Increasing aridity will not offset CO2 fertilization in fast-growing eucalypts with access to deep soil water.

Rising atmospheric [CO2 ] (Ca ) generally enhances tree growth if nutrients are not limiting. However, reduced water availability and elevated evaporative demand may offset such fertilization. Trees with access to deep soil water may be able to mitigate such stresses and respond more positively to Ca . Here, we sought to evaluate how increased vapor pressure deficit and reduced precipitation are likely to modify the impact of elevated Ca (eCa ) on tree productivity in an Australian Eucalyptus saligna Sm. plantation with access to deep soil water. We parameterized a forest growth simulation model (GOTILWA+) using data from two field experiments on E. saligna: a 2-year whole-tree chamber experiment with factorial Ca (ambient =380, elevated =620 µmol mol-1 ) and watering treatments, and a 10-year stand-scale irrigation experiment. Model evaluation showed that GOTILWA+ can capture the responses of canopy C uptake to (1) rising vapor pressure deficit (D) under both Ca treatments; (2) alterations in tree water uptake from shallow and deep soil layers during soil dry-down; and (3) the impact of irrigation on tree growth. Simulations suggest that increasing Ca up to 700 µmol mol-1 alone would result in a 33% increase in annual gross primary production (GPP) and a 62% increase in biomass over 10 years. However, a combined 48% increase in D and a 20% reduction in precipitation would halve these values. Our simulations identify high D conditions as a key limiting factor for GPP. They also suggest that rising Ca will compensate for increasing aridity limitations in E. saligna trees with access to deep soil water under non-nutrient limiting conditions, thereby reducing the negative impacts of global warming upon this eucalypt species. Simulation models not accounting for water sources available to deep-rooting trees are likely to overestimate aridity impacts on forest productivity and C stocks.

Tree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale.

Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10-40% per century under current climate and 20-170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics.

Determinants of drought effects on crown condition and their relationship with depletion of carbon reserves in a Mediterranean holm oak forest.

Severe droughts may increase physiological stress on long-lived woody vegetation, occasionally leading to rapid defoliation and progressive increase in mortality of overstorey trees. Over the last few years, episodes of drought-induced tree dieback have been documented in a variety of woodlands and forests around the world. However, the factors determining tree survival and subsequent recovery are still poorly understood, especially in resprouter species. We have studied the effects of a single drought episode on crown condition in a holm oak (Quercus ilex L.) forest located in NE Spain 7 years after the drought event. Generalized linear models were used to study the environmental correlates of forest crown condition 7 years after the drought event. Additionally, we evaluated the association between crown condition and the carbon and nutrient reserves stored in lignotubers 7 years after the drought. Our study reveals the multifactor nature of a drought-driven forest dieback in which soil depth and the characteristics of individual trees, particularly their number of stems, determined a complex spatial pattern of tree-level responses. This dieback was associated with a depletion of the carbon reserves in lignotubers 7 years after the episode, representing a reduction of up to 60% in highly drought-damaged trees. Interestingly, in the absence of new acute droughts, successive surveys in 2007-11 showed a direct association between carbon reserves depletion and further deterioration of crown condition. More frequent droughts, as predicted by climate change projections, may lead to a progressive depletion of carbon reserves and to a loss of resilience in Mediterranean resprouter species.

Ecosystem service supply and vulnerability to global change in Europe.

Global change will alter the supply of ecosystem services that are vital for human well-being. To investigate ecosystem service supply during the 21st century, we used a range of ecosystem models and scenarios of climate and land-use change to conduct a Europe-wide assessment. Large changes in climate and land use typically resulted in large changes in ecosystem service supply. Some of these trends may be positive (for example, increases in forest area and productivity) or offer opportunities (for example, "surplus land" for agricultural extensification and bioenergy production). However, many changes increase vulnerability as a result of a decreasing supply of ecosystem services (for example, declining soil fertility, declining water availability, increasing risk of forest fires), especially in the Mediterranean and mountain regions.

Comparing and evaluating process-based ecosystem model predictions of carbon and water fluxes in major European forest biomes.

Process-based models can be classified into: (a) terrestrial biogeochemical models (TBMs), which simulate fluxes of carbon, water and nitrogen coupled within terrestrial ecosystems, and (b) dynamic global vegetation models (DGVMs), which further couple these processes interactively with changes in slow ecosystem processes depending on resource competition, establishment, growth and mortality of different vegetation types. In this study, four models - RHESSys, GOTILWA+, LPJ-GUESS and ORCHIDEE - representing both modelling approaches were compared and evaluated against benchmarks provided by eddy-covariance measurements of carbon and water fluxes at 15 forest sites within the EUROFLUX project. Overall, model-measurement agreement varied greatly among sites. Both modelling approaches have somewhat different strengths, but there was no model among those tested that universally performed well on the two variables evaluated. Small biases and errors suggest that ORCHIDEE and GOTILWA+ performed better in simulating carbon fluxes while LPJ-GUESS and RHESSys did a better job in simulating water fluxes. In general, the models can be considered as useful tools for studies of climate change impacts on carbon and water cycling in forests. However, the various sources of variation among models simulations and between models simulations and observed data described in this study place some constraints on the results and to some extent reduce their reliability. For example, at most sites in the Mediterranean region all models generally performed poorly most likely because of problems in the representation of water stress effects on both carbon uptake by photosynthesis and carbon release by heterotrophic respiration (Rh ). The use of flux data as a means of assessing key processes in models of this type is an important approach to improving model performance. Our results show that the models have value but that further model development is necessary with regard to the representation of the some of the key ecosystem processes.