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Fundamental drivers of ecosystem processes such as temperature and precipitation are rapidly changing and creating novel environmental conditions. Forest landscape models (FLM) are used by managers and policy-makers to make projections of future ecosystem dynamics under alternative management or policy options, but the links between the fundamental drivers and projected responses are weak and indirect, limiting their reliability for projecting the impacts of climate change. We developed and tested a relatively mechanistic method to simulate the effects of changing precipitation on species competition within the LANDIS-II FLM. Using data from a field precipitation manipulation experiment in a piñon pine (Pinus edulis) and juniper (Juniperus monosperma) ecosystem in New Mexico (USA), we calibrated our model to measurements from ambient control plots and tested predictions under the drought and irrigation treatments against empirical measurements. The model successfully predicted behavior of physiological variables under the treatments. Discrepancies between model output and empirical data occurred when the monthly time step of the model failed to capture the short-term dynamics of the ecosystem as recorded by instantaneous field measurements. We applied the model to heuristically assess the effect of alternative climate scenarios on the piñon-juniper ecosystem and found that warmer and drier climate reduced productivity and increased the risk of drought-induced mortality, especially for piñon. We concluded that the direct links between fundamental drivers and growth rates in our model hold great promise to improve our understanding of ecosystem processes under climate change and improve management decisions because of its greater reliance on first principles.

Abstract. The incidence of drought is expected to increase worldwide as a factor structuring forested landscapes. Ecophysiological mechanisms are being added to Forest Landscape Models (FLMs) to increase their robustness to the novel environmental conditions of the future (including drought), but their behavior has not been evaluated for mixed temperate forests. We evaluated such an approach by assessing the ability of physiological mechanisms to predict susceptibility to tree mortality as a function of drought in the upper Midwest (USA) through controlled site-level drought simulation experiments using the PnET-Succession extension of the LANDIS-II FLM. We also conducted a landscape-level experiment to study landscape response to drought treatments in the presence of the spatial processes of seed dispersal and stand-replacing disturbance. At the site level we found that net photosynthesis and carbon reserves showed a clear negative response to both the length of drought and the alternating pulses of normal precipitation and drought events, with soils holding more water moderating this response. The effect of the drought treatments varied somewhat depending on the assemblage of competitors and their specific life-history traits such as ability to compete for light, maximum photosynthetic capacity and water use efficiency. A large diversity of assemblages were simulated at the landscape level, and species abundance generally sorted by photosynthetic capacity (foliar nitrogen) and life form (deciduous vs. evergreen), with faster growing species and deciduous species suffering less decline because of drought. Soil type also had an impact on total productivity (biomass), with soils having higher available water being more productive through time. We conclude that (1) the mechanistic, first principles approach is advantageous for global change research because the combination of life-history traits of competitors interact to cause a site-specific dynamic response to fundamental drivers (e.g., precipitation, temperature), and these site-level responses interact spatially to create landscape responses that are complex and difficult to project with less mechanistic approaches, and (2) published findings that increasing drought length (rather than severity) increases tree mortality in the upper Midwest are clearly consistent with a mechanism of acute photosynthetic depression resulting in increased likelihood of carbon starvation as droughts lengthen.

American chestnut (Castanea dentata) was once an important component forests in the central Appalachians (USA), but it was functionally extirpated nearly a century ago. Attempts are underway to reintroduce blight-resistant chestnut to its former range, but it is uncertain how current forest composition, climate, and atmospheric changes and disturbance regimes will interact to determine future forest dynamics and ecosystem services. The combination of novel environmental conditions (e.g. climate change), a reintroduced tree species and new disturbance regimes (e.g. exotic insect pests, fire suppression) have no analog in the past that can be used to parameterize phenomenological models. We therefore used a mechanistic approach within the LANDIS-II forest landscape model that relies on physiological first principles to project forest dynamics as the outcome of competition of tree cohorts for light and water as a function of temperature, precipitation, CO concentration, and life history traits. We conducted a factorial landscape simulation experiment to evaluate specific hypotheses about future forest dynamics in two study sites in the center of the former range of chestnut. Our results supported the hypotheses that climate change would favor chestnut because of its optimal temperature range and relative drought resistance, and that chestnut would be less competitive in the more mesic Appalachian Plateau province because competitors will be less stressed. The hypothesis that chestnut will increase carbon stocks was supported, although the increase was modest. Our results confirm that aggressive restoration is needed regardless of climate and soils, and that increased aggressiveness of chestnut restoration increased biomass accumulation. The hypothesis that chestnut restoration will increase both compositional and structural richness was not supported because chestnut displaced some species and age cohorts. Although chestnut restoration did not markedly enhance carbon stocks, our findings provide hope that this formerly important species can be successfully reintroduced and associated ecosystem services recovered.

