| Literature DB >> 31640300 |
Qasir Abbas1,2, Jiqin Han3, Adnan Adeel4,5, Raza Ullah6.
Abstract
The changing climatic conditions coupled with fodder availability have posed severe challenges and threats for the dairy sector in Pakistan. The current paper determines the influence of climate change on the dairy sector in Pakistan. Comprehensive data set was collected from 450 farmers. The majority of farmers experienced the climate change and its variability and explained that severity and frequency of climatic extreme events such as droughts, heat waves, floods, pests and diseases and humidity is increasing. The study found that farmers considered drought as one of the major climatic risks which severely affects all aspects of dairy production. Specifically, to estimate the perceived impacts of climatic extreme event on milk production, an ordered probit model was applied and identified that climate change had high adverse impact on milk quantity in the study area. Different adaptation practices, such as changing cropping pattern for fodder production, off-farm income activities, diversifying the farm and regular vaccination are mostly used by dairy farmers. The study recommends policy initiatives to be taken by government for long term developments in the dairy farming.Entities:
Keywords: Pakistan; adaptation; climate change; dairy production; farmers’ risk perceptions; perceived impacts
Mesh:
Year: 2019 PMID: 31640300 PMCID: PMC6843986 DOI: 10.3390/ijerph16204036
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Dairy farming context under climatic risks.
Figure 2Map of study area.
Number of Dairy Animals in the Study Area (millions).
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|---|---|---|---|---|---|
| Pakistan | 47.8 | 40.0 | 30.9 | 76.1 | |
| Punjab | 13.204 | 16.019 | 4.942 | 17.392 | |
| Muzaffar-Garh | 1.1 | 0.9 | 0.5 | 1.3 | Cotton, wheat, maize, sugarcane |
| Jhang | 0.9 | 1.2 | 0.4 | 1.0 | Sugarcane, cotton, wheat, maize, tobacco |
| Jhelum | 0.1 | 0.09 | 0.013 | 0.13 | Wheat, rice, fruit, vegetables, fodder |
Source: Pakistan Economic Survey 2018–19 [22]; Punjab Development Statistics 2017 [44].
Figure 3Sampling framework.
Summary statistics of surveyed dairy farmers (n = 450).
| Variables | Mean ± SD or |
|---|---|
| Socio-economic characteristics | |
| Age (years) | 45.1 ± 12.6 |
| Dairy Farming Experience (years) | 21.2 ± 11.7 |
| Size of Family (no. of heads) | 8.5 ± 3.6 |
| Share of Dairy Income (%) | 42.8 ± 15.5 |
| Educational level (years) | |
| No Education | 88 (19.6) |
| Primary School | 137 (30.4) |
| High School | 174 (38.7) |
| College/University | 51 (11.3) |
| Farm characteristics | |
| Farm Size (ha) | 2.9 ± 1.2 |
| Land Allocated to Dairy Animals (ha) | 0.2 ± 0.01 |
| No. of Milking Animals (no. of heads) | 4.5 ± 2.6 |
| Milk Production/per day (liter) | 14.1 ± 6.5 |
| Farm type (in number) | |
| Irrigated | 234 (52) |
| Rain-fed | 210 (46.7) |
| Mixed | 6 (1.3) |
| Breed of dairy animals | |
| Indigenous | 172 (38.2) |
| Cross | 49 (10.9) |
| Mixed | 229 (50.9) |
Figure 4Climate-Related risks perceived by the dairy farmers.
Figure 5Climatic variability perceived by the dairy farmers.
Figure 6Historical trend of climate change in Punjab, Pakistan Source: Pakistan Meteorological Department (PMD) Dataset.
Figure 7Perceived impacts of climatic risks on dairy farming system.
Model results with marginal effects.
| Variables | Coefficients | Marginal Effects | |||
|---|---|---|---|---|---|
| Prob (Y = 1|X) | Prob (Y = 2|X) | Prob (Y = 3|X) | Prob (Y = 4|X) | ||
| dY/dX | dY/dX | dY/dX | dY/dX | ||
|
| |||||
| Drought | 0.1404 (0.064) ** | −0.014(0.007) ** | −0.040(0.018) ** | 0.021(0.010) ** | 0.035(0.014) ** |
| Flood | 0.1461 (0.063) ** | −0.014(0.006) ** | −0.041(0.017) ** | 0.022(0.001) ** | 0.031(0.013) ** |
| Heat Waves | 0.1515 (0.065) * | −0.015(0.006) ** | −0.015(0.006) ** | 0.023(0.011) ** | 0.023(0.011) ** |
| Humidity | 0.1433 (0.066) ** | −0.014(0.007) ** | −0.039(0.018) ** | 0.021(0.010) ** | 0.031(0.014) ** |
| Pest & Diseases | 0.1530 (0.063) ** | −0.015(0.006) ** | −0.043(0.016) ** | 0.023(0.011) ** | 0.032(0.013) ** |
| Heavy Rainfall | 0.0994 (0.064) ns | −0.001(0.006) ns | −0.028(0.017) ns | 0.015(0.001) ns | 0.021(0.014) ns |
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| Education | 0.0275 (0.013) ** | −0.030(0.010) ** | −0.080(0.040) ** | 0.040(0.020) ** | 0.060(0.030) ** |
| Age | 0.0113 (0.007) ns | 0.0113 (0.007) ns | −0.003(0.002) ns | 0.002(0.001) ns | 0.002(0.002) ns |
| Dairy Farming Experience | 0.0201 (0.008) ** | −0.002(0.000) ** | −0.005(0.002) ** | 0.008(0.004) ** | 0.009(0.005) ** |
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| Milking Animals | 0.026 (0.014) *** | −0.003 (0.001) *** | −0.007 (0.004) *** | 0.048 (0.024) *** | 0.060 (0.030) *** |
| Breed of Animals | 0.122 (0.080) ns | −0.012 (0.008) ns | −0.034 (0.022) ns | 0.020 (0.012) ns | 0.030 (0.020) ns |
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| Social Participation | 0.055 (0.072) ns | −0.005 (0.007) ns | −0.015 (0.020) ns | 0.008 (0.010) ns | 0.012 (0.012) ns |
| Source of Information | 0.1061(0.046) ** | −0.010 (0.004) ** | −0.030 (0.013) ** | 0.016 (0.007) ** | 0.023 (0.001) ** |
| Contact with Extension | 0.232 (0.080) * | −0.022 (0.008) *** | −0.064 (0.023) * | 0.034 (0.013) * | 0.050 (0.017) * |
| Services | |||||
| μ1 | 2.4518 (0.494) *** | ||||
| μ2 | 3.7753 (0.496) *** | ||||
| μ3 | 5.2023 (0.518) ** | ||||
| μ4 | 6.8030 (0.576) ** | ||||
| Observations | 450 | ||||
| LR chi2(9) | 94.90 | ||||
| Prob > chi2 | 0.0000 | ||||
| Log likelihood | −512.1638 | ||||
Standard Errors are given in parentheses; *, **, *** are 1%, 5% and 10% level of significance, ‘ns’ indicates not significant.
Figure 8Risk coping adaptation strategies practiced by dairy farmers.