 211979
Structural Framework It is increasingly recognized that technology and organization mediate between population and resources. Assuming that a farming system could be viewed as an organizational factor, the first factor (which identifies irrigated land, productivity of food grains and extension of irrigated land) is indicative of organization. The second factor, representing changes in population and productive land, may be considered a transformative factor and reflects the fundamental structural changes in resource use as well as in the social structure of the country. Another major means of adaptation, described by the third factor, is the seasonal character of Pakistan, which identifies basic relationships between climate and population distribution. Regression Analysis Since the general purpose of factor analysis is to find relationships between clusters of variables (variables sharing similar characteristics) in order to determine the structure of sets of independent variables, principal component analysis was repeated only on seven original variables, eliminating thevariable of population density from the analysis. This operation was undertaken to remove the effect of the variable on other variables, ensuring that the common underlying dimensions are extracted with clusters of related variables that are relatively independent of other clusters, as well as of density of population. An orthogonal varimax rotation again extracted three factors, keeping the same major dimensions, and explained 72.6% of the total variance. The slight alteration of the individual factor loadings did not disturb the measurement of the underlying dimensions of the structural framework identitied above. The statistical relationship between resource structure and population density was developed using regression analysis. The factor scores for the 45 districts of Pakistan derived in the factor analysis were used as independent variables. The logarithmic values of the density of population were fed as dependent variables into the analysis to measure the function. regression technique added one Stepwise variable at a time until the complete equation was finallycalibrated.The order of independent
191
Ceoforum/Volume 1O/Number 2/l 979
variables entered in the regression sequence explained their contribution to explanation of the remaining variance in the dependent variable. The order of factors entering the equation was transformation factor (Factor II), environmental factor (Factor III), and finally organizational factor (Factor I). These factors were added to the equation in an orderly way in accordance with their relative importance, explaining about 34% of the total variance in the density of population. The transformation factor (Factor II), associated with the changes in population and productive land, was the most important and explained about 16% of the total variance, whereas the environmental factor (Factor III) explained about 13% of the total variance. The organizational factor (Factor I) explained only 4% of the total variance. However, the contributions of the variable to the multiple R were not statistically significant (Table 6). In order to compute the residuals, stepwise procedure was terminated after the second and third factor, and the multiple regression equation with respect to population density
Table 6. Summary
Variable entered 1. Factor II 2. Factor III 3. Factor I
Transformational Environmental Organizational
in Pakistan
is, therefore,
log population 2.88940
density -
=
0.13382F2
+
0.12137F3
Thus, the existing economic framework in which population is found produced a correlation of 0.55, indicating that the generated resource structure can account for barely onethird of the variance in population density. The Patterns of Population
Pressure
The residual values derived from regression analysis for each district indicate how well regression predicts the population density per arable unit (as dependent variable) for that particular observation. The predicted values of population density for 45 districts were subtracted from the observed population densities. The resulting values were used to show area1 variation in the degree of fit of the regression equation. Thus, the distribution of positive residuals (districts where density is greater than expected) and distribution of negative residuals (districts where density is less than expected) show spatial differences.
of a stepwise multiple
r
0.404 0.367 0.204
0.404 0.546 0.583
correlation
analysis
R2
Increase inR2
F-value
0.163 0.298 0.340
0.163 0.235 0.042
8.595* 8.248* 2.644t
Based on Step 2: Coefficient 2.88946 -0.13382 0.12147
Variable Constant Factor II Factor III Multiple R Std. error of est. Regression Residual
0.5459 0.2837 Df 2 43
Source: Computed by the author. *Significant on the 99% level. +Not significant.
Sum of squares 1.470 3.462
St. errors 0.0423 0.0423
Mean squares 0.735 0.08 1
F-ratio 9.129*
192
As shown in Figure 3, small residuals reflect very close correspondence between the actual and predicted values. These findings predominate in the districts of Jhelum, Gujrat, and Sialkot in the northern section of the upper Indus Basin, and Nawabshah and Hyderabad in the lower Indus Valley. The actual density of population in these cases was found closest to the predicted values of the model, exhibiting a best fit of the representation of the relationship between the carrying capacity of land and the degree of concentration of population.
