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«Dissertation Zur Erlangung des akademischen Grades Doctor rerum agriculturarum (Dr. rer. agr) eingereicht an der Landwirtschaftlich-Gärtnerischen ...»

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This chapter comprises three parts. The first part (Section 7.2) explains the theory of landuse change and conflicts based on these uses. In the second Section (7.3), the effects of the land-use change on land are presented with an explanation of the various conflicts that arise as the results of land-use change. The correlation of these conflicts with the conflicts of land distribution (explained in Chapter 6) and the joint effect of these two different conflicts on land degradation for the study region is also presented. Finally, a summary of the findings obtained from the study is described in Section 7.4.

7.2 Theory

Land-use change in the three study regions is an economic process that is based on the concept of the return from land pursuant to alternative activities performed on the land (Segerson et al. 2006: 3). The observed decisions about land use have also been related to cost-benefit analysis; if for one use of his land, a landowner might have to bear more costs than benefits, or the average returns from his land are lower than the inputs, he will not prefer this use, because his ultimate goal is to maximize his returns. While taking their decisions, some landowners ignore the externalities that result as returns from land-use change (Milion 2006: 163). These externalities are considered as negative, for example, if they have effects on the soil causing land degradation.

Various reasons for land-use change have been observed in the study regions; the main reason was the change in the natural environment, e.g., shortage of water and land conditions, affecting the decision of humans for land use. Inflation also changed the mind of a landowner;

for example, high inflation rates for seeds and other agricultural inputs raised the cost of production and caused a reduction in the returns of the landowners. Culture and traditions were also of some personal interest and had value for the land users and landowners. An influential actor was observed to force other members of a group/family to accept his decision for the use of their land. Similarly, geographic factors were also of the great importance for the issue of the land-use change, such as the location of land, the infrastructure in the region, and the distance of the land from the cities and main roads. In addition, property rights played a significant role in land-use change (Lambin and Geist 2007: 3).

For the security and sustainability of the land, the proper implementation of rights to the access to the land and for the use the land were very important, as they were found to be highly supportive of land management. Cultural-based relaxations in laws caused a crucial situation both for the landowners and the land itself in the form of conflicts (Alston 1999: 3).

Deprived landowners were not in the position to decide about their land and were bound to accept the pronouncement of another family member who had strong bargaining power or even had his own opinion on the use of the land; the wish of the deprived landowners to maximize their own returns was not possible because of the influence of the powerful actor (Knight 1992, See Section 3.6). This disturbance created a situation of conflict and caused land degradation, because most of the decisions of landowners were not socially efficient and

created an externality such as in the form of biomass reduction (Johnson and Lewis 2007:

164) on land used for non-agricultural purposes.

The analysis of these conflicts for land-use change is helpful in order to answer the following research question presented in this study. What sorts of conflicts exist among the different actors, mainly landholders and land users, for land-use causing land degradation?

For the analysis of this research question, more questions have to be answered. For example, what options are available for land use change? Are people in favor of this change of land use? Which option is more efficient in causing land degradation in these particular regions? Is there any association between the conflicts regarding land-use change and land distribution conflicts? The following results have been observed.

7.3 Results All three areas visited for this study are important from an agricultural point of view and because of their geographical location. As explained in Chapter 4, the land quality is different in these regions, and they have been selected on the basis of the various levels of degradation.

Shaikhupura-Kamoki has a medium level degradation of soil, whereas Qadirabad Dam region suffers from high level degradation. The third region, the Nandipur region, is categorized as being a low-level degraded land area. Geographically, this land is also very valuable for both agricultural and non-agricultural use, as in all these selected regions, most of the visited villages lie near to main roads. These roads link major cities, all of which are industrial cities.

Many other actors, such as industrialists and real estate builders, are involved in the situation because of the importance of this land. The average distance of these villages from the respective main roads is two kilometers. This current trend of land transformation reflects the possibilities for land degradation.

7.3.1 Different Options for Land-use Change Observed in the Region

Mainly, nine different options for the land use were observed in the region; these are presented in Table 7.1. For all these options, landowners from all visited households were asked, whether they were interested in a change in land use or not, and the response was tested against land degradation. Cuse1 is the variable for the response of the respondent 1 (R1) from each household, and Cuse2 is the variable for the response of the respondent 2 (R2) from each household (See Subsection 4.5.1 and 4.5.2). The results are presented in the Table 7.2.

