Ungulate herbivory modifies the effects of climate change on mountain forests

Recent temperature observations suggest a general warming trend that may be causing the range of tree species to shift to higher latitudes and altitudes. Since biotic interactions such as herbivory can change tree species composition, it is important to understand their contribution to vegetation changes triggered by climate change. To investigate the response of forests to climate change and herbivory by wild ungulates, we used the forest gap model ForClim v2.9.6 and simulated forest development in three climatically different valleys in the Swiss Alps. We used altitudinal transects on contrasting slopes covering a wide range of forest types from the cold (upper) to the dry (lower) treeline. This allowed us to investigate (1) altitudinal range shifts in response to climate change, (2) the consequences for tree species composition, and (3) the combined effect of climate change and ungulate herbivory. We found that ungulate herbivory changed species composition and that both basal area and stem numbers decreased with increasing herbivory intensity. Tree species responded differently to the change in climate, and their ranges did not change concurrently, thus causing a succession to new stand types. While climate change partially compensated for the reductions in basal area caused by ungulate herbivory, the combined effect of these two agents on the mix of the dominant species and forest type was non-compensatory, as browsing selectively excluded species from establishing or reaching dominance and altered competition patterns, particularly for light. We conclude that there is an urgent need for adaptive forest management strategies that address the joint effects of climate change and ungulate herbivor

Adapting a growth equation to model tree regeneration in mountain forests

Management and risk analysis of protection forests depend on a reliable estimation of regeneration processes and tree growth under different site conditions. While the growth of forest stands and thus the average growth of larger trees is well studied and published in yield tables as well as embodied in numerous simulation models, there is still a lack of information about the crucial initial stages of tree growth. Thus, we evaluated juvenile tree growth for different site conditions in the Swiss Alps and developed an approach to model both the early and later stages of growth based on the Bertalanffy equation. This equation is physiologically well founded and requires only two parameter estimates: a maximum tree height and a growth parameter. Data for the parameter estimation were available from studies of tree regeneration at a range of sites in Switzerland: growth patterns of larch (Larix decidua) were available from a high-elevation afforestation experiment. For spruce (Picea abies), data were obtained from a blowdown area in the Alps. The growth equation was fitted to the observed data and we found a good correlation of the fitted curves with the observed data. The parameter estimates were validated with independent data sets. The extrapolated growth curves, calculated with the estimated growth rates, correspond well to the validation data. Thus, it is possible to use the Bertalanffy equation to model both the early and later stages of growth. With this approach, we provide a basis for modelling the growth of juvenile and mature trees of different tree species in mountain forests of the European Alp

Drought response and changing mean sensitivity of European beech close to the dry distribution limit

European beech (Fagus sylvatica L.) covers a large area mainly in the colline and montane ranges in Europe, and a drier and warmer climate, as expected for the coming decades, is likely to alter its distribution. So far, an altitudinal shift has been projected using a variety of modelling approaches. However, we lack knowledge about the climatic and edaphic factors that control the growth and competitive behaviour of beech at its dry distribution limit. We applied and further developed dendroecological methods to study the drought response and sensitivity pattern of beech at sites with different moisture regimes. We compared three pairs of sites from different geographical regions near the dry distribution limit of beech in Switzerland, consisting of a dry and mesic site each. Radial growth differed between mesic and dry sites, in that average ring-width at mesic sites was around double the width at dry sites. For the whole study period (1930-2006), the sites with the lowest available soil water capacity (AWC) were found to respond most sensitively to drought. However, in recent years, sites with higher AWC have shown increasing drought sensitivity, i.e. they have responded even more strongly to drought than the dry sites. This change in sensitivity corresponds to a seasonal shift in drought response at mesic sites, with a change in the months showing significant drought response in all three studied regions compared with the past. Even though dry sites generally displayed a larger number of negative pointer years than mesic sites, it appears that the frequency of pointer years has increased at mesic sites, i.e. they have become more sensitive particularly in the last quarter of the twentieth century. Yet, the frequency of pointer years at the dry sites has remained fairly constant. These results indicate that beech trees near their dry distribution limit are adapted to extreme conditions already, while changes in the growth patterns of beech under mesic conditions have to be expecte

