Future climate scenarios indicate a change in precipitation patterns, i.e. in frequency and intensity, and thus a change of water availability for plants. The consequences for ecosystems can be evaluated using dynamic vegetation models (DVMs), but the description of soil properties and assumptions about root distribution and functionality are rather simplistic in many DVMs. We use the LPJ-GUESS model to evaluate (i) the usage of high-quality data sources for describing soil properties and (ii) the assumptions regarding roots. Specifically, we compare simulated carbon uptake when applying the frequently used FAO global soil map vs. soil measurements from 98 sites in the driest regions of Switzerland. The multilayer soil data were used either as observed (non-aggregated) or aggregated into two layers. At sites with low water holding capacities (whc < 100 mm) and a low precipitation sum that does not compensate for small whc, the FAO data led to a higher annual net primary productivity (ANPP) than when using observed soil data. In contrast under wetter conditions, the description of soil data did not make much difference. A comparison of different rooting strategies revealed a higher importance of vertical root distribution per soil layer than variable rooting depths due to the overriding effect of the hydrological assumptions in the model. We conclude that it is pivotal to use high-quality soil data and possibly to refine the hydrological assumptions in DVMs when attempting to study drought impacts on ecosystems. (C) 2014 Elsevier B.V. All rights reserved.

Projected future climate change will alter carbon storage in forests, which is of pivotal importance for the national carbon balance of most countries. Yet, national-scale assessments are largely lacking. We evaluated climate impacts on vegetation and soil carbon storage for Swiss forests using a dynamic vegetation model. We considered three novel climate scenarios, each featuring a quantification of the inherent uncertainty of the underlying climate models. We evaluated which regions of Switzerland would benefit or lose in terms of carbon storage under different climates, and which abiotic factors determine these patterns. The simulation results showed that the prospective carbon storage ability of forests depends on the current climate, the severity of the change, and the time required for new species to establish. Regions already prone to drought and heat waves under current climate will likely experience a decrease in carbon stocks under prospective 'extreme' climate change, while carbon storage in forests close to the upper treeline will increase markedly. Interestingly, when climate change is severe, species shifts can result in increases in carbon stocks, but when there is only slight climate change, climate conditions may reduce growth of extant species while not allowing for species shifts, thus leading to decreases in carbon stocks.

We review observational, experimental, and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied, although potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational, and/or modeling studies have the potential to overcome important caveats of the respective individual approaches.

Aim Despite increasing evidence for plant growth often being limited by sink (meristem) activity rather than source (photosynthesis) activity, all currently available dynamic global vegetation models (DGVMs) simulate plant growth via source-limited processes. For a given climatic region, this may lead to an overestimation of carbon stock per unit surface area, particularly if a model fails to correctly predict forest cover. Our aim is to improve the Lund-Potsdam-Jena (LPJ) DGVM by replacing the source-limited (SoL) tree growth algorithm by a sink-limited (SiL) one. Location Our analysis focuses on the cold tree line at high latitudes and altitudes. We study two altitudinal transects in the Swiss Alps and the northern tree line. Methods We limit annual net primary productivity of the LPJ DGVM by an algorithm based on the annual sum of growing degree-days (GDD), assuming that maximum plant growth is reached asymptotically with increasing GDD. Results Comparing simulation results with observational data, we show that the locations of both the northern and the alpine tree line are estimated more accurately when using a SiL algorithm than when using the commonly employed SoL algorithm. Also, simulated carbon stocks decrease in a more realistic manner towards the tree line when the SiL algorithm is used. This has far-reaching implications for estimating and projecting present and future carbon stocks in temperature-limited ecosystems. Main conclusions In the range of 60-80 degrees N over Europe and Asia, carbon stored in vegetation is estimated to be c. 50% higher in the LPJ standard version (LPJ-SoL) compared with LPJ-SiL, resulting in a global difference in estimated biomass of 25 Pg (c. 5% of the global terrestrial standing biomass). Similarly, the simulated elevation of the upper tree line in the European Alps differs by c. 400 m between the two model versions, thus implying an additional overestimation of carbon stored in mountain forests around the world.

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.

Globally, forest soils contain twice as much carbon as forest vegetation. Consequently, natural and anthropogenic disturbances affecting carbon accumulation in forest soils can alter regional to global carbon balance. In this study, we evaluate the effects of historic litter raking on soil carbon stocks, a former forest use which used to be widespread throughout Europe for centuries. We estimate, for Switzerland, the carbon sink potential in current forest soils due to recovery from past litter raking ('legacy effect'). The year 1650 was chosen as starting year for litter raking, with three different end years (1875/1925/1960) implemented for this forest use in the biogeochemical model LPJ-GUESS. The model was run for different agricultural and climatic zones separately. Number of cattle, grain production and the area of wet meadow have an impact on the specific demand for forest litter. The demand was consequently calculated based on historical statistical data on these factors. The results show soil carbon pools to be reduced by an average of 17 % after 310 years of litter raking and legacy effects were still visible 130 years after abandonment of this forest use (2 % average reduction). We estimate the remaining carbon sink potential in Swiss forest due to legacy effects from past litter raking to amount to 158,000 tC. Integrating historical data into biogeochemical models provides insight into the relevance of past land-use practices. Our study underlines the importance of considering potentially long-lasting effects of such land use practices for carbon accounting.

