Drylands support over 2 billion people and cover 44% of the land surface. Recent evidence through flux towers suggests that drylands have a more dominant role in controlling the interannual variability in terrestrial CO2 uptake. Climate change will likely change this role as these ecosystems have an array of plant functional types (PFTs) that respond differently to climate, being grasses and trees. However, flux tower measurements represent patch-scale (~1 km) composite fluxes of an ecosystem, not the different PFTs. In drylands, there is often a mixture of different PFTs, and flux tower measurements alone cannot tell us how they affect ecosystem-scale fluxes. If the effect of different PFTs’ on ecosystem-scale fluxes can be parsed, then we can gain insights in PFTs’ response to rain pulses and temperature. Accordingly, we use several techniques in remote sensing (NEON for land cover), flux footprint modeling, and phenology (in situ and phenocam) to quantify the effect of different plant types on seasonal patterns of gross primary productivity (GPP) in southern Arizona for 2019. We used a new contribution model to estimate GPP per PFT. This model uses the total GPP from the tower, the area of PFTs, and the green chromatic coordinate (GCC).
Results/Conclusions:
We expect the trees to contribute to total GPP higher at the start and end of the growing season, and for the grasses to contribute higher during peak of season. For phenology, we expect trees to have a longer growing season and GCC at the start and end of the growing season, but for grass to have a higher GCC at the peak of the monsoon season. We found that the trees have a longer growing season than grass. Trees also had a significantly (p < 0.05) higher GCC than grass throughout the monsoon season. For GPP contribution, we expect trees to have a higher contribution to ecosystem GPP at the start and end of the monsoon season. We expect grasses to be higher at the peak of the growing season. However, the monsoon was delayed, likely causing the low grass GCC which may lead to lower grass contribution at the peak of the growing season. By being able to partition GPP to its PFTs, we may now explore how factors, such as rain pulses, drought, disease, etc., affect different plant types’ productivity at the ecosystem scale and gain more insight into CO2 uptake variability across drylands.