Improving the establishment submodel of a forest patch model to assess the long-term protective effect of mountain forests

Simulation models such as forest patch models can be used to forecast the development of forest structural attributes over time. However, predictions of such models with respect to the impact of forest dynamics on the long-term protective effect of mountain forests may be of limited accuracy where tree regeneration is simulated with little detail. For this reason, we improved the establishment submodel of the ForClim forest patch model by implementing a more detailed representation of tree regeneration. Our refined submodel included canopy shading and ungulate browsing, two important constraints to sapling growth in mountain forests. To compare the old and the new establishment submodel of ForClim, we simulated the successional dynamics of the Stotzigwald protection forest in the Swiss Alps over a 60-year period. This forest provides protection for an important traffic route, but currently contains an alarmingly low density of tree regeneration. The comparison yielded a significantly longer regeneration period for the new model version, bringing the simulations into closer agreement with the known slow stand dynamics of mountain forests. In addition, the new model version was applied to forecast the future ability of the Stotzigwald forest to buffer the valley below from rockfall disturbance. Two scenarios were simulated: (1) canopy shading but no browsing impact, and (2) canopy shading and high browsing impact. The simulated stand structures were then compared to stand structure targets for rockfall protection, in order to assess their long-term protective effects. Under both scenarios, the initial sparse level of tree regeneration affected the long-term protective effect of the forest, which considerably declined during the first 40years. In the complete absence of browsing, the density of small trees increased slightly after 60years, raising hope for an eventual recovery of the protective effect. In the scenario that included browsing, however, the density of small trees remained at very low levels. With our improved establishment submodel, we provide an enhanced tool for studying the impacts of structural dynamics on the long-term protective effect of mountain forests. For certain purposes, it is important that predictive models of forest dynamics adequately represent critical processes for tree regeneration, such as sapling responses to low light levels and high browsing pressur

Sustainable land use in mountain regions under global change: synthesis across scales and disciplines

Mountain regions provide essential ecosystem goods and services (EGS) for both mountain dwellers and people living outside these areas. Global change endangers the capacity of mountain ecosystems to provide key services. The Mountland project focused on three case study regions in the Swiss Alps and aimed to propose land-use practices and alternative policy solutions to ensure the provision of key EGS under climate and land-use changes. We summarized and synthesized the results of the project and provide insights into the ecological, socioeconomic, and political processes relevant for analyzing global change impacts on a European mountain region. In Mountland, an integrative approach was applied, combining methods from economics and the political and natural sciences to analyze ecosystem functioning from a holistic human-environment system perspective. In general, surveys, experiments, and model results revealed that climate and socioeconomic changes are likely to increase the vulnerability of the EGS analyzed. We regard the following key characteristics of coupled human-environment systems as central to our case study areas in mountain regions: thresholds, heterogeneity, trade-offs, and feedback. Our results suggest that the institutional framework should be strengthened in a way that better addresses these characteristics, allowing for (1) more integrative approaches, (2) a more network-oriented management and steering of political processes that integrate local stakeholders, and (3) enhanced capacity building to decrease the identified vulnerability as central elements in the policy process. Further, to maintain and support the future provision of EGS in mountain regions, policy making should also focus on project-oriented, cross-sectoral policies and spatial planning as a coordination instrument for land use in general

On learning time delays between the spikes from different input neurons in a biophysical model of a pyramidal neuron.

