Abstract. An earth system model (MIROC-ESM 2010) is fully described in terms of each model component and their interactions. Results for the CMIP5 (Coupled Model Intercomparison Project phase 5) historical simulation are presented to demonstrate the model's performance from several perspectives: atmosphere, ocean, sea-ice, land-surface, ocean and terrestrial biogeochemistry, and atmospheric chemistry and aerosols. An atmospheric chemistry coupled version of MIROC-ESM (MIROC-ESM-CHEM 2010) reasonably reproduces transient variations in surface air temperatures for the period 1850-2005, as well as the presentday climatology for the zonal-mean zonal winds and temperatures from the surface to the mesosphere. The historical evolution and global distribution of column ozone and the amount of tropospheric aerosols are reasonably simulated in the model based on the Representative Concentration Pathways' (RCP) historical emissions of these precursors. The simulated distributions of the terrestrial and marine biogeochemistry parameters agree with recent observations, which is encouraging to use the model for future global change projections.

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that

We report the development of a new Spatially Explicit Individual-Based Dynamic Global 2 Vegetation Model (SEIB-DGVM), the first DGVM that can simulate the local interactions 3 among individual trees within a spatially explicit virtual forest. In the model, a sample plot is 4 placed at each grid box, and then the growth, competition, and decay of each individual tree 5 within each plot is calculated by considering the environmental conditions for that tree as it 6 relates to the trees that surround it. Based on these parameters only, the model simulated time

Circumboreal forest ecosystems are exposed to a larger magnitude of warming in comparison with the global average, as a result of warming-induced environmental changes. However, it is not clear how tree growth in these ecosystems responds to these changes. In this study, we investigated the sensitivity of forest productivity to climate change using ring width indices (RWI) from a tree-ring width dataset accessed from the International Tree-Ring Data Bank and gridded climate datasets from the Climate Research Unit. A negative relationship of RWI with summer temperature and recent reductions in RWI were typically observed in continental dry regions, such as inner Alaska and Canada, southern Europe, and the southern part of eastern Siberia. We then developed a multiple regression model with regional meteorological parameters to predict RWI, and then applied to these models to predict how tree growth will respond to twenty-first-century climate change (RCP8.5 scenario). The projections showed a spatial variation and future continuous reduction in tree growth in those continental dry regions. The spatial variation, however, could not be reproduced by a dynamic global vegetation model (DGVM). The DGVM projected a generally positive trend in future tree growth all over the circumboreal region. These results indicate that DGVMs may overestimate future wood net primary productivity (NPP) in continental dry regions such as these; this seems to be common feature of current DGVMs. DGVMs should be able to express the negative effect of warming on tree growth, so that they simulate the observed recent reduction in tree growth in continental dry regions.

[1] We applied a dynamic global vegetation model (DGVM) to the African continent. After calibration, the model reproduced geographical distributions of the continent's biomes, annual gross primary productivity (GPP), and biomass under current climatic conditions. The model is driven by the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A1B scenario of rising CO 2 , and by climate changes during the twenty-first century resulting from the change in CO 2 concentrations, simulated by a coupled Model for Interdisciplinary Research on Climate (MIROC) ocean atmosphere model. Simulations under this condition revealed time lags between environmental change and biome change, with the extent of these lags depending largely on the type of biome change. A switch in forest type was accompanied by the longest delay in biome change among all changes classified, indicating that resident trees largely prevent the establishment of nonresident tree types adapted to the new environment, and that tree growth requires additional years after successful establishment. In addition, assumptions for tree dispersal, which determine whether nonresident tree types can be established, modified the patterns of biome change under the twenty-first-century environment: under the assumption that nonresident tree types cannot be established even if environmental conditions change, the extent of the forest type switch and the development of forest and savanna were suppressed, while forest dieback was enhanced. These changes accompanied a slowing of the increasing trend in net primary productivity (NPP), biomass, and soil carbon during the twenty-first century and in subsequent years. These results quantitatively demonstrate that both patch dynamics and invasive tree recruitment significantly modify the transient change in vegetation distribution and function under a changing environment on the African continent.Citation: Sato, H., and T. Ise (2012), Effect of plant dynamic processes on African vegetation responses to climate change: Analysis using the spatially explicit individual-based dynamic global vegetation model (SEIB-DGVM),

An earth system model (MIROC-ESM) is fully described in terms of each model component and their interactions. Results for the CMIP5 (Coupled Model Intercomparison Project phase 5) historical simulation are presented to demonstrate the model's performance from several perspectives: atmosphere, ocean, sea-ice, land-surface, ocean and terrestrial biogeochemistry, and atmospheric chemistry and aerosols. An atmospheric chemistry coupled version of MIROC-ESM (MIROC-ESM-CHEM) reasonably reproduces transient variations in surface air temperatures for the period 1850–2005, as well as the present-day climatology for the zonal-mean zonal winds and temperatures from the surface to the mesosphere. The historical evolution and global distribution of column ozone and the amount of tropospheric aerosols are reasonably simulated in the model based on the Representative Concentration Pathways' (RCP) historical emissions of these precursors. The simulated distributions of the terrestrial and marine biogeochemistry parameters agree with recent observations, which is encouraging to use the model for future global change projections

Abstract. The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle, with both recent historical baselines and future responses to environmental change poorly constrained by available observations. In the absence of large-scale observations, models used for global assessments tend to fall back on simplified assumptions of the turnover rates of biomass and soil carbon pools. In this study, the biomass carbon turnover times calculated by an ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to assess their current capability to accurately estimate biomass carbon turnover times in forests and how these times are anticipated to change in the future. Modelled baseline 1985–2014 global average forest biomass turnover times vary from 12.2 to 23.5 years between TBMs. TBM differences in phenological processes, which control allocation to, and turnover rate of, leaves and fine roots, are as important as tree mortality with regard to explaining the variation in total turnover among TBMs. The different governing mechanisms exhibited by each TBM result in a wide range of plausible turnover time projections for the end of the century. Based on these simulations, it is not possible to draw robust conclusions regarding likely future changes in turnover time, and thus biomass change, for different regions. Both spatial and temporal uncertainty in turnover time are strongly linked to model assumptions concerning plant functional type distributions and their controls. Thirteen model-based hypotheses of controls on turnover time are identified, along with recommendations for pragmatic steps to test them using existing and novel observations. Efforts to resolve uncertainty in turnover time, and thus its impacts on the future evolution of biomass carbon stocks across the world's forests, will need to address both mortality and establishment components of forest demography, as well as allocation of carbon to woody versus non-woody biomass growth.

We describe the physiological responses of boreal conifers to climate change for the past 112 years using ring‐width and carbon isotope ratio (δ13C) chronologies at six forest sites in northern Eurasia and Canada. Responses differed among regions, depending on their climatic and/or geographic characteristics. Tree radial growth decreased over the past 52 years in central eastern Siberia with the higher rate of summer temperature increase than other regions, as indicated by the negative correlation between radial growth and summer temperature, but increased in northern Europe and Canada. Changes in tree‐ring δ13C indicated that recent climatic conditions have induced stronger drought stress for trees from central eastern Siberia than for those from other regions. The observed tree growth trends were compared to those simulated using a dynamic global vegetation model. Although the modeled annual net primary production (NPP) for trees generally exhibited similar decadal variation to radial growth, simulations did not show a recent decrease in tree growth, even in central eastern Siberia. This was probably due to an overestimation of the sensitivity of modeled tree NPP to precipitation. Our results suggest that the tree NPP forecasted under the expected future increases in temperature and average precipitation might be overestimated, especially in severely dry regions such as central eastern Siberia.