Guido Schwichtenberg

Helmholtz-Zentrum für Umweltforschung, Leipzig, Saxony, Germany

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Publications (4)6.33 Total impact

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    ABSTRACT: In order to predict which ecosystem functions are most at risk from biodiversity loss, meta-analyses have generalised results from biodiversity experiments over different sites and ecosystem types. In contrast, comparing the strength of biodiversity effects across a large number of ecosystem processes measured in a single experiment permits more direct comparisons. Here, we present an analysis of 418 separate measures of 38 ecosystem processes. Overall, 45 % of processes were significantly affected by plant species richness, suggesting that, while diversity affects a large number of processes not all respond to biodiversity. We therefore compared the strength of plant diversity effects between different categories of ecosystem processes, grouping processes according to the year of measurement, their biogeochemical cycle, trophic level and compartment (above- or belowground) and according to whether they were measures of biodiversity or other ecosystem processes, biotic or abiotic and static or dynamic. Overall, and for several individual processes, we found that biodiversity effects became stronger over time. Measures of the carbon cycle were also affected more strongly by plant species richness than were the measures associated with the nitrogen cycle. Further, we found greater plant species richness effects on measures of biodiversity than on other processes. The differential effects of plant diversity on the various types of ecosystem processes indicate that future research and political effort should shift from a general debate about whether biodiversity loss impairs ecosystem functions to focussing on the specific functions of interest and ways to preserve them individually or in combination.
    Oecologia 02/2013; 173(1). DOI:10.1007/s00442-012-2589-0 · 3.09 Impact Factor
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    ABSTRACT: The diversity–stability hypothesis states that current losses of biodiversity can impair the ability of an ecosystem to dampen the effect of environmental perturbations on its functioning. Using data from a long-term and comprehensive biodiversity experiment, we quantified the temporal stability of 42 variables characterizing twelve ecological functions in managed grassland plots varying in plant species richness. We demonstrate that diversity increases stability i) across trophic levels (producer, consumer), ii) at both the system (community, ecosystem) and the component levels (population, functional group, phylogenetic clade), and iii) primarily for aboveground rather than belowground processes. Temporal synchronization across studied variables was mostly unaffected with increasing species richness. This study provides the strongest empirical support so far that diversity promotes stability across different ecological functions and levels of ecosystem organization in grasslands.
    PLoS ONE 10/2010; 5(10):e13382. DOI:10.1371/journal.pone.0013382 · 3.23 Impact Factor
  • Yao Hu · Guido Schwichtenberg · Luis Samaniego · Sabine Attinger · Anke Hildebrandt ·
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    ABSTRACT: Modeling water uptake by plant roots is essential to improve our understanding of the impact of ecosystems on hydrological cycle and climate. However, no measurement devices enable us to measure water uptake directly. Consequently, root water uptake has to be inferred by numerical methods (e.g. inverse modeling). This kind of numerical inversion is further complicated by the fact that vertical water fluxes between measurement points and water uptake by roots occur simultaneously in the soil matrix during daytime, and are difficult to separate. In order to tackle the challenge to quantify the water uptake, we split our study into two parts: First, we calibrate our soil model to estimate soil parameters during the winter time. Second, we estimate the water uptake as a sink term during daytime in summer, while assuming our soil hydraulic parameters to be known a priori. The solution is then checked during the nighttime. For the first step, we use geostatistical interpolation techniques to derive the soil texture fields and use pedotransfer functions to specify the ranges of the soil hydraulic parameters. We then obtain optimal soil parameter sets by combining a Richards model with a global optimization algorithm. For the second step, we use the day-night differences of water content changes to derive likely root water uptake depths and profiles. Although many state-of-the-art approaches use root spatial distribution functions to allocate plants transpiration over the soil profile, we decide to follow a different approach. In our model any layer in the soil column may contribute a certain percent to the total water uptake. We will compare this approach with another inverse modeling approach, which infers water uptake by using root distribution parameters. We expect that this new approach will offer us an opportunity to gain better understanding of vertical soil water flow and root water uptake for the several plots of differing plant diversity in the Jena Biodiversity Experiment, Germany.
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    ABSTRACT: The spatio-temporal distribution of soil moisture in the unsaturated zone influences the vegetation growth, governs the runoff generation processes as well as the energy balance at the interface between biosphere and the atmosphere, by influencing evapotranspiration. A better understanding of the spatio-temporal variability and dependence of soil moisture on living versus abiotic environment would lead to an improved representation of the soil-vegetation-atmosphere processes in hydrological and climate models. The Jena Experiment site (Germany) was established October 2001 in order to analyse the interaction between plant diversity and ecosystem processes. The main experiment covers 92 plots of 20 x 20 m arranged into a grid, on which a mixture of up to 60 grassland species and of one to four plant functional groups have been seeded. Each of these plots is equipped with at least one measurement tube for soil moisture. Measurements have been conducted weekly for four growing seasons (SSF). Here, we use geostatistical methods, like variograms and multivariate regressions, to investigate in how far abiotic environment and ecosystem explain the spatial and temporal variation of soil moisture at the Jena Experiment site. We test the influence of the soil environment, biodiversity, leaf area index and groundwater table. The poster will present the results of this analysis.