Simulation of decomposition and inorganic nitrogen release in complex biogeochemical models can be based on different principles. A major problem is the link between carbon and nitrogen mineralization and a description of microbial growth dynamics in dependence of a suite of possible substrates. This contribution considers a first order decomposition model with several carbon pools and one nitrogen pool to investigate how the decomposition of plant types and mineralization of nitrogen is related to carbon quality. The model structure assumes that nitrogen is mobilised with the rate at which the lignin compounds decompose. The decomposition module is coupled with microbial dynamics by adjusted Michaelis Menten equations that relate microbial growth to the availability of various substrates. The model was calibrated using Markov Chain Monte Carlo (MCMC) applied to measured litter remnants, concentrations of lignin, cellulose and nitrogen from 30 in situ incubations of foliage litters. Additionally, data from a laboratory incubation experiment were used to analyse the formation of microbial biomass, dissolved organic nitrogen, ammonium (NH 4 + ) and microbial respiration. Parameter sensitivity was analysed according to the rate of acceptance of various settings in the MCMC calibration chain. The most important parameters for the decomposition process were the decomposition rate of lignin, and the temperature response parameter Q 10 . The most important parameters for the formation of microbial biomass, dissolved organic nitrogen, ammonium and microbial respiration, were the potential growth rate of the microbial population and the rate of microbial decay. Estimated optimal decomposition rates for field experiments are 0.003±0.002 d −1 for lignin like compounds, 0.006±0.004 d −1 for cellulose like compounds and 0.0286±0.052 d −1 for solutes. The temperature response parameter Q 10 is 3.2±0.6 and the optimum decomposition temperature is 28.1±4.3°C. Important model parameters on microbial biomass and nitrification are the maximum microbial growth rate μ MAX =0.13±0.82 gC mic gC mic −1 d −1 or the rate of microbial decay D=0.006±0.014 gC mic gC mic −1 d −1 . The model performance was tested for independent datasets. Generally, correlations between modelled and measured values, expressed in R 2 , were high for the remaining tissue dry weight, or concentrations of lignin, cellulose and solutes or organic nitrogen (R 2 >0.84). Due to uncertainties in measurements of DON and NH 4 + concentrations, microbial biomass or basal respiration and significant site variability in these parameters, the model performance for these parameters as expressed as R 2 was somewhat lower, but Plant Soil (2010) 328:271-290 statistically highly significant, and in the range of 0.1-0.96.

Abstract.We studied the impact of climate change on the dynamics of soil organic carbon (SOC) stocks in productive grassland systems undergoing two types of management, an intensive type with frequent harvests and fertilizer applications and an extensive system without fertilization and fewer harvests. Simulations were conducted with a dedicated newly developed model, the Oensingen Grassland Model. It was calibrated using measurements taken in a recently established permanent sward in Central Switzerland, and run to simulate SOC dynamics over 2001-2100 under various climate change scenarios assuming different elements of IPCC A2 emission scenarios. We found that: (1) management intensity dominates SOC until approximately 20 years after grassland establishment. Differences in SOC between climate scenarios become significant after 20 years and climate effects dominate SOC dynamics from approximately 50 years after establishment. (2) Carbon supplied through manure contributes about 60 % to measured organic C increase in fertilized grassland. (3) Soil C accumulates particularly in the top 10 cm of the soil until 5 years after establishment. In the long-term, C accumulation takes place in the top 15 cm of the soil profile, while C content decreases below this depth. The transitional depth between gains and losses of C mainly depends on the vertical distribution of root senescence and root biomass. We discuss the importance of previous land use on carbon sequestration potentials that are much lower at the Oensingen site under ley-arable rotation with much higher SOC stocks than most soils under arable crops. We further discuss the importance of biomass senescence rates, because C balance estimations indicate that these may differ considerably between the two management systems.