Quantifying entrepreneurship and its impact on local economic performance: A spatial assessment in rural Switzerland

Regional and rural development policies in Europe increasingly emphasize entrepreneurship to mobilize the endogenous economic potential of rural territories. This study develops a concept to quantify entrepreneurship as place-dependent local potential to examine its impact on the local economic performance of rural territories in Switzerland. The short-to-medium-term impact of entrepreneurship on the economic performance of 1706 rural municipalities in Switzerland is assessed by applying three spatial random effects models. Results suggest a generally positive relationship between entrepreneurship and local development: rural municipalities with higher entrepreneurial potential generally show higher business tax revenues per capita and a lower share of social welfare cases among the population, although the impact on local employment is less clear. The explanatory power of entrepreneurship in all three models, however, was only moderate. This finding suggests that political expectations of fostering entrepreneurship to boost endogenous rural development in the short-to-medium term should be damped.

Investigating the consistency between proxy-based reconstructions and climate models using data assimilation: a mid-Holocene case study

The mid-Holocene (6 kyr BP; thousand years before present) is a key period to study the consistency between model results and proxy-based reconstruction data as it corresponds to a standard test for models and a reasonable number of proxy-based records is available. Taking advantage of this relatively large amount of information, we have compared a compilation of 50 air and sea surface temperature reconstructions with the results of three simulations performed with general circulation models and one carried out with LOVECLIM, a model of intermediate complexity. The conclusions derived from this analysis confirm that models and data agree on the large-scale spatial pattern but the models underestimate the magnitude of some observed changes and that large discrepancies are observed at the local scale. To further investigate the origin of those inconsistencies, we have constrained LOVECLIM to follow the signal recorded by the proxies selected in the compilation using a data-assimilation method based on a particle filter. In one simulation, all the 50 proxy-based records are used while in the other two only the continental or oceanic proxy-based records constrain the model results. As expected, data assimilation leads to improving the consistency between model results and the reconstructions. In particular, this is achieved in a robust way in all the experiments through a strengthening of the westerlies at midlatitude that warms up northern Europe. Furthermore, the comparison of the LOVECLIM simulations with and without data assimilation has also objectively identified 16 proxy-based paleoclimate records whose reconstructed signal is either incompatible with the signal recorded by some other proxy-based records or with model physics.

Spatial heterogeneity and lake morphology affect diffusive greenhouse gas emission estimates of lakes

Most estimates of diffusive flux (F) of methane (CH4) and carbon dioxide (CO2) from lakes are based on single-point flux chamber measurements or on piston velocity (k) modeled from wind speed and single-point measurements of surface water gas concentrations (C-aq). We analyzed spatial variability of F of CH4 and CO2, as well as C-aq and k in 22 European lakes during late summer. F and k were higher in the lake centers, leading to considerable bias when extrapolating single-point chamber measurements to whole-lake estimates. The ratio of our empirical k estimates to wind speed-modeled k was related to lake size and shape, suggesting a lake morphology effect on the relationship between wind speed and k. This indicates that the error inherent to established wind speed models can be reduced by determining k and C-aq at multiple sites on lakes to calibrate wind speed-modeled k to the local system.

A Process Model of the Formation of Spatial Presence Experiences

In order to bridge interdisciplinary differences in Presence research and to establish connections between Presence and “older” concepts of psychology and communication, a theoretical model of the formation of Spatial Presence is proposed. It is applicable to the exposure to different media and intended to unify the existing efforts to develop a theory of Presence. The model includes assumptions about attention allocation, mental models, and involvement, and considers the role of media factors and user characteristics as well, thus incorporating much previous work. It is argued that a commonly accepted model of Spatial Presence is the only solution to secure further progress within the international, interdisciplinary and multiple-paradigm community of Presence research.