Geoforum/Volume 1O/Number 2/l 979
occurred from the cultivation of low-yield cereals to that of high-yield food crops, such as wheat, rice and sugar cane. The well-irrigated sections of Pakistan are supporting more people because of the quality of their soils and the.practice of suitable types of farming. Thus, there is a definite tendency for districts with deviations from the norm to cluster spatially. Postive deviations tend to cluster in irrigated tracts, and negative deviations in dry and mountainous sections. Conclusion
(i) Areas of Low Population Pressure Large areas in the northwestern and western sections of Pakistan have negative residuals, where actual densities are less than the predicted values. Small areas in the eastern and south-eastern sections of the country also show this trend. It is clear from these negative residuals that districts are distinctly grouped according to the poor population-carrying capacities of their agricultural land. These areas have the least arable land, and are devoid of irrigation or have barani (rain-fed) land. In these districts, yields of food crops remained at low levels, because fertilizer and improved seeds are not used. In the sparsely inhabited or completely uninhabited areas, very little effort has been made to increase the potential for food production, and innovations have not been introduced. (ii) Areas of High Population Pressure In the central sections of the Indus Plain, high positive residuals occur. Very high positive residuals in the districts of Karachi, Lahore, Lyallpur, Peshawar and Rawalpindi reflect urbanization. High positive values also tend to occur in districts that are relatively industrialized or have developed commercial agriculture. The mapping of the positive residuals supports the concept that the magnitude of the population concentration in the upper and lower Indus Plains, where canal and tube well irrigation is intensively used, is positively associated with an increase in land use intensity and the extension of irrigation facilities. In recent years, some of these areas have shown remarkable increases in food production through the use of fertilizer and improved seeds. In many of these districts, a shift has
The study evaluates population pressure in terms of the carrying capacity of agricultural land, as well as an overall population-resource relationship within a conceptual framework. It also suggests that national planning agencies take a population-oriented policy making approach in devising regional development plans for the country. Statistical analysis illustrates the structural framework in which agriculture operates and the ways in which it influences the distribution and concentration of population in Pakistan. The regression model identifies the spatial patterns of the population-carrying capacity of the country’s agricultural land, considering resources in the context of population changes. The predicted values of population densities may provide a rationale for the consideration of regional development plans capable of attracting and absorbing additional population, which is already stagnating in the overpopulated parts of Pakistan. Mapping of residuals reveals a clear relationship between the existing socio-economic structure and the patterns of population pressure in Pakistan. The residuals also indicate that the population pressure is positively related to the agricultural development process. Districts located in the well-irrigated tracts with relatively better agricultural practices and diversified economic structure reflect positive values, indicating underprediction. It follows that in these areas, factors other than the independent variables influence the dependent variable. On the other hand, the districts with lesser agricultural resource development show indicating overprediction. negative results, These negative residuals suggest that in these
Geoforum/Volume
1~l~umber
193
211979
18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
PAKISTAN POPULATION (BASED
ON
TWE
PRESSURE
REGRESSION
ANALYSIS)
1972 RESIDUAL
VALUES
Ly
2 t
-
P
120
- 0.w
.0?6! - 0418 On0
LOW
- -0223
ACTUAL
- -1076
LOW
w ->
-0465
s
- 27c3 _- 434,
s
IilGH
1373 _ ml.47
CLOSEST
TO
-X?l!S--19Q3 4-llGt-I
Figure 3. Population
pressure.
PREDICTED
Geoforum/Volume
194
areas the population is distributed in such a way that there are less resources available for supporting this population. The significant problem that stands in the way of agricultural development in these areas is the lack of an irrigation system to supply the needed water throughout the year. Pakistan’s agriculture has been-and to a large extent still is-dependent on weather conditions. These areas badly need effective irrigation projects. Although the cultivation of upland river valleys and adoption of improved farming methods have created patterns of settlement (in Quetta and Peshawar districts, for example), sparsely populated areas lack resources to support the population. In these areas population shifts may be encouraged either by improving agricultrual practices or developing new economic opportunities through exploitation of mineral and/or other natural resources. The correlation between density of population and organizational factors was disappointingly low (r value of 0.20), indicating that, in an overall sense, the organizational factor is not strongly related to the population density. Such a correlation is not inconsistent with our analysis of residuals. In short, it can be confirmed that a multivariate relation in which population pressure is found in Pakistan largely depends on the changes in population and agricultural inputs and environmental factors. Moreover, each district has a
IO/Number
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position on a development scale representing a continuum of ‘good’ to ‘bad’. References BROWNING
H. L. (1970) Some biological
consider-
ation of population pressure on resources, In:
Geography and A Crowding World, W. Zelinsky, A. Kosinski and R. H. Prothero (Eds.). Oxford University Press, New York, pp. 71-82. GOVERNMENT OF PAKISTAN, AGRICULTURAL CENSUS ORGANIZATION (197 1) Second Pakistan Census of Agriculture, Vol. III, pt. II, Village Statistics, Lahore. GOVERNMENT OF PAKISTAN, CENSUS ORGANIZATION (1973) Population Census of Pakistan, 1972. Census Bulletin No. 1, Islambad. RASHEED, (1961) Census of Pakistan Population, Vol. I. TableandReports, Government of Pakistan, Karachi, pp. 1 l-54. STAMP L. D. (1969) Land for Tomorrow: Our Developing World, Indiana University Press, Bloomington. STEEL R. W. (1970) Population pressure in tropical Africa Trans. Inst. Br. Geogr. 49, l-14. SPENGLER J. J. (1967) Population optima, In: The 99th Hour, E. 0. Price (Ed.). Chapel Hill, N. C. pp. 29-50. TAEBUR IRENE B. (1970) Population dynamics and population pressures: geographic-demographic approaches, In: Geography and a Crowding World, W. Zelinsky, L. A. Kosinski and R. M. Prothero (Eds.). Oxford University Press, New York. UNITED NATIONS, POPULATION DIVISION (1953) The determinants and consequences of population trends, Popul. Stud. 17.