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Industry Land use includes both manufacturing and processing units CNG Filling Stations Land is used for facilities to provide compressed natural gas and and Patrol Pumps patrol used in vehicles as fuel Hotel and Marriage Land is used for hotels and marriage halls for public use on payment Hall Fish Farming A shift of business

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Source: Survey 2008 These results show the positive relationship between the land-use change decisions of landowners and land degradation. This indicates that, when landowners take a decision for higher returns, they have to pay a cost in the form of land deterioration. More land is degraded when an additional household decides on land-use change.

Table 7.2: Results of the Effects of Land-use Change on Land Degradation for all Study Regions

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In the case of SKR, the estimated value for the coefficient of respondent 1 is 12.14, and the value for the second respondent is 9.55. These results show that the decisions of respondents 1 in this region, who are generally loyal to their traditions and not believe in huge changes, such as from mono-cropping to multiple cropping, are harmful to the land, as they stick to the old systems and want to survive in the old setup. On the other hand, the value of respondents 2 is lower compares with the respondents 1 but is positively related to land degradation; this group of respondents in the region wants to change the land use. The value of R2 is 0.19 in this sample, which means that only 19 percent of the total variance of land degradation has been explained, which is not impressive and shows that the data is much scattered.

In the other two cases, viz., QR and NR, respondents 1 are less responsive as compare with respondents 2. In QR, the case is slightly different; because most of the landowners are already convinced of the new use of land for a better standard of living, and respondents 2 want further to change it, because they think that they can obtain even more returns from this new use, although respondents 1 are not supportive of this further new change. Both the old and new changes cause land degradation, which may increase with any change in the decision of another household for land use. In this case, the R2 value is 0.143, according to which, once again, the value of the total explained variance is low and the deviation in data in high.

In case of the Nandipur region, the response is lower meaning that the people in this region are not in the favor of such a change, which increases the land degradation, although here the data is also very scattered, because of the small value of R2; nevertheless, the land-use pattern is much more favorable to resource conservation. These results show that, although a change has a negative impact on the land, the landowners are in favor of this change, because they want to maximize their individual returns and ignore social costs and losses in the form of resource damage.

7.3.2 Effectiveness of Land-use Options for the Degradation of Land

To check which is the most dangerous among these land-use options for land degradation, the efficiency of land degradation with respect to every option was calculated. For this, three separate regression Equations were estimated for the three regions, as land degradation was a dependent variable, and the different options were independent. To estimate the response of the question as to which option more efficiently participates in the process of land degradation, the efficiency of land degradation with respect to each option was calculated by using all options separately.

In the case of the study region Shaikhupura-Kamoki, the Equation was estimated for four different options; however, one option (CNG and filling station) was dropped from this analysis, because of the collinearity problem in estimation. The four options, viz., fish farming, poultry farming, hotel and marriage hall, and others were constant and were not included in the estimation. All other remaining options showed a positive response, with land degradation in the region; the results are summarized in Table 7.3.

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Source: Field Survey 2008 * Significant at level 0.01 ** Significant at level 0.05 *** Significant at level 0.10 According to the estimated Equation, the value of the coefficient of agricultural use is negative, which means that, with an increase of land use for agriculture, land degradation will decrease. All remaining estimated variables have a positive relationship with land degradation and suggest that, with an increase in these variables, land degradation will also increase.

Government acquisition has the strongest effect, as its estimated coefficient is 35. In this estimation, about fifty three percent of the data is explained, and the F distribution is also highly significant.

In the case of the Qadirabad Dam region, six variables were estimated, which are presented in the Table 7.4. The CNG and patrol filling station was deleted because of collinearity, and two options, viz., ‘others’ and ‘government acquisition’, were constant. In this case, the estimated coefficients for all the determinants were positive and will cause an increase in land degradation in the region; only the option of ‘hotel and marriage halls’ is an exception and is insignificant for this case.

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Source: Field Survey 2008 * Significant at level 0.01 ** Significant at level 0.05 *** Significant at level 0.10 The coefficient for industry has a maximum value, which indicates that additional industry in the region would be dangerous, and the land will be affected because of land-use change. On the other hand, agriculture is significant but causes the least effect on land in comparison with the other variables. Most of the variables in this case are significant at the ninety percent confidence interval. Approximately, twenty three percent variance of the data is explained, as the value of R2 is 0.225, and the model is fit for this estimation.

Similarly, in the last case study region, the regression model was estimated for the estimation of unknown coefficients of land-use change options for land degradation. Three out of nine options were estimated, whereas four were constant, viz., others, fish farming, poultry farming, and hotel and marriage halls, and could not be estimated; the option CNG was deleted because of the collinearity, as in SKR.

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