First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems

TL;DR

This study evaluates the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems, demonstrating its effectiveness compared to other models using in situ data.

Contribution

It introduces a PPI-based GPP model that accounts for water stress and compares its performance against existing remote sensing models in African semi-arid regions.

Findings

PPI-based model better captures GPP magnitude than other models.

Models show reasonable agreement with in situ flux tower data.

PPI model is a promising tool for semi-arid ecosystem GPP estimation.

Abstract

The importance of semi-arid ecosystems in the global carbon cycle as sinks for CO2 emissions has recently been highlighted. Africa is a carbon sink and nearly half its area comprises arid and semi-arid ecosystems. However, there are uncertainties regarding CO2 fluxes for semi-arid ecosystems in Africa, particularly savannas and dry tropical woodlands. In order to improve on existing remote-sensing based methods for estimating carbon uptake across semi-arid Africa we applied and tested the recently developed plant phenology index (PPI). We developed a PPI-based model estimating gross primary productivity (GPP) that accounts for canopy water stress, and compared it against three other Earth observation-based GPP models: the temperature and greenness model, the greenness and radiation model and a light use efficiency model. The models were evaluated against in situ data from four semi-arid sites in Africa with varying tree canopy cover (3 to 65 percent). Evaluation results from the four GPP models showed reasonable agreement with in situ GPP measured from eddy covariance flux towers (EC GPP) based on coefficient of variation, root-mean-square error, and Bayesian information criterion. The PPI-based GPP model was able to capture the magnitude of EC GPP better than the other tested models. The results of this study show that a PPI-based GPP model is a promising tool for the estimation of GPP in the semi-arid ecosystems of Africa.