Predicting Understorey VegetationCover from Overstorey Attributes in Two Temperate MountainForests

Summary : It is important to develop a predictive understanding for the environmental controls on understorey vegetation, which harbor most of the plant biodiversity and are the source of food and cover for wildlife. Forest succession models (i. e. gap models) representing overstorey dynamics are not commonly linked to mathematical models of understorey dynamics. This is surprising, given that understorey vegetation clearly responds to changes in the overstorey that result in changing light availability. One difficulty may lie in the coarse representation of light regime captured by most gap models. Linkage of overstorey-understorey models might be facilitated if the diameter structure of simulated stands could be used to drive understorey change, as a proxy for light and other influences. The objective of this study was to determine whether understorey vegetation cover can be adequately predicted by variables derived from overstorey diameter structure alone, or if canopy cover and light availability are important, from additional predictors. Field sampling was conducted at a montane and a subalpine study area in the Swiss Alps. We used regression analysis to assess the relative importance of various overstorey predictors for understorey cover and composition. In the subalpine study area, the relative dominance of graminoids increased with increasing light availability, at the expense of forbs. In the montane study area, forb cover increased sharply with increasing light, while graminoid cover remained at low levels. As a result, the relative dominance of graminoid species declined with increasing light levels. This difference is attributed to the presence of Adenostyles alliariae, a tall, large-leaved forb. The effects of changes in the physical environment on plant community composition were thus mediated by interspecific interactions. This makes it difficult to predict overstorey-induced changes in understorey species composition at the level of functional groups. At both study sites, diameter structure variables were found to provide a reasonable approximation of total understorey cover, cover of the more common species, and species richness. Models of understorey community composition often improved (0-31% increased predictive ability) with inclusion of variables representing the light environment. In the context of gap model development, the great complexity associated with improved representation of light availability must be weighed against the relatively low gain in predictive power that is likely to result. We recommend that efforts to include forest understorey dynamics in gap models begin by considering empirical relationships between understorey patterns and overstorey diameter structur

The speed of learning instructed stimulus-response association rules in human: experimental data and model.

Humans can learn associations between visual stimuli and motor responses from just a single instruction. This is known to be a fast process, but how fast is it? To answer this question, we asked participants to learn a briefly presented (200ms) stimulus-response rule, which they then had to rapidly apply after a variable delay of between 50 and 1300ms. Participants showed a longer response time with increased variability for short delays. The error rate was low and did not vary with the delay, showing that participants were able to encode the rule correctly in less than 250ms. This time is close to the fastest synaptic learning speed deemed possible by diffusive influx of AMPA receptors. Learning continued at a slower pace in the delay period and was fully completed in average 900ms after rule presentation onset, when response latencies dropped to levels consistent with basic reaction times. A neural model was proposed that explains the reduction of response times and of their variability with the delay by (i) a random synaptic learning process that generates weights of average values increasing with the learning time, followed by (ii) random crossing of the firing threshold by a leaky integrate-and-fire neuron model, and (iii) assuming that the behavioural response is initiated when all neurons in a pool of m neurons have fired their first spike after input onset. Values of m=2 or 3 were consistent with the experimental data. The proposed model is the simplest solution consistent with neurophysiological knowledge. Additional experiments are suggested to test the hypothesis underlying the model and also to explore forgetting effects for which there were indications for the longer delay conditions. This article is part of a Special Issue entitled Neural Coding 2012

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

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

On quaternion based parametrization of orientation in computer vision and robotics

The problem of orientation parameterization for applications in computer vision and robotics is examined in detail herein. The necessary intuition and formulas are provided for direct practical use in any existing algorithm that seeks to minimize a cost function in an iterative fashion. Two distinct schemes of parameterization are analyzed: The first scheme concerns the traditional axis-angle approach, while the second employs stereographic projection from unit quaternion sphere to the 3D real projective space. Performance measurements are taken and a comparison is made between the two approaches. Results suggests that there exist several benefits in the use of stereographic projection that include rational expressions in the rotation matrix derivatives, improved accuracy, robustness to random starting points and accelerated convergence

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

Silver fir (Abies alba Mill.) is able to thrive and prosper under meso-Mediterranean conditions

The potential ecological envelope of silver fir (Abies alba Mill.) based on its present distribution suggests a high suitability for moist rather than warm and dry environments. This contrasts with paleoecological evidence reporting its former presence at low elevations under meso-Mediterranean conditions. In this study, we evaluated the growth performance of silver fir at low elevation (20–60 m a.s.l.) under meso-Mediterranean climatic conditions in Tuscany (central Italy). We conducted a dendroecological analysis on Abies alba trees along a geomorphological gradient (from depression to upper slope conditions). Climate-growth relationships were assessed by means of correlations, response functions, pointer years, and superposed epoch analysis. Silver fir was found to grow and regenerate well in these stands mixed with evergreen (e.g., Quercus ilex L.) and thermophilous deciduous Mediterranean tree species (e.g., Q. cerris L.). Summer drought was the most growth-influencing factor, with immediate (i.e., current season) negative impacts on tree-ring widths (TRW). No significant impacts were observed in the four years following extreme summer droughts, but the TRW series (which started between the 1930s and 1950s) showed a growth decline since the mid-1990s that is likely drought-related. Our results show that, provided there is a sufficiently large soil water holding capacity, silver fir provenances exist which are able to withstand Mediterranean summer droughts, can naturally and regularly regenerate in these systems, and may even dominate over typical meso-Mediterranean species. As long as annual precipitation is not too low (i.e., >850 mm) and summer drought conditions not too extreme (i.e., less than three months), silver fir has thus the potential to thrive under warm Mediterranean conditions.ISSN:0378-1127ISSN:1872-704

How robust are future projections of forest landscape dynamics? Insights from a systematic comparison of four forest landscape models

Projections of landscape dynamics are uncertain, partly due to uncertainties in model formulations. However, quantitative comparative analyses of forest landscape models are lacking. We conducted a systematic comparison of all forest landscape models currently applied in temperate European forests (LandClim, TreeMig, LANDIS-II, iLand). We examined the uncertainty of model projections under several future climate, disturbance, and dispersal scenarios, and quantified uncertainties by variance partitioning. While projections under past climate conditions were in good agreement with observations, uncertainty under future climate conditions was high, with between-model biomass differences of up to 200 t ha−1. Disturbances strongly influenced landscape dynamics and contributed substantially to uncertainty in model projections (~25–40% of observed variance). Overall, model differences were the main source of uncertainty, explaining at least 50% of observed variance. We advocate a more rigorous and systematic model evaluation and calibration, and a broader use of ensemble projections to quantify uncertainties in future landscape dynamics