#L17 ACME-FATES: dynamic vegetation and demography

Poster TitleACME-FATES: Using dynamic vegetation and demography to capture changes in forest carbon cycling and competition
AuthorsJennifer Holm, Ryan Knox, William Riley (Unlicensed), Charles Koven (Unlicensed)
GroupLand, CMDV-Land
ExperimentDemography
Poster CategoryEarly Result
Submission TypePresentation
Poster Link2017_Holm_ACME_Poster_FATES_48x48.pdf


Abstract

The inclusion of dynamic vegetation demography in Earth System Models (ESMs) has been repeatedly identified as a critical step in moving ESMs towards more realistic representations of plant ecology, and the processes that govern the climatically important fluxes of carbon, energy, and water mediated by vegetation. Demographic processes have not been represented in the newly developed ACME Land Model (ALM) until the recent integration of the Functionally-Assembled Terrestrial Ecosystem Simulator (FATES). We summarize the first modeling results of ALM-FATES from a single point simulation in Brazil and a globally gridded simulation. We present multiple process approaches to represent plant competition for light, and alterations to the Perfect Plasticity Approximation (PPA) and discretized PPA used in ALM-FATES.

The motivation behind the Brazil simulation is that there is large uncertainty about whether the Amazon will be a carbon sink or source over the next century under a changing climate and rising atmospheric CO2 levels. To investigate this uncertainty, we simulated the ecosystem dynamics of a lowland moist tropical forest using four models for a detailed model comparison. The four models are ED2, ALM-FATES (structured vegetation models), CLM4.5-BGC, and ALMv1-ECA‑CNP (unstructured vegetation models), driven with local climate and CO2 forcing from the preindustrial period to 2100. Tree inventory data from a site north of Manaus, Brazil, with repeated demographic measurements from 1996-2011 were compared against simulations from the same time period. Compared to field observations, ED2 and ALM-FATES showed good agreement with observed biomass and forest size structure, but predicted higher growth and mortality fluxes than observed. These biases led to high, continual growth in all size classes and functional groups, whereas the field data indicate that a quarter of canopy trees showed no detectable growth, and the site had neutral biomass accumulation over the 15-year period. With a doubling of CO2 by 2100, all models predicted an appreciable forest sink, but due to contrasting process representations, different trends in biomass accumulation and opposing responses of vegetation turnover rate emerged. The differences were attributed to phenology response, nutrient constraints, and down-regulation of photosynthesis (native to CLM4.5-BGC and ALMv1-ECA-CNP only), inability to capture accurate density dependent processes (ED2 only), and large woody net primary productivity responses in ED2 and ALM-FATES. Determining appropriate process-level model benchmarks for constraints on carbon accumulation rates with rising CO2 is an important focus for future research.