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Summary Aim Possible effects of current and future climates on boreal vegetation dynamics and carbon (C) cycling were investigated using the CENTURY 4.0 soil process model and a modified version of the FORSKA2 forest patch model. Location Eleven climate station locations distributed along a transect across the boreal zone of central Canada. Methods Both models were driven by detrended long‐term monthly climate data. Using a climate change signal derived from the GISS general circulation model (GCM) 2×CO 2 equilibrium climate scenario, the output from the two models was then used to compare simulated current and possible future total ecosystem C storage at the climate station locations. Results After allowing for their different underlying structures, comparison of output from both models showed good agreement with local field data under current climate conditions. CENTURY 4.0 was able to reproduce spatial variation in soil and litter C densities satisfactorily but tended to overestimate biomass productivity. FORSKA2 reproduced aboveground biomass productivity and spatially averaged biomass densities relatively well. Under the GISS 2×CO 2 scenario, both models generally predicted small increases in aboveground biomass C density for forest and tundra locations, but CENTURY 4.0 predicted greater decreases in soil and litter pools, for overall decreases in ecosystem C storage in the range 16–19%. Main conclusions With some caveats, results imply that effects of increased precipitation (as simulated by the GISS GCM) would more than compensate for any negative effects of increased temperature on forest growth. Increased temperature would also increase decomposition rates of soil and litter organic matter, however, for a net overall decrease in total ecosystem C storage.
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Summary Aim To investigate effects of within‐season and interannual climate variability on the behaviour of boreal forest ecosystems as simulated by the FORSKA2 patch model. Location Eleven climate station locations distributed along a transect across the boreal zone of central Canada. Methods FORSKA2′s water balance submodel was modified to enable it to behave more realistically under a varying climate. Long‐term actual monthly time‐series of temperature and precipitation data were detrended and used to drive the modified model. Long‐term monthly averages of the same detrended data were used to drive the unmodified model. Results Modifications created significant improvements when simulating species composition at sites in boreal Canada. Simulated forest biomass values were slightly higher than those obtained from the unmodified model using averaged climate records, but resembled the observed distribution of vegetation more closely. Main conclusions Modified FORSKA2 suggests that boreal forest composition and distribution may be more sensitive to changes in monthly rainfall data than to changes in temperature. Climate variability affects seasonal water balances and should be considered when using patch models to forecast vegetation dynamics during and following a period of climate transition. The modified model provided improved representation of the latitudinal trend in spatially averaged biomass density in this region.
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Abstract Although fast‐growing Populus species consume a large amount of water for biomass production, there are considerable variations in water use efficiency (WUE) across different poplar species. To compare differences in growth, WUE and anatomical properties of leaf and xylem and to examine the relationship between photosynthesis/WUE and anatomical properties of leaf and xylem, cuttings of six poplar species were grown in a botanical garden. The growth performance, photosynthesis, intrinsic WUE (WUE i ), stable carbon isotope composition (δ 13 C) and anatomical properties of leaf and xylem were analysed in these poplar plants. Significant differences were found in growth, photosynthesis, WUE i and anatomical properties among the examined species. Populus cathayana was the clone with the fastest growth and the lowest WUE i /δ 13 C, whereas P. × euramericana had a considerable growth increment and the highest WUE i /δ 13 C. Among the analysed poplar species, the highest total stomatal density in P. cathayana was correlated with its highest stomatal conductance (g s ) and lowest WUE i /δ 13 C. Moreover, significant correlations were observed between WUE i and abaxial stomatal density and stem vessel lumen area. These data suggest that photosynthesis, WUE i and δ 13 C are associated with leaf and xylem anatomy and there are tradeoffs between growth and WUE i . It is anticipated that some poplar species, e.g. P. × euramericana , are better candidates for water‐limited regions and others, e.g. P. cathayana , may be better for water‐abundant areas.
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Abstract. Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding of land-atmosphere carbon exchange to larger regions. The North American Carbon Program (NACP) Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal model intercomparison and evaluation effort focused on improving the diagnosis and attribution of carbon exchange at regional and global scales. MsTMIP builds upon current and past synthesis activities, and has a unique framework designed to isolate, interpret, and inform understanding of how model structural differences impact estimates of carbon uptake and release. Here we provide an overview of the MsTMIP effort and describe how the MsTMIP experimental design enables the assessment and quantification of TBM structural uncertainty. Model structure refers to the types of processes considered (e.g. nutrient cycling, disturbance, lateral transport of carbon), and how these processes are represented (e.g. photosynthetic formulation, temperature sensitivity, respiration) in the models. By prescribing a common experimental protocol with standard spin-up procedures and driver data sets, we isolate any biases and variability in TBM estimates of regional and global carbon budgets resulting from differences in the models themselves (i.e. model structure) and model-specific parameter values. An initial intercomparison of model structural differences is represented using hierarchical cluster diagrams (a.k.a. dendrograms), which highlight similarities and differences in how models account for carbon cycle, vegetation, energy, and nitrogen cycle dynamics. We show that, despite the standardized protocol used to derive initial conditions, models show a high degree of variation for GPP, total living biomass, and total soil carbon, underscoring the influence of differences in model structure and parameterization on model estimates.