Institut für Geoökologie
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One of the major challenges related with the current practice in seismic hazard studies is the adjustment of empirical ground motion prediction equations (GMPEs) to different seismological environments. We believe that the key to accommodating differences in regional seismological attributes of a ground motion model lies in the Fourier spectrum. In the present study, we attempt to explore a new approach for the development of response spectral GMPEs, which is fully consistent with linear system theory when it comes to adjustment issues. This approach consists of developing empirical prediction equations for Fourier spectra and for a particular duration estimate of ground motion which is tuned to optimize the fit between response spectra obtained through the random vibration theory framework and the classical way. The presented analysis for the development of GMPEs is performed on the recently compiled reference database for seismic ground motion in Europe (RESORCE-2012). Although, the main motivation for the presented approach is the adjustability and the use of the corresponding model to generate data driven host-to-target conversions, even as a standalone response spectral model it compares reasonably well with the GMPEs of Ambraseys et al. (Bull Earthq Eng 3:1-53, 2005), Akkar and Bommer (Seismol Res Lett 81(2):195-206, 2010) and Akkar and Cagnan (Bull Seismol Soc Am 100(6):2978-2995, 2010).
One challenging question in ecology is to explain species coexistence in highly diverse temperate grassland plant communities. Within this context, a clear understanding of the consequences of belowground herbivory for the composition and the diversity of plant communities continue to elude ecologists. The existing body of empirical evidence reveals partly contradictory responses ranging from negative to neutral or positive effects of belowground herbivory on grassland diversity.
To reveal possible mechanistic grounds for these discrepancies, we extended an existing simulation model of grassland communities based on plant functional types to include root herbivory. This enabled us to test the effects of different feeding modes that represent different herbivore guilds. For each belowground feeding mode, we systematically varied the intensity and frequency of herbivory events for three different levels of soil fertility both in the presence and absence of additional aboveground grazing.
Our modelling approach successfully reproduced various empirically reported diversity responses, merely on the basis of the different feeding modes. Different levels of plant resource availability affected the strength, but not the direction of the belowground herbivory effects. The only exception was the scenario with low resource levels, which promoted neutral (neither positive nor negative) diversity responses for some of the feeding modes. Interestingly, aboveground biomass production was largely unaffected by diversity changes induced by belowground herbivory except in the case of selective feeding modes that were related to specific functional traits.
Our findings provide possible explanations for the broad spectrum of belowground herbivory effects on plant community diversity. Furthermore, the presented theoretical modelling approach provides a suitable conceptual framework to better understand the complex linkage between plant community and belowground herbivory dynamics.
We conducted a PUB (predictions in ungauged basins) experiment looking at hydrology and crop dynamics in the semi-arid rural Mod catchment in India. The experiment was motivated by the aims (a) to develop a coupled eco-hydrological model capable of analysing land-use strategies concerning crop water need, erosion protection, crop yield and resistivity against droughts and floods, and (b) to assess the feasibility of a strategy for collecting the necessary data in a data-scarce region. Our experiment combines parsimonious data assessment and eco-hydrological model coupling at the lower mesoscale. Linking bottom-up sampling of functionally representative soil classes and top-down regionalization based on spectral properties of the same resulted in a comprehensive distributed data basis for the model. A clear focus on the dominating processes and the catena as the organizing landscape element in the given environmental setting enabled this. We employed the WASA (Water Availability in Semi-Arid environments) model for uncalibrated process-based water balance modelling and integrated a crop simulation subroutine based on the SWAP (Soil Water Atmosphere Plant) model to account for crop dynamics, feedbacks and yield estimation. While we found the data assessment strategy and the hydrological model application largely feasible, in terms of its accounting for scale, processes and model concepts, the simulation of feedbacks with crops was problematic. Contributing to the PUB issue, more general conclusions are drawn concerning spatially-distributed structural information and uncalibrated modelling.
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Editor Z.W. Kundzewicz; Associate editor F. Hattermann