Forest Simulation Models and Climate Change: A Critical Review

Toshika Tamrakar; Mallesh Yalal; Ram Prakash Yadav; Sourabh Gauraj; Garima Gupta; Ramesh Barki; Nidhish Singh; Vadthyavath Avinash

doi:10.36808/if/2026/v152i6A/171260

Forest Simulation Models and Climate Change: A Critical Review

Authors

Toshika Tamrakar College of Horticulture and Forestry, RLBCAU, Jhansi
Mallesh Yalal College of Horticulture and Forestry, RLBCAU, Jhansi
Ram Prakash Yadav College of Horticulture and Forestry, RLBCAU, Jhansi
Sourabh Gauraj College of Horticulture and Forestry, RLBCAU, Jhansi
Garima Gupta College of Horticulture and Forestry, RLBCAU, Jhansi
Ramesh Barki National Remote Sensing Centre, Hyderabad
Nidhish Singh Department of Genetics and Plant Breeding, RLBCAU, Jhansi
Vadthyavath Avinash College of Horticulture and Forestry, RLBCAU, Jhansi

DOI:

https://doi.org/10.36808/if/2026/v152i6A/171260

Keywords:

Forest simulation models, Climate change, Process-based models, Gap models, MaxEnt, 3-PG, Forest dynamics, India.

Abstract

Forests cover approximately 4.14 billion hectares globally and play an important role in carbon sequestration, biodiversity conservation, and rural livelihoods. However, accelerating climate change is reshaping forest structure, species composition, and ecosystem functioning at an unprecedented pace, creating an urgent need for robust predictive tools. This review examines the major categories of forest simulation models, empirical, process-based, gap, landscape, and hybrid, evaluating their theoretical foundations, practical strengths, and inherent limitations in the context of climate change research. A historical timeline traces model development from 18th-century yield tables to contemporary Earth System Models. Four case studies drawn from India, Spain, and the United States demonstrate how different modelling frameworks perform across contrasting ecological and management contexts, confirming that no single model type is universally appropriate. The review identifies the near complete absence of process-based forest modelling applications in Indian ecosystems as the most significant knowledge gap in the field. Future research priorities include physiological parameterization of Indian tree species, long-term monitoring network development, and the application of multi-model ensemble frameworks to tropical and subtropical forest systems.

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