Predictive models for dry biomass and carbon stock estimation in Litchi chinensis under hot and dry sub-humid climate

ABSTRACT

Accurate and reliable predictive models are necessary to estimate above and below ground biomass of plant and biomass carbon stock non-destructively. Different growth models namely viz, Linear, Allometric, Logistic, Gompertz, Richard’s, Negative exponential, Monomolecular, Mitcherlich and Weibull were fitted to the relationship between dry biomass of litchi tree components with collar diameter. Richard’s model outperformed the others and fulfilled the validation criterions to the best possible extent with lowest Akaike information criteria (AICc) of 90.47 and root mean square error (RMSE) of 1.79. The value of adjusted R² ranged from 0.947 to 0.971 for the Richard’s models fitted on various biomass components and the ‘t’ values for all the components was found non-significant (p > 0.05) indicating the validation of the model. The estimated total dry biomass varied from 0.50 Mg ha⁻¹ in two year to 5.71 Mg ha⁻¹ in 10 year old litchi orchards. The estimated stored biomass carbon stock in litchi orchards (branches, bole and roots) varied from 0.10 Mg ha⁻¹ in two year to 1.85 Mg ha⁻¹ in 10 year orchards with CO₂ sequestration potential from 0.19–4.63 Mg ha⁻¹.

KEYWORDS:

• Biomass
• Carbon
• Litchi chinensis
• Predictive models
• Richard’s model

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Indian Council of Agricultural Research [ICAR/RCER/DC/2011/104].