Evaluating the Quality and Accuracy of TanDEM-X Digital Elevation Models at Archaeological Sites in the Cilician Plain, Turkey

Satellite remote sensing provides a powerful instrument for mapping and monitoring traces of historical settlements and infrastructure, not only in distant areas and crisis regions. It helps archaeologists to embed their findings from field surveys into the broader context of the landscape. With the start of the TanDEM-X mission, spatially explicit 3D-information is available to researchers at an unprecedented resolution worldwide. We examined different experimental TanDEM-X digital elevation models (DEM) that were processed from two different imaging modes (Stripmap/High Resolution Spotlight) using the operational alternating bistatic acquisition mode. The quality and accuracy of the experimental DEM products was compared to other available DEM products and a high precision archaeological field survey. The results indicate the potential of TanDEM-X Stripmap (SM) data for mapping surface elements at regional scale. For the alluvial plain of Cilicia, a suspected palaeochannel could be reconstructed. At the local scale, DEM products from TanDEM-X High Resolution Spotlight (HS) mode were processed at 2 m spatial resolution using a merge of two monostatic/bistatic interferograms. The absolute and relative vertical accuracy of the outcome meet the specification of high resolution elevation data (HRE) standards from the National System for Geospatial Intelligence (NSG) at the HRE20 level.

Conservation of threatened habitat types under future climate change – Lessons from plant-distribution models and current extinction trends in southern Germany

A higher risk of future range losses as a result of climate change is expected to be one of the main drivers of extinction trends in vascular plants occurring in habitat types of high conservation value. Nevertheless, the impact of the climate changes of the last 60 years on the current distribution and extinction patterns of plants is still largely unclear. We applied species distribution models to study the impact of environmental variables (climate, soil conditions, land cover, topography), on the current distribution of 18 vascular plant species characteristic of three threatened habitat types in southern Germany: (i) xero-thermophilous vegetation, (ii) mesophilous mountain grasslands (mountain hay meadows and matgrass communities), and (iii) wetland habitats (bogs, fens, and wet meadows). Climate and soil variables were the most important variables affecting plant distributions at a spatial level of 10 × 10 km. Extinction trends in our study area revealed that plant species which occur in wetland habitats faced higher extinction risks than those in xero-thermophilous vegetation, with the risk for species in mesophilous mountain grasslands being intermediary. For three plant species characteristic either of mesophilous mountain grasslands or wetland habitats we showed exemplarily that extinctions from 1950 to the present day have occurred at the edge of the species’ current climatic niche, indicating that climate change has likely been the main driver of extinction. This is largely consistent with current extinction trends reported in other studies. Our study indicates that the analysis of past extinctions is an appropriate means to assess the impact of climate change on species and that vulnerability to climate change is both species- and habitat-specific.

A systematized workflow for assessing land resources using readily available spatial datasets

Land degradation as well as land conservation maps at a (sub-) national scale are critical for pro-ject planning for sustainable land management. It has long been recognized that online accessible and low-cost raster data sets (e.g. Landsat imagery, SRTM-DEM’s) provide a readily available basis for land resource assessments for developing countries. However, choice of spatial, tempo-ral and spectral resolution of such data is often limited. Furthermore, while local expert knowl-edge on land degradation processes is abundant, difficulties are often encountered when linking existing knowledge with modern approaches including GIS and RS. The aim of this study was to develop an easily applicable, standardized workflow for preliminary spatial assessments of land degradation and conservation, which also allows the integration of existing expert knowledge. The core of the developed method consists of a workflow for rule-based land resource assess-ment. In a systematic way, this workflow leads from predefined land degradation and conserva-tion classes to field indicators, to suitable spatial proxy data, and finally to a set of rules for clas-sification of spatial datasets. Pre-conditions are used to narrow the area of interest. Decision tree models are used for integrating the different rules. It can be concluded that the workflow presented assists experts from different disciplines in col-laboration GIS/RS specialists in establishing a preliminary model for assessing land degradation and conservation in a spatially explicit manner. The workflow provides support when linking field indicators and spatial datasets, and when determining field indicators for groundtruthing.

Achieving a more realistic assessment of rockfall hazards by coupling three-dimensional process models and field-based tree-ring data

