ABSTRACT Climate change poses a critical threat to Pakistan's land resources, with forest area and carbon stocks serving as key mitigation measures to reduce land degradation. This study introduces an innovative approach to examine the heterogeneous, quantile‐dependent relationships among climate change, climate change mitigation measured by forest area and carbon stocks in forests, and their impact on land degradation in Pakistan over the period 1990Q1 to 2022Q4. Employing Quantile‐on‐Quantile Kernel‐Based Regularized Least Squares (QQKRLS) and Quantile Causality Analysis, the findings reveal that climate change consistently exacerbates land degradation across all quantiles. Both mitigation measures significantly reduce degradation, with forest area exhibiting a broader influence across quantiles and carbon stocks showing particularly strong effects in mid‐to‐high degradation contexts. Quantile‐causality analysis confirms strong predictive effects of climate change at lower‐to‐mid degradation levels, while mitigation variables demonstrate greater predictive strength in mid‐to‐high degradation levels. These results emphasize the asymmetric and context‐specific nature of the climate change, climate mitigation–land degradation nexus and highlight the value of quantile‐based approaches for effective sustainability policy design in environmentally vulnerable economies like Pakistan.
Khan et al. (2026) studied this question.