Geomorphological processes are an integral part of ecosystem functioning and ecosystem functioning affects geomorphological processes. Increasingly widespread acknowledgement of this simple idea is manifest in a vigorous research community engaged with questions that address the two-way interaction between biota and geomorphology, at a range of scales and in a variety of terrestrial and aquatic environments. Geomorphological disturbances are a core element of biogeomorphological interest, and although the disciplines of geomorphology and ecology have each developed languages and theories that help to explore, model and understand disturbance events, little attempt has been made to draw together these approaches. Following a brief review of these issues, we introduce thirteen papers that investigate the interactions and feedbacks between geomorphological disturbance regimes and ecosystem functions. These papers reveal the singularity of wildfire impacts, the importance of landsliding for carbon budgeting and of vegetation accumulation for landsliding, the zoogeomorphic role of iconic and Cinderella animals in fluvial geomorphology, biophysical interactions in aeolian, fluvial and torrential environments and the utility of living ecosystems as archives of geomorphic events. Most of these papers were first presented in a conference session at the European Geoscience Union General Assembly in 2010 and several others are from recent volumes of Earth Surface Processes and Landforms.

This paper discusses the effects of vegetation cover and soil parameters on the climate change projections of a regional climate model over the Arctic domain. Different setups of the land surface model of the regional climate model HIRHAM were realized to analyze differences in the atmospheric circulation caused by (1) the incorporation of freezing/thawing of soil moisture, (2) the consideration of top organic soil horizons typical for the Arctic and (3) a vegetation shift due to a changing climate. The largest direct thermal effect in 2 m air temperature was found for the vegetation shift, which ranged between -1.5 K and 3 K. The inclusion of a freeze/thaw scheme for soil moisture shows equally large sensitivities in spring over cool areas with high soil moisture content. Although the sensitivity signal in 2 m air temperature for the experiments differs in amplitude, all experiments show changes in mean sea level pressure (mslp) and geopotential height (z) throughout the troposphere of similar magnitude (mslp: -2 hPa to 1.5 hPa, z: -15 gpm to 5 gpm). This points to the importance of dynamical feedbacks within the atmosphere-land system. Land and soil processes have a distinct remote influence on large scale atmospheric circulation patterns in addition to their direct, regional effects. The assessment of induced uncertainties due to the changed implementations of land surface processes discussed in this study demonstrates the need to take all those processes for future Arctic climate projections into account, and demonstrates a clear need to include similar implementations in regional and global climate models.

Knowledge on the natural dynamics of Norway spruce-European silver fir forests is scarce, but is of high importance for the sustainable management of these ecosystems. Using a unique data set from five forest reserves in the Swiss Alps that covers up to 35 years, we elucidated communalities and differences in stand structure and species composition across the reserves and over time and investigated the role of site conditions versus intrinsic forest dynamics. For the early and late successional phases, we found a clear relationship between stand structure (diameter distributions) and species composition. Two pathways of early succession were evident as a function of the disturbance regime. Thus, the spatial extent of disturbances in spruce-fir forests strongly determines the pathway in early succession. Contrary to earlier descriptions of clearly distinguishable optima phases, our data did not reveal a relationship between stand structure and species composition for the early, mid-, and late optimum phases. Although the reserves investigated here are characterized by highly different climatic and soil conditions, their temporal development was found to fit well into a single successional scheme, suggesting that in spruce-fir mountain forests, the life-history strategies of the tree species may have a stronger influence on successional trajectories than site conditions per se.

Carbon storage and catchment hydrology are influenced both by land use changes and climatic changes, but there are few studies addressing both responses under both driving forces. We investigated the relative importance of climate change vs. land use change for four Alpine catchments using the LPJ-GUESS model. Two scenarios of grassland management were calibrated based on the more detailed model PROGRASS. The simulations until 2100 show that only reforestation could lead to an increase of carbon storage under climatic change, whereby a cessation of carbon accumulation occurred in all catchments after 2050. The initial increase in carbon storage was attributable mainly to forest re-growth on abandoned land, whereas the stagnation and decline in the second half of the century was mainly driven by climate change. If land was used more intensively, i.e. as grassland, litter input to the soil decreased due to harvesting, resulting in a decline of soil carbon storage (1.2−2.9 kg C m^–2) that was larger than the climate-induced change (0.8–1.4 kg C m⁻²). Land use change influenced transpiration both directly and in interaction with climate change. The response of forested catchments diverged with climatic change (11–40 mm increase in AET), reflecting the differences in forest age, topography and water holding capacity within and between catchments. For grass-dominated catchments, however, transpiration responded in a similar manner to climate change (light management: 23–32 mm AET decrease, heavy management: 29–44 mm AET decrease), likely because grassroots are concentrated in the uppermost soil layers. Both the water and the carbon cycle were more strongly influenced by land use compared to climatic changes, as land use had not only a direct effect on carbon storage and transpiration, but also an indirect effect by modifying the climate change response of transpiration and carbon flux in the catchments. For the carbon cycle, climate change led to a cessation of the catchment response (sink/source strength is limited), whereas for the water cycle, the effect of land use change remains evident throughout the simulation period (changes in evapotranspiration do not attenuate). Thus we conclude that management will have a large potential to influence the carbon and water cycle, which needs to be considered in management planning as well as in climate and hydrological modelling.