Sound knowledge of the spatial and temporal patterns of rockfalls is fundamental for the management of this very common hazard in mountain environments. Process-based, three-dimensional simulation models are nowadays capable of reproducing the spatial distribution of rockfall occurrences with reasonable accuracy through the simulation of numerous individual trajectories on highly-resolved digital terrain models. At the same time, however, simulation models typically fail to quantify the ‘real’ frequency of rockfalls (in terms of return intervals). The analysis of impact scars on trees, in contrast, yields real rockfall frequencies, but trees may not be present at the location of interest and rare trajectories may not necessarily be captured due to the limited age of forest stands. In this article, we demonstrate that the coupling of modeling with tree-ring techniques may overcome the limitations inherent to both approaches. Based on the analysis of 64 cells (40 m × 40 m) of a rockfall slope located above a 1631-m long road section in the Swiss Alps, we illustrate results from 488 rockfalls detected in 1260 trees. We illustrate that tree impact data cannot only be used (i) to reconstruct the real frequency of rockfalls for individual cells, but that they also serve (ii) the calibration of the rockfall model Rockyfor3D, as well as (iii) the transformation of simulated trajectories into real frequencies. Calibrated simulation results are in good agreement with real rockfall frequencies and exhibit significant differences in rockfall activity between the cells (zones) along the road section. Real frequencies, expressed as rock passages per meter road section, also enable quantification and direct comparison of the hazard potential between the zones. The contribution provides an approach for hazard zoning procedures that complements traditional methods with a quantification of rockfall frequencies in terms of return intervals through a systematic inclusion of impact records in trees.

A regional climate palaeosimulation for Europe in the period 1500–1990 – Part 2: Shortcomings and strengths of models and reconstructions

This study compares gridded European seasonal series of surface air temperature (SAT) and precipitation (PRE) reconstructions with a regional climate simulation over the period 1500–1990. The area is analysed separately for nine subareas that represent the majority of the climate diversity in the European sector. In their spatial structure, an overall good agreement is found between the reconstructed and simulated climate features across Europe, supporting consistency in both products. Systematic biases between both data sets can be explained by a priori known deficiencies in the simulation. Simulations and reconstructions, however, largely differ in the temporal evolution of past climate for European subregions. In particular, the simulated anomalies during the Maunder and Dalton minima show stronger response to changes in the external forcings than recorded in the reconstructions. Although this disagreement is to some extent expected given the prominent role of internal variability in the evolution of regional temperature and precipitation, a certain degree of agreement is a priori expected in variables directly affected by external forcings. In this sense, the inability of the model to reproduce a warm period similar to that recorded for the winters during the first decades of the 18th century in the reconstructions is indicative of fundamental limitations in the simulation that preclude reproducing exceptionally anomalous conditions. Despite these limitations, the simulated climate is a physically consistent data set, which can be used as a benchmark to analyse the consistency and limitations of gridded reconstructions of different variables. A comparison of the leading modes of SAT and PRE variability indicates that reconstructions are too simplistic, especially for precipitation, which is associated with the linear statistical techniques used to generate the reconstructions. The analysis of the co-variability between sea level pressure (SLP) and SAT and PRE in the simulation yields a result which resembles the canonical co-variability recorded in the observations for the 20th century. However, the same analysis for reconstructions exhibits anomalously low correlations, which points towards a lack of dynamical consistency between independent reconstructions.

Chow–Liu trees are sufficient predictive models for reproducing key features of functional networks of periictal EEG time-series

Seizure freedom in patients suffering from pharmacoresistant epilepsies is still not achieved in 20–30% of all cases. Hence, current therapies need to be improved, based on a more complete understanding of ictogenesis. In this respect, the analysis of functional networks derived from intracranial electroencephalographic (iEEG) data has recently become a standard tool. Functional networks however are purely descriptive models and thus are conceptually unable to predict fundamental features of iEEG time-series, e.g., in the context of therapeutical brain stimulation. In this paper we present some first steps towards overcoming the limitations of functional network analysis, by showing that its results are implied by a simple predictive model of time-sliced iEEG time-series. More specifically, we learn distinct graphical models (so called Chow–Liu (CL) trees) as models for the spatial dependencies between iEEG signals. Bayesian inference is then applied to the CL trees, allowing for an analytic derivation/prediction of functional networks, based on thresholding of the absolute value Pearson correlation coefficient (CC) matrix. Using various measures, the thus obtained networks are then compared to those which were derived in the classical way from the empirical CC-matrix. In the high threshold limit we find (a) an excellent agreement between the two networks and (b) key features of periictal networks as they have previously been reported in the literature. Apart from functional networks, both matrices are also compared element-wise, showing that the CL approach leads to a sparse representation, by setting small correlations to values close to zero while preserving the larger ones. Overall, this paper shows the validity of CL-trees as simple, spatially predictive models for periictal iEEG data. Moreover, we suggest straightforward generalizations of the CL-approach for modeling also the temporal features of iEEG signals.

