Allometric Models for Estimation of Forest Biomass in North East India

Arun Nath,Om Tripathi,Brajesh Tiwari,Gudeta Sileshi,Uttam Sahoo,Sourabh Deb,Dhruba Das,Biplab Brahma,Ashesh Das,Ningthoujam Devi,Demsai Reang,Shiva Chaturvedi,Asha Gupta

doi:10.3390/f10020103

Abstract

In tropical and sub-tropical regions, biomass carbon (C) losses through forest degradation are recognized as central to global terrestrial carbon cycles. Accurate estimation of forest biomass C is needed to provide information on C fluxes and balances in such systems. The objective of this study was to develop generalized biomass models using harvest data covering tropical semi-evergreen, tropical wet evergreen, sub-tropical broad leaved, and sub-tropical pine forest in North East India (NEI). Among the four biomass estimation models (BEMs) tested AGBest = 0.32(D2Hδ)0.75 × 1.34 and AGBest = 0.18D2.16 × 1.32 were found to be the first and second best models for the different forest types in NEI. The study also revealed that four commonly used generic models developed by Chambers (2001), Brown (1989), Chave (2005) and Chave (2014) overestimated biomass stocks by 300–591 kg tree−1, while our highest rated model overestimated biomass by 197 kg tree−1. We believe the BEMs we developed will be useful for practitioners involved in remote sensing, biomass estimation and in projects on climate change mitigation, and payment for ecosystem services. We recommend future studies to address country scale estimation of forest biomass covering different forest types.

Highlights

Land based climate change mitigation strategies have received much global attention in the recent past, due to the large sink capacity and economic viability [1]
The aim of this study is to present generalized biomass estimation models (BEMs) for North East India (NEI) for use by practitioners involved in projects on climate change mitigation, and payment for ecosystem services
In NEI, 17.2 million hectares (M ha) of land is covered with forests, which constitutes ~25% of India’s total forest area [32] and is represented by five broad forest types based on the elevation, forest structure and composition: (i) tropical semi-evergreen, (ii) tropical wet evergreen, (iii) sub-tropical broad leaved (900–1900 m), (iv) sub-tropical pine (1000–3500 m), and (v) alpine temperate [34,35]

Summary

Introduction

Land based climate change mitigation strategies have received much global attention in the recent past, due to the large sink capacity and economic viability [1]. Tropical and sub-tropical forests are considered central to global terrestrial carbon (C) stocks [1,2]. Tropical and sub-tropical regions are well-recognized for losing forests due to agricultural expansion. Forests 2019, 10, 103 and bio-energy production [3]. Information on tropical forest biomass and C fluxes is gaining both economic and political currency in renewable energy development, C credit markets and research in global environmental change. Since the approval of the REDD+ (reducing emissions from deforestation and forest degradation) during the Conference of the Parties (COP 19) in November 2013, the Warsaw.

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