@article{22552, abstract = {Dynamic vegetation models have been widely used for analyzing ecosystem dynamics and their interactions with climate. Their performance has been tested extensively against observations and by model intercomparison studies. In the present analysis, Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS), a state-of-the-art ecosystem model, was evaluated by performing a global sensitivity analysis. The study aims at examining potential model limitations, particularly with regard to long-term applications. A detailed sensitivity analysis based on variance decomposition is presented to investigate structural model assumptions and to highlight processes and parameters that cause the highest variability in the output. First- and total-order sensitivity indices were calculated for selected parameters using Sobol's methodology. In order to elucidate the role of climate on model sensitivity, different climate forcings were used based on observations from Switzerland. The results clearly indicate a very high sensitivity of LPJ-GUESS to photosynthetic parameters. Intrinsic quantum efficiency alone is able to explain about 60% of the variability in vegetation carbon fluxes and pools for a wide range of climate forcings. Processes related to light harvesting were also found to be important together with parameters affecting forest structure (growth, establishment, and mortality). The model shows minor sensitivity to hydrological and soil texture parameters, questioning its skills in representing spatial vegetation heterogeneity at regional or watershed scales. In the light of these results, we discuss the deficiencies of LPJ-GUESS and possibly that of other, structurally similar, dynamic vegetation models and we highlight potential directions for further model improvements.}, author = {Pappas, Christoforos and Fatichi, Simone and Leuzinger, Sebastian and Wolf, Annett and Burlando, Paolo}, issn = {2169-8961}, journal = {Journal of Geophysical Research: Biogeosciences}, number = {2}, pages = {505--528}, publisher = {American Geophysical Union}, title = {{Sensitivity analysis of a process‐based ecosystem model: Pinpointing parameterization and structural issues}}, doi = {10.1002/jgrg.20035}, volume = {118}, year = {2013}, } @article{450, abstract = {Understanding the relative importance of heterosis and outbreeding depression over multiple generations is a key question in evolutionary biology and is essential for identifying appropriate genetic sources for population and ecosystem restoration. Here we use 2455 experimental crosses between 12 population pairs of the rare perennial plant Rutidosis leptorrhynchoides (Asteraceae) to investigate the multi-generational (F1, F2, F3) fitness outcomes of inter-population hybridization. We detected no evidence of outbreeding depression, with inter-population hybrids and backcrosses showing either similar fitness or significant heterosis for fitness components across the three generations. Variation in heterosis among population pairs was best explained by characteristics of the foreign source or home population, and was greatest when the source population was large, with high genetic diversity and low inbreeding, and the home population was small and inbred. Our results indicate that the primary consideration for maximizing progeny fitness following population augmentation or restoration is the use of seed from large, genetically diverse populations.}, author = {Pickup, Melinda and Field, David and Rowell, David and Young, Andrew}, journal = {Proceedings of the Royal Society of London Series B Biological Sciences}, number = {1750}, publisher = {Royal Society}, title = {{Source population characteristics affect heterosis following genetic rescue of fragmented plant populations}}, doi = {10.1098/rspb.2012.2058}, volume = {280}, year = {2013}, } @article{22476, abstract = {Projections of the future carbon and water cycles rely on knowledge on how forests will respond to rising atmospheric CO2. Experiments with elevated CO2 are logistically challenging and carbon pools and fluxes are difficult to measure and upscale due to their spatiotemporal heterogeneity. Therefore, it is important to combine the knowledge derived from experimental results with modeling. Here, we systematically compare data from a free air CO2 enrichment (FACE) experiment in a mature deciduous forest in Switzerland with realizations from an ecohydrological model (Tethys–Chloris). We test whether a mechanistic ecohydrological model is able to simulate physiological plant responses under ambient and elevated CO2 concentration. We overcome measurement limitations by quantifying differences in response to ambient and elevated CO2 over ten years. The reliability of model realizations is demonstrated by comparing simulations with field observations of stomatal conductance, sap flow, leaf and fruit litter, and stem growth. The model successfully captures the observed CO2-induced difference in stomatal conductance and transpiration