Biological systems are able to recognise temporal sequences of stimuli or compute in the temporal domain. In this paper we are exploring whether a biophysical model of a pyramidal neuron can detect and learn systematic time delays between the spikes from different input neurons. In particular, we investigate whether it is possible to reinforce pairs of synapses separated by a dendritic propagation time delay corresponding to the arrival time difference of two spikes from two different input neurons. We examine two subthreshold learning approaches where the first relies on the backpropagation of EPSPs (excitatory postsynaptic potentials) and the second on the backpropagation of a somatic action potential, whose production is supported by a learning-enabling background current. The first approach does not provide a learning signal that sufficiently differentiates between synapses at different locations, while in the second approach, somatic spikes do not provide a reliable signal distinguishing arrival time differences of the order of the dendritic propagation time. It appears that the firing of pyramidal neurons shows little sensitivity to heterosynaptic spike arrival time differences of several milliseconds. This neuron is therefore unlikely to be able to learn to detect such differences

Markov analysis of stochastic resonance in a periodically driven integrate-fire neuron

We model the dynamics of the leaky integrate-fire neuron under periodic stimulation as a Markov process with respect to the stimulus phase. This avoids the unrealistic assumption of a stimulus reset after each spike made in earlier work and thus solves the long-standing reset problem. The neuron exhibits stochastic resonance, both with respect to input noise intensity and stimulus frequency. The latter resonance arises by matching the stimulus frequency to the refractory time of the neuron. The Markov approach can be generalized to other periodically driven stochastic processes containing a reset mechanism.Comment: 23 pages, 10 figure

A multi-species synthesis of physiological mechanisms in drought-induced tree mortality

Widespread tree mortality associated with drought 92 has been observed on all forested continents, and global change is expected to exacerbate vegetation vulnerability. Forest mortality has implications for future biosphere-atmosphere interactions of carbon, water, and energy balance, and is poorly represented in dynamic vegetation models. Reducing uncertainty requires improved mortality projections founded on robust physiological processes. However, the proposed mechanisms of drought-induced mortality, including hydraulic failure and carbon starvation, are unresolved. A growing number of empirical studies have investigated these mechanisms, but data have not been consistently analyzed across species and biomes using a standardized physiological framework. Here we show that xylem hydraulic failure was ubiquitous across multiple tree taxa at drought induced mortality. All species assessed had 60% or higher loss of xylem hydraulic conductivity, consistent with proposed theoretical and modelled survival thresholds. We found diverse responses in non-structural carbohydrate reserves at mortality, indicating that evidence supporting carbon starvation was not universal. Reduced non-structural carbohydrates were more common for gymnosperms than angiosperms, associated with xylem hydraulic vulnerability, and may have a role in reducing hydraulic function. Our finding that hydraulic failure at drought-induced mortality was persistent across species indicates that substantial improvement in vegetation modelling can be achieved using thresholds in hydraulic function

Predicting Maximum Tree Heights and Other Traits from Allometric Scaling and Resource Limitations

Terrestrial vegetation plays a central role in regulating the carbon and water cycles, and adjusting planetary albedo. As such, a clear understanding and accurate characterization of vegetation dynamics is critical to understanding and modeling the broader climate system. Maximum tree height is an important feature of forest vegetation because it is directly related to the overall scale of many ecological and environmental quantities and is an important indicator for understanding several properties of plant communities, including total standing biomass and resource use. We present a model that predicts local maximal tree height across the entire continental United States, in good agreement with data. The model combines scaling laws, which encode the average, base-line behavior of many tree characteristics, with energy budgets constrained by local resource limitations, such as precipitation, temperature and solar radiation. In addition to predicting maximum tree height in an environment, our framework can be extended to predict how other tree traits, such as stomatal density, depend on these resource constraints. Furthermore, it offers predictions for the relationship between height and whole canopy albedo, which is important for understanding the Earth's radiative budget, a critical component of the climate system. Because our model focuses on dominant features, which are represented by a small set of mechanisms, it can be easily integrated into more complicated ecological or climate models.National Science Foundation (U.S.) (Research Experience for Undergraduates stipend)Gordon and Betty Moore FoundationNational Science Foundation (U.S.) (Graduate Research Fellowship Program)Massachusetts Institute of Technology. Presidential FellowshipEugene V. and Clare Thaw Charitable TrustEngineering and Physical Sciences Research CouncilNational Science Foundation (U.S.) (PHY0202180)Colorado College (Venture Grant Program