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Khan, et al.

outcomes improves accuracy. Equation I presents the US dollars. Weather factors, such as temperature and
RLS equation for reference: rainfall, strongly influenced the FCBI. Forest carbon
sequestration was affected by the average temperature
FCBI = Ω +Ω AGRIINC +Ω DEFORATE increase of 0.567°C and annual precipitation of
2
0
1
+Ω FMCP +Ω TEMP +Ω RAINFALL (I) 293.558 mm. The average urban population was 6,110,
4
3
5
+Ω URBANPOP + ε with a range from 3,528 to 8,897. Urbanization patterns
6
shifted and altered forest ecosystems and land use. The
Where: extreme values of each variable demonstrated the range
FCBI = Forest Carbon Benefit Indicator; of variability within the dataset. Kurtosis, skewness,
AGRINC = Agricultural income; and standard deviation provided insights into data
DEFORATE = Deforestation; distribution, symmetry, and dispersion. A kurtosis
FMCP = Forest management and conservation policies; of 5.150 suggests a distribution with heavy tails and
TEMP = Extreme temperature; a large peak, whereas the FCBI’s skewness of 1.574
RAINFALL = Rainfall vulnerability; indicates a right-skewed distribution.
URBANPOP = Urban population; and Figure 1 illustrates the influence statistics. These
Ƹ = Disturbance term. statistics revealed outliers and impactful observations
RLS regression improves empirical validity and within the dataset. The R Student and difference in fit(s)
reduces bias by adhering to quantitative research methods identified two extreme outliers that notably
standards for handling data outliers. It provides affected the regression analysis. The Hat Matrix approach
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a comprehensive and systematic assessment of the also identified two highly leveraged observations that
interrelationships between study variables, leading may significantly influence the regression findings. In
to practical, evidence-based solutions for sustainable addition, COVRATIO detected another outlier in the
forest management and climate change mitigation. dataset. Given these results, RLS regression was the
optimal choice for obtaining robust estimates.
4. Results and discussion Table 3 presents the RLS estimates. The results
indicated a negative association between FCBI and
Table 2 presents the descriptive statistics for the agricultural income. As agricultural income increased,
variables. In Pakistan, the FCBI fluctuated between woodland carbon sequestration decreased. This conclusion
0.464 and 5.660 metric tons of carbon dioxide per year, emphasizes the conflict between forest protection and
with a mean value of 1.940 metric tons. Agriculture agricultural growth. Farming often leads to deforestation
income improved carbon benefits by increasing the to make way for crops or livestock, reducing forest cover
FCBI by 3,740 US dollars. The annual deforestation and carbon stored in soil and woody plants. Agricultural
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rate varied from 0.473% to 1.636%, with an average activities such as soil tilling and fertilizer application
of 0.974%, placing pressure on forest carbon release carbon into the atmosphere. Pakistan, with
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sequestration. The forest sustainability index trends an economy heavily dependent on agriculture, faces
fluctuated over the analyzed period, with an average significant challenges in balancing economic growth and
of 4.780 US dollars, showing a decrease of 1.060 environmental sustainability. 84

Table 2. Descriptive statistics
Methods FCBI AGRINC DEFORATE FMCP TEMP RAINFALL URBANPOP
Mean 1.940 3.740 0.974 4.780 0.567 293.558 6110
Maximum 5.660 8.380 1.636 9.820 1.423 442.880 8897
Minimum 5.464 1.190 0.473 1.060 -0.375 181.500 3528
Std. dev. 1.390 2.480 0.171 2.980 0.475 64.984 1615
Skewness 1.574 0.427 0.923 0.298 -0.191 0.149 0.027
Kurtosis 5.150 1.766 9.793 1.594 2.481 2.215 1.787
Source: Authors’ estimate. Abbreviations: AGRINC: Agricultural income; DEFORATE: Deforestation; FCBI: Forest Carbon Benefit
Indicator; FMCP: Forest management and conservation policies; RAINFALL: Rainfall vulnerability; Std. dev.: Standard deviation;
TEMP: Extreme temperature; URBANPOP: Urban population.

Volume 22 Issue 1 (2025) 58 doi: 10.36922/AJWEP025050027