CO<Subscript>2</Subscript>-fertilization and potential future terrestrial carbon uptake in India

There is huge knowledge gap in our understanding of many terrestrial carbon cycle processes. In this paper, we investigate the bounds on terrestrial carbon uptake over India that arises solely due to CO ₂ -fertilization. For this purpose, we use a terrestrial carbon cycle model and consider two extreme scenarios: unlimited CO₂-fertilization is allowed for the terrestrial vegetation with CO₂ concentration level at 735 ppm in one case, and CO₂-fertilization is capped at year 1975 levels for another simulation. Our simulations show that, under equilibrium conditions, modeled carbon stocks in natural potential vegetation increase by 17 Gt-C with unlimited fertilization for CO₂ levels and climate change corresponding to the end of 21st century but they decline by 5.5 Gt-C if fertilization is limited at 1975 levels of CO₂ concentration. The carbon stock changes are dominated by forests. The area covered by natural potential forests increases by about 36% in the unlimited fertilization case but decreases by 15% in the fertilization-capped case. Thus, the assumption regarding CO₂-fertilization has the potential to alter the sign of terrestrial carbon uptake over India. Our model simulations also imply that the maximum potential terrestrial sequestration over India, under equilibrium conditions and best case scenario of unlimited CO₂-fertilization, is only 18% of the 21st century SRES A2 scenarios emissions from India. The limited uptake potential of the natural potential vegetation suggests that reduction of CO₂ emissions and afforestation programs should be top priorities.     

A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration

The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically support the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.     

Mapping and Modeling the Biogeochemical Cycling of Turf Grasses in the United States

Turf grasses are ubiquitous in the urban landscape of the United States and are often associated with various types of environmental impacts, especially on water resources, yet there have been limited efforts to quantify their total surface and ecosystem functioning, such as their total impact on the continental water budget and potential net ecosystem exchange (NEE). In this study, relating turf grass area to an estimate of fractional impervious surface area, it was calculated that potentially 163,800 km² (± 35,850 km²) of land are cultivated with turf grasses in the continental United States, an area three times larger than that of any irrigated crop. Using the Biome-BGC ecosystem process model, the growth of warm-season and cool-season turf grasses was modeled at a number of sites across the 48 conterminous states under different management scenarios, simulating potential carbon and water fluxes as if the entire turf surface was to be managed like a well-maintained lawn. The results indicate that well-watered and fertilized turf grasses act as a carbon sink. The potential NEE that could derive from the total surface potentially under turf (up to 17 Tg C/yr with the simulated scenarios) would require up to 695 to 900 liters of water per person per day, depending on the modeled water irrigation practices, suggesting that outdoor water conservation practices such as xeriscaping and irrigation with recycled waste-water may need to be extended as many municipalities continue to face increasing pressures on freshwater.