and its sensitivity to atmospheric demand, as well as qualitative changes in soil moisture. The simulated differences between CO2 scenarios generally fall within the uncertainty of experimental observations, both for the carbon and water balance. Simulated total evapotranspiration is 2.8% (18 mm yr−1) lower and soil moisture 1.2% higher in the CO2-enriched scenario. Latent and sensible heat are modified by ca. 1 W m−2. Net primary production is simulated to increase by 19.8% and allocation to stem growth is 53 gC yr−1 m−2 higher in the elevated CO2 scenario, which represents the limit of the detection threshold of the experiment. Results show that while ecohydrological models can be used to reliably simulate multi-year energy, water, and carbon fluxes at the stand level, testing carbon allocation remains critical with current accuracy of field measurements. Uncertainties due to the simplified carbon allocation scheme are shown to be more significant for carbon than for energy and water fluxes. Generally, we conclude that for this type of forest, differences in annual energy and water fluxes induced by elevated CO2 are likely to be less than 10%.}, author = {Fatichi, Simone and Leuzinger, Sebastian}, issn = {1873-2240}, journal = {Agricultural and Forest Meteorology}, keywords = {Ecohydrological modeling, Plant water relations, FACE experiments, Forest productivity, CO2 enrichment, Swiss Canopy Crane}, pages = {144--157}, publisher = {Elsevier}, title = {{Reconciling observations with modeling: The fate of water and carbon allocation in a mature deciduous forest exposed to elevated CO2}}, doi = {10.1016/j.agrformet.2013.02.005}, volume = {174-175}, year = {2013}, } @article{22475, abstract = {This study extends a stochastic downscaling methodology to generation of an ensemble of hourly time series of meteorological variables that express possible future climate conditions at a point-scale. The stochastic downscaling uses general circulation model (GCM) realizations and an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). Marginal distributions of factors of change are computed for several climate statistics using a Bayesian methodology that can weight GCM realizations based on the model relative performance with respect to a historical climate and a degree of disagreement in projecting future conditions. A Monte Carlo technique is used to sample the factors of change from their respective marginal distributions. As a comparison with traditional approaches, factors of change are also estimated by averaging GCM realizations. With either approach, the derived factors of change are applied to the climate statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series of meteorological variables that can be considered to be representative of future climate conditions. In this study, the time series are generated in an ensemble mode to fully reflect the uncertainty of GCM projections, climate stochasticity, as well as uncertainties of the downscaling procedure. Applications of the methodology in reproducing future climate conditions for the periods of 2000–2009, 2046–2065 and 2081–2100, using the period of 1962–1992 as the historical baseline are discussed for the location of Firenze (Italy). The inferences of the methodology for the period of 2000–2009 are tested against observations to assess reliability of the stochastic downscaling procedure in reproducing statistics of meteorological variables at different time scales.}, author = {Fatichi, Simone and Ivanov, V. Y. and Caporali, E.}, issn = {1432-0894}, journal = {Climate Dynamics}, keywords = {Stochastic downscaling, Weather generator, Uncertainty assessment, Firenze, Italy}, pages = {1841--1861}, publisher = {Springer Nature}, title = {{Assessment of a stochastic downscaling methodology in generating an ensemble of hourly future climate time series}}, doi = {10.1007/s00382-012-1627-2}, volume = {40}, year = {2013}, } @article{2811, abstract = {In pipe, channel, and boundary layer flows turbulence first occurs intermittently in space and time: at moderate Reynolds numbers domains of disordered turbulent motion are separated by quiescent laminar regions. Based on direct numerical simulations of pipe flow we argue here that the spatial intermittency has its origin in a nearest neighbor interaction between turbulent regions. We further show that in this regime turbulent flows are intrinsically intermittent with a well-defined equilibrium turbulent fraction but without ever assuming a steady pattern. This transition scenario is analogous to that found in simple models such as coupled map lattices. The scaling observed implies that laminar intermissions of the turbulent flow will persist to arbitrarily large Reynolds numbers.}, author = {Avila, Marc and Hof, Björn}, journal = {Physical Review E}, number = {6}, publisher = {American Physical Society}, title = {{Nature of laminar-turbulence intermittency in shear flows}}, doi = {10.1103/PhysRevE.87.063012}, volume = {87}, year = {2013}, }