Effect sizes and standardization in neighbourhood models of forest stands: potential biases and misinterpretations

Effects of conspecific neighbours on survival and growth of trees have been found to be related to species abundance. Both positive and negative relationships may explain observed abundance patterns. Surprisingly, it is rarely tested whether such relationships could be biased or even spurious due to transforming neighbourhood variables or influences of spatial aggregation, distance decay of neighbour effects and standardization of effect sizes. To investigate potential biases, communities of 20 identical species were simulated with log-series abundances but without species-specific interactions. No relationship of conspecific neighbour effects on survival or growth with species abundance was expected. Survival and growth of individuals was simulated in random and aggregated spatial patterns using no, linear, or squared distance decay of neighbour effects. Regression coefficients of statistical neighbourhood models were unbiased and unrelated to species abundance. However, variation in the number of conspecific neighbours was positively or negatively related to species abundance depending on transformations of neighbourhood variables, spatial pattern and distance decay. Consequently, effect sizes and standardized regression coefficients, often used in model fitting across large numbers of species, were also positively or negatively related to species abundance depending on transformation of neighbourhood variables, spatial pattern and distance decay. Tests using randomized tree positions and identities provide the best benchmarks by which to critically evaluate relationships of effect sizes or standardized regression coefficients with tree species abundance. This will better guard against potential misinterpretations.

A legacy of human-induced ecosystem changes: spatial processes drive the taxonomic and functional diversities of testate amoebae in Sphagnum peatlands of the Galápagos

Aim Our aims were to compare the composition of testate amoeba (TA) communities from Santa Cruz Island, Galápagos Archipelago, which are likely in existence only as a result of anthropogenic habitat transformation, with similar naturally occurring communities from northern and southern continental peatlands. Additionally, we aimed at assessing the importance of niche-based and dispersal-based processes in determining community composition and taxonomic and functional diversity. Location The humid highlands of the central island of Santa Cruz, Galápagos Archipelago. Methods We survey the alpha, beta and gamma taxonomic and functional diversities of TA, and the changes in functional traits along a gradient of wet to dry habitats. We compare the TA community composition, abundance and frequency recorded in the insular peatlands with that recorded in continental peatlands of Northern and Southern Hemispheres. We use generalized linear models to determine how environmental conditions influence taxonomic and functional diversity as well as the mean values of functional traits within communities. We finally apply variance partitioning to assess the relative importance of niche- and dispersal-based processes in determining community composition. Results TA communities in Santa Cruz Island were different from their Northern Hemisphere and South American counterparts with most genera considered as characteristic for Northern Hemisphere and South American Sphagnum peatlands missing or very rare in the Galápagos. Functional traits were most correlated with elevation and site topography and alpha functional diversity to the type of material sampled and site topography. Community composition was more strongly correlated with spatial variables than with environmental ones. Main conclusions TA communities of the Sphagnum peatlands of Santa Cruz Island and the mechanisms shaping these communities contrast with Northern Hemisphere and South American peatlands. Soil moisture was not a strong predictor of community composition most likely because rainfall and clouds provide sufficient moisture. Dispersal limitation was more important than environmental filtering because of the isolation of the insular peatlands from continental ones and the young ecological history of these ecosystems.

Internal Models, Vestibular Cognition, and Mental Imagery: Conceptual Considerations

Vestibular cognition has recently gained attention. Despite numerous experimental and clinical demonstrations, it is not yet clear what vestibular cognition really is. For future research in vestibular cognition, adopting a computational approach will make it easier to explore the underlying mech- anisms. Indeed, most modeling approaches in vestibular science include a top-down or a priori component. We review recent Bayesian optimal observer models, and discuss in detail the conceptual value of prior assumptions, likelihood and posterior estimates for research in vestibular cognition. We then consider forward models in vestibular processing, which are required in order to distinguish between sensory input that is induced by active self-motion, and sensory input that is due to passive self-motion. We suggest that forward models are used not only in the service of estimating sensory states but they can also be drawn upon in an offline mode (e.g., spatial perspective transformations), in which interaction with sensory input is not desired. A computational approach to vestibular cogni- tion will help to discover connections across studies, and it will provide a more coherent framework for investigating vestibular cognition.