Markov Chain Modeling of Forest Cover Change and Forest Type Allocation (2000–2018) with a 2030 Projection

Abstract

This study examines the dynamics of forest cover in Honduras between 2000 and 2018 and projects its economic and environmental implications through 2030. Land-use transition matrices were constructed by harmonizing forest categories (coniferous, deciduous, broadleaf, mangrove, and non-forest areas), and Markov chain models were applied to estimate persistence, losses, and gains. Economic valuation integrated net carbon stocks (tCO2/ha) and ecosystem services (USD/ha) under voluntary market scenarios. The findings reveal a sustained decline in forest cover, particularly within broadleaf and deciduous ecosystems, with significant negative impacts on carbon reserves and ecosystem service values. Projections to 2030 suggest that, if current trends persist, Honduras may experience a substantial reduction in forest cover and its associated economic value, underscoring the urgent need for integrated conservation strategies and strengthened public policy interventions.